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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 19 records
All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

WholeTraveler Anonymized Data Phase 1

Phase 1 of the WholeTraveler Study data collection consisted of an online-only survey. This survey captured data on three categories of observable variation in the population relevant to transportation decisions. First, the survey collected traditional demographic data such as age, gender, income, and education level. Second, it collected data across personality, psychological, and preference categories. This included: 1. The "Big Five" inventory personality traits: openness to new experience, conscientiousness, extroversion, agreeableness, and neuroticism; 2. Risk and time preferences; and 3. Environmental preferences. Third, the survey collected data on historical behavior patterns including: 1. Adoption of (as well as interest in) new technologies or innovations (e.g., smartphones, PEVs, solar panels, adaptive cruise control [ACC]); 2. Car ownership history and current car ownership status; 3. Recent mode use across different time scales (e.g., previous week, previous month, previous year); and 4. Timing of major life events such as starting a family as well as overall lifecycle trajectory patterns. Data from Phase 1 and Phase 2 are linked by a unique respondent identifier. Anonymized versions of the Phase 1 and Phase 2 data are both available on Livewire.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2016

WEC-SIM Phase 1 Validation Testing -- Numerical Modeling of Experiments: Preprint

The Wave Energy Converter Simulator (WEC-Sim) is an open-source code jointly developed by Sandia National Laboratories and the National Renewable Energy Laboratory. It is used to model wave energy converters subjected to operational and extreme waves. In order for the WEC-Sim code to be beneficial to the wave energy community, code verification and physical model validation is necessary. This paper describes numerical modeling of the wave tank testing for the 1:33-scale experimental testing of the floating oscillating surge wave energy converter. The comparison between WEC-Sim and the Phase 1 experimental data set serves as code validation. This paper is a follow-up to the WEC-Sim paper on experimental testing, and describes the WEC-Sim numerical simulations for the floating oscillating surge wave energy converter.

16 TIDAL AND WAVE POWER↗
DOE OSTI2024

Advanced Construction Technology Initiative Program: ACTI Phase 1 ACTI Phase 2

Demonstrate technologies to significantly reduce the cost and schedule for construction of advanced reactors. Demonstrate the technology by 2026/2027 to improve the economics of deploying advanced reactors. Selected technologies will not require major R&D efforts. With prototyping and testing, the technologies will be ready for deployment at scale.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2020

Development of risk mitigation guidance for sensor placement inside mechanically ventilated enclosures – Phase 1

Guidance on Sensor Placement was identified as the top research priority for hydrogen sensors at the 2018 HySafe Research Priority Workshop on hydrogen safety in the category Mitigation, Sensors, Hazard Prevention, and Risk Reduction. This paper discusses the initial steps (Phase 1) to develop such guidance for mechanically ventilated enclosures. This work was initiated as an international collaborative effort to respond to emerging market needs related to the design and deployment equipment for hydrogen infrastructure that is often installed in individual equipment cabinets or ventilated enclosures. The ultimate objective of this effort is to develop guidance for an optimal sensor placement such that, when integrated into a facility design and operation, will allow earlier detection at lower levels of incipient leaks, leading to significant hazard reduction. Reliable and consistent early warning of hydrogen leaks will allow for the risk mitigation by reducing or even eliminating the probability of escalation of small leaks into large and uncontrolled events. To address this issue, a study of a real-world mechanically ventilated enclosure containing GH2 equipment was conducted, where CFD modeling of the hydrogen dispersion (performed by AVT and UQTR, and independently by the JRC) was validated by the NREL Sensor laboratory using a Hydrogen Wide Area Monitor (HyWAM) consisting of a 10-point gas and temperature measurement analyzer. In the release test, helium was used as a hydrogen surrogate. Expansion of indoor releases to other larger facilities (including parking structures, vehicle maintenance facilities and potentially tunnels) and incorporation into QRA tools, such as HyRAM is planned for Phase 2. It is anticipated that results of this work will be used to inform national and international standards such as NFPA 2 Hydrogen Technologies Code, Canadian Hydrogen Installation Code (CHIC) and relevant ISO/TC 197 and CEN documents.

