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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 199 records · Page 11
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Dynamic and Responsive Distributed Energy Resource Education Solutions for Building, Fire, and Safety Department Officials (Final Technical Report)

From April 2021 through March 2024, the Interstate Renewable Energy Council (IREC) led a collaborative project to develop a free online clearinghouse of educational resources about solar photovoltaics (PV), energy storage systems (ESS), electric vehicle supply equipment (EVSE), and grid-interactive efficient building (GEB) technologies. Two websites—the Clean Energy Clearinghouse and CleanEnergyTraining.org—housed over 70 educational resources. Over the course of the three-year project, 154,272 unique visitors accessed the learning materials. Learner feedback was overwhelmingly positive. Even through the end of the project, there was sustained demand for education and communication. A primary innovation of the project was to drive multiple complementary audiences to the same place. Building owners, designers, installation contractors and developers, authorities having jurisdiction (AHJs), and fire service personnel all benefit from a shared understanding of clean energy technologies, including safety and code-related requirements. When considering the impact on the target audience, the project team worked with partners and advisors to inform resource creation and delivery in such a way as to address key motivational factors of the target audience and compel each user to seek additional information on the topic and return to the Clean Energy Clearinghouse website as their central location for more information. Resources were intentionally developed to be concise—five to 15 minutes—and accessible, meaning not overly technical. Providing basic information demystified the technologies and invited the professional to explore additional learning opportunities. Awardee and partner collaboration was key to project success. IREC facilitated collaboration among the other Topic 2 awardees, Southface and New Buildings Institute (NBI). The three awardees shared relevant information gained through discovery and validation questionnaires that informed product development and reduced duplication of effort by coordinating the development of complementary, and not competing, educational resources. Inspired by this collaboration, IREC brought on additional partners even in the final year of the project. Five regional energy efficiency organizations were part of the project, which expanded the connection between efficiency and distributed energy resources. We also included resources on the Clearinghouse that were developed through other federally funded projects, such as the Buildings Energy Efficiency Frontiers & Innovation Technologies (BENEFIT) program. The website was developed with the learner in mind, and not solely the funding source. Feedback from stakeholders throughout the project, and especially in its final year, indicated the need for continued education and facilitated communication among stakeholders to further the safe and widespread adoption of clean energy.

14 SOLAR ENERGY↗
DOE OSTI2022

Communication systems and methods for authenticating data packets within network flow

A communication system includes a first quantum key distribution device and an intermediary device. The first quantum key distribution device is configured to be coupled to a second quantum key distribution device over a quantum channel and to generate a shared key with the second quantum key distribution device based on a quantum state transmitted along the quantum channel. The intermediary device is disposed along a communication pathway within a network between a sender device and a receiver device. The intermediary device is communicatively connected to the first quantum key distribution device and configured to utilize the shared key to authenticate one or more data packets communicated from the sender device along the communication pathway by examining the one or more data packets for a presence of an information pattern that is associated with the shared key.

Bush, Stephen Francis↗
DOE OSTI2024

Agent-based simulations of shared automated vehicle operations: reflecting travel-party size, season and day-of-week demand variations

Here, this paper explores the effects of day of week and season of year demand variations for shared rides, along with realistic travel party sizes, on shared autonomous vehicle (SAV) services across the Austin, Texas region. Using the agent-based POLARIS program, synthetic person-trips that reflect travel-party size (from one to four persons) and demand variations over days and months, as evident in the National Household Travel Survey data were simulated in each scenario over a 24 h travel day. Results show that realistic party sizes can bring considerable changes to SAV fleet performance, including up to 8.5% higher service rates (number of requests accepted within 15 min), 5 min shorter journey times (wait time + travel time), 28% higher vehicle occupancies on weekends, and roughly 4% lower empty fleet VMT. Weekend travel is most impacted by season of year, with weekday travel patterns looking more uniform (thanks to work and school trips). Various performance metrics for the Austin network, like total and empty VMT, change by up to 30% when considering realistic variations in party size and time of year. This paper underscores the value of recognizing day-to-day and month-to-month variations in travel demand, and the importance of agent-based model equations to reflect travel-party size. Such realism can help quantify SAV seat occupancies more accurately, highlighting the importance of shared mobility. However, it also creates demand and supply issues for operators that now need more information on party size to manage dynamic ride-sharing, or those that may wish to shift their fleet vehicles to other regions for special events to protect profits while offering reasonable wait times to customers throughout the year.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2024

