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NASA NTRS1989

Real-time closed-loop simulation and upset evaluation of control systems in harsh electromagnetic environments

Digital control systems for applications such as aircraft avionics and multibody systems must maintain adequate control integrity in adverse as well as nominal operating conditions. For example, control systems for advanced aircraft, and especially those with relaxed static stability, will be critical to flight and will, therefore, have very high reliability specifications which must be met regardless of operating conditions. In addition, multibody systems such as robotic manipulators performing critical functions must have control systems capable of robust performance in any operating environment in order to complete the assigned task reliably. Severe operating conditions for electronic control systems can result from electromagnetic disturbances caused by lightning, high energy radio frequency (HERF) transmitters, and nuclear electromagnetic pulses (NEMP). For this reason, techniques must be developed to evaluate the integrity of the control system in adverse operating environments. The most difficult and illusive perturbations to computer-based control systems that can be caused by an electromagnetic environment (EME) are functional error modes that involve no component damage. These error modes are collectively known as upset, can occur simultaneously in all of the channels of a redundant control system, and are software dependent. Upset studies performed to date have not addressed the assessment of fault tolerant systems and do not involve the evaluation of a control system operating in a closed-loop with the plant. A methodology for performing a real-time simulation of the closed-loop dynamics of a fault tolerant control system with a simulated plant operating in an electromagnetically harsh environment is presented. In particular, considerations for performing upset tests on the controller are discussed. Some of these considerations are the generation and coupling of analog signals representative of electromagnetic disturbances to a control system under test, analog data acquisition, and digital data acquisition from fault tolerant systems. In addition, a case study of an upset test methodology for a fault tolerant electromagnetic aircraft engine control system is presented.

Belcastro, Celeste M.↗

NASA NTRS2002

An expert system for fault management assistance on a space sleep experiment

The expert system, Principal Investigator-in-a-box, or [PI], was designed to assist astronauts or other operators in performing experiments outside their expertise. Currently, the software helps astronauts calibrate instruments for a Sleep and Respiration Experiment without contact with the investigator on the ground. It flew on the Space Shuttle missions STS-90 and STS-95. [PI] displays electrophysiological signals in real time, alerts astronauts via the indicator lights when a poor signal quality is detected, and advises astronauts how to restore good signal quality. Thirty subjects received training on the sleep instrumentation and the [PI] interface. A beneficial effects of [PI] and training reduced troubleshooting time. [PI] benefited subjects on the most difficult scenarios, even though its lights were not 100% accurate. Further, questionnaires showed that most subjects preferred monitoring waveforms with [PI] assistance rather than monitoring waveforms alone. This study addresses problems of complex troubleshooting and the extended time between training and execution that is common to many human operator situations on earth such as in power plant operation, and marine exploration.

NASA Discipline Neuroscience↗

DOE OSTI2025

AUTOMATIC GENERATION OF EVENT TREES AND FAULT TREES: A MODEL-BASED APPROACH

In the past few decades, increasing complexity in modern engineering systems has been driven by the integration of a large number of components and by the fact that the system operations involve many disciplines (e.g., thermal-hydraulics, plant operations, cyber-security). Current safety/reliability modeling approaches to such systems are labor intensive, difficult to learn, and rely heavily on simplistic Boolean logic to depict failure propagation and accident progression. While these methods serve well for simple systems (i.e., linear causal systems with limited small inter- and intra-system interactions), their results are difficult to verify when modeling complex systems (typically performed through the extensive use of modeling assumptions). The development of new methods is addressed to meet these challenges through a model-based system engineering (MBSE) lens. Under MBSE philosophy, every aspect of the system (form or function) is represented by a model that completely characterizes its architecture or behavior. MBSE approach greatly improves the management of design, analysis and verification of complex systems. An integration of Dynamic Probabilistic Risk Assessment (DPRA) methods with MBSE models is proposed to perform safety/reliability analyses of engineering systems. In particular, MBSE representation of the system (performed using Systems Modeling Language [SysML]) is coupled with DPRA methods to automatically generate event trees and fault trees.

