Surrogate assisted reliability analysis and probabilistic design of structures under uncertainty
department or school: Applied Science, Faculty of
department or school: Engineering, School of (Okanagan)
data provider: DSpace
degree campus: UBCO
creator: Das, Sourav
issued: 2023-06-01T19:57:46Z
issued: 2023
related degree: Doctor of Philosophy - PhD
degree grantor: University of British Columbia
description: This thesis presents the reliability analysis and probabilistic design of a one-storey moment-resisting frame coupled with a nonlinear energy sink (NES) with negative stiffness and sliding friction and a shape memory alloy (SMA)-based damped outrigger structure when the structures are subjected to earthquake excitation. Initially, the reliability-based design optimization (RBDO) of the above structures is carried out to estimate the tuning parameters of NES and SMA so that the proposed systems produce effective performances when exposed to uncertain environments. To do that, the probability of failure of the structure is estimated using an outcrossing rate approach based on a stationary assumption. To reduce the computational time, a surrogate model is used in the RBDO analysis. To overcome stationary assumption, the next work is devoted to formulate an efficient reliability analysis method using surrogate model-based probability density evolution method (PDEM). The PDEM is used to estimate the probability density function (PDF) of the structural responses. The partial differential equations (PDE) in PDEM are solved using the finite difference method coupled with total variation diminishing, in which a set of representative points of random parameters are generated using the generalized F-discrepancy scheme. To obtain satisfactory accuracy of the numerical solution, representative points are needed, which becomes computationally expensive for complex structures. To reduce the computation burden, the stochastic spectral embedding (SSE) surrogate model is used, which approximates the original response surface. The SSE is a class of supervised machine learning algorithm where it is trained by few observations and enables output prediction as spectral representation. In general, PDE in PDEM are solved using a finite difference scheme in which the accuracy of the numerical solution depends on the number of temporal and spatial discretizations, making them computationally…
aggregated CHO: https://circle.library.ubc.ca/rest/handle/2429/84769
note: Surrogate Assisted ReliabilityAnalysis and Probabilistic Design ofStructures under UncertaintybySourav DasB.E., Jadavpur University, 2014M.Tech., Indian Institute of Technology, Guwahati, 2017A THESIS SUBMITTED IN PARTIAL FULFILLMENT OFTHE REQUIREMENTS FOR THE DEGREE OFDOCTOR OF PHILOSOPHYinTHE COLLEGE OF GRADUATE STUDIES(Civil Engineering)THE UNIVERSITY OF BRITISH COLUMBIA(Okanagan)May 2023© Sourav Das, 2023The following individuals certify that they have read, and recommend to the College ofGraduate Studies for acceptance, a dissertation entitled:Surrogate Assisted Reliability Analysis and Probabilistic Design of Struc-tures under Uncertaintysubmitted by Sourav Das in partial fulfillment of the requirements for the degree of Doctorof PhilosophyDr. Solomon Tesfamariam, School of EngineeringSupervisorDr. Warren Hare, IKB Faculty of ScienceSupervisory Committee MemberDr. Abbas Milani, School of EngineeringSupervisory Committee MemberDr. Ahmad Al-Dabbagh, School of EngineeringUniversity ExaminerDr. Ertugrul Taciroglu, University of California - Los AngelesExternal ExamineriiAbstractThis thesis presents the reliability analysis and probabilistic design of a one-storeymoment-resisting frame coupled with a nonlinear energy sink (NES) with negative stiffnessand sliding friction and a shape memory alloy (SMA)-based damped outrigger structurewhen the structures are subjected to earthquake excitation.Initially, the reliability-based design optimization (RBDO) of the above structures iscarried out to estimate the tuning parameters of NES and SMA so that the proposed systemsproduce effective performances when exposed to uncertain environments. To do that, theprobability of failure of the structure is estimated using an outcrossing rate approach basedon a stationary assumption. To reduce the computational time, a surrogate model is usedin the RBDO analysis.To overcome stationary assumption, the next work is devoted to formulate an efficient re-liability analysis method using su…
has type: Thesis/Dissertation
date issued: 2023-05
is shown at: 10.14288/1.0432798
language: eng
degree discipline: Civil Engineering
provider: Vancouver : University of British Columbia Library
publisher: University of British Columbia
rights: Attribution 4.0 International
rights URI: http://creativecommons.org/licenses/by/4.0/
scholar level: Graduate
contributor: Tesfamariam, Solomon
type: Text
identifier URI: http://hdl.handle.net/2429/84769