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Modeling and Control of Fuel Cell Using Artificial Neural Networks
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This paper includes an experimental study of hydrogen mass flow rate and inlet hydrogen pressure effect on the fuel cell performance. Depending on the experimental results, a model of fuel cell based on artificial neural networks is proposed. A back propagation learning rule with the log-sigmoid activation function is adopted to construct neural networks model. Experimental data resulting from 36 fuel cell tests are used as a learning data. The hydrogen mass flow rate, applied load and inlet hydrogen pressure are inputs to fuel cell model, while the current and voltage are outputs. Proposed model could successfully predict the fuel cell performance in good agreement with actual data. This work is extended to developed fuel cell feedback control system using PID controller to stabilize the fuel cell voltage. Particle swarm optimization technique is used to tune the PID controller gains. The voltage error and hydrogen flow rate are input and the actuator of the PID controller respectively. Simulation results showed that using PID controller with proposed model of fuel cell can successfully improve system performance in tracking output voltage under different operating conditions.

 

 

 

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Publication Date
Wed Mar 18 2020
Journal Name
Baghdad Science Journal
Solving Linear Volterra – Fredholm Integral Equation of the Second Type Using Linear Programming Method
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In this paper, a new technique is offered for solving three types of linear integral equations of the 2nd kind including Volterra-Fredholm integral equations (LVFIE) (as a general case), Volterra integral equations (LVIE) and Fredholm integral equations (LFIE) (as special cases). The new technique depends on approximating the solution to a polynomial of degree  and therefore reducing the problem to a linear programming problem(LPP), which will be solved to find the approximate solution of LVFIE. Moreover, quadrature methods including trapezoidal rule (TR), Simpson 1/3 rule (SR), Boole rule (BR), and Romberg integration formula (RI) are used to approximate the integrals that exist in LVFIE. Also, a comparison between those methods i

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Publication Date
Mon Jun 01 2020
Journal Name
Journal Of Engineering Science And Technology
The feasibility of using styrene-butadiene-styrene (SBS) as modifier in Iraqi bituminous binder
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The increase in the number of trucks and other heavy vehicles in Iraqi highways lead to cracking and deteriorations in the flexible highway. The use of polymermodified asphalt may solve this problem to match the required performance standards. This study investigates the effects of styrene-butadiene-styrene (SBS) polymer on the performance behaviour of Iraqi bitumen binder. The characteristics of bitumen binder were analysed to observe the compatibility of bitumen with SBS polymer. The bitumen binder was mixed with three different contents of SBS (4%, 4.5%, and 5%) by weight of asphalt cement. Viscosity tests were conducted on the SBS polymer-modified asphalt at 135 oC and 165 oC in addition to conventional binder tests. The prepar

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Publication Date
Sat May 01 2021
Journal Name
Journal Of Physics: Conference Series
The Classification of Fetus Gender Based on Fuzzy C-Mean Using a Hybrid Filter
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Abstract<p>This paper proposes a new approach, of Clustering Ultrasound images using the Hybrid Filter (CUHF) to determine the gender of the fetus in the early stages. The possible advantage of CUHF, a better result can be achieved when fuzzy c-mean FCM returns incorrect clusters. The proposed approach is conducted in two steps. Firstly, a preprocessing step to decrease the noise presented in ultrasound images by applying the filters: Local Binary Pattern (LBP), median, median and discrete wavelet (DWT), (median, DWT & LBP) and (median & Laplacian) ML. Secondly, implementing Fuzzy C-Mean (FCM) for clustering the resulted images from the first step. Amongst those filters, Median & Lap</p> ... Show More
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Publication Date
Mon May 06 2024
Journal Name
Journal Of Ecological Engineering
Using Machine Learning Algorithms to Predict the Sweetness of Bananas at Different Drying Times
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The consumption of dried bananas has increased because they contain essential nutrients. In order to preserve bananas for a longer period, a drying process is carried out, which makes them a light snack that does not spoil quickly. On the other hand, machine learning algorithms can be used to predict the sweetness of dried bananas. The article aimed to study the effect of different drying times (6, 8, and 10 hours) using an air dryer on some physical and chemical characteristics of bananas, including CIE-L*a*b, water content, carbohydrates, and sweetness. Also predicting the sweetness of dried bananas based on the CIE-L*a*b ratios using machine learn- ing algorithms RF, SVM, LDA, KNN, and CART. The results showed that increasing the drying

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Publication Date
Tue Nov 01 2022
Journal Name
Energy Reports
Thermal effectiveness of solar collector using Graphene nanostructures suspended in ethylene glycol–water mixtures
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Publication Date
Sun Jan 01 2023
Journal Name
Technologies And Materials For Renewable Energy, Environment And Sustainability: Tmrees22fr
Investigate the structural properties of Tl1-xHgxSr2Ca2Cu3O8+δ compound by using Scherrer modified equation
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Publication Date
Fri May 01 2020
Journal Name
Environmental Technology & Innovation
Environmental remediation of synthetic leachate produced from sanitary landfills using low-cost composite sorbent
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Publication Date
Sat Jun 01 2024
Journal Name
Journal Of Ecological Engineering
Using Machine Learning Algorithms to Predict the Sweetness of Bananas at Different Drying Times
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Publication Date
Thu Nov 02 2023
Journal Name
Journal Of Engineering
Numerical Study of Piled Raft Foundation in Non-Homogeneous Soil Using Finite Element Method
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This paper analyzes a piled-raft foundation on non-homogeneous soils with variable layer depth percentages. The present work aims to perform a three-dimensional finite element analysis of a piled-raft foundation subjected to vertical load using the PLAXIS 3D software. Parametric analysis was carried out to determine the effect of soil type and initial layer thickness. The parametric study showed that increasing the relative density from 30 % to 80 % of the upper sand layer and the thickness of the first layer has led to an increase in the ultimate load and a decrease in the settlement of piled raft foundations for the cases of sand over weak soil.  In clay over weak soil, the ultimate load of the piled raft foundation w

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Publication Date
Tue Nov 08 2022
Journal Name
Buildings
An Experimental Study of Granular Material Using Recycled Concrete Waste for Pavement Roadbed Construction
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Rapid worldwide urbanization and drastic population growth have increased the demand for new road construction, which will cause a substantial amount of natural resources such as aggregates to be consumed. The use of recycled concrete aggregate could be one of the possible ways to offset the aggregate shortage problem and reduce environmental pollution. This paper reports an experimental study of unbound granular material using recycled concrete aggregate for pavement subbase construction. Five percentages of recycled concrete aggregate obtained from two different sources with an originally designed compressive strength of 20–30 MPa as well as 31–40 MPa at three particle size levels, i.e., coarse, fine, and extra fine, were test

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