97 - MATHEMATICS AND COMPUTING↗

DOE OSTI2023

Quantifying Uncertainty of Deep Reinforcement Learning Based Decision Making for Operations and Maintenance of Nuclear Power Plant

This paper summarizes research that integrates condition monitoring and prognostics with decision making for nuclear power plant operations and maintenance. As part of this research, we have developed an online asset management tool to help reduce life-cycle maintenance and repair costs. Using the latest advancements in condition monitoring, supply chain analytics, and deep reinforcement learning, we have created a predictive maintenance tool that can optimize the maintenance and spare-part management of a repairable nuclear system. To demonstrate these methods, preliminary studies were conducted on a simple, representative maintenance system undergoing a stochastic degradation process that requires repairs or replacement to continue operation. Through Monte Carlo simulations, we were able to reduce maintenance spending by approximately 50% compared to optimized, time-based maintenance strategies. Not only does the decision maker reduce the average life-cycle costs, it also minimizes the chance of high cost scenarios, lowering the variance of the expected cost distributions, and reducing overall financial risk. Furthermore, this work also studies the ability of the decision maker to handle various levels of noise from observation uncertainty. By introducing uncertainty into the decision-making process, we have quantified the robustness and resiliency of the decision maker, as well as identified necessary levels of observability to demonstrate cost effectiveness.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

DOE OSTI2023

Transient Efficiency, Flexibility, and Reliability Optimization of Coal-Fired Power Plants - Final Report

This program developed an advanced model-based monitoring and model-predictive control algorithms for a coal fired power plant (CFPP), and deployed these algorithms in a real-time platform to demonstrate performance benefits for transient flexibility and plant operation efficiency. More specifically, the objectives were successfully achieved through a combination of (i) developing a high-fidelity transient plant model in Apros, which was used as a high-fidelity plant simulation between $100-50\% TMCR$ where TMCR denotes the turbine maximum continuous rating, i.e., baseload, (ii) developing a very fast physics-based reduced-order model (ROM) of the plant, which ran more than $100\times$ faster than real-time, enabling its use as real-time embedded model for model-based estimation (MBE) and model predictive control (MPC) (iii) implementing a real-time MBE based on ROM using a robust unscented Kalman filter (UKF) to continuously tune the ROM to match the measurements from high-fidelity Apros plant model despite significant plant-model mismatch, and thus, obtain a Digital Twin of the plant (iv) designing and implementing a real-time MPC with dual objectives of transient plant load tracking with high ramp rates and minimizing coal consumption, i.e., improving plant efficiency in the baseload-partload operation range of $100-50\% TMCR$. Each key element above was developed and tested individually, and has been reported in corresponding Topical Reports. Finally, all the individual elements were integrated in an overall closed-loop system, that was successfully tested in desktop Simulink test harness simulations with ROM or high-fidelity model as the plant. Thereafter, the Simulink implementation was used to auto-generate C-code and deploy as real-time Docker microservice containers in Linux, and validate that they can run in real-time in the hardware-in-the loop (HIL) setup and produce the same results as in Simulink. The results of the integrated simulation tests in Simulink as well as the real-time HIL deployment are documented in this final report, showing good load tracking for load ramps at $3-4\%/min$ ramp rates, and achieving up to $5.5\%$ reduction in coal relative to baseline operation at $50\% TMCR$ load. The desktop and HIL simulations show successful performance of the overall model based estimation and control solution and achieve the key objectives of the program for flexible, efficient and reliable operation of subcritical coal fired power plants.

20 FOSSIL-FUELED POWER PLANTS↗

DOE OSTI2023

Projecting Future Colorado River Basin Water and Hydropower Operations

Drought, variable renewable energy (VRE) resources (primarily wind and photovoltaic technologies), and power markets can all impact hydropower plant operations. We analyze how these three factors collectively may potentially change the future operation and economics of federal dams and hydropower plants located in the Colorado River Basin (CRB). Federal CRB energy and capacity resources, including 4,200 MW of hydropower capacity, are marketed by Western Area Power Administration (WAPA) and sold through long-term Firm Electric Service (FES) contracts to entities located in 15 western and central States that serve millions of electricity consumers. The parameters of FES contracts allow a wide range of scheduling flexibility for FES customers. The FES customers will adjust the timing of energy delivery according to the changing water, power market, and VRE contribution level to the power grid. We simulate and project water and hydropower operations with two models: 1) reservoir operation and 2) power system operation (production cost) with various temporal granularity. We consider two sets of grid scenarios (one representing today's infrastructure, and one representing higher VRE contributions in 2036) and two sets of water scenarios (drought and normal hydrology). We modeled scenarios to understand the power market-energy price levels and patterns, FES customer scheduling, hydropower economics, WAPA finances and hydropower operation for various hydrologic conditions, and VRE contribution level to the power grid. The detailed modeling framework includes: (1) creating ensembles of CRB hydrologic and hydropower futures, (2) selecting representative futures, (3) simulation of FES customer contracts, (4) simulating western U.S. power grid economic scheduling and dispatch under two VRE contribution levels, utilizing information from modeling steps (1)-(4), (5) assessment of reservoir water and hydropower operation, and (6) comparing scenario operations and economics. Our study team comprising WAPA, and an interdisciplinary team of national labs will gain insight into how WAPA can prepare for and adapt its practices in response to an evolving U.S. power grid.

