发表机构
Boeing Aerostructures Australia (BAA); Sir Lawrence Wackett Defence and Aerospace Centre, RMIT University（波音澳大利亚航空结构公司; RMIT大学劳伦斯·瓦凯特国防与航空航天中心）
机构由 AI 辅助整理，请以论文原文为准。AI 中文总结
针对高度受限的气动外形优化，提出一种结构模态参数化方法，通过可调伪结构的模态基参数化几何，实现参数简洁、约束感知与几何灵活性的平衡。
AI 中文摘要
飞机外模线通常在早期就受到载荷要求、可制造性限制和低可观测性考虑的严重约束。剩余的气动设计空间通常很小、高度受限，并且难以用一组简洁且物理意义明确的设计变量来表示。针对此类问题，本文引入了一种结构模态参数化方法（MPM）。该方法构建一个可调的伪结构，并求解其特征值问题以获得模态基，从中选取模态子集对几何进行参数化。边界条件、刚度分布、密度、厚度和附加质量被视为有意的基设计变量，这些变量在优化前塑造了可接受的变形空间。所得的设计坐标与任何特定的流动求解器无关，使得该方法具有广泛的适用性。对于高度受限的气动外形优化问题，该方法在参数简洁性、稳健的约束感知和几何灵活性之间提供了实用的平衡。
英文摘要
Aircraft outer mould lines are often heavily constrained early by payload requirements, manufacturability limits, and low-observability considerations. The remaining aerodynamic design space is typically small, highly constrained, and difficult to represent using a concise and physically meaningful set of design variables. A structural modal parameterisation method (MPM) is introduced for such problems. The method constructs a tunable pseudo-structure and solves its eigenvalue problem to obtain a modal basis, from which a selected subset of modes parameterises the geometry. Boundary conditions, stiffness distribution, density, thickness, and added masses are treated as intentional basis-design variables that shape the admissible deformation space prior to optimisation. The resulting design coordinates are independent of any specific flow solver, making the approach broadly applicable. For tightly constrained aerodynamic shape optimisation problems, it provides a practical balance of parameter conciseness, robust constraint awareness, and geometric flexibility.
Comments22 pages, 17 figures. Accepted for presentation at ICAS 2026. Conference presentation scheduled for 17 September 2026. v2: Corrected arXiv PDF pagination around Figure 12 and Table 5. Updated Figure 12(d)
