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Article
PREDICTION OF HEAT TRANSFER CHARACTERISTICS FOR FORCED CONVECTION PIPE FLOW USING ARTIFICIAL NEURAL NETWORKS

Authors: Khalid B. Saleem --- Imad A. Kheioon --- Hussien S. Sultan
Journal: KUFA JOURNAL OF ENGINEERING مجلة الكوفة الهندسية ISSN: 25230018 Year: 2019 Volume: 10 Issue: 3 Pages: 73-89
Publisher: University of Kufa جامعة الكوفة

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Abstract

This paper investigates the ability of utilizing the artificial neural network (ANN) in calculating the forced convection characteristics coefficients from internal flow of air inside a pipe subjected to constant heat flux. The heat transfer characteristics such as Nusselt number (Nu), Stanton number (St) and friction factor (f) which are calculated using the empirical correlations have high deviation from that obtained from the experiments. So, the ANN method is proposed for predicting these characteristics coefficients more close to the experimental results. The training and testing data for optimizing the ANN structure are based on the experimental data obtained from the experiments performed on a forced convection apparatus. Three training algorithms for the training of the ANN were used and the presented ANN is implemented by using such MATLAB program. For the preferable ANN structure acquired in the current work, an acceptable mean square error was achieved for the training and test data, using the Trainlm algorithm. The results reveal that the estimated results are very close to the experimental data. Also, a new Graphical User Interface (GUI) is implemented for the application of ANN in the calculation of the attempted heat transfer parameters.


Article
A New Fuzzy-NARMA L2 Controller Design for Active Suspension System

Authors: Imad A. Kheioon عماد خيون --- Basil Sh. Munahi باسل شنين مناحي --- Ali H. Abdulaali علي حسن عبدالعالي
Journal: Basrah Journal for Engineering Science مجلة البصرة للعلوم الهندسية ISSN: Print: 18146120; Online: 23118385 Year: 2017 Volume: 17 Issue: 2 Pages: 43-50
Publisher: Basrah University جامعة البصرة

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Abstract

This paper is concerned with the design of a newcontroller for active suspension system. The model isconsidered as a quarter-car. The presented controller dependson the fuzzy technique and NARMA-L2 linearizationalgorithm. The compensation system that added by the fuzzyrules improves the performance of the controller, while theneural network produces the required control signal. The newcontroller can achieve an improvement of the ride comfortwith a reasonable value of power consumption. Themathematical analysis of the mechanical power used by themodel is focused on the average and the RMS of the powersupplied to the system, regardless of the frequency content ofthe vibration signal. The simulation results which are verifiedby a practical examples of road profiles, demonstrate theefficacy of the proposed controller.

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