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Article
Publication date: 22 June 2012

ZhiQun Liu, YiShang Zhang and WenBo Wang

The purpose of this paper is to optimize the key dimensions parameters of the missile suspension structure to ensure the structural fatigue life (>10000 cycles) with the…

Abstract

Purpose

The purpose of this paper is to optimize the key dimensions parameters of the missile suspension structure to ensure the structural fatigue life (>10000 cycles) with the reliability of 0.995.

Design/methodology/approach

The design objective is the fatigue life reliability of the structure, while the design variables are the four fatigue‐sensitive dimensions. The nominal stress approach is introduced to predict the fatigue life, and it was verified by comparing with experimental data. The second respond surface method is applied to solve the reliability in a finite element‐supported analysis using software MSC Patran/Nastran. A Sequential quadratic programming (SQP) algorithm is used for structure optimization.

Findings

The fillet radius r is the most important factor that influences the fatigue life reliability of the structure. The four optimal dimensions parameters are obtained by a reliability‐based design optimization process with the fatigue life and reliability fulfilling the demands.

Originality/value

The optimal result can be used as the design values for missile suspension structure. The feasibility of the reliability‐based design optimization method is validated for the design of missile suspension structure.

Article
Publication date: 16 April 2018

Naser Safaeian Hamzehkolaei, Mahmoud Miri and Mohsen Rashki

Reliability-based design optimizations (RBDOs) of engineering structures involve complex non-linear/non-differentiable performance functions, including both continuous and…

Abstract

Purpose

Reliability-based design optimizations (RBDOs) of engineering structures involve complex non-linear/non-differentiable performance functions, including both continuous and discrete variables. The gradient-based RBDO algorithms are less than satisfactory for these cases. The simulation-based approaches could also be computationally inefficient, especially when the double-loop strategy is used. This paper aims to present a pseudo-double loop flexible RBDO, which is efficient for solving problems, including both discrete/continuous variables.

Design/methodology/approach

The method is based on the hybrid improved binary bat algorithm (BBA) and weighed simulation method (WSM). According to this method, each BBA’s movement generates proper candidate solutions, and subsequently, WSM evaluates the reliability levels for design candidates to conduct swarm in a low-cost safe-region.

Findings

The accuracy of the proposed enhanced BBA and also the hybrid WSM-BBA are examined for ten benchmark deterministic optimizations and also four RBDO problems of truss structures, respectively. The solved examples reveal computational efficiency and superiority of the method to conventional RBDO approaches for solving complex problems including discrete variables.

Originality/value

Unlike other RBDO approaches, the proposed method is such organized that only one simulation run suffices during the optimization process. The flexibility future of the proposed RBDO framework enables a designer to present multi-level design solutions for different arrangements of the problem by using the results of the only one simulation for WSM, which is very helpful to decrease computational burden of the RBDO. In addition, a new suitable transfer function that enhanced convergence rate and search ability of the original BBA is introduced.

Article
Publication date: 18 October 2018

Lei Wang, Haijun Xia, Yaowen Yang, Yiru Cai and Zhiping Qiu

The purpose of this paper is to propose a novel non-probabilistic reliability-based topology optimization (NRBTO) method for continuum structural design under interval…

Abstract

Purpose

The purpose of this paper is to propose a novel non-probabilistic reliability-based topology optimization (NRBTO) method for continuum structural design under interval uncertainties of load and material parameters based on the technology of 3D printing or additive manufacturing.

Design/methodology/approach

First, the uncertainty quantification analysis is accomplished by interval Taylor extension to determine boundary rules of concerned displacement responses. Based on the interval interference theory, a novel reliability index, named as the optimization feature distance, is then introduced to construct non-probabilistic reliability constraints. To circumvent convergence difficulties in solving large-scale variable optimization problems, the gradient-based method of moving asymptotes is also used, in which the sensitivity expressions of the present reliability measurements with respect to design variables are deduced by combination of the adjoint vector scheme and interval mathematics.

Findings

The main findings of this paper should lie in that new non-probabilistic reliability index, i.e. the optimization feature distance which is defined and further incorporated in continuum topology optimization issues. Besides, a novel concurrent design strategy under consideration of macro-micro integration is presented by using the developed RBTO methodology.

Originality/value

Uncertainty propagation analysis based on the interval Taylor extension method is conducted. Novel reliability index of the optimization feature distance is defined. Expressions of the adjoint vectors between interval bounds of displacement responses and the relative density are deduced. New NRBTO method subjected to continuum structures is developed and further solved by MMA algorithms.

Article
Publication date: 1 January 2014

Ziyan Ren, Dianhai Zhang and Chang Seop Koh

The purpose of this paper is to propose a multi-objective optimization algorithm, which can improve both the performance robustness and the constraint feasibility when the…

Abstract

Purpose

The purpose of this paper is to propose a multi-objective optimization algorithm, which can improve both the performance robustness and the constraint feasibility when the uncertainty in design variables is considered.

Design/methodology/approach

Multi-objective robust optimization by gradient index combined with the reliability-based design optimization (RBDO).

