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Go to Editorial ManagerMost researches have predicted soil erosion of cohesive riverbanks using linear (excess shear stress model) and non-linear (Wilson model) models based on two soil parameters (detachment coefficient, kd, and critical shear stress, ?c) of the linear model and two soil mechanistic parameters (mechanistic detachment parameter, b0, and threshold parameter, b1) of the non-linear model. The goal of this research was to quantify the soil erodibility parameters of Tigris Riverbanks on Nu’maniyah-Kut Barrage reach using linear and non-linear models through the model parameters at three different water contents: dry side, optimum side, and wet side of water contents. Soil samples were collected from three locations south of Baghdad city on Nu’maniyah-Kut Barrage reach of Tigris Riverbanks. Six soil samples acquired from these sites were laboratory tests achieved using a miniature version of Jet Erosion Test device (“mini” JET) to determine the erodibility parameters of both linear and non-linear models. Blaisdell solution (BL) and scour depth solution (SD) were applied to determine (kd and ?c) of linear model from JETs data. Physical soil characteristics; including bulk density, particle size distribution (sand%, silt%, and clay%), average particle size (D50), and angle of repose were reported for six samples acquired from the three sites. The results showed lower value of kd of toe in compared with bank side for some specific sites as observed for both BL and SD solutions of excess shear stress model especially at wet side of water content. No general pattern of ?c related to different water content were observed. The parameters (b0 and b1) of non-linear model have the same behavior of linear model parameters (kd and ?c), but with different magnitude related to different water contents, respectively.
This paper presents a simple strut and tie model to calculate the shear strength of reinforced concrete deep beams. The proposed model assumes that the shear strength is the algebraic sum of three strength components: concrete diagonal strut, vertical stirrups, and horizontal web reinforcements. The contribution of each strength components was calibrated with the test results of 305 deep beams compiled from previous studies with wide range of geometrical and material properties. The predictions of the proposed model were compared with those of the current codes of practice (ACI-318-14 and ASHTOO 2014) and those of existing model in the literature. Comparisons revealed that the proposed model provided better predictions than other models. The mean of predicted strength to test of the proposed model, the ACI-318-14 model, the ASHTOO 2014 model were 0.98, 0.79, and 0.75, respectively. The corresponding standard deviations were 0.17, 0.28, and 0.49, respectively.
Recently, three-dimensional models 3DM in the prosthetics field gained popularity, especially in the context of residual limb shape creation resulting from collecting medical images in Digital Imaging and Communications in Medicine DICOM format from a magnetic resonance imaging MRI after image processing accurately. In this study, a three-dimensional model of the residual limb for a patient with transtibial amputation was realized with the integration of artificial intelligence and a computer vision approach demonstrating the benefits of AI segmentation tools and artificial algorithms to generate higher accuracy three-dimensional model before prosthetic socket design or in case of comparison the 3D model generated from MRI with another 3D model generated from another technique, where a residual limb of a 23 years old male patient with amputation in the left leg wearing a prosthetic socket liner, and having 62 kg weight, 168 cm height, with high activity level. The patient was scanned using GE Medical Systems, 1,5 Tesla Signa Excite. MRI images in DICOM format were read to retrieve essential metadata such as pixel spacing and slice thickness. These images were processed to obtain a model that reflects the real shape of the residual limb using a specific algorithm, and the 3D model was extracted using AI segmentation tools. The obtained 3D model result with high resolution proves the potential of the artificial intelligence approach with deep learning to reconstruct 3D models concluding that AI has an instrumental role in medical image analysis, particularly in the areas of organ and tissue classification and segmentation., thus generating automatic and repetitive a 3D model.
CFDSST Concrete Filled Double-skinned steel tubular columns are composite columns consisting of two concentric circular steel tubes with concrete filler in between. Finite elements method is considered through the use of the computer program ABAQUS to model CFDSST columns numerically under cyclic axial compression. Damage plasticity model was considered to model the concrete while elastic-plastic model used to model the steel tubes. six CFDSST specimens and three ordinary Concrete Filled Steel Tubular (CFST) specimens were analyzed under static axial compression, while three CFDSST specimens were considered for analysis under cyclic axial compression. The numerical results were presented in terms of axial load axial strain displacement curves. It was found that the ultimate axial load carrying capacity calculated numerically in good agreement with that of the experimentally tested specimens. Also it was concluded that Damage plasticity model used for simulating the behavior of concrete and metal plasticity model used for simulating the behavior of steel produced accurate results as compared to the experimental results.
Public school building projects in Karbala Province experiences payment problems due to improper cash-flow planning by both parties; contractors and clients. These payment problems lead to work stoppages and conflicts. This research aims at developing a suitable model to forecast the expected contractors’ cash-in-flow in public school building projects in Karbala based on historical data. Complete sets of interim payments of (33) out of (38) school building projects finished in the years (2007-2012) in Karbala were interpolated using seven different regression methods namely; Polynomial, Gompertz, Morgan-Morgan-Finney, Logistic, Exponential, Gaussian and Linear in order to identify the best-suited model. It is found that the third degree polynomial model is more suitable for cash-in-flow forecasting of the case under study with coefficient of correlation of (97.89%) and standard error of (0.0441). Data of the remaining (5) projects were used to test the validity of the best-fitted model using Mean Absolute Percentage Error, Root Mean Square Error and Average Accuracy Percentage. The model is expected to be of high advantage in predicting contractors’ cash-in-flow in public school building projects in Karbala, and consequently clients’ cash-out-flow as well._x000D_
There is very close relation between the pile capacity and surrounding soil conditions . In cohesionless soil the pile effected on surround soil by compact loose ,cohesionless deposits through a combination of pile volume displacement and driving vibrations .the pile foundation usually designed to exceed the weak soil to the firm deposit .in this study we shall try to improve the weak soil surround the pile and observe the effect of improvement on pile capacity for driven pile._x000D_ The improvement suggested in this study is compacting for surrounding soil . for this purpose we prepare testing program by selection two types of sand soil one as the origin soil and the other as improving soil (soil will be compacted and replace surround pile model) . pile model prepared for this purpose is consist of reinforcement steel bar covered with cement mortar , 50 kN automatic electromechanical compression machine was used for testing load- settlement test on pile model. The Testing procedure includes changing the diameter of soil compacted around pile model and execute the load settlement test and compare the results.
The interest in the Eye-tracking technology field dramatically grew up in the last two decades for different purposes and applications like keeping the focus of where the person is looking, how his pupils and irises are reacting for a variety of actions, etc. The resulted data can deliver an extraordinary amount of information about the user when it's interlocked through advanced data analysis systems, it may show information concerned with the user’s age, gender, biometric identity, interests, etc. This paper is concerned about eye motion tracking as an unadulterated tool for different applications in any field required. The improvements in this area of artificial intelligence (AI), machine learning (ML), and deep learning (DL) with eye-tracking techniques allow large opportunities to develop algorithms and applications. In this paper number of models were proposed based on Convolutional neural network (CNN) have been designed, and then the most powerful and accurate model was chosen. The dataset used for the training process (for 16 screen points) consists of 2800 training images and 800 test images (with an average of 175 training images and 50 test images for each spot on the screen of the 16 spots), and it can be collected by the user of any application based on this model. The highest accuracy achieved by the best model was (91.25%) and the minimum loss was (0.23%). The best model consists of (11) layers (4 convolutions, 4 Max pooling, and 3 Dense). Python 3.7 was used to implement the algorithms, KERAS framework for the deep learning algorithms, Visual studio code as an Integrated Development Environment (IDE), and Anaconda navigator for downloading the different libraries. The model was trained with data that can be gathered using cameras of laptops or PCs and without the necessity of special and expensive equipment, also It can be trained for any single eye, depending on application requirements.
Optical coherence tomography (OCT) allows for direct and immediate imaging of the morphology of retinal tissue. It has become a crucial imaging modality for diagnosing eye problems in ophthalmology. One of the most significant morphological characteristics of the retina is the structure of the retinal layers, which provides important evidence for diagnostic purposes and is related to a variety of retinal diseases. In this paper, a convolutional neural network (CNN) model is proposed that can identify the difference between a normal retina and three common macular diseases: Diabetic macular edema (DME), Drusen, and Choroidal neovascularization (CNV). This proposed model was trained and tested on an open source dataset of OCT images also with professional disease classifications such as DME, CNV, Drusen, and Normal. The suggested model has achieved 98.3% overall classification accuracy, with only 7 wrong classifications out of 368 test samples. The suggested model significantly outperforms other models that made use of the identical dataset. The final results show that the suggested model is particularly adapted to the detection of retinal disorders in ophthalmology centers.
This paper proposes robust control for three models of the linear inverted pendulum (one mass linear inverted pendulum model, two masses linear inverted pendulum model and three masses linear inverted pendulum model) which represents the upper, middle and lower body of a bipedal walking robot. The bipedal walking robot is built of light-weight and hard Aluminum sheets with 2 mm thickness. The minimum phase system and non-minimum phase system are studied and investigated for inverted pendulum models. The bipedal walking robot is programmed by Arduino microcontroller UNO. A MATLAB Simulink system is built to embrace the theoretical work. The results showed that one linear inverted pendulum is the worst performance, worst noise rejection and the worst set point tracking to the zero moment point. But two masses linear inverted pendulum models and three masses linear inverted pendulum model have a better performance, a better high-frequency noise rejection characteristic and better set-point tracking to the zero moment point.
Alzheimer's disease (AD) is a progressive neurodegenerative disorder that severely impacts cognitive functions such as memory, attention, and reasoning, ultimately affecting daily life. Early and accurate detection is crucial for timely intervention and management. Traditional diagnostic methods, including neuroimaging and cognitive assessments, can be expensive and time-consuming, necessitating more accessible and efficient alternatives. This study aims to develop an automated and efficient deep learning-based detection system that uses Electroencephalogram (EEG) signals to accurately classify AD and healthy individuals. A Convolutional Neural Network (CNN) model was designed to extract meaningful features from preprocessed EEG data. The architecture consists of convolutional layers with max pooling, dropout regularization, and fully connected layers to improve classification accuracy. The model was trained and evaluated on a comprehensive EEG dataset, using key performance metrics such as accuracy, recall, precision, and F1-score. The proposed CNN model achieved a high classification accuracy of 94.56%, a low loss of 0.2162, and an AUC value of 0.93828, demonstrating superior classification capability. The results indicate that the model effectively distinguishes between AD and healthy individuals, outperforming several state-of-the-art approaches. The findings highlight the potential of deep learning-based EEG analysis for AD detection, providing an accessible and cost-effective tool for early diagnosis. The high accuracy of the proposed CNN model suggests that it can assist medical professionals in making well-informed decisions, ultimately improving patient outcomes.
In this work, constant and increasing temperature fatigue interaction effect on fatigue behavior of 2017-T4 aluminum alloy was investigated. Fatigue tests at constant load constant temperature and constant load increasing temperature were performed for five applied stresses which are (350,275,200,175 and 150 MPa) that based on the tensile test behavior .The constant temperatures were room temperature (RT) (25 ?C) and 100 ?C. While the increasing temperatures were RT, 50 ?C, 100 ?C and 150 ?C for one test program. The constant fatigue property of the increasing temperatures was observed the worst case compared to the others constant fatigue properties. A new variable temperature fatigue damage model was proposed. It is based on the S-N curve and taking into account the effects of constant loads and variable temperature. A comparison between prediction of the proposed model and crack growth rate due to Miner rule was made. The results proved that this model is satisfactory and gave safe results than Miner rule compared to experimental data.
In this paper, a quick stop device technique and the streamline model were employed to study the chip formation in metal cutting. The behavior of chip deformation at the primary shear zone was described by this model. Orthogonal test of turning process over a workpiece of the 6061-T6 aluminum alloy at different cutting speeds was carried out. The results of the equivalent strain rate and cumulative plastic strain were used to describe the complexity of chip formation. Finite element analysis by ABAQUS/explicit package was also employed to verify the streamline model. Some behavior of formation and strain rate distribution differs from the experimental results, but the overall trend and maximum results are approximately close. In addition, the quick stop device technique is described in detail. Which could be used in other kinds of studies, such as the metallurgical observation.
