Hybrid reliability-based multidisciplinary design optimization with random and interval variables

Yang, Fan; Yue, Zhufeng; Li, Lei; Guan, Dong

doi:10.1177/1748006x17736639

Cited by 5 publications

(4 citation statements)

References 51 publications

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“…Zaman 34 expressed the interval uncertainty with Johnson's distribution, and performed the MRA employing random probabilistic methods. Du 35,36 and Yang 37 studied the MRA in the situation that both random and interval variables coexists, and proposed to measure the reliability with the worst-case reliability index within the interval range. The above researches transform the interval uncertainty into a random uncertainty problem and thus use the random probabilistic method to evaluate the reliability.…”

Section: 13mentioning

confidence: 99%

Interval uncertainty‐based multidisciplinary reliability analysis method for information‐poor complex system

Fang

Tang

Zhang

et al. 2022

Numerical Meth Engineering

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Due to integrated structures and multiple functions, complex systems, such as large-scale equipment and aerospace vehicle, faced prominent reliability problems. However, in real-world applications, collecting sufficient reliability data is costly and time-consuming. To overcome this difficulty, the information-poor variables are modeled with interval models and the corresponding reliability analysis method for complex system is studied in this paper. First, we establish a multidisciplinary nonprobabilistic reliability model based on interval analysis, which is an optimization framework with an objective of nonprobabilistic reliability index and two constraints of interdisciplinary consistency equation and limit state equation. Second, two types of algorithms for the above model are studied. Based on typical methods of multidisciplinary design optimization (MDO), the direct algorithms including RA-MDF and RA-IDF are developed.Then, a decoupled reliability analysis algorithm is proposed to realize parallel multidisciplinary reliability analysis, in which two methods of multidisciplinary interval uncertainty analysis are formulated to decouple the coupling relationship between disciplines. Finally, three examples are employed to illustrate the validity and efficiency of the proposed methods.

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Section: 13mentioning

confidence: 99%

Interval uncertainty‐based multidisciplinary reliability analysis method for information‐poor complex system

Fang

Tang

Zhang

et al. 2022

Numerical Meth Engineering

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“…For example, in fluid structure thermal coupling analysis, the pressure values from fluid analysis should be transferred to the structure discipline for finite element analysis. e conventional structure of EBMDO contains a triple loop, as shown in Figure 1 [36,37].…”

Section: Ebmdomentioning

confidence: 99%

Evidence‐Based Multidisciplinary Design Optimization with the Active Global Kriging Model

Yang

Liu

et al. 2019

Complexity

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This article presents an approach that combines the active global Kriging method and multidisciplinary strategy to investigate the problem of evidence-based multidisciplinary design optimization. The global Kriging model is constructed by introducing a so-called learning function and using actively selected samples in the entire optimization space. With the Kriging model, the plausibility, Pl, of failure is obtained with evidence theory. The multidisciplinary feasible and collaborative optimization strategies of multidisciplinary design optimization are combined with the evidence-based reliability analysis. Numerical examples are provided to illustrate the efficiency and accuracy of the proposed method. The numerical results show that the proposed algorithm is effective and valuable, which is valuable in engineering application.

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“…They used the Single-Level Strategy (SLS) idea to design a single-loop RBMDO architecture. Yang et al 31 considered random and interval-based variables in RBMDO and recommended Kriging and MCS to find the optimum design. Applying IDF MDO architecture, Huang et al 32 tried to convert the RBMDO problem into several RBDO subproblems using an incremental shifting vector to solve the resulting RBDO subproblems.…”

Section: Introductionmentioning

confidence: 99%

Reliability-based multidisciplinary design optimization of an aeroelastic unpowered guided aerial vehicle

Pourtakdoust,

Khodabakhsh

2023

Proceedings of the Institution of Mechanical Engineers, Part G:

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Most Aeronautical and Astronautical Systems (AAS) are inherently complex, multidisciplinary, nonlinear, and computationally intensive for design and analysis. Utilizing the Reliability-Based Multidisciplinary Design Optimization framework can address the multidisciplinary nature of these systems while accounting for inherent uncertainties. In this paper, an efficient methodology for Reliability-Based Multidisciplinary Design optimization of an aerial vehicle is developed. The computational burden of reliability assessment could make its integration within a Multidisciplinary Design Optimization cycle a formidable task. In this respect, a multilevel Multidisciplinary Design Optimization architecture is proposed in which the computational cost is reduced by considering the reliability analysis, as needed only for critical subsystems. To this end, a single-level Reliability-Based Multidisciplinary Design Optimization is derived using the Performance Measure Analysis and the Karush-Kuhn-Tucker condition. The work demonstrates the integration of this formulation into the proposed multilevel Reliability-Based Multidisciplinary Design Optimization architecture. The proposed design architecture is implemented for an aeroelastic Unpowered Guided Aerial Vehicle whose outcomes are compared with previous results obtained via a mono-level Uncertainty-Based Multidisciplinary Design Optimization architecture.

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Hybrid reliability-based multidisciplinary design optimization with random and interval variables

Cited by 5 publications

References 51 publications

Interval uncertainty‐based multidisciplinary reliability analysis method for information‐poor complex system

Interval uncertainty‐based multidisciplinary reliability analysis method for information‐poor complex system

Evidence‐Based Multidisciplinary Design Optimization with the Active Global Kriging Model

Reliability-based multidisciplinary design optimization of an aeroelastic unpowered guided aerial vehicle

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