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DOE OSTI2025

PSA 2025 DPRA for Cyber Optimization

Cyberattacks can have many different attack paths, durations, and goals. There are also many different mitigation options involving hardware, software, and/or humans. Evaluating defense options should include quantitative evaluation of overall effectiveness to make cost and risk-informed decisions. Typical cyberattack modeling methods only provide a qualitative evaluation and have difficulty with time dependent scenarios. The main areas of cybersecurity are confidentiality, integrity, and availability. For companies with cyber-physical systems such as advanced nuclear reactors, cyber-related integrity is a requirement set by the U.S. Nuclear Regulatory Commission. But companies are also concerned about availability or reliability as a business case. As cyber threats are evolving to a business-for-hire structure, more attacks focus on disrupting business success and reliability, causing financial and economic stability risk. Companies want reliability analysis while optimizing cost, which requires more than safety modeling methods. Dynamic-state-based and Markov-based modeling provides a method for better cyber scenario modeling with timing and conditional features not found in other numerical evaluation methods. EMRALD (Event Modeling Risk Assessment using Lined Diagrams) is a dynamic risk analysis modeling and simulation tool and has features that reduce modeling issues such as state-base explosion found in Markov-based tools. It has been used to model different time-dependent events including plant behavior and operator procedures. As a general modeling tool, EMRALD can also be used to model cyberattack scenarios with varying mitigation options and quantify effectiveness, producing numerical data for risk-informed decisions. This paper uses EMRALD to demonstrate that dynamic risk analysis can be used for cyber threat modeling to provide insights for design decision-making and optimize defense strategies.

97 - MATHEMATICS AND COMPUTING↗
NASA NTRS2011

NASA System Safety Handbook: System Safety Framework and Concepts for Implementation - Volume 1

