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Titlebook: Advances in Structural and Multidisciplinary Optimization; Proceedings of the 1 Axel Schumacher,Thomas Vietor,Kurt Maute Conference proceed

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發(fā)表于 2025-3-21 17:40:43 | 只看該作者 |倒序?yàn)g覽 |閱讀模式
期刊全稱Advances in Structural and Multidisciplinary Optimization
期刊簡稱Proceedings of the 1
影響因子2023Axel Schumacher,Thomas Vietor,Kurt Maute
視頻videohttp://file.papertrans.cn/150/149899/149899.mp4
發(fā)行地址Includes supplementary material:
圖書封面Titlebook: Advances in Structural and Multidisciplinary Optimization; Proceedings of the 1 Axel Schumacher,Thomas Vietor,Kurt Maute Conference proceed
影響因子The volume includes papers from the WSCMO conference in Braunschweig 2017 presenting research of all aspects of the optimal design of structures as well as multidisciplinary design optimization where the involved disciplines deal with the analysis of solids, fluids or other field problems. Also presented are practical applications of optimization methods and the corresponding software development in all branches of technology.
Pindex Conference proceedings 2018
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Multidisciplinary Design Optimization of Body Exterior Structuresy. In vehicle engineering the objective typically is to optimize weight while maintaining performance involving various load cases from multiple CAE attributes. The MDO process can be divided into three successive steps: (1) data generation entailing creation, submission and post-processing of vario
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Benchmarking Approaches for the Multidisciplinary Analysis of Complex Systems Using a Taylor Series-s–Seidel iteration, which consists in solving each discipline in a sequential manner, and repeating this sequence until convergence. This approach is easy to implement but often exhibits slow convergence rates or does not converge at all. An alternative is to use approaches based on Newton’s method
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Convergence Strategy for Parallel Solving of Analytical Target Cascading with Augmented Lagrangian Cets and responses among subsystems. Augmented Lagrangian relaxation with Alternating Direction method (AL-AD) has been widely used for the coordination process of both hierarchical ATC and non-hierarchical ATC, and theoretically guarantees convergence under the assumption that all subsystem problems
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Producing Smart Pareto Sets for Multi-objective Topology Optimisation Problemss usually involve several different objectives, most of which counteract each other. Therefore, designers typically seek a set of Pareto optimal solutions, a solution for which no other solution is better in all objectives, which capture the trade-off between these objectives. This set is known as a
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