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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
Sun Jul 09 2023
Journal Name
Journal Of Engineering
Deep Desulfurization of Diesel Fuel by Guard Bed Adsorption of Activated Carbon and Locally Prepared Cu-Y Zeolite
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Desulfurization of a simulated diesel fuel by different adsorbents was studied in a fixed-bed adsorption process operated at ambient temperature and pressure.  Three different adsorption beds were used, commercial activated carbon, Cu-Y zeolite, and layered bed of 15wt% activated carbon followed by Cu-Y zeolite.Initially Y-zeolite was prepared from Iraqi rice husk and then impregnated with copper. In general, the adsorbents tested for total sulfur adsorption capacity at break through followed the order Ac/Cu-Y zeolite>Cu-Y zeolite>Ac. The best adsorbent, Ac/Cu-Y zeolite is capable of producing more than 30 cm3 of simulated diesel fuel per gram of adsorbent with a weighted average content of 5 ppm-S, while Cu-Y zeolite producing of

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Publication Date
Mon Dec 23 2024
Journal Name
Al–bahith Al–a'alami
HUMAN MODELING IN THE IRAQI PRESS: (A Survey of Human Modeling for March And April 2011)
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This research deals with what so called concept of The Human Model and how Iraqi Media concerns of this concept practically as it plays a key role in attracting readers, on the first hand. On the second, it is important to shed light on the scientific desire of the Iraqi Media and how it deals with this contemporary trend especially in editorial media.

The importance of the research stems from the fact that it alerts to a new stream of modern trends in journalistic writing, according to many modern Arab and foreign media studies; and to the importance of employing human modeling in dealing with facts, events, issues and problems in various editorial arts within their effective influence in concilia

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Publication Date
Wed Aug 30 2023
Journal Name
Iraqi Journal Of Science
Community Detection in Modular Complex Networks Using an Improved Particle Swarm Optimization Algorithm
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     Community detection is an important and interesting topic for better understanding and analyzing complex network structures. Detecting hidden partitions in complex networks is proven to be an NP-hard problem that may not be accurately resolved using traditional methods. So it is solved using evolutionary computation methods and modeled in the literature as an optimization problem.  In recent years, many researchers have directed their research efforts toward addressing the problem of community structure detection by developing different algorithms and making use of single-objective optimization methods. In this study, we have continued that research line by improving the Particle Swarm Optimization (PSO) algorithm using a

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Publication Date
Tue Dec 31 2013
Journal Name
Al-khwarizmi Engineering Journal
Design of an Adaptive PID Neural Controller for Continuous Stirred Tank Reactor based on Particle Swarm Optimization
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 A particle swarm optimization algorithm and neural network like self-tuning PID controller for CSTR system is presented. The scheme of the discrete-time PID control structure is based on neural network and tuned the parameters of the PID controller by using a particle swarm optimization PSO technique as a simple and fast training algorithm. The proposed method has advantage that it is not necessary to use a combined structure of identification and decision because it used PSO. Simulation results show the effectiveness of the proposed adaptive PID neural control algorithm in terms of minimum tracking error and smoothness control signal obtained for non-linear dynamical CSTR system.

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Publication Date
Sun Apr 23 2017
Journal Name
Ibn Al-haitham Journal For Pure And Applied Sciences
Control of American Foul Brood Disease (AFB) in Honey Bee Using Thyme Extracts and Thymol
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 Ethanolic extracts of Thyme (Thymbra spicata) were tested for their inhibitory action on Paenibacillus larvae the causative agent of American foul brood with different concentration by using disc assay and mixed with culture media . Results showd that 3000mg / disc and 3000 mg / ml was the effective concentroation for the both methods .Thymol was isolated by using TLC technique . The effective concentration of thymol on growth of bacteria was 1000 mg / disc .          Thymol and crude extracts of thyme 3000 mg / ml were tested on infected hives by mixed with sugar  solution . The symptoms of AFB disease was full disappearance within 21 , 27 days after treatment with thymol and thyme

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Publication Date
Mon Dec 18 2017
Journal Name
Al-khwarizmi Engineering Journal
Using Smart Control System to Enhancement the Split Air Conditioning System Performance
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In IRAQ, the air conditioners are the principal cause of high electrical demand. In summer, the outer temperature sometimes exceeds 500C which significantly effects on the A/C system performance and power consumed. In the present work, the improvement in mechanical and electrical performance of split A/C system is investigated experimentally and analytically. In this paper, performance and energy saving enhancement of a split-A/C system was experimentally investigated to be efficiently compatible with elevated temperature weathers. This improvement is accomplished via Smart Control System integrate with Proportional-Integral- Differential PID algorithm. The PIC16F877A micro-controller has been programmed with the PID and PWM c

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Publication Date
Tue Apr 21 2020
Journal Name
University Of Thi-qar Journal Of Science (university Of Thi-qar Journal Of Science (utsci) The 4th Scientific Conference Of Science College/ University Of Thi_qari) The 4th Scientific Conference Of Science College/ University Of Thi_qar
Enhancement of Nano Catalyst for an Alkaline Fuel Cells
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Publication Date
Wed Mar 01 2017
Journal Name
2017 Annual Conference On New Trends In Information & Communications Technology Applications (ntict)
Automatic Iraqi license plate recognition system using back propagation neural network (BPNN)
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Publication Date
Thu Dec 01 2016
Journal Name
2016 Asia-pacific Microwave Conference (apmc)
High selectivity microstrip bandpass filter using feedback CRLH-TL unit cell
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Publication Date
Wed May 31 2023
Journal Name
Iraqi Geological Journal
Studying the Effect of Permeability Prediction on Reservoir History Matching by Using Artificial Intelligence and Flow Zone Indicator Methods
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The map of permeability distribution in the reservoirs is considered one of the most essential steps of the geologic model building due to its governing the fluid flow through the reservoir which makes it the most influential parameter on the history matching than other parameters. For that, it is the most petrophysical properties that are tuned during the history matching. Unfortunately, the prediction of the relationship between static petrophysics (porosity) and dynamic petrophysics (permeability) from conventional wells logs has a sophisticated problem to solve by conventional statistical methods for heterogeneous formations. For that, this paper examines the ability and performance of the artificial intelligence method in perme

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