Links among available integral benchmarks and differential date evaluations, computational biases and uncertainties, and nuclear criticality safety biases on potential MOX production throughput

Through the use of Oak Ridge National Laboratory's recently developed and applied sensitivity and uncertainty computational analysis techniques, this paper presents the relevance and importance of available and needed integral benchmarks and differential data evaluations impacting potential MOX production throughput determinations relative to low-moderated MOX fuel blending operations. The relevance and importance in the availability of or need for critical experiment benchmarks and data evaluations are presented in terms of computational biases as influenced by computational and experimental sensitivities and uncertainties relative to selected MOX production powder blending processes. Recent developments for estimating the safe margins of subcriticality for assuring nuclear criticality safety for process approval are presented. In addition, the impact of the safe margins (due to computational biases and uncertainties) on potential MOX production throughput will also be presented. (author)