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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 235 records · Page 13
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Improved Particle Swarm Algorithm Using Rubik’s Cube Topology for Bilevel Building Energy Transaction

Following the rapid growth of distributed energy resources (e.g., renewables, battery), localized peer-to-peer energy transactions are receiving more attention for multiple benefits, such as reducing power loss and stabilizing the main power grid. To promote distributed renewables locally, the local trading price is usually set to be within the external energy purchasing and selling price range. Consequently, building prosumers are motivated to trade energy through a local transaction center. This local energy transaction is modeled in bilevel optimization game. A selfish upper level agent is assumed with the privilege to set the internal energy transaction price with an objective of maximizing its arbitrage profit. Meanwhile, the building prosumers at the lower level will response to this transaction price and make decisions on electricity transaction amount. Therefore, this non-cooperative leader-follower trading game is seeking for equilibrium solutions on the energy transaction amount and prices. Additionally, a uniform local transaction price structure (purchase price equals selling price) is considered here. Aiming at reducing the computational burden from classical Karush–Kuhn–Tucker (KKT) transformation and protecting the private information of each stakeholder (e.g., building), swarm intelligence-based solution approach is employed for upper level agent to generate trading price and coordinate the transactive operations. On one hand, to decrease the chance of premature convergence in global-best topology, Rubik’s Cube topology is proposed in this study based on further improvement of a two-dimensional square lattice model (i.e., one local-best topology-Von Neumann topology). Rotating operation of the cube is introduced to dynamically changing the neighborhood and enhancing information flow at the later searching state. Several groups of experiments are designed to evaluate the performance of proposed Rubik’s Cube topology-based particle swarm algorithm. The results have validated the effectiveness of proposed topology and operators comparing with global-best version PSO and Von Neumann topology-based PSO and its scalability on larger scale applications.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2023

Environmental life cycle assessment of treatment and management strategies for food waste and sewage sludge

A consequential life cycle assessment (LCA) was utilized to compare the environmental impacts of food waste and sewage sludge management strategies. The strategies included a novel two-phase anaerobic digestion (AD) system and alternatives including landfill, waste-to-energy, composting, anaerobic membrane bioreactor, and conventional AD (wet continuous stirred-tank reactor [CSTR]). The co-management of food waste with sewage sludge was also considered for the two-phase AD system and for a conventional AD reactor. Further, a multidimensional LCA approach was taken, considering the five-midpoint impact categories of global warming, smog, human health particulate, acidification, and eutrophication estimated using the U.S. EPA Tool for the Reduction and Assessment of Chemical and Other Environmental Impacts. Co-management of food waste and sewage sludge using the novel two-phase AD system was shown to maximize energy recovery and had a net global warming benefit while reducing other environmental impacts compared with the alternative management strategies. It had similar relative environmental advantages across all categories as conventional AD, with the advantage of a smaller physical footprint. However, both approaches featured net environmental burdens when the background electric grid intensity fell below 0.25 kg CO 2 -eq kWh -1 , as could be expected in a decarbonized electric future. Upgrading the biogas produced from AD to renewable natural gas can displace the use of fossil natural gas for other non-electricity energy requirements that are difficult to decarbonize and may extend the time period of significant environmental benefits of utilizing AD for organic waste management. Treatment of the nutrient-rich supernatant generated by the novel two-phase AD system could be an obstacle for utilities with stringent nutrient discharge limits. Future research and full-scale implementation are needed to demonstrate the benefits of the two-phase AD system predicted through this analysis.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Black hole explosions as probes of new physics

The final stage of black hole evaporation is a potent probe of physics beyond the Standard Model: Hawking-Bekenstein radiation may be affected by quantum gravity “memory burden effects,” or by the presence of “dark,” beyond-the-Standard-Model degrees of freedom in ways that are testable with high-energy gamma-ray observations. We argue that information on either scenario can best be inferred from measurements of the evaporation’s light curve and by correlating observations at complementary energies. We offer several new analytical insights in how such observations map on the fundamental properties of the evaporating black holes and of the possible exotic particles they can evaporate into. Published by the American Physical Society 2025

