A two-step procedure for time-dependent reliability-based design optimization involving piece-wise stationary Gaussian processes

We consider in this paper a time-dependent reliability-based design optimization (RBDO) problem with constraints involving the maximum and/or the integral of a random process over a time interval. We focus especially on problems where the process is a stationary or a piece-wise stationary Gaussian process. A two-step procedure is proposed to solve the problem. First, we use ergodic theory and extreme value theory to reformulate the original constraints into time-independent ones. We obtain an equivalent RBDO problem for which classical algorithms perform poorly. The second step of the procedure is to solve the reformulated problem with a new method introduced in this paper and based on an adaptive kriging strategy well suited to the reformulated constraints called AK-ECO for adaptive kriging for expectation constraints optimization. The procedure is applied to two toy examples involving a harmonic oscillator subjected to random forces. It is then applied to an optimal design problem for a floating offshore wind turbine.

Automated summary

In this paper, we study a time-dependent reliability-based design optimization problem with constraints involving the maximum and/or the integral of a random process over a time interval. We propose a two-step procedure to solve the problem, which involves reformulating the original constraints using ergodic theory and extreme value theory, and then solving the reformulated problem using a new method called AK-ECO.