Colorado River↗

DOE OSTI2024

Life Cycle Greenhouse Gas Emissions of Coal-Biomass Co-Firing Power Plants with Carbon Capture and Storage

The United States has set a target to achieve the net-zero economy by 2050. Bioenergy with Carbon Capture and Sequestration (BECCS) is one of the promising negative-emission routes in the mitigation portfolio to help meet this goal. Coal-biomass co-firing with carbon capture and storage (CCS) is a key BECCS technology to realize the carbon mitigation at fossil-fuel power plants. The mitigation potential of co-firing option is affected by numerous critical factors, such as biomass properties, co-firing level, and carbon capture rate. The objectives of the study are to characterize and estimate the life cycle greenhouse gas (GHG) emissions and performance of coal-biomass co-firing power plants with CCS, determine the breakeven co-firing level at power plants necessary to achieve net-zero life cycle emissions, and quantify the variabilities and uncertainties in life cycle emissions. The scope of the life cycle assessment includes the fuel supply, combustion-based power generation, and CO2 transport and storage. A fuel-based life cycle module is developed and embedded in the Integrated Environmental Control Model (IECM), a fossil-fuel power plant modeling tool. This study then applies the enhanced IECM to conduct the process-based life cycle assessment for an array of biomass co-firing scenarios. Deterministic analysis indicates that reaching net-zero life cycle emissions in a biomass co-firing plant without CCS deployment is challenging. Combining biomass co-firing and CCS deployment can significantly lower the overall life cycle emissions of power plants. Net-zero life cycle emissions can be achieved with a 20 wt.% co-firing level and 90% CCS when the Powder River Basin coal is co-fired with energy crops or forestry residues. However, the breakeven co-firing level for net-zero emissions depend on the selected fuel properties. Fuel supply and plant operation are the critical stages influencing the life cycle emissions of power plants with 90% CCS. Deployment of deep CCS beyond 90% CO2 capture can remarkably reduce operational emissions and the breakeven co-firing level. With 99% CCS, the breakeven co-firing rate can be reduced to 12% on average. These findings highlight the trade-offs between technical performance and environmental impact of biomass co-firing at coal-fired power plants and emphasize the role of deep CCS in achieving a net-zero emissions future.

Wu, Wanying↗

DOE OSTI2023

Transient Efficiency, Flexibility, and Reliability Optimization of Coal-Fired Power Plants - Final Program Review

20 FOSSIL-FUELED POWER PLANTS↗

DOE OSTI2021

Influence of Business Models on PV-Battery Dispatch Decisions and Market Value

PV-battery hybrid projects dominate interconnection queues in some regions in the United States, but few projects have been operational long enough to assess how the hybrid capabilities may be used in practice. We interview plant operators and analyze empirical dispatch data for eleven large-scale PV-battery hybrids in three organized wholesale markets in the United States. We use the dispatch data and wholesale market prices to estimate the market value of our sample hybrids in 2020. The empirical increase in market value of a PV-battery hybrid relative to a standalone PV plant varies by project and ranges from $\$$1 to $\$$48/MWhsolar. The premium is driven by market, location, technical characteristics of the PV and battery asset, and battery dispatch strategies. In contrast to the widespread assumptions in the PV-battery hybrid modeling literature, only three of the eleven project operators optimize battery usage for wholesale market revenue as merchant plants. Instead, the majority of operators in the sample have alternate objectives. For example, load-serving entities target peak load reductions, incentive program participants focus on compliance with program requirements, and large energy consumers prioritize resiliency and utility bill minimization. Understanding prevalent dispatch signals and the degree of alignment with system-wide grid needs can increase the market value of PV-battery hybrids.

