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NASA NTRSDate not supplied

Impact Outputs for A Representative Extended Duration Artemis Mission

BACKGROUND: As NASA and private industry begin preparation for long-duration spaceflight, quantifying the impact that potential human health and performance capabilities have on crew health outcomes is imperative for medical risk mitigation. NASA’s Informing Mission Planning via Analysis of Complex Tradespaces tool (IMPACT) applies Probabilistic Risk Assessment (PRA) methodology to estimate these outcomes. OVERVIEW: As NASA prepares to return to the Moon, medical system planning has already begun for extended Artemis missions, which will see humans spending months at a time in cis-lunar space and on the surface of the Moon. The Long Duration Lunar Orbital and Lunar Surface (LDLOLS) design reference mission (DRM) lasts 9 months, including 3 months on the lunar surface, and involves 2 male and 2 female crewmembers. LDLOLS assumes no extravehicular activities (EVAs) in orbit, but, while on the lunar surface, involves 2-4 EVAs/month in a pressurized rover and 2-4 EVAs/month in an unpressurized rover or on foot. This DRM assumes a physician level Crew Medical Officer with commensurate knowledge, skills, and abilities. The IMPACT tool was utilized to estimate in-flight medical risk for this mission. More specifically, 100,000 simulations of this DRM were modeled, and overall estimates for loss of crew life (LOCL), need for evacuation (RTDC; return to definitive care), and crew task time lost (TTL; a measure of disability) were calculated. A recommended medical capability set, with appropriate mass and volume constraints, was also generated. DISCUSSION: This abstract reviews the IMPACT-derived risk for these mission outcomes with and without treatment, a macroscopic look at the total mass and volume necessary for full diagnostic and treatment capability, and how these change with input mission parameters.

J G Steller↗
NASA NTRSDate not supplied

Derivation of the Most Influential Medical Conditions for An Extended Duration Artemis Mission

BACKGROUND: The risk of loss of mission due to medical conditions may be influenced by loss of crew life (LOCL), need for evacuation (RTDC; return to definitive care), and crew task time lost. Predicting what medical conditions are most likely to lead to crew morbidity and mortality may influence medical system design, clinical capability prioritization, and research strategies. NASA’s Informing Mission Planning via Analysis of Complex Tradespaces tool (IMPACT) applies Probabilistic Risk Assessment (PRA) methodology to assess these risks. OVERVIEW: A team of subject matter experts (SME) from a variety of medical disciplines developed a consensus-based process to determine 120 of the most clinically relevant medical conditions for long-duration exploration missions (LDEMs) . This IMPACT Condition List (ICL) expanded upon previous work done for Integrated Medical Model (IMM). For each condition a best-case and worst-case definition were derived. These definitions were used to identify probability of occurrence, proportion of cases that are best case vs. worst case, clinical phase duration, and risk of outcomes (task time loss [TTL], RTDC, and LOCL) for both treated and untreated states. These data were sources from existing spaceflight databases (e.g. Longitudinal Survey of Astronaut Health), relevant models (e.g. the ISS fire model), and/or terrestrial literature. Each condition was then tied to diagnostic and therapeutic resources and capabilities. IMPACT was then run for the LDLOLS DRM (see Abstract #2 for this panel). DISCUSSION: This abstract will present the process for generating the IMPACT condition list, the relevant data for each clinical condition, and present results for the ten most influential conditions impacting LOCL, RTDC, and TTL for a representative extended duration Artemis mission.

A Nelson↗
NASA NTRSDate not supplied

Impact-Identified Medical Capabilities with Largest Effect on Medical Risk for an Extended Duration Artemis Mission

Historically, identifying resources to include in a medical system has been based on heuristically guided clinical subject matter expert assessment. Probabilistic risk assessment (PRA) and tradespace analysis have the power to simplify and increase the fidelity of this traditional approach by providing initial risk estimates and system design solutions that fit within the specified constraints. This will be especially important as the increased mission complexity, distance from Earth, and duration of LDEMs is likely to drive an increase in mission medical risk. NASA’s Informing Mission Planning via Analysis of Complex Tradespaces tool (IMPACT) is designed to do just that. IMPACT uses an evidence based medical database of conditions likely to affect LDEM outcomes and a PRA computational engine to estimate how medical conditions and included medical capabilities affect mission outcomes. We identified the 10 medical conditions with the largest effect on medical risks and determined what medical system capabilities affected risk reduction the greatest.

