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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 199 records · Page 11
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

First Cosmology Results using Supernovae Ia from the Dark Energy Survey: Survey Overview, Performance, and Supernova Spectroscopy

We present details on the observing strategy, data-processing techniques, and spectroscopic targeting algorithms for the first three years of operation for the Dark Energy Survey Supernova Program (DES-SN). This five-year program using the Dark Energy Camera mounted on the 4 m Blanco telescope in Chile was designed to discover and follow supernovae (SNe) Ia over a wide redshift range (0.05 < z < 1.2) to measure the equation-of-state parameter of dark energy. We describe the SN program in full: strategy, observations, data reduction, spectroscopic follow-up observations, and classification. From three seasons of data, we have discovered 12,015 likely SNe, 308 of which have been spectroscopically confirmed, including 251 SNe Ia over a redshift range of 0.017 < z < 0.85. We determine the effective spectroscopic selection function for our sample and use it to investigate the redshift-dependent bias on the distance moduli of SNe Ia we have classified. The data presented here are used for the first cosmology analysis by DES-SN (“DES-SN3YR”), the results of which are given in Dark Energy Survey Collaboration et al. The 489 spectra that are used to define the DES-SN3YR sample are publicly available at https://des.ncsa.illinois.edu/releases/sn.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2023

Characterization of radiation damage effects in high-energy neutrino target graphite using low-energy ions

Exposure of graphite targets to high intensity proton beams at neutrino production facilities causes changes in the target material that can result in a shortened operation lifetime. The dominant factors in this process are currently thought to be mechanical in nature resulting primarily from microstructural effects that lead to thermal and structural changes in bulk material properties. As currently planned beam facilities with increased proton energy and intensity begin to come online it will be important to thoroughly understand these processes, and ideally to be able to predict the effects of new beam designs on target properties. Direct analysis of targets exposed to existing high-energy proton beams is complicated by several factors, such as very limited access to proton beam facilities, high associated costs, irradiation times on the order of months, and the resulting radioactivity of irradiated samples that requires special facilities for post-irradiation examination. Much of the existing literature concerning irradiation damage in graphite has been focused on the needs of the nuclear engineering community, however high-energy proton targets operate in a much different environment. In comparison to graphite irradiated in a nuclear reactor, graphite used in proton beam targets receives a higher dose rate, have greater gas production, and experience short irradiation pulses as opposed to continuous irradiation. Low-energy ion irradiation offers a method of inducing similar levels of radiation damage to high-energy protons while avoiding many of the difficulties and limitations associated with high-energy proton beams and the corresponding activated specimen testing. My research described in this thesis focused on investigating how low-energy ion irradiation could be used to induce the same or similar types of microstructural alteration and mechanical property degradation as that seen in high-energy neutrino production target graphites by varying damage le vels and irradiation temperatures prior to post-irradiation characterisation.

43 PARTICLE ACCELERATORS↗
DOE OSTI2023

Protecting Customer Privacy Through Distributed Energy Resource Anonymization

Due to their stochastic nature, the increase of Renewable Energy Resources (RERs) as a primary source of energy for power grids creates challenges regarding the reliability and resilience of the system. In order to combat these obstacles, expansion of Distributed Energy Resources (DERs) and their participation in Demand Response (DR) programs is necessary. Widespread participation requires prioritizing customer privacy and addressing concerns that may arise regarding communication between DERs and the Grid Service Provider (GSP). This paper discusses the use of flow reservation resources to split the operating cycles of DER load profiles into unique phases. The splitting of phases increases anonymization of the DERs by making it more difficult to determine the individual characteristics of the device. We discuss an example of this using simulated DER load profile data and examine the resulting effectiveness by using a machine learning algorithm for classification, called Support Vector Machine (SVM).

