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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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At least 127 records · Page 7

Cybersecurity Vulnerability Mitigation Framework through Empirical Paradigm: Enhanced Prioritized Gap Analysis

Existing cybersecurity vulnerability assessment tools were designed based on the policies and standards defined by organizations such as the U.S. Department of Energy and the National Institute of Standards and Technology (NIST). Frameworks such as the cybersecurity capability maturity model (C2M2) and the NIST Cybersecurity Framework (CSF) are often used by the critical infrastructure owners and operators to determine the cybersecurity maturity of their facility. Although these frameworks are exceptional at performing qualitative cybersecurity analysis and identifying vulnerabilities, they do not provide a means to perform prioritized mitigation of those vulnerabilities in order to achieve a desired cybersecurity maturity. To address that challenge, we developed a framework and software application called the cybersecurity vulnerability mitigation framework through empirical paradigm (CyFEr). This paper presents the detailed architecture of CyFEr’s enhanced prioritized gap analysis (EPGA) methodology and its application to CSF. The efficacy of the presented framework is demonstrated by comparing against existing similar models and testing against the cyber injects from a real-world cyber-attack that targeted industrial control systems (ICS) in critical infrastructures.

Gourisetti, Sri Nikhil G.↗

Reinforcement Learning for Intentional Islanding in Resilient Power Transmission Systems

Intentional islanding is the process of identifying and deliberately decomposing the transmission network to form self-sustained islands from an endangered network during disruptions to improve resilience and security. Most existing intentional islanding models are offline resilience decision tools and hence do not provide outage responses in a timely manner. In this paper, a reinforcement learning (RL) based model for intentional islanding is developed, which offers real-time switching control, online deployability, and adaptability to varying system conditions. The intentional islanding process is formulated as a Markov decision process, where the optimal transmission switching policy is learned using the RL approach. The control policy is learned over an environment that encompasses a Power System Simulator for Engineering (PSS/E) model of the transmission network, facilitated by an interface to the standard openAI Gym framework. The proposed RL-based methodology aims to form stable and self-sustainable islands by ensuring voltage stability while reducing the power mismatch in the formed islands. A proximal policy optimization algorithm is designed, which is suitable for controlling the on/off status of the switches with multi-layer perceptron as value and actor networks. The effectiveness of the proposed framework in the self-recovery of the grid by island formation is applied on the modified IEEE 39-bus test network and validated by dynamic simulations.

24 POWER TRANSMISSION AND DISTRIBUTION↗

PoliMOR

PoliMOR is a scalable, automated, and customizable policy engine framework for multi-tiered parallel file systems. It is composed of single-purpose agents that handle tasks such as gathering file metadata, making policy decisions, and then executing actions based on those policies. These agents are designed to communicate using distributed message queues, allowing the number of individual agents to be scaled up as needed. PoliMOR automates the data management tasks by precluding the need for admin intervention. The agents in PoliMOR can be customized to integrate any utilities/tools that perform tasks like metadata scanning and data placement management.

Brumgard, Christopher↗

Product Innovation to Increase Low-to-Moderate-Income Customers' Adoption of Community Solar PV

This study aims to comprehensively analyze community solar project preferences for consumers and suppliers by conducting three distinct analyses. First we analyze the predictors of community solar contract adoption to understand how individual priorities affect the probability of adoption. Using an original data set of survey responses from potential community solar customers, we analyzed the predictors of contract adoption by employing a weighted logit model. We find that individuals who were previously familiar with community solar projects were significantly more likely to adopt than those who were not familiar. Secondly, a survey of community solar developers and financiers identified industry perceived barriers to community solar access and inclusion. Thirdly, we gathered payment performance information from community solar initiatives to measure how financial risks are perceived and how they interact with customer demographics. Our study is beneficial to the public by providing insights into the drivers and barriers of community solar adoption and sheds light on the importance of understanding individual priorities in designing effective community solar policies. The community solar industry has changed significantly since the beginning of this project. The industry continues to grow at a rapid rate, with an additional 7 gigawatts expected to come online between 2022 and 2027. With federal pressure to meet climate goals, as the harms of climate change continue to impact everybody, legislators are looking to community solar as a method to achieving their states energy policy goals. These new policies that push for low-to-moderate inclusion, coupled with the increase in community solar capacity illustrate a new era for the community solar industry. A number of policies have arisen in the last few months that push for more inclusive practices including the groundbreaking Solar for All program run by the EPA. The research created a “best practice” contract that can then be used, in conjunction with the manuscript and validated study, to pitch the industry on a more inclusive community solar product.

