CAREER: Modernizing Risk Assessment Through Systematic Integration of Probabilistic Risk Assessment (PRA) and Prognostics and Health Management (PHM)

职业：通过概率风险评估 (PRA) 和预测与健康管理 (PHM) 的系统集成实现风险评估现代化

• 批准号: 2045519
• 负责人: Katrina Groth
• 金额: $ 50万
• 依托单位: University of Maryland, College Park
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2021
• 资助国家: 美国
• 起止时间: 2021-08-01 至 2026-07-31
• 项目状态: 未结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2045519&HistoricalAwards=false
• 关键词: CAREER; Modernizing; Risk; Assessment; Through

Safe, reliable, affordable energy is intricately connected to broad advances in health, science, prosperity, and our national defense. Engineering risk assessment is an essential tool used in designing the regulations, codes, and standards that enhance energy system safety and resilience without imposing unreasonable regulatory burden. Advancing the science behind risk-informed regulation is essential as systems become more complex and new challenges emerge. This Faculty Early Career Development (CAREER) project investigates how principles from two domains of reliability engineering can be systematically integrated to advance this science. This research that Probabilistic Risk Assessment (PRA) and Prognostics and Health Management (PHM) have complementary characteristics that can offset their individual weaknesses. The research will establish and validate a conceptual framework along with mathematical and computational methods to systematically integrate PRA and PHM methods, data, and models. Direct engagement with interdisciplinary stakeholders from nuclear power plant and hydrogen transportation infrastructure applications will facilitate both validation and adoption of the new methods. The results will provide new knowledge about the range of data and models that can be used in regulatory design and decision making. Integrated educational initiatives include design of the first public museum exhibit on energy system risk assessment, enhanced reliability engineering coursework, and diversity and inclusion initiatives for women and underrepresented minorities in engineering.The overarching goal of this project is to establish a strong foundation of integrated research and educational activities centered on energy system risk assessment. The research focuses on transforming risk-informed regulation for energy systems through systematic integration of concepts, data and methods drawn from PRA and PHM and rigorous validation using both energy system case studies and expert stakeholder engagement. The educational activities enhance K-12 and public education through a new museum exhibit on energy system risk assessment that will be displayed in the nation’s only nuclear history and science museum and that will also be made available to a broad network of affiliated museums. Graduate coursework in reliability engineering will be enhanced through development of new active learning exercises based on this research. The research draws upon engineering techniques of PRA, which provides a comprehensive quantitative approach for synthesizing data, scenarios, and probability models to assess risk under uncertainty for complex engineering systems; and PHM, which provides powerful algorithms for using sensor data and failure models to understand and predict health of components. To date, there has been little work at the intersection of PRA and PHM. Unlike previous approaches which seek to make PRA more dynamic or to extend PHM to more complicated components within their current architectures, this research seeks to deconstruct PRA and PHM and engineer a new approach which leverages the benefits of both approaches. The research starts by defining the conceptual framework and then defining mathematical and computational structures. The candidate structures will be compared and validated using energy system case studies and stakeholder-based validation. Nuclear power plants and hydrogen fueling stations are used as testbeds to ensure that the results are generalizable beyond a single energy system or regulatory process. The research has broader societal impact by creating new knowledge and methods that will impact the design of regulations for nuclear power plants, hydrogen infrastructure, pipelines, and other energy systems and critical infrastructures. The integrated educational activities broaden K-12, graduate student, and public understanding of the science behind energy system safety. Broader participation of women and underrepresented minorities in engineering will be encouraged via the enhancement of graduate student recruitment and mentoring activities.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

安全、可靠、负担得起的能源与健康、科学、繁荣和国防的广泛进步密不可分。工程风险评估是设计法规、规范和标准的重要工具，可在不施加不合理监管负担的情况下提高能源系统的安全性和弹性。随着系统变得更加复杂和新的挑战出现，推进风险知情监管背后的科学至关重要。这个教师早期职业发展（CAREER）项目研究如何从可靠性工程的两个领域的原则可以系统地整合，以推进这门科学。本研究认为，概率风险评估（PRA）和预测与健康管理（PHM）具有互补的特点，可以弥补各自的弱点。本研究将建立并验证一个概念框架，沿着与数学和计算方法，系统地整合PRA和PHM的方法，数据和模型。与来自核电站和氢运输基础设施应用的跨学科利益相关者的直接接触将促进新方法的验证和采用。研究结果将提供有关可用于监管设计和决策的数据和模型范围的新知识。综合教育举措包括设计第一个关于能源系统风险评估的公共博物馆展览，加强可靠性工程课程，以及为妇女和工程领域代表性不足的少数民族提供多样性和包容性举措。该项目的总体目标是为以能源系统风险评估为中心的综合研究和教育活动奠定坚实的基础。该研究的重点是通过系统整合PRA和PHM的概念，数据和方法，以及使用能源系统案例研究和专家利益相关者参与的严格验证，改变能源系统的风险知情监管。教育活动通过一个关于能源系统风险评估的新博物馆展览加强了K-12和公众教育，该展览将在全国唯一的核历史和科学博物馆展出，并将提供给广泛的附属博物馆网络。在可靠性工程研究生课程将通过开发新的主动学习练习，基于这项研究得到加强。该研究借鉴了PRA的工程技术，该技术提供了一种综合数据，场景和概率模型的综合定量方法，以评估复杂工程系统在不确定性下的风险; PHM提供了强大的算法，用于使用传感器数据和故障模型来了解和预测组件的健康状况。迄今为止，在PRA和PHM的交叉点上几乎没有工作。与以前的方法，寻求使PRA更动态或扩展PHM更复杂的组件在其当前的架构，本研究旨在解构PRA和PHM和工程师的一种新的方法，利用这两种方法的好处。研究首先定义概念框架，然后定义数学和计算结构。候选结构将进行比较，并使用能源系统的案例研究和基于身份验证验证。核电站和加氢站被用作测试平台，以确保结果可推广到单一能源系统或监管过程之外。 该研究创造了新的知识和方法，将影响核电站，氢基础设施，管道和其他能源系统和关键基础设施的法规设计，从而产生更广泛的社会影响。综合教育活动拓宽了K-12，研究生和公众对能源系统安全背后的科学的理解。通过加强研究生招聘和指导活动，将鼓励妇女和代表性不足的少数民族更广泛地参与工程。该奖项反映了NSF的法定使命，并通过使用基金会的智力价值和更广泛的影响审查标准进行评估，被认为值得支持。

项目成果

A comparison of DBN model performance in SIPPRA health monitoring based on different data stream discretization methods

• DOI: 10.1016/j.ress.2023.109206
• 发表时间: 2023-02
• 期刊: Reliab. Eng. Syst. Saf.
• 作者: Austin D. Lewis;K. Groth

A novel probabilistic approach to counterfactual reasoning in system safety

• DOI: 10.1016/j.ress.2022.108785
• 发表时间: 2022-08
• 期刊: Reliab. Eng. Syst. Saf.
• 作者: Andres Ruiz-Tagle;E. Droguett;K. Groth