14 SOLAR ENERGY↗

DOE OSTI2023

Report on the Creation and Progress of the Hydrogen Regulatory Research Review Group

The current U.S. nuclear generation fleet is increasingly recognized by governmental, scientific, public policy, and industrial communities as having a strategic role in support of the ongoing national transition to a clean energy future. Federal incentives and actions are aligning to expand the role of nuclear power as a viable and more flexible contributor to the evolving national clean energy mix through programs and initiatives such as nuclear power loan guarantees; the Inflation Reduction Act’s (IRA) clean nuclear electrical, steam, and hydrogen incentives; the Infrastructure Investment and Jobs Act (IIJA, also referred to as the Bipartisan Infrastructure Act or BIL); and near term Department of Energy (DOE) funding opportunities related to nuclear based hydrogen hubs and nuclear integrated hydrogen demonstration projects. . Additionally, leveraging clean nuclear electricity and steam is being explored by industries desiring to transition away from carbon-intensive energy sources. Even with all these emerging enablers, notable barriers remain for the widespread adoption of these opportunities within the U.S. nuclear fleet, including the following: • Assurance of the markets for alternate products needed to support decision-making for large capital modification investments • Electric utility mindset and business history centered solely on producing electricity • Design change complexity and regulatory uncertainty associated with plant modifications needed to support alternate product streams The DOE Light Water Reactor Sustainability (LWRS) Flexible Plant Operations and Generation (FPOG) Pathway is developing options to help U.S. nuclear power plants (NPP) in all these areas to enable NPPs designed for steady baseload operation to integrate with intermittent wind and solar capacity to assure reliable clean energy for the nation. Current and near-term laboratory research is focusing on the technical, regulatory, safety, demonstration, and economic elements in support of improving nuclear plant flexibility through hybrid production of electricity and other non-electric products such as hydrogen and energy arbitrage.

42 ENGINEERING↗

DOE OSTI2019

Support for Reactor Operators in Case of Cyber-Security Threats (NEUP Final Report)

Increasing use of digital technology in nuclear power plants (NPPs) poses cyber-security as a crucial threat to public safety and to continuous energy production. Cyber-security risks are comprised of complex known and unknown interactions between various entities, system vulnerabilities, network protocols, human users and malicious attacks. There is little understanding or research geared towards plant operators’ response under cyber-security threats and operational procedures to cope with such threats. This is particularly critical when a cyber-security event masquerades as a safety incident or an evolving accident. Instead of leading operators to the remediation of the accident, the masked cyber event may lead them to circumvent the safety mechanisms of the plant. Given these challenges, the objective of this project is to develop a tool to characterize abnormal NPP events as “cyber” or “safety” incidents, and to further develop this tool as a real-time operator aid to assist in response to the incident. This NEUP Final Report summarizes the research efforts towards the above goals and the results in the following three aspects. First, a methodology for classifying abnormal NPP events as cyber-attacks or safety incidents was developed. This provides the basis for responding to potential cyber-attacks. In this methodology, the causal relationships between various variables (i.e., physical variables, network variables, and control variables) for a nuclear system under consideration are modeled using dynamic Bayesian networks. Based on observations of certain variables (i.e., the evidence), inference is performed to identify the state of hidden variables, which helps indicate the occurrence of cyber-attacks or safety incidents. The proposed methodology was applied to the full scope NPP simulator system at The Ohio State University as a case study. The result shows that the proposed methodology is capable of distinguishing between cyber-attacks and safety incidents. Second, a game-theoretic approach for responding to cyber-attacks on nuclear power plants was developed. This is the second major goal of the project, and the method is used to recommend optimal responses to reactor operators in the case of cyber-attacks. We consider two cases in this research. In the first case, the interaction between the defender (i.e., the reactor operator) and the attacker is modeled as a two-player, nonzero-sum, Markov game with an infinite time horizon. In the second case, we consider a semi-Markov game between the defender and the attacker within a finite time horizon. The model in the second case enables us to consider the time sensitive response of the defender. In each case, the method for deriving the Nash equilibrium is developed. The Nash Equilibrium of the game provides the valid prediction of both players’ actions because no single player can benefit from unilaterally deviating from the equilibrium policy if the other player adheres to his/hers, hence it provides the best response of the defender to cyber-attacks. The proposed method in each case is demonstrated through a simplified benchmark digital feedwater control system. Third, a prototype display is developed to integrate the above information. The prototype display depicts the communication information to the operator and incorporates the cyber-security tool developed by the team into the interface. It consists of the regular display in current control rooms, as well as a panel used to indicate the occurrence of cyber-attacks or safety events and a panel used to guide the operator’s response to detected cyber-attacks.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

DOE OSTI2026

Valuing Maintenance Strategies for Fusion Plants as Part of a Future Electricity Grid

