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1 – 10 of over 3000Yidu Zhang, Yongshou Liu and Qing Guo
This paper aims to develop a method for evaluating the failure probability and global sensitivity of multiple failure modes based on convex-probability hybrid uncertainty.
Abstract
Purpose
This paper aims to develop a method for evaluating the failure probability and global sensitivity of multiple failure modes based on convex-probability hybrid uncertainty.
Design/methodology/approach
The uncertainty information of the input variable is considered as convex-probability hybrid uncertainty. Moment-independent variable global sensitivity index based on the system failure probability is proposed to quantify the effect of the input variable on the system failure probability. Two-mode sensitivity indices are adopted to characterize the effect of each failure mode on the system failure probability. The method based on active learning Kriging (ALK) model with a truncated candidate regions (TCR) is adopted to evaluate the systems failure probability, as well as sensitivity index and this method is termed as ALK-TCR.
Findings
The results of five examples demonstrate the effectiveness of the sensitivity index and the efficiency of the ALK-TCR method in solving the problem of multiple failure modes based on the convex-probability hybrid uncertainty.
Originality/value
Convex-probability hybrid uncertainty is considered on system reliability analysis. Moment-independent variable sensitivity index based on the system failure probability is proposed. Mode sensitivity indices are extended to hybrid uncertain reliability model. An effective global sensitivity analysis approach is developed for the multiple failure modes based on convex-probability hybrid uncertainty.
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Yuzhen Zhao, Wei Liu, Qing Guo and Zijun Zhang
The purpose of this paper is to study the resonance failure sensitivity analysis of straight-tapered assembled pipe conveying nonuniform axial fluid by an active learning Kriging…
Abstract
Purpose
The purpose of this paper is to study the resonance failure sensitivity analysis of straight-tapered assembled pipe conveying nonuniform axial fluid by an active learning Kriging (ALK) method.
Design/methodology/approach
In this study, first, the motion equation of straight-tapered assembled pipe conveying nonuniform fluid is built. Second, the Galerkin method is used for calculating the natural frequency of assembled pipe conveying nonuniform fluid. Third, the ALK method based on expected risk function (ERF) is used to calculate the resonance failure probability and moment independent global sensitivity analysis.
Findings
The findings of this paper highlight that the eigenfrequency and critical velocity of uniform fluid-conveying pipe are less than the reality and the error is biggest in first-order natural frequency. The importance ranking of input variables affecting the resonance failure can be obtained. The importance ranking is different for a different velocity and mode number. By reducing the uncertainty of variables with a high index, the resonance failure probability can be reduced maximally.
Research limitations/implications
There are no experiments on the eigenfrequency and critical velocity. There is no experiments about natural frequency and critical velocity of straight tapered assembled pipe to verify the theory in this paper.
Originality/value
The originality of this paper lies as follows: the motion equation of straight-tapered pipe conveying nonuniform fluid is first obtained. The eigenfrequency of nonuniform fluid and uniform fluid inside the assembled pipe are compared. The resonance reliability analysis of straight-tapered assembled pipe is first proposed. From the results, it is observed that the resonance failure probability can be reduced efficiently.
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The paper attempts to establish the connection between structural reliability and structural optimization for the particular case of plastic structures. Along this line, the paper…
Abstract
The paper attempts to establish the connection between structural reliability and structural optimization for the particular case of plastic structures. Along this line, the paper outlines a reliability‐based optimization approach to design plastic structures with uncertain interdependent strengths and acted on by random interdependent loads. The importance of such interdependencies, and of some of the other statistical parameters used as input data in probabilistic computations, is demonstrated by several examples of sensitivity studies on both the probability of collapse failure as well as the reliability‐based optimum solution.
This paper aims to present a new method, named as augmented polynomial dimensional decomposition (PDD) method, for robust design optimization (RDO) and reliability-based design…
Abstract
Purpose
This paper aims to present a new method, named as augmented polynomial dimensional decomposition (PDD) method, for robust design optimization (RDO) and reliability-based design optimization (RBDO) subject to mixed design variables comprising both distributional and structural design variables.
Design/methodology/approach
The method involves a new augmented PDD of a high-dimensional stochastic response for statistical moments and reliability analyses; an integration of the augmented PDD, score functions, and finite-difference approximation for calculating the sensitivities of the first two moments and the failure probability with respect to distributional and structural design variables; and standard gradient-based optimization algorithms.
Findings
New closed-form formulae are presented for the design sensitivities of moments that are simultaneously determined along with the moments. A finite-difference approximation integrated with the embedded Monte Carlo simulation of the augmented PDD is put forward for design sensitivities of the failure probability.
Originality/value
In conjunction with the multi-point, single-step design process, the new method provides an efficient means to solve a general stochastic design problem entailing mixed design variables with a large design space. Numerical results, including a three-hole bracket design, indicate that the proposed methods provide accurate and computationally efficient sensitivity estimates and optimal solutions for RDO and RBDO problems.
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Gonçalo das Neves Carneiro and Carlos Conceição António
In the reliability assessment of composite laminate structures with multiple components, the uncertainty space defined around design solutions easily becomes over-dimensioned, and…
Abstract
Purpose
In the reliability assessment of composite laminate structures with multiple components, the uncertainty space defined around design solutions easily becomes over-dimensioned, and not all of the random variables are relevant. The purpose of this study is to implement the importance analysis theory of Sobol’ to reduce the dimension of the uncertainty space, improving the efficiency toward global convergence of evolutionary-based reliability assessment.
