Time-dependent failure possibility of structures involving epistemic uncertainty

Time-dependent failure possibility (TDFP) is the possibility of performance less than zero under fuzzy uncertainty in the given time interval. Failure possibility of structures gets accelerated by improper consideration of input variables, mathematical and structural models, and environmental factors. To explore the environmental factors in structures, the time-variant creep and shrinkage model for concrete structures, and deterioration of steel cross-section and other ma-terial properties due to corrosion, and increment of action on the structure with time are considered. A real-time data has been collected from the city of Addis Ababa, Ethiopia for the case study to substantiate the methodology presented in this paper. In this paper, identification the possible failure modes, estimation of the time-dependent performance of failure modes, gener-ating membership function (MF) of fuzzy input and output variables, and finally, the TDFP evaluated from MF of output quantities. Because of its simplicity and frequent application, triangular MF is used to characterize epistemic uncertainty of parameters. However, the failure possibility analysis is a complex problem for practicing engineering that needs a rigorous procedure, a single-loop optimization method (SLOM) is employed to evaluate TDFP of structures involving epistemic uncertainty. The effectives of SLOM has been checked by adaptive SORM Breitung's algorithm. To enhance the validation of the proposed approach, several examples are thoroughly carried out that indicate the SLOM is bit conservative compared with SORM Brei-tung's algorithm in such a way that their maximum recorded percentage difference is 9.464%.

Automated summary

Time-dependent failure possibility (TDFP) refers to the possibility of performance less than zero under fuzzy uncertainty in the given time interval. Failure possibility of structures gets accelerated by improper consideration of input variables, mathematical and structural models, and environmental factors.