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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 559 records · Page 31
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Upper Limit for the 248 Cm( 50 Ti, x n) 298− x Og Reaction Cross Section

After the synthesis of element 113, nihonium (Nh) via the 209 Bi( 70 Zn,n) 278 Nh cold fusion reaction using the RIKEN heavy-ion Linear ACcelerator (RILAC) and the GAs-filled Recoil Ion Separator (GARIS), the search for the heaviest isotopes of oganesson was initiated with GARIS-II by means of the 248 Cm( 50 Ti,xn) 298−x Og fusion evaporation reaction. The optimal bombarding energy for the 50 Ti + 248 Cm reaction was determined from the quasielastic barrier distribution extracted from the excitation function of quasielastic backscattering. Here, this method optimizes the compound nucleus formation. The search for Og was conducted for 39 days on the basis of the experimentally derived 50 Ti beam energy of 227.9(5) MeV at the middle of 248 Cm target. A precise analysis of the dataset based on multiple event search strategies revealed no decay chains with a total dose on 248 Cm target of 4.93 × 10 18 50 Ti projectiles, reaching a sensitivity of 0.27 pb and a 1σ upper cross section limit of 0.50 pb.

Gall, Benoît Jean-Paul [University of Strasbourg (↗
DOE OSTI2021

REopt Lite User Manual

REopt Lite evaluates the economic viability of grid-connected solar photovoltaics, wind, combined heat and power, and electric and thermal storage at commercial and small industrial sites. It allows building owners to identify the system sizes and dispatch strategies that minimize the site’s life cycle cost of energy. REopt Lite also estimates the amount of time on-site generation and storage can sustain the site's critical load during a grid outage and allows the user the choice of optimizing for energy resilience. It is primarily used to inform project development decisions and to support research on the factors that drive project feasibility for market development and policy analysis. It is available through a web interface, application programing interface, and open-source code. This user manual provides an overview of the model, including its capabilities and typical applications; inputs and outputs; economic calculations; technology descriptions; and model parameters, variables, and equations. The model is highly flexible and is continually evolving to meet the needs of each analysis. Therefore, this report is not an exhaustive description of all capabilities, but rather a summary of the core components of the model.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2025

Development of an interatomic potential for the Ta–Li system

A new interatomic potential for the Ta–Li system is introduced to facilitate the study of phase stability, mechanical properties and non-equilibrium dynamics after Li implantation in Ta. Here, this potential is based on a generalization of the embedded atom method (GEAM) and includes contributions from embedding energy, explicit two- and three-body interactions, and nonlocal many-body interaction terms. The parameters of the potential are optimized using energies and atomic forces for a wide range of configurations obtained from ab initio density functional theory (DFT) calculations. The potential is rigorously validated across a range of physical properties, including elastic constants, equations of state, phonon dispersion curves, point defect properties, and melting temperatures for different compositions. Although our potential is trained on a small dataset, its accuracy is comparable to that of available machine learning potentials for Li and Ta. Our simulations show that at temperatures below 500 K, Li atoms in Ta–Li alloys form clusters separated by Ta-rich domains, and we find no evidence of ordered phase formation. For Li concentrations below a few percent, Li atoms preferentially segregate to surfaces and grain boundaries. However, in alloys containing more than ~10% Li, the accumulation of Li in symmetric-tilt grain boundaries can lead to one of the following effects: formation of amorphous-like regions, changes in grain boundary structural units, or lateral movement of the grain boundary.

GEAM potential↗
NASA NTRS1989

Recent advances in efficient long-life, eye-safe solid state and CO2 lasers for laser radar applications

The key problems in the development of eye-safe solid-state lasers are discussed, taking into account the energy transfer mechanisms between the complicated energy level manifolds of the Tm, Ho, Er ion dopants in hosts with decreasing crystal fields such as YAG or YLF. Optimization of energy transfer for efficient lasing through choice of dopant concentration, power density, crystal field and temperature is addressed. The tailoring of energy transfer times to provide efficient energy extraction for short pulses used in DIAL and Doppler lidar is considered. Recent advances in Pt/SnO2 oxide catalysts and other noble metal/metal oxide combinations for CO2 lasers are discussed. Emphasis is given to the dramatic effects of small quantities of H2O vapor for increasing the activity and lifetime of Pt/SnO2 catalysts and to increased lifetime operation with rare isotope (C-12)(O-18)2 lasing mixtures.

