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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 109 records · Page 6

Risk Retirement—Decreasing Uncertainty and Informing Consenting Processes for Marine Renewable Energy Development

Marine renewable energy (MRE) is under development in many coastal nations, adding to the portfolio of low carbon energy sources that power national electricity grids as well as off-grid uses in isolated areas and at sea. Progress in establishing the MRE industry, largely wave and tidal energy, has been slowed in part due to uncertainty about environmental risks of these devices, including harm to marine animals and habitats, and the associated concerns of regulators and stakeholders. A process for risk retirement was developed to organize and apply knowledge in a strategic manner that considered whether specific environmental effects are likely to cause harm. The risk retirement process was tested against two key MRE stressors: effects of underwater noise from operational MRE devices on marine animals, and effects of electromagnetic fields from MRE electrical export cables on marine animals. The effects of installation of MRE devices were not accounted for in this analysis. Applying the risk retirement process could decrease the need for costly investigations of each potential effect at every new MRE project site and help move the industry beyond current barriers.

16 TIDAL AND WAVE POWER↗

Risk-informed Hierarchical Control of Behind-the-Meter DERs with AMI Data Integration (Final Technical Report)

This project addresses several key barriers to implement the next generation demand response applications and provides a clear understanding of implementing hierarchical and standalone control using AMI data. Through this program, Eaton has developed and tested a meter-as-a-controller prototype with the help of other partners--- National Renewable Energy Laboratory (NREL), Electric Power Research Institute (EPRI), Pecan St Inc. (PSI), and Delaware Electric Cooperative (DEC). The controller can utilize residential controllable loads such as heating, ventilation, and air conditioner (HVAC), electric water heater and distributed energy resources like solar PV and battery energy storage systems for off-setting the demand that is required from the grid, thus providing reliable grid-services for demand reduction or peak shaving. The controller is also capable of coordinating the resources of the premises for better management and energy efficiency while meeting the comfort bound of the premises owner as quality-of-service. The development has been demonstrated in a three virtual-home setup at system performance lab of NREL with real appliances (HVAC, electric water heater, solar PV, and battery). The technology has also been proved through laboratory and field demonstration with successful interconnectivity (e.g., end-to-end communication and data exchange) between the residential appliances and utility through the RF network at Delaware Electric Co-op (DEC) in Delaware.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Developing Standards for AI/ML Systems in Civil Aviation: Challenges and Barriers

The inability to establish appropriate assurance methods for AI/ML components in safety critical systems leaves us unable to effectively manage the risks and benefits of such systems. It drives cost of development for systems with AI/ML components uneconomically high, it delays the adoption of systems with AI/ML components at scale, and it can result in catastrophic consequences in terms of the safety of systems with AI/ML components. In this presentation we will explore what constitutes sufficient scientific-based evidence to substantiate a safety claim related to an AI/ML component performing a safety-critical function.

AI/ML Standards↗

Wind Plant Performance Prediction Benchmark Phase 1 (Technical Report)

Financial risk resulting from the uncertainty associated with developing, owning, and operating wind power plants remains a barrier to reducing the levelized cost of energy (LCOE). On average, modern wind power plants in the U.S. underperform their expected annual energy output by 3.5-4.5% , with many underperforming by over 10%. To compensate for this uncertainty, investors require a larger return on investment (ROI) and apply "knock-down" factors that mask much of the underlying sources of uncertainty. Wind energy projects thus have reduced access to low-cost capital. Furthermore, operating wind plants often take a simple approach to estimating operations & maintenance (O&M) costs (e.g. straight-line estimates based on similar plants), which can eat into profits. To overcome these issues, the wind industry must improve the models they use for estimating wind plant performance and operations. An industry consortium (IC) requested that the National Renewable Energy Laboratory (NREL) lead a Department of Energy (DOE) working group to benchmark the accuracy of wind power plant energy predictions against real operational data. The IC was also motivated by DOE and NREL's potential to characterize systematic energy underperformance, identify sources of uncertainty, and explore root causes. The Wind Plant Performance Prediction (WP3) project was created out of this request, and this report represents the successful completion of Phase 1 of the WP3 project. During the project, wind plant owners provided both pre-construction and operational data to NREL. The pre-construction data was provided to wind resource assessment (WRA) consultants so they could conduct energy yield assessments (EYA). NREL took all of the completed EYAs, along with the operational data, and conducted an operational assessment to benchmark the EYA results against actual operational data. Given the large amounts of sensitive data required for this effort, as well as historical opposition to sharing data within industry, successful completion of Phase 1 represents an unprecedented milestone for industry data sharing. To improve the accuracy and confidence of pre-construction EYAs, wind plant owners and investors need better, more certain, energy yield predictions. The WP3 Benchmark Project is an industry-driven response to this reality. For the first time, industry has taken the important step of working together at scale, sharing valuable operational data with DOE and NREL in order to investigate the sources of bias and uncertainty in these energy estimates. This IC provides wind plant preconstruction and operational data to NREL in an organized and documented fashion and provides guidance and feedback as needed. The IC also provides introspection of the design of experiment, key metrics of success, data challenges, analysis best practices, and quality of results.

