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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 379 records · Page 21
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Isotope dependence of the type I ELMy H-mode pedestal in JET-ILW hydrogen and deuterium plasmas

The pedestal structure, edge transport and linear MHD stability have been analyzed in a series of JET with the ITER-like wall hydrogen (H) and deuterium (D) type I ELMy H-mode plasmas. The pedestal pressure is typically higher in D than in H at the same input power and gas rate, with the difference mainly due to lower density in H than in D (Maggi et al (JET Contributors) 2018 Plasma Phys. Control. Fusion 60 014045). A power balance analysis of the pedestal has shown that higher inter-ELM separatrix loss power is required in H than in D to maintain a similar pedestal top pressure. This is qualitatively consistent with a set of interpretative EDGE2D-EIRENE simulations for H and D plasmas, showing that higher edge particle and heat transport coefficients are needed in H than in D to match the experimental profiles. It has also been concluded that the difference in neutral penetration between H and D leads only to minor changes in the upstream density profiles and with trends opposite to experimental observations. This implies that neutral penetration has a minor role in setting the difference between H and D pedestals, but higher ELM and/or inter-ELM transport are likely to be the main players. The interpretative EDGE2D-EIRENE simulations, with simultaneous upstream and outer divertor target profile constraints, have indicated higher separatrix electron temperature in H than in D for a pair of discharges at low fueling gas rate and similar stored energy (which required higher input power in H than in D at the same gas rate). The isotope dependence of linear MHD pedestal stability has been found to be small, but if a higher separatrix temperature is considered in H than in D, this could lead to destabilization of peeling-ballooning modes and shrinking of the stability boundary, qualitatively consistent with the reduced pedestal confinement in H.

08 HYDROGEN↗
DOE OSTI2020

Using Residential and Office Building Archetypes for Energy Efficiency Building Solutions in an Urban Scale: A China Case Study

Building energy consumption accounts for 36% of the overall energy end use worldwide and is growing rapidly as developing countries continue to urbanize. Understanding the energy use at urban scale will lay the foundation for identification of energy efficiency opportunities to be deployed at speed. China has almost half of global new constructions and plays an important role in building suitability. However, an open source national building energy consumption database is not available in China. To provide data support for building energy consumptions, this paper used a simulation method to develop an urban building energy consumption database for a pilot city in Wuhan, China. First, residential, small, and large office building archetype energy models were created in EnergyPlus to represent typical building energy consumption in Wuhan. The baseline reference model simulation results were further validated using survey data from the literature. Second, stochastic simulations were conducted to consider different design parameters and occupants’ energy usage intensity scenarios, such as thermal properties of the building envelope, lighting power density, equipment power density, HVAC (heating, ventilation and air conditioning) schedule, etc. A building energy consumption database was generated for typical building archetypes. Third, data-driven regression analysis was conducted to support quick building energy consumption prediction using key high- level building information inputs. Finally, a web-based urban energy platform and an interface were developed to support further third-party application development. The research is expected to provide fast energy efficiency building design solutions for urban planning, new constructions as well as building retrofits.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2026

AI-Based Analytics and Energy Modeling Framework for Characterizing Urban Energy Systems

Developing location-specific district energy models is essential for understanding energy patterns and supporting efficient management and planning decisions. However, accurately characterizing these models remains challenging due to gaps in building characteristics and labor-intensive traditional modeling workflows. To address these challenges, we develop an AI-based framework that integrates top-down and bottom-up building energy data to automate urban energy model characterization. The framework trains multimodal deep learning models using heterogeneous ResStockTM datasets to infer missing building characteristics from varying levels of known information and generate simulation-ready inputs for district-scale energy modeling. It also employs a conditioning-based injection approach to generate ”what-if” scenarios, enabling users to explore retrofit, efficiency, and technology-upgrade pathways. Integrated within URBANoptTM, a bottom-up district energy modeling platform for simulating co-located buildings, the framework infers detailed building-level inputs required for bottom-up simulations. Both localized and generalized AI models are developed to learn relationships across categorical, numerical, and time-series data, enabling reconstruction of missing attributes and generation of targeted upgrade scenarios. We demonstrate this methodology on a residential neighborhood in Baltimore, MD, assessing internal consistency against ResStock reference data and URBANopt simulation, and comparing selected attributes against real-world building characteristics. Results show strong overall predictive accuracy in data completion and scenario generation, with localized and generalized models offering complementary trade-offs between precision and scalability. Overall, our automated framework streamlines energy modeling and provides a reliable framework for urban building energy characterization.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2024

