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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

COVID-19 Joint Pandemic Modeling and Analysis Platform

The non-pharmaceutical intervention to reduce the impact and spread of COVID-19 requires the development of policies and guidance through a collaborative effort among government, academia, medicine, and citizens. To operationalize this effort, we have developed an all-encompassing situational awareness platform that can process multi-modal and multi-source data allowing informed decision making. Besides, showing the current spread of infection, the platform also captures the impact of human dynamics on the infection spread, location, and availability of critical infrastructure, prediction, and high-performance computing driven simulation. The platform is extensible, allowing third-party integration and services to consume the curated data and analytics in near real-time. We believe the platform will augment critical decision making for reducing the impact and spread of the pandemic.

Thakur, Gautam↗
DOE OSTI2025

Improving Cyber Situational Understanding

Effective cybersecurity operations require the ability to analyze large amounts of information to assess security risks and formulate defensive strategies against adversaries. This has become more complex in recent years as the sprawl and interconnectivity of devices grows through implementation of virtualization, cloud computing, and Internet of Things (IoT). The amount of data and analysis required for effective cybersecurity command and control decisions far exceeds humans’ capacity to perform manually. We characterize the analysis problem as cyber situational understanding. The research presented to improve cyber situational understanding focuses on vulnerability analysis and threat intelligence. Regarding vulnerabilities, entities must analyze and plan work for between thousands and tens of thousands of software vulnerabilities annually. Entities heavily use network firewalls to limit vulnerability exposure. As a result, some of these vulnerabilities permit exposure to adversarial exploitation, whereas others are inaccessible and therefore present negligible risk of exploitation. Distinguishing between high and low risk software vulnerabilities requires a deep understanding of the vulnerability, network firewall protection, and characteristics of the targeted device. This problem is solved by extracting network service features from vulnerability data features using both machine-learning and natural language processing. Then, the network firewall topology is parsed to determine which vulnerabilities are reachable by adversaries. Ultimately, a state-based safety analysis ascertains which vulnerabilities are unsafe. A related vulnerability analysis problem occurs in cybersecurity operations when associating an entity’s hardware and software assets to public vulnerability databases. Assets often reveal hardware and software through installation artifacts and network service identification, and entities store these artifacts in inventory databases. However, software and hardware vendors apply a standard Common Platform Enumeration (CPE) naming convention when publicly reporting vulnerabilities. Associating these two datasets often requires many hours to days of manual inspection. The proposed solution automates the mapping approach of human analysts using fuzzy matching techniques, natural language processing, and, ultimately, machine learning to present a small set of recommendations for mapping the two datasets. The result significantly reduces human analysis time and reduces the occurrence of false positives in vulnerability notifications. Finally, cyber threat intelligence (CTI) requires associating cyber observable artifacts, such as IP addresses, URIs, and file hashes, with cyber threat tactics, techniques, and procedures. Unfortunately, most CTI data is compartmentalized across multiple organizations and cannot be shared due to the legal and reputational risk with cyber threat being associated with the entity. The approach to solving this problem inovlves using a distributed ledger with anonymous token spending and authentication. This allows a consortium of semi-trusted entities to share the workload of curating CTI for a threat sharing community’s cooperative benefit.

Huff, Philip↗
DOE OSTI2024

Integrating Human Factors in Dynamic Rideshare Assignment: Willingness-To-Pay for Delay

Dynamic ride-sharing (DRS) has been projected to be a key solution to lowering system-wide congestion. Despite recent developmental progress, demand studies for DRS suggest low levels of willingness for travelers to use such services. The disconnect between DRS system designs and user preferences limits the application impacts of DRS in the real world. Therefore, this paper aims to design a new DRS trip/vehicle assignment strategy by considering the user preferences of choices under different levels of service. In this study, an agent-based simulation approach is used to model a fleet of shared vehicles that allows DRS. An optimization model is developed to match riders to vehicles while accounting for traveler delay and delay acceptance. Travelers are also dynamically issued predictive discounts, catered to their expected willingness to pay, to incentivize them to accept longer trip delays. Results show that the proposed approach can improve system efficiency by increasing average vehicle occupancy by up to 1.0 persons/trip and DRS acceptance by up to 38.9% depending on fleet size. Additionally, congestion is eased through the decrease of empty vehicle miles traveled by up to 7.1%.

