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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 145 records · Page 8

Rescue Shuttle Flight Re-Entry: Controlling Astronaut Thermal Exposure

A rescue mission for the STS-125 Hubble Telescope Repair Mission requires reentry from space with 11 crew members aboard, exceeding past cabin thermal load experience and risking crew thermal stress potentially causing cognitive performance and physiological decrements. The space shuttle crew cabin air revitalization system (ARS) was designed to support a nominal crew complement of 4 to 7 crew and 10 persons in emergencies, all in a shirt-sleeve environment. Subsequent to the addition of full pressure suits with individual cooling units, the ARS cannot maintain a stable temperature in the crew cabin during reentry thermal loads. Bulk cabin thermal models, used for rescue mission planning and analysis of crew cabin air, were unable to accurately represent crew workstation values of air flow, carbon dioxide, and heat content for the middeck. Crew temperature models suggested significantly elevated core temperatures. Planning for an STS-400 potential rescue of seven stranded crew utilized computational fluid dynamics (CFD) models to demonstrate inhomogeneous cabin thermal properties and improve analysis compared to bulk models. In the absence of monitoring of crew temperature, heart rate, metabolic rate and incomplete engineering data on the performance of the integrated cooling garment/cooling unit (ICG/CU) at cabin temperatures above 75 degrees F, related systems & models were reevaluated and tests conducted with humans in the loop. Changes to the cabin ventilation, ICU placement, crew reentry suit-donning procedures, Orbiter Program wave-off policy and post-landing power down and crew extraction were adopted. A second CFD and core temperature model incorporated the proposed changes and confirmed satisfactory cabin temperature, improved air distribution, and estimated core temperatures within safe limits. CONCLUSIONS: These changes in equipment, in-flight and post-landing procedures, and policy were implemented for the STS-400 rescue shuttle & will be implemented in any future rescue flights from the International Space Station of stranded shuttle crews.

Gillis, David B.↗

Modeling direct air carbon capture and storage in a 1.5 °C climate future using historical analogs

Limiting the rise in global temperature to 1.5 °C will rely, in part, on technologies to remove CO 2 from the atmosphere. However, many carbon dioxide removal (CDR) technologies are in the early stages of development, and there is limited data to inform predictions of their future adoption. Here, we present an approach to model adoption of early-stage technologies such as CDR and apply it to direct air carbon capture and storage (DACCS). Our approach combines empirical data on historical technology analogs and early adoption indicators to model a range of feasible growth pathways. We use these pathways as inputs to an integrated assessment model (the Global Change Analysis Model, GCAM) and evaluate their effects under an emissions policy to limit end-of-century temperature change to 1.5 °C. Adoption varies widely across analogs, which share different strategic similarities with DACCS. If DACCS growth mirrors high-growth analogs (e.g., solar photovoltaics), it can reach up to 4.9 GtCO 2 removal by midcentury, compared to as low as 0.2 GtCO 2 for low-growth analogs (e.g., natural gas pipelines). For these slower growing analogs, unabated fossil fuel generation in 2050 is reduced by 44% compared to high-growth analogs, with implications for energy investments and stranded assets. Residual emissions at the end of the century are also substantially lower (by up to 43% and 34% in transportation and industry) under lower DACCS scenarios. The large variation in growth rates observed for different analogs can also point to policy takeaways for enabling DACCS.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Design of COVID-19 staged alert systems to ensure healthcare capacity with minimal closures

Community mitigation strategies to combat COVID-19, ranging from healthy hygiene to shelter-in-place orders, exact substantial socioeconomic costs. Judicious implementation and relaxation of restrictions amplify their public health benefits while reducing costs. We derive optimal strategies for toggling between mitigation stages using daily COVID-19 hospital admissions. With public compliance, the policy triggers ensure adequate intensive care unit capacity with high probability while minimizing the duration of strict mitigation measures. In comparison, we show that other sensible COVID-19 staging policies, including France’s ICU-based thresholds and a widely adopted indicator for reopening schools and businesses, require overly restrictive measures or trigger strict stages too late to avert catastrophic surges. As proof-of-concept, we describe the optimization and maintenance of the staged alert system that has guided COVID-19 policy in a large US city (Austin, Texas) since May 2020. As cities worldwide face future pandemic waves, our findings provide a robust strategy for tracking COVID-19 hospital admissions as an early indicator of hospital surges and enacting staged measures to ensure integrity of the health system, safety of the health workforce, and public confidence.

