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An improved multidisciplinary feasible method using DACE approximation approach

机译:使用DACE近似方法改进的多学科可行方法

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Multidisciplinary feasible method (MDF) is conventional method to multidisciplinary optimization (MDO) and well-understood by users. It reduces the dimensions of the multidisciplinary optimization problem by using the design variables as independent optimization variables. However, at each iteration of the conventional optimization procedure,multidisciplinary analysis (MDA) is numerously performed that results in extreme expense and low optimization efficiency. The intrinsic weakness of MDF is due to the times that it loop fixed-point iterations in MDA, which drive us to improve MDF by building inexpensive approximations as surrogates for expensive MDA. An simple example is presented to demonstrate the usefulness of the improved MDF. Results show that a significant reduction in the number of multidisciplinary analysis required for optimization is obtained as compared with original MDF and the efficiency of optimization is increased.
机译:多学科可行方法(MDF)是用于多学科优化(MDO)的传统方法,并通过用户良好地理解。它通过使用设计变量作为独立优化变量来减少多学科优化问题的维度。然而,在传统优化过程的每次迭代,多学科分析(MDA)无大量执行,导致极端费用和低优化效率。 MDF的内在弱点是由于它在MDA中的循环定点迭代的时间,这使我们能够通过将廉价的近似作为昂贵的MDA的替代品来改善MDF。提出了一个简单的例子来证明改进的MDF的有用性。结果表明,与原始MDF相比,获得优化所需的多学科分析数量的显着降低,并增加了优化效率。

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