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DOE OSTI2024

An Evaluation of The Dynamic Physical Security Risk Assessment Methodology for Fleet-Wide Applications

The requirements for U.S. nuclear power plants to maintain a large onsite physical security force contribute to their high operational costs. The cost of maintaining the current physical security posture is approximately 10% of the overall operation and maintenance budget for commercial nuclear power plants. The goal of the Light Water Reactor Sustainability (LWRS) program’s physical security pathway is to develop tools, methods, and technologies and provide the technical basis for an optimized physical security posture. The conservatisms built into current security postures may be analyzed and minimized to reduce security costs while still ensuring adequate security and operational safety. The research performed at Idaho National Laboratory within LWRS program’s physical security pathway has successfully developed a dynamic force-on-force modeling framework using various computer simulation tools and integrating them with the dynamic assessment Event Modeling Risk Assessment using Linked Diagrams (EMRALD) tool. This integrated process for physical security analysis is named Modeling and Analysis for Safety Security using Dynamic EMRALD Framework (MASS-DEF). This document provides an update on the progress in applying the MASS-DEF process to an operating commercial nuclear power plant as well as additional industry feedback regarding use of the tool for other physical security risk-informed topics. This report is only a summary of the progress and does not contain specific modeling results as those contain sensitive security information. Previous reports described how a user could integrate their plant-specific force-on-force models with the dynamic simulation tool EMRALD, model operator actions, and integrate with probabilistic risk assessment tools, such as CAFTA (Computer Aided Fault Tree Analysis System) or SAPHIRE (Systems Analysis Programs for Hands-on Integrated Reliability Evaluations), and with thermal-hydraulic tools, such as RELAP-5 or MAAP. Previous reports applied various combinations of available simulations codes with EMRALD using generic plant models to demonstrate how to perform the analysis. This report is an update the progress of applying the dynamic computational framework to an actual nuclear facility using their security scenarios and timelines. This report also provides an update to the procedural guidance for the MASS-DEF process and an overview of the generic models available for use by utilities. This report does not contain any plant’s sensitive information and/or safeguards information. This study’s purpose was to verify that the results achieved using generic models are similar to actual plant results and refine our guidance on the use of the framework. This assessment enables further analysis, such as what-if scenarios and staff-reduction evaluation, thereby optimizing physical security at plants.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

NASA NTRS2003

Bayesian estimation of dose thresholds

An example is described of Bayesian estimation of radiation absorbed dose thresholds (subsequently simply referred to as dose thresholds) using a specific parametric model applied to a data set on mice exposed to 60Co gamma rays and fission neutrons. A Weibull based relative risk model with a dose threshold parameter was used to analyse, as an example, lung cancer mortality and determine the posterior density for the threshold dose after single exposures to 60Co gamma rays or fission neutrons from the JANUS reactor at Argonne National Laboratory. The data consisted of survival, censoring times and cause of death information for male B6CF1 unexposed and exposed mice. The 60Co gamma whole-body doses for the two exposed groups were 0.86 and 1.37 Gy. The neutron whole-body doses were 0.19 and 0.38 Gy. Marginal posterior densities for the dose thresholds for neutron and gamma radiation were calculated with numerical integration and found to have quite different shapes. The density of the threshold for 60Co is unimodal with a mode at about 0.50 Gy. The threshold density for fission neutrons declines monotonically from a maximum value at zero with increasing doses. The posterior densities for all other parameters were similar for the two radiation types.

NASA Discipline Radiation Health↗

DOE OSTI2025

Novel Results Visualization for Dynamic PSA and New Modeling Features in EMRALD

The Event Modeling Risk Assessment Linked Diagram (EMRALD) tool, developed at the Idaho National Laboratory (INL), was designed to simplify the creation of dynamic models and support various research projects. One of the primary goals of EMRALD was to provide visual methods for modeling. EMRALD consists of two main components: a web-based user interface for model development and a solve engine for running model simulations. Over time, it has evolved to meet the diverse needs of its users. Initially, EMRALD's results were simple text outputs with final key state percentages and uncertainty bounds. However, because EMRALD utilizes a three-phase discrete event simulation and tracks the paths of each simulation run leading to a key state, there is significant potential to analyze large sets of path results data, including state paths, events, and timing. Visualizing this data meaningfully posed a challenge. To address this, a novel time-based Sankey diagram was developed. EMRALD exports results data in a format that can be opened in this Sankey viewer, allowing users to visualize paths, occurrences, events, and probability data for the entire simulation run in a single diagram. Moreover, when EMRALD was first created, there were limited tools capable of meeting its graphical requirements, many of which are no longer supported. In 2024, a new web-based interface was developed using modern graphing tools, enabling additional modeling features. This paper discusses the new dynamic PSA results visualization capability and the enhanced modeling tools available in EMRALD.

