06. Improved Inventory Distributions for Los Alamos National Laboratory's Area G Performance Assessment and Composite Analysis Modeling

Numerical models are essential in many fields, including radioactive waste management, but they often involve significant uncertainty. Practitioners may address this by (i) building increasingly complex models or (ii) accepting and characterizing uncertainty. Inventory modeling at Los Alamos National Laboratory's Material Disposal Area G (Area G) illustrates how the second approach can enhance analyses and reduce costs.

Area G is a low-level radioactive waste disposal facility comprising pits and shafts. It is subject to U.S. DOE Order 435.1, which requires performance and composite analyses (PA/CA). Current modeling uses triangular distributions to represent uncertainty in radionuclide inventories-defined by a minimum, mode, and maximum. Typically, the mode equals the inventory estimate, with multipliers of 0.1 and 10 for the minimum and maximum, respectively. This strongly right-skewed distribution results in a median over three times the input estimate, potentially inflating projected dose.

To address this, gamma and normal distributions were implemented to better align the modeled median with the input estimate while preserving the high-end uncertainty. These distributions offer more accurate central tendencies without underrepresenting upper bounds.

Initial PA/CA model results using gamma/normal distributions show reduced total radiological dose compared to the triangular case: roughly three-to-two-fold for shafts and up to fourfold for pits. Lower projected doses could justify a thinner cover at site closure, reducing the need for truckloads of material and associated construction. Thus, revising the inventory modeling approach may lead to significant taxpayer savings while maintaining analytical integrity.

Radioactive Waste Management

Monte Carlo Simulation Software

GoldSim

Distribution Elicitation 

Mid-Level

Influence

Women in Statistics and Data Science 2025