Masked Particle Modeling on Sets: Towards Self-Supervised High Energy Physics Foundation Models

Abstract We propose masked particle modeling (MPM) as a self-supervised method for learning generic, transferable, and reusable representations on unordered sets of inputs for use in high energy physics (HEP) scientific data. This work provides a novel scheme to perform masked modeling based pre-training to learn permutation invariant functions on sets. More generally, this work provides a step towards building large foundation models for HEP that can be generically pre-trained with self-supervised learning and later fine-tuned for a variety of down-stream tasks. In MPM, particles in a set are masked and the training objective is to recover their identity, as defined by a discretized token representation of a pre-trained vector quantized variational autoencoder. We study the efficacy of the method in samples of high energy jets at collider physics experiments, including studies on the impact of discretization, permutation invariance, and ordering. We also study the fine-tuning capability of the model, showing that it can be adapted to tasks such as supervised and weakly supervised jet classification, and that the model can transfer efficiently with small fine-tuning data sets to new classes and new data domains.

Heinrich, Lukas (ORCID:0000000240487584)↗
DOE OSTI2022

Scalable membrane-less microbial electrolysis cell with multiple compact electrode assemblies for high performance hydrogen production

Bioelectrochemical hydrogen production via microbial electrolysis cells (MECs) is a promising method for sustainable energy production and decarbonization of energy systems. However, the application of MECs is limited by the electrochemical performance, scalability, and the cost associated with expensive materials. Here, in this study, a scalable MEC (500 mL) with novel compact electrode assemblies and high electrode surface area to volume ratio (160 m 2 /m 3 ) was designed and constructed. The use of membranes, precious metal catalyst, and current collectors with high costs was avoided. A high current density at the steady state of 49.5 ± 5.3 A/m 2 was achieved using acetate as the substrate with phosphate buffer under the applied voltage of 1.01 V. The corresponding volumetric current density was 3948 ± 422 A/m 3 . The compact electrode assembly design limited methane production rate to 3.9 ± 0.2 L/L/D, while achieving a hydrogen production rate of 33.7 ± 1.7 L/L/D. With the suppression of microbial hydrogen consumption, the hydrogen production rate was 39.8 ± 1.9 L/L/D, higher by almost one order of magnitude than those of MECs with scaling up attempts. The compact electrode configuration reduced internal resistance to 88.5 ± 4.4 Ω cm 2 . The energy efficiency based on input electricity was 146 ± 7 % to 189 ± 9 % within the applied voltage range of 0.71 to 1.05 V. The results in this study demonstrated successful scaling up of high performance small MECs and offered a new possible approach of scaling up MECs by stacking high-performance subunits, with no trade-offs on electrochemical performance.

08 HYDROGEN↗
DOE OSTI2020

Mechanistic Understanding and Rational Design of Quantum Dot/Mediator Interfaces for Efficient Photon Upconversion

The semiconductor-nanocrystal-sensitized, three-component upconversion system has made great strides over the past 5 years. The three components (i.e., triplet photosensitizer, mediator, and emitter) each play critical roles in determining the input and output photon energy and overall quantum efficiency (QE). The nanocrystal photosensitizer converts the absorbed photon into singlet excitons and then triplet excitons via intersystem crossing. The mediator accepts the triplet exciton via either direct Dexter-type triplet energy transfer (TET) or sequential charge transfer (CT) while extending the exciton lifetime. Through a second triplet energy-transfer step from the mediator to the emitter, the latter is populated in its lowest excited triplet state. Triplet–triplet annihilation (TTA) between two triplet emitters generates the emitter in its bright singlet state, which then emits the upconverted photon. Quantum dots (QD) have a tunable band gap, large extinction coefficient, and small singlet–triplet energy losses compared to metal–ligand charge-transfer complexes. This high triplet exciton yield makes QDs good candidates for photosensitizers. In terms of driving triplet energy transfer, the triplet energy of the mediator should be slightly lower than the triplet exciton energy of the QD sensitizer for a downhill energy landscape with minimal energy loss. The same energy cascade is also required for the transfer from the mediator to the emitter. Lastly, the triplet energy of the emitter must be slightly larger than one-half of its singlet energy to ensure that TTA is exothermic. Optimization of the sensitizer, mediator, and emitter will lead to an increase in the anti-Stokes shift and the total quantum efficiency. Evaluating each individual step’s efficiency and kinetics is necessary for the understanding of the limiting factors in existing systems.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Non-Hermitian Quantum Mechanics Approach for Extracting and Emulating Continuum Physics Based on Bound-State-like Calculations

