A two-level Kriging-based approach with active learning for solving time-variant risk optimization problems

•Adaptive surrogate models for solution of time-variant risk optimization problems;•Efficient Global Optimization (EGO) and Efficient Global Reliability Analysis (EGRA) combined;•One surrogate for objective function, one for limit state;•Stochastic processes explicitly modelled as time series;•Load-path dependent reliability problems addressed;