60 APPLIED LIFE SCIENCES↗

Transferable Reinforcement Learning for Smart Homes: Preprint

To harness the great amount of untapped resources at the demand side, smart home technology plays a vital role in solving the "last mile" problem in smart grid. Reinforcement learning (RL), which has demonstrated an outstanding performance in solving many sequential decision-making problems, can be a great candidate to be used in smart home control. For instance, many studies have started investigating the load scheduling problem under dynamic pricing scheme. Based on those, this study aims at providing an affordable solution to encourage a higher smart home adoption rate. Specifically, we investigate combining transfer learning (TL) with RL to reduce the training cost of an optimal RL control policy. Given an optimal policy for a benchmark home, TL can jump-start the RL training of a policy for a new home, which has different appliances and user preferences. Simulation results show that by leveraging TL, RL training converges faster and requires much less computing time for new homes that are similar to the benchmark home. In all, this study proposes a cost-effective approach for training RL control policies for homes at scale, which ultimately reduces the controller's implementation costs, increases the adoption rate of RL controllers, and makes more homes grid-interactive.

ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATION,↗

Community Solar Reaches Adopters Underserved by Rooftop Solar

Community solar, a business model where multiple customers buy output from shared solar systems, has expanded solar access among multifamily housing occupants, renters, and low-income households. Policies to enable community solar could be expanded and benefits of access augmented through targeted measures to support community solar adoption in underserved communities.

community solar↗

Driving the grid forward: How electric vehicle adoption shapes power system infrastructure and emissions

We model the effect of plug-in electric vehicle (EV) adoption on U.S. power system generator capacity investment, operations, and emissions through 2050 by estimating power systems outcomes under a range of EV adoption trajectory scenarios. Our EV adoption scenarios are informed by 1) an Energy Information Administration scenario with no policy intervention, 2) EV growth expected under the Inflation Reduction Act (IRA), 3) a Biden Administration 50% EV sales target by 2030, 4) the Environmental Protection Agency’s projections under vehicle emissions standards, and 5) the International Energy Agency’s roadmap to Net Zero by 2050. We find across these scenarios that increasing EV adoption induces investment in new wind, solar, storage, and natural gas capacity, affecting power generation mix and emissions. The net effect of increasing EV adoption beyond our IRA base case is to increase power sector emissions by about 5 mtCO 2 eq per EV-year in 2026 (comparable to displaced gasoline vehicle combustion emissions), but this effect rapidly drops to annual levels below 1 mtCO 2 eq per EV-year by 2032 and continues below this level through 2050. Consequential effects of EV adoption vary regionally, with most regions primarily increasing wind or solar capacity and some regions primarily increasing natural gas capacity, even in 2050. Our national emissions estimates per EV-year are relatively robust to the level of EV adoption beyond our baseline and to variation in assumptions about power systems, EV behavior, and policy.

Science & Technology - Other Topics↗

Residential Solar-Adopter Income and Demographic Trends: 2021 Update [Slides]

The report describes income, demographic, and other socio-economic trends among U.S. residential rooftop solar adopters. The report is based on data for roughly 1.9 million residential rooftop solar systems installed through 2019, representing 82% of all U.S. systems. With its unique size, geographic scope, and level of detail, this report is intended to serve as a foundational reference document for policy-makers, industry stakeholders, and researchers. Key findings include the following: Solar adopters generally skew towards higher incomes, though that trend continues to diminish over time. Solar adopter incomes vary considerably and encompass many low-to-moderate income (LMI) households. Solar-adopter incomes are consistently higher for systems paired with battery storage, for host-owned systems, and for systems installed on single-family homes. Solar adopters differ from the broader U.S. population in terms of a variety of other demographic and socioeconomic measures. State-level comparisons indicate that solar-adopters tend to live in neighborhoods with relatively high non-Hispanic White and Asian populations, and with relatively low Hispanic and Black populations. In conjunction with the report, Berkeley Lab has published an updated accompanying set of online data visualizations that allow users to further explore the underlying data. Berkeley Lab is also offering related analytical support to states, local agencies, and other organizations on issues related to solar adoption among low-to-moderate income households.