System safety assessment is defined in NPR 8715.3C, NASA General Safety Program Requirements as a disciplined, systematic approach to the analysis of risks resulting from hazards that can affect humans, the environment, and mission assets. Achievement of the highest practicable degree of system safety is one of NASA's highest priorities. Traditionally, system safety assessment at NASA and elsewhere has focused on the application of a set of safety analysis tools to identify safety risks and formulate effective controls.1 Familiar tools used for this purpose include various forms of hazard analyses, failure modes and effects analyses, and probabilistic safety assessment (commonly also referred to as probabilistic risk assessment (PRA)). In the past, it has been assumed that to show that a system is safe, it is sufficient to provide assurance that the process for identifying the hazards has been as comprehensive as possible and that each identified hazard has one or more associated controls. The NASA Aerospace Safety Advisory Panel (ASAP) has made several statements in its annual reports supporting a more holistic approach. In 2006, it recommended that "... a comprehensive risk assessment, communication and acceptance process be implemented to ensure that overall launch risk is considered in an integrated and consistent manner." In 2009, it advocated for "... a process for using a risk-informed design approach to produce a design that is optimally and sufficiently safe." As a rationale for the latter advocacy, it stated that "... the ASAP applauds switching to a performance-based approach because it emphasizes early risk identification to guide designs, thus enabling creative design approaches that might be more efficient, safer, or both." For purposes of this preface, it is worth mentioning three areas where the handbook emphasizes a more holistic type of thinking. First, the handbook takes the position that it is important to not just focus on risk on an individual basis but to consider measures of aggregate safety risk and to ensure wherever possible that there be quantitative measures for evaluating how effective the controls are in reducing these aggregate risks. The term aggregate risk, when used in this handbook, refers to the accumulation of risks from individual scenarios that lead to a shortfall in safety performance at a high level: e.g., an excessively high probability of loss of crew, loss of mission, planetary contamination, etc. Without aggregated quantitative measures such as these, it is not reasonable to expect that safety has been optimized with respect to other technical and programmatic objectives. At the same time, it is fully recognized that not all sources of risk are amenable to precise quantitative analysis and that the use of qualitative approaches and bounding estimates may be appropriate for those risk sources. Second, the handbook stresses the necessity of developing confidence that the controls derived for the purpose of achieving system safety not only handle risks that have been identified and properly characterized but also provide a general, more holistic means for protecting against unidentified or uncharacterized risks. For example, while it is not possible to be assured that all credible causes of risk have been identified, there are defenses that can provide protection against broad categories of risks and thereby increase the chances that individual causes are contained. Third, the handbook strives at all times to treat uncertainties as an integral aspect of risk and as a part of making decisions. The term "uncertainty" here does not refer to an actuarial type of data analysis, but rather to a characterization of our state of knowledge regarding results from logical and physical models that approximate reality. Uncertainty analysis finds how the output parameters of the models are related to plausible variations in the input parameters and in the modeling assumptions. The evaluation of unrtainties represents a method of probabilistic thinking wherein the analyst and decision makers recognize possible outcomes other than the outcome perceived to be "most likely." Without this type of analysis, it is not possible to determine the worth of an analysis product as a basis for making decisions related to safety and mission success. In line with these considerations the handbook does not take a hazard-analysis-centric approach to system safety. Hazard analysis remains a useful tool to facilitate brainstorming but does not substitute for a more holistic approach geared to a comprehensive identification and understanding of individual risk issues and their contributions to aggregate safety risks. The handbook strives to emphasize the importance of identifying the most critical scenarios that contribute to the risk of not meeting the agreed-upon safety objectives and requirements using all appropriate tools (including but not limited to hazard analysis). Thereafter, emphasis shifts to identifying the risk drivers that cause these scenarios to be critical and ensuring that there are controls directed toward preventing or mitigating the risk drivers. To address these and other areas, the handbook advocates a proactive, analytic-deliberative, risk-informed approach to system safety, enabling the integration of system safety activities with systems engineering and risk management processes. It emphasizes how one can systematically provide the necessary evidence to substantiate the claim that a system is safe to within an acceptable risk tolerance, and that safety has been achieved in a cost-effective manner. The methodology discussed in this handbook is part of a systems engineering process and is intended to be integral to the system safety practices being conducted by the NASA safety and mission assurance and systems engineering organizations. The handbook posits that to conclude that a system is adequately safe, it is necessary to consider a set of safety claims that derive from the safety objectives of the organization. The safety claims are developed from a hierarchy of safety objectives and are therefore hierarchical themselves. Assurance that all the claims are true within acceptable risk tolerance limits implies that all of the safety objectives have been satisfied, and therefore that the system is safe. The acceptable risk tolerance limits are provided by the authority who must make the decision whether or not to proceed to the next step in the life cycle. These tolerances are therefore referred to as the decision maker's risk tolerances. In general, the safety claims address two fundamental facets of safety: 1) whether required safety thresholds or goals have been achieved, and 2) whether the safety risk is as low as possible within reasonable impacts on cost, schedule, and performance. The latter facet includes consideration of controls that are collective in nature (i.e., apply generically to broad categories of risks) and thereby provide protection against unidentified or uncharacterized risks.

Dezfuli, Homayoon↗
DOE OSTI2025

Risk assessment of wellbore leakage during underground hydrogen storage

The expansion of renewable energy sources would require large-scale energy storage options to overcome the intermittent nature of these sources. Underground hydrogen storage (UHS) in depleted hydrocarbon reservoirs offers a scalable and practical energy storage solution. These reservoirs are chosen for their availability and large capacity, but the unique properties of hydrogen raise concerns about potential leakage pathways, particularly through wellbores. In this study, we develop and apply, for the first time, reduced-order models (ROMs) specifically designed for efficient leakage risk prediction in UHS systems operating in depleted hydrocarbon reservoirs. Using 3,000 high-fidelity simulation scenarios, we examine the influence of 11 key parameters, including reservoir and aquifer depths, wellbore permeability and porosity, initial saturations of water, oil and gas fractions (hydrogen, light, intermediate, and heavy hydrocarbons), reservoir pressure multiplier, and the aquifer-to-reservoir volume ratio, to simulate leakage behavior over a 1,000-year timescale. We train ROMs using a two-step classification-regression approach, achieving R 2 values exceeding 99 % across all targets. These ROMs effectively capture the leakage evolution and identify critical controls of leakage, guiding the design of mitigation strategies. Results indicate that gas leakage occurs in about 27 % of scenarios as early as five years post-operation, reaching volumes of up to 106 ft3. Oil leakage is less frequent (~17 %) and typically begins decades later. Our findings also show that hydrogen often migrates first, owing to its smaller molecular size and higher buoyancy, followed by heavier hydrocarbons. Over time, these heavier components contribute significantly to the total leaked volume, reinforcing the need for targeted monitoring and remediation strategies. Our analysis highlights that deeper storage reservoirs, shallower aquifers, and low-permeability wellbores significantly reduce leakage risks. In conclusion, this work offers a robust framework for risk-informed UHS deployment, supporting energy security through reliable large-scale hydrogen storage while safeguarding environmental integrity.

