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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 397 records · Page 22
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Commercial, industrial, and institutional discount rate estimation for efficiency standards analysis: Sector-level data 1998–2023

Underlying each of the U.S. Department of Energy’s (DOE’s) federal appliance and equipment energy conservation standards are a set of complex analyses of the projected costs and benefits of regulation. Any new or amended standard must be designed to achieve significant additional energy conservation, provided that it is technologically feasible and economically justified (42 U.S.C. 6295(o)(2)(A)). DOE determines economic justification based on whether the benefits exceed the burdens, considering a variety of factors, including the economic impact of the standard on consumers of the product and the savings in lifetime operating cost compared to any increase in price or maintenance expenses (42 U.S.C. 6295(o)(2)(B)). As part of this determination, DOE conducts a life-cycle cost (LCC) analysis, which models the combined impact of appliance first cost and operating cost changes on a representative commercial building sample to identify the fraction of customers achieving LCC savings or incurring net cost at the considered efficiency levels. Thus, the commercial discount rate value(s) used to calculate the present value of energy cost savings within the LCC model implicitly plays a role in estimating the economic impact of potential standard levels. This report provides an in-depth discussion of the commercial discount rate estimation process relying on the Capital Asset Pricing Model (CAPM) to estimate a business’ cost of equity, and by adding a risk adjustment factor to the risk-free rate associated with long-term U.S. Treasury bonds to estimate their cost of debt. It is an update to previous reports on estimating commercial discount rates from firm-level and sector-level financial data (e.g., Fujita, 2021, 2016). Major topics covered in this report include the following: • Discount rate estimation methods and rationale • Data sources used and data limitations • Discount rate distributions for use in standards analysis • Discount rate estimation methods and distributions specific to the small business subgroup analysis.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2024

A Comprehensive Analysis of PINNs for Power System Transient Stability

The integration of machine learning in power systems, particularly in stability and dynamics, addresses the challenges brought by the integration of renewable energies and distributed energy resources (DERs). Traditional methods for power system transient stability, involving solving differential equations with computational techniques, face limitations due to their time-consuming and computationally demanding nature. This paper introduces physics-informed Neural Networks (PINNs) as a promising solution for these challenges, especially in scenarios with limited data availability and the need for high computational speed. PINNs offer a novel approach for complex power systems by incorporating additional equations and adapting to various system scales, from a single bus to multi-bus networks. Our study presents the first comprehensive evaluation of physics-informed Neural Networks (PINNs) in the context of power system transient stability, addressing various grid complexities. Additionally, we introduce a novel approach for adjusting loss weights to improve the adaptability of PINNs to diverse systems. Our experimental findings reveal that PINNs can be efficiently scaled while maintaining high accuracy. Furthermore, these results suggest that PINNs significantly outperform the traditional ode45 method in terms of efficiency, especially as the system size increases, showcasing a progressive speed advantage over ode45.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

A Reduced-form Cost Model for Prefeasibility Analysis of Hydropower at Non-Powered Dams

This study presents a reduced-form model to support a better understanding of the capacity potential and drivers of costs for hydropower development at U.S. non-powered dams (NPD), which are existing dams that are not currently used for hydropower. With information on nineteen reference sites, a set of reduced-form design and cost equations were estimated to enable rapid assessments of aggregate costs and their components for a large number of NPD sites. The model was then applied to 36,000+ potential U.S. NPD sites using the limited data commonly available. Although the cost estimates span a wide range, there exists a significant amount of U.S. NPD hydropower capacity potential, which are considered cost-competitive in the current market using baseline technologies.

13 HYDRO ENERGY↗
DOE OSTI2024

Uncertainty Quantification and Sensitivity Analysis for Quantitative Risk Assessments of Hydrogen Infrastructure

Typical QRAs provide deterministic estimates and understanding of risks posed but are constructed using significant assumptions and uncertainties due to limited data availability and historical momentum of using nominal estimates. This report presents a hydrogen QRA analysis using HyRAM+ that incorporates uncertainty with Latin hypercube sampling and sensitivity analysis using linear regression.