Here, this Letter introduces a unified emulation framework for studying continuum physics in finite quantum systems. Using a reduced basis method, we construct powerful emulators for the inhomogeneous Schrödinger equation that operate in a combined parameter space of complex energy (𝐸) and other inputs (𝜽). Within the space, the emulators simultaneously perform analytical continuation in 𝐸—extracting continuum physics from numerically simpler bound-state-like calculations—and interpolate this entire process across 𝜽. This yields a small, non-Hermitian system whose properties (e.g., resonances and scattering observables) can be rapidly predicted for any 𝜽. Crucially, the complex-𝐸 emulation provides a pathway to compute continuum observables for complex systems where advanced bound-state methods exist but direct continuum calculations are yet to be developed, while the 𝜽 emulation enables rapid parameter-space exploration and can be adapted to accelerate other existing continuum calculations. Demonstrations with two- and three-body systems highlight the method’s effectiveness and suggest its connection to (near-)optimal rational approximation. This Letter presents the key results, with further details reserved for a companion paper.

ab initio calculations↗
DOE OSTI2025

EverBESS

SF-25-113 This software is a website for the EverBESS model. This model examines the cost and environmental impacts related to end-of-life management of battery energy storage systems. Users input their system's specifications and the model returns estimates for the costs of decommissioning, transporting, and recycling the system.

Elias, Jakob [Argonne National Laboratory (ANL), A↗
DOE OSTI2022

GIS-Based Graphical User Interface Tools for Analyzing Solar Thermal Desalination Systems & High-Potential Implementation

This project developed a user-friendly, open-source, software that enables a comparative evaluation of solar thermal desalination technology options and employs geospatial data layers to identify regions of high-potential for solar thermal desalination. This was accomplished by integrating solar models with desalination models and enhancing their utility by providing GIS-based data inputs. The developed Solar Energy Desalination Analysis Tool (SEDAT) enables techno-economical evaluation of desalination technologies and selection of regions with the highest potential for using solar energy to power desalination plants. It simplifies the planning, design, and valuation of solar thermal and solar hybrid desalination systems in the U.S. and worldwide. SEDAT uses Dash for integrating various layers of large volumes of GIS data with Python-based models of solar energy generation and desalination technologies. It derives time-series of energy generation and water production, with details of plant performance and suggestions for improving the solar-desalination coupling. It is a one of-a-kind tool of analysis representing a definitive advancement in the state-of-the-art. Of solar desalination modeling This report summarizes the various phases of the tool’s development, and presents examples of the results.

14 SOLAR ENERGY↗
DOE OSTI2023

Creation of Multiple Effect Evaporator and Combined Cycle Modelica Modules, and Optimization of Potable Water Generation from Saltwater Sources (Final Technical Report)

Modelica models for a Heat Recovery Steam Generator (HRSG) and Multiple Effect Evaporator have been developed. These models have been validated against results from literature and from an actual cogeneration system on the campus of NC State University. The models are capable of connecting to other components to create multi-input, multi-output energy systems with storage, also known as integrated energy systems. An existing 35 MW gas turbine model is connected to the HRSG model created for this project to produce 9 bar steam. The high pressure steam feeds a backpressure steam turbine from the library to generate additional electric power. 2 bar steam leaves the turbine to supply an 8 effect MEE to generate water for a community. As part of the effort, three research papers were submitted (two published in ANS Proceedings and one submitted to Applied Energy).

20 FOSSIL-FUELED POWER PLANTS↗
DOE OSTI2023

Energy Cane Cultivation

This unit process includes operations for cultivation of energy cane biomass including inputs of herbicide, fertilizer, and water, and associated emissions.