08 HYDROGEN↗
DOE OSTI2016

Summary of Phase 1 and Plans for Phase 2 of the Washington State Geothermal Play-Fairway Analysis

A geothermal play fairway is constituted by the collocation of heat, permeability, and saturated porosity in sufficient volume that provide adequate heat exchange at depths accessible by modern drilling technologies. The focus of Phase 1 of the Washington State play-fairway analysis (PFA) was to develop and apply a methodology to integrate detailed models of heat and permeability potential for each play (study area). The goal is to minimize risk associated with investments in geothermal exploration of greenfield projects by rigorously analyzing available data, applying favorability modeling concepts that have been successfully used at known geothermal systems, and addressing data quality and model sensitivity. The integrated results indicate locations where commercial geothermal potential is highest, based on available data. Here, these results also reveal where new data are needed to increase resolution and reduce uncertainty to minimize risk (work conducted in Phase 2), and thus successfully identify sites for exploration wells (in Phase 3).

geothermal favorability↗
DOE OSTI2023

Phase 1: Duke Energy Zero Emission Resource Integration Study (ZERIS); Phase 2: Carbon-Free Resource Integration Study for Duke Energy (Final Report)

Phase 1: This statement of work makes up Phase 1 of a larger effort. During this Phase 1 effort, NREL will work with Duke Energy to analyze the impacts of integrating significant amounts of new solar power into the Duke Energy power system under a variety of different penetrations scenarios, with a maximum of ten (10) full scenarios examined. The existing fleet, particularly the nuclear generation, will be considered in the quantitative assessments and discussions. Duke Energy is looking to quantify how much solar generation its system can handle. NREL will work with Duke Energy to quantify solar potential, identify likely integration challenges and possible opportunities for wind, storage, demand side resources and other technologies. Phase 2: This Statement of Work consists of a follow-up effort (Phase 2) to a recently completed Phase 1 modeling effort. During Phase 2, NREL will work closely with Duke Energy to analyze the impacts of integrating significant amounts of variable generation resources (wind and solar) and storage into Duke Energy's system in the Carolinas. The existing fleet, particularly nuclear generation, will be considered in the quantitative assessment and discussions. This Statement of Work also includes an extension to Phase II of the Carbon-Free Resource Integration Study for Duke Energy. In this extension, NREL will work closely with Duke Energy to extend the production cost analysis developed in Phase II to 2018 weather and load data for Duke Energy's territory. This extension leverages the modeling tools and datasets developed as part of Phase II. The analysis will compare results from Phase II (using 2012 weather and load) with 2018 results to assess system operations with increased penetration of renewables and storage. Simplifying assumptions will be made for modeling Duke Energy's neighbors in the production cost model.

14 SOLAR ENERGY↗
DOE OSTI2020

Advanced Modular Sub-Atmospheric Hybrid Heat Engine (Phase 1 Final Report)

The Phase 1 Final Report describes the results of the work completed during the “Advanced Modular Sub-Atmospheric Hybrid Heat Engine” project. The objectives of Phase 1 work were to develop a conceptual design of the turbine-based modular hybrid heat engine (MHHE), including thermodynamic cycle analysis, define the nominal engine component boundary conditions, identify technology gaps, and develop a detailed test plan to address these gaps through bench scale testing in a potential subsequent Phase 2 project. To achieve the project objective, the following activities were performed in Phase 1 work: (1) Market analysis and primary fuel selection, (2) Conceptual design and integrated layout development, (3) Design support and key components characterization, (4) Planning to move technology to pre-commercial demonstration.

