Reliable design space and complete single-loop reliability-based design optimization

Shan, Songqing; Wang, G. Gary

doi:10.1016/j.ress.2007.07.006

Cited by 166 publications

(64 citation statements)

References 21 publications

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“…Although the single-loop methods are much more efficient than the two-level approaches, they can still be computationally challenging for real engineering problems involving many reliability constraints. Li et al (2013) proposed using reliable design space (RDS) (Shan and Wang 2008) to completely convert the RBDO problem to a deterministic optimization problem. The RDS is defined through sensitivities at the current design point, instead of the sensitivities at the MPP of each limit-state function.…”

Section: Introductionmentioning

confidence: 99%

A two-phase approach based on sequential approximation for reliability-based design optimization

Zhou

Zhifan

et al. 2018

Struct Multidisc Optim

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The original problem of reliability-based design optimization (RBDO) is mathematically a nested two-level structure that is computationally time consuming for real engineering problems. In order to overcome the computational difficulties, many formulations have been proposed in the literature. These include SORA (sequential optimization and reliability assessment) that decouples the nested problems. SLA (single loop approach) further improves efficiency in that reliability analysis becomes an integrated part of the optimization problem. However, even SLA method can become computationally challenging for real engineering problems involving many reliability constraints. This paper presents an enhanced version of SLA where the first phase is based on approximation at nominal design point. After convergence of first iterative phase is reached the process transitions to a second phase where approximations of reliability constraints are carried out at their respective minimum performance target point (MPTP). The solution is implemented in Altair OptiStruct, where adaptive approximation and constraint screening strategies are utilized in the RBDO process. Examples show that the proposed two-phase approach leads to reduction in finite element analyses while preserving equal solution quality.

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Section: Introductionmentioning

confidence: 99%

A two-phase approach based on sequential approximation for reliability-based design optimization

Zhou

Zhifan

et al. 2018

Struct Multidisc Optim

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“…This procedure is referred to as reliabilitybased design optimization (RBDO); in this case, the reliability index becomes an extra constraint to the optimization problem. According to [3], in the last decade, the RBDO significance and conceptual and mathematical complexity have been intensively studied. The optimization procedure may require a high computational cost [4].…”

Section: Introductionmentioning

confidence: 99%

“…The optimization procedure may require a high computational cost [4]. For this reason, several authors have studied methods that use single loop RBDO [3,[5][6][7]. These authors have applied reliability-based design optimization strategies like SAP (Sequential Approximate Programming) and SORA (Sequential Optimization and Reliability Assessment), which are capable of solving the majority of practical cases, when multiple modes of failure are present, but for linear and smooth functions.…”

Section: Introductionmentioning

confidence: 99%

A Hybrid Method for Truss Mass Minimization considering Uncertainties

Gomes

Corso

2017

Mathematical Problems in Engineering

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In real-world structural problems, a number of factors may cause geometric imperfections, load variability, or even uncertainties in material properties. Therefore, a deterministic optimization procedure may fail to account such uncertainties present in the actual system leading to optimum designs that are not reliable; the designed system may show excessive safety or sometimes not sufficient reliability to carry applied load due to uncertainties. In this paper, we introduce a hybrid reliability-based design optimization (RBDO) algorithm based on the genetic operations of Genetic Algorithm, the position and velocity update of the Particle Swarm Algorithm (for global exploration), and the sequential quadratic programming, for local search. The First-Order Reliability Method is used to account uncertainty in design and parameter variables and to evaluate the associated reliability. The hybrid method is analyzed based on RBDO benchmark examples that range from simple to complex truss parametric sizing optimizations with stress, displacements, and frequency deterministic and probabilistic constraints. The proposed final problem, which cannot be handled by single loop RBDO algorithms, highlights the importance of the proposed approach in cases where the discrete design variables are also random variables.

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“…Double-loop methods are time consuming because it involves a two-level optimization structure, where the outer optimization loop is applied to calculate the iteration design variables and the inner loop is applied to calculate the failure probability or MPP [29]. Single-loop methods [4,22] have only one optimization loop because the reliability analysis loop is approximated by its Karush-Kuhn-Tucker (KKT) optimality conditions. Decoupledloop methods [6,12,13] separate the reliability analysis loop from the design optimization loop, then the RBDO problem is converted into a sequence of deterministic optimization problems.…”

Section: Introductionmentioning

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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Reliable design space and complete single-loop reliability-based design optimization

Cited by 166 publications

References 21 publications

A two-phase approach based on sequential approximation for reliability-based design optimization

A two-phase approach based on sequential approximation for reliability-based design optimization

A Hybrid Method for Truss Mass Minimization considering Uncertainties

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

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