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

中文翻译：

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模型简化框架，对具有线性化流固耦合约束的优化问题采用新的主动子空间

在本文中，提出了一种新的活动子空间概念，用于在多学科分析和优化 (MDAO) 问题中减少设计参数空间的维数。新方法与自适应参数采样、基于投影的模型降阶以及配备矩阵流形插值的线性、基于投影的降阶模型数据库的概念交织在一起，以构建有效的 MDAO 计算框架. 该框架完全针对具有线性化流固耦合约束的 MDAO 问题而开发。它应用于两种不同飞行系统在颤振约束下的气动弹性剪裁：NASA 通用研究模型的灵活配置；和 NASA 的气动弹性研究翼 #2 (ARW-2)。