17 WIND ENERGY↗

SAM Code Development for Source Term Modeling in Fluoride-salt-cooled High-temperature Reactors

The SAM code is under development and supported by DOE-NE’s Nuclear Energy Advanced Modeling and Simulation program as a modern system-level modeling and simulation tool for advanced non-light water reactor safety analyses. These advanced reactor concepts incorporate novel and improved approaches to achieve safety and economic feasibility. Many concepts leverage higher operating temperatures for improved efficiency with a variety of coolants and structural materials to support those needs. Such design choices may also pose unique radiological source term risks. There are continuous efforts to incorporate new physics and phenomena relevant to advanced reactor concepts, including capabilities to enable system-level source term modeling. The Pebble-Bed Fluoride-salt-cooled High-temperature Reactor (PB-FHR) is a promising candidate among advanced nuclear reactor concepts with its improved passive safety characteristics and high thermal efficiency. In addition to past efforts to support the development and utilization of SAM for PB-FHR safety analysis, the species transport modeling capabilities in SAM have been extended to simulate source term phenomena in concepts like the PB-FHR. The PB-FHR concept utilizes pebble-form TRISO fuel and FLiBe salt coolant to provide robust barriers to the release of almost all fission products and radiological source terms. However, tritium poses a unique radiological risk due to its significant production from neutron interactions with 6 Li and 9 Be in the FLiBe as well as its high mobility at elevated temperatures where it can permeate through structural metals. Secondly, the use of graphite at elevated temperatures poses the risk of oxidation damage to any structural components or fuel pebbles that are exposed to accidental air ingress. This report summarizes progress made in modeling these phenomena in SAM, which leverages the system-level multi-physics thermal hydraulic simulation to support an effective engineering-scale source term modeling capability. A tritium transport model is developed to simulate the various transport pathways in FHR and MSR concepts and is presented through verification and validation examples as well as demonstrations simulating experimental test loops and reference plant FHR models. A graphite oxidation model is also introduced to calculate local oxidation rates and is presented with initial validation results.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

CONTAMINATION CONTROL FOR ULTRA-SENSITIVE LIFE DETECTION SCIENCE MISSIONS

"This study report summarizes technological developments in science-required contamination control for cost-capped, life-detection missions in the Solar System. Technology advances focus on developing implementable strategies to restrict contamination of the spacecraft and instruments by the launch vehicle hardware. Secondary bake out operations during cruise further reduce molecular contaminants down to femtomolar levels in the sample path. The study validated a full-spacecraft, deployable barrier design as an effective strategy to isolate the spacecraft from the pre-launch processing and launch environment (e.g., fairing acoustic materials). It accommodates late mounting of RTGs and other required prelaunch activities. A new, high-fidelity physics, contamination-transport model for particles (including cells and their parts) and science-relevant molecules (e.g., possible biomolecules) was developed to validate the barrier concept. Importantly, this model takes into account the physics of extremely clean surfaces achieved by the best traditional contamination engineering. The ability to deal with very low levels of particulate and molecular contamination makes this model unique among standard contamination modeling approaches. Modeling also demonstrated that a high-temperature bake out during interplanetary cruise of the sample collector that comprises the largest surface area in the sample path for an Enceladus orbiter reference mission, was extremely effective. This study included the evaluation of other details necessary for an effective contamination control strategy for life detection missions including feasibility of achieving parts per trillion level cleanliness for semi-volatile hydrocarbons in nitrogen purge gas, identification of launch vehicle services required for the baseline contamination control, and defining additional contamination control measures to be taken during launch operations. Key results of the study are: • New spacecraft barrier design that accommodates RTGs is readily cleanable and repairable. Deployment of a 1/3 scale model was successfully demonstrated. • The barrier reduces particle contamination (likely biological) from fairing to spacecraft by 1e-2 to 1e-3. • On-cruise bake-out of critical surfaces significantly reduced molecular contamination (by as much as 1e-12). Subsequently, the probability of a surface contamination particle being transported to an instrument by an ice particle is less than 5.1e-5 (for microbes specifically, 4.39e-10). The report concludes that a full-spacecraft barrier designed specifically for life-detection missions that require stringent control of particulate and molecular contaminates is an effective means of mitigating risks of false positive and negative results for life signature investigations. Further, secondary cleaning steps for critical sections of the sample path can be highly effective at reducing molecular contaminants to low femtomolar levels."