14 SOLAR ENERGY↗

Louisville Communities LEAP Engagement: Improving Energy Efficiency in Affordable Housing

This report is a comprehensive summary of the related workstreams pursued through the Communities Local Energy Action Program (Communities LEAP) pilot Technical Assistance (TA) program in Louisville, Kentucky. It begins with an analysis around energy efficiency technologies, focused on building envelope improvements, that explores the impact to individual residents as well as the impact to the community at-large if the upgrades were adopted city-wide. Community benchmarking ordinances and complementary policies are considered next, including comparisons of programs with peer communities. A workforce development section then covers the state of Louisville's workforce today and identifies programs in peer communities that Louisville could consider emulating to achieve a "right-sized" workforce. The document closes out with an overview of policies around energy efficiency in peer communities that Louisville could explore, with considerations for the City's unique policy context.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Safer Systems: A NextGen Aviation Safety Strategic Goal

The Joint Planning and Development Office (JPDO), is charged by Congress with developing the concepts and plans for the Next Generation Air Transportation System (NextGen). The National Aviation Safety Strategic Plan (NASSP), developed by the Safety Working Group of the JPDO, focuses on establishing the goals, objectives, and strategies needed to realize the safety objectives of the NextGen Integrated Plan. The three goal areas of the NASSP are Safer Practices, Safer Systems, and Safer Worldwide. Safer Practices emphasizes an integrated, systematic approach to safety risk management through implementation of formalized Safety Management Systems (SMS) that incorporate safety data analysis processes, and the enhancement of methods for ensuring safety is an inherent characteristic of NextGen. Safer Systems emphasizes implementation of safety-enhancing technologies, which will improve safety for human-centered interfaces and enhance the safety of airborne and ground-based systems. Safer Worldwide encourages coordinating the adoption of the safer practices and safer systems technologies, policies and procedures worldwide, such that the maximum level of safety is achieved across air transportation system boundaries. This paper introduces the NASSP and its development, and focuses on the Safer Systems elements of the NASSP, which incorporates three objectives for NextGen systems: 1) provide risk reducing system interfaces, 2) provide safety enhancements for airborne systems, and 3) provide safety enhancements for ground-based systems. The goal of this paper is to expose avionics and air traffic management system developers to NASSP objectives and Safer Systems strategies.

Darr, Stephen T.↗

LMI Solar Context for WAP

Low-to-moderate income (LMI) households represent 43% of the U.S. population and spend disproportionately more of their income on energy. Solar has been disproportionately adopted by high-income households. Increasing interest in policy interventions to include LMI households and create more equitable solar access.

ENERGY PLANNING, POLICY, AND ECONOMY↗

Towards Off-policy Evaluation as a Prerequisite for Real-world Reinforcement Learning in Building Control

We present an initial study of off-policy evaluation (OPE), a problem prerequisite to real-world reinforcement learning (RL), in the context of building control. OPE is the problem of estimating a policy's performance without running it on the actual system, using historical data from the existing controller. It enables the control engineers to ensure a new, pretrained policy satisfies the performance requirements and safety constraints of a real-world system, prior to interacting with it. While many methods have been developed for OPE, no study has evaluated which ones are suitable for building operational data, which are generated by deterministic policies and have limited coverage of the state-action space. After reviewing existing works and their assumptions, we adopted the approximate model (AM) method. Furthermore, we used bootstrapping to quantify uncertainty and correct for bias. In a simulation study, we evaluated the proposed approach on 10 policies pretrained with imitation learning. On average, the AM method estimated the energy and comfort costs with 1.84% and 14.1% error, respectively.

Chen, B↗

Residential Solar-Adopter Income and Demographic Trends: 2022 Update

The report describes income, demographic, and other socio-economic trends among U.S. residential rooftop solar adopters. The report is based on data for roughly 1.9 million residential rooftop solar systems installed through 2019, representing 82% of all U.S. systems. With its unique size, geographic scope, and level of detail, this report is intended to serve as a foundational reference document for policy-makers, industry stakeholders, and researchers. Key findings include the following: -Solar adopters generally skew towards higher incomes, though that trend continues to diminish over time. -Solar adopter incomes vary considerably and encompass many low-to-moderate income (LMI) households. -Solar-adopter incomes are consistently higher for systems paired with battery storage, for host-owned systems, and for systems installed on single-family homes. -Solar adopters differ from the broader U.S. population in terms of a variety of other demographic and socioeconomic measures. -State-level comparisons indicate that solar-adopters tend to live in neighborhoods with relatively high non-Hispanic White and Asian populations, and with relatively low Hispanic and Black populations.