14 SOLAR ENERGY↗

LA100 Equity Strategies

In the Los Angeles 100% Renewable Energy Study (LA100), the National Renewable Energy Laboratory (NREL) found that the City of Los Angeles can achieve its ambitious goal of reliable, 100% carbon-free energy as early as 2035. While all communities will benefit from air quality and health improvements of clean energy, improving equity in participation and outcomes requires intentionally designed equity strategies. To plan for a clean energy future that benefits all Angelenos, the Los Angeles Department of Water and Power (LADWP), NREL, and the University of California Los Angeles (UCLA) partnered on the LA100 Equity Strategies project. In an innovative, community-informed approach, the LA100 Equity Strategies project integrated robust social science research techniques with rigorous data analysis - and incorporated what community members themselves know is needed to achieve a more equitable energy future. The team developed effective strategies for engaging communities, funding equitable technology and infrastructure investments, expanding existing clean energy and energy assistance programs, and designing new programs and policies to enhance equity.

community↗

Assessing Customer Experience and Business Models around Price-to-Device Communication and Smart Control Pathways in CalFlexHub

California is facing three major challenges in electrical grid operation: renewable overgeneration, steep evening ramping, and growing peak demand. The state has identified dynamic retail price response as a key strategy evidenced by CPUC’s Dynamic Rates proceeding and CEC’s Load Management Standards. Furthermore, the CEC launched a $16M “California Load Flexibility Research and Deployment Hub (CalFlexHub)” administered by Berkeley Lab to accelerate price-response flexible load technologies in buildings and EV charging. There are more than 16 laboratory and field demonstration projects in CalFlexHub, each demonstrating innovative automated price-response technologies. CalFlexHub tests various pathways through which hourly price signals and triggered control commands are communicated to load-flexible devices such as smart thermostats, heat pumps, water heaters, and EVs. We identified seven unique communication and control pathways, which involve combinations of third-party cloud, device OEM’s cloud, building central gateway, and local controller in between the price server and the load-flexible devices. It is important for utilities and policy makers to understand the long-term implications of each pathway in designing future programs and creating related policies and mandates for market transformation. We propose an evaluation framework including the following aspects: ● Functionality: connectivity and uptime, resilience, and optimization; ● Customer experience: simplicity in setup, troubleshooting support, continuity, customer choice, first cost, and ongoing cost; ● Business model and scalability: advance interoperability, holistic solution, bridge unique gap, customer base, and value streams and pricing structures. In this paper, we identify emerging business models associated with each communication pathway and discuss their positive features and challenges from the above aspects.

Liu, Jingjing↗

Estimation of abatement potentials and costs of air pollution emissions in China

Understanding the air pollution emission abatement potential and associated control cost is a prerequisite to design cost ef?cient control policies. In this study, a linear programming algorithm model, International Control Cost Estimate Tool, was updated with cost data for applications of 56 types of end-of-pipe technologies and ?ve types of renewable energy in 10 major sectors namely power generation, industry combustion, cement pro-duction, iron and steel production, other industry processes, domestic combustion, transportation, solvent use, livestock rearing, and fertilizer use. The updated model was implemented to estimate the abatement potential and marginal cost of multiple pollutants in China. The total maximum abatement potentials of sulfur dioxide (SO2), nitrogen oxides (NOx), primary particulate matter (PM2.5), non-volatile organic compounds (NMVOCs), and ammonia (NH3) in China were estimated to be 19.2, 20.8, 9.1, 17.2 and 8.6 Mt, respectively, which accounted for 89.7%, 89.9%, 94.6%, 74.0%, and 80.2% of their total emissions in 2014, respectively. The associated control cost of such reductions was estimated as 92.5, 469.7, 75.7, 449.0, and 361.8 billion CNY in SO2, NOx, primary PM2.5, NMVOCs and NH3, respectively. Shandong, Jiangsu, Henan, Zhejiang, and Guangdong provinces exhibited large abatement potentials for all pollutants. Provincial disparity analysis shows that high GDP regions tend to have higher reduction potential and total abatement costs. End-of-pipe technologies tended be a cost-ef?cient way to control pollution in industries processes (i.e., cement plants, iron and steel plants, lime production, building ceramic production, glass and brick production), whereas such technologies were less cost- effective in fossil fuel-related sectors (i.e., power plants, industry combustion, domestic combustion, and transportation) compared with renewable energy. The abatement potentials and marginal abatement cost curves developed in this study can further be used as a crucial component in an integrated model to design optimized cost-ef?cient control policies.