Contamination↗

Contamination Control for Ultra-Sensitive Life-Detection Missions

"This study report summarizes technological developments in science-required contamination control for cost-capped, life-detection missions in the Solar System. Technology advances focus on developing implementable strategies to restrict contamination of the spacecraft and instruments by the launch vehicle hardware. Secondary bake out operations during cruise further reduce molecular contaminants down to femtomolar levels in the sample path. The study validated a full-spacecraft, deployable barrier design as an effective strategy to isolate the spacecraft from the pre-launch processing and launch environment (e.g., fairing acoustic materials). It accommodates late mounting of RTGs and other required prelaunch activities. A new, high-fidelity physics, contamination-transport model for particles (including cells and their parts) and science-relevant molecules (e.g., possible biomolecules) was developed to validate the barrier concept. Importantly, this model takes into account the physics of extremely clean surfaces achieved by the best traditional contamination engineering. The ability to deal with very low levels of particulate and molecular contamination makes this model unique among standard contamination modeling approaches. Modeling also demonstrated that a high-temperature bake out during interplanetary cruise of the sample collector that comprises the largest surface area in the sample path for an Enceladus orbiter reference mission, was extremely effective. This study included the evaluation of other details necessary for an effective contamination control strategy for life detection missions including feasibility of achieving parts per trillion level cleanliness for semi-volatile hydrocarbons in nitrogen purge gas, identification of launch vehicle services required for the baseline contamination control, and defining additional contamination control measures to be taken during launch operations. Key results of the study are: • New spacecraft barrier design that accommodates RTGs is readily cleanable and repairable. Deployment of a 1/3 scale model was successfully demonstrated. • The barrier reduces particle contamination (likely biological) from fairing to spacecraft by 1e-2 to 1e-3. • On-cruise bake-out of critical surfaces significantly reduced molecular contamination (by as much as 1e-12). Subsequently, the probability of a surface contamination particle being transported to an instrument by an ice particle is less than 5.1e-5 (for microbes specifically, 4.39e-10). The report concludes that a full-spacecraft barrier designed specifically for life-detection missions that require stringent control of particulate and molecular contaminates is an effective means of mitigating risks of false positive and negative results for life signature investigations. Further, secondary cleaning steps for critical sections of the sample path can be highly effective at reducing molecular contaminants to low femtomolar levels."

contamination, life detection, barrier, modeling↗

Advanced Transmission Technologies –GETs and HPCs Session 3: HPCs and Building Actions Plans to Digital Assurance Risks

The third session of the Idaho National Laboratory’s (INL) Technical Assistance for Digital Assurance (TADA) program, held on November 11, 2025, centered on High Performance Conductors (HPCs) and the formulation of action plans to address digital assurance risks associated with Grid-Enhancing Technologies (GETs). This session convened experts from utilities, vendors, and government agencies to examine the technical, operational, and cybersecurity aspects of HPC deployment. Discussions highlighted the benefits of HPCs, such as their ability to rapidly increase transmission capacity using existing corridors, improve grid resilience, reduce system losses, and align with FERC Orders 2023 and 1920. Participants evaluated supply chain and digital assurance risks, including reliance on imported materials, limited domestic manufacturing capacity, workforce shortages, and traceability issues. The session also emphasized the importance of digital trust, integration-layer cybersecurity, and unified risk frameworks, introducing tools like intrusion detection systems, encryption, zero trust networking, and firmware integrity. Recaps of earlier workshops on Dynamic Line Ratings (DLRs), Advanced Power Flow Control (APFC), and Transmission Topology Optimization (TTO) underscored institutional barriers and integration challenges. Action plans were proposed to mitigate issues such as inconsistent cybersecurity practices, SBOM usage, supply chain visibility, operator trust, and misaligned incentives. Additionally, INL presented its supply chain risk management tools and Cyber-Informed Engineering (CIE) principles to support secure procurement and system design. The session concluded with a commitment to share key takeaways, incorporate cohort feedback into future policy development, and continue collaborative engagement through upcoming pilot activities. Session 3 of 3.