Federico, Kevin (ORCID:0009000708441977)↗
DOE OSTI2026

Netload Range Cost Curves for Coordinated Transmission-Distribution Planning Under DER Growth Uncertainty

The increasing penetration of distributed energy resources (DERs) requires better coordination between transmission and distribution (T&D) planning to ensure system security and cost efficiency. However, misaligned planning horizons, computational burdens, and privacy concerns hinder effective coordination, leading to either underutilized resources caused by overinvestments or reliability risks due to underinvestment. To address this challenge, we introduce netload range cost curves (NRCCs), a novel approach for managing long-term DER growth uncertainty through T&D coordination, while preserving existing data-sharing and regulatory structures. NRCCs provide pairs of (i) peak substation netload guarantees and (ii) corresponding distribution upgrade options and costs, enabling their seamless integration into transmission planning workflows. To compute NRCCs efficiently, we develop a transmission-aware distribution network planning (TADNP), which is subsequently integrated to an iterative computation procedure. These NRCCs are then embedded into an NRCC-informed transmission planning model to enable resource-efficient coordination. We illustrate our proposed approach with a case study based on realistic distribution and transmission systems in the San Francisco Bay Area, California. Our results indicate the possibility of dramatic savings in transmission investments by incorporating the proposed NRCC-integrated T&D coordination framework.

Li, Yujia↗
DOE OSTI2021

Advancing Equity in Utility Regulation

Increasingly, states are recognizing equity as a goal of utility regulation, going beyond traditionally stated objectives to ensure that electricity systems are reliable, safe, and fairly priced. State initiatives are critical not only to address historical inequities, but to ensure equitable benefits and burdens in the transition to net-zero emissions by 2050. This report provides four perspectives on advancing equity in electric utility regulation, from representatives of energy justice and consumer organizations and a leading utility in this area. The authors provide recommendations related to regulatory issues such as stakeholder engagement, defining "public interest," intervenor funding, electricity infrastructure siting, access to distributed energy technologies, consumer protections, bill affordability programs, rate design, program design, and metrics to track and evaluate results of policies, regulations, and programs intended to deliver equitable outcomes.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2021

Rubik’s Cube Topology Based Particle Swarm Algorithm for Bilevel Building Energy Transaction

Following the rapid growth of distributed energy resources (e.g. renewables, battery), localized peer-to-peer energy transactions are receiving more attention for multiple benefits, such as, reducing power loss, stabilizing the main power grid, etc. To promote distributed renewables locally, the local trading price is usually set to be within the external energy purchasing and selling price range. Consequently, building prosumers are motivated to trade energy through a local transaction center. This local energy transaction is modeled in bilevel optimization game. A selfish upper level agent is assumed with the privilege to set the internal energy transaction price with an objective of maximizing its arbitrage profit. Meanwhile, the building prosumers at the lower level will response to this transaction price and make decisions on electricity transaction amount. Therefore, this non-cooperative leader-follower trading game is seeking for equilibrium solutions on the energy transaction amount and prices. In addition, a uniform local transaction price structure (purchase price equals selling price) is considered here. Aiming at reducing the computational burden from classical Karush-Kuhn-Tucker (KKT) transformation and protecting the private information of each stakeholder (e.g., building), swarm intelligence based solution approach is employed for upper level agent to generate trading price and coordinate the transactive operations. On one hand, to decrease the chance of premature convergence in global-best topology, Rubiks Cube topology is proposed in this study based on further improvement of a two-dimensional square lattice model (i.e., one local-best topology-Von Neumann topology). Rotating operation of the cube is introduced to dynamically changing the neighborhood and enhancing information flow at the later searching state. Several groups of experiments are designed to evaluate the performance of proposed Rubiks Cube topology based particle swarm algorithm. The results have validated the effectiveness of proposed topology and operators comparing with global-best version PSO and Von Neumann topology based PSO and its scalability on larger scale applications.