Design/methodology/approach
Sobol’ indices are formulated analytically for implicit structural response functions, following the theory of propagation of moments and without violating the fundamental principles presented by Sobol’. An evolutionary algorithm capable of global convergence in reliability assessment is instrumented with the Sobol’ indices. A threshold parameter is introduced to identify the important variables. A set of optimal designs of a multi-laminate composite structure is evaluated.
Findings
Importance analysis shows that uncertainty is concentrated in the laminate where the critical stress state is found. Still, it may also be reasonable in other points of the structure. An accurate and controlled reduction of the uncertainty space significantly improves the convergence rate, while maintaining the quality of the reliability assessment.
Practical implications
The theoretical developments assume independent random variables.
Originality/value
Applying Sobol’ indices as an analytical dimension reduction technique is a novelty. The proposed formulation only requires one adjoint system of equilibrium equations to be solved once. Although a local estimate of a global measure, this analytical formulation still holds because, in structural design, uncertainty is concentrated around the mean-values.
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G. Chiandussi, R. Fontana and F. Urbinati
A method to solve shape and size optimisation problems with linear and non‐linear responses has been studied taking advantage of statistical methodologies. A nested optimisation…
Abstract
A method to solve shape and size optimisation problems with linear and non‐linear responses has been studied taking advantage of statistical methodologies. A nested optimisation procedure has been fixed. The global optimisation problem is decomposed in several subproblems where each non‐linear response is locally approximated with a first degree polynomial function identified by the definition and execution of an experimental plan. The approximating functions so obtained are used to evaluate the design sensitivity coefficients required by the optimisation procedure. The numerical results obtained during the optimisation process to verify exactly the value of the non‐linear responses are used to verify and to improve the approximating function accuracy. The non‐linear design sensitivity analysis method so defined has been used to solve a multidisciplinary shape optimisation problem involving a real 3D automotive structure.
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Bingqian Chen, Anqiang Wang, Qing Guo, Jiayin Dai and Yongshou Liu
This paper aims to solve the problem that pipes conveying fluid are faced with severe reliability failures under the complicated working environment.
Abstract
Purpose
This paper aims to solve the problem that pipes conveying fluid are faced with severe reliability failures under the complicated working environment.
Design/methodology/approach
This paper proposes a dynamic reliability and variance-based global sensitivity analysis (GSA) strategy with non-probabilistic convex model for pipes conveying fluid based on the first passage principle failure mechanism. To illustrate the influence of input uncertainty on output uncertainty of non-probability, the main index and the total index of variance-based GSA analysis are used. Furthermore, considering the efficiency of traditional simulation method, an active learning Kriging surrogate model is introduced to estimate the dynamic reliability and GSA indices of the structure system under random vibration.
Findings
The variance-based GSA analysis can measure the effect of input variables of convex model on the dynamic reliability, which provides useful reference and guidance for the design and optimization of pipes conveying fluid. For designers, the rankings and values of main and total indices have essential guiding role in engineering practice.
Originality/value
The effectiveness of the proposed method to calculate the dynamic reliability and sensitivity of pipes conveying fluid while ensuring the calculation accuracy and efficiency in the meantime.
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Gulshan Singh, Miguel Cortina, Harry Millwater and Allan Clauer
The purpose of this paper is to estimate probabilistic and regional importance sensitivities of fatigue life, with respect to the laser peening (LP) parameters applied to a…
Abstract
Purpose
The purpose of this paper is to estimate probabilistic and regional importance sensitivities of fatigue life, with respect to the laser peening (LP) parameters applied to a Titanium turbine disk.
Design/methodology/approach
The sensitivities were calculated from Monte Carlo (MC) analysis of 21,000 simulations and probabilistic sensitivity methods.
Findings
The probabilistic sensitivity results indicate that the peak pressure and the mid‐span are the most important variables. The regional importance sensitivity results indicate that probability of failure is the most sensitive to the left tail of peak pressure and middle region of mid‐span and the fatigue life mean is the most sensitive to the left tails of the peak pressure and the mid‐span.
Practical implications
The sensitivity results of this research indicate that more time and energy should be focused on managing peak pressure and mid‐span, as compared to the remaining variables, to design and improve the laser peening process.
Originality/value
The paper presents four sensitivity analysis approaches which were formulated and employed to estimate fatigue life sensitivities with respect to the LP variables.
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Gives introductory remarks about chapter 1 of this group of 31 papers, from ISEF 1999 Proceedings, in the methodologies for field analysis, in the electromagnetic community…
Abstract
Gives introductory remarks about chapter 1 of this group of 31 papers, from ISEF 1999 Proceedings, in the methodologies for field analysis, in the electromagnetic community. Observes that computer package implementation theory contributes to clarification. Discusses the areas covered by some of the papers ‐ such as artificial intelligence using fuzzy logic. Includes applications such as permanent magnets and looks at eddy current problems. States the finite element method is currently the most popular method used for field computation. Closes by pointing out the amalgam of topics.
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