42 ENGINEERING↗
DOE OSTI2026

ICE Calculator 2: Final Report for Phase 1 and 2 of the National Initiative to Update the Interruption Cost Estimate (ICE) Calculator

ICE 2.0 Phase 2 Final Report In 2021, Berkeley Lab and Resource Innovations, Inc. launched the “ICE Calculator 2 Initiative” – a national study to refresh the underlying data and enhance the functionality of the ICE Calculator. The Initiative involves Berkeley Lab contracting with sponsoring utilities to administer identical, updated and comprehensive interruption cost surveys to statistically representative samples of each utility’s customers. Berkeley Lab and Resource Innovations then pool the survey results across the utilities and use them to update the analytical engines that drive the ICE Calculator. The ICE Calculator 2 Initiative is being conducted in phases. Each phase involves the administration of interruption cost surveys to the customers of sponsoring utilities, followed by an update to the ICE Calculator based on analysis of the pooled survey results. This report describes the activities and findings from Phase 1 and 2 of the ICE Calculator 2 Initiative. Phase 1 was sponsored by eight utilities: American Electric Power, Commonwealth Edison, Dominion Energy, Duke Energy, DTE Electric, Exelon, National Grid, and Puget Sound Energy. Phase 2 was sponsored by six utilities: Empire District Electric Company, Evergy Missouri, Pacific Gas & Electric, San Diego Gas & Electric, Southern California Edison, and Union Electric. Phase 1 and 2 involved 15 customer interruption cost survey activities representing a total of 30 electricity distribution service territories. ICE Calculator Version 2.0 and 2.2 Comparison This memorandum describes–at a high-level–the improvements in interruption cost estimates for the version 2.2 of the ICE Calculator (released February 2026) compared to version 2.0 (released in April 2025). Version 2.2 of the ICE Calculator corresponds to Phase 2 of the initiative, while version 2.0 corresponds to Phase 1. The improvements in version 2.2 result from both a significant increase in the number of customer responses that have been collected and the identification of seven additional factors that help estimate customer interruption costs.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2024

Towards a Workforce Roadmap for Distributed Wind: Phase 1 - Identifying Needs and Barriers

Despite recent policy, research efforts, and resources available for utility-scale and offshore wind workforce development, the distributed wind (DW) industry has yet to make similar advances to address its workforce challenges. This report initiates the phased development of a DW workforce roadmap to provide a foundation for roadmap development. Phase 1, contained in this report, uses desk-based research on clean energy workforce approaches and a DW interested-party survey to discuss needs and barriers hindering the workforce from expanding. Findings are summarized into goals and solutions for Phase 2 of roadmap development, which identifies actors responsible for implementing solutions identified in Phase 1. Phase 1 results suggest that the sector's small size and limited growth motivate the short-term need for skilled workers or candidates with well-rounded and multifaceted abilities. Long-term expansion plans must diversify positions while capitalizing on existing utility-scale wind and offshore workforce efforts, as well as other renewable sector best practices where possible. The findings in this report can advance workforce development in the DW sector by aligning interested industry parties around common goals to address challenges. Training providers, installers, operators, manufacturers, federal agencies, national laboratories, academic partners, and labor unions can utilize the findings to help promote sustainable growth of the DW sector.

17 WIND ENERGY↗
DOE OSTI2016

Frontier Observatory for Research in Geothermal Energy: Phase 1 Topical Report Fallon, NV