Feng, Xiaochun↗
DOE OSTI2023

Degeneracy Removal of Spin Bands in Collinear Antiferromagnets with Non–Interconvertible Spin–Structure Motif Pair

Energy bands in antiferromagnets are supposed to be spin degenerate in the absence of spin–orbit coupling (SOC). Recent studies have identified formal symmetry conditions for antiferromagnetic crystals in which this degeneracy can be lifted, spin splitting, even in the vanishing SOC (i.e., non-relativistic) limit. Materials having such symmetries could enable spin-split antiferromagnetic spintronics without the burden of using heavy-atom compounds. However, the symmetry conditions that involve spin and magnetic symmetry are not always effective as practical material selection filters. Furthermore, these symmetry conditions do not readily disclose trends in the magnitude and momentum dependence of the spin-splitting energy. Here, it is shown that the formal symmetry conditions enabling spin-split antiferromagnets can be interpreted in terms of local motif pairs, such as octahedra or tetrahedra, each carrying opposite magnetic moments. Here, collinear antiferromagnets with such a spin-structure motif pair, whose components interconvert by neither translation nor spatial inversion, will show spin splitting. Such a real-space motif-based approach enables an easy way to identify and design materials (illustrated in real example materials) having spin splitting without the need for SOC, and offers insights into the momentum dependence and magnitude of the spin splitting.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Role of climate goals and clean-air policies on reducing future air pollution deaths in China: a modelling study

Over 3 million people still die every year from diseases caused by exposure to outdoor PM 2.5 air pollution, and more than a quarter of these premature deaths occur in China. In addition to clean air policies that target pollution emissions, climate policies aimed at reducing fossil-fuel CO 2 emissions (e.g., to avoid 1.5°C of warming) may also dramatically improve air quality and public health. Yet there has been no comprehensive accounting of public health outcomes under different energy pathways and local clean air management decisions in China. In particular, further research is needed to understand the relationships among climate and clean air polices and future health burdens in China, where an aging population will further exacerbate the impacts of air pollution. Using a China-focused integrated assessment model (GCAM-China) and a dynamic emission projection model (DPEC), we project future Chinese air quality in scenarios spanning a range of global climate targets (i.e. 1.5°0C, 2°C, NDC, unambitious, baseline, and 4.5°C) as well as national clean air actions (i.e. 2015-pollution, current-pollution, and ambitious-pollution). We then evaluate the health impacts of PM2·5 air pollution of scenario matrix using the chemical transport model WRF-CMAQ and the latest epidemiological concentration–response (C-R) functions (i.e. GBD2019). We find that, without ambitious climate mitigation (e.g., under current NDC pledges), Chinese deaths related the PM2.5 air pollution do not substantially decrease—and often grow—by mid-century, regardless of clean air policies and air quality improvements. For example, in scenarios that track China’s current NDC pledge and deploy best-available pollution control technologies, PM 2.5 -related deaths in China decrease slightly by 2030 (to 1.2 million per year) but no further by mid-century (Ambitious-pollution-NDC-goals; 1.2 million deaths in 2050) despite substantial and continuous improvements in population-weighted air quality (27.2 to 16.0 µg/m 3 from 2030 to 2050). The contrary trends of improving air quality and increasing PM 2·5 -related deaths in many of our scenarios reveals the extent to which extra efforts are needed to compensate for the established fact of increasing age of China’s population in future. Substantial decreases in China’s PM 2.5 -related deaths and age-standardized death rates (e.g., decreasing by 0.3–0.5 million deaths and 10.2–14.2 per 100,000 population age-standardized death rates per year) thus require the sort of large-scale transition in energy sources entailed by scenarios that meet international climate goals to avoid 1.5°C and 2°C of warming (Ambitious-pollution-2°C- and 1.5°C-goals).