Zhang, Fenfen↗

2025 Large Load Literature Review

This literature review catalogs more than 90 publications focused on large loads, and groups the documents and resources thematically into 12 categories, (listed below). The 2026 Large Load Literature Review and Data Sources summary reports are available here: https://emp.lbl.gov/publications/2026-large-load-literature-review -Load forecasting -Data sources -Reliability and resource adequacy -Large load interconnection -Demand flexibility -Generation -Co-location -Data center location/infrastructure -Large load tariffs -Policy options -Maps and tools -Design and operations

97 MATHEMATICS AND COMPUTING↗

Community Solar 101 [Slides]

This presentation deck provides an overview of community solar for a new user. The presentation covers community solar structures, considerations for low- and moderate-income (LMI) customers, policies related to community solar design, and a community solar market overview.

14 SOLAR ENERGY↗

Staying cool: The development of India's pioneering energy efficiency policy for chillers

Abstract Chillers are the key energy‐consuming piece of equipment in most large space cooling systems. They can account for more than 40% of total energy consumption in any typical commercial building and in specific industrial building installations depending on the product and process. With climate change driving rapidly rising demand for commercial and industrial cooling, especially in emerging economies, energy efficiency policies for chillers are crucial to moderate future electricity demand and thereby minimize greenhouse gas emissions. However, most developing and emerging economies lack energy efficiency policies for this significant and growing cooling equipment sector. India recently announced new energy efficiency policies for chillers, projected to avoid 28 TWh of electricity consumption and 23 million tons of CO 2 emissions cumulatively through 2030. This article presents a case study of the unique challenges and solutions required to design a new energy efficiency policy for chillers in India. First, the energy consumed in chiller systems is sensitive to building occupancy, load changes, seasonal variations, operation and maintenance, and climatic conditions. In order to address these sensitivities, the chiller testing standard in India factors local weather and temperature conditions into energy performance ratings to account for these sensitivities. Further, every large chiller is a customized product, therefore developing a viable policy and implementation process required collaboration with international and national experts in standardization, manufacturers, building consultants, and testing laboratories. This article is categorized under: Energy Efficiency > Economics and Policy Solar Energy: Thermal ‐‐> Climate and Environment

Mukherjee, P. K.↗

Institutional and Policy Landscape for Solar-Plus-Storage Deployment by Electric Cooperatives

As co-location with battery storage has become a significant solar project-design trend across the United States, policies at all levels have started to adjust. Generally, these policies address battery storage development in major, urban markets, served by large investor-owned utilities (IOUs). Yet all kinds of utilities nationwide are seeking ways to tap into the fast-growing battery storage market, and they are all stakeholders in the federal, state, and local policies that impact the storage market's development. The electric cooperative sector, which includes some 830 distribution utilities and 63 generating and transmission (G&T) utilities across a mostly rural landscape, is no exception. It is impacted by federal, state, and local government policy requirements and incentives, as well as by policies that are controlled by the sector's own institutions. The objective of this paper is to identify and discuss the various policy and institutional factors that are relevant to the electric cooperative sector, and especially to local, distribution-level electric cooperatives (co-ops) that may be interested in procuring energy storage. Given this, the paper is largely written from the local co-op perspective. It also may be useful to wholesale G&T cooperatives. Other parties that may find the paper useful include storage developers, who are often unfamiliar with co-ops; local and state policymakers addressing policy options for this sector, and local renewable or storage stakeholders, who wish to understand the policy landscape affecting their local utility. Although co-op energy storage programs may tap customer-side batteries, this examination is focused on utility-side "front of the meter" projects and the policy issues they raise.