Scheduled maintenance is likely to be lengthy and therefore consequential for the economics of fusion power plants. The maintenance strategy that maximizes the economic value of a plant depends on internal factors such as the cost and durability of the replaceable components, the frequency and duration of the maintenance blocks, and the external factors of the electricity system in which the plant operates. Here, this paper examines the value of fusion power plants with various maintenance properties in a decarbonized United States Eastern Interconnection circa 2050. Seasonal variations in electricity supply and demand mean that certain times of year, particularly spring to early summer, are best for scheduled maintenance. Seasonality has two important consequences. First, the value of a plant can be 15% higher than what one would naively expect if value were directly proportional to its availability. Second, in some cases, replacing fractions of a component in shorter maintenance blocks spread over multiple years is better than replacing it all at once during a longer outage, even through the overall availability of the plant is lower in the former scenario.

power plant, maintenance, seasonality, electricity↗

DOE OSTI2021

High-Accuracy Simulations to Model Pyrometallurgical Processes in a Secondary Lead Reverberatory Furnace

The US manufacturing industry produces about 1.3 million tons of refined lead each year using secondary sources consisting mainly of lead batteries. ORNL is partnering with Gopher resource, the second largest lead recycling company in the United States, and GTI, to develop a high-fidelity CFD model of a directly fired, reverberatory-style, secondary lead furnace. These High Performance Computing (HPC) simulations are aimed to use first principles modeling for combustion and melting processes of the secondary lead feed while accounting for complex interphase interactions between the gas, solid charge (lead) material, slag, and metal phases. Through validation against operating plant data, this effort will enable significant improvements in design, operational parameters, and energy efficiency, thus improving productivity and refractory lifetime of secondary lead melting furnaces. Estimated savings/reduction of, at least, 1 trillion BTU, 1 million ton/year of greenhouse gas emissions, and $\$50$ million/year to the US lead industry can be expected. ORNL resources and expertise in high-performance computing and multicomponent, multiphase flows were utilized to realize this goal while advancing the understanding of the smelting and melting processes occurring within the furnace.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

NASA NTRS1999

10 000-hr Cyclic Oxidation Behavior of 68 High-Temperature Co-, Fe-, and Ni- Base Alloys Evaluated at 982 deg. C (1800 deg. F)

Power systems with operating temperatures in the range of 815 to 982 C (1500 to 1800 F) frequently require alloys that can operate for long times at these temperatures. A critical requirement is that these alloys have adequate oxidation resistance. The alloys used in these power systems require thousands of hours of operating life with intermittent shutdown to room temperature. Intermittent power plant shutdowns, however, offer the possibility that the protective scale will tend to spall (i.e., crack and flake off) upon cooling, increasing the rate of oxidative attack in subsequent heating cycles. Thus, it is critical that candidate alloys be evaluated for cyclic oxidation behavior. It was determined that exposing test alloys to ten 1000-hr cycles in static air at 982 10 000-hr Cyclic Oxidation Behavior of 68 High-Temperature Co-, Fe-, and Ni-Base Alloys Evaluated at 982 C (1800 F) could give a reasonable simulation of long-time power plant operation. Iron- (Fe-), nickel- (Ni-), and cobalt- (Co-) based high-temperature alloys with sufficient chromium (Cr) and/or aluminum (Al) content can exhibit excellent oxidation resistance. The protective oxides formed by these classes of alloys are typically Cr2O3 and/or Al2O3, and are usually influenced by their Cr, or Cr and Al, content. Sixty-eight Co-, Fe-, and Ni-base high-temperature alloys, typical of those used at this temperature or higher, were used in this study. At the NASA Lewis Research Center, the alloys were tested and compared on the basis of their weight change as a function of time, x-ray diffraction of the protective scale composition, and the physical appearance of the exposed samples. Although final appearance and x-ray diffraction of the final scale products were two factors used to evaluate the oxidation resistance of each alloy, the main criterion was the oxidation kinetics inferred from the specific weight change versus time data. These data indicated a range of oxidation behavior including parabolic (typical of isothermal oxidation), paralinear, linear, and mixed-linear kinetics.