14 SOLAR ENERGY↗

Exploring the Potential of Rainwater Harvesting for Cooling Towers: A Systematic Review and Regional Feasibility Assessment

Water scarcity has driven interest in rainwater harvesting, especially for U.S. industries like power and manufacturing, which dedicate a large percentage of their water needs to cooling towers. This paper provides a comprehensive systematic review of studies on the use of rainwater in cooling tower applications, along with an assessment of the regional feasibility of integrating RWH in U.S. manufacturing cooling towers. The systematic review examines the technical, economic, environmental, and policy feasibility of utilizing harvested rainwater, and the regional feasibility analysis evaluates the practical implementation of RWH in manufacturing cooling towers, considering factors such as regional RWH potential, water costs, state policies, and the industrial water use of manufacturing facilities per state. This study supports the hypothesis that RWH for cooling towers is technically feasible, economically viable, and environmentally beneficial. Harvested rainwater is naturally less conductive and soft, and rainwater reuse minimizes the ecological footprint. Supportive state policies, regional RWH potential, and rising water costs across the U.S. are important variables that may impact RWH adoption. The review highlights rooftop RWH as the most studied method and notes that implementing RWH requires infrastructure changes and filtration techniques. While initial investment costs may be high, operational and maintenance costs are low, making RWHS economically feasible over time. Regions with higher water costs and supportive policies are more likely to benefit from RWH adoption. The study provides a foundation for understanding the potential for using RWH in industrial cooling towers.

Cooling towers↗

Alternative Fuel Vehicle Usage and Owner Demographics in New York State

With mounting concerns over climate change and the environmental impact of fossil fuels, the United States has witnessed a growing interest in alternative fuel vehicles (AFVs). In 2021, approximately 1.5 million battery EVs (BEVs), 0.8 million plug-in hybrid EVs (PHEVs), and 5.5 million hybrid EVs (HEVs) were registered in the United States. In the state of New York, a total of 51,900 BEVs, 44,600 PHEVs, and 221,600 HEVs were registered in 2021. The current report presents the results of an analysis of AFV adoption patterns in New York State and the rest of the United States based on data from the 2017 National Household Travel Survey (NHTS). Overall, the report reveals the demographics and mobility factors (e.g., household income, homeownership, and trip length) that contribute to the adoption of AFVs. This study provides insights that can inform policy decisions aimed at promoting sustainable transportation solutions.The 2017 NHTS data showed that the percentage of households owning at least one AFV is lower in New York City compared with that in other regions of New York State. From the NHTS samples, of the 25 households that owned at least one BEV in New York State, 15 households (60%) lived within a 5-mile radius, based on the great circle distance, of the nearest charging station, and 23 households (92%) lived within a 10-mile radius of the nearest charging station. Furthermore, among the 40 households in New York State that own at least one PHEV, 48% (19 households) lived within a 5-mile radius of the closest EV charging station, and 83% (33 households) lived within a 10-mile radius of the nearest charging station. The rest of the United States had a higher percentage of households that own at least one AFV compared with that of New York State. A comparison was made between EV adoption levels using NHTS and EValuateNY, which is a tool that gathers statistics on the electric car market in New York State. The estimates obtained from New York State household samples in NHTS were slightly lower than the data provided by EValuateNY. In New York State and the rest of the United States, households with higher incomes tended to have a higher proportion of AFV ownership compared with those with lower incomes. For example, households in New York State earning $\$ $150,000 or more had an approximately 6% share of owning at least one AFV, which was markedly higher than those earning less than $\$ $100,000 (less than 3%). Additionally, homeowners in New York State and the rest of the United States also exhibited a significantly higher share of AFV ownership compared with that of renters. In New York State, households that own at least one AFV tended to travel farther and had longer travel times compared with their counterparts without an AFV. In terms of households with at least one AFV, households with HEVs tended to have more person trips, longer person miles of travel, and more vehicle miles traveled, resulting in longer travel times than that of households with BEVs or PHEVs. Notably, households with AFVs had a slightly lower share of family and personal business trips but a higher share of social and recreational trips compared with households without AFVs. Additionally, households with at least one AFV tended to have a slightly higher share of walking trips than their counterparts without an AFV. However, the comparisons were not statistically significant. These travel patterns observed in New York State were consistent with those observed in other regions of the United States.

