1. Multi-performance reliability-based concept-detailed co-design of offshore structures using modified conjugate FR algorithm.
- Author
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Cui, Yupeng, Yu, Yang, Cheng, Siyuan, Wei, Mingxiu, Pan, Yu, and Dong, Zewei
- Subjects
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OFFSHORE structures , *PARTICIPATORY design , *CONTINUATION methods , *ALGORITHMS - Abstract
Engineering applications of topology optimization (TO) geared towards creating concept structures with superior properties are notoriously challenging. Multi-performance and uncertainty risks are essential considerations in the design of offshore structures. In this paper, a reliability-based multi-performance concept-detailed co-design (RBMPCD) framework is developed for the two-phase optimization of offshore structures. In the 1st phase, a multi-performance optimization (MPO) system consisting of the extended TO technique and the combination weighting strategy is utilized to perform the multi-objective TO study to capture the creative concept layout. The polynomial penalty model using the continuation method serves as a theory support for the 1st phase. In the 2nd phase, a decoupled reliability-based size optimization (RBSO) strategy is suggested to industrialize the concept pattern. The deterministic size optimization (DSO) cycles and inverse reliability analysis (RA) cycles are alternately run to conduct the reliability-based detailed design of offshore structures. A modified conjugate Fletcher-Reeves (MCFR) algorithm incorporating the classical function type criterion is presented to perform inverse RA under complex implicit probability constraints. A numerical example including a 3D T-beam, and an engineering application of a pillar deck are exploited to show the effectiveness and state-of-the-art of the RBMPCD framework. • A reliability-based multi-performance concept-detailed co-design framework is first developed. • New pillar deck is uncertainty-resistant, spatially rationalized, high-performance. • A modified conjugate Fletcher-Reeves (MCFR) algorithm is presented. • MCFR possesses advanced stability, robustness, accuracy, and efficiency. [ABSTRACT FROM AUTHOR]
- Published
- 2024
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