08 HYDROGEN↗
DOE OSTI2026

Evaluating Supply Prioritization Strategies for Risk-Informed Decision Making in an Arbitrary Gas Network

Supply disruptions and infrastructure failures in natural gas networks present critical challenges to energy reliability and risk-informed planning. This study evaluates two supply prioritization strategies, Maximum Delivery Prioritization (MDP) and Demand-Based Prioritization (DBP), within an arbitrary natural gas network under conditions of supply shortage. Model performance under both strategies is assessed in response to node and edge failure using demand satisfaction metrics, system-wide and localized dependency scores, and geographic information system (GIS)-based spatial analysis. Results show that DBP better preserves supply for high-demand nodes, while MDP offers broader coverage. The underlying network topology plays a critical role in shaping prioritization outcomes. Integrated GIS visualization enhances the interpretability of vulnerability assessments, revealing structurally critical components and localized vulnerabilities. The proposed framework supports scalable, data-driven decision-making for infrastructure planners and engineers, enabling improved disruption recovery and efficiency in constrained natural gas networks. These insights contribute to the development of more robust energy systems capable of withstanding stress and disruptions.

Peterson, Steven [ORNL] (ORCID:0000000287672998)↗
DOE OSTI2026

Operating Experience Data Analysis for Digital Instrumentation and Control System Reliability and Risk Assessment in Nuclear Power Plants

The implementation of advanced digital instrumentation and control (DI&C) systems in U.S. nuclear power plants (NPPs) can bring significant advancements in reliability, monitoring, and control capabilities. However, these systems also introduce new challenges, particularly in assessing risks such as common-cause failures (CCFs) and establishing robust reliability estimates for DI&C components. Addressing these challenges is critical for ensuring the safe and efficient operation of NPPs. Recently, Idaho National Laboratory was tasked by the U.S. Nuclear Regulatory Commission (NRC) to conduct a DI&C reliability study using operating experience data from the nuclear industry. The two operating experience data sources for the study are the Institute of Nuclear Power Operations’ Industry Reporting and Information System (IRIS) and the NRC’s Licensee Event Report database which is hosted at Idaho National Laboratory at https://lersearch.inl.gov/LERSearchCriteria.aspx. This report provides a comprehensive examination of DI&C systems, including their architecture, operational advantages, and associated challenges. It reviews existing industry DI&C studies and failure mode taxonomies, along with reliability data from various industries. Through a detailed analysis of these databases, the study provides insights into DI&C system performance. Considerations should be given to incorporate DI&C failure data into the NRC's Integrated Data Collection and Coding System and updating the Reliability and Availability Data System to support ongoing DI&C reliability studies. Recommendations are also provided for modeling DI&C reliability and CCF in probabilistic risk assessment, thereby supporting risk-informed decision-making and enhancing the reliability and safety of NPPs.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
NASA NTRS2010

Risk-Informed Decision Making: Application to Technology Development Alternative Selection