Paul, Joseph↗
DOE OSTI2025

Protecting honey bees through microbiome engineering

Honey bees are indispensable insects. Their pollination services support modern agriculture and natural ecosystems. Managed honey bee colonies face increasing threats to their survival, ranging from environmental stressors that include agrochemicals to infestations of arthropod pests and infections with microbial pathogens. Like humans, honey bees have a native gut microbiome that supports their health. However, the bee gut microbiome has a simpler composition than the gut microbiome of mammals, and its main constituent bacterial species can be easily cultured outside of the host. Furthermore, this experimental tractability and the need for new methods for protecting hive health have made honey bees a testbed for synthetic microbiomes augmented with probiotic bacteria and engineered DNA. Here, we discuss the natural benefits of bee gut bacteria, recent progress in genetically modifying these bacteria, and how symbiont-mediated RNA interference and other microbiome engineering approaches can boost bee immunity and suppress bee pathogens and parasites. Finally, we discuss how emerging methods for microbiome engineering and biocontainment could be applied to honey bees and used to address challenges in translating these proof-of-principle achievements into safe and effective technologies for field applications at scale.

Biological and medical sciences↗
DOE OSTI2025

Synopsis of NREL's Automated Mobility District (AMD) Research Program and Associated Publications

An automated mobility district (AMD) envisions a system of integrated mobility options that serves major activity centers such as campuses, central business districts, and large medical facilities. The National Renewable Energy Laboratory (NREL) has been investigating the implementation prospects for fully automated passenger transport systems that are deployed to operate within dense urban settings. This document provides a synopsis of findings revealed over the last three phases of work, which have yielded insights into the creation and management of AMDs anticipated to use automated vehicle (AV) technology over the next decade. Phase I and Phase II tracked the deployment and lessons learned from 10 early-stage demonstrations of automated shuttle deployments, and their associated insights into the challenges for automated driving systems to achieve safe operations within district-scale deployments. Phase III began in-depth investigations of critical subsystem components, as automation, electrification, and on-demand service continue to converge within initial AMD operations. These directed studies focus on elements of electrification, curbfront/station management, the role of infrastructure sensing, and overall integration of AMD safety management in central, simultaneous coordination of multiple AMD fleets. Future research in AMDs includes systems engineering methodology (more frequently referred to as "digital twins") for planning, design, testing, and ongoing operation of AMDs; location (or co-location) of management functions; and human supervision and passenger communications for safety and security in unattended vehicles. The synopsis references the foundational research products (papers and presentations) that have been published through conference proceedings, journal articles, and NREL reports.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2024

Ambient energy for buildings: Beyond energy efficiency

The following Key Messages comprise the salient findings of this study: 1. Ambient energy (from sun, air, ground, and sky) can heat and cool buildings; provide hot water, ventilation and daylighting; dry clothes; and cook food. These services account for about three-quarters of building energy consumption and a third of total US demand. Biophilic design (direct and indirect connections with nature) is an intrinsic adjunct to ambient energy systems, and improves wellness and human performance. 2. The current strategy of electrification and energy efficiency for buildings will not meet our climate goals, because the transition to an all-renewable electric grid is too slow. Widespread adoption of ambient energy is needed. Solar-heated buildings also flatten the seasonal demand for electricity compared to all-electric buildings, reducing required production capacity and long-term energy storage. In addition, ambient-conditioned buildings improve resilience by remaining livable during power outages. 3. National policies, incentives, and marketing should be enacted to promote ambient energy use. Federal administrative priorities should reflect the importance of ambient energy for buildings. Use of ambient energy should be encouraged through existing and new building codes and standards. 4. Ambient energy system design tools are needed for architects, engineers, builders, building scientists, realtors, appraisers, and consumers. PVWatts is used over 100 million times per year for photovoltaic system design. A similar, simple, and accessible tool for ambient design is crucial. 5. Training on ambient energy is needed throughout secondary, post-secondary, and continuing education for workforce development. Currently, only about 10% of colleges teach courses on passive heating and cooling systems. 6. Ambient-conditioned buildings should be demonstrated in all US climate zones. Performance should be monitored and reported, with quantitative case studies made widely available. 7. While current technology is sufficient to build high-performance ambient buildings now, research is needed to develop new technologies to harness ambient energy more effectively and more economically. Such advancements will facilitate adoption of ambient energy technologies in a wider range of buildings, including retrofits. Examples include windows with much lower thermal losses, use of the building shell as thermal storage, alternative light-weight thermal storage systems, sky radiation cooling systems, automated controls for solar gains and passive cooling, and ground coupling.