The present work is a manual that describes the practical aspects of optimizing dental precision by virtual dentoskeletal modeling, use the precises model in virtual planning, and splint design of orthognathic surgery. A single case study is used to demonstrate the stages involved in this approach, which include acquiring CBCT scan data and digital dental models, incorporating this data into developing a virtual dentoskeletal model using superimposition process to replace the unclear teeth. Utilizes virtual assessment and three-dimensional cephalometry to diagnose the maxillofacial deformity of the patient correctly. The results of the diagnosis played a crucial role in formulating a comprehensive plan for dental alignment, which involved osteotomy and correction of bone positions. The final step is to create a personalized splint. The importance of virtual tools is highlighted in our work to optimizing dental precision, diagnose and treat maxillofacial deformities. Present a virtual planning methodology for orthognathic surgeons as well as researchers.
The research proposed a developed methodology for evaluation the system performance in uncertainty associated with traditional modelling methodology is focused on either load L or resistance R variability, but not both. A two-dimensional (2D) fuzzy set (traditional model), represent with the one dimension for universe of discourse (in x-direction) and the second dimension of his membership degree (in y-direction), is not full sufficient to handle both, load and resistance variation of system performance. The theoretical principle basis of this research is based on development of the three dimensional (3D) of fuzzy set that includes system performance variability in load and resistance from two dimensional. The proposed methodology (traditional model) extends the acceptance level of partial performance of system concept to a 3D-dimantion representation. This representation allows to capturing the changing of preferences of decision makers in load and resistance. The major objective of the research is to proposed the original methodology for evaluate system performance and management that is capable of; (a) addressing uncertainty caused by load and resistance variability and ambiguity; (b) integrating objective and subjective evaluation; and (c) assisting system performance management decision making based on a more detailed certainty evaluation of load and resistance variability. The study proposed two models for fuzzy reliability performance indexes: first traditional model included (I) 2D fuzzy reliability-vulnerability Rv index, (II) 2D fuzzy robustness Ro index; the second developed model (i) 3D fuzzy reliability-vulnerability Rv index, (ii) 3D fuzzy robustness Ro index; and comparing between them. These indexes have the capability of evaluating the operational performance of complex systems. Proposed methodology is illustrated by using the Al-Wathba Water Supply System (WWSS) as a case study.
Deep learning modeling could provide to detected Corona Virus 2019 (COVID-19) which is a critical task these days to make a treatment decision according to the diagnostic results. On the other hand, advances in the areas of artificial intelligence, machine learning, deep learning, and medical imaging techniques allow demonstrating impressive performance, especially in problems of detection, classification, and segmentation. These innovations enabled physicians to see the human body with high accuracy, which led to an increase in the accuracy of diagnosis and non-surgical examination of patients. There are many imaging models used to detect COVID-19, but we use computerized tomography (CT) because is commonly used. Moreover, we use for detection a deep learning model based on convolutional neural network (CNN) for COVID-19 detection. The dataset has been used is 544 slice of CT scan which is not sufficient for high accuracy, but we can say that it is acceptable because of the few datasets available in these days. The proposed model achieves validation and test accuracy 84.4% and 90.09%, respectively. The proposed model has been compared with other models to prove superiority of our model over the other models.
In this study, the analytic model (Azmi Model) had been considered for computation the load capacities of the composite open web steel joists and compared them with those obtained from experimental tests. The capacities of seven joists had been studied, each including one of the following variables (distribution of headed studs, connection degree of the connectors, inclination of the web, shape of the web, density of slab concrete, length of connectors).Theoretically, according to the Analytic model, the referenced joist of (45° web inclination , uniformly distributed ,over connected ,short headed studs) exhibited maximum load capacity of (18.45) ton, while the joist of (45° web inclination, uniformly distributed, under connected, short headed studs) exhibited minimum load capacity of (16.23) ton at yield point of bottom chord. Experimentally, the referenced joist exhibited maximum load capacity of (15.51) ton, while the joist of (34° web inclination, uniformly distributed, over connected, short headed studs) exhibited (12.49) ton load capacity. The load capacities values of the tested joists ranged between (67%-85%) of the predicted values according to the analytic model.
This paper presents a numerical investigation to study the effect of variations in displacement history sequence and magnitude on cyclic response of RC tapered (haunched) beams (RCHBs).Five simply supported RCHBs (four haunched and one prismatic) were selected from experimental work carried out by Aranda et al. The selected variables included were five loading history types. The first part of this study focused to verify the finite element analysis with selected experimental work and the second part of this study focused too studying the effect of varying in loading history to the response of RCHBs. The finite element code Abaqus was used in the modeling. The adopted cyclic simulation performance of the selected beams using the plastic- damage model for concrete developed by Lubliner and Lee & Fenves. The constitutive model of plain concrete describing the uniaxial compression response under cyclic loading proposed by Thorenfeldt, and the uniaxial tension response follows the softening law proposed by Hordijk was used in the modeling. Menegotto-Pinto model was used to simulate the steel response. Model verification has shown A good agreement to the selected experimental work. The variations in loading history will decrease the ultimate load and corresponding deflection with increase in the number of cycles at ultimate load.
Diabetes is one of the most critical diseases in the world which requires measuring the concentration of glucose also the injection of insulin to control the glucose rate in the body. The proposed controller is applied to the Bergman’s three-state minimal patient model, where the model is considered certain but with unknown meal. In the present work, a nonlinear controller is designed to control the concentration of glucose based on the Backstepping approached with a sliding mode for observing the disturbance meal. So will have estimated the meal and have canceled the effect that the glucose concentration has regulating to the basal level._x000D_ The effectiveness of the proposed controller, which represent the insulin dose, is proved via simulating the Bergman’s model with designed controller via MATLAB Simulink software. The result clarify the ability and the robustness of the proposed controller.
This paper proposes the design and simulation of Interval Type-2 Fuzzy Logic Control using MATLAB/Simulink to control the position of the bucket of the backhoe excavator robot during digging operations. In order to reach accurate position responses with minimum overshoot and minimum steady state error, Ant Colony Optimization (ACO) algorithm is used to tune the gains of the position and force parts for the force-position controllers to obtain the best position responses. The joints are actuated by the electro-hydraulic actuators. The force-position control incorporating two-Mamdani type-Proportional-Derivative-Interval Type-2 Fuzzy Logic Controllers for position control and 3-Proportional-Derivative Controllers for force control. The nonlinearity and uncertainty in the model that inherit in the electro hydraulic actuator system are also studied. The nonlinearity includes oil leakage and frictions in the joints. The friction model is represented as a Modified LuGre friction model in actuators. The excavator robot joints are subjected to Coulomb, viscous and stribeck friction. The uncertainty is represented by the variation of bulk modulus. It can be shown from the results that the ACO obtain the best gains of the controllers which enhances the position responses within the range of (19, 23 %) compared with the controllers tuned manually.
Artificial neural networks (ANN) as new techniques employed for the development of predictive models to estimate the needed parameters in geotechnical engineering to be used for comparison with laboratory and field tests and consequently reduce the cost, time, and effort. Flexible computing techniques are using an alternative statistical tool to analyze and evaluate experimental data from 102 consolidation tests on a variety of undisturbed soils from Ramadi city. The regression equations are developed to estimate the compression index and the compression ratio from index data. Multi-Layer Perceptron (MLP) network model is used to calculate compression index and a compression ratio of soils and comparing with the multiple linear regression statistical model MLR. It is found that the MLP showed a higher performance than MLR in predicting Cc and Cr and model accuracy between 0.81 to 16 percent. This will provide a good method for minimizing the potential inconsistency of correlations.
In this study, low cost biosorbent ? inactive biomass (IB) granules (dp=0.433mm) taken from drying beds of Al-Rustomia Wastewater Treatment Plant, Baghdad-Iraq were used for investigating the optimum conditions of Pb(II), Cu(II), and Ni(II) biosorption from aqueous solutions. Various physico-chemical parameters such as initial metal ion concentration (50 to 200 mg/l), equilibrium time (0-180 min), pH (2-9), agitation speed (50-200 rpm), particles size (0.433 mm), and adsorbent dosage (0.05-1 g/100 ml) were studied. Six mathematical models describing the biosorption equilibrium and isotherm constants were tested to find the maximum uptake capacities: Langmuir, Freundlich, Redlich–Peterson, Sips, Khan, and Toth models. The best fit to the Pb(II) and Ni(II) biosorption results was obtained by Langmuir model with maximum uptake capacities of 52.76 and 36.97 mg/g for these two ions respectively. While for Cu(II) the corresponding value was 38.07 mg/g obtained with Khan model. The kinetic study demonstrated that the optimum agitation speed was 400 rpm, at which the best removal efficiency and/or minimum surface mass transfer resistance (MSMTR) was achieved. A pseudo-second-order rate kinetic model gave the best fit to the experimental data (R2=0.99), resulting in mass transfer coefficient values of 42.84× , 1.57× , and 2.85× m/s for Pb(II), Cu(II), and Ni(II) respectively. The thermodynamic study showed that the biosorption process was spontaneous and exothermic in nature.
Thyroid nodules (TNs) are discrete abnormalities located within the thyroid gland that are radiologically different from the surrounding thyroid tissue. Ultrasound is an accurate and efficient way to diagnose thyroid nodules. Recently, several methods of AI were proposed to improve the detection of thyroid nodules ultrasound images with good performances. However, in some cases related to the type or size of the dataset using machine or transfer deep learning methods alone is unable to achieve high accuracy and high specificity. Consequently, the addition of feature selection)FS) to the deep learning method enhances the results by reducing the high features and the time needed for training the dataset. This study proposes two deep-learning models for classifying thyroid nodule US images into two categories: benign and malignant. ResNet50 was the first model used to extract deep features from US images. The second model integrates ResNet50 and principal component analysis (PCA) for feature selection, intending to reduce dataset dimensionality while maintaining the greatest data variance possible before classification. The proposed model was created using a freely available dataset. The dataset consists of 800 images, 400 benign and 400 malignant. The suggested system was accessed based on accuracy, precision, recall, and F1 score. The classification accuracy for ResNet50 was 85%, while ReNet50-PCA was 89.16%. The combination of deep learning and FS techniques in this research produces an interesting diagnostic framework that can potentially increase efficiency and accuracy in thyroid cancer detection, especially in local healthcare centers.
Box-Wilson experimental design method was employed to optimize bioethanol production from low grade, unclassified, waste Iraqi dates. The optimization process was based on four independent relevant parameters-initial sugar concentration (50-100 g/l), pH (4.5-6.5), fermentation time (48-96 hrs), and temperature (25-35?). A maximum bioethanol yield of 33.9 g/l was practically achieved following thirty different experimental runs, as specified by 24-Central Composite Design (CCD). The optimum values for the aforementioned four parameters, corresponding to the maximum yield, were: 75g/l, pH 5.5, 72 hrs, 30?, respectively. The obtained experimental data were utilized to develop a semi-empirical model, based on a second-degree polynomial, to predict bioethanol yield. The model was tested using ANOVA software (Design expert® 9) and found acceptable (R2=0.9025). Yield response surface and contour plots were created using the developed model, which revealed the presence of high-yield plateaus whose specifications will be useful in controlling pilot-or industrial scale future units to ensure economical feasibility.
The oil industry has a direct impact on the economic feasibility of other sectors and is considered to be the most important energy source used to turn the wheels of other industries. Therefore, it was necessary to pay attention and continuously develop this industry, to find the best modern techniques for designing, pre-commissioning and controlling process, to improve efficiency, preserve energy and achieve the highest production of costly components with the highest purity of the product. This study aims to provide a literary analysis of the stages of development and progress of the dynamics and control of the petroleum industry, in particular the distillation column, because it is multivariable with high interaction between control cycles, nonlinear behaviour and large gains. Control processes have undergone many developments and modernizations to achieve the best results. Various control methods have been used, ranging from simple proportional-integral-derivative controller (PID) to advanced control strategies such as model predictive control (MPC), multivariate model predictive control (MMPC), fuzzy logic control (FLC), quadratic dynamic matrix control (QDMC), artificial neural network control (ANN) and other advanced control techniques. The authors concluded from the review that the advanced control strategies superior than the conventional methods.