97 - MATHEMATICS AND COMPUTING↗

NASA NTRS2019

Mitigation Strategies for Space Radiation Health Risks

Astronauts embarking on missions beyond low Earth orbit (LEO) will be exposed to a radiation field that may increase the risks of developing cancer, cardiovascular diseases, central nervous system disorders, and immune decrements. Operational parameters will be the primary determinants of crew radiation exposure. NASA uses integrated design tools and risk models to optimize these parameters to minimize radiation exposure. NASA is also considering medical countermeasures (MCMs) to reduce radiation-associated health risks. MCMs for potential use in space-based applications can be developed from a variety of sources, including: a) population-based chemoprevention trials against targeted diseases b) drug development efforts focused on treating acute effects from accidental radiation exposures c) drug development to mitigate side effects of radiotherapy d) mechanistic studies of distinct damage caused by high charge (Z) and energy (HZE) radiation. Use of agents developed for other applications, or repurposed, is advantageous because long-term safety in humans is already established.

Huff, Janice L.↗

NASA NTRSDate not supplied

Medical Countermeasure Requirements for Meeting Permissible Radiation Exposure Limits in Space

The space radiation environment consists of ionizing radiation that poses healthrisks to crew members who embark on a mission to Mars. NASA requiresthat astronaut career radiation limits for the Risk of Exposure Induced Death(REID) should not exceed 3% at the upper 95% confidence level for cancermortality. However, the lifetime career limit is likely to be exceeded for eventhe shortest round-trip mission scenario to Mars. As such, approaches fordirectly reducing the radiation risk, despite the large uncertainties, are beinginvestigated. A recent study showed that medical countermeasures (MCM)which reduced background cancer mortality rates may be effective in mitigatingthe REID, where the data employed in the sensitivity analysis were limited tocohort studies of aspirin and warfarin. The present work addresses the generalMCM requirements that are needed to meet the lifetime career exposure limitsby examining modifications to the background cancer mortality rates, radiationquality factor, and low-LET radiation risk models for a Mars mission scenario.These results may be used to help inform decision-makers about potentialexperimental measurements that facilitate the greatest propensity for MCM risk reduction.

Charles M Werneth↗

DOE OSTI2023

Analysis of Tasks in Autonomous Systems Using the EMRALD Dynamic Risk Assessment Tool

An autonomous system refers to the system that has the power and ability for self-governance in the performance of system functions. Autonomous systems have been actively pursued in a variety of domains such as automotive, aviation, maritime, medicine, and nuclear fields. As an unmanned concept employing the highest automation level, the autonomous system basically performs most of the work in normal operations or emergency situations. However, despite advances in technology, many researchers have noted these systems still require human actions. The nature of human actions on autonomous systems is different than the human actions that are considered in existing systems. Nevertheless, only a few studies have been conducted on 1) characterizing the different types of errors and risks associated with human actions interacting with autonomous systems and 2) how to evaluate human actions in the autonomous operations. As a starting point, this study aims to investigate differences of tasks in autonomous operation compared to those in existing nuclear power plant operation using the Event Modeling Risk Assessment Using Linked Diagram (EMRALD) software. In this paper, insights aspect of human error and time are derived out and discussed based on the output of the EMRALD models.

99 GENERAL AND MISCELLANEOUS↗

DOE OSTI2025

Copula based Damage Detection for Structural Health Monitoring

This project utilizes copulas for damage detection in a Structural Health Monitoring (SHM) application. A copula-based system was chosen for the benefit of multivariate joint distribution with a goal to detect damage based on how the system as a whole reacts rather than one or two sensors by themselves. Copulas are commonly used in the field of finance for risk modeling based on two or more random inputs. A few applications in the field of SHM and Non-Destructive Evaluation (NDE) have been researched mostly on risk or reliability of the structure. The goal of this project is to determine if a copula-based approach can be used for damage detection. An unsupervised learning method was desired to reduce the dimensionality, minimal training, and be a faster evaluation method than other unsupervised methods. If a copula method can be used to detect damage what additional information on the damage can be interpreted. The remainder of this report will go over the background needed, SHM methodology, SHM applications, conclusions, and future developments.

