Time-variant reliability-oriented structural optimization and a renewal model for life-cycle costing

Socio-economically sustainable civil engineering infrastructures by optimization

“…For example, serviceability failure, obsolescence, aging, deterioration and inspection and maintenance, finite renewal times, repeated renewal during construction and finite service times can be dealt with. Benefit and damage terms can be functions of time [22,43,59,60]. Also, multiple failure modes can been considered [60].…”

Time-Dependent Reliability Modeling and Analysis Method for Mechanics Based on Convex Process

“…Since the development of Rice's formula, amounts of improvements have been made. For example, Vanmarcke proposed a commonly used improved formula, accounting for the dependence between the crossing events and the time that the process spends above the barrier in application to normal stationary random process model 2 Mathematical Problems in Engineering [18]; Madsen and Krenk developed an integral equation method for solving the first-passage problems [19]; a timedependent reliability analysis method with joint upcrossing rates, inspired by [19], was further developed by Hu and Du [20] for more general cases of the limit-state functions that involve time, random variables, and stochastic processes; by combination of the ideas of outcrossing and system reliability, Wang et al [13] presented an improved subset simulation with splitting approach by partitioning the original high dimensional random process into a series of correlated, short duration, low dimensional random processes; several improved formulations for calculating the outcrossing rate based on the Poisson assumption were, respectively, extended by Schall et al [21], Engelund et al [22], Streicher and Rackwitz [23], and so forth. Recently, additional correlational researches have been also suggested by [24,25].…”

On the Robustness of Structural Risk Optimization With Respect to Epistemic Uncertainties

“…This possibility can be measured in terms of probability, and then multiplied by the cost (monetary measure of the consequences) of failure. The resulting term, also known as the expected cost of failure, can be incorporated in the objective function, leading to an unconstrained optimization problem: minimization of total expected costs [16][17][18][19][20][21]. This formulation, also known as risk optimization [22], allows one to find the optimum point of compromise between different possible failure modes, as well as the optimum safety margin with respect to each failure mode [23].…”