An efficient reliability analysis approach for structure based on probability and probability box models

Liu, Xin; Yin, Lairong; Hu, Lin; Zhang, Zhiyong

doi:10.1007/s00158-017-1659-7

Cited by 34 publications

(15 citation statements)

References 40 publications

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“…[46][47][48][49][50][51][52] This process can affect the reliability of equipment performance or even result in the failure of works. 12,[53][54][55][56][57][58][59][60][61] To enhance safety, many different uncertainty analysis and reliability evaluation approaches were proposed and developed in the past decades. In general, three types of these approaches are usually been utilized.…”

Section: Simulation or Approximation Reliability Methodsmentioning

confidence: 99%

“…In practical engineering, uncertainties exist widely and are transported in multidisciplinary systems . This process can affect the reliability of equipment performance or even result in the failure of works . To enhance safety, many different uncertainty analysis and reliability evaluation approaches were proposed and developed in the past decades.…”

Section: The Saddlepoint Approximation Analysis Methods and The Formulmentioning

confidence: 99%

See 1 more Smart Citation

Structural reliability analysis and uncertainties‐based collaborative design and optimization of turbine blades using surrogate model

Meng

Yang

Zhang³

et al. 2018

Fatigue Fract Eng Mat Struct

136

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In power and energy systems, both the aerodynamic performance and the structure reliability of turbine equipment are affected by utilized blades. In general, the design process of blade is high dimensional and nonlinear. Different coupled disciplines are also involved during this process. Moreover, unavoidable uncertainties are transported and accumulated between these coupled disciplines, which may cause turbine equipment to be unsafe. In this study, a saddlepoint approximation reliability analysis method is introduced and combined with collaborative optimization method to address the above challenge. During the above reliability analysis and design optimization process, surrogate models are utilized to alleviate the computational burden for uncertainties‐based multidisciplinary design and optimization problems. Smooth response surfaces of the performance of turbine blades are constructed instead of expensively time‐consuming simulations. A turbine blade design problem is solved here to validate the effectiveness and show the utilization of the given approach.

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Section: Simulation or Approximation Reliability Methodsmentioning

confidence: 99%

Section: The Saddlepoint Approximation Analysis Methods and The Formulmentioning

confidence: 99%

Structural reliability analysis and uncertainties‐based collaborative design and optimization of turbine blades using surrogate model

Meng

Yang

Zhang³

et al. 2018

Fatigue Fract Eng Mat Struct

136

View full text Add to dashboard Cite

show abstract

“…Due to the influence of uncertainty in engineering, the reliability of products could not reach a higher standard 21 . Therefore, more and more uncertain design methods 12,22 are studied and applied in industry, government and academia. There are generally two kinds of uncertainties in engineering according to the classification of experimental data 23,24 .…”

Section: Introductionmentioning

confidence: 99%

Reliability analysis of excavator boom considering mixed uncertain variables

Zhang

Liu

et al. 2020

Quality & Reliability Eng

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There are differences among sampling data and representation types of uncertain interval, fuzzy and random variables, which increases the complexity of structure reliability analysis. A α, β‐Cut‐FORM is proposed to analyze structure reliability considering the mixed uncertain variables. Fuzzy variables are optimized on the interval under two cut sets (α, β) based on the theory of cut set optimization. Interval variables are modeled with probability using a uniformity method. The proposed method involves the nested probabilistic analysis and interval analysis. The first‐order reliability method (FORM) is used for probabilistic analysis and nonlinear optimization is used for interval analysis. The excavator boom performance function is established for reliability analysis considering the mixed uncertain input variables, which verifies the effectiveness and advantages of the proposed method. And it has great application for safe and reliable design of excavator boom.

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“…In practical engineering, it is not easy to get the theoretically optimal design results for MDOPs. [1][2][3][4][5] Consequently, the satisfactory results are selected, rather than the theoretically optimal ones. There are many approaches have been given to solve MDOPs using the satisficing theory.…”

Section: Introductionmentioning

confidence: 99%

An enhanced genetic algorithm–based multi-objective design optimization strategy

Yuan

Wang

2018

Advances in Mechanical Engineering

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In this study, an enhanced genetic algorithm is proposed to solve multi-objective design and optimization problems in practical engineering. In the given approach, designers choose available design results from the given samples first. These samples are reordered according to their mutual relationships. After that, designers choose an exact ratio of conformity as available field. Furthermore, more weight information can be obtained through finding the minimum value of the norm of unconformity and satisfactory samples. These samples can be used to reflect the preference chosen for Pareto design solutions. A structure design problem of speed increaser used in wind turbine generator systems is solved to show the application of the given design strategy.

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An efficient reliability analysis approach for structure based on probability and probability box models

Cited by 34 publications

References 40 publications

Structural reliability analysis and uncertainties‐based collaborative design and optimization of turbine blades using surrogate model

Structural reliability analysis and uncertainties‐based collaborative design and optimization of turbine blades using surrogate model

Reliability analysis of excavator boom considering mixed uncertain variables

An enhanced genetic algorithm–based multi-objective design optimization strategy

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