Hess, R. V.↗
DOE OSTI2021

Fully variational incremental CASSCF

We report the complete-active-space self-consistent field (CASSCF) method is a canonical electronic structure theory that holds a central place in conceptualizing and practicing first principles simulations. For application to realistic molecules, however, the CASSCF must be approximated to circumvent its exponentially scaling computational costs. Applying the many-body expansion - also known as the method of increments - to CASSCF (iCASSCF) has been shown to produce a polynomially scaling method that retains much of the accuracy of the parent theory and is capable of treating full valence active spaces. Due to an approximation made in the orbital gradient, the orbital parameters of the original iCASSCF formulation could not be variationally optimized, which limited the accuracy of its nuclear gradient. Herein, a variational iCASSCF is introduced and implemented, where all parameters are fully optimized during energy minimization. This method is able to recover electronic correlations from the full valence space in large systems, produce accurate gradients, and optimize stable geometries as well as transition states. Demonstrations on challenging test cases, such as the oxoMn(salen)Cl complex with 84 electrons in 84 orbitals and the automerization of cyclobutadiene, show that the fully variational iCASSCF is a powerful tool for describing challenging molecular chemistries.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

H2Integrate [SWR-23-31]

H2Integrate(H2I) is an open-source Python package for hybrid systems engineering design and technoeconomic analysis. It models and optimizes hybrid energy plants that produce electricity, hydrogen, ammonia, steel, and other products. H2Integrate is designed to be flexible and extensible, allowing users to create their own components and models for various energy systems. The tool currently includes distributed energy generation (wind, solar, wave, tidal), battery storage, hydrogen, ammonia, methanol, and steel technologies. Other elements such as desalination systems, pipelines, compressors, and storage systems can also be included as developed by users. Some modeling capabilities in H2Integrate are provided by integrating existing tools, such as HOPP, PySAM, ORBIT, and ProFAST. The H2Integrate tool is built on top of NASA's OpenMDAO framework, which provides a powerful and flexible environment for modeling and optimization.

King, Jennifer [National Renewable Energy Laborato↗
DOE OSTI2020

Optimizing Cornell’s future geothermal district heating performance through systems engineering and simulation

Cornell University’s intention to lower its carbon footprint has motivated this engineering evaluation of using low-temperature geothermal energy to supply heat to the campus district energy system. Optimal selection and operation of heat pumps can significantly improve system performance. To support this analysis, we model the quantitative relationships between heat pump configurations and source flow, supply and distribution temperatures, facility heating design options, output heat generation, and carbon abatement outcomes. A systems approach is used for analysis, troubleshooting, and improvement of the model. The result of this effort is a dynamic tool that appropriately responds to hourly thermal demand and communicates energy response for techno-economic analysis. Simulations indicate that a single well-pair in the local Basement Contact Zone reservoir can satisfy almost 68% of annual thermal demand at nearly 20 MWth average capacity while remaining financially competitive compared to conventional heating with levelized cost of heating (LCOH) as low as $4.55/MMBTU ($15.53/MWh th ). A direct-use scheme with heat pump augmentation provided more carbon abatement and 50 to 150% more annual heat supply than one without augmentation. Exploration of three and four well-pair scenarios prove the capability to achieve 50 MW th baseload heating capacity with competitive LCOH and significant carbon reductions.