24 - POWER TRANSMISSION AND DISTRIBUTION↗

Spatial ecology of translocated raccoons

Raccoons (Procyon lotor) are routinely translocated both legally and illegally to mitigate conflicts with humans, which has contributed to the spread of rabies virus across eastern North America. The movement behavior of translocated raccoons has important ramifications for disease transmission yet remains understudied and poorly quantified. To examine the spatial ecology of raccoons following experimental translocation, we performed reciprocal 16 km-distance translocations of 30 raccoons between habitats of high and low raccoon density (bottomland hardwood and upland pine, respectively) across the Savannah River Site (SRS) in Aiken, South Carolina, USA (2018–2019). Translocation influenced patterns of raccoon space use, with translocated animals exhibiting a 13-fold increase in 95% utilization distributions (UDs) post- compared to pre-translocation (mean 95% UD 35.8 ± 36.1 km 2 vs 1.96 ± 1.17 km 2 ). Raccoons originating from upland pine habitats consistently had greater space use and larger nightly movement distances post-translocation compared to raccoons moved from bottomland hardwood habitats, whereas these differences were generally not observed prior to translocation. Estimated home ranges of male raccoons were twice the area as estimated for female raccoons, on average, and this pattern was not affected by translocation. After a transient period lasting on average 36.5 days (SD = 30.0, range = 3.25–92.8), raccoons often resumed pre-experiment movement behavior, with 95% UD sizes not different from those prior to translocation (mean = 2.27 ± 1.63km 2 ). Most animals established new home ranges after translocation, whereas three raccoons moved > 16 km from their release point back to the original capture location. Four animals crossed a 100-m wide river within the SRS post-translocation, but this behavior was not documented among collared raccoons prior to translocation. Large increases in space use combined with the crossing of geographic barriers such as rivers may lead to elevated contact rates with conspecifics, which can heighten disease transmission risks following translocation. These results provide additional insights regarding the potential impacts of raccoon translocation towards population level risks of rabies outbreaks and underscore the need to discourage mesocarnivore translocations to prevent further spread of wildlife rabies.

59 BASIC BIOLOGICAL SCIENCES↗

Machine-Learning-Based Mapping and Modeling of Solar Energy with Ultra-High Spatiotemporal Granularity