Anderson A↗
NASA NTRSDate not supplied

Spaceflight Over the Last Ten Years: Failures and Fix-ups 2013 - 2022 RAMS XV Conference

This project is an overview and analysis of the past ten years (2013 – present) in global spaceflight, highlighting the orbital launches of countries, particularly the failures that occurred, the reasons they occurred, and a breakdown of the related statistics and background information. The analysis is conducted from a perspective of reliability and maintainability engineering and Probabilistic Risk Assessment (PRA) to formulate a quantifiable understanding of the data and how it is pertinent to Safety and Mission Assurance (SMA) in spaceflight. There is a breakdown by country or group, timelines, and number of launches. The failures over the years are categorized, all given a broad analysis of subsystem failures and details of events. A few failures are given a more in-depth analysis of root causes and failure modes determined by their unique or common nature. The data is retrieved from online, publicly available sources.

Quinn Slaugenhoupt↗
NASA NTRSDate not supplied

Improving the Fidelity of Capability & Resource Weighting in A Probalistic Risk Assessment Model for Spaceflight

INTRODUCTION NASA’s Informing Mission Planning via Analysis of Complex Tradespaces (IMPACT) tool uses Probabilistic Risk Assessment (PRA) to provide an evidence-based, data-driven estimate of how medical system capabilities affect mission outcomes. IMPACT maps condition incidence to available resources thereby facilitating the calculation of outcome metrics that allow the estimation of mission medical risk. Conditions can be nominally categorized as either treated or untreated depending on the availability of necessary diagnostic and therapeutic capabilities. This categorization enables IMPACT to estimate the effect of various medical system configurations on mission outcomes such as crew mortality, disability, crew member down-time, return to duty/recovery, and need for evacuation. IMPACT currently employs an equal weighting, “partial credit” approach to define treatment in which each of the capabilities associated with a given condition contributes an equal amount to management of the condition. This feature enables IMPACT to report values in between “fully untreated” and “fully treated” based on the proportion of capabilities available within the model. However, as is normal in medical/clinical practice, not all individual capabilities contribute equally to medical care. For example, the ability to provide intramuscular epinephrine during an anaphylactic episode contributes more likelihood of overall management success than does the administration of oral diphenhydramine. We hypothesize that weighting the relative contribution of each capability to each specific condition will improve outcome prediction and therefore will better provide mission planners with more nuanced and accurate options when designing space medical systems. METHODS Using a five-point Fibonacci scaling sequence (1, 2, 3, 5, 8) subject matter experts from NASA’s Exploration Medical Capabilities (ExMC) element assigned relative contribution weighting values to each identified capability within IMPACT. Since the relative importance of each capability varies depending on the specific condition, the resulting “partial” weighting was completed for more than 1,600 individual weighting assignments for 666 capabilities across 121 conditions. Each assignment required three-physician concurrence based on the overall importance of the capability to the diagnosis and management of the condition being considered and the difficulty with which it could be improvised by the crew. Once complete, 100,000 IMPACT simulations were run for a 6-month Lunar mission with a 30-day surface stay to evaluate the effect of this modification of the model. RESULTS Partial weighting significantly decreased predicted task time loss (TTL), evacuation, and loss of crew life without causing significant changes to the recommended medical system design. CONCLUSIONS The paucity of real-world referent data to support long-duration space missions of this type limits the ability to judge one predictive analytics method as superior to another. However, since the proposed method significantly reduces and optimizes outcome risks—without changing the medical system design—incorporating a partial weighting methodology is likely to provide a more accurate and operationally-relevant representation of medical risk without compromising IMPACTs ability to inform overarching medical system requirements.

