A multi-objective optimization method for uncertain structures based on nonlinear interval number programming method

Liu, Xin; Zhang, Zhiyong; Yin, Lairong

doi:10.1080/15397734.2016.1141365

Cited by 32 publications

(10 citation statements)

References 29 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

130

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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

130

View full text Add to dashboard Cite

show abstract

“…On I, we define the following operations. This definition of arithmetic of intervals has been discussed and used in many existing works such as [17,3,13,14,5,30]. This definition of arithmetic operations can also be used for the representation a = a C , a W .…”

Section: Preliminariesmentioning

confidence: 99%

Numerical solution of an obstacle problem with interval coefficients

Wang¹

2020

Numerical Algebra, Control &Amp; Optimization

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In this work we propose a novel numerical method for a finitedimensional optimization problem arising from the discretization of an infinitedimensional constrained optimization problem, called an obstacle problem, with interval coefficients. In this method, the two different ways of characterizing the optimal solutions, i.e., minimizing the mid-point and one end-point (the worst-case scenario) or the mid-point and the width of the objective interval, are formulated as a single constrained multi-objective minimization problem and the KKT conditions of the optimization problem defining the Pareto optimal solution to the multi-objective problem are of the form of a Linear Complementarity Problem (LCP) which is shown to have a unique solution. The LCP is the approximated by a non-linear equation using an interior penalty approach. We prove that the penalty equation is uniquely solvable and its solution converges to that of LCP as the penalty constant approaches to zero. Numerical results are presented to demonstrate the usefulness of the numerical method proposed.

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“…The weighted summation method is used widely in practical engineering for MDOP because of its comparability. [21][22][23][24][25][26] It should be noted that the value of objective satisfaction degree can be represented by weight coefficients.…”

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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A multi-objective optimization method for uncertain structures based on nonlinear interval number programming method

Cited by 32 publications

References 29 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

Numerical solution of an obstacle problem with interval coefficients

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

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