Extension of stratum level stochastic model to compute facility level detection probability

Lohith Annadevula - University of Massachusetts Lowell
Sukesh Aghara - University of Massachusetts Lowell

The International Atomic Energy Agency (IAEA) defines a nuclear state as a collection of nuclear facilities, a nuclear facility being a collection of strata in which nuclear material of similar characteristics are being stored in items/batches. Proliferators, either state-sponsored or other, aim to divert this nuclear material thereby introducing multiple defected items in the nuclear stratum. As part of its technical objective to detect these defects, IAEA employs well-established statistical methods to assess the effectiveness of its inspection plans on a multi-defect stratum by evaluating defect detection probability (DP). At stratum-level, the defect detection probability is the chance of identifying at least one defect when a defected stratum is subjected to a certain inspection plan. A Stochastic Model is developed to compute DP results within the allotted number of trials/computational resources. The stochastic results have error associated with them which is calculated to provide the error bound for the computed DP. To extend the model to a state-level concept, the probability of detecting material diversion at the facility level must be calculated. The initial approach involved calculating DP curves for each stratum. These are then aggregated using event independence principle to determine the probability of detecting material diversion at the facility level. This approach, although effective, requires several serial steps leading to heavy computational penalties for multi-stratum, multi-item facilities. An alternative set of algorithms are developed which directly compute facility-level DP without first computing the DP curves for each stratum in the facility. The results of the new model will be compared to previously published results.