Steller JG↗
NASA NTRSDate not supplied

Supply and Resource Management to Progressively Enable EIMO

BACKGROUND: Current medical operations in Low Earth Orbit (LEO) allow for real-time audio-video communication with a flight surgeon at mission control, resupply, and medical evacuation to earth on the order of hours. As mission profiles change from LEO to the Moon, Mars, and beyond, medical risk as a contribution to overall mission risk is anticipated to rise substantially. Concurrently, due to the distance, the medical systems on board vehicles proposed for these mission types are expected to have reduced mass and volume allocation. Together, astronaut crews will be at a higher risk of major medical events, be required to perform a broader set of tasks, and have substantially reduced resources and support to do so. Earth Independent Medical Operations (EIMO) aims to identify and fill the gaps present in this progressively changing paradigm. OVERVIEW: Medical supplies, resources, and skills are central to spaceflight medical systems. Vehicles used for non-LEO missions are anticipated to be smaller and thus the medical system will also need to have reduced mass, volume, and power. Medical resources are another form of consumable and may need resupply or pre-deployment to meet crew needs. One particular concern is the degradation of medications which become less efficacious and potentially toxic with time, particularly given environmental conditions such as temperature, humidity, oxygen, and radiation which have not yet been fully studied. Supply and resource management in LEO is dependent on resupply, however the supply chain of transporting equipment does not yet have a clear infrastructure for missions beyond LEO. DISCUSSION: EIMO is intended to systemically identify and fill these gaps with forward-looking solutions. In mission monitoring of resources with technology like RFID, improving medical resource longevity, targeted resupply and careful pre-mission planning will be central to facilitate crew health and performance. One approach to optimizing resources is the Informing Mission Planning via Analysis of Complex Tradespaces (IMPACT) tool, which uses probabilistic risk assessment (PRA) to quantitatively predict medical risk and identify resources and skills that mitigate this risk. This evidence based, quantitative analysis prediction tool and several other approaches to meeting the challenge of supply and resource management are discussed.

Arian Anderson↗
NASA NTRSDate not supplied

Long-Term Health Metric Development Effort

INTRODUCTION Probabilistic Risk Assessment (PRA) is a methodology applied when high-stakes decisions need to be made about complex systems. PRA often uses risk minimization to aid decision making, such as when establishing vehicle requirements or resource allocations. The NASA Human System Risk Board (HSRB) maintains the human spaceflight risk postures, many of which have in-mission medical outcomes, but the full risk set also includes performance and Long-Term Health (LTH) outcomes. An effort is underway to determine the dependencies between LTH risk outcomes and mission characteristics and to identify metrics for quantifying LTH outcomes. The LTH metrics will be incorporated into future PRA tools currently under development to support crew health and performance decision making. LONG-TERM HEALTH (LTH) RISK LTH risk encompasses the timeframe from immediately post-flight, through the rest of an astronaut’s career, through retirement, and until death. LTH outcomes include the time and interventions needed for the astronaut to return to preflight physiological states after experiencing spaceflight hazards and recovery from any in-mission medical events that persist into the post-flight timeframe. It includes chronic complications that may arise due to experiencing in-flight medical conditions or injuries and medical conditions that occur later in life with a higher probability of occurrence or with more severity because of their spaceflight exposure. Finally, LTH outcomes can also include a reduction in life expectancy due to spaceflight exposures. Eighteen of the HSRB risks contain an LTH component, each with a unique incidence rate and consequence severity. ON-GOING LTH METRIC DEVELOPMENT EFFORTS Based on guidance from a stakeholder workshop held on June 1, 2023, only LTH outcomes with causes tied to spaceflight experience that are significantly different from normal healthy aging and which can be affected by changes in in-mission resources are targeted for inclusion within the PRA modeling efforts. Current on-going efforts include a sensitivity analysis of potential in-flight medical conditions to determine which conditions may persist into post-flight and how the consequences may be affected by in-mission medical resources. Also underway is determination of differences in the time for a return to preflight physiological baselines when in-flight countermeasures are available versus when they are not. Analyses performed with publicly available astronaut data and collaborations with the Lifetime Surveillance of Astronaut Health team are being designed to understand which LTH outcomes differ significantly from natural healthy aging. Information exchanges are also occurring with LTH risk custodians to understand how they quantify outcomes. FUTURE PLANS Risk characteristics will be determined for each LTH risk that meets our inclusion criteria and the dependencies of their outcomes to in-mission resources and mission characteristics will be established. The individual risks will be integrated together into one or more high level LTH metrics for inclusion in the PRA tool, so that LTH risks can be considered along with in-mission risks during crew health and performance system decision support trade studies.

B. E. Lewandowski↗
NASA NTRS2024

Quantifying Risk to Improve Medical System Design for Long Duration Artemis Missions: A Demonstration of NASA's IMPACT Tradespace Analysis Tool