Distributed Energy Resource, Anonymization, Renewa↗
DOE OSTI2022

Route Optimization for Energy Efficient Airport Shuttle Operations - A Case Study from Dallas Fort Worth International Airport

Air travel and requisite surface traffic supporting passenger arrival/departure constitutes a significant portion of travel and emissions in cities with large airports. An airport trip can segment into three parts namely: i) travel from a location in the city to the airport; ii) travel from a parking lot or rental car center to the terminal (i.e., within the airport premises), and iii) travel inside the terminal. Depending on the airport access mode all or a part of these legs comprise a traveler’s journey to the airport. The priority of airport ground transport management teams is to provide passengers with a seamless travel experience within the airport, so it is understandable that within airport shuttle routes might not be optimized for minimizing energy consumption. Solutions that meet the dual objective of reducing energy consumption from airport shuttle operations without compromising on passenger travel experience are key to improving system efficiency. There is currently a dearth of research and tools that can inform airports in making such decisions. Addressing this need, this research effort puts forth an optimization model that generates optimal shuttle routes for a given set of constraints, and a discrete-event simulator that evaluates the optimal solutions in a stochastic environment to understand the tradeoffs between passenger wait times, and within airport shuttle energy consumption. The proposed set of tools are tested in the context of optimizing airport shuttles routes within the Dallas Fort Worth International Airport (DFW). In addition to shuttle spatial positioning, and passenger demand information, high-fidelity vehicle data was collected using data loggers installed on DFW shuttles. Results show that 20% energy reduction in shuttle operations is possible with a modest two-minute increase in average passenger wait times. The tools developed in this research effort are designed to be generalizable and can help optimize shuttle operations planning at any major airport.

air travel↗
DOE OSTI2024

Consumer Benefits of Clean Energy: Renewable Energy

Meeting national and state decarbonization goals requires a transition to clean energy technologies. Energy efficiency, demand flexibility, renewable energy and storage can reduce consumers’ electricity bills, lower total electricity system costs, and provide health and resilience benefits. Berkeley Lab developed a series of briefs that explore these consumer benefits of a clean energy transition. This brief discusses some of the possible consumer benefits of utility-scale and behind the meter renewable energy, with a focus on how these resources can contribute to a low-cost electricity system. It begins with a literature review of modeled impacts, primarily considering consumer benefits, of the Inflation Reduction Act and Bipartisan Infrastructure Law. Next, it discusses how utility-scale renewable energy can contribute to a low-cost electricity system (e.g., in some cases, low resource costs relative to other alternatives). It concludes with a discussion of behind-the-meter renewable energy consumer benefits (e.g., reduced host electricity bill, increased property value, resilience).

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2025

High Energy Physics Network Requirements Review: Final Report, July 2024–December 2024

The world-class research infrastructure at the US Department of Energy (DOE) Office of Science (SC) provides the research community with premier observational, experimental, computational, and network capabilities. Each user facility is designed to provide unique capabilities to advance the core DOE mission in science and technology for its SC program to stimulate rich scientific discoveries and enhance its innovation ecosystem. Research communities gather and flourish around each user facility, bringing together new and enhanced perspectives. The continual reinvention of the practice of science — as users and staff forge novel approaches expressed in research workflows — unlocks new discoveries and propels scientific progress. Within this research ecosystem, the high-performance computing (HPC) and networking user facilities stewarded by the SC’s Advanced Scientific Computing Research (ASCR) program play a dynamic cross-cutting role, enabling complex workflows demanding high-performance data, networking, and computing solutions. The ASCR facilities enterprise seeks to understand and meet the needs and requirements across SC and DOE domain science programs and priority efforts, highlighted by the formal requirements review methodology. Between July and December 2024, the Energy Sciences Network (ESnet) and the Office of High Energy Physics (HEP) of the DOE-SC organized an ESnet requirements review of HEP-supported program activities. Preparation for these events included identification of key stakeholders: program and facility management, research groups, and technology providers. Each stakeholder group was asked to prepare formal case study documents about its relationship to the HEP program to build a complete understanding of the current, near-term, and long-term status, expectations, and processes that will support the science going forward.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2020

An Evaluation of Energy Storage Cost and Performance Characteristics

The energy storage industry continues to expand globally as costs continue to fall and opportunities in consumer, transportation and grid applications are defined. As the rapid evolution of the industry continues, it has become increasingly important to understand how varying technologies compare in terms of cost and performance. This paper defines and evaluates cost and performance parameters of six battery energy storage technologies (BESS) - lithium-ion batteries, lead-acid batteries, redox flow batteries, sodium-sulfur batteries, sodium metal halide batteries, and zinc-hybrid cathode batteries - four non-BESS storage technologies - pumped storage hydropower, flywheels, compressed air energy storage, and ultracapacitors - and combustion turbines. Cost and performance information was compiled based on an extensive literature review, conversations with vendors and stakeholders, and costs of systems procured at sites across the United States. Detailed cost and performance estimates are presented for 2018 and projected out to 2025. Annualized costs were also calculated for each technology.

