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首页> 外文会议>AIAA Aerospace Sciences Meeting Including the New Horizons Forum and Aerospace Exposition >A Knowledge-Based Geometry Repair System for Robust Parametric CAD Models
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A Knowledge-Based Geometry Repair System for Robust Parametric CAD Models

机译：基于知识的高压参数CAD模型的几何修复系统

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In modern multi-objective design optimization (MDO) an effective geometry engine is becoming an essential tool and its performance has a significant impact on the entire MDO process. Building a parametric geometry requires difficult compromises between the conflicting goals of robustness and flexibility. This article presents a method of improving the robustness of parametric geometry models by capturing and modeling engineering knowledge with a support vector regression surrogate, and deploying it automatically for the search of a more robust design alternative while trying to maintain the original design intent. Design engineers are given the opportunity to choose from a range of optimized designs that balance the 'health' of the repaired geometry and the original design intent. The prototype system is tested on a 2D intake design repair example and shows the potential to reduce the reliance on human design experts in the conceptual design phase and improve the stability of the optimization cycle. It also helps speed up the design process by reducing the time and computational power that could be wasted on flawed geometries or frequent human interventions.
机译：在现代多目标设计优化（MDO）有效几何引擎正在成为一个不可或缺的工具，其性能对整个MDO过程显著的影响。建立一个几何参数，需要鲁棒性和灵活性的相互冲突的目标之间很难妥协。本文介绍了通过捕捉和建模与支持向量回归替代工程知识，并为寻找一个更强大的设计选择自动部署它同时试图保持原有的设计意图改善几何参数模型的鲁棒性的方法。设计工程师有机会从一系列优化设计，以选择平衡修复几何“健康”和原始设计意图。原型系统在2D进气设计修复一例，表示测试，以减少在概念设计阶段对人类设计专家的依赖，提高了优化周期的稳定性的潜力。它还通过减少可能有缺陷的几何形状或频繁的人类干预被浪费的时间和计算能力有助于加快设计进程。

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