BACKGROUND NASA’s human exploration spaceflight missions to the Moon and Mars present unprecedented challenges for in-mission medical care. A greater distance from Earth will mean increased mission durations, communication delays, limited to no resupply opportunities, and constraints on the evacuation of ill or injured crew. Mass, volume, and power will be limited while higher demands will be placed on the crews to manage medical events. NASA’s Moon to Mars exploration strategy outlines increasingly complex Artemis missions both in terms of duration and operations. In these more challenging deep space missions, it is important to quantitatively estimate the human system risk attributable to medical conditions and use these estimates to advance medical system design. METHODS IMPACT (Informing Mission Planning via Analysis of Complex Tradespaces) is a probabilistic risk assessment (PRA) and tradespace analysis tool developed by NASA to advance exploration mission medical system design. IMPACT v1.0 includes a novel evidence library baselined to exploration environments; an expanded list of 119 medical conditions; a large increase in the number of medical resources and the flexibility of their use; and the ability for rapid and iterative analysis. Medical system risk estimates include loss of crew life, consideration of the need for return to definitive care (medical evacuation), and an estimate of crew time affected due to medical conditions. A notional long duration lunar orbit and lunar surface design reference mission (DRM) was chosen with a 4-astronaut crew to mimic a foundational exploration Artemis mission. The DRM profile includes outbound transit on Orion, Gateway space station rendezvous in lunar orbit, 6 months on the Lunar surface with extravehicular activity (EVA), return rendezvous with Gateway, and transit back to Earth. RESULTS/DISCUSSION: Overall, IMPACT successfully quantified medical risk and derived an optimal medical system to support crew on a long duration lunar mission. In this DRM, the calculated loss of crew life from a medical event was 0.008 events per mission, risk of potential need for evacuation was 0.30 events per mission, and cumulative crew time affected by medical conditions was 103 days. The medical conditions that most contributed to medical risk were decompression sickness, trauma, and respiratory failure. The conditions that had the largest effects on crew performance included musculoskeletal injuries and lunar dust exposure. The IMPACT-generated medical system included resources that target the most common and highest risk conditions and performed as expected. This demonstrates the value of the IMPACT tool in medical system design for human exploration spaceflight missions.

Arian Anderson↗
NASA NTRS2024

Risk of Bone Fracture due to Spaceflight-induced Changes to Bone

The Human Research Program (HRP) is taking a biomechanical approach to assessing subsequent fracture risk in active astronauts as a consequence of spaceflight exposure. Triennial testing of active and retired astronauts continues as Space Medicine monitors for a premature diagnosis of primary osteoporosis, which is associated with age-related bone loss and skeletal fragility. This updated 2023 Fracture Evidence Report has expanded the description of skeletal changes to capture the full effects of spaceflight on bone: • Recent analysis of fractures from health records of the full astronaut cohort, suggests an increased incidence rate of hip and spine fractures in astronauts following longer spaceflight duration flights compared to incident rates found in shorter duration flights. • Routine preflight-to-postflight surveillance by DXA (dual-energy x-ray absorptiometry) does not provide the full detection of loss and recovery in the long-duration (LD) astronaut nor the full recovery of hip trabecular bone. • The inclusion of hip quantitative computed tomography (QCT) in flight studies delineates effects of spaceflight, of countermeasures, and of post-flight recovery on cortical and trabecular bone parameters—some of which are verified predictors of hip fracture in the aged. • QCT detects and compares the distinct countermeasure effects of the pharmaceutical alendronate and of resistive exercise (on the Advanced Resistive Exercise Device, ARED) in specific cortical and trabecular bone sub-regions during spaceflight. • A published comparison of QCT-determined loss rates of hip trabecular bone in LD astronauts compared to terrestrial cohorts suggest that accelerated loss rates in trabecular volumetric BMD (vBMD) during spaceflight might be analogous to skeletal effects of accelerated loss rates in females due to menopause, potentially leading to disruptions in trabecular microarchitecture. • A dataset of finite element (FE) estimates of hip bone strength in aging terrestrial cohorts (spanning astronaut age-range) provides comparative context for changes in the FE of hip bone strength in LD astronauts, including comparison (force unit of newton) to percentiles (50th, 75th, and 100th) of sex-matched aged humans with hip fractures. • Risk of fracture, due to the mechanical overloading of bones, is being updated with IMPACT, the next-generation tool suite for probabilistic risk assessment (PRA) for exploration missions being created by the Exploration and Medical Capability Element (ExMC) at NASA. IMPACT is currently in development and will not be included in this 2024 update. The risk for fracture necessitates understanding the relationship between applied loads to bone and the biomechanical competence of bone. The Risk for Early Onset Osteoporosis focuses on the weakened condition of bone (including development of new technologies, measurements of novel skeletal attributes, translation of multiple measures to an index of bone fragility, and interpretations of data used to reflect a weakened bone), while the Risk for Fracture assesses factors that influence the probability an astronaut would encounter applied loads exceeding the biomechanical competence of bones, resulting in fracture. This Evidence Report combines the research gaps and tasks associated with both risks.