Barrett, Charles A.↗

NASA NTRS1984

A Summary Description of a Computer Program Concept for the Design and Simulation of Solar Pond Electric Power Generation Systems

A solar pond electric power generation subsystem, an electric power transformer and switch yard, a large solar pond, a water treatment plant, and numerous storage and evaporation ponds. Because a solar pond stores thermal energy over a long period of time, plant operation at any point in time is dependent upon past operation and future perceived generation plans. This time or past history factor introduces a new dimension in the design process. The design optimization of a plant must go beyond examination of operational state points and consider the seasonal variations in solar, solar pond energy storage, and desired plant annual duty-cycle profile. Models or design tools will be required to optimize a plant design. These models should be developed in order to include a proper but not excessive level of detail. The model should be targeted to a specific objective and not conceived as a do everything analysis tool, i.e., system design and not gradient-zone stability.

Source record↗

DOE OSTI2023

Integrated Operations for Nuclear: Work Reduction Opportunity Demonstration Strategy

EXECUTIVE SUMMARY The Light Water Reactor Sustainability Program Plant Modernization Pathway has been working with industry for a number of years to leverage digital technology to extend the life and improve the performance of the existing fleet through modernized technologies and improved processes for plant operation and power generation. This includes development of modernization solutions to improve reliability and economic performance while addressing US nuclear industry’s aging and obsolescence challenges. The objective of these efforts is to deliver a sustainable business model that enables US nuclear industry to remain competitive. Digital Infrastructure (DI) research has established a technical foundation for these efforts. This effort began with technical analysis and support for a safety-related instrumentation and control (I&C) pilot upgrade being performed at Constellation Energy Generation’s Limerick Nuclear Plant. The following publicly available reports were produced as part of this effort. • INL/EXT-20-61079, Vendor-Independent Design Requirements for a Boiling Water Reactor Safety System Upgrade [1] • INL/EXT-20-59371, Business Case Analysis for Digital Safety-Related Instrumentation & Control System Modernizations [2] • INL/EXT-20-59809, “Safety-Related Instrumentation and Control Pilot Upgrade: Initial Scoping Phase Implementation Report and Lessons Learned [3] • INL/RPT-23-72105, Safety-Related Instrumentation and Control Upgrade: Conceptual – Detailed Design Phase Report and Lessons Learned [4]

99 GENERAL AND MISCELLANEOUS↗

DOE OSTI2023

Precursor Analysis Report: JBS Foods Ransomware Attack 2021

The JBS Foods 2021 Ransomware Attack Precursor Analysis Report leverages publicly available information about the JBS ransomware cyber attack and catalogs anomalous observables for each technique employed in the attack. This analysis is based upon the methodology of the Cybersecurity for the Operational Technology Environment (CyOTE) program. In late May 2021, one of the world’s largest meat producers, JBS Foods, announced they had fallen victim to a worldwide ransomware attack, later found to be REvil ransomware. In the United States alone, JBS Foods accounts for nearly 25% of beef and roughly 20% of pork production. Adversaries initially launched a Distributed Denial of Service (DDoS) attack on the company’s Information Technology (IT) networks in Australia, but the attack impacted operations in Brazil, Canada, and the United States, as well. The attack caused plant operations in all four countries to shut down for at least one day. All nine of the U.S. meatpacking plants temporarily shut down because of the attack. The adversaries initially demanded a $\$$22 million ransom for the company’s data, but later negotiated the ransom down to $\$$11 million even after JBS Foods restored most of their systems. JBS Foods eventually paid the $\$$11 Million for reassurance from the adversaries that none of their customers’ data would be compromised in the future. Despite its short duration, the attack still caused large stocks of meat to spoil. The incident also underscored how adversaries can simultaneously compromise and move laterally through global subsidiaries of an organization. Researchers and analysts identified 22 unique techniques (in a sequence of 21 steps) utilized during the attack with a total of 361 observables using MITRE ATT&CK® for Industrial Control Systems. The CyOTE program assesses observables accompanying techniques used prior to the triggering event to identify opportunities to detect malicious activity. If observables accompanying the attack techniques are perceived and investigated prior to the triggering event, earlier comprehension of malicious activity can take place. Sixteen of the identified techniques used during the JBS Foods cyber attack were precursors to the triggering event. Analysis identified 308 observables associated with these precursor techniques, 163 of which were assessed to have an increased likelihood of being perceived in the 75 days preceding the triggering event. The response and comprehension time could have been reduced if the observables had been identified earlier. The information gathered in this report contributes to a library of observables tied to a repository of artifacts, data sources, and technique detection references for practitioners and developers to support the comprehension of indicators of attack. Asset owners and operators can use these products if they experience similar observables or to prepare for comparable scenarios.

45 MILITARY TECHNOLOGY, WEAPONRY, AND NATIONAL DEF↗

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↗