The modern development in prosthetics field demand the evaluation of the dynamical behavior and automatic control .The key process in the design and implement of these devices is the determination of the model parameters inherited with the transfer function .In such complicated structures it is so difficult to evaluate transfer function analytically ,however experimental approaches can serve as a simple and effective tool for estimating transfer function and model parameters .In this regard computer software such as Matlab is used .System Identification SID refers to the method for estimating the system transfer function from experimental tests by using computer .In the present paper; SID method is employed for analyzing below-knee prosthesis leg .In order to simulate with the practical requirement for design and evaluation ,two phases of human gait are considered ,namely; swing phase and single support of stance phase .The validity of this method is firstly checked by applying it on clamped-clamped beam model where the required parameters are evaluated and compared theoretically (via modal analysis) and experimentally (via System identification) .It is found that ; the error in estimating the transfer function parameter of beam is not exceeded 6% . Then the transfer function of the prosthesis are estimated for two phases of gait cycle .It is found that; the estimated transfer function of the prosthesis leg is highly affected by the phase type of gait cycle , where ;the natural frequency highly increases, the static gain decrease for support phase as compared with the swing phase ,however the damping ratio does not affected .
The aim of this study is to evaluate the sediment transport and to assess the quality of water for a reach of Euphrates River with a length of (124.4 km), begins from downstream of Haditha dam which represents the upstream of study, and ends at Heet station in Heet city which represents the downstream. There are 196 cross-sections which were distributed along the study area by using the model of one-dimensional HEC-RAS version 4.1. Calibration and Verification processes from(01-Sep-2013) to (30-Nov2013) and (01-DEC-2013) to (28-FEB-2014) respectively, show that the optimal Manning Roughness Coefficient (n) is equal to (0.033) which gives the less error ratio between the observed and calculated water surface elevations. By comparing the results of sediment transport “mass accumulated” for this study which equal to (237.38ton/day) was larger than the value of the previous study which equal to (165ton/day, measured in 2010). But the value of sediment load of this study at Heet station was equal to (551.76 ton/day) which was less than the value of previous study (189.041×103 ton/day,measured in 1988), due to increasing in the rates ofdischarge that was arrived the reach of study area.
In this vast world after an earthquake lessons are learned; many strategies have been considered in order to achieve a proper seismic strength capacity.The aim of this paper is studying the seismic behavior of a typical reinforced concrete bridge pier in Iraq and implementing a proper technique of strengthening in order to fix any damage that had happened.Structure of a full scale three-dimensional finite element model was used in order to simulate a reinforced concrete pier via the computer software ABAQUS/CAE 2017 using concrete plasticity damage model (CDP).Under the action of Halabja earthquake, which was recorded at city of Halabja in Iraq on 12 November 2017, the behavior of model was traced, analyzed and the resulted damages were managed.The finite element analysis results indicated that the proposed configuration of carbon fiber reinforced polymers laminates substantially increases the lateral load strength and deformation capacity of the bridge pier
This study evaluates the performance and efficiency of four deep learning models—VGG-16, ResNet-50, Inception-V3, and DenseNet-121—in detecting pneumonia from chest X-rays, addressing the critical need for balanced accuracy and computational efficiency in clinical diagnostics. Methods: A dataset of 5,234 chest X-rays (3,875 pneumonia, 1,341 normal) was augmented via rotation, flipping, and zooming to mitigate class imbalance. Models were trained on an RTX 2060 GPU for 40 epochs, with performance assessed using accuracy, F1 score, sensitivity, specificity, precision, and computational metrics (training time, memory usage). Statistical significance was validated via paired t-tests (p < 0.05). Results: DenseNet-121 achieved the highest accuracy (95.2% ± 0.8), F1 score (95.1% ± 0.7), and throughput (400 images/sec) with minimal memory usage (33MB). ResNet-50 and Inception-V3 showed moderate performance, while VGG-16 exhibited overfitting tendencies. In conclusion, DenseNet-121 showed strong performance compared to other models, both in terms of accuracy and processing speed, which is essential for use in real-time clinical settings. However, the small size of the validation set and limited population diversity are important limitations that should be addressed in future studies. Moreover, more testing on larger datasets is needed to confirm the stability of the model and see how the model will work in different settings. Future work should address ethical considerations in AI-driven diagnostics and validate findings across multi-institutional datasets.
This research study the rheological properties ( plastic viscosity, yield point and apparent viscosity) of non-Newtonian fluids under the addition of different chemical additives with different concentrations, such as (xanthan gum (xc-polymer) , carboxy methyl cellulose ( high and low viscosity ) ,polyacrylamide, polyvinyl alcohol, starch, quebracho, chrome lignosulfonate, and sodium chloride (NaCl). Fann viscometer model 800 with 8-speeds was used to measure the rheological properties of these samples, that have already been prepared. All samples were subjected to Bingham plastic model. It was concluded that the plastic viscosity, yield point and apparent viscosity should be increased with increasing the concentrations of (xanthan gum (xc-polymer) , carboxy methyl cellulose ( high and low viscosity ) ,polyacrylamide, polyvinyl alcohol, starch and sodium chloride (NaCl), while the opposite is true for quebracho, chrome lignosulfonate.
Breast cancer is one of the greatest frequent tumours among females in Iraq. Medical ultrasound imaging has become a common modality for breast tumour imaging because of its ease of use, low cost, and safety. In the present study, Convolutional Neural Network (CNN) feature extraction approaches were used to classify breast ultrasound imaging. The CNN model used is composed of four-layer for breast cancer ultrasound image analysis. Two types of free datasets were used. These data were divided into groups A and B. Group A has three classes, namely benign, malignant and normal, while group B has two classes, namely, benign and malignant. The proposed technique was assessed based on its accuracy, precision, F1 score and recall. The model's classification accuracy for data A was 96%, whereas for data B was 100%.
Fused deposition modeling (FDM) is a commonly used 3D printing technique that involves heating, extruding, and depositing thermoplastic polymer filaments. The quality of FDM components is greatly influenced by the chosen processing settings. In this study, the Taguchi technique and artificial neural network were employed to predict the ultimate tensile strength of FDM components and establish a mathematical model. The mechanical properties of ABS were analyzed by varying parameters such as layer thickness, printing speed, direction angle, number of parameters, and nozzle temperature at five different levels. FDM 3D printers were used to fabricate samples for testing, following the ASTM-D638 standards, using the Taguchi orthogonal array experimental design method to set the process parameters. The results indicated that the printing process factors had a significant impact on tensile strength, with test values ranging from 31 to 38 MPa. The neural network achieved a maximum error of 5.518% when predicting tensile strength values, while the analytical model exhibited an error of 19.376%.
The present work demonstrates the optimization process of Micro- hole of Electrical Discharge Machining (EDM) by Adaptive Neuro Fuzzy Inference System (ANFIS). The workpiece material was copper alloy. The current, gap distance and pulse on time were the control parameters of EDM. The process has been successfully modeled using ANFIS model constructs a fuzzy inference system in MATLAB 7.2 Software Gaussian type for optimization of micro diameter, were adopted during the training and testing process of ANFIS model in order to compare the prediction accuracy of micro diameter by one membership function. Finally, the comparison of ANFIS results with experimental data indicates that adoption of Gaussian membership function in proposed system achieved satisfactory accuracy. Prediction using ANFIS model compared with experimental values of micro holes at correspond ratio 98.37%.
Lung cancer is the most common dangerous disease that, if treated late, can lead to death. It is more likely to be treated if successfully discovered at an early stage before it worsens. Distinguishing the size, shape, and location of lymphatic nodes can identify the spread of the disease around these nodes. Thus, identifying lung cancer at the early stage is remarkably helpful for doctors. Lung cancer can be diagnosed successfully by expert doctors; however, their limited experience may lead to misdiagnosis and cause medical issues in patients. In the line of computer-assisted systems, many methods and strategies can be used to predict the cancer malignancy level that plays a significant role to provide precise abnormality detection. In this paper, the use of modern learning machine-based approaches was explored. More than 70 state-of-the-art articles (from 2019 to 2024) were extensively explored to highlight the different machine learning and deep learning (DL) techniques of different models used for the detection, classification, and prediction of cancerous lung tumors. The efficient model of Tiny DL must be built to assist physicians who are working in rural medical centers for swift and rapid diagnosis of lung cancer. The combination of lightweight Convolutional Neural Networks and limited resources could produce a portable model with low computational cost that has the ability to substitute the skill and experience of doctors needed in urgent cases.
The ability of fungal waste biomass type White Agaricus Bisporus to biosorb Pb(II) ,Cr(III), Cd(II) and Co(II) from wastewater was investigated in batch process. Single and binary mixtures were used at low metal concentration wastewater treatment. The size of the biosorbent ranged 0.3-1 mm. The biosorption capacity of the biosorbent was evaluated under equilibrium conditions at 25 °C. Results indicated that the biosorption capacity of waste of fungi for the binary mixture was always lower than that for a single component system. Eight isotherm models were used to fit the experimental data of single system and Langmuir model was found a suitable to describe the biosorption data. The maximum uptake capacity (qe) of Pb(II), Cr(III), Cd(II) and Co(II) in single system was 158.73, 46.94, 40.16 and15.94 mg/g respectively with correlation coefficients 0.999,0.998,0.988 and 0.991 respectively. For binary system, four biosorption models were used to fit the experimental data. Extended Langmuir model gave the best fitting. The removal percentage of heavy metals onto fungal waste biomass was in order of Pb(II) > Cr(III) > Cd(II) > Co(II) in both single and binary system. The results show that the using waste of fungi as a biosorbent of heavy metals gave a higher uptake capacity of four heavy metals.
It is essential to review and develop a system of water control structures and canals that can be used to manage high-flow discharges and the flood control plan requirement to modify the system's capacity. Al-Ramadi Project System is considered one of the main flood control projects on the Euphrates River within Anbar Governorate, Western Iraq. This study will focus on Al-Majjarah Canal and Regulator, which is part of Al-Ramadi Project and has the function of a link canal between Al-Habbaniyah and Al-Razazza lakes, and describe the capacity of the canal under typical operating conditions and during floods. The study used HEC-RAS 6.1 software to run a numerical model to simulate this canal. According to previous research studies near the research region on the Euphrates River, for the main canal, the roughness coefficient was taken at 0.026, and for the flood plain, it was taken at 0.03. The same parameter value was applied to Al-Majjarah Canal. Due to the study region's similar geology and nature. Moreover, a sensitivity analysis was made of the roughness coefficient and its influence on the water surface elevation for the canal. The model result indicated in the current situation of Al-Majjarah Canal can pass a flow rate of 1300 m3/s when Al-Razazza Lake is at an average water level that has been approved by the Ministry of Water Resources at 32.02 m.a.m.s.l.. If the water level in Al-Razazza Lake is in the semi-filled position of 40 m.a.m.s.l., it causes floods for the canal because the water level rises above the banks of the canal at the last kilometer from the canal, even when passing a few discharges through the canal. Accordingly, it is not possible to safely pass the flow rate for a flood wave with a 500-year return period predicted by the "Study of Strategy for Water and Land Resources in Iraq (2014)", which is 2000 m3/s for this canal, without making modifications to the expansion of Al-Majjarah Regulator by adding additional gates, expanding the entrance and exit of the Regulator, reshaping and expanding some cross-sections, and raising some of the banks for the canal. The above-mentioned modification were applied for the purpose of passing the expected discharge from the canal, while maintaining a freeboard of 1 m between the water surface and the canal banks.
The adsorption characteristics of Nickel (II) onto Iraqi Bentonite clay from aqueous solution have been investigated with respect to changes in pH of solution, adsorbent dosage, contact time and temperature of the solution. The maximum removal efficiency of Nickel (II) ions is 96% at pH=6.5 and exposure to 100 g/L adsorbent. For the adsorption of Nickel (II) ions, the Freundlich isotherm model fitted the equilibrium data better than the Langmuir isotherm model. Experimental data are also evaluated in terms of kinetic characteristics of adsorption and it was found that the adsorption process for Ni+2 ions follows well pseudo-second-order kinetics. Thermodynamic functions, the change of free energy (?G°), enthalpy (?H°) and entropy (?S°) of adsorption are also calculated for Nickel (II) ions. The results show that the adsorption of the Nickel (II) ions on Iraqi Bentonite is feasible and exothermic at (20-50) °C.
