A comparative study on reliability-index and target-performance-based probabilistic structural design optimization

Lee, Jae-Ohk; Yang, YoungSoon; Ruy, Won-Sun

doi:10.1016/s0045-7949(02)00006-8

Cited by 210 publications

(81 citation statements)

References 6 publications

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“…However, reliability index approach (RIA) has been demonstrated to be inefficient and unstable by many researches [15]. Therefore, a new scheme based on arc search in PMA+ and linear interpolation is proposed in this paper to determine the optimal radius of RBIS.…”

Section: Determination Of Optimal Radius Of Rbismentioning

confidence: 99%

An Efficient Moving Optimal Radial Sampling Method for Reliability-Based Design Optimization

Li¹

2017

IJPE

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Reliability-based design optimization (RBDO) plays an essential role in structure and system design. However, its application in practical engineering is hindered by the huge computational cost in performance function evaluation. In this paper, a moving optimal radial sampling (MORS) method is proposed for RBDO problems to substantially improve the computational efficiency of Monte Carlo simulation (MCS). In MORS, the failure probability and its gradient are calculated using radius based importance sampling (RBIS) method. The initial radius is selected according to the target reliability, which can also be used to check the feasibility of probabilistic constraints afterwards. The arc search scheme in enhanced performance measure approach (PMA+) and linear interpolation scheme are used to calculate the optimal radius of RBIS. After the failure probability and its gradient are calculated, the optimal design is obtained using sequential approximation programming (SAP). The computational capability of the proposed MORS method is demonstrated using a honeycomb crashworthiness design application, a nonlinear mathematical problem and a speed reducer design. The comparison results show that the proposed MORS-SAP method is very efficient and accurate.

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Section: Determination Of Optimal Radius Of Rbismentioning

confidence: 99%

An Efficient Moving Optimal Radial Sampling Method for Reliability-Based Design Optimization

Li¹

2017

IJPE

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“…As such, the methods described above are used within the classical techniques that address such problems, including double-loop approaches [79] (consisting of a design optimization loop which repeatedly calls a reliability analysis method in a series of inner loops). The computational effort of such approaches may be prohibitive in some cases and other alternatives were proposed.…”

Section: Classical Techniquesmentioning

confidence: 99%

Probabilistic constraint reasoning

Carvalho¹

2015

Constraints

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perpétuo e sem limites geográficos, de arquivar e publicar esta dissertação através de exemplares impressos reproduzidos em papel ou de forma digital, ou por qualquer outro meio conhecido ou que venha a ser inventado, e de a divulgar através de repositórios científicos e de admitir a sua cópia e distribuição com objectivos educacionais ou de investigação, não comerciais, desde que seja dado crédito ao autor e editor.For Laura with love.My endless source of inspiration with her tender heart and ingenious mind. AcknowledgementsFor me, writing this thesis was like a long, long journey, with many ups and downs. In every step of the way I faced challenges that made me grow as a researcher and as a person. But the journey is coming to an end and is now time to remember and be grateful to those who crossed my path and helped me to achieve my goal in many different ways. Neste trabalho desenvolvemos um paradigma de restrições em domínios contínuos que associa um espaço probabilísticoàs variáveis do problema, permitindo efectuar raciocínio probabilístico. Tal raciocínio baseia-se na avaliação de informação probabilística que requer a computação de integrais multidimensionais em regiões possivelmente não lineares. São desenvolvidos algoritmos capazes de avaliar essa informação, usando técnicas de integração seguras ou aproximadas e dependendo de métodos de programação por restrições em domínios contínuos para obter coberturas da região de integração.A plataforma probabilística de restrições em domínios contínuosé adequada para suporteà decisão em problemas não lineares em domínios contínuos, com incerteza. A sua aplicabilidadeé ilustrada em problemas inversos e problemas de fiabilidade, que são duas classes distintas de problemas de engenharia, representativas do tipo de raciocínio com incerteza requerido pelos decisores.

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“…, although reaching the same conclusions, showed that the PMA is far more effective when the probabilistic constraint is either very feasible or very infeasible. In a different paper, Youn and Choi (2004a) concluded that the PMA is quite attractive when compared to other probabilistic approaches in RBDO, such as the RIA and the approximate moment approach (Lee et al, 2002).…”

Section: Ria Versus Pmamentioning

confidence: 99%

“…sphere; in other words, the number of iterations of RIA increases with the reliability index while the PMA search is independent of the target performance (Lee et al, 2002). A second consequence is that, in the case of non-activated constraints, the PMA becomes even more effective.…”

Section: Ria Versus Pmamentioning

confidence: 99%