14 SOLAR ENERGY↗
DOE OSTI2022

LWR Aging Management for Life Beyond 80

While several decades of materials degradation research enabled the current US fleet of Light Water Reactors (LWR) to plan to produce electrical power through extended operations up to 80 years of plant life, it now seems appropriate to evaluate what issues, methods, and timelines need to be considered to meet the expected electric power demands for life beyond eighty (LBE) years. To address these questions, it will be necessary to review the electrical capacity and the projected LWR fleet capacity including new builds and advanced reactors. This effort should begin with a materials degradation assessment focused on known and possible unknown issues using a reduced Expanded Materials Degradation Assessment [1], which was employed to identify knowledge gaps for a second license renewal (60-80 yrs.). The focus of the LBE assessment should include: Establishing a timeline to initiate assessments of possible materials aging issues and to ensure sufficient time to evaluate materials degradation research gaps; assessing components and materials to be evaluated, e.g., metals (reactor pressure vessels and alloys within and outside the pressure boundary), concrete, cables, as well as mitigation methods, advanced monitoring, and validation with ex-service materials; initiating a LBE research plan focused on developing an expanded mechanistic understanding of materials degradation and refined models through Codes and Standards evaluation for use by the nuclear industry; and maintaining and strengthening the nuclear materials human knowledge base to address new and as yet unknown degradation modes.

Chen, Xiang↗
DOE OSTI2025

Characterization of the procoagulant phenotype of amniotic fluid across gestation in rhesus macaques and humans

Background: Amniotic fluid (AF) plays a key role in fetal development, yet the evolving composition of AF and its effects of hemostasis and thrombosis are poorly understood. Objectives: Here, we aim to determine how the evolving molecular composition of AF relates to its procoagulant properties. Methods: We analyzed the proteomes, lipidomes and procoagulant properties of AF obtained by amniocentesis from rhesus macaque and human pregnancies at gestational-age matched timepoints. Results When added to human plasma, both rhesus and human AF accelerated clotting time and fibrin generation. We identified proteomic modules associated with clotting time and enriched for coagulation-related pathways. Proteins known to be involved in hemostasis were highly correlated with each other and their intensity of expression varied across gestation in both rhesus and humans. Inhibition of contact pathway did not affect the procoagulant effect of AF. Blocking tissue factor pathway inhibitor reversed the ability of AF to block the generation of FXa. The prothrombinase activity of AF was inhibited by phospholipid inhibitors. The levels of phosphatidylserine in AF were inversely correlated with clotting time. AF promoted platelet activation and secretion in plasma. Conclusions: The addition of AF to plasma enhances coagulation in a manner dependent on phospholipids as well as the presence of proteases and other proteins that directly regulate coagulation. We describe a correlation between clotting time and expression of coagulation proteins and phosphatidylserine in both rhesus and human AF, supporting the use rhesus models for future studies of AF biology.

amniotic fluid↗
DOE OSTI2021

An Observational Understanding of Connected Lighting Systems

As part of the Internet of Things (IoT), connected lighting systems provide additional control capabilities and nonlighting-related services (such as communications and data infrastructure) to reduce energy use while increasing both application efficiency and system value. But the positive or negative energy impact of implementing these systems is still largely unknown due to the variety of human factors associated with installation, maintenance, and use. These complications interfere with adoption and acceptance rates of products that will play a significant role in achieving energy savings long-term. Next Generation Lighting Systems, or NGLS, developed and implemented an observational research methodology for connected lighting systems. The methodology was implemented at an indoor (classroom/office) Living Lab at Parsons School of Design in New York City, and an outdoor (parking lot) Living Lab at Virginia Tech Transportation Institute in Blacksburg, Virginia. Although this report focuses on the approach to indoor installations, observational research in both settings provides insight to the type, scale, and frequency of issues across available products as experienced by installing contractors, end users, and other stakeholders.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2020