OpenFacadeControl: enabling integration of automated facades with other building systems

Automated facades are, for the most part, still considered as separate from other building systems throughout the design, installation, commissioning, operation, and maintenance cycle. This takes place despite the fact that their energy and comfort performance are deeply interlinked with the operation of lighting and HVAC systems. Over the last two decades, research has shown that there are significant advantages from operating facades as an integrated system with the rest of the building. Nevertheless, significant barriers prevent this type of integration becoming more common. One of them is the lack of a platform that is inexpensive to implement and that easily allows the practical implementation of integrated control algorithms across fenestration and other building systems, using a variety of communications protocols. This is particularly challenging when automated facades are installed in existing buildings, where interaction with legacy building systems that were installed over the past lifetime of the building can require a high degree of interoperability. OpenFacadeControl (OFC) is an open-source controls framework aimed at unified control of facades and other building systems, including the sharing of third-party sensor information. Through leveraging the Volttron controls platform, it allows the integration of systems and sensors that are manufactured by different companies and that use different communications protocols into an ensemble that functions as a single system. OFC is designed to enable integrated control algorithms of varying degrees of complexity, ranging from simple, heuristic controls to more sophisticated approaches like model-predictive control. Use of a research version to test advanced lighting and shading strategies in a full-scale experimental testbed has demonstrated the ease of deploying advanced control solutions using OpenFacadeControl. This paper presents the structure of OpenFacadeControl and a demonstration case showing the use of OFC in laboratory tests of advanced lighting and fenestration controls that coordinated motorized shades communicating via the BACnet building communications standard and lights communicating via internet-protocol-based application programming interface (API), based on the readings of a shared light level sensor communicating via a different API.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2022

Accelerating shared file checkpoint with local burst buffers

A data management system and method for accelerating shared file checkpointing. Written application data is aggregated in an application data file created in a local burst buffer memory at a compute node, and an associated data mapping built index to maintain information related to the offsets into a shared file at which segments of the application data is to be stored in a parallel file system, and where in the buffer those segments are located. The node asynchronously transfers a data file containing the application data and the associated data mapping index to a file server for shared file storage. The data management system and method further accelerates shared file checkpointing in which a shared file, together with a map file that specifies how the shared file is to be distributed, is asynchronously transferred to local burst buffer memories at the nodes to accelerate reading of the shared file.

Gooding, Thomas↗
DOE OSTI2025

Winds of fortune? Understanding the geographic, sociodemographic, and temporal distribution of benefit mechanisms from land-based wind projects in the United States

Despite decades of research on factors shaping local responses to wind development, there is relatively little known about benefit mechanisms (e.g., agreements, funds, donations) used by developers in the U.S. land-based wind sector. To address this gap, we collected benefit mechanism data across all current utility-scale land-based wind projects installed between 1982 and 2024 (n = 1047), finding that just under one-third of projects had a benefit mechanism attached to them. We find the use of benefit mechanisms has become more common over time, is associated with larger projects, and varies by region. In terms of host community characteristics, the use of benefit mechanisms is associated with characteristics like higher education level, higher percent white, higher percent Republican, higher decision-making capacity, lower unemployment rate, and higher poverty rate. Building on a theoretical framework of purposes, we discuss what these findings could suggest about the motivations driving developers' use of these mechanisms, such as increasing local acceptance of a wind project or supporting distributive fairness. This first-of-its-kind study builds a comprehensive understanding of how benefit mechanisms have been used in the U.S. wind industry throughout its history, which can inform future approaches to benefit-sharing across sectors.

