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

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错综复杂地联系在一起。工程风险评估是在设计法规、规范和标准时使用的基本工具，这些法规、规范和标准在不施加不合理的监管负担的情况下提高了能源系统的安全性和弹性。随着系统变得更加复杂和出现新的挑战，推进风险知情监管背后的科学至关重要。该学院早期职业发展(CALEAR)项目研究如何将可靠性工程的两个领域的原理系统地整合起来，以促进这门科学的发展。这项研究认为，概率风险评估(PRA)和预见学和健康管理(PHM)具有互补的特点，可以弥补各自的弱点。这项研究将建立和验证一个概念框架以及数学和计算方法，以系统地整合PRA和PHM方法、数据和模型。与核电站和氢气运输基础设施应用领域的跨学科利益攸关方直接接触，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。综合教育活动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，以及为妇女和工程界代表性不足的少数群体开展多样性和包容性倡议。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。这项研究的重点是通过系统地整合来自PRA和PHM的概念、数据和方法，并使用能源系统案例研究和专家利益攸关方参与的严格验证，来转变对能源系统的风险知情监管。这些教育活动通过一个新的关于能源系统风险评估的博物馆展览来加强K-12和公共教育，该展览将在该国唯一的核历史和科学博物馆展出，并将向广泛的附属博物馆网络提供。在这项研究的基础上，通过开发新的主动学习练习，可靠性工程的研究生课程将得到加强。这项研究借鉴了PRA和PHM的工程技术，PRA提供了一种综合的量化方法来综合数据、情景和概率模型，以评估复杂工程系统在不确定条件下的风险；PHM提供了强大的算法，使用传感器数据和故障模型来了解和预测部件的健康状况。到目前为止，在PRA和PHM的交叉口几乎没有什么工作。与以往试图使PRA更加动态或将PHM扩展到其当前体系结构中更复杂的组件的方法不同，本研究试图解构PRA和PHM，并设计一种利用这两种方法的优点的新方法。这项研究首先定义了概念框架，然后定义了数学和计算结构。将使用能源系统案例研究和基于利益相关者的验证对候选结构进行比较和验证。核电站和氢气加气站被用作试验台，以确保结果可推广到单一能源系统或监管过程之外。这项研究创造了新的知识和方法，将影响核电站、氢气基础设施、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。综合教育活动扩大了K-12、研究生和公众对能源系统安全背后的科学的理解。通过加强研究生招生和指导活动，将鼓励女性和代表性不足的少数族裔更广泛地参与工程学。该奖项反映了NSF的法定使命，并通过使用基金会的智力优势和更广泛的影响审查标准进行评估，被认为值得支持。

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.