Findings

It is shown that searching for the optimal design of the TEAM problem 22, which can minimize the magnetic stray field by keeping the target system energy (180 MJ) and improve the feasibility of superconductivity constraint (quenching condition), is possible by using the proposed method.

Originality/value

RBDO method applied to the electromagnetic problem cooperated with the design sensitivity analysis by the finite element method.

Details

COMPEL: The International Journal for Computation and Mathematics in Electrical and Electronic Engineering, vol. 33 no. 1/2
Type: Research Article
ISSN: 0332-1649

Keywords

Article
Publication date: 14 August 2020

Sadik Lafta Omairey, Peter Donald Dunning and Srinivas Sriramula

The purpose of this study is to enable performing reliability-based design optimisation (RBDO) for a composite component while accounting for several multi-scale…

Abstract

Purpose

The purpose of this study is to enable performing reliability-based design optimisation (RBDO) for a composite component while accounting for several multi-scale uncertainties using a large representative volume element (LRVE). This is achieved using an efficient finite element analysis (FEA)-based multi-scale reliability framework and sequential optimisation strategy.

Design/methodology/approach

An efficient FEA-based multi-scale reliability framework used in this study is extended and combined with a proposed sequential optimisation strategy to produce an efficient, flexible and accurate RBDO framework for fibre-reinforced composite laminate components. The proposed RBDO strategy is demonstrated by finding the optimum design solution for a composite component under the effect of multi-scale uncertainties while meeting a specific stiffness reliability requirement. Performing this using the double-loop approach is computationally expensive because of the number of uncertainties and function evaluations required to assess the reliability. Thus, a sequential optimisation concept is proposed, which starts by finding a deterministic optimum solution, then assesses the reliability and shifts the constraint limit to a safer region. This is repeated until the desired level of reliability is reached. This is followed by a final probabilistic optimisation to reduce the mass further and meet the desired level of stiffness reliability. In addition, the proposed framework uses several surrogate models to replace expensive FE function evaluations during optimisation and reliability analysis. The numerical example is also used to investigate the effect of using different sizes of LRVEs, compared with a single RVE. In future work, other problem-dependent surrogates such as Kriging will be used to allow predicting lower probability of failures with high accuracy.

Findings

The integration of the developed multi-scale reliability framework with the sequential RBDO optimisation strategy is proven computationally feasible, and it is shown that the use of LRVEs leads to less conservative designs compared with the use of single RVE, i.e. up to 3.5% weight reduction in the case of the 1 × 1 RVE optimised component. This is because the LRVE provides a representation of the spatial variability of uncertainties in a composite material while capturing a wider range of uncertainties at each iteration.

Originality/value

Fibre-reinforced composite laminate components designed using reliability and optimisation have been investigated before. Still, they have not previously been combined in a comprehensive multi-scale RBDO. Therefore, this study combines the probabilistic framework with an optimisation strategy to perform multi-scale RBDO and demonstrates its feasibility and efficiency for an fibre reinforced polymer component design.

Details

Engineering Computations, vol. 38 no. 3
Type: Research Article
ISSN: 0264-4401

Keywords

Article
Publication date: 1 September 2004

Jenam Kang, Chwail Kim and Semyung Wang

This paper presents a probabilistic optimal design for electromagnetic systems. A 2D magnetostatic finite element model is constructed for a reliability‐based topology…

Abstract

This paper presents a probabilistic optimal design for electromagnetic systems. A 2D magnetostatic finite element model is constructed for a reliability‐based topology optimization (RBTO). Permeability, coercive force, and applied current density are considered as uncertain variables. The uncertain variable means that the variable has a variance on a certain design point. In order to compute reliability constraints, a performance measure approach is widely used. To find reliability index easily, the limit‐state function is linearly approximated at each iteration. This approximation method is called the first‐order reliability method, which is widely used in reliability‐based design optimizations. To show the effectiveness of the proposed method, RBTO for the electromagnetic systems is applied to magnetostatic problems.

Details

COMPEL - The international journal for computation and mathematics in electrical and electronic engineering, vol. 23 no. 3
Type: Research Article
ISSN: 0332-1649

Keywords

Article
Publication date: 6 July 2015

Hyeong-Uk Park, Jae-Woo Lee, Joon Chung and Kamran Behdinan

The purpose of this paper is to study the consideration of uncertainty from analysis modules for aircraft conceptual design by implementing uncertainty-based design

Abstract

Purpose

The purpose of this paper is to study the consideration of uncertainty from analysis modules for aircraft conceptual design by implementing uncertainty-based design optimization methods. Reliability-Based Design Optimization (RBDO), Possibility-Based Design Optimization (PBDO) and Robust Design Optimization (RDO) methods were developed to handle uncertainties of design optimization. The RBDO method is found suitable for uncertain parameters when sufficient information is available. On the other hand, the PBDO method is proposed when uncertain parameters have insufficient information. The RDO method can apply to both cases. The RBDO, PBDO and RDO methods were considered with the Multidisciplinary Design Optimization (MDO) method to generate conservative design results when low fidelity analysis tools are used.

