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Optimizing Structure of Catalysts and Development of Kinetic Parameters for Synthesis Gas to Olefin Reaction
, Ph.D. Dissertation Sharif University of Technology ; Ghotbi, Siroos (Supervisor) ; Bozorg Mehri, Ramin (Supervisor) ; Zarrinpashne, Saeid (Supervisor)
Abstract
Synthesis gas to light olefin reactions especially propylene production is one of the important path for clean fuel production in gas conversion processes. The object of this study is to define true kinetic model of process first step (e.g. Synthesis gas to light Olefins). For that, kinetic model for Co/Mn/TiO2 catalyst, which has the best conversion and selectivity for propylene, has been developed. Kinetic reaction parameters were measured by kinetic modeling in (220-300)0C temperature , (1-5)bar pressure , H2/CO=(1:3) and (450-600)hr-1 space velocity .After studying with significant models ,the best fitting can obtained with "KPCO P 1/2H2/(1+aPco+bPH2 1/2)2"equation. Later to...
Genetic algorithm-optimised structure of convolutional neural network for face recognition applications
, Article IET Computer Vision ; Volume 10, Issue 6 , 2016 , Pages 559-566 ; 17519632 (ISSN) ; Pooyan, M ; Manzuri Shalmani, M. T ; Sharif University of Technology
Institution of Engineering and Technology
2016
Abstract
Proposing a proper method for face recognition is still a challenging subject in biometric and computer vision applications. Although some reliable systems were introduced under relatively controlled conditions, their recognition rate is not satisfactory in the general settings. This is especially true when there are variations in pose, illumination, and facial expression. To alleviate these problems, a hybrid face recognition system is proposed which benefits from the superiority of both convolutional neural network (CNN) and support vector machine (SVM). To this end, first a genetic algorithm is employed to find the optimum structure of CNN. Then, the performance of the system is improved...
Simultaneous optimization and simulation of a-Si1-xC x layers on n-type silicon solar cells
, Article Solar Energy Materials and Solar Cells ; Volume 85, Issue 4 , 2005 , Pages 467-476 ; 09270248 (ISSN) ; Asadi, K ; Sharif University of Technology
2005
Abstract
We have applied Rosenbrock's optimization algorithm to obtain the optimized efficiency of a solar cell and its structural parameters. To obtain these parameters, we have developed a computer program for simultaneous optimization and simulation of the solar cell. We have used experimental data on the electrical and optical properties of a-Si1-xCx layers, put them into the written code and obtained the optimized parameters of this solar cell. The maximum efficiency is 6.32% which is close to one experimental result. © 2004 Elsevier B.V. All rights reserved
Comparative analysis of hydrate formation pressure applying cubic equations of state (eos), artificial neural network (ann) and adaptive neuro-fuzzy inference system (anfis)
, Article International Journal of Thermodynamics ; Volume 15, Issue 2 , 2012 , Pages 91-101 ; 13019724 (ISSN) ; Saber, M ; Ameri, A ; Sharif University of Technology
Abstract
The objective of this work is making comparison between thermodynamic models and data-driven techniques accuracy in prediction of hydrate formation pressure as a function of temperature and composition of gas mixtures. The Peng-Robinson (PR) and Patel-Teja (PT) equations of state are used for thermodynamic modeling and Artificial Neural Networks (ANNs) and Adaptive Neuro-Fuzzy Inference System (ANFIS) are used as data-driven models. The capability of each method is evaluated by comparison with the experimental data collected from literature. It is shown that there is a good agreement between thermodynamic modeling and the experimental data in most of the cases; however, the prediction...