Mongird, Kendall↗
DOE OSTI2023

Implementing Clean Energy Transitions for Small Communities: NREL Supports Sierra Club Florida in Efforts to Help Florida Communities Achieve 100% Renewable Energy

Sierra Club Florida's "Clean Energy for All" campaign helps communities in Florida transition to 100% clean energy. The organization sought the help of National Renewable Energy Laboratory (NREL) analysts to achieve to achieve two goals: (1) create a Clean Energy Toolkit to help communities in Florida and across the country find data and and analysis to achieve clean energy goals, and (2) provide direct analysis of local clean energy potential for two Florida communities, the cities of Tallahassee and Sarasota.

clean energy toolkit↗
DOE OSTI2024

A techno-economic survey of energy storage media for long-duration energy storage applications

Energy storage technologies that can economically store and provide electricity over multi-day and seasonal timescales are likely to be a critical component of a sustainable and resilient energy system. In this analysis, we perform a broad survey of energy storage technologies to find storage media (SM) that are promising for these long-duration energy storage (LDES) applications. The energy capital cost of the SM is identified as a key figure of merit for LDES. We develop a data collection framework to collect material price and physical property data, which are used to calculate the energy capital cost floor for 376 SM. These costs are then compared with cost targets for the LDES applications. The results show a multitude of thermal and chemical SM are economically promising, including some synthetic fuels, sensible thermal, latent thermal, thermochemical, and batteries based on low-cost materials. In contrast, currently deployed energy storage systems such as lithium-ion batteries and pumped hydro storage do not appear to be promising systems for LDES applications.

25 ENERGY STORAGE↗
DOE OSTI2023

Modeling nuclear energy’s future role in decarbonized energy systems

Increased attention has been focused on the potential role of nuclear energy in future electricity markets and energy systems as stakeholders target rapid and deep decarbonization and reductions in fossil fuel use. This paper examines models of electric sector planning and broader energy systems optimization to understand the prospective roles of nuclear energy and other technologies. In this perspective, we survey modeling challenges in this environment, illustrate opportunities to propagate best practices, and highlight insights from the deep decarbonization literature on the range of visions for nuclear energy's role. Nuclear energy deployment is highest with combinations of stringent emissions policies, nuclear cost reductions, and constraints on the deployment of other technologies, which underscores model dimensions related to these areas. New modeling capabilities are needed to adequately address emerging issues, including representing characteristics and applications of nuclear energy in systems models, and to ensure the relevance of models for policy and planning as deeper decarbonization is explored.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2021

Examination of How Well Long-Range-Corrected Density Functionals Satisfy the Ionization Energy Theorem

For this work, we calculated the vertical ionization energies (VIE) of 99 species in two ways to examine the accuracy of several long-range-corrected (LC) hybrid meta functionals in comparison with a gradient approximation (GA), global hybrids, and doubly hybrids. In the category of LC functionals, we examined both those with meta ingredients (i.e., that depend on the kinetic energy density) and those without them. The LC-hybrid meta functionals examined are M11, revM11, M11plus, and ωB97M-V. The reference data used to assess accuracy consist of 95 molecules and 4 atoms in the GW100 set. The two methods studied are the ΔSCF method (involving the difference of neutral and cation self-consistent field (SCF) energies) and the ionization energy theorem (involving the orbital energy of the highest occupied molecular orbital, HOMO). We calculated linear correlation coefficients (r 2 ) and mean absolute deviations (MADs) between each approach and the reference VIE value from the CCSD(T)/def2-TZVPP level of theory. We compared the new LC-hybrid meta calculations to calculations with the 10 functionals in a previous VIE study by Brémond et al. and to the calculations with LC-BLYP (LC-Becke, Lee–Yang–Parr), CAM-B3LYP (Coulomb-attenuating-method Becke-3-parameter Lee–Yang–Parr), LC-ωHPBE, and ωB97X-D. The results show that Minnesota LC-hybrid meta functionals have the smallest mean absolute deviation of ionization energy theorem VIEs with the reference data; the LC-ωHPBE functional also does quite well in this test. This is very encouraging and indicates that LC-hybrid meta functionals would be the best starting points for the tuning strategy that has been shown to be a very good procedure for improving time-dependent density functional calculations, and it also helps explain the good success of LC-hybrid meta functionals for molecular excitation energies.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