The Department of Energy (DOE) Frontier Observatory for Research in Geothermal Energy (FORGE) is to be a dedicated site where the subsurface scientific and engineering community can develop, test, and improve technologies and techniques for the creation of cost-effective and sustainable enhanced geothermal systems (EGS) in a controlled, ideal environment. The establishment of FORGE will facilitate development of an understanding of the key mechanisms controlling a successful EGS. Execution of FORGE is occurring in three phases with five distinct sub-phases (1, 2A, 2B, 2C, and 3). This report focuses on Phase 1 activities. During Phase 1, critical technical and logistical tasks necessary to demonstrate the viability of the Fallon FORGE Project site were completed and the commitment and capability of the Fallon FORGE team to execute FORGE was demonstrated. As part of Phase 1, the Fallon FORGE Team provided an assessment of available relevant data and integrated these geologic and geophysical data to develop a conceptual 3-D geologic model of the proposed test location. Additionally, the team prepared relevant operational plans for full FORGE implementation, provided relevant site data to the science and engineering community, engaged in outreach and communications with interested stakeholders, and performed a review of the environmental and permitting activities needed to allow FORGE to progress through Phase 3. The results of these activities are provided as Appendices to this report. The Fallon FORGE Team is diverse, with deep roots in geothermal science and engineering. The institutions and key personnel that comprise the Fallon FORGE Team provide a breadth of geoscience and geoengineering capabilities, a strong and productive history in geothermal research and applications, and the capability and experience to manage projects with the complexity anticipated for FORGE. Fallon FORGE Team members include the U.S. Navy, Ormat Nevada Inc., Sandia National Laboratories (SNL), Lawrence Berkeley National Laboratory (LBNL), the United States Geological Survey (USGS), the University of Nevada, Reno (UNR), GeothermEx/Schlumberger (GeothelinEx), and Itasca Consulting Group (Itasca). The site owners (through direct land ownership or via applicable permits)—the U.S. Navy and Ormat Nevada Inc.—are deeply committed to expanding the development of geothermal resources and are fully supportive of FORGE operations taking place on their lands.

15 GEOTHERMAL ENERGY↗
DOE OSTI2025

A Data-Agnostic, Continuous Machine Learning Framework for Application in High Energy Physics and Beyond: Phase 1 Final Scientific/Technical Report

This Phase 1 effort has focused on the development of continual learning frameworks for use in machine learning, specifically in the applied context of High Energy Physics (HEP). Machine learning (ML) is a transformative technology by which computers, typically through the use of neural networks, are able to perform tasks with proficiency that rivals or surpasses that of human users. Model Degradation & Catastrophic Forgetting are two undesired phenomena which can occur in ML where the performance of a model degrades when either deployed on novel data streams, or trained on novel data which are sufficiently different than the data the models were initially trained on. A natural example where these sorts of effects can be observed is in the performance of detectors in harsh environments, where the detector signature may change over the lifetime of the detector as it ages and deteriorates — precisely what occurs in the experiments conducted in HEP. Real world HEP data is therefore an excellent test-ground and use-case for Continual Learning paradigms, which are techniques used in ML to counteract these problems. Ensemble learning is one such technique, where multiple smaller models are trained on subsets of the overall data and are ensembled together during inference. The intuition behind this technique is that, although there are shifts in the distributions which govern the incoming data streams, these shifts are not expected to be homogeneous or global. If a sufficient diversity in solutions within the various sub-models has been achieved, then at least one sub-model is expected to retain its performance within the overall ensemble. One further strength of this approach is that the architectures of the various models do not need to be identical, and in fact even different modalities of data can naturally be combined in this way. This work focused on applying ensemble learning techniques to derive results using two main datasets, anomaly detection in HEP data & time-series forecasting in semiconductor manufacturing data. Semiconductor manufacturing involves data with surprising similarity to that of HEP (e.g. wafer maps look very similar to digi-occupancy maps) and Cerium Lab’s prominence within the semiconductor industry makes semiconductor manufacturing a natural opportunity for commercialization of this work. Our efforts have led to two strong results. The first is that we evaluated the proposed ensembling techniques using previously proposed machine learning architectures for use in anomaly detection, namely AutoEncoder based models and their derivatives. We also developed new architectures which have not been evaluated in this context before. In fact, this work marks the first use of Vision Transformers for anomaly detection in HEP. Second, we demonstrated that ensemble learning significantly improves model performance in scenarios prone to degradation, validating its effectiveness across both HEP and semiconductor datasets. These results further support ensemble learning as a powerful strategy for mitigating catastrophic forgetting and maintaining robust performance in evolving data environments.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2020