Despite the rapid growth of solar energy, we still lack a dynamic, high-fidelity database that tracks the spatiotemporal variations of solar PVs and their associated infrastructures across different places at a spatially resolved scale. The absence of such data presents a barrier to various applications such as solar PV growth projection, solar energy integration, solar incentive design, and climate risk assessment. In this project, we aim to bridge this gap by developing AI-based algorithms to extract granular information about solar PV installations and their associated infrastructures (i.e., distribution grids) from widely available unstructured data like remote sensing images and street views. As a result, we have built the Solar Energy Atlas, a fine-grained, large-scale geospatial overlay of distributed solar PVs and distribution grids. On top of it, we have advanced the understanding of solar adoption and distribution grid vulnerability to climate-induced extremes. Our major contributions can be summarized as follow: (1) By developing new AI algorithms, we have built the most comprehensive solar PV spatiotemporal database covering the entire US. This is the first time we obtained the exact GPS locations, size, subtype, and installation year information for rooftop solar PVs across the US. This database can be used for solar PV growth projection, solar energy integration, solar energy policy analysis and design, and spatially-resolved climate risk assessment. (2) Leveraging this database, we have uncovered the socioeconomic driving factors that are correlated with earlier onset of solar adoption and higher saturated adoption levels. We have identified the heterogeneity in the effects of different types of financial incentives on solar adoption and provided implications for tailoring incentive design based on local income levels to promote equitable solar adoption. (3) We have developed a distribution grid GIS mapping algorithm which can obtain granular geospatial and topology information about distribution grids using multi-modal open data, reducing the dependency on hard-to-obtain smart meter data of conventional approaches. It shows effectiveness in both the U.S. and Sub-Saharan Africa. Using this algorithm, we have uncovered the non-uniform vulnerability of distribution grids to wildfires in California in the aspects of undergrounding protection and Distributed Energy Resources (DER) preparedness. This has provided important implications for improving the affordability and equity of grid adaptation approaches. (3) We have made our produced database publicly available and provided user-friendly interface to enable various stakeholders and the general public to interact with the data. We have also integrated the produced data into the Data Commons platform to enable the public to access the data and correlate it with other location-specific characteristics simply using natural language as queries. The impact of our project is three-fold: (1) New algorithms for mapping solar PVs and distribution grids across space and time, which are open source to facilitate researchers and industry; (2) New databases of solar PVs and distribution grids that have been made publicly available for engineering, social, and policy applications; (3) New understandings and actionable insights on the potential approaches to promoting solar adoption and reducing energy infrastructure vulnerabilities. In this report, we start by discussing the project background and motivation (section 5), followed by the overview of project objectives (section 6). Results and discussion for each task are presented in section 7. Significant accomplishments are summarized in section 8. This report will be concluded by discussing the paths forwards (section 9), products (section 10), and team roles (section 11).

14 SOLAR ENERGY↗

Research and Development on Advanced Electrochemical Energy Storage Devices Enabling a Spectrum of Electrified Vehicles

The USABC Advanced Battery development plan had the following three focus areas: 1. Existing technology validation, implementation, and cost reduction 2. Identification of the next viable technology with emphasis on the potential to meet USABC cost and energy density goals. 3. Support high-risk, high-reward battery technology R&D The primary aim of this project was focused on the barriers that most impede wider public adoption of electrification in vehicles-cost, energy density, low-temp performance, calendar life, and improvements in abuse tolerance. The specific objectives are as follows: Cost Reduction: drive to significantly reduce battery cost to be in-line with the $\$$100/kWh or less (by the end of calendar year 2020) DOE cost goals. Additionally, goals of $\$$75/KWh were set for 2023 aligned with fast charge and some offset of energy density. Energy Density Increase: focus on improving the cell-level specific energy and energy densities to >350 watt hours per kilogram (Wh/kg) and >750Wh/L. Low Temperature Performance Increase: strive toward developments that improve the discharge power and eliminate or dramatically reduce the life limiting lithium plating associated with regenerative braking at low temperatures, during the program. Calendar Life Increase: drive to achieve a 15-year calendar life. Abuse Tolerance Improvement: strive to develop improvements in Li-ion abuse tolerance and/or development of electrochemical energy storage technologies with inherently better response to abuse circumstances. Emerging Areas: initiate new programs that address emerging technologies that arise during the contract period.

25 ENERGY STORAGE↗

Electromagnetic Radiation Effects on MgO-Based Magnetic Tunnel Junctions: A Review

Magnetic tunnel junctions (MTJs) have been widely utilized in sensitive sensors, magnetic memory, and logic gates due to their tunneling magnetoresistance. Moreover, these MTJ devices have promising potential for renewable energy generation and storage. Compared with Si-based devices, MTJs are more tolerant to electromagnetic radiation. In this review, we summarize the functionalities of MgO-based MTJ devices under different electromagnetic irradiation environments, with a focus on gamma-ray radiation. We explore the effects of these radiation exposures on the MgO tunnel barriers, magnetic layers, and interfaces to understand the origin of their tolerance. This review enhances our knowledge of the radiation tolerance of MgO-based MTJs, improves the design of these MgO-based MTJ devices with better tolerances, and provides information to minimize the risks of irradiation under various irradiation environments. This review starts with an introduction to MTJs and irradiation backgrounds, followed by the fundamental properties of MTJ materials, such as the MgO barrier and magnetic layers. Then, we review and discuss the MTJ materials and devices’ radiation tolerances under different irradiation environments, including high-energy cosmic radiation, gamma-ray radiation, and lower-energy electromagnetic radiation (X-ray, UV–vis, infrared, microwave, and radiofrequency electromagnetic radiation). In conclusion, we summarize the radiation effects based on the published literature, which might benefit material design and protection.