NASA NPR 8000.4A, Agency Risk Management Procedural Requirements, defines risk management in terms of two complementary processes: Risk-informed Decision Making (RIDM) and Continuous Risk Management (CRM). The RIDM process is used to inform decision making by emphasizing proper use of risk analysis to make decisions that impact all mission execution domains (e.g., safety, technical, cost, and schedule) for program/projects and mission support organizations. The RIDM process supports the selection of an alternative prior to program commitment. The CRM process is used to manage risk associated with the implementation of the selected alternative. The two processes work together to foster proactive risk management at NASA. The Office of Safety and Mission Assurance at NASA Headquarters has developed a technical handbook to provide guidance for implementing the RIDM process in the context of NASA risk management and systems engineering. This paper summarizes the key concepts and procedures of the RIDM process as presented in the handbook, and also illustrates how the RIDM process can be applied to the selection of technology investments as NASA's new technology development programs are initiated.

Dezfuli, Homayoon↗
NASA NTRS2010

Space Shuttle Probabilistic Risk Assessment (SPRA) Iteration 3.2

The Shuttle is a very reliable vehicle in comparison with other launch systems. Much of the risk posed by Shuttle operations is related to fundamental aspects of the spacecraft design and the environments in which it operates. It is unlikely that significant design improvements can be implemented to address these risks prior to the end of the Shuttle program. The model will continue to be used to identify possible emerging risk drivers and allow management to make risk-informed decisions on future missions. Potential uses of the SPRA in the future include: - Calculate risk impact of various mission contingencies (e.g. late inspection, crew rescue, etc.). - Assessing the risk impact of various trade studies (e.g. flow control valves). - Support risk analysis on mission specific events, such as in flight anomalies. - Serve as a guiding star and data source for future NASA programs.

Boyer, Roger L.↗
NASA NTRS2011

Probabilistic Risk Assessment Procedures Guide for NASA Managers and Practitioners (Second Edition)

Probabilistic Risk Assessment (PRA) is a comprehensive, structured, and logical analysis method aimed at identifying and assessing risks in complex technological systems for the purpose of cost-effectively improving their safety and performance. NASA's objective is to better understand and effectively manage risk, and thus more effectively ensure mission and programmatic success, and to achieve and maintain high safety standards at NASA. NASA intends to use risk assessment in its programs and projects to support optimal management decision making for the improvement of safety and program performance. In addition to using quantitative/probabilistic risk assessment to improve safety and enhance the safety decision process, NASA has incorporated quantitative risk assessment into its system safety assessment process, which until now has relied primarily on a qualitative representation of risk. Also, NASA has recently adopted the Risk-Informed Decision Making (RIDM) process [1-1] as a valuable addition to supplement existing deterministic and experience-based engineering methods and tools. Over the years, NASA has been a leader in most of the technologies it has employed in its programs. One would think that PRA should be no exception. In fact, it would be natural for NASA to be a leader in PRA because, as a technology pioneer, NASA uses risk assessment and management implicitly or explicitly on a daily basis. NASA has probabilistic safety requirements (thresholds and goals) for crew transportation system missions to the International Space Station (ISS) [1-2]. NASA intends to have probabilistic requirements for any new human spaceflight transportation system acquisition. Methods to perform risk and reliability assessment in the early 1960s originated in U.S. aerospace and missile programs. Fault tree analysis (FTA) is an example. It would have been a reasonable extrapolation to expect that NASA would also become the world leader in the application of PRA. That was, however, not to happen. Early in the Apollo program, estimates of the probability for a successful roundtrip human mission to the moon yielded disappointingly low (and suspect) values and NASA became discouraged from further performing quantitative risk analyses until some two decades later when the methods were more refined, rigorous, and repeatable. Instead, NASA decided to rely primarily on the Hazard Analysis (HA) and Failure Modes and Effects Analysis (FMEA) methods for system safety assessment.