Driven piles have often been used in many civil structures to provide structural loading support. However, the unavoidable vibrations induced by pile driving processes may cause varying degrees of damage to adjacent structures. This research presents experimental studies to investigate the transmitted vibrations induced by impact of pile driving on vicinity piles. In the experimental work, a small scale model was tested in a sand box (steel container 1 × 1.5 × 0.8 m) with pile driving hammer device to install the impact pile in sand soil by dropping weights (1, 2, 3, 4 and 5 kg) for different heights of falling (4, 8, 12, 16 and 20 cm). The peak particle velocity was measured at a head of the vicinity piles by vibration meter device. In this study, several piles on different distances away from the vibration source were studied. The experimental results indicate that the peak particle velocity for vibrations emitted with impact pile driving is increased with increasing the energy and the penetration depth of pile driving for all vicinity piles and it can be decreased without change in the driving energy by decreasing the weight of hammer and increasing the height of falling hammer. Vibration intensities are attenuated with increasing surface distance from the pile driving and the peak particle velocity decreased uniformly with surface distance from the pile driving for piles. Also, through laboratory model representation and evaluation of the results obtained in the laboratory, the empirical relations which were determined based on the scaled-distance concept, are appropriate and give results very close and can be relied upon to represent the transmission of vibration resulting from the impact of pile driving to nearby piles.
The goal of the study is to predict the Man in the Middle attack in the packets of Wireshark program by using Support Vector Machines (SVM).In the time of using the internet, it has become a tool targeted by attackers and hackers; it is a serious threat to the devices. A uniqueness of an attack that appears in multiple identities for legitimate agencies. It is very necessary to know the behavior attack and predict the possible actions of an attacker. In this research a detection of Man in the Middle attack by monitoring the Wireshark program and recording any changes can be recognized in packet information. The classification of packets is divided into two categories (normal and abnormal). The proposed model is designed in many stages: loading data, processing data, training data, and testing data. The detection of SVM based on abnormal network packet through movement packets in the Wireshark program that needs to deal with current packets to recognize a new attack that one does not have prior knowledge of its detection, and there is a need for an intelligent way to separate network packets that represent normal. The proposed approach achieved an accuracy of 97.34% in detecting attacks. The results show that the proposed model effectively visualizes attacker behavior from data that represents abnormal network attackers. Research achieves successful accuracy in predicting abnormalities.
Non-dispersive near-infrared technique is widely used nowadays for the detection of gases, especially in harsh environments. In this study, an optical gas cell was designed for oxygenator exhaust capnometry. A computer-based simulation was used for the analysis of air flows for model selection. ANSYS Discovery 2020 R2 was used for model simulation. The gas flow cells were tested using a custom-made gas rig to measure the fraction absorbance of carbon dioxide gas at the detector. Two gases were used, nitrogen gas as a reference gas (0%) and 9% carbon dioxide. Three gas cells with the following optical path lengths were tested: 31mm, 36mm, and 40mm. The results showed that all gas flow cells produced laminar flow and small pressure drop across the inlet and outlet of the cell (11~12 Pa). Further, the minimum velocity is obtained in the 40mm gas flow sensor and it is located at the gas outlet path away from the effective optical gas path. The simulation and experimental results indicate that the gas flow cell of 40mm optical path length is more suitable for the intended application as it offers a maximum effective absorption path compared to the stagnation areas, and as a result, it provides the maximum fraction absorbance.
The phenomenon of climate change resulting from the increase of global warming has become one of the main problems facing the world. Where researchers and specialists have worked for many years to find a solution that reduces this phenomenon and limits its risks. It is likely that clean energy is an alternative to fossil fuel sources, which are the main source of global warming. One of the clean energy sources is ocean wave energy, which is a huge and untapped energy source, despite the possibility of extracting large energy from waves. This paper focuses on the study of deep-sea turbines and their results. A study was conducted on the capture chamber. Where this paper presents an experimental model of a water tank with certain dimensions in the university laboratories to describe the dynamic behavior of the capture chamber. The Froude number scale was used to model the dimensions and depth of the water as well as the wave properties. Through experimental work and its results show, and it was found that the power generated by the motion of the wave strength is related to the height and frequency of the wave.
As internet network developed rapidly in the past ten years, and its operating environment is constantly changing along with the development of computer and communication technology, the congestion problem has become more and more serious. Since TCP is the primary protocol for transport layers on the internet, the data transmitted via the transport protocol utilizes Vegas Transmission Control Protocol (TCP) as the congestion control algorithm, where it uses increasing in delay round trip time (RTT) as a signal of network congestion. However, this congestion control algorithm will attempt to fill network buffer, which causes an increase in (RTT) determined by Vegas, thereby reducing the congestion window, and making the transmission slower, Therefore Vegas has not been widely adopted on the Internet. In this paper, an improved algorithm called TCP Vegas-A is proposed consist of two parts: the first part is sending the congestion window used by the algorithm for congestion avoidance along with the TTL (Time To Live) mechanism that limits the lifetime of a packet in the network. While the second part of the algorithm is the priority-based packet sending strategy, and jitter is used as a congestion signal indication. The combination of the two is expected to improve the efficiency of congestion detection. A mathematical model is established, and the analysis of the model shows that the algorithm has better effects on controlling congestion and improving the network throughput, decreasing packet loss rate and increasing network utilization, the simulation is done using NS-2 network simulation platform environment and the results support the theoretical analysis.
In this work a general dynamic response of two-story building due to earthquake is investigated .A spatial case of two degree mass-spring–damper random vibration model is employed .The base excitation acceleration is represented according to the well- known_x000D_ regression model by Kanai –Tajimi in term of the power specturm density (PSD). The transfer function between the ground an the roofs are evaluated assuming transverse modes of vibration._x000D_ A case study of typical two symitrical story building manufactored from reinforced concret and steel is investigated.The vibration parameters such as effective mass and stiffiness and damping are calculated according to the ACI 318-11 code.The natural frequncies , mode shape and transfer functions are calculated and plotted.The PSD acceleration at the roofs are evaluated from which the mean and standared diviation of the random accelration are found .The drift at the walls is calculated and compared with the allowable limits recommended by IBC 2015 .It is found that the probability of the bulding to be safe is between (13.74 -7.35)% for the first story and (8.7 - 1.67) % for the second.
The finite element method is one of the important methods in analyzing geotechnical engineering problems; its main advantage is the ability to apply for the materials exhibiting non-linear stress-strain behavior. In this study the finite element program PLAXIS 3D 2013 is used to study the behavior of the piles under the influence of seismic waves in saturated sandy soil and the effect of adding geogrid with the pile foundation. The program has been used to facilitate the representation of the real model, input the required soil parameters and implementation of seismic data. Seismic wave, the soil geometry and the pile dimensions were fixed in all models, while dimension and depth of the geogrid used were varied to study the influence of different depth and dimension in reducing the pile displacements and the pore water pressure of soil. The results show that The reduction in settlement ratio (the difference between settlement of pile without and with using geogrid to the settlement without using geogrid) for ( ×L/2), (L×L) and (2L×2L) are 10.6%, 17% and 21.3% respectively. And the settlement ratio for geogrid at depths 8.33% and 12.5% of pile length are 9.6% and 17% respectively.
This study concerns utilization of nonlinear finite element method for to evaluate the role of longitudinal soffit-bonded CFRP strips in elevating the shear behavior of RC beams without stirrups. All beams cross-sections were of 150 mm breadth and 200 mm depth, the overall length was 1500 mm with clear span 1300 mm. One beam was provided by minimum web reinforcement according to the ACI 318M-14, while the other five were without web reinforcement but externally strengthened by a variety of CFRP-strip combinations consisting of longitudinal soffit-bonded strips. The predictions of a proposed ANSYS (version 14.5) model for six of the test beams including modeling of concrete, steel rebars, CFRP strips and supports and loading steel plates, by SOLID65, LINK180, SHELL41 and SOLID185 elements, respectively, show high agreements with experimental evidence, which stands as a definite witness to the efficiency and reliability of the present numerical model.
An investigation of thermal conductivity enhancement, melting and solidification processes of Phase Change Materials (PCMs) by using metal foams has been carried out. Two models have been used in the experiments, model I for measuring the effective thermal conductivity of metal foam embedded in paraffin wax, and model II used as a small scale thermal energy storage device with and without metal foam for investigating melting and solidification processes of the PCM under different cooling conditions (natural and forced convection). The theoretical investigation involves analytical solution of two models, the semi-infinite medium for calculating the thermal conductivity, and the thermal energy storage system TESS has been analyzed including several assumptions for determining the convective heat transfer coefficient and the factors that controlling forced convection and solidification of the PCM. The experimental results show that the thermal conductivity of wax with 10 PPI metal foam increased by (37-39) times that of pure wax. Effects of pore density (10 and 40 PPI), metal foam, and mass flow rate on solidification process have been studied and the effects of pore density and metal foam on the melting process have also been investigated. The present experimental results have been compared with the available previous studies and gave a good agreement.
This research presents an experimental study of forced convection heat transfer for laminar steady flows in a duct filled with saturated porous media glass balls.The heater model consists of a circular cylinder , square cylinder and triangular cylinder .The experimental work was studied the effect of changing heater section on forced convection heat transfer with selected values of heat supply ( 2455W/m2 ).The experiments were carried out for Reynolds number ( 1094 ?
The evaluation of the behavior of bridge piers with soils surrounding them during earthquakes became necessary in Iraq especially after the influential earthquakes hit middle and south of Iraq during the last few years. A three dimensional finite element model for the bridge substructure and soil surrounding the bored piles with the actual dimensions and actual properties corresponding to "Sheikh Sa'ad Bridge" in Sheikh Sa'ad district at Wasit Governorate 37km south east of Kut city is presented. The model loaded with earthquake ground motion applied as lateral forces at one side of piles cap. The Earthquake hit 11 km from Ali-Al Gharbee in Maysan Province in 2012 with a magnitude of ML = 4.9 is used as the input ground motion. The response of the pier was investigated and the performance of piles and the soil surrounding them was examined. Then these typical piers and surrounding soils were checked weather they can bear the stresses induced due to these earthquake forces. From this work, it was found that typical piers used in bridges in Iraq can sustain earthquakes up to those with a magnitude of ML = 6.8 maximum.
This paper presents the design of robust four parameters (two degree of freedom) PI-PD controller based on Kharitonov theorem for antilock braking system. The Particle Swarm Optimization (PSO) method is used to tune the parameters of the proposed controller based on Kharitonov theorem to achieve the robustness over a wide range of system parameters change. The proposed cost function combines the time response specifications represented by the model reference and the frequency response specifications represented by gain margin and phase margin and the control signal specifications. The model reference control is used because of the antilock braking system is originally nonlinear and has different operating points. The robust stability is guaranteed by applying the Kharitonov theorem. Three types of road conditions (dry asphalt, gravel and icy) are used to test the proposed controller.
The main objective of this study was to model the left ventricle (LV) based on 2D echocardiography imaging technique to assess the cardiac mechanics for group of patients affected by heart failure. A prospective study has been made at Ibn Al-Bitar center for cardiac surgery, for 13 patients with heart failure (HF), 9 patients were males (69%) and 4 females (31%). The mean age was 54±7 years. Those patients were supposed to undergo a CRT-D (Cardiac Resynchronization Therapy Defibrillator) implant as they didn’t respond to drug therapy. Before CRT-D implantation, 2D echocardiography was performed for all the patients, to model the left ventricle and to measure indices that were used to evaluate cardiac mechanics which are LV pressure, wall stresses, global longitudinal strain, and cardiac output. After 3-months of follow-up, 2D echocardiography was re-assessed and the left ventricular mechanics has been re-measured. Post CRT-D implantation, significant improvement in the cardiac mechanics was observed in 54% of the patients which were called responders (patients that respond to CRT-D device) and the other patients were called non-responders. It has been seen that, the circumferential wall stresses were decreased in responder’s group while increased or remain unchanged in non-responders. Global longitudinal strain for the responder’s group were increased while remain unchanged in the non-responders. So, patients were divided into responders and non-responders, based on improvement of the cardiac mechanics after 3-moths of follow up. It has been concluded that the modelling of the left ventricle based on images obtained from 2D echocardiography imaging techniques, was an important computational tool that was used to enhance understanding and support the evaluation, surgical guidance and treatment management of basic biophysics underlying cardiac mechanics.