Phase 1 NuScale SMR FOAK Nuclear Demonstration Readiness Project (Final Scientific/Technical Report)

The overarching objective of the Phase 1 NuScale SMR First-of-a-Kind (FOAK) Nuclear Demonstration Readiness Project was to enhance competitiveness of the U.S. nuclear industry by enabling timely deployment of the NuScale small modular reactor (SMR). The scope of this Phase 1 project continued to advance the licensing and design maturity, particularly in those areas related to supporting customer readiness, supply chain integration, cost competitiveness, and cost confidence. This investment provided by the Government has accelerated development of these designs and technologies so that the existing domestic fleet of nuclear power plants remains viable and the most mature in the nuclear industry. The intent is to have the new, advanced U.S. designs be deployed as early 2026, and be globally competitive. As a part of the First-of-a-Kind Nuclear Demonstration Readiness Project, NuScale has been developing an advanced reactor design, leading the path for other development projects or complex technology advancements for existing plants that have significant technical and licensing risk. The NuScale Power team (NuScale) is advancing licensing, engineering, supply chain development, testing, and other required activities to enhance the innovation and competitiveness of the U.S. nuclear industry by enabling timely deployment of the NuScale SMR. Specifically, NuScale is performing the following activities in Phase 1. Fully supporting the NRC review of the NuScale DCA to ensure approval of a final safety evaluation report by the end of 2020. Improving plant cost confidence and cost competitiveness through design and supply chain advancement, incorporation of constructability best practices, and margin recovery to increase plant power output. Accelerating design maturity, technology development, and operational program readiness to support a customer commitment for plant deployment. The Department of Energy (DOE) Office of Scientific and Technical Information (OSTI), a unit of the Office of Science, fulfills agency-wide responsibilities to collect, preserve, and disseminate both unclassified and classified scientific and technical information (STI) emanating from DOE-funded research and development (R&D) activities at DOE national laboratories and facilities and at universities and other institutions nationwide. This scientific and technical report provides summaries of the analyses and research that was performed by NuScale under this project that achieves the objective of disseminating information to the nuclear industry to ensure the innovations realized are shared for the benefit of the industry at large.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2024

Ultra-high Q cavity-based search for the Dark Photon: new exclusion limit from Dark SRF phase 1 and step forward for phase 2

We present here the first results of Dark SRF, a light-shining-through-wall (LSW) experiment that leverages ultra-high quality factor superconducting radio frequency (SRF) cavities to search for dark photons. The use of Nb SRF cavities combined with a strict calibration and measurement protocol increased sensitivity to dark photons by several orders of magnitude compared to other LSW experiments, as demonstrated by our new limit that excluded a broad range of previously unstudied dark photon mass and mixing angle.In addition to the results of the search conducted in liquid helium using 1.3GHz SRF cavities, we also present the first steps of the second phase of the experiment, which will take place in a dilution refrigerator using 2.6GHz SRF cavities. These experiments are part of a wider effort of the Superconducting Quantum Materials and Systems (SQMS) Center to employ ultra-high Q SRF cavities to search for Beyond the SM particles and wavelike dark matter.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2020

Reduced Complexity Model Intercomparison Project Phase 1: introduction and evaluation of global-mean temperature response