08 HYDROGEN↗
DOE OSTI2025

Hourly Load Profile Dataset for Electric Airport Ground Support Equipment in the United States

Currently, there are limited data on the magnitude and timing of electricity demand from electric ground support equipment (eGSE) across U.S. airports. To address this gap, this study presents a modeling approach for estimating hourly annual electricity demand from eGSE at the 50 largest U.S. commercial airports. These datasets, accessible at data.nrel.gov/submissions/279, provide critical insights into the potential grid impacts and electricity demand associated with eGSE adoption.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2025

Decision Tree for Variable Selection vs. Impact on Durability for Biomass and Biochar Burial Pathways [Slides]

Quantifying durability for lower-TRL BiCRS pathways has been challenging as limited data are available from real-world projects and long-term experiments, resulting in an overall lack of scientific consensus. We develop a decision tree that aims to summarize the current scientific understanding and state-of-the-art project experience. The decision tree can be used to (1) guide the selection of key variables and evaluate their relative impact on durability, (2) identify data and knowledge gaps for future research.

09 BIOMASS FUELS↗
DOE OSTI2025

Report on Updated Properties Handbook of Printed Stainless Steel 316

This report focuses on summarizing mechanical behavior of 316H stainless steel (SS) printed using laser powder bed fusion (LPBF). 316H SS is one of the six alloys that has been qualified for use in nuclear reactors. The Advanced Materials and Manufacturing Technologies (AMMT) program has identified the use of the additive manufacturing (AM) process of LPBF as one of the manufacturing modalities to fabricate components for nuclear applications. Unlike wrought material, AM material displays significant heterogeneity in properties, resulting from changes in process parameters, machine-to-machine variability, and minor changes in feedstock chemistry from one batch to another. Although significant work has been done on 316L SS in the literature and has been summarized in several review papers, very limited data exist on 316H SS. Therefore, this report aims to provide a concise summary of the properties of 316H SS printed using different machines and at different locations as a part of the AMMT program.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Depletion Benchmark of the AFIP-7 Experiment in the Advanced Test Reactor

Reactor physics depletion benchmarks for low-enriched uranium fuel are limited in number. In particular, there is very limited data for LEU benchmarks for U-10Mo (Uranium-10% Molybdenum) plate fuel developed for use in U.S. high-performance research reactors (USHPRR). USHPRR includes the Advanced Test Reactor (ATR), Advanced Test Reactor Critical Facility (ATR-C), High Flux Isotope Reactor (HFIR), University of Missouri Research Reactor (MURR), Massachusetts Institute of Technology Reactor (MITR), and National Bureau of Standards Reactor (NBSR) at the National Institute of Science and Technology. These reactors are fueled with high-enriched uranium dispersed fuel in a silicon/aluminum matrix. In support of conversion to a HALEU fuel, qualification of U-10Mo formed into a monolithic foil is being performed. Fuel qualification involves irradiated fueled specimens in the ATR. The irradiation tests provide an opportunity to benchmark depletion capabilities of reactor physics codes in support of the ATR operation, as well as develop benchmarks that can be used by other institutions to benchmark other reactor physics codes. This report documents the development of a benchmark model of the irradiation of the ATR Full -size plate In center flux trap Position 7 (AFIP-7) experiment.

11 - NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2025

Demonstration of the surveillance test article for an advanced reactor surveillance test program

Operational environments in generation IV reactors involve corrosive and irradiative conditions at elevated temperatures. Typical reactor operations consist of transients which impose cyclic loads on reactor components. These cyclic loads, combined with corrosive and irradiative environments, result in synergistic degradation of component materials. However, limited data exists on the coupled damage effects on materials for reactor environments. While the surrogate material surveillance concept has been used in light water reactors to assess irradiation damage, existing material surveillance technologies are not suitable for in-situ monitoring of coupled material degradation. The materials surveillance program focuses on material degradation management and the estimation of remaining life of reactor components through surveillance test articles. This paper presents the design and analysis methodology of a bi-metal surveillance test article, which uses difference in thermal expansion coefficient between two metals to induce in-situ cyclic loads. This report presents the work conducted in FY 25, to test the surveillance test article in air and salt environments. These test specimens were evaluated after thermal cycle exposure and remaining life is measured through creep test.