Stamatelatos,Michael↗
NASA NTRS2011

NASA Accident Precursor Analysis Handbook, Version 1.0

Catastrophic accidents are usually preceded by precursory events that, although observable, are not recognized as harbingers of a tragedy until after the fact. In the nuclear industry, the Three Mile Island accident was preceded by at least two events portending the potential for severe consequences from an underappreciated causal mechanism. Anomalies whose failure mechanisms were integral to the losses of Space Transportation Systems (STS) Challenger and Columbia had been occurring within the STS fleet prior to those accidents. Both the Rogers Commission Report and the Columbia Accident Investigation Board report found that processes in place at the time did not respond to the prior anomalies in a way that shed light on their true risk implications. This includes the concern that, in the words of the NASA Aerospace Safety Advisory Panel (ASAP), "no process addresses the need to update a hazard analysis when anomalies occur" At a broader level, the ASAP noted in 2007 that NASA "could better gauge the likelihood of losses by developing leading indicators, rather than continue to depend on lagging indicators". These observations suggest a need to revalidate prior assumptions and conclusions of existing safety (and reliability) analyses, as well as to consider the potential for previously unrecognized accident scenarios, when unexpected or otherwise undesired behaviors of the system are observed. This need is also discussed in NASA's system safety handbook, which advocates a view of safety assurance as driving a program to take steps that are necessary to establish and maintain a valid and credible argument for the safety of its missions. It is the premise of this handbook that making cases for safety more experience-based allows NASA to be better informed about the safety performance of its systems, and will ultimately help it to manage safety in a more effective manner. The APA process described in this handbook provides a systematic means of analyzing candidate accident precursors by evaluating anomaly occurrences for their system safety implications and, through both analytical and deliberative methods used to project to other circumstances, identifying those that portend more serious consequences to come if effective corrective action is not taken. APA builds upon existing safety analysis processes currently in practice within NASA, leveraging their results to provide an improved understanding of overall system risk. As such, APA represents an important dimension of safety evaluation; as operational experience is acquired, precursor information is generated such that it can be fed back into system safety analyses to risk-inform safety improvements. Importantly, APA utilizes anomaly data to predict risk whereas standard reliability and PRA approaches utilize failure data which often is limited and rare.

Groen, Frank↗
NASA NTRS2012

An Altair Overview: Designing a Lunar Lander for 21st Century Human Space Exploration

Altair, the lunar lander element of NASA's Constellation program, was conducted in a different design environment than many other NASA projects of similar scope. Because of this relatively unique approach, there are a number of significant success stories that should be considered during the development of any future lunar landers or human spacecraft. This paper is divided into two separate themes; the first is the approach used during the conceptual design studies, including the systematic analysis cycles and the decision making process associated with each: and the second is a summary of the resulting lessons learned that were compiled after looking back at the lifetime of the Project. Altair was terminated before entering Phase B of its design, and was often criticized for being a very heavy and very large vehicle. While there was specific rationale for all of the decisions that led up to that configuration, future design cycles were specifically planned to re-address the mass challenge. Had the project continued, the deliberate, stepwise design process would have converged on an optimized lander design that balanced mass, risk, cost and capabilities. Some of the specific items that will be addressed in this paper include project development strategy, organizational approach and team dynamics, risk-informed design process, mission architecture constraints, mission key driving requirements, model-based systems engineering process, configuration studies, contingency considerations, subsystem overviews and key trade studies. The paper will conclude with a summary of the lessons identified during the Altair project and make suggestions for application to future studies.

Brown, Kendall K.↗
NASA NTRS2015

NASA System Safety Handbook. Volume 2: System Safety Concepts, Guidelines, and Implementation Examples

This is the second of two volumes that collectively comprise the NASA System Safety Handbook. Volume 1 (NASASP-210-580) was prepared for the purpose of presenting the overall framework for System Safety and for providing the general concepts needed to implement the framework. Volume 2 provides guidance for implementing these concepts as an integral part of systems engineering and risk management. This guidance addresses the following functional areas: 1.The development of objectives that collectively define adequate safety for a system, and the safety requirements derived from these objectives that are levied on the system. 2.The conduct of system safety activities, performed to meet the safety requirements, with specific emphasis on the conduct of integrated safety analysis (ISA) as a fundamental means by which systems engineering and risk management decisions are risk-informed. 3.The development of a risk-informed safety case (RISC) at major milestone reviews to argue that the systems safety objectives are satisfied (and therefore that the system is adequately safe). 4.The evaluation of the RISC (including supporting evidence) using a defined set of evaluation criteria, to assess the veracity of the claims made therein in order to support risk acceptance decisions.