Reduced-complexity climate models (RCMs) are critical in the policy and decision making space, and are directly used within multiple Intergovernmental Panel on Climate Change (IPCC) reports to complement the results of more comprehensive Earth system models. To date, evaluation of RCMs has been limited to a few independent studies. Here we introduce a systematic evaluation of RCMs in the form of the Reduced Complexity Model Intercomparison Project (RCMIP). We expect RCMIP will extend over multiple phases, with Phase 1 being the first. In Phase 1, we focus on the RCMs' global-mean temperature responses, comparing them to observations, exploring the extent to which they emulate more complex models and considering how the relationship between temperature and cumulative emissions of CO2 varies across the RCMs. Our work uses experiments which mirror those found in the Coupled Model Intercomparison Project (CMIP), which focuses on complex Earth system and atmosphere–ocean general circulation models. Using both scenario-based and idealised experiments, we examine RCMs' global-mean temperature response under a range of forcings. We find that the RCMs can all reproduce the approximately 1°C of warming since pre-industrial times, with varying representations of natural variability, volcanic eruptions and aerosols. We also find that RCMs can emulate the global-mean temperature response of CMIP models to within a root-mean-square error of 0.2°C over a range of experiments. Furthermore, we find that, for the Representative Concentration Pathway (RCP) and Shared Socioeconomic Pathway (SSP)-based scenario pairs that share the same IPCC Fifth Assessment Report (AR5)-consistent stratospheric-adjusted radiative forcing, the RCMs indicate higher effective radiative forcings for the SSP-based scenarios and correspondingly higher temperatures when run with the same climate settings. In our idealised setup of RCMs with a climate sensitivity of 3°C, the difference for the ssp585–rcp85 pair by 2100 is around 0.23°C(±0.12°C) due to a difference in effective radiative forcings between the two scenarios. Phase 1 demonstrates the utility of RCMIP's open-source infrastructure, paving the way for further phases of RCMIP to build on the research presented here and deepen our understanding of RCMs.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2016

Simultaneous Integrated Boost Volumetric Modulated Arc Therapy in the Postoperative Treatment of High-Risk to Intermediate-Risk Endometrial Cancer: Results of ADA II Phase 1-2 Trial

Purpose: A prospective phase 1-2 clinical trial aimed at determining the recommended postoperative dose of simultaneous integrated boost volumetric modulated arc therapy (SIB-VMAT) in a large series of patients with high-risk and intermediate-risk endometrial cancer (HIR-EC) is presented. The study also evaluated the association between rate and severity of toxicity and comorbidities and the clinical outcomes. Methods and Materials: Two SIB-VMAT dose levels were investigated for boost to the vaginal vault, whereas the pelvic lymph nodes were always treated with 45 Gy. The first cohort received a SIB-VMAT dose of 55 Gy in 25 consecutive 2.2-Gy fractions, and the subsequent cohort received higher doses (60 Gy in 2.4-Gy fractions). Results: Seventy consecutive HIR-EC patients, roughly half of whom were obese (47.1%) or overweight (37.1%), with Charlson Age-Comorbidity Index >2 (48.5%), were enrolled. Thirty-one patients (44.3%) were administered adjuvant chemotherapy before starting radiation therapy. All patients (n=35 per dose level) completed irradiation without any dose-limiting toxicity. Proctitis (any grade) was associated with radiation therapy dose (P=.001); not so enterocolitis. Grade ≥2 gastrointestinal (GI) and genitourinary (GU) toxicity were recorded in 17 (24.3%) and 14 patients (20.0%), respectively, and were not associated with radiation dose. As for late toxicity, none of patients experienced late grade ≥3 GI or grade ≥2 GU toxicity. The 3-year late grade ≥2 GI and GU toxicity–free survival were 92.8% and 100%, respectively, with no difference between the 2 dose levels. With a median follow-up period of 25 months (range, 4-60 months), relapse/progression of disease was observed in 10 of 70 patients (14.2%). The 3-year cumulative incidence of recurrence was 1.5% (95% confidence interval (CI): 0.2-10.7), whereas the 3-year disease-free survival was 81.3% (95% CI: 65.0-90.0). Conclusions: This clinical study showed the feasibility of this technique and its good profile in terms of acute and late toxicity at the recommended doses even in aged and frail patients.

62 RADIOLOGY AND NUCLEAR MEDICINE↗