This paper discusses the development of a seven-band coherent wavelength-division multiplexing (WDM) system covering the T to U systems, aiming to enhance the capacity and system efficiency. Seven multiband systems (C+L, S+C+L, S+C+L+U, E+S+C+L, E+S+C+L+U, O+E+S+C+L+U, and T+O+E+S+C+L+U) are designed with 40 GBaud symbol rate, 50 GHz channel spacing, and dual-polarization (DP)-16QAM signaling. The analysis adopted the enhanced Gaussian noise model, considering the amplified spontaneous emission of inline optical amplifiers and nonlinear interference (NLI) from fiber nonlinear optics, including Kerr effect and stimulated Raman scattering (SRS) which it implemented using Matlab (Ver. 2020b) program. The results show that the optimal powers are -4, -5, -5, -4.5, -3.5, -6, and -4.5 dBm for the seven WDM systems, respectively. Further, with a fiber span length of 100 km, the C+L system has the longest transmission reach of 20 span. However, using S+C+L+U system gives the highest bit rate-distance product of 1619 Tbps.km. The O+E+S+C+L+U and T+O+E+S+C+L+U systems are designed with 50 km-span length to reduce the effect of NLI caused by the large numbers of channels (1060 and 1200, respectively).
This study implements the soft computing techniques such as Artificial Neural Network (ANN) and an adaptive Neuro-Fuzzy (ANFIS) approach. Thus to model the rutting prediction with the aid of experimental uniaxial creep test results for asphalt mixtures. Marshall samples, having Maximum Nominal Size of 12.5 mm, have been selected from previous studies. These samples have been prepared and tested under different conditions. They were also subjected to different loading stress (0.034, 0.069, 0.103) MPa, and tested at various temperature (10, 20, 40, and 55) °C. The modeling analysis revealed that both approaches are powerful tools for modeling creep behavior of pavement mixture in terms of Root Mean Square Error and Correlation Coefficient. The best results are obtained with the ANFIS model.
The human body poses the most important aim for many researchers. In nowadays, the science complex required the involvement of many resources and the coordinated team work of doctors, engineers, and other from the specialists. In the case of dental medicine, due to the nature of teeth material, their dimension and geometrical position, very important problems, like cavities that led to tooth losses. In this study, both the Experimental methods as well as the numerical finite element method have been used to analyze the stress within human teeth under forces similar to those that usually occur during chewing process with different type of food in experimental work. It was manufactured a device Resembling chewing process with vertical movement by converting circular movement into reciprocating. And used DAQ system (strain gauge sensor, DAQ and LABVIEW program) to measure the stress and strain resulted from tooth during the mastication process. Models of Natural lower first molars teeth were collected. All the teeth were cleaned from the soft tissue and stored in saline at room temperature. The teeth were randomly divided into two experimental groups according to the treated cavities shape (class I and class II) each class restored with two type of dental fillings material (Nanohybrid composite and Microhybrid composite), and then strain gauge was bonded at a buccal surface of tooth used. Their installed in acrylic jaws and applied different vertical loads. With used various morsels with different elastic modulus. The stress was calculated at the crown. In numerical 2D model of teeth were created by software Auto CAD (V.14) using wheeler 's data were transfer to ANSYS mechanical APDL (V. 16), subjected load at model similar at that applied at the Experimental work. Class I exhibited the highest stresses compared with class II, in two case Nanohybrid bear stress higher than microhybrid composite. At class I the stress at Nanohybrid is higher than Microhybrid for all morsels by rate (12.96%, 21.48%, 41.8%, 16.56%, 16.86% and 15.74%) at (E1, E2, E3, E4, E5 and E6) respectively, and the stress at Nanohybrid is higher than Microhybrid by almost (36.67%, 45.69%, 47.89%, 34.21%, 41.2% and 165.01%) respectively at the same morsels used at class II. _x000D_ Keywords: , , .
The 3-D numerical simulations of the thermal collectors in solar heating systems were conducted to simulate the conventional solar heating system, multipurpose solar water heater (MPSWH), and multipurpose solar air heater (MPSAH). The commercial computational fluid dynamics (CFD), AVL Fire ver. 2009.2 was used to solve and investigate the temperature distributions in the absorber plate and riser tube of both solar water and air heater during summer and winter seasons. The RNG k -turbulence model was employed for this CFD study. The present paper was to provide a good understanding of thermal performance for the solar collector at different operating conditions. The experimental setup and physical data of Venkatesh, R. and Christraj, W. [15] were employed as geometric parameters and initial boundary conditions to model and to validate the predicted numerical values. Comparing to the values of temperatures for the conventional SWH and SAH, the predicted results of the MPSWH and the MPSAH showed a good improvement on the thermal performance. These enhancements on the temperature may have been due to the new design adopted in the multipurpose solar heating systems by using riser tubes and headers to the original design of the thermal systems. Additionally, the thermal performance of solar collectors increases with increasing the mass flow rates and thermal conductivity of absorber plate. For validation aspect, the predicted results of all cases examined showed a good agreement against the measured results in terms of temperature distribution levels and thermal efficiencies.
Friction Stir welding (FSW) parameters, which play a vital principle, that impact on the mechanical, microstructural properties of the weldment because of the warmth produced by the contact between the instrument and work-piece, An AA6061-T6 aluminum composite plate with measurements (186*150*4) mm3 welded through various rotational paces 800, 1000, 1200 and 1450 rpm, the created heat measured through thermocouples embedded in study zones of the Weldment, a Finite Element model have been executed by utilizing ANSYS 12.1 bundle charges to ponder the temperature appropriation amid stay stage, the outcomes demonstrates a decent assention between the after effects of exploratory and hypothetical tests. The most extreme temperature measured at this condition was 0.71 from the liquefying temperature of the sample at a maximum rotational speed of (1450) r/min.
Numerical analysis of the performance of reinforced concrete (RC) deep beam subjected to static and fixed-point pulsating loading at the midpoint has been investigated. Three-dimensional nonlinear finite element model using the Strut and Tie approach was adopted. The damage level under the influence of the applied fixed pulsating loading is higher than the static applied loading, hence early crack was observed because of the stepwise loading in the form of vibration. Although the Strut and Tie approach gave a good estimation of the resistance capacity of the beam, the beam undergo high shear damage when subjected to these two types of loading. Material strength properties, applied loadings and cross-sections adopted are some of the factors that affect the performance of the deep beam.
The solar vortex engine (SVE) has been investigated to generate power using renewable energy. The SVE was constructed from a vortex generation engine (VGE) and solar air collector (SAC). The SVE system primarily utilizes vertical air movement. However, the airflow entering the VGE experiences an obstruction. The purpose of this paper is to propose a new design for the VGE that creates a swirling updraft capable of overcoming air obstruction and reducing energy losses. A 3D numerical model of VGE was developed to visualize vortex generation. The modeling of the VGE is carried using SOLIDWORKS software and ANSYS-FLUENT 18. The improved VGE has six vertical twisted convergence blades connected to six guide vanes to direct updraft air in an anticlockwise swirl. All blades and vanes are housed in a VGE cylinder with a diameter of 20cm and a height of 30cm. The simulation results were validated by comparing with the results obtained from the present experimental model. The simulation results match with a mean difference of less than 5% with the experimental measurements. The results of the current CFD investigation indicate that there is a gradient in air temperature and pressure within the VGE, ranging from the highest values of 314 K and 3.85 Pa to the lowest values of 308 K and 2.42 Pa, respectively. The CFD visualization shows a threefold increase in axial velocity and a fivefold increase in tangential velocity within an artificial vortex. Therefore, it can be concluded that the new VGE construction is highly efficient in generating a vortex.
Reverse Engineering is a process of re-producing existing parts by obtaining digital models using a special data taken from the original parts using specific techniques. It can be used to redesign existing parts either due to lost data or the parts are no longer available. In this paper, surface modelling technique using special data taken from CMM (Coordinate Measuring Machine) was employed to redesign a candle holder. Specific MATLAB code was generated to model the data taken from the surface of a candle holder made of glass. Bezier curve technique was implemented in this research to model the curve of the outer surface of the candle holder. Various orders of Bezier curves were discussed and used to give better approximation of the original data curve with error percentage monitoring each time. The thickness of the candle holder was reduced from 5mm to 3mm and the volume reduction was calculated. The amount of reduction in the glass volume when reducing the thickness was found to be 210mm3. In addition, the amount of increase in the area of glass section was calculated to be 138.5mm2. This reduction gives a better vision of the amount of glass saved using this procedure. Two different shapes were found and plotted by varying the control points coordinates.
In the last two decades, underwater acoustic sensor networks have begun to be used for commercial and non-commercial purposes. In this paper, the focus will be on improving the monitoring performance system of oil pipelines. Linear wireless sensor networks are a model of underwater applications for which many solutions have been developed through several research studies in previous years for data collection research. In underwater environments, there are certain inherent limitations, like large propagation delays, high error rate, limited bandwidth capacity, and communication with short-range. Many deployment algorithms and routing algorithms have been used in this field. In this work a new hierarchical network model proposed with improvement to Smart Redirect or Jump algorithm (SRJ). This improved algorithm is used in an underwater linear wireless sensor network for data transfer to reduce the complexity in routing algorithm for relay nodes which boost delay in communication. This work is implemented using OMNeT++ and MATLAB based on their integration. The results obtained based on throughput, energy consumption, and end to the end delay.
In the present work the worn journal bearing is simulated to discuss the effect of adding TiO2 nanoparticles to the base oil on its thermal performance. An extensive numerical investigation is carried out to study the effect of different parameters affecting thermal performance of worn journal bearing such as the eccentricity ratio (?), the wear depth parameter (?), and the nanoparticle concentration (?). The computational approach is provided by using finite difference method for solving the governing equations, namely, the modified Reynolds equation, energy and heat conduction equations with suitable equation to include the variation of the oil film thickness due to the bearing wear in order to estimate the benefits of using nanolubricant in worn journal bearings. Oil viscosity dependence on nanoparticle concentrations is considered by using Krieger Dougherty model. The mathematical model as well as the computer program prepared to solve the governing equations were validated by comparing the oil film pressure distribution obtained in the present work for a worn journal bearing with that obtained numerically by Hashimoto et.al [2](1986) with 3% maximum deviation between the results. The maximum oil film pressure obtained in this work was compared with that obtained experimentally by Roy [12] (2009) for intact journal bearing with 3% as a maximum error between the results. The results obtained show that the nanoparticles addition by 0.5% and 1% to the base oil increases the load carrying capacity of the worn journal bearing by 20% and 40% respectively while decreases the oil side leakage by 5% and 10% and friction coefficient by 2.75% and 5.7% as compared to that lubricated with pure oil. This is happen with the expense of power losses. Calculations also shows that adding a higher percentage of nanoparticles (2%) has a harmful effect on the performance of a worn journal bearing since the power losses is highly increased.
This paper presents a study of a nonholonomic differential drive wheeled mobile robot (WMR) of the type (BOE-Bot). In this paper, two aims are presented: the first is the study of the WMR movement on a specific trajectories to get the desired goals positions and the second is the evaluation of the kinematic performance factor of the WMR movement. The kinematic model of the robot movement in terms of the robot wheels velocity is studied by making the robot to move on the desired trajectories. The determination of the actual robot centre position in two dimensions (X) and (Y) is done by tracking the movement of a red point located above the robot by using a fixed camera attached to the ceiling. The position error between the theoretical and actual WMR position vectors is studied and calculated in global and local coordinates' frames. The values of the position error percentage ratios when the robot moved on a (S-shape) trajectory were higher than its values when the robot moved on a (straight-line) trajectory because of the existence of a gyroscopic torque resulted from the WMR circular movement around an axis perpendicular to the axis of the WMR wheels rotation. Finally, the kinematic performance factor of the WMR movement is evaluated depending on the position error in the global coordinate.
The Mono and binary-mixed oxide catalysts were prepared by precipitation and co-precipitation method and investigated for the photocatalytic decolorization of orange G dye which was used as a pollutant model in this study. The structure of the synthesized catalysts were characterized by the X-ray diffraction (XRD), bonding by fourier transfer infrared (FTIR), morphology by scanning electron microscope (SEM) and reflection using UV-VIS diffuse reflectance spectra. The XRD results revealed that the mono oxide catalysts confirm well the cubic phase of cadmium and cerium oxide and that their mixed oxide catalyst i.e. 50Ce/25Cd show the same characteristic peaks of pure cerium oxide with slight shift to higher wave lengths for two crystalline peaks at 33.15° and 56.15° respectively. The FTIR spectra of 50Ce/25Cd mixed oxide catalyst improved the combination between both pure cadmium and cerium oxide catalyst. The diffuse reflectance showed a blue shift towards lower wave length and that the energy gap was increased with an increase in cerium content. Different reaction variables such as, effect of metal content, pH values, amount of hydrogen peroxide and effect of catalyst amount were studied to estimate their effect on the decolorization efficiency of orange G dye. The maximum catalytic activity achieved was 91% at a solution pH of 2.1, catalyst dosage of 1.5 g/L, 0.15 mL of H2O2 /100 mL of reaction volume and initial dye concentration of 10 mg/L after 60 min of reaction time.