15 GEOTHERMAL ENERGY↗
DOE OSTI2020

Sensor Impacts Evaluation and Verification: Expert Interview Responses

The sensor configuration/deployment method has critical impacts on energy efficient building control and thermal comfort. However, traditional sensor techniques for building operation and fault detection and diagnostics (FDD) are not necessarily optimal in terms of energy efficiency and thermal comfort, and their global effects are not thoroughly investigated. In an effort to address and overcome this limitation, a multilaboratory and multiyear project, “Sensor Impact Evaluation and Verification,” was proposed. Its purpose is to develop a framework to investigate the impacts of sensor deployment and configuration on building energy optimization, FDD, occupant thermal comfort, and potentially grid efficiency. The first project task was a literature review to establish a solid knowledge of and a background related to sensor technologies and placement. To accomplish this task, an extensive review of previous research literature was performed. A series of expert interviews were conducted to augment the findings of the literature review. This report summarizes the interview design and interview results and findings. The interview was designed and performed to (1) investigate the current status and limitations of sensor configuration, (2) identify the research gaps and expectations for potential improvements in sensor configuration and deployment, and (3) integrate expert (e.g., researcher, building operation practitioner) knowledge and experience to develop use-case scenarios.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2026

Field Validation of a Grid-Interactive Efficient Building Software Solution

The U.S. General Services Administration's (GSA's) Green Proving Ground (GPG) program, in partnership with the National Laboratory of the Rockies (NLR), completed a field study of a Grid-Interactive Efficient Buildings (GEB) software solution. The study focused on a single testbed facility to test the GEB functionality of the software solution, along with other features. The testbed facility - a courthouse - is a common building type in GSA's vast building portfolio, offering potentially impactful findings on a scalable level. The study evaluated Prescriptive Data's technology, Nantum OS, a connected building operating system ("GEB Solution") which aggregates multiple sources of previously siloed building data and combines that data with external sources, such as weather information or utility signals, into a single integrated platform. A GEB Solution is a type of Energy Management Information System (EMIS). EMIS is defined as a system of devices, data services, and software applications that communicates with any building system or third-party data source to aggregate and transform data into new capabilities to aid in the optimization of energy use at the building, campus, or agency level. This specific GEB Solution is an EMIS with ASO, automated system optimization, offering supervisory control of certain aspects of the Building Automation System (BAS). Multiple features were evaluated including, but not limited to, Continuous Demand Management to avoid setting new monthly kilowatt (kW) peaks, energy efficiency for reduction of kilowatt hours (kWh) and natural gas consumption, and automated demand response (ADR) for purposes of lowering demand during a utility called Demand Response (DR) event. The testbed facility was the Foley Federal Building and US Courthouse ("Foley Federal Building") located in Las Vegas, NV. This is a 209,496 sq. ft. building constructed in the 1960s with major renovations in 2004. The facility was a good candidate due to the large prevalence of office and courthouse spaces in the GSA portfolio of buildings. It also has many features which allow integration into and control of the building and a strong facilities team to assist with the study. Quantitative and qualitative performance objectives were developed using GSA's GPG GEB project template along with input from the vendor and building facility staff; these are outlined in Table 1. The quantitative performance objectives focused on continuous demand management, energy efficiency, and automated demand response. The qualitative performance objectives focused on the ease of installation and commissioning as well as the operability of the GEB solution. Other performance metrics that are reported on include carbon reduction, cost effectiveness, and occupant acceptance.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2020

Minimizing total energy cost and tardiness penalty for a scheduling-layout problem in a flexible job shop system: A comparison of four metaheuristic algorithms

Job scheduling and machine layout are interrelated in improving energy consumption (EC) and productivity measures such as tardiness and represent two important decisions that must be made by manufacturers. This interdependency can be explained by transportation time, which connects scheduling and layout. Scheduling and layout, however, have not been thoroughly studied in conjunction using an integrated model in the context of sustainable manufacturing. Hence, we propose an energy-aware optimization model in which scheduling is integrated with layout in a single-level framework. More specifically, a single objective function is defined to minimize the facility energy cost and the job tardiness penalty, which control EC and tardiness respectively in a flexible job shop system. In order to model machine EC more accurately, we also consider three different machine states: a processing state and two idle states. Our case studies show that the integrated model exhibits better performance in controlling manufacturing EC and job tardiness than a non-integrated model in which machine locations are uncontrollable and transportation times between machines are unchangeable. To deal with large-sized problems, we also introduce four new metaheuristics. The performances of these new metaheuristics are compared in terms of objective function values and CPU times using various case studies. The results indicate that a hybrid ant colony optimization and simulated annealing (ACO-SA) algorithm provides better performance than the other algorithms. Specifically, our case studies show that the integrated model using ACO-SA can improve the objective function value by around 5% when compared to the non-integrated model.

