Reliability-Based Structural Optimization Under Stochastic Time Varying Loads

Kim, S.H.; Wen, Y.K.

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https://hdl.handle.net/2142/14159 Copy

Description

Title

Reliability-Based Structural Optimization Under Stochastic Time Varying Loads

Author(s)

• Kim, S.H.
• Wen, Y.K.

Issue Date

1987-02

Keyword(s)

• Load combination
• optimization

Date of Ingest

2009-11-04T21:48:10Z

Abstract

Most optimization studies have been concerned with member or system geometry of structures under loads which are static or deterministic or both. The objective of this study is to develop a method for design under multiple stochastic loads based on optimization. The objective function such as cost is minimized under the constraint that the probabilities of various limit states being reached are within allowable limit. The loads are treated as random processes and their possible combined effect evaluated by the load coincidence method. The limit states considered are either yielding or first plastic hinge at the member level or plastic collapse at the system level. A penalty function approach and a Sequential Unconstrained Minimization (SUMT) method are used. Sensitivity studies with respect to the loading parameters are carried out. It is found that an optimization-based design satisfying the constraints at the member levels, may not have desirable system reliability and vice versa. A balanced design using a bi-level (member and system reliability constraints is proposed and shown to yield more risk consistent results. Also current design formats are examined. An improvement is introduced by adding a load combination formula including all loads under consideration.

Publisher

University of Illinois Engineering Experiment Station. College of Engineering. University of Illinois at Urbana-Champaign.

Series/Report Name or Number

Civil Engineering Studies SRS-533

Type of Resource

text

Genre of Resource

Technical Report

Language

en

Permalink

http://hdl.handle.net/2142/14159

Sponsor(s)/Grant Number(s)

National Science Foundation Grants CEE 82-07590 and DFR 84-14284

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