A novel aspect of composite sandwich fairing structure optimization of a two-stage launch vehicle (Safir) using multidisciplinary design optimization independent subspace approach

Morovat, Foozieh; Mozaffari, Ali; Roshanian, Jafar; Zare, Hadi

doi:10.1016/j.ast.2018.10.033

Cited by 17 publications

(1 citation statement)

References 25 publications

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“…In recent years, substantial advances have been made in the application of MDO architectures to aircraft design practices [17,18]. Generally speaking, these architectures can be divided into two main groups: single-level and multi-level approaches.…”

Section: Classification Of Mdo Architecturesmentioning

confidence: 99%

A Review of Uncertainty-Based Multidisciplinary Design Optimization Methods Based on Intelligent Strategies

Wang,

Fan,

Qiang

2023

Symmetry

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The design of aerospace systems is recognized as a complex interdisciplinary process. Many studies have shown that the exchange of information among multiple disciplines often results in strong coupling and nonlinearity characteristics in system optimization. Meanwhile, inevitable multi-source uncertainty factors continuously accumulate during the optimization process, greatly compromising the system’s robustness and reliability. In this context, uncertainty-based multidisciplinary design optimization (UMDO) has emerged and has been preliminarily applied in aerospace practices. However, it still encounters major challenges, including the complexity of multidisciplinary analysis modeling, and organizational and computational complexities of uncertainty analysis and optimization. Extensive research has been conducted recently to address these issues, particularly uncertainty analysis and artificial intelligence strategies. The former further enriches the UMDO technique, while the latter makes outstanding contributions to addressing the computational complexity of UMDO. With the aim of providing an overview of currently available methods, this paper summarizes existing state-of-the art UMDO technologies, with a special focus on relevant intelligent optimization strategies.

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Section: Classification Of Mdo Architecturesmentioning

confidence: 99%