17 WIND ENERGY↗
DOE OSTI2026

Challenges and Vision for Standardization of Biopolymer Data Sets for Machine Learning

Machine learning (ML) is transforming materials research, yet potential for biopolymer discovery remains constrained by fragmented data and nonstandardized reporting. Biopolymers differ significantly from synthetic polymers, requiring specialized approaches to represent their biosynthetic origins, hierarchical structures, and application-specific metrics. In this Perspective, we identify three core challenges limiting biopolymer representation: information encoding, data quality, and data sharing. We describe the most pressing issues and propose commensurate approaches to address each key challenge. Recommendations include the design and adoption of biopolymer-specific fingerprinting and representation frameworks, development of hybrid human-large language model (LLM) data extraction strategies, and expanding Findable, Accessible, Interoperable, Reusable (FAIR)-compliant repositories. We propose a robust foundation to define interoperable, high-quality data sets that capture the full context of biopolymer materials. Standardized metadata, shared ontologies, and community-driven infrastructure would enable scalable, reproducible workflows and accelerate the ML-driven development of biopolymers.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Preparing for the next pandemic via transfer learning from existing diseases with hierarchical multi-modal BERT: a study on COVID-19 outcome prediction

Abstract Developing prediction models for emerging infectious diseases from relatively small numbers of cases is a critical need for improving pandemic preparedness. Using COVID-19 as an exemplar, we propose a transfer learning methodology for developing predictive models from multi-modal electronic healthcare records by leveraging information from more prevalent diseases with shared clinical characteristics. Our novel hierarchical, multi-modal model ( $${\textsc {TransMED}}$$ T R A N S MED ) integrates baseline risk factors from the natural language processing of clinical notes at admission, time-series measurements of biomarkers obtained from laboratory tests, and discrete diagnostic, procedure and drug codes. We demonstrate the alignment of $${\textsc {TransMED}}$$ T R A N S MED ’s predictions with well-established clinical knowledge about COVID-19 through univariate and multivariate risk factor driven sub-cohort analysis. $${\textsc {TransMED}}$$ T R A N S MED ’s superior performance over state-of-the-art methods shows that leveraging patient data across modalities and transferring prior knowledge from similar disorders is critical for accurate prediction of patient outcomes, and this approach may serve as an important tool in the early response to future pandemics.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

Self-Security for Grid-Interactive Smart Inverters Using Steady-State Reference Model

Smart inverters exchange information with other devices through a shared communication link, making the inverters more prone to receive harmful commands from external parties. This erroneous data can be received due to an anomaly in the system, such as a device fault, unintentional utility operator action, or a cyber-attack. In this paper, a device-level self-security strategy is implemented using reference models for a grid-interactive inverter to examine the incoming power setpoints, detect the anomalies, and protect the system accordingly. The PQ setpoints received from the utility supervisory controller are autonomously examined using the inverter’s normal and stable operating regions before engaging the setpoints to the inverter’s local controller. Grid parameters are estimated in real-time during the examination process. The efficacy of the self-security algorithm is tested using a three-phase 3-kVA SiC-MOSFET inverter and a 12-kW NHR 9410 regenerative grid emulator. The results verify that the proposed method can detect harmful PQ setpoints that can cause abnormal or unstable inverter operation.

Gursoy, Mehmetcan↗
DOE OSTI2020

Using Machine Learning to Predict Future Temperature Outputs in Geothermal Systems

Optimizing the power output, and economic value, of geothermal power plants over decades of operation is a major challenge in renewable energy. Optimizing the output requires the ability to predict the mass flow rates and the output temperatures of production wells based on the inputs of injection wells, as well as the time history of the system. Machine Learning (ML) that incorporates the known physics of geothermal systems is one possible solution to this challenge. In this work, we explore the ability of ML algorithms to predict future temperature outputs based on historical data. Considering the challenges with obtaining an empirical dataset from field data that is large enough to enable reliable ML, we propose an alternate approach: developing a high-fidelity reservoir model and using computational resources to build a dataset that enables ML. As a first step towards achieving this goal, we present preliminary results from applying ML to predict the temperature timeseries of simple modeled geothermal systems. We describe the application of relevant state-of-the-art ML approaches, such as the Long Short-Term Memory (LSTM) networks and Convolutional Neural Networks (CNN), to extract temporal structures in the model data. We assess the accuracy of the forecasts we obtain, compare the selected approaches, and share the lessons learned that would inform the process of training and utilizing ML algorithms for larger and more complex geothermal systems.