Safety Case↗
NASA NTRS2016

Assurance of Fault Management: Risk-Significant Adverse Condition Awareness

Fault Management (FM) systems are ranked high in risk-based assessment of criticality within flight software, emphasizing the importance of establishing highly competent domain expertise to provide assurance for NASA projects, especially as spaceflight systems continue to increase in complexity. Insight into specific characteristics of FM architectures seen embedded within safety- and mission-critical software systems analyzed by the NASA Independent Verification Validation (IVV) Program has been enhanced with an FM Technical Reference (TR) suite. Benefits are aimed beyond the IVV community to those that seek ways to efficiently and effectively provide software assurance to reduce the FM risk posture of NASA and other space missions. The identification of particular FM architectures, visibility, and associated IVV techniques provides a TR suite that enables greater assurance that critical software systems will adequately protect against faults and respond to adverse conditions. The role FM has with regard to overall asset protection of flight software systems is being addressed with the development of an adverse condition (AC) database encompassing flight software vulnerabilities.Identification of potential off-nominal conditions and analysis to determine how a system responds to these conditions are important aspects of hazard analysis and fault management. Understanding what ACs the mission may face, and ensuring they are prevented or addressed is the responsibility of the assurance team, which necessarily should have insight into ACs beyond those defined by the project itself. Research efforts sponsored by NASAs Office of Safety and Mission Assurance defined terminology, categorized data fields, and designed a baseline repository that centralizes and compiles a comprehensive listing of ACs and correlated data relevant across many NASA missions. This prototype tool helps projects improve analysis by tracking ACs, and allowing queries based on project, mission type, domain component, causal fault, and other key characteristics. The repository has a firm structure, initial collection of data, and an interface established for informational queries, with plans for integration within the Enterprise Architecture at NASA IVV, enabling support and accessibility across the Agency. The development of an improved workflow process for adaptive, risk-informed FM assurance is currently underway.

Software Verification & Validation↗
NASA NTRS2017

Risk-Significant Adverse Condition Awareness Strengthens Assurance of Fault Management Systems

As spaceflight systems increase in complexity, Fault Management (FM) systems are ranked high in risk-based assessment of software criticality, emphasizing the importance of establishing highly competent domain expertise to provide assurance. Adverse conditions (ACs) and specific vulnerabilities encountered by safety- and mission-critical software systems have been identified through efforts to reduce the risk posture of software-intensive NASA missions. Acknowledgement of potential off-nominal conditions and analysis to determine software system resiliency are important aspects of hazard analysis and FM. A key component of assuring FM is an assessment of how well software addresses susceptibility to failure through consideration of ACs. Focus on significant risk predicted through experienced analysis conducted at the NASA Independent Verification & Validation (IV&V) Program enables the scoping of effective assurance strategies with regard to overall asset protection of complex spaceflight as well as ground systems. Research efforts sponsored by NASAs Office of Safety and Mission Assurance (OSMA) defined terminology, categorized data fields, and designed a baseline repository that centralizes and compiles a comprehensive listing of ACs and correlated data relevant across many NASA missions. This prototype tool helps projects improve analysis by tracking ACs and allowing queries based on project, mission type, domain/component, causal fault, and other key characteristics. Vulnerability in off-nominal situations, architectural design weaknesses, and unexpected or undesirable system behaviors in reaction to faults are curtailed with the awareness of ACs and risk-significant scenarios modeled for analysts through this database. Integration within the Enterprise Architecture at NASA IV&V enables interfacing with other tools and datasets, technical support, and accessibility across the Agency. This paper discusses the development of an improved workflow process utilizing this database for adaptive, risk-informed FM assurance that critical software systems will safely and securely protect against faults and respond to ACs in order to achieve successful missions.