14 SOLAR ENERGY↗

Preliminary Shielding Analysis for the 1012 400 MeV Linac Building

EIC is planning to purchase a 400 MeV turnkey pre-injector linear accelerator (Linac) which will be in a new building at the end of an existing RHIC tunnel at 12 o’clock. The building will contain the Linac Tunnel and associated accelerating structures, Klystron Gallery and waveguides, laser, utility, and control rooms. This report only examines the radiation source term produced by operating the Linac and not supplemental shielding that may be required to shield the Klystrons or solid state amplifiers in the Klystron Gallery from the x rays they emit. Normal Portland concrete blocks are planned to provide shielding between the Linac vault and the occupiable portions of the building per the attached drawing. It is expected that this facility will not be routinely occupied during operations (post commissioning). The shielding design considers EIC’s draft Shielding Policy that states shielding and other controls for areas where access is controlled for radiological purposes will be designed so that an ambient dose of 100 mrem per year to a worker is not likely.

43 PARTICLE ACCELERATORS↗

Analysis of incentive policies for phosphorus recovery at livestock facilities in the Great Lakes area

Livestock operations have been highly intensified over the last decades, resulting in the advent of large concentrated animal feeding operations (CAFOs). Intensification decreases production costs but also leads to substantial environmental impacts. Specifically, nutrient runoff from livestock waste results in eutrophication, harmful algal blooms, and hypoxia. The implementation of nutrient recovery systems in CAFOs can abate nutrient releases and negative ecosystem responses, although they might negatively affect the economic performance of CAFOs. We design and analyze potential incentive policies for the deployment of phosphorus recovery technologies at CAFOs considering the geospatial vulnerability to nutrient pollution. The case study demonstration consists of 2217 CAFOs in the U.S. Great Lakes area. The results reveal that phosphorus recovery is more economically viable in the largest CAFOs due to economies of scale, although they also represent the largest eutrophication threats. For small and medium-scale CAFOs, phosphorus credits progressively improve the profitability of nutrient management systems. The integration of biogas production does not improve the economic performance of phosphorus recovery systems at most of CAFOs, as they lack enough size to be cost-effective. Furthermore, phosphorus recovery proves to be economically beneficial by comparing the net costs of nutrient management systems with the negative economic impact derived from phosphorus releases. The incentives necessary for avoiding up to 20.7.10 3 ton/year phosphorus releases and achieve economic neutrality in the Great Lakes area are estimated at $223 million/year. Additionally, the fair distribution of limited incentives is studied using a Nash allocation scheme, determining the break-even point for allocating monetary resources.

54 ENVIRONMENTAL SCIENCES↗

Retrofit-ability: A supplementary metric to inform energy efficiency policies and programs

Building Energy Use Intensity (EUI) has been commonly used to facilitate policy makers and utilities to design energy efficacy programs and help building managers prioritize investment in building upgrades. Buildings with higher EUIs are usually chosen as better candidates for retrofit. Our study of nearly one hundred buildings in Seattle’s Building Tune Up Accelerator program and thousands of buildings in the Asset Score database reveals that EUI (after weather/location/use type normalization) alone is not the best indicator of a building’s potential to save energy, especially for those buildings in the mid-range (30-70 percentile EUI). In this paper, we introduce the concept of “retrofit-ability” — a building’s real potential to reduce its energy use cost-effectively — as a supplementary metric to inform energy efficiency policy and investment. Currently, such potential analyses are predicted for a building stock using prototypical building models or statistical data. However, typical buildings or general historical data may not sufficiently represent building configurations in a portfolio and predict their saving potentials. We utilized machine learning to investigate how key building characteristics (such as envelope attributes, HVAC type, location, use type, etc.) affect a building’s improvement potentials and developed a low-cost method to quantify such potentials for a portfolio of buildings. The supplementary perspective provided by “retrofit-ability” highlights which building assets correlate most with a building’s energy savings potential across region, building use type and more.

Wang, Na↗

Farmer characteristics and decision-making: A model for bioenergy crop adoption

We report the commercial development of biofuels and bioproducts depends on whether renewable biomass feedstock is available while not directly competing with the production of food. Farmers are one of the most important stakeholders in the biofuel supply chain and confront a range of uncertainties while entering the bioenergy market. Their decision-making process is extremely complex and rarely purely rational. Modeling farmer behavior requires considering a wide range of individual-level factors, socio-temporal dynamics, institutional settings, and their interactions. These characteristics make agent-based modeling a suitable framework for evaluating such systems. We developed a model to simulate farmer bioenergy crop adoption behavior across a 50-county study region in Nebraska, Kansas, and Colorado. The analysis considers adoption decisions for two bioenergy feedstocks, crop residues and energy crops. We examine the influence of individual and farm characteristics, market structure, social networks, and media influence on farmer adoption decisions. Our results indicate that different factors can have varied impacts on the speed of adoption for the crop residues and energy crops. Identifying levers that have the most impact on grower adoption can inform the design of interventions both from policy and private sector standpoints with important implications for the future the bioenergy industry.

