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A simulation-based two-step method for optimal thermal design of multiple compartments

机译:一种基于模拟的多隔室最佳热设计的两步方法

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摘要

To achieve the target of temperature control with minimum power consumption, a simulation-based two-step method for optimal thermal design of multiple compartments is proposed. First, the flow passages are designed to accomplish the goal of allocating the cooling capacity based on thermal load distribution. Thermal load analysis is performed to obtain an approximate flow rate. Multiple tools, including genetic algorithm (GA), design of experiment (DOE), response surface method (RSM) and computational fluid dynamic (CFD) are coupled to find the approximate solutions of the design variables. These approximate solutions are set as an estimation of the Pareto solutions of the tradeoff between temperature targets and power consumption. Secondly, a multi-objective genetic algorithm and CFD are coupled to find the Pareto solutions. A model of multiple compartments with different thermal loads is evaluated as demonstration. The results reveal that the response surfaces based on a 200% over-determined provide a satisfactory predicting capability. The solution space is greatly reduced in the first step with less computational cost. The approximate solutions obtained from the design of flow passages are an excellent estimation of the optimal solutions. For the second step, the Pareto solutions satisfying the requirement of temperature control are acquired through the evolution of 10 generations. (C) 2017 Elsevier Ltd. All rights reserved.
机译:为了实现具有最小功耗的温度控制目标,提出了一种用于多个隔室的最佳热设计的基于模拟的两步方法。首先,流动通道旨在实现基于热负荷分布分配冷却能力的目标。进行热负荷分析以获得近似的流速。多种工具,包括遗传算法(GA),实验设计(DOE),响应面方法(RSM)和计算流体动态(CFD),以找到设计变量的近似解。这些近似解决方案被设定为温度目标和功耗之间的权衡的Pareto解决方案的估计。其次,耦合多目标遗传算法和CFD以找到帕累托解决方案。具有不同热载荷的多个隔室的模型被评估为示范。结果表明,基于200%过分确定的响应表面提供了令人满意的预测能力。在具有较少计算成本的第一步中,解决方案空间大大减少。从流动通道设计获得的近似解是对最佳解决方案的优异估计。对于第二步,通过10代的演化获取满足温度控制要求的帕累托解决方案。 (c)2017 Elsevier Ltd.保留所有权利。

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