Optimization using surrogate models and partially converged computational fluid dynamics simulations
Optimization using surrogate models and partially converged computational fluid dynamics simulations
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DOI：
10.1098/rspa.2006.1679
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发表时间：
2006-07
期刊：
影响因子：
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通讯作者：
Alexander I. J. Forrester;N. Bressloff;A. Keane
中科院分区：
文献类型：
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作者：
Alexander I. J. Forrester;N. Bressloff;A. Keane
使用计算流体动力学模拟进行全局气动优化的有效方法应旨在减少评估设计概念所需的时间和优化所需的评估次数。本文研究的方法，提高这种效率，通过使用部分收敛的计算流体动力学的结果。这使得代理模型可以在基于收敛结果的模型所需时间的一小部分内构建。所提出的优化方法提高了收敛到全局最优的速度，同时减少了在不良设计领域所花费的计算机资源。一个战略相结合的全局近似建立使用部分收敛的模拟与预期的改善更新收敛的模拟优于传统的代理为基础的优化。
Efficient methods for global aerodynamic optimization using computational fluid dynamics simulations should aim to reduce both the time taken to evaluate design concepts and the number of evaluations needed for optimization. This paper investigates methods for improving such efficiency through the use of partially converged computational fluid dynamics results. These allow surrogate models to be built in a fraction of the time required for models based on converged results. The proposed optimization methodologies increase the speed of convergence to a global optimum while the computer resources expended in areas of poor designs are reduced. A strategy which combines a global approximation built using partially converged simulations with expected improvement updates of converged simulations is shown to outperform a traditional surrogate-based optimization.