The Energy Interaction Model: A promising new methodology for projecting GPHS-RTG cladding failures, release amounts & respirable release fractions for postulated pre-launch, launch, and post-reentry earth impact accidents

Abstract

Safety analyses and evaluations must be scrutable, defensible, and credible. This is particularly true when nuclear systems are involved, with their attendant potential for releases of radioactive materials (source terms) to the unrestricted environment. Analytical projections of General Purpose Heat Source Radioisotope Thermoelectric Generator (GPHS-RTG) source terms, for safety analyses conducted to date, have relied upon generic data correlations using a single parameter of cladding damage, termed “distortion.” However, distortion is not an unequivocal measure of cladding insult, failure, or release. Furthermore, the analytical foundation, applicability, and broad use of distortion are argumentative and, thus, somewhat troublesome. In an attempt to avoid the complications associated with the use of distortion, a new methodology, referred to as the Energy Interaction Model (EIM), has been preliminarily developed. This new methodology is based upon the physical principles of energy and energy exchange during mechanical interactions. Specifically, the EIM considers the energy imparted to GPHS-RTG components (bare fueled clads, GPHS modules, and full GPHS-RTGs) when exposed to mechanical threats (blast/overpressure, shrapnel and fragment impacts, and Earth surface impacts) posed by the full range of potential accidents. Expected forms are developed for equations intended to project cladding failure probabilities, the number of cladding failures expected, release amounts, and the fraction released as respirable particles. The coefficients of the equations developed are then set to fit the GPHS-RTG test data, ensuring good agreement with the experimental database. This assured, fitted agreement with the test database, along with the foundation of the EIM in first principles, provides confidence in the model’s projections beyond the available database. In summary, the newly developed EIM methodology is described and discussed. The conclusions reached are that the EIM holds great promise as a predictive analytical tool for future GPHS-RTG safety assessments, and this promise can become a reality in the near future—given a modest level of advancement and refinement.