58 GEOSCIENCES↗
DOE OSTI2021

Source sector and fuel contributions to ambient PM 2.5 and attributable mortality across multiple spatial scales

Ambient fine particulate matter (PM 2.5 ) is the world’s leading environmental health risk factor. Reducing the PM 2.5 disease burden requires specific strategies that target dominant sources across multiple spatial scales. We provide a contemporary and comprehensive evaluation of sector- and fuel-specific contributions to this disease burden across 21 regions, 204 countries, and 200 sub-national areas by integrating 24 global atmospheric chemistry-transport model sensitivity simulations, high-resolution satellite-derived PM 2.5 exposure estimates, and disease-specific concentration response relationships. Globally, 1.05 (95% Confidence Interval: 0.74–1.36) million deaths were avoidable in 2017 by eliminating fossil-fuel combustion (27.3% of the total PM 2.5 burden), with coal contributing to over half. Other dominant global sources included residential (0.74 [0.52–0.95] million deaths; 19.2%), industrial (0.45 [0.32–0.58] million deaths; 11.7%), and energy (0.39 [0.28–0.51] million deaths; 10.2%) sectors. Our results show that regions with large anthropogenic contributions generally had the highest attributable deaths, suggesting substantial health benefits from replacing traditional energy sources.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Dancoff-based Wigner-Seitz approximation for the subgroup resonance self-shielding in the VERA neutronic simulator MPACT

The MPACT neutronics module of the Virtual Environment for Reactor Analysis (VERA) has used the subgroup method for resonance self-shielding calculation, for which two-dimensional (2D) fixed-source transport calculations are performed using the method of characteristics for resonance energy groups. When considering thermal feedbacks, the subgroup calculation must be performed at each outer iteration. Therefore, the computing time for cross section processing is a significant burden for computational efficiency. The Dancoff-based Wigner-Seitz approximation (DWA) capability has been implemented into MPACT in conjunction with the subgroup method, which has been used in SCALE/XSProc since SCALE version 6.0 and has recently been called an equivalent Dancoff-factor cell (EDC) method. The issue of relatively large reactivity bias in DWA for the gadolinia rods was resolved by introducing multiple Dancoff factors. Benchmark results for the VERA pressurized and boiling water reactor benchmark suites show that the DWA capability would significantly enhance computational efficiency with comparable accuracy. (authors)

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2022

LLNS Request for Variance from 10 CFR 851 for Construction of LLNL Digital Infrastructure Capabilities Expansion Project

Lawrence Livermore National Security, LLC (LLNS) requests variance to 10 CFR 851 (the Rule) for the construction of the Digital Infrastructure Capabilities Expansion (DICE) project. The request isin continued support of the National Nuclear Security Administration (NNSA) “pilot” to streamline the delivery of commercial-like line-item construction projects under $50 million. This pilot is aligned with the approved NA-50 safety approach. Experience gained in the construction of the new Lawrence Livermore National Laboratory (LLNL) Emergency Operations Facility (EOC) under the variance granted in June 2020 is very encouraging. While detailed analysis will be forthcoming after that project is completed, there are strong indicators that a benefit has been realized by the subcontractors executing the work. The variance has permitted local/regional construction businesses contracted to Management & Operation contractor operated facilities and lower tier subcontractors to bid, operate, execute, and comply with safety and health standards they utilize in their business outside of the Department of Energy (DOE) Complex. While compliance to standards that are as safe and healthful as those in 10 CFR 851: confusion, additional cost, and inefficiencies associated with the burden of compliance to an unfamiliar regulatory spectrum has been avoided. Safety and health performance on the EOC construction project including the number of inspection and surveillance issues is comparable to other subcontractors and projects at LLNL executed under 10 CFR 851.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2023