Regaining the activities of daily living after stroke and spinal cord injury requires repetitive and intensive tasks, meaning that rehabilitation therapy should be treated with a long duration. Thus, the need for rehabilitation devices based home is of most importance to increase the rehabilitation process and provide more comfortability for patients. This paper focuses on implementing and construction of a three degree of freedom (DOF) (flexion/extension, adduction/abduction, and pronation/supination), low cost, lightweight, and portable robotic exoskeleton for wrist-forearm rehabilitation. SolidWorks software program and 3D printer technology are used to model and construct the proposed robotic exoskeleton structure. In addition, the anthropometric parameters of the normal human lower arm are considered for this exoskeleton to provide a range of motion (ROM) and velocity for the links, joints, which matches with the anatomical structure of human and also to avoid the excesses motions over the normal range. The exoskeleton is constructed by a 3D printer utilizing polylactic acid (PLA) plastic material. The proposed implementing structure of the robotic exoskeleton shows comfortable, lightweight, simple and economic as well.
With the occurrence of pathological disorders in some people or aging, metabolic energy consumption begins significantly due to the weakness of the peripheral muscles and the increase in body fat with time, which aggravates the issues for this type of people, causing the rest hours extremely lengthy and consequently may produce heart or arterial diseases and elevate the mortality rate. Regarding the significance of the matter, this study examines a number of previous researches that featured several approaches to energy calculation and strategies for lowering energy consumption through the use of various external assistance devices, such as exosuits or exoskeletons, to assist people in carrying out their everyday tasks. And additionally discussed musculoskeletal simulation employs a variety of programs, especially OpenSim, which enables users to build models of musculoskeletal structures and produce dynamic movement simulations. According to the research findings, exoskeletons and other assistive technology can successfully lower the cost of metabolic energy to varying extents, depending on the device's weight, placement within the body, and whether it is active, semi-active, or inactive. In the future, the work to design and simulate a semi-active torsional ankle-foot exoskeleton with a specialized mechanism aimed to minimize metabolic energy.
The intention of this study was to explore the efficiency and feasibility of adsorption of Reactive Blue dye (H3R) used in textile industries using Raw wheat straw (RWS) and Modified wheat straw (MWS) as a low-cost adsorbent. Wheat straw was modified using cationic surfactant (CTAB) to study the improvement of dye removal. The properties of Raw and Modified wheat straw are studied by means of Fourier transform infrared (FTIR) and scanning electron microscope (SEM) analyses to determine the functional groups and the nature of their surface. Continuous experiments were done by fixed-bed column to study the characteristics of the breakthrough curve using different bed heights and flow rates. Results showed that the breakthrough time increases with increasing bed height and decreasing flow rate, in turn results into higher removal capacity. Results also showed a higher flow rate lead a lower adsorption capacity due to insufficient residence time. Bed depth service time model (BDST), Adam-Bohart and Thomas models were used to predict the breakthrough curves and to determine the adsorption capacity of the column. The highest bed capacity of 12.95 and 32.2 mg/g for MWS was obtained using 10 mg/L, 10 cm bed height at 10 mL/min and 30 mL/min respectively.
Kidney disease is a global health concern, often leading to kidney failure and impaired function. Artificial intelligence and deep learning have been extensively researched, with numerous proposed models and methods to improve kidney disease diagnosis. This work aims to enhance the efficiency and accuracy of the diagnostic system for kidney disease by using Deep Learning, thereby contributing to effective healthcare delivery. This work proposed three models: CNN, CNN-XGBoost and CNN-RF to extract features and classify kidney Ultrasound images into four categories: three abnormal cases (stones, hydronephrosis, and cysts) and one normal case. The models were tested on a real dataset of 1260 kidney ultrasound images (from 1000 patients) collected from the Lithotripsy Centre in Iraq. CNN models are often viewed as black boxes due to the challenge of understanding their learned behaviors, Visualizing Intermediate Activations (VIA) was used to address this issue. The proposed framework was assessed based on precision, recall, F1-score, and accuracy. CNN-RF is the most accurate model, with an accuracy of 99.6%. This study can potentially assist radiologists in high-volume medical facilities and enhance the accuracy of the diagnostic system for kidney disease.
In an original article, an addition was made to the well-known Taguchi’s methodical design literature by proposing how Poisson distribution may be incorporated into the Taguchi method for enhanced performance analysis in optimization. While the article is recent, it was found compelling enough to apply this novel concept of Poisson distribution to a growing area of maintenance research known as maintenance downtime analysis. Consequently, this paper contributes to the expanding research neighborhood through a Taguchi optimization method based on Poisson distribution related to the maintenance process optimization. A valuable method to optimize maintenance downtime was developed wherein the Poisson distribution was used to achieve the probability of maintenance downtime. An important foundation of the method is the Taguchi scheme. These elements were transformed into the factor-level design of the Poisson enhanced Taguchi scheme while the framework was tested using data from a process industry for validation. Interesting, the Taguchi's signal-to-noise quotient led to an enhanced set of limiting factors for better reliability of the system as G1H1I1J1K3. By interpretation, the following was found: downtime (204.61 mins), probability density function (0.00187), and cumulative density function (0.00776). The combination of these factors and levels will enhance maintenance downtime in the process industry as a result of their contributions. The outcome revealed the competence of the model to optimization schemes.
This study focused on the urban transformations resulting from the removal processes taking place in the urban fabric of sacred city centers, under the pretext of increasing urban capacity due to the density of use, which leads to the removal of important parts of the traditional urban fabric and adding them to the public urban space. To determine the amount of usage densities that the area can accommodate represented by the case study, which is the center of the holy city of Najaf: the study was based on using a quantitative measurement approach to test the hypothesis using a multivariable density measurement tool. A space matrix capable of measuring densities, accessibility, and diversity in the fabric during three time periods, a historical period 1900, 1990, and the current time 2024, to know the amount of changes that have occurred in the fabric. A qualitative measurement tool, which is a random sample questionnaire, was used to measure perceived density to find out which fabrics within the city center are more accommodating of congestion. The research has found that high and advanced accessibility through an integrated fabric with high connectivity that makes the city spaces work as one space leads to an increase in flows. It works to reduce the momentum in the city center and thus preserve the traditional urban fabric that must be emptied for pedestrians, as it represents the only fabric with The human scale at the level of the city as a whole (i.e. a fabric that is comfortable for pedestrians) also represents the identity of the area, and to accommodate the densities, the percentage of building density must be increased outside the traditional fabric.
The composite opened web steel joist supported floor systems have been common for many years. It is economic and has light weight and can embed the electrical conduit, ductwork and piping, eliminating the need for these to pass under the member, consequently eliminate the height between floors. In order to study the joist strength capacity under the various conditions, it had been fabricated seven joists composed of the steel and concrete slab connected to the top chord by shear connectors (headed studs). These joist have 2820 mm length c/c of the supports and 235 mm overall depth. In the present study, six variable parameters are adopted (Studs distribution, Degree of shear connection, Degree of the web inclination, Shape of the web, Density of concrete for slab and length of the shear connector). The test results exhibited that minimum strength capacity was 160kN for light weight joist and maximum capacity was 225kN for joist of long shear connectors at failure. The results were compared by ultimate flexural model by Azmi.
Mathematical and numerical study of finned tube air cooled condenser for air conditioning unit with two ton refrigeration capacity using R22 as a base fluid and R407C an alternative fluid was investigated. Different parameters were considered in this work, such as condensing pressure, ambient temperature and refrigerant mass flow. A comparison of performance between two condensers when using R22 and R407C were performed. A redesign the condenser operates with the R407C to operate with the same system that operates with R22. The result showed the same behavior for the two refrigerants, the condensers are possible to work with R407C for the same geometry and some modifications in the structure of heat exchange with the same air velocity. The proposed model was validated with the outputs from the test data given in literature papers, derived from air cooled condensers with different dimensions. The results exhibited an agreement with the experimental results with a percentage of compatibility ± 10%.
The transportation cost problem of solid waste presents the biggest part of the budget allocated by municipalities for SWM. So, there is no comprehensive plan to address transport routes optimization problems in SWM that including the transfer of solid waste from transfer stations to final landfill sites. Therefore, the aim of the study finding a scientific method to solve the transportation problem of solid waste transport suitable Baghdad city that tries to find feasible solutions that ensure reducing total transport costs and leads to an effective solid waste management system. In this research, a new methodology has been developed to select the optimal transport routs of SWM in Baghdad city which involves determining the best-supposed scenario. the proposed methodology includes integration of Global Positioning System (GPS) technologies with Network Analysis model (NA). Therefore, this work provides an advanced framework of decision-makers for analysis and simulation of the optimal transport routs problem related to SWM. Applying these modeling tools to select the scenario that can provide economic benefits by minimizing travel time, travel distance and reduction of total transportation costs. The Results of work implementation show that all solutions that include current state S1 and suggested scenarios have been evaluated. The scenarios generated include (S2, S3) by applying the proposed technique for analyzed and identified the optimal routes. The solutions of scenario S2, specified with two landfill sites while scenarios S3 specified with four landfill sites. Finally, this work shows the Scenario S3 is the best scenario of the solution, that include applied GPS and Network Analysis for four landfill sites.
In Republic of Iraq, ready-mix concrete production plants have been adversely affected by the lack of modern and advanced technology to assess their performance in line with technological advancements. Current evaluation methods rely on traditional approaches and financial measures, yielding unrealistic performance results. To address this problem, there is a need to utilize modern models and methods for performance evaluation. The study's main objective This was achieved by employing a literature survey methodology and utilizing digital databases such as the Iraqi Scientific Journals website, virtual libraries, and scientific platforms like ScienceDirect, Springer, Google Scholar, and Gate Research between 2015 and 2023. The research study provided a comprehensive overview of performance evaluation, including its definitions, importance, and an introduction to modern models and evaluation methods. The study found that no previous studies have been conducted in Iraq to evaluate ready-mix concrete production plants. However, four studies were found in Egypt, Sudan, and India. The previous similar relevant studies discussed various topics and related studies. Firstly, they discussed the classification, advantages, and disadvantages of concrete mixing plants. Additionally, the previous studies analyzed the factors that most influence the performance of concrete production plants, including laboratory manager efficiency, work team efficiency, communication and relationships within work teams, plant operator, material transportation method, and time and courses. Furthermore, the previous research studies present a comprehensive analysis of all variable data simultaneously using the statistical package for Social Science (SPSS) input stage. The evaluation also extends to the evaluation of laboratories, encompassing plant arrangement, internal quality control systems, and final product quality. The overall evaluation results of previous studies. Indicate that 75% of the concrete production plants failed to meet the required criteria, while only 25% demonstrated satisfactory performance. The study proposed improvements to enhance the performance rate of ready-mix concrete production plants by leveraging the most influential variables, which will be considered in the study.
The traditional electric poles in Iraq are usually made from steel materials. Such materials induced high weight, corrosion, permanent deformation caused by high wind speed, etc. The study aimed to numerically examine the strength of few poles made from different materials. The pole subjected to pressure developed by actual measured wind speed of 140 km/h. The numerical model of different materials and cross sections, an octagonal section electric pole made from composite material FRP–HDPE–FRP is suggested to replace the traditional one. The results showed high safety factor, approximately 5.51 besides the low ratio of high strength to weight as compared to steel materials. Using HDPE as reinforced material resulted in pole elastically deformed with only 0.222 mm. Therefore, it can be assumed that the suggested pole acts partially as a damper. Straight octagonal cross - section of pole promoted high reduction (74.22%) in maximum Von–Misses stress of that obtained in cylindrical three-stage pole. High reduction (5.87 times) in maximum deformation value was obtained when composite octagonal pole was used as compare to tapered pole made from steel.