47 OTHER INSTRUMENTATION↗

DOE OSTI2021

Generic Pressurized Water Reactor Model for SAPHIRE

Generic Pressurized Water Reactor Model for SAPHIRE This report contains a data dump from a SAPHIRE Generic Pressurized Water Reactor (PWR) model. The intent is to have this information reviewed for export control and classification so that the generic model can be used external to INL. The facility model is not applicable to any existing nuclear reactors. The Generic PWR model does not represent any existing power plant and was created to support research and training purposes. Three distinct types of data are used to create a SAPHIRE risk model: - Event trees representing typical PWR sequences - Fault trees representing generic system performance - Basic events (e.g., component failure information) Where possible, we have taken information from publicly available documents and referenced that information tagged to a specific item.

99 GENERAL AND MISCELLANEOUS↗

NASA NTRS2010

Development of NASA's Accident Precursor Analysis Process Through Application on the Space Shuttle Orbiter

Accident Precursor Analysis (APA) serves as the bridge between existing risk modeling activities, which are often based on historical or generic failure statistics, and system anomalies, which provide crucial information about the failure mechanisms that are actually operative in the system. APA docs more than simply track experience: it systematically evaluates experience, looking for under-appreciated risks that may warrant changes to design or operational practice. This paper presents the pilot application of the NASA APA process to Space Shuttle Orbiter systems. In this effort, the working sessions conducted at Johnson Space Center (JSC) piloted the APA process developed by Information Systems Laboratories (ISL) over the last two years under the auspices of NASA's Office of Safety & Mission Assurance, with the assistance of the Safety & Mission Assurance (S&MA) Shuttle & Exploration Analysis Branch. This process is built around facilitated working sessions involving diverse system experts. One important aspect of this particular APA process is its focus on understanding the physical mechanism responsible for an operational anomaly, followed by evaluation of the risk significance of the observed anomaly as well as consideration of generalizations of the underlying mechanism to other contexts. Model completeness will probably always be an issue, but this process tries to leverage operating experience to the extent possible in order to address completeness issues before a catastrophe occurs.

Maggio, Gaspare↗

NASA NTRS2010

Human System Drivers for Exploration Missions

Evaluation of DRM4 in terms of the human system includes the ability to meet NASA standards, the inclusion of the human system in the design trade space, preparation for future missions and consideration of a robotic precursor mission. Ensuring both the safety and the performance capability of the human system depends upon satisfying NASA Space Flight Human System Standards.1 These standards in turn drive the development of program-specific requirements for Near-earth Object (NEO) missions. In evaluating DRM4 in terms of these human system standards, the currently existing risk models, technologies and biological countermeasures were used. A summary of this evaluation is provided below in a structure that supports a mission architecture planning activities. 1. Unacceptable Level of Risk The duration of the DRM4 mission leads to an unacceptable level of risk for two aspects of human system health: A. The permissible exposure limit for space flight radiation exposure (a human system standard) would be exceeded by DRM4. B. The risk of visual alterations and abnormally high intracranial pressure would be too high. 1

Kundrot, Craig E.↗

NASA NTRS1982

Preliminary risk benefit assessment for nuclear waste disposal in space

This paper describes the recent work of the authors on the evaluation of health risk benefits of space disposal of nuclear waste. The paper describes a risk model approach that has been developed to estimate the non-recoverable, cumulative, expected radionuclide release to the earth's biosphere for different options of nuclear waste disposal in space. Risk estimates for the disposal of nuclear waste in a mined geologic repository and the short- and long-term risk estimates for space disposal were developed. The results showed that the preliminary estimates of space disposal risks are low, even with the estimated uncertainty bounds. If calculated release risks for mined geologic repositories remain as low as given by the U.S. DOE, and U.S. EPA requirements continue to be met, then no additional space disposal study effort in the U.S. is warranted at this time. If risks perceived by the public are significant in the acceptance of mined geologic repositories, then consideration of space disposal as a complement to the mined geologic repository is warranted.

Rice, E. E.↗

DOE OSTI2023

Dynamic Model Agnostic Reliability Evaluation of Machine-Learning Models Integrated in Instrumentation & Control Systems

