科技报告详细信息
Safety Analysis for a Radioisotope Stirling Generator.
Novascone, S. R. ; Dolphin, B. H. ; Lacy, J. M. ; Richins, W. D.
Technical Information Center Oak Ridge Tennessee
关键词: Radioisotope heat sources;    Electric generators;    Stirling cycle;    Safety analysis;    Containment;   
RP-ID  :  DE2008912897
学科分类:工程和技术(综合)
美国|英语
来源: National Technical Reports Library
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【 摘 要 】

The Idaho National Laboratory (INL) is conducting safety analyses of various lowpower Radioisotope Stirling Generator (RSG) design concepts for the U. S. Department of Energy. These systems are electrical power generators converting thermal energy from plutonium (238Pu) decay to electrical energy via a Stirling cycle generator. The design and function are similar to the RTG (Radioisotope Thermoelectric Generator) used in space missions since the early 1960s, with a more efficient Stirling cycle generator replacing the proven thermoelectric converter. This paper discusses the methods the INL is employing in the safety analysis effort, along with the software tools, lessons learned, and results. The overall goal of our safety analyses is to determine the probability of an accidental plutonium release over the life of the generator. Historical accident rates for various transportation modes were investigated using event tree methods. Source terms were developed for these accidents including primarily impact, fire, and creep rupture. A negative result was defined as rupture of the tantalum alloy containment vessel surrounding the encapsulated plutonia pellet. Damage due to identified impact accidents was evaluated using non-linear finite element software tools. Material models, gathered from a wide variety of sources, included strain-rate and temperature dependencies on yield strength, strain hardening, and rupture. Both individual component and overall system simulation results will be validated by impact testing to be conducted by Los Alamos National Laboratory. Results from deterministic impact, fire, and creep rupture analyses were integrated into the probabilistic (Monte Carlo) risk assessment by correlation functions relating accident parameters to component damage. This approach presented challenges, which are addressed.

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