论文标题
模型还原框架具有新的主动空间，以实现线性化流体结构互动约束的优化问题
Model Reduction Framework with a New Take on Active Subspaces for Optimization Problems with Linearized Fluid-Structure Interaction Constraints
论文作者
论文摘要
在本文中，提出了一个新的概念，即在多学科分析和优化（MDAO）问题中降低设计参数空间的维度的概念。新方法与自适应参数采样，基于投影的模型订单降低以及基于矩阵歧管上插值的线性，基于投影的简化阶模型的数据库相互交织，以构建MDAO的有效计算框架。该框架是针对线性化流体结构相互作用约束的MDAO问题的全面开发的。它适用于两个不同的飞行系统的飘逸限制下的气体弹性剪裁：NASA常见研究模型的灵活配置；以及NASA的Aero弹性研究部＃2（ARW-2）。获得的结果说明了计算框架对现实的MDAO问题的可行性，并强调了新方法的好处，该方法以解决方案最佳性和降低墙壁限制的方式构建了主动子空间
In this paper, a new take on the concept of an active subspace for reducing the dimension of the design parameter space in a multidisciplinary analysis and optimization (MDAO) problem is proposed. The new approach is intertwined with the concepts of adaptive parameter sampling, projection-based model order reduction, and a database of linear, projection-based reduced-order models equipped with interpolation on matrix manifolds, in order to construct an efficient computational framework for MDAO. The framework is fully developed for MDAO problems with linearized fluid-structure interaction constraints. It is applied to the aeroelastic tailoring, under flutter constraints, of two different flight systems: a flexible configuration of NASA's Common Research Model; and NASA's Aeroelastic Research Wing #2 (ARW-2). The obtained results illustrate the feasibility of the computational framework for realistic MDAO problems and highlight the benefits of the new approach for constructing an active subspace in both terms of solution optimality and wall-clock time reduction