U.S.-China Clean Energy Research Center Building Energy Efficiency (CERC-BEE) Open-Source Retrofit Targeting Tool (CRADA FP00007338 Final Report)

To increase the cost-saving energy and carbon dioxide (CO 2 ) emissions reductions in buildings and portfolios at the scale and speed necessary to limit climate change, researchers at LBNL and Johnson Controls (JCI) developed the Building Efficiency Targeting Tool for Energy Retrofits (BETTER). BETTER is a software tool that consists of three components: (1) the BETTER analytical engine source code (which was developed with intellectual property provided by JCI under CRADA FP00007338); (2) the BETTER web application, developed by LBNL and McQuillen Interactive Pty. Ltd; and (3) the BETTER application programming interface (API), also developed by LBNL and McQuillen Interactive Pty. Ltd. BETTER enables building and portfolio owners, managers, and service providers worldwide to quickly, easily identify cost-saving energy efficiency retrofits in existing buildings and portfolios without expensive site visits or complex modeling. With minimal data input, the tool benchmarks a building’s electric and fossil energy usage against peers; quantifies energy, cost and greenhouse gas (GHG) emission reduction potentials at the building and portfolio levels; and recommends energy efficiency measures to decarbonize and electrify buildings and portfolios, targeting specific energy savings levels. No other tool so comprehensively analyzes buildings and portfolios with such ease. If fully implemented, it is estimated that BETTER could help reduce emissions equivalent to planting 1.3 billion trees globally by 2030. Moreover, an additional 50-75% of embodied GHG emissions could be avoided in each case where BETTER results in a building being retrofitted instead of demolished and replaced, providing substantial additional decarbonization benefits for the buildings sector. BETTER has garnered multiple awards and avid interest from investors. In 2020, it earned a R&D 100 Award for innovation and a LBNL Director’s Award for Technology Transfer. In 2021, BETTER was named an EarthX E-Capital Summit Climate Tech Prize semi-finalist

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2021

Reducing Energy Use and Making Energy More Efficient in the Native Village of Kiana (Final Technical Report)

The goal of the Remote Alaska Community Energy Efficiency (RACEE) Competition was to advance the implementation of affordable, resilient, and clean energy-efficient solutions for remote Alaska communities. RACEE assisted Kiana with its unique challenges, mostly the remote nature of their location paired with the harsh temperatures and isolated electrical grid resulting in high energy costs. In addition to the assistance from DOE, the Alaska Energy Authority (AEA) provided direct technical assistance to RACEE recipients throughout their projects. Before Kiana started work, AEA conducted energy audits in public buildings and facilities to identify which energy measures would be most effective for the community’s energy goals.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2023

Just Transition Principles: Prepared for the APEC Energy Working Group Workshop on Promoting a Just Energy Transition

A global energy transition from fossil energy to clean energy is unfolding. Just transition is an iterative, continuous process of moving from a fossil-fuel economy to a green economy that provides decent, productive, and ecologically sustainable livelihoods; nurtures social dialogue; and equitably distributes costs and benefits of the energy system. It is aimed at supporting affected workers and communities and affirms that the transition is towards a more equitable energy system. Though the Asia-Pacific Economic Cooperation (APEC) region as a whole is largely representative of global energy transition trends, APEC’s member economies – and communities within them – will have their own transition nuances. Approaches to just transition must therefore recognize both the global and the local transition dynamics. The report offers eight just transition principles that can help inform work that assures the current energy transition, and its future iterations, are fair and equitable.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2025

Next-Level Energy Management in Manufacturing: Facility-Level Energy Digital Twin Framework Based on Machine Learning and Automated Data Collection

