卢吉承, 宋文滨, 郑彭军. 高维度气动优化问题的可视化方法[J]. 空气动力学学报, 2018, 36(5): 780-790. DOI: 10.7638/kqdlxxb-2016.0079
引用本文: 卢吉承, 宋文滨, 郑彭军. 高维度气动优化问题的可视化方法[J]. 空气动力学学报, 2018, 36(5): 780-790. DOI: 10.7638/kqdlxxb-2016.0079
LU Jicheng, SONG Wenbin, ZHENG Pengjun. A visualization method for high-dimensional aerodynamic optimization[J]. ACTA AERODYNAMICA SINICA, 2018, 36(5): 780-790. DOI: 10.7638/kqdlxxb-2016.0079
Citation: LU Jicheng, SONG Wenbin, ZHENG Pengjun. A visualization method for high-dimensional aerodynamic optimization[J]. ACTA AERODYNAMICA SINICA, 2018, 36(5): 780-790. DOI: 10.7638/kqdlxxb-2016.0079

高维度气动优化问题的可视化方法

A visualization method for high-dimensional aerodynamic optimization

  • 摘要: 随着高可信度数值分析模型的参数维数的增加和非线性关联度的提高,不但计算量增加,针对二维和三维数据的常规可视化方法也难以直接、全面展示变量与响应函数之间的复杂关系。本文在总结常用低维度数据可视化方法的基础上,结合数据样本和响应面模型,利用MATLAB提供的基础数据分析与显示功能,发展了一种模块化的、复合及动态的可视化方法及工具,该方法可以系统、灵活地展示高维参数空间、多维响应函数空间,以及两者之间的关联关系。在测试函数和翼型气动优化问题上的应用表明该方法有助于提高高维问题的优化效率和质量。

     

    Abstract: The use of high-fidelity physics-based simulation models has become increasingly important in aircraft design process, including models based on computational fluid dynamics, finite element structure analysis, and system simulation methods. It is now common to formulate a problem with large number of design variables with complex and nonlinear relations among them. The increase in the number of variables, coupled with high computational cost associated with those high fidelity models, has led to a challenging task of global optimization even on high performance computing facilities within the time constraint and of visualizing the results with the typical 2D and 3D visualization methods currently available. In this paper, the common visualization methods for low dimensional data are first reviewed, and then a couple of new visualization techniques are proposed and implemented in a modular and hybrid visualization tool, based on a combination of design of experiments, response surface models and some data analysis methods. The tool is implemented in MATLAB and is capable of systematically presenting the high-dimensional design space, multi-dimensional response functions and their relationships. The applications on test functions and airfoil aerodynamic optimization indicate that the proposed visualization method is useful for designers to analyze high-dimensional data set and to increase the efficiency and quality of high-dimensional optimization solution.

     

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