Probabilistic error upper bounds for verification and validation practices for nuclear reactor modelling and simulation

Abstract

Verification and Validation (V&V) are the primary means to assess the accuracy and reliability in computational simulations which are used in the necessary practices of design, simulation and system optimisation. The main challenge is the ability to quantify the predictability of the model and establish an error upper bound in the V&V conclusions with a probabilistic statement. Therefore, this work introduces an iterative algorithm that quantifies the confidence in verification/validation conclusions and assigns a probabilistic statement given an error upper bound tolerance. Two case studies are used to illustrate and test the proposed algorithm. The first case study is a solution verification case study while the second is a simple validation-like case study. Results indicate that the proposed algorithm can help in assigning a violation probability estimate to certain error upper bound tolerance.