Advanced Analysis of Nuclear Waste Storage Health

Period of Performance: 01/01/2013 - 12/31/2013

$225K

Phase 1 STTR

Recipient Firm

Global Technology Connection, Inc.
2839 Paces Ferry Road SouthEast Array
Atlanta, GA 30339
Principal Investigator, Firm POC

Research Institution

Pacific Northwest National Laboratory
902 Battelle Blvd.
Richland, WA 99354

Abstract

The potential longevity and number of dry storage systems employed for storage of used nuclear fuel necessitate a deliberate consideration of long-term data management approaches. Necessary considerations include approaches to ensure archival of data over multiple centuries and data fusion methods to facilitate decision making based on multiple streams of information. Also important is establishing a advanced data analyses methodology for characterizing the physical condition of dry-storage systems in order to understand how their condition changes over time. Global Technology Connection, Inc. (GTC), in collaboration with its partners, proposes to develop an advanced data analysis methodology to monitor the integrity of nuclear waste containers/casks. The proposed & quot;Advanced Analysis of Nuclear Waste Storage Health & quot; (AANWSH) tool will combine information from various data streams to help assess Nuclear Waste container/cask material degradation status. The data analysis methodology will ensure nuclear waste containers or casks structural integrity by detecting early indications of degradation from multiple heterogeneous sources of information. The system will provide status indicators/features using combined model-based and data-driven approaches from a structural and material point of view. These indicators/features will be fused using hybrid modeling based on Bayesian theory to provide an overall safety of a container or a cask. The resulting technology from this effort can be applied to wide range of applications employed for monitoring of machinery and structural components. The commercial intent is to produce low-rate production quantities for commercial markets. Potential commercial applications include diagnostics/prognostics of machinery and structural health monitoring.