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首页> 外文期刊>Meccanica: Journal of the Italian Association of Theoretical and Applied Mechanics >Intelligent design of waste heat recovery systems using thermoelectric generators and optimization tools
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Intelligent design of waste heat recovery systems using thermoelectric generators and optimization tools

机译:使用热电发电机和优化工具的废热回收系统的智能设计

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摘要

Optimal design of thermal systems that effectively use energy resources is one of the foremost challenges that researchers almost confront. Until now, several researches have been made to enhance the performance of major thermal systems. In this investigation, the authors try to make a conceptual design to maximize the electricity demand of Damavand power plant as the biggest thermal system in Middle East sited in Iran. The idea of designing is laid behind applying a number of thermoelectric modules within the condenser in order to recover the waste heat of the thermal systems. Besides, the authors have developed some intelligent tools to elaborate on the performance of their proposed model. Firstly, an artificial neural network has been utilized to estimate the potential power generation of the thermoelectric modules. At the second step, computational fluid dynamic solver, FLUENT is used to determine the variation of the temperature through the length of the thermoelectric module assembly. Based on the gained results, an intelligent multi-objective optimization algorithm called Pareto based mutable smart bee is developed to optimize the properties of the thermoelectric component.
机译:有效利用能源的热力系统的优化设计是研究人员几乎面临的首要挑战之一。迄今为止,已经进行了一些研究来增强主要热系统的性能。在这项调查中,作者试图进行概念设计,以最大限度地提高达马万德电厂的电力需求,该电厂是伊朗位于中东的最大热力系统。设计的想法是在冷凝器内应用多个热电模块,以回收热系统的废热。此外,作者还开发了一些智能工具来详细说明所提出模型的性能。首先,人工神经网络已被用来估算热电模块的潜在发电量。在第二步中,使用计算流体动力学求解器FLUENT确定热电模块组件长度范围内的温度变化。基于获得的结果,开发了一种智能的多目标优化算法,称为基于Pareto的可变智能蜂,以优化热电组件的性能。

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