33 ADVANCED PROPULSION SYSTEMS↗

Assessing the behavioral realism of energy system models in light of the consumer adoption literature

Effective policymaking to achieve net zero greenhouse gas emissions demands an understanding of the complex drivers of, and barriers to, consumer adoption behavior via behaviorally realistic energy system models. Existing models tend to oversimplify by focusing on homogenized financial factors while neglecting consumer heterogeneity and non-monetary influences. This study develops and applies a comprehensive framework for evaluating the behavioral realism of consumer adoption models, informed by the adoption literature. It introduces a typology for factors influencing low-carbon technology adoption decisions: monetary and non-monetary factors relating to household characteristics, psychology, technological attributes, and contextual conditions. Next, reviews of the consumer adoption and decision-making literature identify the most influential adoption factor categories for distributed solar photovoltaics, electric vehicles, and air-source heat pumps. Finally, the extent to which a selection of energy system models accounts for these adoption factors is assessed. Existing models predominantly emphasize the economic aspects of technology, which are generally identified as the most important factors. Where the models fall short — in considering moderately important factor categories — sector-specific and agent-based models can offer more behaviorally realistic insights. This study sheds light on which types of factors are most important for consumer adoption decisions and investigates how well current models rise to the challenge of behavioral realism. The end-to-end analysis presented enables internally consistent comparisons across models and energy technologies. This research advances timely conversations on consumer adoption. It could inform more behaviorally realistic energy system modeling, and thereby more effective decarbonization policymaking.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Projecting Recent Advancements in Battery Technology to Next–Generation Electric Vehicles

Electric vehicles (EVs) have seen rapid growth in adoption over the last several years. Advancements to increase battery life and performance, policy shifts, and high charging rate are expected to further accelerate the development of next generation of EVs. Battery improvements continue to emerge, enabling increased driving range, total distance driven over the life of vehicles, and ability to charge at high rates. Herein, an analysis framework to provide insights into inclusive design metrics, such as specific energy of batteries, energy consumption of vehicles, and charging power infrastructure development, is developed. Various cell-level fast charge protocols to realistic battery designs to understand the infrastructure needs associated with achieving range replacement of 32.25 km min -1 (20 mi min -1 ) are also scaled. Additionally, by calculating scaled power and peak to average power ratio, it is found that there needs to be more distinct alignment between the research efforts focused at the cell level and what is being developed for EV charging infrastructure needs. Finally, impact of high direct current voltage architecture in next-generation EVs is discussed. The findings in this work provide an insight into recent advancements in battery technology to next-generation EVs.

20 mi/min↗

Korean Power System Challenges and Opportunities, Priorities for Swift and Successful Clean Energy Deployment at Scale

With South Korea’s electricity demand expected to grow 30% by 2035, transitioning to clean energy resources will be critical in reducing the electric sector emissions and achieving national climate goals. Rapid technological improvements can help keep costs low and maintain grid reliability, if Korea’s government takes a coordinated approach to the clean energy transition. This policy brief identifies key barriers to Korea’s shift toward clean energy, based on the authors’ companion report (A Clean Energy Korea by 2035: Transitioning to 80% Carbon-Free Electricity Generation ), interviews with experts, and the most recent data and literature. It then explores policy solutions for overcoming these technological, economic, and institutional barriers, and suggests market transformation strategies to speed the adoption of clean energy technologies. Amid ongoing cost and technological improvements in wind, solar, and energy storage, advancing this report’s recommended policy actions with maximum coordination among government officials can meaningfully accelerate Korea’s clean energy transition.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

The State of Electric Vehicle Adoption in Colorado for Multifamily versus Single-Family Dwellings: A Methodology for Quantifying Deviation from Parity

Given that electric vehicle adoption is well underway, the spatial distribution of electric vehicle owners by housing type—single-family or multifamily— shows whether parity (equal adoption rates) is being achieved or to what extent adoption by housing type is over or undersaturated (i.e., over- or under-adoption). We use a proprietary dataset of vehicle registrations with modeled housing type to analyze saturation ratios in Colorado in 2022. We found significant single-family oversaturation and multifamily undersaturation in 14% and 23% of ZIP codes, respectively, suggesting Colorado can still mitigate disparities in electric vehicle adoption by housing type through accessible vehicles and charging.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