Anthropogenic Markers in Alta Irrigation District Water Supply Wells

In July 2016, LLNL produced a report for the Kings River Watershed Coalition Authority (KRWCA) entitled “Groundwater Age and Nitrate Isotopic Composition in Alta Irrigation District Water Supply Wells” (Esser et al., 2016). That report summarized groundwater age and nitrate isotopic composition data produced by LLNL for Alta Irrigation District (AID) groundwater wells sampled by KRWCA in a pilot project to test the utility of advanced isotopic methods for constraining the timing and source of nitrate in groundwater at selected sites in the Kings River service area. One section of that report made recommendations for follow-on study. The first and strongest recommendation was to measure a wider suite of source tracers including co-contaminants such as herbicides, pesticides, pharmaceuticals, personal care products, and food constituents and additives. KRWCA followed up on this recommendation in Phase II of the pilot study by re-sampling the original set of wells and submitting the samples to a commercial laboratory for analysis of a limited range of co-contaminants (including pharmaceuticals, personal care products , and food constituents and additives, but not including herbicides or pesticides). They have asked that LLNL review and interpret these data in the context of previous LLNL analyses and to evaluate the utility of such co-contaminant analyses in providing additional constraints on the source of groundwater nitrate contamination in Alta Irrigation District water supply wells. The goal of the second phase of this pilot project is to evaluate the utility of co-contaminant occurrence for constraining nitrate source in groundwater at selected sites in the Kings River service area, with special reference to the use of such data in conjunction with advanced isotopic methods such as nitrate isotopic composition and groundwater age. Nitrate isotopic composition alone cannot distinguish nitrate derived from animal manure from nitrate derived from human septic waste. The presence or absence of agricultural chemicals (herbicides, pesticides, veterinary pharmaceuticals) or chemicals associated with people (human pharmaceuticals, artificial sweeteners) can help make this distinction. Co-contaminant analyses using multi-analyte LC-MS-MS protocols are now commercially available and reasonably priced. The feasibility and utility of the using co-contaminants for nitrate source attribution can be evaluated by 1) determining the degree to which co-contaminants occur in distinct and easily attributable groupings (e.g. agricultural chemicals vs personal care products and food additives); 2) determining the degree to which co-contaminant occurrence is consistent with nitrate isotopic composition and groundwater age (e.g. no co-contaminant occurrence in very old groundwater; co-contaminants consistent with animal manure or human septic waste occurring in groundwaters having nitrate isotopic composition also consistent with animal manure or human septic waste); and 3) determining the degree to which co-contaminants provide additional constraint on nitrate source over and beyond nitrate isotopic composition and groundwater age (e.g. distinguishing between animal manure and human septic waste).

58 GEOSCIENCES↗
DOE OSTI2020

Quantifying Occupant Health and Productivity for Deep Retrofits: Beyond Traditional IEQ Studies

As energy-efficiency standards for both new construction and existing building renovations become more stringent, further reductions become less tractable and more expensive. With increasing interest and rising investment in healthy built environments, integrating energy efficiency with improved occupant experience (i.e., health, comfort, and work performance) offers a new path to drive deep energy retrofits. However, the difficulty in quantifying and verifying health and productivity gains from building upgrades leads to lower valuation of human benefits in practice. Building codes and standards have progressive energy targets but often give minimum requirements to occupant health for factors such as ventilation and thermal comfort. State and federal laws in the United States that govern the energy service performance contract (ESPC) have no clear and consistent guidance on quantifying non-energy benefits and incorporating them into a formal cost-effectiveness analysis. This paper presents a methodology to measure a building’s potential performance improvement regarding occupant health based on existing evidence correlating IEQ to occupant outcomes. Health improvement measures are integrated with a building energy model to identify and measure the impact of holistic improvement strategies. The net present value of these measures is determined based on the investment costs required to attain those improvements, energy savings, and personnel gains. We will discuss results from one pilot building, which showed nearly $50 per square foot 20-year net present value using the integrated approach.