LLNS Request for Permanent Variance from 10 CFR 851 for Construction

Lawrence Livermore National Security, LLC (LLNS) requests variance from 10 CFR 851 (the Rule) for construction work at Lawrence Livermore National Laboratory (LLNL). The request is based upon successful application of similar variances granted to LLNS in continued support of the National Nuclear Security Administration (NNSA) initiative to streamline the delivery of line-item construction projects under $50 million. This request is aligned with the approved NA 50 safety approach. Experience gained in the construction of the new LLNL Emergency Operations Center (EOC) under the variance granted in June 2020 and construction preparations to date on the Digital Infrastructure Capabilities Expansion (DICE) under the variance granted April 2022 is very encouraging. There are strong indicators that a benefit has been realized by both the subcontractors executing the work and the Laboratory. The variance has permitted local/regional construction businesses contracted to Management & Operation Contractor operated facilities and lower tier subcontractors to bid, operate, execute, and comply with safety and health standards they utilize in their business outside of the Department of Energy (DOE) Complex. While compliance to standards that are as safe and healthful as those in 10 CFR 851: confusion, additional cost, and inefficiencies associated with the burden of compliance to an unfamiliar regulatory spectrum has been avoided. Safety and health performance on the construction project including the number of inspection and surveillance issues is comparable to other subcontractors and projects at LLNL executed under 10 CFR 851. This variance application was prepared according to the requirements in 10 CFR 851, Subpart D – Variances, § 851.31 Variance Process. This request is limited to subcontractor executed construction at LLNL.

42 ENGINEERING↗
DOE OSTI2024

Unlocking the Path to Decarbonized Building Thermal Systems: Strategies for Designers and Contractors: Preprint

The design and construction community plays a pivotal role in facilitating the transition to decarbonized thermal systems that maintain human comfort while reducing building emissions. Through the U.S. Department of Energy Better Buildings initiative's Design and Construction Allies, a cohort of leading architecture, engineering, and construction firms have identified top ranked barriers that designers and contractors face when implementing solutions for building owners. These barriers to decarbonizing thermal - especially heating - systems include equipment availability; electrical capacity constraints; space allocations; complex system configurations; and lack of experience in designing, installing, and maintaining heat pumps. These impediments significantly amplify the risk and financial burden associated with the adoption of decarbonized solutions. The barriers also decrease the likelihood that designers, contractors, and owners will adopt decarbonization strategies without clear plans and guidance on how to implement these solutions, mitigate risk, and overcome the identified barriers. The National Renewable Energy Laboratory, the Design and Construction Allies, and the American Society of Heating, Refrigerating, and Air-Conditioning Engineers have developed "how to" thermal decarbonization guidance based on best practices. The subjects covered range from the role of energy efficiency in facilitating decarbonized heating solutions to strategies for decarbonizing new and existing heating, ventilating, and air-conditioning systems. The focus is on overcoming barriers so that energy-efficient, electrified buildings - both new and retrofit - become the industry standard. This paper outlines 1) the method used to collect and organize this guidance, 2) industry barriers to decarbonization, and 3) decarbonization techniques that have broad market applicability.

building heating↗
DOE OSTI2025

Advection algorithms for quantum neutrino moment transport

Neutrino transport in compact objects is an inherently challenging multidimensional problem. Here, this difficulty is compounded if one includes flavor transformation—an intrinsically quantum phenomenon requiring one to follow the coherence between flavors and thus necessitating the introduction of complex numbers. To reduce the computational burden, simulations of compact objects that include neutrino transport often make use of momentum-angle-integrated moments (the lowest order ones being commonly referred to as the energy density and flux) and these quantities can be generalized to include neutrino flavor, i.e., they become quantum moments. Numerous finite-volume approaches to solving the moment evolution equations for classical neutrino transport have been developed based on solving a Riemann problem at cell interfaces. In this paper we describe our generalization of a Riemann solver for quantum moments, specifically decomposing complex numbers in terms of a (signed) magnitude and phase instead of real and imaginary parts. We then test our new algorithm in numerous cases showing a neutrino fast flavor instability, varying from toy models with analytic solutions to snapshots from neutron star merger simulations. Compared to previous algorithms for neutrino transport with flavor mixing, we find uniformly smaller growth rates of the flavor transformation along with concomitantly larger length-scales, and that the results are a better match with the growth rates seen from multiangle codes.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2023

Perspectives on future research directions in green manufacturing for discrete products