Design/methodology/approach

Methods combining MDO with RBDO, PBDO and RDO were developed and have been applied to a numerical analysis and an aircraft conceptual design. This research evaluates and compares the characteristics of each method in both cases.

Findings

The RBDO result can be improved when the amount of data concerning uncertain parameters is increased. Conversely, increasing information regarding uncertain parameters does not improve the PBDO result. The PBDO provides a conservative result when less information about uncertain parameters is available.

Research limitations/implications

The formulation of RDO is more complex than other methods. If the uncertainty information is increased in aircraft conceptual design case, the accuracy of RBDO will be enhanced.

Practical implications

This research increases the probability of a feasible design when it considers the uncertainty. This result gives more practical optimization results on a conceptual design level for fabrication.

Originality/value

It is RBDO, PBDO and RDO methods combined with MDO that satisfy the target probability when the uncertainties of low fidelity analysis models are considered.

Article
Publication date: 15 June 2022

Kaixuan Feng and Zhenzhou Lu

This study aims to propose an efficient method for solving reliability-based design optimization (RBDO) problems.

Abstract

Purpose

This study aims to propose an efficient method for solving reliability-based design optimization (RBDO) problems.

Design/methodology/approach

In the proposed algorithm, genetic algorithm (GA) is employed to search the global optimal solution of design parameters satisfying the reliability and deterministic constraints. The Kriging model based on U learning function is used as a classification tool to accurately and efficiently judge whether an individual solution in GA belongs to feasible region.

Findings

Compared with existing methods, the proposed method has two major advantages. The first one is that the GA is employed to construct the optimization framework, which is helpful to search the global optimum solutions of the RBDO problems. The other one is that the use of Kriging model is helpful to improve the computational efficiency in solving the RBDO problems.

Originality/value

Since the boundaries are concerned in two Kriging models, the size of the training set for constructing the convergent Kriging model is small, and the corresponding efficiency is high.

Details

Multidiscipline Modeling in Materials and Structures, vol. 18 no. 4
Type: Research Article
ISSN: 1573-6105

Keywords

Article
Publication date: 5 March 2018

Siyang Deng, Stéphane Brisset and Stephane Clénet

This paper compares six reliability-based design optimization (RBDO) approaches dealing with uncertainties for a simple mathematical model and a multidisciplinary…

Abstract

Purpose

This paper compares six reliability-based design optimization (RBDO) approaches dealing with uncertainties for a simple mathematical model and a multidisciplinary optimization problem of a safety transformer to highlight the most effective.

Design/methodology/approach

The RBDO and various approaches to calculate the probability of failure are is presented. They are compared in terms of precision and number of evaluations on mathematical and electromagnetic design problems.

Findings

The mathematical example shows that the six RBDO approaches have almost the same results except the approximate moment approach that is less accurate. The optimization of the safety transformer highlights that not all the methods can converge to the global solution. Performance measure approach, single-loop approach and sequential optimization and reliability assessment (SORA) method appear to be more stable. Considering both numerical examples, SORA is the most effective method among all RBDO approaches.

Originality/value

The comparison of six RBDO methods on the optimization problem of a safety transformer is achieved for the first time. The comparison in terms of precision and number of evaluations highlights the most effective ones.

Details

COMPEL - The international journal for computation and mathematics in electrical and electronic engineering, vol. 37 no. 2
Type: Research Article
ISSN: 0332-1649

Keywords

Article
Publication date: 3 June 2021

Shuai Li, Zhencai Zhu, Hao Lu and Gang Shen

This paper aims to present a dynamic reliability model of scraper chains based on the fretting wear process and propose a reasonable structural optimization method.

Abstract

Purpose

This paper aims to present a dynamic reliability model of scraper chains based on the fretting wear process and propose a reasonable structural optimization method.

Design/methodology/approach

First, the dynamic tension of the scraper chain is modeled by considering the polygon effect of the scraper conveyor. Then, the numerical wear model of the scraper chain is established based on the tangential and radial fretting wear modes. The scraper chain wear process is introduced based on the diameter wear rate. Furthermore, the time-dependent reliability of scraper chains based on the fretting wear process is addressed by the third-moment saddlepoint approximation (TMSA) method. Finally, the scraper chain is optimized based on the reliability optimization design theory.

Findings

There is a correlation between the wear and the dynamic tension of the scraper conveyor. The unit sliding distance of fretting wear is affected by the dynamic tension of the scraper conveyor. The reliability estimation of the scraper chain with incomplete probability information is achieved by using the TMSA for the method needs only the first three statistical moments of the state variable. From the perspective of the chain drive system, the reliability-based optimal design of the scraper chain can effectively extend its service life and reduce its linear density.

Originality/value

The innovation of the work is that the physical model of the scraper chain wear is established based on the dynamic analysis of the scraper conveyor. And based on the physical model of wear, the time-dependent reliability and optimal design of scraper chains are carried out.

Details

Engineering Computations, vol. 38 no. 10
Type: Research Article
ISSN: 0264-4401

Keywords

1 – 10 of 349