Fracture↗
NASA NTRS2025

Assessment of Model Outcomes Between the Integrated Medical Model (IMM) and the Medical Extensible Dynamic Probabilistic Risk Assessment Tool (MEDPRAT)

The Medical Extensible Dynamic Probabilistic Risk Assessment Tool (MEDPRAT) is a computational model that provides human health and medical risk predictions for crewed spaceflight missions. MEDPRAT utilizes discrete event modeling and dynamic probabilistic simulation to predict critical mission outcomes (total medical events, crew health index, quality time lost, loss of crew life, removal to definitive care), condition occurrences, and resource consumption. Input parameters for MEDPRAT include crew attributes (e.g., sex), types of mission activities (e.g., whether and where crew members perform an extravehicular activity (EVA)), available resources, treatment information, and probability distributions for medical conditions. As an evolution of the Integrated Medical Model (IMM), MEDPRAT provides enhanced capabilities and higher fidelity, and incorporates more appropriate assumptions for long-duration spaceflight. IMM is the currently accepted standard for quantifying spaceflight mission medical risk in NASA operations that uses a probabilistic risk assessment (PRA) approach. MEDPRAT builds on the same logical foundation as IMM but implements the model architecture through highly optimized Monte Carlo sampling methods. An analysis is performed comparing the outputs from IMM with those from MEDPRAT V1.0 and V2.0 for the same reference missions in order to quantify similarities and differences in the model outcomes. The juxtaposition between IMM and MEDPRAT V1.0 and 2.0 shown in this report demonstrates that these two models generate very similar results; where differences in outcomes are shown, these are in accordance with the underlying assumptions and differences in the model architectures. This validation effort further establishes the credibility and reliability of the MEDPRAT software.

Matthew T Prelich↗
DOE OSTI2021

Optimization of Mitigating System Performance Index to Improve Nuclear Power Plant Safety and Efficiency

MSPI (Mitigation System Performance Index) is one of the risk-informed, plant-specific performance indicators of NRC’s Reactor Oversight Process. MSPI is used by the regulator and nuclear industry to monitor and assess the performance of plant mitigating systems. In this project, a calculation tool has been developed by incorporating the plant operation data, Probabilistic Risk Assessment (PRA) data, and industry baseline values to automate the calculation process of MSPI and the generation of the report. This is the first stage in an effort to optimize the MSPI through advanced artificial intelligence (AI) and machine learning (ML) techniques to improve nuclear power plant safety and efficiency.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2021

Dynamic, risk informed decision support systems and methods

The present disclosure is directed to a decision support system or tool based on a Bayesian Network (BN) framework. The diagnostic support tool is created by using advanced Probabilistic Risk Assessment (PRA) method(s) to construct Bayesian Networks (BNs) that form a Bayesian Decision Support Process (BDSP) to provide science-based decision support for understanding and managing events in complex systems. In an embodiment, the PRA method(s) may include Discrete Dynamic Event Trees (DDETs) and simulations.

Groth, Katrina↗
DOE OSTI2021

Modular High Temperature Gas-Cooled Reactor: Accident Analysis

Licensing Modernization Project (LMP) Risk Informed Approach Selection of Licensing Basis Events (LBEs) Frequency-Consequence Target LBE Cumulative Risk Targets Structures, Systems, and Components (SSC) Safety Categories Classification Evaluation of Defense in Depth (DID) Use of Probabilistic Risk Assessment (PRA) in LMP Process PRA Policy Statement American Nuclear Society (ANS) Non-Light-Water Reactor (non-LWR) PRA Standard

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2023

Probabilistic Risk Assessment of a Light Water Reactor Coupled with a High-Temperature Electrolysis Hydrogen Production Plant