42 ENGINEERING↗
DOE OSTI2022

Colloidal Platinum–Copper Nanocrystal Alloy Catalysts Surpass Platinum in Low-Temperature Propene Combustion

Low-temperature removal of noxious environmental emissions plays a critical role in minimizing the harmful effects of hydrocarbon fuels. Emission-control catalysts typically consist of large quantities of rare, noble metals (e.g., platinum and palladium), which are expensive and environmentally damaging metals to extract. Alloying with cheaper base metals offers the potential to boost catalytic activity while optimizing the use of noble metals. In this work, we show that Pt x Cu 100–x catalysts prepared from colloidal nanocrystals are more active than the corresponding Pt catalysts for complete propene oxidation. By carefully controlling their composition while maintaining nanocrystal size, alloys with dilute Cu concentrations (15–30% atomic fraction) demonstrate promoted activity compared to pure Pt. Complete propene oxidation was observed at temperatures as low as 150 °C in the presence of steam, and five to ten times higher turnover frequencies were found compared to monometallic Pt catalysts. Additionally, through DFT studies and structural and catalytic characterization, the remarkable activity of dilute Pt x Cu 100–x alloys was related to the tuning of the electronic structure of Pt to reach optimal binding energies of C* and O* intermediates. This work provides a general approach toward investigation of structure–property relationships of alloyed catalysts with efficient and optimized use of noble metals.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

A Case Study about Energy and Cost Impacts for Different Community Scenarios Using a Community-Scale Building Energy Modeling Tool

The United States building sector consumed approximately 75% of electricity in 2019. By implementing renewable energy technologies and control strategies into buildings, future buildings will serve as energy generators as well as consumers. To accommodate this transition, communications among buildings and between buildings and the grid could provide more possibilities to optimize the energy performance of buildings. This paper develops a community-scale building energy model tool and conducts a case study adopting behind-the-meter distributed energy resources, sharing energy in different buildings, and using different electricity tariff structures. Three scenarios are studied: (1) electricity only supplied by the grid, (2) photovoltaic (PV) panels installed on and available to some but not all buildings, and (3) a connected community. To consider the impacts of locations and energy tariffs, this paper selects four cities and three electricity tariffs to evaluate the energy and cost performances of these three scenarios. The results show that the PV panels in Scenario 2 reduce 25% to 33% of the community-level electricity consumption and 20% to 30% of the community-level electricity cost compared with Scenario 1 in all studied locations and energy tariffs. By considering power management in the connected community (Scenario 3), the electricity consumption and cost can be further reduced by 6% to 7% and 5% to 11%, respectively, compared with Scenario 2.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2026

Data-Driven Modeling of High-Resolution Residential Load Profiles Using Low-Resolution Smart Meter Measurements

Accurate and high-resolution residential load profiles are essential for power system modeling, demand response planning, and effective grid operation. As the energy sector moves towards a more actively managed distribution system, the ability to understand residential energy consumption at a minute-by-minute scale becomes increasingly critical. High-resolution load profiles provide key insights into demand patterns and user behavior, enabling grid operators to design more effective energy solutions; however, residential load measurements in the field are typically recorded at low resolutions, such as 15-60 minutes, which makes it hard to study the characteristics of different residential customers. This paper addresses these challenges by introducing a data-driven approach to generate realistic, high-resolution residential load profiles based on lowre-solution measurements and weather information. The proposed method retains the key features of the actual residential load measurements while offering appliance-level energy consumption details for each residential building. The results demonstrate the effectiveness of the proposed load profile generator, proving its capability to support utilities in optimizing residential energy management and ensuring a more reliable and resilient grid.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2021

Computational framework for behind-the-meter DER techno-economic modeling and optimization: REopt Lite

