Structural Reliability Analysis of Limit State Functions With Multiple Design Points Using Evolutionary Strategies

Abstract

THE COMPLETE IDENTIFICATION OF ALL RELEVANT DESIGN POINTS IS OF PARAMOUNT IMPORTANCE FOR THE RELIABILITY ANALYSIS OF REAL STRUCTURES. IN THIS PAPER A METHODOLOGY BASED ON EVOLUTIONARY STRATEGIES (ES) ALGORITHM IS PROPOSED TO PERFORM STRUCTURAL RELIABILITY ANALYSIS OF LIMIT STATE FUNCTIONS WITH MULTIPLE DESIGN POINTS. A MULTI DIMENSIONAL OPTIMIZATION METHOD USING ES IS FIRST USED TO OBTAIN A PRELIMINARY MAPPING OF THE RELEVANT DESIGN POINTS (LOCAL MAXIMA). THE APPROXIMATE COORDINATES OF THESE POINTS ARE EMPLOYED AS INITIAL GUESSES IN THE HL-RF (HASOFER AND LINDRACK WITZ AND FIESSLER) ALGORITHM WHEN THE FIRST ORDER RELIABILITY METHOD (FORM) FOR SERIES SYSTEMS IS USED TO EVALUATE THE SYSTEM PROBABILITY OF FAILURE. THESE POINTS ARE ALSO USED AS THE CENTRAL POINTS WHEN MONTE CARLO SIMULATION WITH IMPORTANCE SAMPLING (MCIS) METHOD IS EMPLOYED IN THE STRUCTURAL RELIABILITY EVALUATION. NUMERICAL APPLICATIONS SHOW THE FEASIBILITY AND THE ROBUSTNESS OF THE PROPOSED METHODOLOGY.