In this paper, models were applied to investigate the parameters that affect membrane fouling. Osmotic pressure across the membrane, salt concentration at the surface of the membrane, solute mass transfer coefficient, effective coefficient diffusion of water, and concentration polarization factor were the main parameters that calculated in this simulation. Sodium chloride was assumed the only salt existed in the feed flux. In addition, changing the applied pressure versus increasing the salt concentration in the feed flux and their effect on the water permeation coefficient was investigated. The results confirmed that concentration polarization gives a good indication about the formation of the fouling layer at the membrane surface and consequently permeate decline.
One of the unique properties of laser heating applications is its powerful ability for precise pouring of energy on the needed regions in heat treatment applications. The rapid rise in temperature at the irradiated region produces a high temperature gradient, which contributes in phase metallurgical changes, inside the volume of the irradiated material. This article presents a comprehensive numerical work for a model based on experimentally laser heated AISI 1110 steel samples. The numerical investigation is based on the finite element method (FEM) taking in consideration the temperature dependent material properties to predict the temperature distribution within the irradiated material volume. The finite element analysis (FEA) was carried out using the APDL scripting language (ANSYS Parametric Design Language) that is provided by the commercial code ANSYS. Infrared (IR) thermography technique was used to explore the workpiece surface and to validate the obtained results. The work takes into account the effect of different speeds of the laser beam and pulses overlap on the temperature pattern of the material surface and depth.
Due to significant increasing in seismic activity in world during the last decades especially in Middle East region; engineers have been giving increasing attention to the design of buildings for earthquake resistance. In this study 3-D seismic behavior of piles is investigated using the finite element program PLAXIS 3D 2013. _x000D_ Piles are one of the most commonly used foundations in seismic areas where the soil is inadequate to carry the load on its own. In these seismic areas, piles often pass through (penetrate) shallow loose and/or soft soil deposits and rests on competent end bearing soils. Thus a model of soil - pile system is simulated in the finite element program._x000D_ The dynamic parameters of soil are used as input dynamic data of PLAXIS 3D program, in addition to the static properties of soil collected from soil investigation works._x000D_ The research showed the susceptibility of PLAXIS 3D program in analyzing piles with different soil conditions under earthquake action. The results also showed the importance of studying seismic behavior of soil-pile system using 3-D analysis rather than 2-D analysis because the problem is truly 3-D and should be analyzed as such.
This study has been performed to compare the compartmental modeling of two types of extravascular routes, sustained-release (SR) oral dosage forms and intramuscular (IM) injection. Twenty healthy volunteers received a single dose of 100 mg Diclofenac Sodium (DS) sustained-release tablet, then 75 mg DS Intramuscular injection after two weeks washout period. The concentrations of DS in plasma were measured using reverse-phase high-performance liquid chromatography (HPLC). The data analyzed using compartmental modeling, with single time-variant input and output. Primary kinetic parameters for both formulations, ( , , ) and other kinetic parameters were evaluated. The result shows that the IM injection needs a shorter time to reach the maximum concentration with convergent bioavailability to SR oral dosage forms, in another hand the data of IM injection fitted to single-compartment model with a correlation coefficient of 0.93 and the data of SR tablet fitted to two-compartment models with a correlation coefficient of 0.97.
This research submits theoretical and experimental realization of shear behavior of RC I-beams with polypropylene fiber with different volume fraction of plastic fiber as additive. The enhance of the sustainability of structural elements through the development of its mechanical performance by adding new materials such as plastic raw materials has become more important in the current period , particularly I- beams that was used in the long spans structure to become more environmentally-friendly. Seven specimens were tested in this study and only the amount of fiber volume fraction was varied. Experimental results showed that the ultimate strengths are increased in range (4.4% to 35.27%) that of control IB-1 for the tested beams containing Polypropylene Fiber Reinforced Concrete (PPFRC) with varied amount percentage of fiber material. Crack arrest mechanism of polypropylene fibers, and compressive strength of concrete increased in range (7.42% to 29.3%) that of plain concrete, and improved the tensile response in range (8.36% to 92.7%) that of plain concrete, limited crack propagation. So, improved behavior was obtained._x000D_ ANSYS 11, Finite Element models software are used to emulate two tested I-beams. 3D - nonlinear solid elements was utilized to model the concrete, while, the steel reinforcement was demonstrated by spar element. It was found that the general practices of the FE models demonstrated acceptable concurrence with perceptions and information from the experimental tests.
Water seepage can cause serious problems in geotechnical engineering especially for construction under the water level. Baghdad metro tunnel is one of the leading vital projects to solve the major problem of crowding roadways in a highly population increase city like Baghdad. In this study, the seepage rate that will flow toward different selected points along the tunnel section across Tigris River was calculated during the excavation process, with the consideration of three different water levels of River at maximum, moderate, and minimum water depths. A three-dimensional model of the study has been modeled using the finite element software (PLAXIS 3D V20). The water seepage was observed for six different locations on each route of the tunnel. The study showed that the change of water depth in the river has no significant effect on the seepage – time curve shape. However, increasing the water level in River from minimum to maximum leads to increase the seepage rate about 15%.
Super-hydrophobic is the tendency of a surface to spit out water droplets. Only a surface with high apparent contact angle (>1500), low contact angle hysteresis (<100), low sliding angle (<50), and strong Cassie model state stability is considered a super-hydrophobic surface. In an attempt to create highly hydrophobic synthetic surfaces suitable for a range of uses, attempts have been made to mimic the super-hydrophobicity found in natural materials (such as lotus leaves). Due to its wide range of applications including waterproof, anti-fog, anti-ice and anti-corrosion surface, the laser processing process achieved the use of process parameters which had a significant impact on the roughness factor. High roughness factor F. At constant values of p = 3 mW and ω = 10 μm, at scanning speeds of 6000 mm/s.
The aim of this study was to support surgeons to decide where to place the screws in order to achieve an optimal fracture healing and to prevent implant failure after a femoral shaft fracture So this paper focus on the analysis of bone-plate construct by using Finite element Analysis (FEA), comminuted femur fractured bone fixed with Dynamic Compression Plate (DCP) 16 holes by 4.5 Cortex screws, to investigate the effects of screws configuration on the mechanical behavior of different seven model as Interfragmentary strain which is the most important factor for femur fracture healing. The results state the relationships between the Von-Mises stress, Total deformation and Interfragmentary strain with respect to the screws configuration. The study shows the regions of maximum stress from stress distribution and also founded that we can decrease the Interfragmentary strain by increasing the number of screws.
This paper deals with the elastic stability of a column bolted at its mid-height to a simply supported square plate and subjected to a concentrated load, using energy method. A uniform homogeneous column is assumed to be pinned at both ends. From symmetry considerations, half of the column is modeled by making the plate acting as a torsion spring on the column at its mid-height. The column length and cross-section, plate dimensions and thickness, and the material properties for the column and the plate catch the interest of the author. The problem is solved by using energy method and ultimately, the elastic buckling load is found. The analytical elastic buckling load is compared with a numerical solution obtained from finite element method using SAP2000. The numerical results agree with the analytical solution. The finite element model is refined to catch the actual effect of the bolted plate on the elastic buckling load. It has been found that the elastic buckling load is increased due to the increase in the rotational stiffness provided from the plate.
The goal of this paper is to present a study of tuning the Proportional-Integral-Derivative (PID) controller for control the position of a DC motor by using the Particle Swarm Optimization (PSO) technique as well as the Ziegler & Nichols (ZN) technique. The conventional Ziegler & Nichols (ZN) method for tuning the PID controller gives a big overshoot and large settling time, so for this reason a modern control approach such as particle swarm optimization (PSO) is used to overcome this disadvantage. In this work, a third order system is considered to be the model of a DC motor. Four types of performance indices are used when using the particle swarm optimization technique. These indices are ISE, IAE, ITAE and ITSE. Also study the effect of each one of these performance indices by obtaining the percentage overshoot and settling time when a unit step input is applied to a DC motor. A comparison is made between the two methods for tuning the parameters of PID controller for control the position of a DC motor is considered. The first one is tuning the controller by using the Particle Swarm Optimization technique where the second is tuning by using the Ziegler & Nichols method. The proposed PID parameters adjustment by the Particle Swarm Optimization technique showed better results than the Ziegler & Nichols’ method. The obtained simulation results showed good validity of the proposed method. MATLAB programming and Simulink were adopted in this work.
Hydraulic structures can be accepted as the key components in improving aeration efficiency because of the strong turbulent mixing associated with substantial air bubble entrainment at these structures. Different hydraulic structures have been designed to enhance aeration such as stepped cascades. A laboratory model of stepped cascade weir with five different shapes of end sill (normal, triangle, rectangle1, rectangle2 and rectangle3) have been installed at Al- Mustansiriya University, College of Engineering to evaluate treatment system and reduced pollutants in marginal water for different flow rates (35,60 and 80 L/min). Results indicate that high removal efficiency of all pollutants parameter (Cu, Cr, Mo, Br, Fe, Mn, Zn, PO4, Cl-, ClO2, Hardness as CaCO3, NH3, NO2, Toxic matter) is for rectangle1 shape at Q=60L/min. High aeration efficiency is 45.7% for rectangle1 shape at Q=80L/min. High removal efficiency for BOD5 and COD are 48% and 47% respectively for rectangle 1 at Q=80 L/min.
Continuous Positive Airway Pressure (CPAP) ventilation remains a mainstay treatment for different respiratory disorders. Good pressure stability and pressure reduction during exhalation are of major importance condition to ensure the clinical efficacy and comfort of CPAP therapy. Obstructive Sleep Apnea (OSA) and today coronavirus (COVID-19) are the main two diseases mitigated by the CPAP. This paper introduced a systematic review of the CPAP design in terms of the hardware design, Simulation-based CPAP system, control algorithm, and the measured performance. The accuracy is used as measurement of performance and calculated from the pressure value. The accuracy was compared to the predefined U.S. Food and Drug Administration (FDA)-based threshold value in which it considers this value as a reference. The results related to the modern CPAP devices introduced in this study to explain the accuracy of experimental CPAP. These were compared with a commercial CPAP devices. Also, it was revealed how the results coincide with the error ratio defined by the FDA as an evaluation measurement. The FDA error ratio determines the performance of the optimized CPAP device. This work is the first review that presented the knowledge about engineering design of the CPAP system, so it will be the first in the literature.
Basrah is the richest town and the economic capital of Iraq. It suffers from lack of drinking water. This project is a dream to supply drinking water to Basrah citizens within WHO standards. Water should pass sedimentation and filtration stages before interring reverse osmosis unit. The design is carried out using lewaplus2 software. Several parameters should be selected in the design step membrane type, number of stages, number per element in each stage, and the recovery percentage. An optimization is carried out using Minitab ver. 18 for the acceptable limit of TDS and minimum cost and it was found that the optimum conditions were 52% for first stage, the numbers of vessels are 20 for both the first and second stage. In addition, results showed that the pressure and the total dissolved solid increase with increasing the recovery while parameters like the feed flow rate per vessel, the power, and the cost are decreasing with the recovery. Mathematical model described the cost was conducted and statistical study was also done to ensure the results.
Free Space Optics (FSO) plays a vital role in modern wireless communications due to its advantages over fiber optics and RF techniques where a transmission of huge bandwidth and access to remote places become possible._x000D_ The specific aim of this research is to analyze the Bit-Error Rate (BER) for FSO communication system when the signal is sent the over medium of turbulence channel, where the fading channel is described by the Gamma-Gamma model. The signal quality is improved by using Optical Space-Time Block- Code (OSTBC) and then the BER will be reduced. Optical 2×2 Alamouti scheme required 14 dB bit energy to noise ratio (Eb/N0) at 10-5 bit error rate (BER) which gives 3.5 dB gain as compared to no diversity scheme._x000D_ The results show that using Multiple-Input-Multiple-Output (MIMO) technique represented by Alamouti scheme gives the improved BER performance as compared with no diversity (Single-Input-Single-Output (SISO)) technique.