42 ENGINEERING↗

Hybrid Energy Systems: Opportunities for Coordinated Research

This chapter presents a baseline assessment of DOE’s current portfolio related to hybrid systems that produce electricity as their only output (Track 1), within the context of the key challenges facing these systems. Of particular importance is that this chapter is focused on understanding what makes a hybrid different from two standalone technologies, both in terms of the research being performed and the challenges that ongoing and planned research will seek to overcome. The purpose of summarizing and describing current research areas is to identify opportunities DOE could consider supporting in the near term. DOE encompasses several offices, each of which has unique objectives and is financially constrained. Additionally, the emergence of low-cost hybrid resources presents an array of new opportunities for the electricity sector, including better managing and allocating risk, improving operating performance, reducing system costs, and enhancing reliability and resilience. Realizing these opportunities will require overcoming barriers to the deployment of hybrids through targeted R&D which multiple DOE offices can invest in and benefit from.

42 ENGINEERING↗

Spatial inequities in access to medications for treatment of opioid use disorder highlight scarcity of methadone providers under counterfactual scenarios

Access to treatment and medication for opioid use disorder (MOUD) is essential in reducing opioid use and associated behavioral risks, such as syringe sharing among persons who inject drugs (PWID). Syringe sharing among PWID carries high risk of transmission of serious infections such as hepatitis C and HIV. MOUD resources, such as methadone provider clinics, however, are often unavailable to PWID due to barriers like long travel distance to the nearest methadone provider and the required frequency of clinic visits. The goal of this study is to examine the uncertainty in the effects of travel distance in initiating and continuing methadone treatment and how these interact with different spatial distributions of methadone providers to impact co-injection (syringe sharing) risks. A baseline scenario of spatial access was established using the existing locations of methadone providers in a geographical area of metropolitan Chicago, Illinois, USA. Next, different counterfactual scenarios redistributed the locations of methadone providers in this geographic area according to the densities of both the general adult population and according to the PWID population per zip code. We define different reasonable methadone access assumptions as the combinations of short, medium, and long travel distance preferences combined with three urban/suburban travel distance preference. Our modeling results show that when there is a low travel distance preference for accessing methadone providers, distributing providers near areas that have the greatest need (defined by density of PWID) is best at reducing syringe sharing behaviors. However, this strategy also decreases access across suburban locales, posing even greater difficulty in regions with fewer transit options and providers. As such, without an adequate number of providers to give equitable coverage across the region, spatial distribution cannot be optimized to provide equitable access to all PWID. Our study has important implications for increasing interest in methadone as a resurgent treatment for MOUD in the United States and for guiding policy toward improving access to MOUD among PWID.

59 BASIC BIOLOGICAL SCIENCES↗

Potential Cost Reduction in New Nuclear Deployments Based on Recent AP1000 Experience

The completion of Vogtle Units 3 and 4, despite significant cost and schedule overruns, a major bankruptcy, and a pandemic, demonstrates that the U.S. nuclear industry can still develop new supply chains, train a highly skilled workforce, and build large nuclear power plants. Vogtle, being a first-of-a-kind (FOAK) plant, faced overruns, but FOAK overruns can decrease with more deployments through a combination of design standardization and modularization, transferring and implementing lessons learned between consecutive projects, and innovation. This report quantifies the potential cost and schedule reductions in future AP1000 plants in the US and identifies the barriers in achieving those reductions. It starts with a summary and analysis of the cost and construction timeline data for AP1000 plants that started construction in the United States (Vogtle) and China. Motivated by the steep schedule reductions from the first to second series of AP1000 plants in China, a cost reduction model was developed to quantify potential reductions for future AP1000 builds in the US. Results show that within about 3 more builds, AP1000s can become economically attractive in large markets in the U.S., without leveraging the Investment Tax Credit (ITC) or Production Tax Credit (PTC), and much sooner if these tax credits are available. Importantly the financial risks for future AP1000 builds in the US might be much smaller than observed in the FOAK plants. The study also identifies various barriers for future builds including the availability of a supply chain and a skilled workforce, and emphasizes the importance of making investments to gather and implement lessons learned between consecutive projects.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Multilaminate Energy Storage Films from Entropy‐Driven Self‐Assembled Supramolecular Nanocomposites