This research introduces an energy prediction framework at the facility level supported by automated data collection and machine learning models. It investigates whether reducing the prediction time scale allows for applying more complex machine learning techniques and if those techniques improve the prediction accuracy. The primary advantages of this framework lie in its automation of the energy prediction process and its provision of real-time energy data suitable for use in energy dashboards or digital twins. A sitewide dataset was created by combining 15 min energy and daily production data of five shops—assembly, battery, body (electric), body (gas), and paint—from a globally recognized electric vehicle manufacturer. Various machine learning models were evaluated on daily, weekly, and monthly datasets, including, in increasingly complex order: naïve, simple linear regression, net regularized generalized linear regression, principal component regression, k-nearest neighbor, random forest, and Bayesian regularized neural network. Compared to the current state-of-the-art energy consumption prediction for the industrial facility level, this research investigates more complex models and smaller time intervals for higher accuracy. The findings revealed that the more complex monthly models require a minimum of a year and a half of data to operate, while weekly models demand a year of data to achieve improved accuracy. Daily models can operate with only six months of data but exhibit poor performance due to reduced prediction accuracy of production. Key challenges identified include access to reliable, high-quality energy and production data and the initial demand for human labor.

digital twin↗
DOE OSTI2022

A Search for Photons with Energies Above 2 × 10 17 eV Using Hybrid Data from the Low-Energy Extensions of the Pierre Auger Observatory

Ultra-high-energy photons with energies exceeding 10 17 eV offer a wealth of connections to different aspects of cosmic-ray astrophysics as well as to gamma-ray and neutrino astronomy. The recent observations of photons with energies in the 10 15 eV range further motivate searches for even higher-energy photons. In this paper, we present a search for photons with energies exceeding 2 × 10 17 eV using about 5.5 yr of hybrid data from the low-energy extensions of the Pierre Auger Observatory. The upper limits on the integral photon flux derived here are the most stringent ones to date in the energy region between 10 17 and 10 18 eV.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2025

Reducing Data Center Peak Cooling Demand and Energy Costs with Underground Thermal Energy Storage (UTES)

By recent estimates, data center energy demands are projected to consume between 6.7% and 12% of U.S. annual electricity generation by the year 2028, driven primarily by expanded demands from cloud services, big data analytics, and Artificial Intelligence (AI) (Shehabi et al., 2024). As much as 40% of data center total energy consumption are loads associated with the site infrastructure cooling systems, and these are often highly water consumptive (Aljbour et al., 2024). For energy system planners, this presents significant challenges to meeting and managing the anticipated loads, and especially the peak loads of projected data center deployments. Geothermal technologies offer two unique solutions to these challenges: 1) by serving loads through the deployment of new conventional and/or next-generation geothermal power technologies such as EGS and 2) through an often-overlooked opportunity to reduce data center peak cooling loads. The latter is the focus of this paper which explores Cold Underground Thermal Energy Storage ("Cold UTES") as an emerging industrial-scale geothermal cooling solution. This cooling solution is energy efficient, non-water-consumptive, and utilizes long duration energy storage (LDES) on both diurnal and seasonal time scales. Cold UTES has the potential to also function as a virtual power plant (VPP). The US Department of Energy's Geothermal Technologies Office is supporting R&D to understand the grid and system-wide value, costs, and impacts of deploying this emergent cooling solution at scale.

AI↗
DOE OSTI2020

Energy, economic, and environmental analysis of integration of thermal energy storage into district heating systems using waste heat from data centres

Data centres produce waste heat, which can be utilized in district heating systems. However, the mismatch between data centres’ heat supply and district heating systems’ heat demands limits its utilization. Further, high peak loads increase the operation cost of district heating systems. This study aimed to solve these problems by introducing thermal energy storages. A water tank and a borehole thermal energy storage system were selected as the short-term and long-term thermal energy storage, respectively. Energy, economic, and environmental indicators were introduced to evaluate different solutions. The case study was a campus district heating system in Norway. Results showed that the water tank could shave the peak load by 31% and save the annual energy cost by 5%. The payback period was lower than 15 years when the storage efficiency remained higher than 80%. However, it had no obvious benefits in terms of mismatch relieving and CO emissions reduction. In contrast, the borehole thermal energy storage increased the waste heat utilization rate to 96% and reduced the annual CO emissions by 8%. However, the payback period was more than 17 years. These results provide guidelines for the retrofit of district heating systems, where data centres’ waste heat is available.

25 ENERGY STORAGE↗