Using Parametric Effectiveness for Efficient CAD-Based Adjoint Optimization
Using Parametric Effectiveness for Efficient CAD-Based Adjoint Optimization
复制标题
使用参数有效性进行基于 CAD 的高效伴随优化
DOI：
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发表时间：
2018
影响因子：
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通讯作者：
C. Armstrong
中科院分区：
文献类型：
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作者：
Dheeraj Agarwal;Kapellos Christos;T. Robinson;C. Armstrong
参数有效性是定义用于优化的 CAD 模型的参数能力的度量。它将使用 CAD 模型参数化可实现的最佳性能变化与模型自由移动时可获得的最大性能改进进行了比较。本文的目的是提出一种自动化方法来有效计算 CAD 建模软件 CATIA V5 中定义的参数的参数有效性。该方法经过进一步开发，可自动识别 CAD 参数子集，从而提供最大的性能改进潜力。选择此类子集的理由是减少优化过程中更新参数化 CAD 模型所需的时间，这是工业工作流程中需要考虑的重要因素。该方法应用于 S 弯管道的形状优化，以最大限度地减少功率损耗，以及汽车后视镜的形状优化，以最大限度地减少汽车驾驶员感受到的噪音。流量灵敏度是用连续伴随法计算的。
Parametric effectiveness is a measure of the ability of the parameters defining a CAD model to be used for optimization. It compares the optimum change in performance that can be achieved using a CAD model’s parameterization, to the maximum performance improvement that could be obtained if the model is free to move. The aim of this paper is to present an automated approach to efficiently compute the parametric effectiveness for the parameters defined within a CAD modelling software CATIA V5. The approach is further developed to automatically identify a subset of CAD parameters which provides the greatest potential for performance improvement. The rationale for selecting such a subset is to reduce the time required to update a parametric CAD model during the optimization, which is an important factor to be considered in an industrial workflow. The approach is applied to the shape optimization of an S-Bend duct for minimizing the power-loss and an automotive car mirror for minimizing the noise perceived by the driver of the car. The flow sensitivities are computed with a continuous adjoint method.