scholarly journals Performance of surrogate models in reliability-based design optimization

2014 ◽  
Author(s):  
M. Cid Montoya ◽  
J. Díaz ◽  
S. Hernández
Keyword(s):  
Design Optimization ◽  
Surrogate Models ◽  
Reliability Based Design Optimization ◽  
Reliability Based Design

Efficient Global Surrogate Modeling for Reliability-Based Design Optimization

2012 ◽  
Vol 135 (1) ◽  
Author(s):  
Barron J. Bichon ◽  
Michael S. Eldred ◽  
Sankaran Mahadevan ◽  
John M. McFarland
Keyword(s):  
Global Optimization ◽  
Design Optimization ◽  
Reliability Analysis ◽  
Optimization Problem ◽  
Wide Spectrum ◽  
Surrogate Models ◽  
Efficient Global Optimization ◽  
Test Problems ◽  
Reliability Based Design Optimization ◽  
Reliability Based Design

Determining the optimal (lightest, least expensive, etc.) design for an engineered component or system that meets or exceeds a specified level of reliability is a problem of obvious interest across a wide spectrum of engineering fields. Various formulations and methods for solving this reliability-based design optimization problem have been proposed, but they typically involve accepting a tradeoff between accuracy and efficiency in the reliability analysis. This paper investigates the use of the efficient global optimization and efficient global reliability analysis methods to construct surrogate models at both the design optimization and reliability analysis levels to create methods that are more efficient than existing methods without sacrificing accuracy. Several formulations are proposed and compared through a series of test problems.

Reliability Based Design Optimization Using a Single Constraint Approximation Point

2011 ◽  
Vol 133 (3) ◽  
Author(s):  
Tomas Dersjö ◽  
Mårten Olsson
Keyword(s):  
Design Optimization ◽  
Solid Mechanics ◽  
Surrogate Models ◽  
Computational Effort ◽  
Fe Model ◽  
Reliability Based Design Optimization ◽  
Reliability Based Design ◽  
Constrained Problems ◽  
Single Constraint ◽  
Starting Point

The computational effort for reliability based design optimization (RBDO) is no longer prohibitive even for detailed studies of mechanical integrity. The sequential approximation RBDO formulation and the use of surrogate models have greatly reduced the amount of computations necessary. In RBDO, the surrogate models need to be most accurate in the proximity of the most probable point. Thus, for multiply constrained problems, such as fatigue design problems, where each finite element (FE)-model node constitutes a constraint, the computational effort may still be considerable if separate experiments are used to fit each constraint surrogate model. This paper presents an RBDO algorithm that uses a single constraint approximation point (CAP) as a starting point for the experiments utilized to establish all surrogate models, thus reducing the computational effort to that of a single constraint problem. Examples of different complexities from solid mechanics applications are used to present the accuracy and versatility of the proposed method. In the studied examples, the ratio of the computational effort (in terms of FE-solver calls) between a conventional method and the single CAP algorithm was approximately equal to the number of constraints and the introduced error was small. Furthermore, the CAP-based RBDO is shown to be capable of handling over 10,000 constraints and even an intermittent remeshing. Also, the benefit of considering other objectives than volume (mass) is shown through a cost optimization of a truck component. In the optimization, fatigue-specific procedures, such as shot peening and machining to reduce surface roughness, are included in the cost as well as in the constraints.

scholarly journals Development of surrogate models in reliability-based design optimization: A review

2021 ◽  
Vol 18 (5) ◽  
pp. 6386-6409
Author(s):  
Xiaoke Li ◽  
◽  
Qingyu Yang ◽  
Yang Wang ◽  
Xinyu Han ◽  
...  
Keyword(s):  
Design Optimization ◽  
Reliability Analysis ◽  
Surrogate Models ◽  
Modeling Method ◽  
Reliability Based Design Optimization ◽  
Global Modeling ◽  
Advantages And Disadvantages ◽  
Modeling Methods ◽  
Reliability Based Design ◽  
Local Modeling

<abstract> <p>Reliability-based design optimization (RBDO) is applied to handle the unavoidable uncertainties in engineering applications. To alleviate the huge computational burden in reliability analysis and design optimization, surrogate models are introduced to replace the implicit objective and performance functions. In this paper, the commonly used surrogate modeling methods and surrogate-assisted RBDO methods are reviewed and discussed. First, the existing reliability analysis methods, RBDO methods, commonly used surrogate models in RBDO, sample selection methods and accuracy evaluation methods of surrogate models are summarized and compared. Then the surrogate-assisted RBDO methods are classified into global modeling methods and local modeling methods. A classic two-dimensional RBDO numerical example are used to demonstrate the performance of representative global modeling method (Constraint Boundary Sampling, CBS) and local modeling method (Local Adaptive Sampling, LAS). The advantages and disadvantages of these two kinds of modeling methods are summarized and compared. Finally, summary and prospect of the surrogate–assisted RBDO methods are drown.</p> </abstract>

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