The study aims to evaluate the current flood carrying capacity and its change after some cross sections developments for the 110 km reach of Tigris River and Kmait flood escape system. This reach extends from Ali Al-Gharbi station to Amarah Barrage station. The model is calibrated by using set of data at the Ali Al-Garbi gaging station, that includes flow varied between 790 to 470 m3/s during April 2019. Manning’s n coefficient value of (0.03) is selected as it has the minimum least-squares root difference of (0.148) between the measured and estimated water levels. The results show that the current capacity of Kmait flood escape and this Tigris River reach are 280 m3/s and 1100 m3/s, respectively. According to the study of strategic for water and land resources in Iraq, 2014, scenarios are conducted for some cross sections development to improve the capacity of the reach to 2750 m3/s. Results of applied development show that Tigris River can safely accommodate a flood wave of 2750 m3/s when modifying the cross-sections in different locations, and raising the banks level in three locations, 0+00, 79+00 and 95+00km. Earthworks volume of development of the reach is 247603200 million m³, with the total cost of 490 billion IQD.
In this Research Geometric network modeled for combined sewer network pipe design were establish for AL-Nahrain University site by Arc map and GIS tools which is built within a feature dataset in the geodatabase. The geometric networks consist of lines and points which refer to the pips and junctions respectively. Data were collected for manholes location, flow direction, slop and elevations. Many influencing features were used in multi criteria decision making (MCDM) vie Super decision 2.0.8 software which be selected to fix the problem and find the alternative for two sewer networks. The first sewer network (A) considered the existing one and the second was the alternative one (B) , Bentley sewer Cad V8 have the ability to work with ArcGIS program as a part of it by export data as shape file from GIS then by scenario report form program that exam the part of network and find the alternative . The purpose of this research was to use this data GIS model, and developed it in future event by predicting some function like rainfall amount or adding population increasing density represent by both student and employers. As a result using (ANP) analysis this method allow to make consideration alternative we found the network(A) need to add some routs depending in the amount of person daily consumption with the amount of rain fall Intensity for the next years., judgment based on expert advice is obtained through pair-wise comparisons. Afterwards, the corresponding matrix is established, and sanity of the comparisons is checked by super decision software. Finally Existing network (A) shows highest benefit score and efficiency in this time for steady case depends on two criteria coast and optimum flow for person consumption.
Power outages are a common and persistent problem in Iraq, significantly impacting various aspects of life and business. These interruptions disrupt routine household tasks and hinder more complex technical operations in industries and services. Emphasizing the need for careful management and proactive solutions. This paper introduces a real-world time series dataset for Baghdad city, including historical outages, weather conditions (such as temperature), and power overloads, and analyzes the correlation among these parameters in different seasons. The research uses this dataset to train one-dimensional Convolutional Neural Networks (1D CNN) to find patterns and relationships that can accurately predict when power outages can happen in the long term and short term to improve the management of the Baghdad electricity grid through data-driven networks. This model was evaluated using performance metrics, and the results show that CNN is accurate in predicting outages in the short term with a Mean Absolute Error (MAE) of (0.0077), whereas, in the long term, it has achieved an MAE of (0.0775). These predictive models have the potential to facilitate the development of proactive measures aimed at reducing the impact of power outages by anticipating potential outages in advance. This research focuses on enhancing the reliability and efficiency of Baghdad's electricity supply, ultimately contributing to economic growth and stability.
Face recognition and identification have recently become the most widely employed biometric authentication technologies, especially for access to persons and other security purposes. It represents one of the most significant pattern recognition technologies that uses characteristics included in facial images or videos to detect the identity of individuals. However, most of the traditional facial algorithms have faced limitations in identification and verification accuracy. As a result, this paper presents a sophisticated system for face identification adopting a novel algorithm of deep learning, namely, You Only Look Once version 8 (YOLOv8). This system can detect the face identity of different individuals with different positions with high accuracy. The YOLOv8 model has been trained for several target face images classified as training and validation images of 1190 and 255, respectively. The experimental results show a significant improvement in face identification accuracy of 99% of mean average precision, which outperforms many state-of-the-art face identification techniques.
This study presents a numerical analysis for point contact Elasto-hydrodynamic lubrication EHL. The oils used are (0W-30 and 10W-40) as lubricants. The pressure and film-thickness profiles for point contact EHL are evaluated. The aims of this study are to estimate the effect of oil’s temperature on friction force, coefficient of friction and load carrying capacity. By using FORTRAN program, the Forward-iterative method is used, to solve two dimensional (2D) EHL problem. The viscosity is updating in the solution by using Roeland’s model. After the convergence of pressure is done, the friction force, friction power losses, and friction coefficient are calculated. The temperature used ranges from (-20 to 120 oC). The results showed the film-thickness decreases with the increasing of temperature. Though the maximum pressure is not affected, only the pressure distribution and profile are changed, inlet pressure decreases and the pressure profile tends towards a hertzian (dry contact) one. The friction force and the coefficient of friction decrease with the increasing of temperature.
In this paper, the design of a robust controller for two wheeled inverted pendulum (TWIP) system is presented. In the first stage of the design, a full state feedback H2 control is designed for stabilizing the inclination of (TWIP) system to upright position. The H? controller for the stabilized system is synthesized in the second stage. The mathematical model of the system based on the Newtonian approach is developed. The results verify that the proposed controller can compensate the system parameter uncertainty with a more desirable time response specifications.
The Unified Power Flow Controller (UPFC) is a most complex power electronic device, which can simultaneously control a local bus voltage and optimize power flows in the electrical power transmission system. This paper presents the effect of installing the UPFC on the Iraqi (400 kV) grid transmission system to control the active and reactive power flow by choosing the optimal location and parameters of Unified Power Flow Controllers (UPFCs), which were specified based on the Genetic Algorithm (GA) optimization method. The objectives are improving voltage profile, reducing power losses, treating power flow in overloaded transmission lines, and reducing power generation. The steady state model of UPFC has been adopted on (400 kV) Iraq transmission lines and simulated using the MATLAB programming language. The Newton-Raphson (NR) numerical analysis method has been used for solving the load flow of the system. The practical part has been solved through Power System Simulation for Engineers (PSS\E) software Version 32.0. The Comparative results between the experimental and practical parts obtained from adopting the UPFC were too close and almost the same under different loading conditions, which are (5%, 10%, 15% and 20%) of the total load.
In this paper, the robustness properties of sliding mode control (SMC) which is designed to produce a dynamic output feedback controller to achieve robustness for trajectory tracking of the nonlinear human swing leg system is presented. The human swing leg represents the support of human leg or the humanoid robot leg which is usually modeled as a double pendulum. The thigh and shank of a human leg will respect the pendulum links, hip and knee will connect the upper body to thigh and then shank respectively. The total moments required to move the muscles of thigh and shank are denoted by two external (servomotors) torques applied at the hip and knee joints. The mathematical model of the system is developed. The results show that the proposed controller can robustly stabilize the system and achieve a desirable time response specification.
Many researchers have applied several experiments and research studies by developing criteria's design of drainage to improve the drainage process, and to show that the filters plays an important role to improve and maintain the drainage system from being blocked due to siltation. There are several types of filters, including granular mineral materials and organic materials, the other filter that was used is made from a special fabric material such as paper, burlap, or special fabric textile material. The objective of this study is to evaluate the performance of textile filters, and if it is desirable and suitable for Iraqi soil using statistical analysis. This study was conducted in the laboratory using sand tank model and two types of filters (graded crushed gravel and textile) with two types of soil (sandy soil and loamy soil) to compare and evaluate the hydraulic performance and the efficiency of utilizing textile filter instead of graded crushed gravel filter in drainage systems using statistical analysis methods. These statistical analysis show that there was a good agreement between measured and theoretical values of entrance resistance when using the two filters in sandy soil. On the other hand, the results showed that there was a weak performance when textile filters in were used in heavy soil (loamy soil) due to the high value of root mean square error (RMSE) and low value of agreement index (d). The results of statistical analysis show that the textile filter is desirable and suitable for Iraqi soil especially for sandy soil due to low entrance resistance of flow compared to loamy soil.
A new robust control algorithm is proposed for a class of nonlinear systems represented by a Single Link Manipulator (SLM) system. This algorithm is based on new techniques and methods in order to obtain a controller for the SLM system. First of all, the system is simplified using Variable Transformation Technique (VTT) in order to fit the analysis procedure. Then, a new idea of designing a model reference for the multiple states (n=4) system is presented to correspond the control design. Next, the Lyapunov Stability Analysis (LSA) is used to figure out a proper controller that can compensate the stability and the performance of the SLM system. After that, the Most Valuable Player Algorithm (MVPA) is applied to find the optimal parameters of the proposed controller to accomplish the optimum performance improvement. Finally, it can be concluded that the proposed control algorithm has improved the stability and the performance of the SLM system. In addition, the simulation results show the remarkable effects of the proposed nonlinear controller on the SLM system.
In this paper, an Adaptive Sliding Mode Controller (ASMC) is designed and applied for a magnetic levitation system (Maglev) where a steel ball is desired to be stabilized at a desired position with existence of uncertainty in system model. Additionally, a sliding mode differentiator (SMD) is used for estimating the ball velocity since it’s needed for the controller to work properly. The designed controller and differentiator are applied practically to an experimental laboratory size magnetic levitation system and the results were plotted to show the behavior of the system under the effect of the designed controller. The experimental results reveal clearly the effectiveness and ability of the suggested controller in forcing the steel ball to follow various desired position.
Forced vibration has been experimentally investigated on a model consists of circular pipe with1.6m length. The pipe built in tank (1.2m length, 0.6m height and 0.6m width) horizontally at 0.4m height with two different diameters d=15mm and d=35mm. The pipe conveying laminar flow in the fully developed region, of Reynolds number equals 2000. The experimental results of span pipe conveying water at five stations of forced excitation vibration were studied. The harmonic forced vibration with two different excitation frequencies (10 Hz and 15 Hz) are imposed at all of the five locations. The distance between two stations is (0.2m). Two conditions of pipe environment have been applied, the first in air and the other was immersed in water. It is concluded that the effect of flow induced vibration due to the pipe conveying fluid increases the maximum deflection when the fluid speed increases. The water surrounds the pipes reduce the effect of excitation vibration about (33 – 46%). The effect difference between the excitation frequencies was about (4 – 7%).
Recently, there is increasing interest in using the 18 THz bandwidth offered by S+C+L band to increase the transmission capacity of fiber communication systems. This leads to the generation of ultra-wideband (UWB) wavelength-division multiplexing (WDM) optical communication systems. In these advanced systems, stimulated Raman scattering (SRS) causes a power transfer from high-frequency channels to low-frequency channels. This effect leads to an increase in the nonlinear interference (NLI) between the UWB-WDM channels. Power optimization techniques are required to balance transfer power between band channels, thus increasing the maximum transmission reach (MTR) along with increasing system capacity. In this paper, the transmission performance of S+C+L band system operating with dual-polarization 16-QAM signaling is investigated using enhanced Gaussian noise model. The transmitter and receiver for each DP channel use a -polarized laser and incorporate two identical configurations, one for x- and the other for y-state of polarization (SOP). The results are presented for two values of symbol rate, 40 and 80 GBaud, where the system carries 360 (=160+80+120) and 180 (=80+40+60) channels, respectively. The results revel that the MTR of both cases is equal to 12 100 km-spans when the channel lunch power equals to -4 and -2 dBm, respectively. This work also shows the effect of NLI components as a function of the number of spans, channel spacing, and channel launch power. The results show that the cross-phase modulation component of the NLI has high accumulated value with transmission distance, while the self-phase modulation component is almost constant.
Numerical and experimental investigations were carried out on the effect of the vortex generators on the flow field and heat transfer from duct heaters. The flow Reynolds number ranging from 32000<Re<83000 with a constant heat flux of 43.09426._x000D_ In the numerical investigation, Fluent package (6.3) was used to solve the steady, (3-D), continuity, momentum and energy equations where the standard (k-?) model was used to remedy the turbulent effects. Theoretical results show that the presence of VGs would save 27% of heaters power. The effects of two areas of VGs were looked at a small circle cross section vortex generator (SCCSVG) and a big circle cross section vortex generator (BCCSVG) of similar shapes (where)._x000D_ The experimental results showed that there were an enhancement in heat transfer with the presence of VGs and heat transfer depends on VGs’ areas. The BCCSVG was the better one of enhancing heat transfer by (2.76%-4.11%). Additionally, the increase of area of VGs, number of rows for VGs and the distance between each two rows of VGs and the heaters are the most effective parameters in improving the performance of heat transfer.