IV&V↗
NASA NTRS2017

Risk-Significant Adverse Condition Awareness Strengthens Assurance of Fault Management Systems

As spaceflight systems increase in complexity, Fault Management (FM) systems are ranked high in risk-based assessment of software criticality, emphasizing the importance of establishing highly competent domain expertise to provide assurance. Adverse conditions (ACs) and specific vulnerabilities encountered by safety- and mission-critical software systems have been identified through efforts to reduce the risk posture of software-intensive NASA missions. Acknowledgement of potential off-nominal conditions and analysis to determine software system resiliency are important aspects of hazard analysis and FM. A key component of assuring FM is an assessment of how well software addresses susceptibility to failure through consideration of ACs. Focus on significant risk predicted through experienced analysis conducted at the NASA Independent Verification Validation (IVV) Program enables the scoping of effective assurance strategies with regard to overall asset protection of complex spaceflight as well as ground systems. Research efforts sponsored by NASA's Office of Safety and Mission Assurance defined terminology, categorized data fields, and designed a baseline repository that centralizes and compiles a comprehensive listing of ACs and correlated data relevant across many NASA missions. This prototype tool helps projects improve analysis by tracking ACs and allowing queries based on project, mission type, domaincomponent, causal fault, and other key characteristics. Vulnerability in off-nominal situations, architectural design weaknesses, and unexpected or undesirable system behaviors in reaction to faults are curtailed with the awareness of ACs and risk-significant scenarios modeled for analysts through this database. Integration within the Enterprise Architecture at NASA IVV enables interfacing with other tools and datasets, technical support, and accessibility across the Agency. This paper discusses the development of an improved workflow process utilizing this database for adaptive, risk-informed FM assurance that critical software systems will safely and securely protect against faults and respond to ACs in order to achieve successful missions.

Fault management↗
NASA NTRS2014

An Integrated Reliability and Physics-Based Risk Modeling Approach for Assessing Human Spaceflight Systems

This paper presents an integrated reliability and physics-based risk modeling approach for assessing human spaceflight systems. The approach is demonstrated using an example, end-to-end risk assessment of a generic-crewed space transportation system during a reference mission to the International Space Station. The behavior of the system is modeled using analysis techniques from multiple disciplines in order to properly capture the dynamic time- and state- dependent consequences of failures encountered in different mission phases. We discuss how to combine traditional reliability analyses with Monte Carlo simulation methods and physics-based engineering models to produce loss-of- mission and loss-of-crew risk estimates supporting risk-based decision-making and requirement verification. This approach facilitates risk-informed design by providing more realistic representation of system failures and interactions; identifying key risk-driving sensitivities, dependencies, and assumptions; and tracking multiple figures of merit within a single, responsive assessment framework that can readily incorporate evolving design information throughout system development.

Risk assessment↗
NASA NTRS2014

Comparative Analysis of Static and Dynamic Probabilistic Risk Assessment

Implementation of risk-informed design allows the design team to thoroughly explore the risks of a system while iterating the operations concept, design, and requirements until the system meets mission objects and is achievable within constraints. To arrive at a space system design that is likely to meet all constraints placed upon mass, cost, performance and risk, the system requirements must be understood and traded against each other as early as the conceptual design phase. Depending on the project phase and the goals of the risk analysis, various PRA methodologies could be used to produce quantitative risk estimates to enable such a process. In order to better understand the applicability, advantages, and limitations of various PRA methodologies, a comparative analysis of three bottom-up, component-based PRA approaches was performed. The three methods examined are a traditional static fault tree, a fault tree hybrid, and a dynamic Monte Carlo simulation. Each approach was used to assess a generic reaction control system (RCS) thruster pod and mission. The methods are assessed in terms of the process of modeling a system, the actionable information produced for the design team, and the overall fidelity of the quantitative risk evaluation generated. The paper also discusses the applicability of each methodology to the different phases of system development.