In recent years, the field of machine learning (ML), specifically neural networks, has grown significantly and has spurred research in its applicability to digital instrumentation and control systems (DI&C). While ML models have shown promise in operational contexts, the trustworthiness of using such algorithms has not been adequately assessed. Failures of ML integrated systems are not well understood, and the lack of comprehensive risk modeling can degrade the trustworthiness in these systems. In recent reports by the National Institute for Standards and Technology (NIST) [1] and the Nuclear Regulatory Commission (NRC) [2], they indicate that trustworthiness in ML is a critical barrier and will play a vital role in the safe, accountable, and secure operation of intelligent systems. Thus, in this work, we demonstrate a dynamic model-agnostic method to quantify the relative reliability of AI/ML predictions by incorporating out-of-distribution (OOD) detection on the training dataset. It is well documented that most ML algorithms excel at interpolation (or near-interpolation) tasks but experience significant performance degradation at extrapolation. The method, referenced as the Laplacian distributed decay for reliability (LADDR), determines the difference between the operational and training datasets which can used to the relative reliability of AI/ML predictions. LADDR is then demonstrated on a feedforward neural network based digital twin used for the prediction of safety significant factors during a loss-of-flow transient. LADDR is used to demonstrate how training data can be used as evidence to support the relative reliability of ML/AI predictions enhancing the overall trustworthiness of the system.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

DOE OSTI2025

Improving Dose Modeling With Dynamic Modeling Tools [Slides]

Utilities aiming for higher fuel enrichment for power uprates or extended operation times before refueling must conduct a new dose analysis. Current conservative dose estimation standards may cause utilities to exceed regulatory limits for proposed increased fuel enrichment. A more accurate modeling of doses from reactor accidents can lower these conservative assumptions. Prescott et al. (2022) demonstrated that the Event Modeling Risk Assessment using Linked Diagrams (EMRALD) software tool, developed at Idaho National Laboratory (INL), can be coupled with the Modular Accident Analysis Program (MAAP5) for dynamic accident analysis in reactor plants. EMRALD forms models of potential accident scenarios, while MAAP5 simulates the accident progression and dose consequences. By integrating these software tools with utility-specific data, a more precise estimation of dose consequences from plant accidents can be achieved. Preliminary findings indicate that EMRALD provides accurate mean core damage frequencies for generalized accident scenarios. Future work includes expanding the model to account for plant-specific data and mitigation factors.

97 - MATHEMATICS AND COMPUTING↗

DOE OSTI2023

Synthetic Electricity Market Data Generation and HERON Use Case Setup of Advanced Nuclear Reactors Coupled with Thermal Energy Storage Systems

This study evaluates and optimizes advanced nuclear reactors coupled with thermal energy storage (TES) systems in an Integrated Energy System (IES) architecture to enable advanced nuclear power plants (A NPP) to participate in multi-commodity markets, thus enhancing their economic competitiveness. Nuclear-TES coupling scenarios studied herein are designed attenuate the nuclear heat dynamics and defer energy delivery to a later time, enabling the nuclear reactor to continue operating at or near steady-state design conditions as usual while also enabling flexible generation. Three A-NPPs, namely, an advanced light-water reactor (A LWR), a high temperature gas-cooled reactor (HTGR) and a liquid-metal fast reactor (LMFR) were selected as the initial use cases for demonstrating the technoeconomic of thermally balanced energy storage coupling design for thermal power extraction. Each of the reactor technologies were evaluated in two different electricity markets. Stochastic optimization approach was adopted which included the evaluation of price signals from the Pennsylvania-New Jersey-Maryland (PJM) market, and Electric Reliability Council of Texas (ERCOT), using an autoregressive moving average (ARMA) model. Risk Analysis Virtual Environment (RAVEN) tool and its dispatch optimization plugin, the Holistic Energy Resource Optimization Network (HERON), were used to perform dispatch and capacity optimization, using the price data provided by the ARMA models. The results from the Nuclear-TES use cases will be used to design and characterize dynamic integrated system behavior and feedback.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

DOE OSTI2023

Concepts of association between cancer and ionising radiation: accounting for specific biological mechanisms

The probability that an observed cancer was caused by radiation exposure is usually estimated using cancer rates and risk models from radioepidemiological cohorts and is called assigned share (AS). This definition implicitly assumes that an ongoing carcinogenic process is unaffected by the studied radiation exposure. However, there is strong evidence that radiation can also accelerate an existing clonal development towards cancer. In this work, we define different association measures that an observed cancer was newly induced, accelerated, or retarded. The measures were quantified exemplarily by Monte Carlo simulations that track the development of individual cells. Three biologically based two-stage clonal expansion (TSCE) models were applied. In the first model, radiation initiates cancer development, while in the other two, radiation has a promoting effect, i.e. radiation accelerates the clonal expansion of pre-cancerous cells. The parameters of the TSCE models were derived from breast cancer data from the atomic bomb survivors of Hiroshima and Nagasaki. For exposure at age 30, all three models resulted in similar estimates of AS at age 60. For the initiation model, estimates of association were nearly identical to AS. However, for the promotion models, the cancerous clonal development was frequently accelerated towards younger ages, resulting in associations substantially higher than AS. This work shows that the association between a given cancer and exposure in an affected person depends on the underlying biological mechanism and can be substantially larger than the AS derived from classic radioepidemiology.