36 - MATERIALS SCIENCE↗
DOE OSTI2026

Reducing Deferrals by Integrating Health Homes with Weatherization

The U.S. Department of Energy’s Weatherization Assistance Program (WAP) improves energy efficiency and household health for low-income families, yet a substantial number of otherwise eligible homes are deferred from due to health and safety concerns in their homes, including mold, moisture damage, or structural deficiencies. These deferred homes are often occupied by marginalized or otherwise vulnerable residents who may be exposed to elevated indoor air pollutant concentration. Integrating Healthy Homes (HH) interventions with weatherization has been proposed as a strategy to reduce deferrals, address environmental justice concerns, and improve health outcomes. However, limited data on the health and economic implications of such integration exist. This study aimed to assess the potential health benefits and savings-to-investment ratio (SIR) associated with integrating Healthy Homes interventions into weatherization programs for homes typically deferred from WAP services. We collected indoor air pollutant data from homes undergoing health home renovations, including fine particulate matter (PM 2.5 ), nitrogen dioxide (NO 2 ), carbon monoxide (CO), and formaldehyde, with sampling times up to one month. Except for fomaldehyde, which was measured using passive UMEx badges, the other metrics were measured using the airQ Pro indoor air quality monitor.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2025

Applying Transfer Learning for Street-Scale Nuisance Flood Forecasting in Coastal-Urban Cities

An important challenge with Machine Learning (ML) is its transferability; that is, whether a ML model trained on one set of data can be applied to a second set of data without requiring a full re-training of the model. Transfer Learning (TL) addresses this challenge by transferring knowledge learned in the source domain (the data it was trained on) to the target domain (a second set of data that is statistically different but related, which the model was not trained on). This study investigates the use of TL for street-scale nuisance flood forecasting by exploring whether a ML model trained on data collected for one set of streets can effectively forecast flooding for another set of streets in the same city using TL. The envisioned use case is a city deploying a new flood depth monitoring sensor on a street and using TL to apply a ML model, trained on sensor data from an existing flood depth sensor network, to this new street. Eventually, the new flood depth sensor will have a sufficient dataset for training its own ML model, but TL can be used to fill the gap in time while this new dataset is being generated. This method is explored using a Long Short-Term Memory (LSTM) model trained on data for the flood-prone streets of Norfolk City, Virginia. The data used for training includes environmental time series (rainfall, tide), topographic features (Digital Elevation Model (DEM), Topographic Wetness Index (TWI), Depth To Water (DTW)), and street-scale flood depth time series obtained from a high-fidelity physics-based model, acting as a synthetic street-scale stream depth sensor dataset since actual stream depth sensor data is generally unavailable for most cities. A set of 180 flood-prone streets was used to train a base model, while another set of 180 flood-prone streets was used to re-train that model using different TL strategies. The results show that full-weight re-training proved most effective and minimal re-training of only the output layer was insufficient. The advantage of TL was most pronounced when target data was limited, meaning data collected at the new water depth sensor location included generally less than 18 flood events. As target data increased beyond 18 flood events, the benefit of TL diminished relative to training a ML model directly on the local flood events. These findings can assist cities as they implement street-scale flood sensing systems to create accurate forecasts for new sensing locations that do not yet have sufficient data records to train a local ML model.

Roy, Binata [Univ. of Virginia, Charlottesville, V↗
DOE OSTI2022

Distributed Transient Safety Verification via Robust Control Invariant Sets: A Microgrid Application

Modern safety-critical energy infrastructures are increasingly operated in a hierarchical and modular control framework which allows for limited data exchange between the modules. In this context, it is important for each module to synthesize and communicate constraints on the values of exchanged information in order to assure system-wide safety. To ensure transient safety in inverter-based microgrids, we develop a set invariance-based distributed safety verification algorithm for each inverter module. Applying Nagumo's invariance condition, we construct a robust polynomial optimization problem to jointly search for safety-admissible set of control set-points and design parameters, under allowable disturbances from neighbors. We use sum-of-squares (SOS) programming to solve the verification problem and we perform numerical simulations using grid-forming inverters to illustrate the algorithm.

Bouvier, Jean-Baptiste H.↗
DOE OSTI2023

Fan and Pump Efficiency in Modelica based on the Euler Number

Simulation programs often assume constant hydraulic efficiency for fan or pump models when performance curves are unavailable. This is inaccurate because the hydraulic efficiency varies with the operation condition. It therefore consistently underestimates the power draw at off-design conditions at which the hydraulic efficiency drops. Use of a modified Euler number allows computing the hydraulic efficiency and shaft power with limited data. Others showed the validity of the modified Euler number for fan efficiency calculations. We show that it is also applicable for pumps, and present its implementation in Modelica for a fan or pump model. Here, the only input required from the user is one data point at which the hydraulic efficiency is at its maximum. The reported method is applicable regardless of the type, size, or operational region of the fan or pump. Across a sample of eighteen sets of pump data and seven sets of fan data, the errors of the computed power from interpolated data were within 15% for the range of 20% - 70% of maximum flow rate and 40% - 90% of maximum pressure rise, excluding outliers.

