Assessing confidence in inferring reactor type and fuel burnup: A Markov chain Monte Carlo approach

We extend the previous maximum likelihood solution to this inverse problem by using Markov Chain Monte Carlo to simulate observations from the posterior distribution for reactor type and burnup. This provides an alternate estimation strategy, an estimate of the confidence in the inferred reactor type and burnup, and improves prediction performance. We also investigate the impact of increased error variance as a step toward including the effect of computer-code uncertainty.