Global Sensitivity Analysis and Reliability-Based Design Optimization of Electronic Packages subject to Thermal Loading

2014 ◽  
Author(s):  
Y. Aoues ◽  
A. Makhloufi ◽  
A. El-Hami ◽  
P. Pougnet
Keyword(s):  
Sensitivity Analysis ◽  
Design Optimization ◽  
Thermal Loading ◽  
Global Sensitivity Analysis ◽  
Electronic Packages ◽  
Reliability Based Design Optimization ◽  
Global Sensitivity ◽  
Reliability Based Design

System Reliability-Based Design Optimization Under Tradeoff Between Reduction of Sampling Uncertainty and Design Shift

2019 ◽  
Vol 141 (4) ◽  
Author(s):  
Sangjune Bae ◽  
Nam H. Kim ◽  
Seung-gyo Jang
Keyword(s):  
Sensitivity Analysis ◽  
Bayesian Network ◽  
Design Optimization ◽  
Failure Probability ◽  
System Reliability ◽  
Global Sensitivity Analysis ◽  
Conservative System ◽  
Reliability Based Design Optimization ◽  
Sampling Uncertainty ◽  
Reliability Based Design

This paper presents a tradeoff between shifting design and controlling sampling uncertainty in system reliability-based design optimization (RBDO) using the Bayesian network. The sampling uncertainty is caused by a finite number of samples used in calculating the reliability of a component, and it propagates to the system reliability. A conservative failure probability is utilized to consider sampling uncertainty. In this paper, the sensitivity of a conservative system failure probability is derived with respect to the design change and the number of samples in a component using Bayesian network along with global sensitivity analysis (GSA). In the sensitivity analysis, GSA is used for local sensitivity calculation. The numerical results show that sampling uncertainty can significantly affect the conservative system reliability and needs to be controlled to achieve the desired level of system reliability. Numerical examples show that both shifting design and reducing sampling uncertainty are crucial in the system RBDO.

scholarly journals Reliability-Based Design Optimization of Structures Using Complex-Step Approximation with Sensitivity Analysis

2021 ◽  
Vol 11 (10) ◽  
pp. 4708
Author(s):  
Junho Chun
Keyword(s):  
Sensitivity Analysis ◽  
Structural Optimization ◽  
Design Optimization ◽  
Optimization Problems ◽  
Probabilistic Constraints ◽  
Reliability Based Design Optimization ◽  
Step Size ◽  
First Derivative ◽  
Step Approximation ◽  
Reliability Based Design

Structural optimization aims to achieve a structural design that provides the best performance while satisfying the given design constraints. When uncertainties in design and conditions are taken into account, reliability-based design optimization (RBDO) is adopted to identify solutions with acceptable failure probabilities. This paper outlines a method for sensitivity analysis, reliability assessment, and RBDO for structures. Complex-step (CS) approximation and the first-order reliability method (FORM) are unified in the sensitivity analysis of a probabilistic constraint, which streamlines the setup of optimization problems and enhances their implementation in RBDO. Complex-step approximation utilizes an imaginary number as a step size to compute the first derivative without subtractive cancellations in the formula, which have been observed to significantly affect the accuracy of calculations in finite difference methods. Thus, the proposed method can select a very small step size for the first derivative to minimize truncation errors, while achieving accuracy within the machine precision. This approach integrates complex-step approximation into the FORM to compute sensitivity and assess reliability. The proposed method of RBDO is tested on structural optimization problems across a range of statistical variations, demonstrating that performance benefits can be achieved while satisfying precise probabilistic constraints.

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