GEOTHERMAL ENERGY↗
DOE OSTI2020

Panel Session 115: Collaboration Across Borders to Deliver Cleanup and Decommissioning Challenges

This panel focused on where multiple countries have collaborated to solve difficult remediation and cleanup challenges through either formal or informal means. The focus was to share real examples of where collaboration has accelerated cleanup saving time and money. This could be through policy or process improvements, technology transfer or sharing R and D, or other means of collaborative efforts. Panelists with presentations: Canada-AECL Collaboration Across Borders (Richard Sexton, Alastair MacDonald); Collaboration Across Borders to Deliver Cleanup and Decommissioning Challenges (Anthony Banford); IAEA Perspective on International Collaboration in D and ER (Horst Monken Fernandes); How, Why and Benefits of Collaboration (Kurt Gerdes)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2026

Strategic Energy Plan: Playa de Ponce, Ponce, Puerto Rico

Un Nuevo Amanecer Inc. (UNA), a community-based NGO (501C(3)), sought technical assistance through the U.S. Department of Energy's (DOE's) Energy Technology Innovation Partnership Project (ETIPP) to develop a strategic energy plan (SEP) for the community of Playa de Ponce on the south coast of Puerto Rico. A SEP helps communities identify energy goals and priority projects, and outline strategies and actions to build a shared path toward their energy vision. The primary goal of this SEP is to collaboratively explore pathways for the community's energy future. Researchers from the National Laboratory of the Rockies (NLR) engaged with the community for a period of seven months and facilitated a series of in-person community engagement workshops along with ETIPP regional partner Puerto Rico Hispanic Federation, UNA, and community leaders. The SEP workshops were held twice, March 18-20 and June 24-26, 2025. Through facilitated discussions, the community worked together to define and articulate a clear vision for its short-, medium-, and long-term energy goals. The workshops played a key role in identifying the specific strategies and priority projects that would best suit the needs of the community. The discussions outlined the community's energy aspirations, establishing a shared vision, setting goals, and outlining the priority actions needed to bring them to fruition. During the workshops, the community shared some of the most pressing energy challenges that they face on a regular basis, such as high energy costs that disproportionately impact an aging population and unreliable electricity during extreme weather events that result in frequent power outages. These issues have also exacerbated risks to public health and safety of the community. In response, UNA requested technical assistance through ETIPP to inform the development of a SEP tailored to Playa de Ponce to support its energy vision. This document explores four community-driven energy strategies aligned with that vision. Figure 1 shows the strategies outlined in this plan, which are categorized into three focus areas as identified by the community: energy reliability; safety and security; and stakeholder participation, education, and capacity building. This document serves as a shared roadmap for developing and implementing energy solutions that meet the needs of Playa de Ponce. It is intended to serve as a public resource for the community, UNA, and local authorities - providing tools, information and a shared foundation to inform future implementation efforts. This plan is intended to complement ongoing planning frameworks at the municipal, regional, and island-wide levels. As a living document, this SEP can evolve alongside Playa de Ponce's changing energy goals, while offering a framework to help them realize their energy vision.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2026