Abstract Composite materials comprising polymers and inorganic nanoparticles (NPs) are promising for energy storage applications, though challenges in controlling NP dispersion often result in performance bottlenecks. Realizing nanocomposites with controlled NP locations and distributions within polymer microdomains is highly desirable for improving energy storage capabilities but is a persistent challenge, impeding the in‐depth understanding of the structure–performance relationship. In this study, a facile entropy‐driven self‐assembly approach is employed to fabricate block copolymer‐based supramolecular nanocomposite films with highly ordered lamellar structures, which are then used in electrostatic film capacitors. The oriented interfacial barriers and well‐distributed inorganic NPs within the self‐assembled multilaminate nanocomposites effectively suppress leakage current and mitigate the risk of breakdown, showing superior dielectric strength compared to their disordered counterparts. Consequently, the lamellar nanocomposite films with optimized composition exhibit high energy efficiency (>90% at 650 MV m −1 ), along with remarkable energy density and power density. Moreover, finite element simulations and statistical modeling have provided theoretical insights into the impact of the lamellar structure on electrical conduction, electric field distribution, and electrical tree propagation. This work marks a significant advancement in the design of organic–inorganic hybrids for energy storage, establishing a well‐defined correlation between microstructure and performance.

Li, He↗

Re-Envisioning RCx: Achieving Max Potential HVAC Controls Retrofits through Modernized BAS Hardware and Software

Most existing buildings have sub-optimal heating, ventilation, and air conditioning (HVAC) controls, resulting in wasted energy and occupant discomfort. Retro-commissioning (RCx) addresses many of these issues, but it is a lengthy and highly customized process. Limited capabilities of existing building automation system hardware restricts the scope of most RCx projects. Incentive programs consider building automation system (BAS) hardware retrofits to be high-capital investments and do not allow them in typical RCx programs. This paper describes work that the authors are leading to facilitate technical and market innovation in the BAS industry to unlock large savings in existing commercial buildings through deep retrofits of BAS hardware and software. California and New York research projects are demonstrating BAS retrofits leveraging the American Society of Heating, Refrigeration, and Air Conditioning Engineers’ (ASHRAE) new Guideline 36 high performance sequences of operation to achieve greater than 20 percent whole building energy savings, while saving costs and reducing risk through streamlined processes and standardization across BAS manufacturer product lines and across implementation practices. This paper describes market barriers that impede achieving deep savings from BAS retrofits in custom incentive and traditional RCx programs and presents a new maximum potential BAS retrofit model that addresses these barriers. The new model leverages the authors’ efforts in market enablement through open standards, BAS industry partnerships, and tools for cost-effective scaling that includes tools for project screening, savings calculations, and measurement and verification (M&V). This approach is widely applicable and will be ready for at-scale implementation within two years.

Paliaga, Gwelen↗

Explaining Health Risk Behaviors in the U.S. with Social Deprivation at Local and Regional Levels

Health risk behaviors are precursors to many chronic health outcomes, and hence, they pose a challenge to public health. Social deprivation undoubtedly creates circumstances that limit access to healthy habits. Moreover, broad regional effects (weather patterns, political ideology, social norms), and local characteristics (cultural notions and barriers, urban places) also influence lifestyle choices and must be accounted for to truly understand the impact of social deprivation on risky behaviors. This research fills the knowledge gap in epidemiological modeling of health risk behaviors by leveraging machine learning to find associations between social deprivation and health risk behaviors, when adjusted by regional and local effects. Four health risk behaviors, namely, binge drinking, smoking, lack of sleep, and lack of physical activity from the CDC PLACES project are considered in a single framework to understand and compare the interplay between local/regional characteristics and seven measures of social deprivation. Our results indicate that local and/or regional factors rise to the top for three out of four risk behaviors (binge drinking, smoking and lack of sleep) out-competing social deprivation measures. Un-entangling the geographical effects reveals that poverty, educational attainment and non-employment are the three deprivation measures most significantly associated with all four health risk factors. The research thus indicates that public health policies to promote healthy lifestyle behaviors must seek to remedy social deprivation, but using socially and culturally sensitive interventions.

Gokhale, Swapna↗