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首页> 外文期刊>Annals of nuclear energy >Multi-objective, multi-physics optimization of 3D mixed-oxide LWR fuel assembly designs using the MOJADE algorithm
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Multi-objective, multi-physics optimization of 3D mixed-oxide LWR fuel assembly designs using the MOJADE algorithm

机译:使用MOJADE算法的3D混合氧化物LWR燃料组件设计的多目标,多物理优化

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Optimization problems in the research literature are typically simplified and/or heavily constrained and focus on a single set of physical processes. Real-world nuclear engineering problems feature competing multi-physics phenomena and require equally complex analysis. To prove its usefulness in this area, optimization must demonstrate an ability to handle many competing objectives whilst accurately simulating the reactor environment. This paper applies the MOJADE optimization algorithm to two design problems, a 3D PWR Supercell and a 3D BWR fuel assembly, evaluating performance objectives related to neutronics and thermal hydraulics simultaneously, using the concept of Pareto dominance. In both cases, MOJADE was able to find competitive or non-dominated designs compared to baseline solutions generated from the literature and required no control parameter tuning or training time. Analysis revealed that MOJADE can identify key variables which impact objective performance, demonstrating the algorithm's ability to provide new insight to complex 3D problems featuring multi-physics analysis. (C) 2020 Elsevier Ltd. All rights reserved.
机译:研究文献中的优化问题通常是简化和/或严重限制并专注于单一的物理过程。现实世界核工程问题特征竞争多物理现象,需要同样复杂的分析。为了证明其在该领域的实用性,优化必须表明能够处理许多竞争目标的能力,同时准确地模拟反应器环境。本文将Mojade优化算法应用于两个设计问题,3D PWR超级电池和3D BWR燃料组件,同时评估与中型和热水力学相关的性能目标,使用Pareto优势的概念。在这两种情况下,与文献生成的基线解决方案相比,Mojade能够找到竞争或非主导的设计,并且无需控制参数调整或培训时间。分析显示,Mojade可以识别影响客观性能的关键变量,展示算法为具有多物理分析的复杂3D问题提供新的洞察力的能力。 (c)2020 elestvier有限公司保留所有权利。

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