Travel Decision Survey - San Francisco - 2012

On behalf of the San Francisco Municipal Transportation Agency (SFMTA), Corey, Canapary & Galanis undertook a Travel Decision Survey within the City and County of San Francisco, as well the eight surrounding Bay Area counties of Alameda, Contra Costa, San Mateo, Marin, Santa Clara, Napa, Sonoma, and Solano. The primary goals of this study were to accurately assess mode share for trips within San Francisco (including trips to or from San Francisco, but excluding through trips) among city residents and residents of other Bay Area counties; provide additional trip details, including trip purpose information for each trip in the mode-share question series; and use the mode-share percentages collected on this survey in conjunction with total trip estimates provided by SFMTA to project the number of trips by mode on an average day in San Francisco.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2020

Soluble limit and criticality of fermions in $\mathbb Z_2$ gauge theories

Quantum information theory and strongly correlated electron systems share a common theme of macroscopic quantum entanglement. In both topological error correction codes and theories of quantum materials (spin liquid, heavy fermion and high-$T_c$ systems), entanglement is implemented by means of an emergent gauge symmetry. Inspired by these connections, in this paper we introduce a simple model for fermions moving in the deconfined phase of a $\mathbb Z_2$ gauge theory by coupling Kitaev's toric code to mobile fermions. This permits us to exactly solve the ground state of this system and map out its phase diagram. Reversing the sign of the plaquette term in the toric code permits us to tune the ground state between an orthogonal metal and an orthogonal semimetal in which gapless quasiparticles survive despite a gap in the spectrum of original fermions. The small-to-large Fermi surface transition between these two states occurs in a stepwise fashion with multiple intermediate phases. By using a diagrammatic technique, we are able to explore physics beyond the integrable point to examine various instabilities of the deconfined phase and to derive the critical theory at the transition between deconfined and confined phases. We outline how the fermionic toric code can be implemented as a quantum circuit, thus providing an important link between quantum materials and quantum information theory.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2026

Public water supply infrastructure extensification and diversification in surface waters is insufficient to meet future demands in Texas

The data were developed to evaluate the capacity of existing and potential new surface water supply infrastructure to meet projected public water demands across districts in Texas under multiple future socioeconomic and climate scenarios. The database integrates hydrologic, water quality, infrastructure, energy, cost, demographic, and demand-projection information for candidate surface water supply locations. Candidate sites include stream reaches, waterbodies, reservoir surplus locations, and potential new reservoir sites. Water availability is characterized using historical and projected flow conditions, while site suitability is evaluated using five indicators: Water Availability Index (WAI), Water Quality Index (WQI), Energy Requirement Index (ERI), Water Treatment Cost (WTC), and Water Infrastructure Cost (WIC). The datasets include statewide candidate-site information, district-level demand projections under Shared Socioeconomic Pathways (SSPs), runoff-based allocation constraints, climate-stress metrics, and optimization outputs evaluating alternative infrastructure planning strategies. Optimization results compare Business-as-Usual (BAU) and All Surface Water (AllSW) demand-management approaches under both scaled and fixed cost-cap strategies. Associated validation datasets provide district-level feasibility assessments, infrastructure selection outcomes, cost-cap utilization, demand satisfaction metrics, and constraint diagnostics. Additional datasets quantify projected changes in storage and flow conditions as well as water availability stress for both existing and newly selected intake locations under the SSP5 scenario for mid-century and late-century climate conditions. Together, these datasets support assessment of the extent to which surface-water infrastructure expansion and diversification strategies can satisfy future public water demands while accounting for hydrologic, economic, and planning constraints across Texas. Dataset(s) Description Dataset_preoptimization.xlsx Comprehensive pre-optimization dataset containing candidate water-supply sites and associated hydrologic, water-quality, infrastructure, climate, demographic, runoff, and demand-projection variables used as inputs to the optimization analyses. Includes variable descriptions and the full statewide candidate-site database. District_level_site_selection.zip - Compressed archive containing all SSP-specific district-level optimization result files MESIO_ssp1_results.xlsx District-level site selection results for SSP1 (MESIO). Includes variable descriptions, BAU and AllSW site-selection results under scaled and fixed cost strategies, and district-level validation diagnostics. MESID_ssp2_results.xlsx District-level site selection results for SSP2 (MESID). Includes variable descriptions, BAU and AllSW site-selection results under scaled and fixed cost strategies, and district-level validation diagnostics. LCMRD_ssp3_results.xlsx District-level site selection results for SSP3 (LCMRD). Includes variable descriptions, BAU and AllSW site-selection results under scaled and fixed cost strategies, and district-level validation diagnostics. IRDev-Low_ssp4l_results.xlsx District-level site selection results for SSP4-Low (IRDev-Low). Includes variable descriptions, BAU and AllSW site-selection results under scaled and fixed cost strategies, and district-level validation diagnostics. IRDev-High_ssp4h_results.xlsx District-level site selection results for SSP4-High (IRDev-High). Includes variable descriptions, BAU and AllSW site-selection results under scaled and fixed cost strategies, and district-level validation diagnostics. RSIM_ssp5_results.xlsx District-level site selection results for SSP5 (RSIM). Includes variable descriptions, BAU and AllSW site-selection results under scaled and fixed cost strategies, and district-level validation diagnostics. tx_hydrological_stress.xlsx Hydrological stress dataset for existing and newly selected intake locations. Includes projected mid-century and late-century changes, gain/loss classifications, planning strategy information, and accompanying variable descriptions. Also includes water-stress metrics derived from historical and projected low-flow conditions.