The energy system is undergoing a major transformation with the global emphasis on decarbonization. Distributed generation is projected to play a significant role in the new energy system, and energy models are informing how distributed generation can be integrated reliably and economically. In this work, we present an end-to-end computational framework for distributed energy resource (DER) modeling, REopt Lite™, which captures the interface of technology, economics, and policy in the energy modeling process. We describe the problem space, the building blocks of the model, the scaling capabilities of the design, the optimization formulation, and the extensibility of the model. We present a framework for accelerating the techno-economic analysis of behind-the-meter distributed energy resources to enable rapid planning and decision-making, thereby enabling greater renewable energy deployment. This computation framework is open-sourced to facilitate transparency, flexibility, and wider collaboration opportunities within the worldwide energy modeling community.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2024

Development of typical solar years and typical wind years for efficient assessment of renewable energy systems across the U.S.

Weather data plays a critical role in renewable energy analysis. Compared to using multiple Actual Meteorological Years, simulations using a single typical year require significantly fewer computational resources. Previous efforts to create typical weather datasets for renewable energy analysis either lack justified or optimized strategies for selecting and weighting different weather parameters or are limited to a few specific locations. Here, in this study, we developed a dataset comprising Typical Solar Years (TSYs) and Typical Wind Years (TWYs) for over 2000 locations across the U.S., based on data from NASA's POWER project. The strategies for creating TSYs and TWYs were optimized based on the simulated outputs of various PV systems and wind turbines in 16 representative cities. This dataset provides an efficient means for the rapid evaluation and optimization of renewable energy systems throughout the entire U.S. Additionally, the optimal strategies identified in this study can be directly applied to create near-optimal TSYs and TWYs for most locations worldwide. However, readers can also employ the optimization approach presented in this work to develop optimal strategies tailored for particular regions.

NASA POWER↗
DOE OSTI2024

Powering Data Centers with Clean Energy: A Techno-Economic Case Study of Nuclear and Renewable Energy Dependability

Rising data demands from artificial intelligence (AI) and large language models (LLMs) generating images, videos, and text have prompted increased need for larger and more robust data centers in the United States. Major companies interested in these larger data centers face the choice of linking them to existing regional grids, building stand-alone power supplies onsite, or a combination of both. The request, review, and approval process for new transmission lines to grids in the United States, however, has grown in recent years to times spans rivaling those of new construction for nuclear power plants. Building an islanded power supply for each data center is therefore becoming a prominent option. In this case study, several technologies are modeled in techno-economic simulations for long-term system costs subject to fixed electricity demand from a singular data center. A 250 MWe data center is assumed with additional 50 MWe for resiliency. Techno-economic simulations are conducted using the Holistic Energy Resource Optimization Network (HERON) software, which is a part of the Framework for Optimization of Resources and Economics (FORCE) tool suite. Technologies considered include solar, wind, lithium-ion batteries, and several types of nuclear reactors: large-scale reactors, small modular reactors, and microreactors. A low- and high-cost estimate for each technology is assumed to develop a range of expected economic performance. Low-cost estimates included several clean energy production tax credits. Different combinations of renewable energy generators with nuclear reactors are considered, ranging from a fully renewable-powered data center to a fully nuclear-powered data center. Historic time series of wind and solar availability from the Texas grid are used to train a reduced order model; this model then generates unique time series with similar characteristics of the training dataset. Multiple scenarios of weather and subsequent operations are simulated for each renewable-nuclear combination to determine total costs throughout the project lifetime. Fully renewable-powered configurations required large amounts of installed capacity (GW scale) in the simulations to meet the fixed demand of the data center. This is due to some scenarios in the historical dataset which captured low-wind and low-solar days, requiring over-building of these technologies as well as batteries to compensate for the low amounts of electricity generation. Fully nuclear-powered configurations outperformed the fully renewable and mixed renewable-nuclear configurations in terms of cost, with ranges between $1B and $10B in 2023 USDs compared to $40B+ for fully renewable configurations. Of the nuclear technologies, small modular reactors performed better economically than large-scale nuclear models due to lower projected capital costs, and both performed better than the microreactor models. These results demonstrate the applicability of firm, dispatchable electricity resources from baseload generators like nuclear power plants for operating facilities that run at constant power without daily variability.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
NASA NTRSDate not supplied

