STRUCTURAL RELIABILITY MODEL CONSIDERING MIXED PROBABILISTIC AND INTERVAL VARIABLES

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XIANQI DENG

Abstract

TRADITIONAL PROBABILITY-BASED STRUCTURAL RELIABILITY ANALYSIS METHOD CAN ONLY CONSIDER RANDOM UNCERTAINTIES DESCRIBED BY RANDOM DISTRIBUTION FUNCTIONS, WHICH REQUIRED SUFFICIENT EXPERIMENTAL SAMPLES. ON COMPARISON, INTERVAL UNCERTAINTIES CAN BE MORE APPROPRIATE WHEN LACKING INFORMATION. IN REALISTIC SITUATIONS, SEVERAL STRUCTURAL RELIABILITY MODELS CONSIDERING MIXED PROBABILISTIC AND INTERVAL VARIABLES ARE PROPOSED. BESIDES CHOOSING RELIABILITY MODEL ACCORDING TO THE INFORMATION AVAILABLE OF THE UNCERTAINTIES, THIS PAPER PRESENTS A PERSPECTIVE IN STRUCTURAL DESIGN THAT FOR A SPECIFIC DESIGN, THE CONTROLLABLE STRUCTURAL UNCERTAIN PARAMETERS SHOULD BE BETTER DESCRIBED AS INTERVAL VARIABLES WHILE OTHER UNCONTROLLABLE UNCERTAIN PARAMETERS SUCH AS EXTERNAL LOADS DESCRIBED AS RANDOM VARIABLES IF SUFFICIENT INFORMATION IS AVAILABLE. THE CORRESPONDING RELIABILITY ANALYSIS MODEL IS PROPOSED. FURTHER, FOR SIMPLE TRUSS STRUCTURES, THIS PAPER DEMONSTRATES THAT THE EXTREME HYBRID RELIABILITY INDEX CAN BE ATTAINED WHEN THE INTERVAL VARIABLES REACH THEIR UPPER OR LOWER BOUNDS. TO SOLVE THE HYBRID RELIABILITY INDEX, A SEQUENTIAL SINGLE-LOOP STRATEGY COMBINED WITH AN INTERMEDIATE-VARIABLE BASED RESPONSE SURFACE AND THE METHOD OF MOVING ASYMPTOTES OPTIMIZATION SOLVER IS PROPOSED. FINALLY, NUMERICAL EXAMPLES ARE GIVEN TO DEMONSTRATE THE APPLICABILITY OF THE PROPOSED METHOD AND CONCLUDING REMARKS ARE MADE.

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