Two-Stage Nested Optimization-Based Uncertainty Propagation Method for Uncertainty Reduction

A new method of epistemic uncertainty reduction is investigated according to the uncertainty of modeling and simulation. First, technical background of the uncertainty propagation in modeling and simulation is introduced. Uncertainty propagation procedure is divided into three major steps. Next, an epistemic uncertainty reduction method based on two-stage nested sampling uncertainty propagation is proposed, Monte Carlo Simulation method for the inner loop is applied to propagate the aleatory uncertainties and method based on optimization method is applied for the outer loop to propagate the epistemic uncertainties. The optimization objective function is the difference between the result of inner loop and the experiment data. Finally, the thermal challenge problem is given to validate the reasonableness and effectiveness of the proposed method.