63 RADIATION, THERMAL, AND OTHER ENVIRON. POLLUTAN↗

NASA NTRSDate not supplied

LLMs and GenAI Tools to Depict Contributions of Human Systems to Spaceflight Tasks Execution

Recent advancements in Artificial Intelligence and Machine Learning (AI/ML) technologies, particularly Large Language Models (LLMs) capable of sophisticated syntax analysis, offer substantial potential in automating complex processes, thereby saving time and human resources. This study explores the development of an LLM-driven model designed to analyze and categorize a diverse set of Mars mission tasks into 18 predefined Human System Task Categories (HSTCs) based on their textual descriptions. As part of developing the Crew Health and Performance – Probabilistic Risk Assessment (CHP-PRA projects Performance Risk Model (PRisM) proof-of-concept, we established a framework to project performance scores from small-scale tests onto a preliminary list of Mars tasks. The foundation of our model was a comprehensive spreadsheet populated by NASA experts and clinicians, which detailed each Mars task alongside binary indicators of HSTC involvement. This dataset enabled the initial application of supervised ML, training and testing on existing HSTC labels. The HSTCs were originally defined from a medical system perspective, focusing on task impairments due to deteriorated human health. To expand our model's scope to include categories impacting performance, we face the challenge of generating binary labels (0 or 1) for new categories without pre-existing data. We address this by employing Generative AI (GenAI) software to determine whether a given task involved a new category by asking, "Does task A involve using category B?" We validate our approach by comparing the GenAI's binary classifications with the expert-provided labels for existing HSTCs. Notably, we utilize Ollama [4], a locally hosted GenAI tool that does not require cloud access, thus safeguarding NASA's proprietary data from unauthorized exposure. This study demonstrates the feasibility of leveraging cutting-edge AI tools to advance research, paving the way for automation and rapid decision-making in space exploration.

Mona Matar↗

DOE OSTI2021

Data requirements for improving the Quantitative Risk Assessment of liquid hydrogen storage systems

Quantitative Risk Assessment (QRA) supports the development of risk-informed safety codes and standards which are employed to enable the safe deployment of hydrogen technologies essential to decarbonize the transportation sector. System reliability data is a necessary input for rigorous QRA. Here, the lack of reliability data for bulk liquid hydrogen (LH 2 ) storage systems located on site at fueling stations limits the use of QRAs. In turn, this hinders the ability to develop the necessary safety codes and standards that enable worldwide deployment of these stations. Through a QRA-based analysis of a LH 2 storage system, this work focuses on identifying relevant scenario and probability data currently available and ascertaining future data collection requirements regarding risks specific to liquid hydrogen releases. The work developed consists of the analysis of a general bulk LH 2 storage system design located at a hydrogen fueling station. Failure Mode and Effect Analysis (FMEA) and traditional QRA modeling tools such as Event Sequence Diagrams (ESD) and Fault Tree Analysis (FTA) are employed to identify, rank, and model risk scenarios related to the release of LH 2 . Based on this analysis, scenario and reliability data needs to add LH 2 -related components to QRA are identified with the purpose of improving the future safety and risk assessment of these systems.

08 HYDROGEN↗

DOE OSTI2021

Industry Level Integrated Fire Modeling Using Fire Risk Investigation in 3D (FRI3D)

The software Fire Risk Investigation in 3D (FRI3D) has been developed over the last 2 years to integrate 3D spatial modeling with existing fire probabilistic risk assessment (PRA) models and fire simulation codes. The goal of this research and development is to automate many of the fire analysis manual tasks to reduce industry efforts in the initial fire modeling and operational costs for the model maintenance and evaluations required during normal plant operations. The tasks for Fiscal Year (FY) 2021 include first testing the FRI3D modeling capabilities by importing an industry fire model into FRI3D and making a 3D model of a complex/high-risk significant area. (For this work, the switchgear room was chosen.) Then, the second task of FY 2021 is to develop a dynamic fire PRA process that can help optimize traditional fire PRA models. The switchgear room model will be used for the dynamic fire PRA work. This report describes the work and insights learned when using FRI3D software to model both a Nuclear Regulatory Report (NUREG) example models and a full industry switchgear room.

97 MATHEMATICS AND COMPUTING↗