Keene, Kevin M.↗
DOE OSTI2026

Human Supervision of Autonomous Vehicle Fleet Operations and Associated Passenger Communications: Preprint

Advances in automated vehicle (AV) technology and expanded operations are rapidly emerging with Automated Mobility District (AMD) deployments in global cities. NLR's AMD research addresses critical elements of human supervision of AV fleet operations and associated passenger communications for vehicles in which no driver or safety attendant is present. Although sufficiently advanced AVs no longer have direct oversight by a driver, fleet management remains staffed with operations personnel at the operations command and control (OCC) facility. This paper examines the functionality of the OCC, drawing comparisons of how automated train control and automated people mover OCCs operate. Within an AMD, the OCC manages various vehicle types, sizes, and operational modes, including on-demand and fixed route service, to facilitate a 'network of networks' for transport within a metropolitan area. The OCC serves as oversight for multiple AV fleets assisting AVs via remote operation of vehicles, communication, and dispatching personnel to resolve problems. The OCC also coordinates system operation, geographically staging vehicles, and managing weather, police, and emergency events. Informed by traffic management center (TMC) strategies using highly integrated software and communications, OCCs facilitate seamless information flows. OCC personnel remotely assist passengers and oversee multi-party operation to ensure safety and security. Although social norms mitigate large-capacity unattended vehicle operations, social interaction in multi-party automated small vehicles has little precedent. This poses a new frontier for society and requires research to effectively understand and manage. Future research will monitor OCC implementations, passenger interfaces, and deployment scaling of initial AMD systems.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2024

Residential energy demand, emissions, and expenditures at regional and income-decile level for alternative futures

Income and its distribution profile are important determinants of residential energy demand and carry direct implications for human well-being and climate. We explore the sensitivity of residential energy systems to income growth and distribution across shared socioeconomic pathway-representative concentration pathways scenarios using a global, integrated, multisector dynamics model, Global Change Analysis Model, which tracks national/regional household energy services and fuel choice by income decile. Nation/region energy use patterns across deciles tend to converge over time with aggregate income growth, as higher-income consumers approach satiation levels in floorspace and energy services. However, in some regions, existing within-region inequalities in energy consumption persist over time due to slow income growth in lower income groups. Due to continued differences in fuel types, lower income groups will have higher exposure to household air pollution, despite lower contributions to greenhouse gas emissions. We also find that the share of income dedicated to energy is higher for lower deciles, with strong regional differences.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2026

Dataset 2: A National Dataset on Human Choices in Pooled Rideshare, 2022

Dataset 2: A National Dataset on Human Choices in Pooled Rideshare, 2022. Dataset Description: Pooled Rideshare Acceptance Survey - Phase 2 (2022, N = 2,884). This dataset captures responses from a nationally representative sample of 2,884 adults across the United States to understand choice behaviors between personal and pooled rideshare services. The primary objective of this research is to investigate choice behaviors in rideshare services and provide insights that inform service design, policymaking, and transportation planning, with the aim of encouraging pooled rideshare adoption and enhancing transportation network energy efficiency. Data was collected via an online survey administered through a national panel provider. Participants ranged in age from 18 to 94 years, and representation from all U.S. regions. The survey was designed with a focus on investigating the stated-preference between personal and pooled rideshare services. Each participant responded to 20 stated-preference questions, where they were presented with a hypothesized situation to choose between a personal rideshare option and a pooled rideshare option to complete a trip. The sociodemographic information and attitudes towards factors of pooled rideshare acceptance were also collected to support the comprehensive investigation of participants’ rideshare choice behaviors. - Phase_2_Final - Each row represents an individual respondent, and each column corresponds to a variable such as stated-preference scenario attributes, stated-preference scenario responses, attitudes toward specific service features, and sociodemographic data. The data is available in both .CSV and .SAV formats. - Phase_2_Final_MapFile - The accompanying data dictionary explains all variable labels, response scales, and codes. An .XLSX format of the full survey instrument is included to support interpretation and reuse of the dataset.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2023

Energy-Efficient Maneuvering of Connected and Automated Vehicles (CAVs) with Situational Awareness at Intersections (Final Progress Report)