This paper presents recent updates on the Level 1 Probabilistic Risk Assessment (PRA) of Light Water Reactors (LWRs) coupled with a hydrogen production plant. It provides the overview of past results on the PRA for Pressurized Water Reactors (PWRs) and Boiling Water Reactors (BWRs) coupled to a 1150 MW High Temperature Electrolysis Facility (HTEF), as well as the latest research results for a smaller 100 MW HTEF facility. Differences between the two HTEF designs are listed. Key differences include the amount and quality of diverted LWR steam, complexity of the Heat Extraction System (HES), and the electrical power source for the HTEF plant. A Failure Mode and Effect Analysis (FMEA) was conducted for the new HTEF design, and the LWR PRA models were modified in the SAPHIRE risk assessment tool to account for the newly identified risk contributors. These include the steam loss event at the HES system, the electrical overcurrent event at the HTEF facility and at the transmission line from the LWR plant, and the hydrogen detonation event at the HTEF facility. The coupling of LWRs with a 100 MW HTEF increases the frequency of several initiating events. For the reference PWR, the largest frequency increase is for the steam line break event at 5.5%. While for the reference BWR, the largest frequency increase is for the switchyard-related Loss of Offsite Power (LOOP) event at 0.11%. The overall plant risk increases by 6.56% and 0.03% for PWR and BWR reference plants respectively. It is found that these risk metrics satisfy the safety criteria of both 10 CFR 50.59 and Regulatory Guide 1.174 licensing pathways.

08 HYDROGEN↗
DOE OSTI2020

Use of Flooding Probabilistic Risk Assessment

General slide information on using flooding Probabilistic Risk Assessment (PRA) taken from published INL reports or public Nuclear Regulatory Commission (NRC) information. Topics covered are: SDP related to flooding in US Door integrity tests at Idaho State University Smoothed Particle Hydrodynamics for external flooding NRC-INL Flood Barrier project

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2022

The Publication and Endorsement of the ASME/ANS Probabilistic Risk Assessment Standard for Advanced Non-Light Water Reactor Nuclear Power Plants

Due to growing interest in non-light water reactor (NLWR) concepts, the predecessor to the American Nuclear Society (ANS)/American Society of Mechanical Engineers (ASME) Joint Committee on Nuclear Risk Management (JCNRM) initiated development of a NLWR probabilistic risk assessment (PRA) standard in 2006. The developed standard, released for trial use in 2013, was the first integral PRA standard created by the JCNRM, containing requirements ranging from the development of initiating events to the analysis of offsite radiological consequence. Based on feedback from pilot applications of the trial standard, a revised version of the standard was developed and balloted in 2020, with unanimous passage by the JCNRM and formal publication as an American National Standards Institute (ANSI) standard in 2021. The paper provides an overview of the standard and its development process. In addition, the paper reviews the latest status of U.S. Nuclear Regulatory Commission endorsement efforts through Regulatory Guide 1.247.

Fleming, K.↗
DOE OSTI2024

Dose Consequence and Probabilistic Risk Assessment Integration into Digital Documented Safety Analysis

This is an intern poster presentation. The current reactor authorization process is complex and error prone. The development of a digital Documented Safety Analysis has been proposed to provide an automated and integrated solution to enhance the design and authorization process. The digital DSA will consist of interlinked models, analyses, and reports, all of which will be updated using automated workflows when design changes are made. This poster examines the integration of the probabilistic risk assessment (PRA) with the transient and dose consequence analyses. A PRA for a generic high temperature gas-cooled reactor (HTGR) has been constructed which will drive the input parameters for a transient analysis model currently being constructed. Dose consequence will be determined using the results of the transient analysis and the Radiation Safety Analysis Computer (RSAC) code. Dose consequence data will then be input back into the PRA to drive design parameters.

42 ENGINEERING↗
DOE OSTI2025

Advancing Multi-Hazard Risk and Safety Considerations for Aging Nuclear Facilities

While probabilistic risk assessment (PRA) of nuclear facilities is expected to include internal and external hazards for a risk-informed and performance-based design, the current state of practice treats each hazard independently. However, such an independent treatment of hazards may not account for the correlations between different hazards and their response of and damage to the structures, systems, and components (SSCs) in a plant resulting in underestimating the overall risk. This project proposes to advance the multi-hazard PRA of nuclear facilities to more adequately evaluate concurrent hazards and contribute to an increased safety of nuclear plants. A framework for multi-hazard PRA will be developed by identifying concurrent hazard events (both internal and external) and event sequences that include interdependencies through the response of SSCs. An example application of the multi-hazard PRA framework will be demonstrated by considering a generic pressurized water reactor (PWR) subjected to seismic and internal flooding hazards. Computational models for the response of components will be developed to generated multi-hazard fragility surfaces under seismic and flooding loads. A PRA model consisting of event and fault trees will also be developed to quantify the multi-hazard risk profile and compare it with the independent hazard risk profile. Overall, by advancing the multi-hazard PRA of nuclear facilities, this project enhances nuclear safety and reduces costs by mitigating unforeseen consequences caused by correlations between concurrent hazards.

97 - MATHEMATICS AND COMPUTING↗