09 BIOMASS FUELS↗

Advancements in Yttrium Hydride Moderator Development

As microreactors evolve to become a more affordable and efficient worldwide energy source, the development of moderator material within the system to decrease the required mass of low-enriched uranium fuel is important. The use of low- instead of high-enriched uranium in small nuclear reactors stems from recent national policies associated with nonproliferation. New designs are being developed for a range of applications and nuclear space systems in particular. Using system geometries such as those described in this paper, the next step is to advance the technology readiness level of moderator material such as delta-yttrium hydride (YH x,x = 1.6–2.0 ) so that it can be qualified for use in a microreactor system. Although characterization of unirradiated material has been documented previously, to fully understand the performance of this material, behavior in relevant irradiation environments must occur. This paper describes the fabrication of yttrium hydride samples through innovative techniques and how these samples were tested in two relevant neutron environments. These two experiments include (1) a critical experiment performed at the National Criticality Experiments Research Center (NCERC) to evaluate reactivity changes in a neutron-critical environment and (2) irradiation in the Advanced Test Reactor (ATR) to assess structural integrity/material form, thermophysical data, hydrogen permeability, and other features post irradiation. For this purpose, hundreds of samples were fabricated for the NCERC and ATR experiments and are described within this paper.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

HAM: Hotspot-Aware Manager for Improving Communications with 3D-Stacked Memory

merging High-Performance Computing (HPC) workloads, such as graph analytics, machine learning, and big data science, are data-intensive. Data-intensive workloads usually present fine-grained memory accesses with limited or no data locality, and thus incur frequent cache misses and low utilization of memory bandwidth. 3D-stacked memory devices such as Hybrid Memory Cube (HMC) and High Bandwidth Memory (HBM) can provide significantly higher bandwidth than conventional memory modules. However, the traditional interfaces and optimization methods for JEDEC DDR devices do not allow to fully exploit the potential performance of 3D-stacked memory with the massive amount of irregular memory accesses of data-intensive applications. In this paper, we propose a novel Hotspot-Aware Manager (HAM) infrastructure for 3D-stacked memory devices capable of optimizing memory access streams via request aggregation, hotspot detection, and in-memory prefetching. %and an associated hotspot-aware page policy. We present the HAM design and implementation, and simulate it on a system using RISC-V embedded cores with attached HMC devices. We extensively evaluate HAM with over 12 benchmarks and applications representing diverse irregular memory access patterns. The results show that, on average, HAM reduces redundant requests by 37.51\% and increases the prefetch buffer hit rate by 4.2 times, compared to a baseline streaming prefetcher. On the selected benchmark set, HAM provides performance gains of 21.81\% in average (up to 34.28\%) and power savings of 35.07\% over a standard 3D-stacked memory.

Wang, Xi↗

ORCHID: Orchestrated Retrieval-Augmented Classification of High-Risk Property with Intelligent Decision-Making

High-Risk Property (HRP) classification is critical at U.S. Department of Energy (DOE) sites, where inventories include sensitive and often dual-use equipment. Compliance must track evolving rules designated by various export control policies to make transparent and auditable decisions. Traditional expert-only workflows are time-consuming, backlog-prone, and struggle to keep pace with shifting regulatory boundaries. We propose ORCHID, a modular agentic framework for HRP classification that pairs retrieval-augmented generation (RAG) with human oversight to produce policy based outputs that can be audited. Small cooperating agents—retrieval, description refiner, classifier, validator, and feedback logger—coordinate via agent-to-agent messaging and invoke tools through the Model Context Protocol (MCP) for model-agnostic on-premise operation. The interface follows an "Item to Evidence to Decision" loop with step-by-step reasoning, on-policy citations, and append-only audit bundles (run-cards, prompts, evidence). In preliminary tests on real HRP cases, ORCHID improves accuracy and traceability over a non-agentic baseline while deferring uncertain items to Subject Matter Experts (SMEs). The demonstration shows single item submission, grounded citations, SME feedback capture, and exportable audit artifacts—illustrating a practical path to trustworthy LLM assistance in sensitive DOE compliance workflows.

Das, Sanjay [ORNL] (ORCID:0009000542591915)↗