The increased development of Connected and Automated Vehicle (CAV) systems, currently used for safety and driver convenience, presents new opportunities to improve the energy efficiency of vehicles. Southwest Research Institute (SwRI) achieved a 20% energy consumption reduction in a 2017 Toyota Prius Prime plug-in hybrid by using connectivity (V2V, V2I, V2X) as part of the Next Generation Energy Technologies for Connected and Automated on-Road Vehicles (NEXTCAR) program. The energy consumption gains were achieved by a combination of vehicle dynamics and powertrain control algorithms with a focus on SAE L1 and L2 automated vehicles where a human is still responsible for safe operation. SwRI is now involved in NEXTCAR-II, focusing on energy-efficient control tech for SAE Level 4/5 automated vehicles, aiming for a 30% energy reduction compared to stock hybrids. The rise of Mobility as a Service (MaaS) is driving investments in L4 and L5 automated vehicles. A study by the University of Michigan shows these vehicles might increase energy use and emissions by 3-20%. Technology similar to NEXTCAR can enhance energy efficiency in highly automated vehicles, leveraging improved sensing and actuation capabilities. While the NEXTCAR programs targeted energy efficiency improvements for a single vehicle, this program adopts a more expansive approach. It places its focus on understanding and testing the cumulative effects within a region or corridor, aiming to assess how a subset of vehicles equipped with NEXTCAR-style technologies influence the overall energy consumption of all vehicles traveling within that area. Additionally, the program explores infrastructure-based mobility solutions to optimize efficiency, and seeks to understand and quantify public perception and likelihood of technology adoption.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2022

WormBase in 2022—data, processes, and tools for analyzing Caenorhabditis elegans

WormBase (www.wormbase.org) is the central repository for the genetics and genomics of the nematode Caenorhabditis elegans. We provide the research community with data and tools to facilitate the use of C. elegans and related nematodes as model organisms for studying human health, development, and many aspects of fundamental biology. Throughout our 22-year history, we have continued to evolve to reflect progress and innovation in the science and technologies involved in the study of C. elegans. We strive to incorporate new data types and richer data sets, and to provide integrated displays and services that avail the knowledge generated by the published nematode genetics literature. Here, we provide a broad overview of the current state of WormBase in terms of data type, curation workflows, analysis, and tools, including exciting new advances for analysis of single-cell data, text mining and visualization, and the new community collaboration forum. Concurrently, we continue the integration and harmonization of infrastructure, processes, and tools with the Alliance of Genome Resources, of which WormBase is a founding member.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Earth's record-high greenness and its attributions in 2020

Terrestrial vegetation is a crucial component of Earth's biosphere, regulating global carbon and water cycles and contributing to human welfare. Despite an overall greening trend, terrestrial vegetation exhibits a significant inter-annual variability. The mechanisms driving this variability, particularly those related to climatic and anthropogenic factors, remain poorly understood, which hampers our ability to project the long-term sustainability of ecosystem services. Here, in this work, by leveraging diverse remote sensing measurements, we pinpointed 2020 as a historic landmark, registering as the greenest year in modern satellite records from 2001 to 2020. Using ensemble machine learning and Earth system models, we found this exceptional greening primarily stemmed from consistent growth in boreal and temperate vegetation, attributed to rising CO 2 levels, climate warming, and reforestation efforts, alongside a transient tropical green-up linked to the enhanced rainfall. Contrary to expectations, the COVID-19 pandemic lockdowns had a limited impact on this global greening anomaly. Our findings highlight the resilience and dynamic nature of global vegetation in response to diverse climatic and anthropogenic influences, offering valuable insights for optimizing ecosystem management and informing climate mitigation strategies.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Cyber Threat Assessment Methodology for Autonomous and Remote Operations for Advanced Reactors (Conference Presentation)

The next generation of Advanced Reactors include planned capabilities for both Autonomous (operating without human interaction for a set period-of-time) and Remote (operating with human interaction from a separate physical location) Operations. Existing Nuclear Reactor architectures include a set of safety and security constraints tightly coupled with personnel policies and procedures. As Advanced Reactors are fielded with these new Autonomous and Remote operational capabilities, the architectures and associated infrastructure services and components will perceivably expand the overall attack surface and risk calculations with regards to safe and secure operations. This paper is part of an FY21 work program focused on ensuring Advanced Reactor designs are informed with threat-based guidance on design and operation of Secure Architectures with a specific focus on the deployment of Autonomous Systems in support of Advanced Reactor Operations. The next phase of this research program is to complement produce a methodology for assessment of the cyber threat against these architectures as well as a catalogue of Use Cases to support the Advanced Reactor community in their implementation of Autonomous and Remote Operations.

97 MATHEMATICS AND COMPUTING↗