contributor author | Li, Dan | |
contributor author | Wang, Yang | |
date accessioned | 2019-09-18T09:04:33Z | |
date available | 2019-09-18T09:04:33Z | |
date copyright | 1/7/2019 0:00 | |
date issued | 2019 | |
identifier issn | 2572-3901 | |
identifier other | nde_002_01_011005.pdf | |
identifier uri | http://yetl.yabesh.ir/yetl1/handle/yetl/4258565 | |
description abstract | This research investigates the application of sum-of-squares (SOS) optimization method on finite element model updating through minimization of modal dynamic residuals. The modal dynamic residual formulation usually leads to a nonconvex polynomial optimization problem, the global optimality of which cannot be guaranteed by most off-the-shelf optimization solvers. The SOS optimization method can recast a nonconvex polynomial optimization problem into a convex semidefinite programming (SDP) problem. However, the size of the SDP problem can grow very large, sometimes with hundreds of thousands of variables. To improve the computation efficiency, this study exploits the sparsity in SOS optimization to significantly reduce the size of the SDP problem. A numerical example is provided to validate the proposed method. | |
publisher | American Society of Mechanical Engineers (ASME) | |
title | Sparse Sum-of-Squares Optimization for Model Updating Through Minimization of Modal Dynamic Residuals | |
type | Journal Paper | |
journal volume | 2 | |
journal issue | 1 | |
journal title | Journal of Nondestructive Evaluation, Diagnostics and Prognostics of Engineering Systems | |
identifier doi | 10.1115/1.4042176 | |
journal fristpage | 11005 | |
journal lastpage | 011005-9 | |
tree | Journal of Nondestructive Evaluation, Diagnostics and Prognostics of Engineering Systems:;2019:;volume ( 002 ):;issue: 001 | |
contenttype | Fulltext | |