Efficient Monte Carlo Methods for Characterization of Safety Margins of Nuclear Power Plants

用于表征核电厂安全裕度的高效蒙特卡罗方法

• 批准号: 1537322
• 负责人: Marvin Nakayama
• 金额: $ 27万
• 依托单位: New Jersey Institute of Technology
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2015
• 资助国家: 美国
• 起止时间: 2015-09-01 至 2019-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1537322&HistoricalAwards=false
• 关键词: Efficient; Monte; Carlo; Methods; Characterization

The goal of the award is to devise efficient computational methods for performing risk and safety analyses of nuclear power plants. A recent international effort of the Nuclear Energy Agency formulated a new framework, known as risk-informed safety-margin characterization, to address several critical issues facing the nuclear industry today. The impacts of these developments, which include extending licenses for aging facilities and operating them at higher power levels, can profoundly affect safety margins, and there is an urgent need to better understand the risks in the changes. Indeed, the catastrophic 2011 accident at the Fukushima Daiichi plant in Japan clearly shows the utmost importance of accurately measuring risk. In addition to performing efficient nuclear safety analyses, the techniques may also be applied to attack problems in civil and mechanical engineering, catastrophe modeling, and finance.This research combines theoretical and practical components, including designing new Monte Carlo algorithms, formally establishing their validity, and implementing them to analyze risks of existing nuclear plants. The core of the work will focus on variance-reduction techniques for efficient simulation for performing risk and safety analyses of nuclear facilities. Because current simulations can require enormous computational effort, applying variance reduction is essential for performing safety analyses. If successful, the new methods will profoundly reduce computation time, perhaps by orders of magnitude. To further account for the statistical error of the resulting estimators, the investigator also plans to produce asymptotically valid confidence intervals.

该奖项的目标是设计有效的计算方法，用于执行核电厂的风险和安全分析。核能机构最近的一项国际努力制定了一个新的框架，称为风险知情安全裕度定性，以解决核工业今天面临的几个关键问题。这些发展的影响，包括延长老化设施的许可证和以更高的功率水平运行，可能会深刻影响安全裕度，迫切需要更好地了解变化中的风险。事实上，2011年发生在日本福岛第一核电站的灾难性事故清楚地表明了准确衡量风险的极端重要性。除了进行有效的核安全分析，该技术也可以应用到土木和机械工程，灾难建模和financy.This研究结合理论和实践的组件，包括设计新的蒙特卡罗算法，正式建立其有效性，并实施它们来分析现有的核电站的风险攻击问题。工作的核心将集中在方差减少技术，有效的模拟进行核设施的风险和安全分析。由于当前的模拟可能需要大量的计算工作，因此应用方差缩减对于执行安全分析至关重要。如果成功，新方法将大大减少计算时间，也许是数量级的。为了进一步解释所得估计量的统计误差，研究者还计划生成渐近有效的置信区间。