Okoye, Perpetua I. (ORCID:0000000215545033)↗
DOE OSTI2024

Holographic tensor networks with bulk gauge symmetries

Abstract Tensor networks are useful toy models for understanding the structure of entanglement in holographic states and reconstruction of bulk operators within the entanglement wedge. They are, however, constrained to only prepare so-called “fixed-area states” with flat entanglement spectra, limiting their utility in understanding general features of holographic entanglement. Here, we overcome this limitation by constructing a variant of random tensor networks that enjoys bulk gauge symmetries. Our model includes a gauge theory on a general graph, whose gauge-invariant states are fed into a random tensor network. We show that the model satisfies the quantum-corrected Ryu-Takayanagi formula with a nontrivial area operator living in the center of a gauge-invariant algebra. We also demonstrate nontrivial,n-dependent contributions to the Rényi entropy and Rényi mutual information from this area operator, a feature shared by general holographic states.

Physics↗
DOE OSTI2021

Genome-wide toxicogenomic study of the lanthanides sheds light on the selective toxicity mechanisms associated with critical materials

Significance The growing use of lanthanides in various industries has increased the potential for human exposure to large concentrations of these heavy metals throughout the life cycle of new technologies, requiring more detailed investigations into their toxicological properties. The eukaryote model organism Saccharomyces cerevisiae is ideal to apply functional toxicogenomics tools at the system level and probe fundamental cellular functions disrupted by rare-earth metals. A comprehensive mechanistic assay was conducted to evaluate toxicity across the entire lanthanide series and provide information about which toxicological mechanisms may be shared by the different metals. We identified distinct characteristic behaviors between early and middle/late lanthanides, highlighting the powerful discrimination capabilities of natural systems and pointing to detailed mechanistic pathways associated with lanthanide exposure.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

Interconnected Risks in Electricity Systems: Understanding Research Challenges, Needs, and Partnerships

The U.S. federal government has a potential role in mitigating the most poorly addressed risks across electricity markets and interdependent systems. Electricity system risks stem from extreme acute shocks (e.g., cyberattacks, extreme weather, and supply chain disruptions) and chronic stressors (e.g., global economic competition, uncertainties surrounding emerging technologies, climate change, and related conflicts). These acute shocks and chronic stressors can result in dire consequences for society, underscoring the need for better information for decision makers in both public and private sectors. Best practices and a shared understanding of risk management and risk quantification must be rapidly developed and disseminated. Informed by a quantitative treatment of risk to electrical infrastructure and interdependent systems, decision makers can more prudently and efficiently prioritize mitigation initiatives to maximize benefits to government, businesses, and the public.

24 POWER TRANSMISSION AND DISTRIBUTION↗