Identifying Optimal Site Location for Wind Energy Farms Considering Ecological and Social Impacts

With the increasing cost and declining availability of fossil fuels, renewable energy, specifically wind power, has become one of the fastest growing sources of energy in New Mexico. To assist with the goals set by the state’s Renewables Standard Portfolio established in 2004, the NASA DEVELOP team created three Optimal Wind Farm Suitability maps that consider social impact, ecological impact, and power production efficiency. The team utilized datasets from February 2013 – May 2018 that show vulnerable species, average wind patterns, and US Air Force Base locations. These three maps were combined into a final suitability map for optimal wind farm placement.

Joy Marich↗
DOE OSTI2021

Energy Arbitrage: Comparison of Options for use with LWR Nuclear Power Plants

Arbitrage is the opportunistic buying and selling of a commodity during local pricing valleys and peaks respectively to maximize economic value. This report evaluates options for energy arbitrage integrated with existing light water reactor (LWR) nuclear power plants (NPPs) where nuclear energy could be stored in a variety of forms and later recovered to generate electrical power during periods when grid electricity demand and pricing are high. The forms of energy storage examined in this report include the potential value of batteries, hydrogen, and thermal energy storage for coupling with nuclear power. Various large demand response options are also analyzed, including the production of liquid nitrogen via air separation and liquefaction, liquefaction of hydrogen, compressed hydrogen, and the cryogenic capture of CO2. Demand response refers to dispatchable loads that can cycle up or down depending on-grid electricity demand to aid in balancing the grid. Large demand response options could dispatch to aid nuclear power stations in avoiding power turndowns by providing an alternate disposition for electrical energy by producing marketable products (e.g., liquid nitrogen, hydrogen, or captured CO2). Static conditions were chosen and analyzed in this report for each option. Dynamic operation or optimization of energy arbitrage or demand response are out of scope for this report. The analysis is based on storage systems with discharge capacities of 500 MW for which various durations of storage and costs of charging (electricity cost) are examined. While the value of thermal energy to an industrial user for flexible plant operations has been previously proven as a business case, this report evaluates costs of hydrogen energy storage and leading thermal energy storage options, and large demand response loads that could be integrated with LWRs in comparison to utility-scale battery storage for use of off-peak nuclear energy. Compilation of this information will be used by the Idaho National Laboratory (INL) RAVEN/HERON systems integration and economics tool to evaluate thermal energy dispatch to industrial users. Relative ranking of energy storage options was done using a levelized cost of storage (LCOS) metric which calculates a rough breakeven cost for the system, taking into account the capital and operating costs as well as the revenue from arbitrage. Table ES1 below shows the LCOS for each of the energy storage options considered. First, in the table, lithium iron (Fe) phosphate batteries are listed as the base case for comparison against the other options. Next is hydrogen storage where most of the hydrogen analyses assumed the hydrogen to be produced using solid oxide electrolytic cell (SOEC) high temperature steam electrolysis (HTSE). The others used existing models of polymer electrolyte membrane (PEM) low temperature electrolysis to produce hydrogen. HTSE performance parameters and costs were taken from existing INL models. Various means were assumed to convert the hydrogen to electricity, including PEM fuel cells (FCs) and a gas turbine mixed in a 30 vol% mixture with natural gas. Physical storage (pressure vessels) and geological storage (natural underground features) were used to store the hydrogen as noted. Geological storage is more economical, but the locations are limited because of the requirement for pre-existing geological formations that will support storage. Thermal energy storage (TES) options were also analyzed including electro-thermal energy storage (ETES) and four different liquid sensible heat TES storage media as noted (Hitec, Hitec XL, Therminol-66, and Dowtherm A). The ETES process considered was modified using existing public documentation on an Echogen process and uses a separate supercritical CO2 charge and discharge cycle with sand as the heat storage media.

25 ENERGY STORAGE↗