component model↗
DOE OSTI2025

Unique genetic signatures in HIV-1 subtype A1 and A1D recombinant envelope glycoprotein distinguish contemporary transmitted/founder viruses from historical strains in East Africa

Introduction: The envelope glycoprotein (Env) of HIV-1 Transmitted/Founder (T/F) viruses in subtypes B and C carries distinct genetic signatures that enhance transmission fitness, augment infectivity and immune evasion. However, there is limited data on such signatures in T/F subtypes A1, D and A1D recombinants that predominate East Africa’s HIV epidemic.Methods: We used phylogenetically corrected approaches to detect distinct genetic signatures by comparing 44 contemporary HIV-1 T/F Envs with 229 historical Envs of the same subtype in East Africa.Results and Discussion: Subtype analysis based on the full-length Env gene of contemporary T/F viruses revealed a high proportion of subtype A1, followed by A1D recombinants, and fewer subtype D. Signature analysis revealed that the contemporary subtype A1 T/Fs were more likely to select distinct amino acids, including M22 in the signal peptide, R82 in gp120, A172 in the V2 loop, E230 in the glycosite 230, K275 in the D loop, Y317 in the V3 loop, K476 and N477 in the CD4 contact site, when compared with the historical Envs (q-value < 0.2). Conversely, the contemporary subtype A1 T/F Envs were less likely to carry the amino acids Q432 in the CD4 contact site, and the L784 signature within the LLP-2 (q-value < 0.2). The A1D recombinant T/Fs were more likely to select the D620 in the C-helix, but under selected the L34 in gp120, P299 in the V3 loop and Y643 in the Heptad repeat-2, compared to the historical Envs (q-value < 0.2). The distinct signature sites reported in this study may contribute to the successful establishment of acute infection as well as the persistence of long-term infection. Therefore, effective therapeutics and vaccines may target these distinct amino acid signatures especially for the East African region as it may be necessary to employ subtype-specific vaccines according to the subtype distribution.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

A Comprehensive Analysis of PINNs for Power System Transient Stability

The integration of machine learning in power systems, particularly in stability and dynamics, addresses the challenges brought by the integration of renewable energies and distributed energy resources (DERs). Traditional methods for power system transient stability, involving solving differential equations with computational techniques, face limitations due to their time-consuming and computationally demanding nature. This paper introduces physics-informed Neural Networks (PINNs) as a promising solution for these challenges, especially in scenarios with limited data availability and the need for high computational speed. PINNs offer a novel approach for complex power systems by incorporating additional equations and adapting to various system scales, from a single bus to multi-bus networks. Our study presents the first comprehensive evaluation of physics-informed Neural Networks (PINNs) in the context of power system transient stability, addressing various grid complexities. Additionally, we introduce a novel approach for adjusting loss weights to improve the adaptability of PINNs to diverse systems. Our experimental findings reveal that PINNs can be efficiently scaled while maintaining high accuracy. Furthermore, these results suggest that PINNs significantly outperform the traditional ode45 method in terms of efficiency, especially as the system size increases, showcasing a progressive speed advantage over ode45.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2021

Recovery of Rare Earth Oxides from Flotation Concentrates of Bastnaesite Ore by Ultra-Fine Centrifugal Concentration

Historically, the ability to effectively separate carbonate gangue from bastnaesite via flotation has frequently proven to be challenging without sacrificing significant rare earth oxide (REO) grade or recovery. However, in light of the fact that the rare earth bearing minerals often exhibit higher specific gravities than the carbonate gangue, the possibility exists that the use of gravity separation could be used to achieve such a selective separation. This however is complicated by the fact that, in cases such as this study when the liberation size is finer than 50 microns, most traditional gravity separation methods become increasingly challenging. The aim of this study is to determine the applicability of centrifugal concentrators to beneficiate ultra-fine (UF) bastnaesite and calcite bearing flotation concentrates. By using a UF Falcon, it was possible to achieve initial gravity REO recoveries exceeding 90% while rejecting on the order of 25% to 35% of the total calcium from an assortment of rougher and cleaner flotation concentrates. Additionally, when additional stages of cleaner UF Falcon gravity separation were operated in an open circuit configuration, it was possible, from an original fine feed of 35 microns containing 50.5% REO and 5.5% Ca, to upgrade up to approximately 59% REO and 2.0% calcium. While not the goal of this study, these results also support previous limited data to suggest that UF Falcons are potentially capable of treating a wider range of materials than they were originally designed for, including feeds rich in heavy mineral content.

