Advanced search
Start date
Betweenand
(Reference retrieved automatically from Web of Science through information on FAPESP grant and its corresponding number as mentioned in the publication by the authors.)

Application of a Reduced Order Model for Fuzzy Analysis of Linear Static Systems

Full text
Author(s):
Valdebenito, Marcos A. [1] ; Jensen, Hector A. [1] ; Wei, Pengfei [2] ; Beer, Michael [3] ; Beck, Andre T. [4]
Total Authors: 5
Affiliation:
[1] Univ Tecn Federico Santa Maria, Dept Obras Civiles, Ave Espana 1680, Valparaiso 2390123 - Chile
[2] Northwestern Polytech Univ, Sch Mech Civil Engn & Architecture, Xian 710072 - Peoples R China
[3] Leibniz Univ Hannover, Inst Risk & Reliabil, Callinstr 34, D-30167 Hannover - Germany
[4] Univ Sao Paulo, Dept Struct Engn, Ave Trabalhador Sao Carlense 400, BR-13566590 Sao Carlos, SP - Brazil
Total Affiliations: 4
Document type: Journal article
Source: ASCE-ASME JOURNAL OF RISK AND UNCERTAINTY IN ENGINEERING SYSTEMS PART B-MECHANICAL ENGINEERING; v. 7, n. 2 JUN 1 2021.
Web of Science Citations: 0
Abstract

This contribution proposes a strategy for performing fuzzy analysis of linear static systems applying alpha-level optimization. In order to decrease numerical costs, full system analyses are replaced by a reduced order model that projects the equilibrium equations to a small-dimensional space. The basis associated with the reduced order model is constructed by means of a single analysis of the system plus a sensitivity analysis. This reduced basis is enriched as the alpha-level optimization strategy progresses in order to protect the quality of the approximations provided by the reduced order model. A numerical example shows that with the proposed strategy, it is possible to produce an accurate estimate of the membership function of the response of the system with a limited number of full system analyses. (AU)

FAPESP's process: 19/13080-9 - Optimal reliability-based design of structural systems considering progressive collapse
Grantee:André Teófilo Beck
Support Opportunities: Regular Research Grants