With the increasing concern due to climate change caused by a higher atmospheric concentration of CO 2 and other greenhouse gases, reducing environmental impact is becoming more important for every part of society. Manufacturing is responsible for a significant amount of energy/material consumption and environmental burden and, therefore, has a great opportunity to reduce its impact through green manufacturing. Green manufacturing presents opportunities across the manufacturing enterprise to increase the efficient usage of energy and material resources. These opportunities include designing products to consume fewer materials and energy during manufacturing and use, incorporating more efficient manufacturing processes, streamlining and optimizing manufacturing schedules and plans, and circularizing products. The goal of this paper will be to provide a perspective from the authors on the opportunities that exist within green manufacturing for discrete products through a review of pertinent topics and future directions. The paper will focus on processes, manufacturing equipment, manufacturing systems, recovering value at a product’s end-of-life, and additional thoughts that include metrics and indicators, techno-economic assessment, and a discussion of efficiency and effectiveness. Key findings from this review include a need for social indicators and renewable energy considerations in scheduling and process planning, integrating Industry 4.0 into circular economy along with social and institutional dimensions, consistency in the ability to measure and conceptualize metrics and indicators, a detailed evaluation of the life cycle impacts and cost of Addit Manuf, and more human and environment-oriented considerations for smart manufacturing.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2025

ExtremeMETA: High-speed Lightweight Image Segmentation Model by Remodeling Multi-channel Metamaterial Imagers

Deep neural networks (DNNs) have heavily relied on traditional computational units, such as CPUs and GPUs. However, this conventional approach brings significant computational burden, latency issues, and high power consumption, limiting their effectiveness. This has sparked the need for lightweight networks such as ExtremeC3Net. Meanwhile, there have been notable advancements in optical computational units, particularly with metamaterials, offering the exciting prospect of energy-efficient neural networks operating at the speed of light. Yet, the digital design of metamaterial neural networks (MNNs) faces precision, noise, and bandwidth challenges, limiting their application to intuitive tasks and low-resolution images. In this study, we proposed a large kernel lightweight segmentation model, ExtremeMETA. Based on ExtremeC3Net, our proposed model, ExtremeMETA maximized the ability of the first convolution layer by exploring a larger convolution kernel and multiple processing paths. With the large kernel convolution model, we extended the optic neural network application boundary to the segmentation task. To further lighten the computation burden of the digital processing part, a set of model compression methods was applied to improve model efficiency in the inference stage. The experimental results on three publicly available datasets demonstrated that the optimized efficient design improved segmentation performance from 92.45 to 95.97 on mIoU while reducing computational FLOPs from 461.07 MMacs to 166.03 MMacs. The large kernel lightweight model ExtremeMETA showcased the hybrid design’s ability on complex tasks.

large convolution kernel↗
DOE OSTI2025

Super-Resolution for Renewable Energy Resource Data with Wind from Reanalysis Data and Application to Ukraine

With a potentially increasing share of the electricity grid relying on wind to provide generating capacity and energy, there is an expanding global need for historically accurate, spatiotemporally continuous, high-resolution wind data. Conventional downscaling methods for generating these data based on numerical weather prediction have a high computational burden and require extensive tuning for historical accuracy. In this work, we present a novel deep learning-based spatiotemporal downscaling method using generative adversarial networks (GANs) for generating historically accurate high-resolution wind resource data from the European Centre for Medium-Range Weather Forecasting Reanalysis version 5 data (ERA5). In contrast to previous approaches, which used coarsened high-resolution data as low-resolution training data, we use true low-resolution simulation outputs. We show that by training a GAN model with ERA5 as the low-resolution input and Wind Integration National Dataset Toolkit (WTK) data as the high-resolution target, we achieved results comparable in historical accuracy and spatiotemporal variability to conventional dynamical downscaling. This GAN-based downscaling method additionally reduces computational costs over dynamical downscaling by two orders of magnitude. We applied this approach to downscale 30 km, hourly ERA5 data to 2 km, 5 min wind data for January 2000 through December 2023 at multiple hub heights over Ukraine, Moldova, and part of Romania. With WTK coverage limited to North America from 2007–2013, this is a significant spatiotemporal generalization. The geographic extent centered on Ukraine was motivated by stakeholders and energy-planning needs to rebuild the Ukrainian power grid in a decentralized manner. This 24-year data record is the first member of the super-resolution for renewable energy resource data with wind from the reanalysis data dataset (Sup3rWind).

17 WIND ENERGY↗