Norgren, Alex↗
DOE OSTI2022

Hydriding, Oxidation, and Ductility Evaluation of Cr-Coated Zircaloy-4 Tubing

Accident-tolerant fuel concepts have been developed recently in diverse research programs. Recent research has shown clear advantages of Cr-coated Zr cladding over bare cladding tubes regarding oxidation behavior under the design basis loss-of-coolant accident condition. However, limited data are available about the hydriding behavior of the Cr coating. For that purpose, Cr-coated Zricaloy-4 tubes were tested to investigate the effects of hydriding, oxidation, and postquench ductility behavior on coated Zr cladding. A high-power impulse magnetron sputtering (HiPIMS) process was used to produce a high-density coating on the Zircaloy-4 tube surface. Coated and uncoated Zircaloy-4 tube specimens underwent one-sided hydriding in a tube furnace filled with pure hydrogen gas at 425 °C. The tubing specimen ends were sealed with Swagelok plugs before the hydriding runs. For uncoated specimens, H analysis of the hydrided specimens indicated that the H content increased as the test time and initial pressure increased. However, almost no change was observed for the coated specimens that were hydrided under the same test conditions. After one-sided hydriding, the hydrided coated and uncoated specimens were exposed to steam at high temperatures for two-sided oxidation studies to simulate accident conditions. The coated specimens showed a slower oxidation: oxygen pickup was 50% lower than the uncoated specimens tested under the same conditions. Ring compression testing was performed to evaluate the embrittlement behavior of the Cr-coated specimens after hydriding and oxidation. The results indicated that the HiPIMS coating provides excellent protection from hydriding and oxidation at high temperatures.

36 MATERIALS SCIENCE↗
DOE OSTI2022

A Hybrid Experimental and Theoretical Approach to Optimize Recovery of Rare Earth Elements from Acid Mine Drainage Precipitates by Oxalic Acid Precipitation

The development of processing techniques for the extraction of rare earth elements and critical minerals (REE/CM) from acid mine drainage precipitates (AMDp) has attracted increased interest in recent years. Processes under development often utilize a standard hydrometallurgical approach that includes leaching and solvent extraction followed by oxalic acid precipitation and calcination to produce a final rare earth oxide product. Impurities such as Ca, Al, Mn, Fe and Mg can be detrimental in the oxalate precipitation step and a survey of the literature showed limited data pertaining to the REE precipitation efficiency in solutions with high impurity concentrations. As such, a systematic laboratory-scale precipitation study was performed on a strip solution generated by the acid leaching and solvent extraction of an AMDp feedstock to identify the optimal processing conditions that maximize REE precipitation efficiency and product purity while minimizing the oxalic acid dosage. Given the unique chemical characteristics of AMDp, the feed solution utilized in this study contained a moderate concentration of REEs (440 mg/L) as well a significant concentration (>7000 mg/L total) of non-REE contaminants such as Ca, Al, Mn, Fe and Mg. Initially, a theoretical basis for the required oxalic acid dose, optimal pH and predicted precipitation efficiency was established by solution equilibrium calculations. Following the solution chemistry calculations, bench-scale precipitation experiments were conducted and these test results indicate that a pH of 1.5 to 2, a reaction time of more than 2 h and an oxalic acid dosage of 30 to 40 g/L optimized the REEs recovery of at ~95% to nearly 100% for individual REE species. The test results validated the optimal pH predicted by the solution chemistry calculations (1.5 to 5); however, the predicted dosage needed for complete REE recovery (10 g/L) was significantly lower than the experimentally-determined dosage of 30 to 40 g/L. The reason for this discrepancy was determined to be due to the large concentration of impurities and large number of potential metal complexes that cause inaccuracies in the solution equilibrium calculations. Based on these findings, a hybrid experimental and theoretical approach is proposed for future oxalic acid precipitation optimization studies.

oxalic acid precipitation↗