Probablistic↗
NASA NTRS2018

NASA’s Mid-Atlantic Communities and Areas at Intensive Risk Demonstration: Translating Compounding Hazards to Societal Risk

Remote sensing provides a unique perspective on our dynamic planet, tracking changes and revealing the course of complex interactions. Long term monitoring and targeted observation combine with modeling and mapping to provide increased awareness of hydro-meteorological and geological hazards. Disasters often follow hazards and the goal of NASA’s Disasters Program is to look at the earth as a highly coupled system to reduce risk and enable resilience. Remote sensing and geospatial science are used as tools to help answer critical questions that inform decisions. Data is not the same as information, nor does understanding of processes necessarily translate into decision support for disaster preparedness, response and recovery. Accordingly, NASA is engaging the scientific and decision-support communities to apply remote sensing, modeling, and related applications in Communities and Areas at Intensive Risk (CAIR). In 2017, NASA’s Applied Sciences Disasters Program hosted a regional workshop to explore these issues with particular focus on coastal Virginia and North Carolina. The workshop brought together partners in academia, emergency management, and scientists from NASA and partnering federal agencies to explore capabilities among the team that could improve understanding of the physical processes related to these hazards, their potential impact to changing communities, and to identify methodologies for supporting emergency response and risk mitigation. The resulting initiative, the mid-Atlantic CAIR project, demonstrates the ability to integrate satellite derived earth observations and physical models into actionable, trusted knowledge. Severe storms and associated storm surge, sea level rise, and land subsidence coupled with increasing populations and densely populated, aging critical infrastructure often leave coastal regions and their communities extremely vulnerable. The integration of observations and models allow for a comprehensive understanding of the compounding risk experienced in coastal regions and enables individuals in all positions make risk-informed decisions. This initiative uses a representative storm surge case as a baseline to produce flood inundation maps. These maps predict building level impacts at current day and for sea level rise (SLR) and subsidence scenarios of the future in order to inform critical decisions at both the tactical and strategic levels. To accomplish this analysis, the mid-Atlantic CAIR project brings together Federal research activities with academia to examine coastal hazards in multiple ways: 1) reanalysis of impacts from 2011 Hurricane Irene, using numerical weather modeling in combination with coastal surge and hydrodynamic, urban inundation modeling to evaluate combined impact scenarios considering SLR and subsidence, 2) remote sensing of flood extent from available optical imagery, 3) adding value to remotely sensed flood maps through depth predictions, and 4) examining coastal subsidence as measured through time-series analysis of synthetic aperture radar observations. Efforts and results are published via ArcGIS story maps to communicate neighborhoods and infrastructure most vulnerable to changing conditions. Story map features enable time-aware flood mapping using hydrodynamic models, photographic comparison of flooding following Hurricane Irene, as well as visualization of heightened risk in the future due to SLR and land subsidence.

Rogers, Laura↗
DOE OSTI2025

Important Human Actions for Advanced Reactors: Implications for Human Factors

As advanced reactor platforms continue to develop and gain traction in the energy sector there is a need for risk-informed, scalable regulations that match that progress. This is a core component of the U.S. Nuclear Regulatory Commission’s proposed Part 53 Rule Making; the Accelerating Deployment of Versatile, Advanced Nuclear for Clean Energy (ADVANCE) Act; and other efforts that seek to update nuclear power regulations. This paper covers one key aspect of that regulatory evolution: Important Human Actions (IHA). In this paper, we discuss how the understanding and definitions of IHAs have changed and what that means for human factors engagement through the process of developing these technologies. Instead of a narrow focus on control actions that led to an increase in core damage risk, the new focus is on IHAs is “wherever they occur.” What this means is that having a highly automated or passive safety system does not eliminate IHAs. Rather, it shifts the focus point to all the actions that enable these systems. Everything from maintenance, to design, to training can be considered an IHA and that dramatically shifts the efforts and level of engagement necessary for human factors to enable these technologies. We discuss the notions of risk-informed human factors that underpin these efforts, give several examples, and briefly describe the risk assessment methodologies that will be needed. In the past, IHAs were identified and then became a focus point of human factors engineering (HFE) activities to ensure a robust evaluation of the task was completed. The future is less clear. HFE for nuclear energy will need to evolve and become more integrated in technology development than ever before.

22 - GENERAL STUDIES OF NUCLEAR REACTORS↗