Double-Loop Optimization and Soft Computing Based Inverse Analysis Approaches for Performing Reliability-based Design

2015 ◽  
Author(s):  
D. Lehký ◽  
O. Slowik ◽  
D. Novák
Keyword(s):  
Soft Computing ◽  
Inverse Analysis ◽  
Double Loop ◽  
Loop Optimization ◽  
Reliability Based Design

An improved binary bat flexible sampling algorithm for reliability-based design optimization of truss structures with discrete-continuous variables

2018 ◽  
Vol 35 (2) ◽  
pp. 641-671
Author(s):  
Naser Safaeian Hamzehkolaei ◽  
Mahmoud Miri ◽  
Mohsen Rashki
Keyword(s):  
Low Cost ◽  
Bat Algorithm ◽  
Truss Structures ◽  
Double Loop ◽  
Continuous Variables ◽  
Discrete Variables ◽  
Engineering Structures ◽  
Content Type ◽  
Reliability Based Design ◽  
Continuous And Discrete Variables

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.

Braess paradox and double-loop optimization method to enhance power grid resilience

2021 ◽  
pp. 107913
Author(s):  
Xi Zhang ◽  
Haicheng Tu ◽  
Jianbo Guo ◽  
Shicong Ma ◽  
Zhen Li ◽  
...  
Keyword(s):  
Power Grid ◽  
Optimization Method ◽  
Double Loop ◽  
Braess Paradox ◽  
Loop Optimization

Reliability Design of Footings in Cohesionless Soils using Soft Computing Metamodelings

2016 ◽  
pp. 442-464
Author(s):  
Anthony T. C. Goh ◽  
Wengang Zhang
Keyword(s):  
Bearing Capacity ◽  
Soft Computing ◽  
Model Building ◽  
Limit State ◽  
Multivariate Adaptive Regression Splines ◽  
Ultimate Limit State ◽  
Cohesionless Soils ◽  
Reliability Design ◽  
Reliability Based Design ◽  
Adaptive Regression Splines

An extensive database of full-scale field load tests was used to build predictive models to determine the bearing capacity of footings under axial compression in cohesionless soils. Based on this database, soft computing techniques, i.e., the multivariate adaptive regression splines (MARS) and artificial neural networks (ANN) are adopted for comparison for surrogate model building on bearing capacity. The performances of the two computing techniques are compared. A reliability-based design of footings was then presented. It allows one to obtain the probability that the ultimate limit state was exceeded for a given soil variability.

Reliable Space Pursuing for RBDO With Black-Box Performance Functions

2007 ◽  
Author(s):  
S. Shan ◽  
G. Gary Wang
Keyword(s):  
Design Space ◽  
Reliability Assessment ◽  
Black Box ◽  
Double Loop ◽  
High Current ◽  
Reliability Based Design Optimization ◽  
Reliability Based Design ◽  
Reliable Design ◽  
Loop Procedure ◽  
Very High

Reliability-based design optimization (RBDO) is intrinsically a double-loop procedure since it involves an overall optimization and an iterative reliability assessment at each search point. Due to the double-loop procedure, the computational expense of RBDO is normally very high. Current RBDO research is focused on performance functions having explicit analytical expression and readily available gradients. This paper addresses a more challenging type of RBDO problem in which the performance functions are computation intensive. These computation intensive functions are often considered as a “black-box” and their gradients are not available or not reliable. Based on the reliable design space (RDS) concept proposed earlier by the authors, this paper proposes a Reliable Space Pursuing (RSP) approach, in which RDS is first identified and then gradually refined while optimization is performed. It theoretically avoids the nested optimization and probabilistic assessment loop. This approach can apply to RBDO problems with either analytical or blackbox performance functions. Three well known numerical problems from the literature are used to test and demonstrate the effectiveness of RSP.

scholarly journals Multi-Objective, Reliability-Based Design Optimization of a Steering Linkage

2020 ◽  
Vol 10 (17) ◽  
pp. 5748
Author(s):  
Suwin Sleesongsom ◽  
Sujin Bureerat
Keyword(s):  
Design Optimization ◽  
Double Loop ◽  
Reliability Based Design Optimization ◽  
Case Scenario ◽  
Worst Case ◽  
Multi Objective ◽  
Reliability Based Design ◽  
Linkage Design ◽  
A New Technique ◽  
Optimization Loop

Reliability-based design optimization (RBDO) of a mechanism is normally based on the non-probabilistic model, which is viewed as failure possibility constraints in each optimization loop. It leads to a double-loop nested problem that causes a computationally expensive evaluation. Several methods have been developed to solve the problem, which are expected to increase the realization of optimum results and computational efficiency. The purpose of this paper was to develop a new technique of RBDO that can reduce the complexity of the double-loop nested problem to a single-loop. This involves using a multi-objective evolutionary technique combined with the worst-case scenario and fuzzy sets, known as a multi-objective, reliability-based design optimization (MORBDO). The optimization test problem and a steering linkage design were used to validate the performance of the proposed technique. The proposed technique can reduce the complexity of the design problem, producing results that are more conservative and realizable.

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