09 BIOMASS FUELS↗
DOE OSTI2024

Virtual Synchronous Machine Grid-Forming Inverter Model Specification (REGFM_B1)

This report describes a generic virtual synchronous machine (VSM) grid-forming inverter (GFM) model - REGFM_B1. The initial model specification was proposed by Pacific Northwest National Laboratory (PNNL), General Electric (GE), and Electric Power Research Institute (EPRI). Siemens Gamesa Renewable Energy (SGRE) also provided inputs to the specification. The model specification has been revised multiple times based on the discussions between all the contributors listed in this report. This work was funded by the Universal Interoperability for Grid-Forming Inverters (UNIFI) Consortium. This generic model is developed to help the utility industry understand the concept of VSM GFMs. The model could be used to represent equipment for long-term planning studies where vendor-specific models are not available. As equipment mature and improve, generic models will be updated to capture the new functionalities of GFMs. It is not intended that these models will always remain representative of all future GFM technologies.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2026

First Measurement of Sub-GeV nu_mu Charged-Current Coherent Pion Production on Argon in MicroBooNE

Coherent pion production, characterized by a neutrino interacting with an entire nucleus without breaking it apart, results in a forward-going muon, pion, and a low-momentum recoil nucleus. This process provides a sensitive probe of neutrino-nucleus interactions and offers a potential standard candle for neutrino-flux normalization in neutrino-oscillation experiments. We present the first measurement of the flux-averaged charged-current coherent pion production cross section on argon nucleus using the MicroBooNE liquid argon time projection chamber. The analysis employs particle identification together with a data-driven background parameterization to isolate the coherent signal. This measurement uses the full MicroBooNE dataset collected from the Fermilab Booster Neutrino Beam, corresponding to an exposure of 1.26E10^21 protons on target and an average neutrino energy of approximately 0.8 GeV. The result provides the first constraint on charged-current coherent pion production on argon nucleus at sub-GeV energies and supplies important input for improving neutrino interaction modeling in current and future experiments such as DUNE.

Hussain, Adil [Kansas State U.] (ORCID:00000001621↗
DOE OSTI2021

Characterizing the target selection pipeline for the Dark Energy Spectroscopic Instrument Bright Galaxy Survey

ABSTRACT We present the steps taken to produce a reliable and complete input galaxy catalogue for the Dark Energy Spectroscopic Instrument (DESI) Bright Galaxy Survey (BGS) using the photometric Legacy Survey DR8 DECam. We analyse some of the main issues faced in the selection of targets for the DESI BGS, such as star–galaxy separation, contamination by fragmented stars and bright galaxies. Our pipeline utilizes a new way to select BGS galaxies using Gaia photometry and we implement geometrical and photometric masks that reduce the number of spurious objects. The resulting catalogue is cross-matched with the Galaxy And Mass Assembly (GAMA) survey to assess the completeness of the galaxy catalogue and the performance of the target selection. We also validate the clustering of the sources in our BGS catalogue by comparing with mock catalogues and the Sloan Digital Sky Survey (SDSS) data. Finally, the robustness of the BGS selection criteria is assessed by quantifying the dependence of the target galaxy density on imaging and other properties. The largest systematic correlation we find is a 7 per cent suppression of the target density in regions of high stellar density.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2023

Comparing Regional Energy Consumption for Direct Drone and Truck Deliveries

Drone delivery, once thought of as fictitious, is becoming a reality with the efforts of both forward-looking enterprises and supportive government policies. This emerging mode of e-commerce delivery raises many concerns. One important concern is the energy efficiency of direct delivery drones compared with conventional delivery trucks at a regional systems level. Here, in this study, we develop and apply methods to quantify the regional energy impacts of drone delivery, then we assess these impacts and compare them with the impacts of truck delivery. To study this problem, we develop an optimization model that determines an optimal set of fulfillment centers (FCs) with variable service capacities that allow drones to make direct e-commerce deliveries. We adopt two drone delivery energy estimation models from the literature and use them as inputs to demonstrate the potential range of energy needs. We also develop another optimization model to account for the energy consumption of diesel trucks (DTs) and battery electric vehicles (BEVs). We test the models using validated simulation data for the Chicago metropolitan area in the U.S. to quantify the energy implications of these three delivery modes. For drone delivery, we further extend our analyses by considering the impact of wind speed and flight patterns. Our results show that direct delivery drones require 15.8% more energy than BEVs on an average windy day, and they need 15% more energy than DTs on a very windy day. We provide essential parameter values for reproducibility and list relevant open problems.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2026

Powering mCDR with Marine Renewable Energy

This presentation is for a panel that James Niffenegger was invited to speak at called "Powering Marine Carbon Dioxide Removal" (mCDR), which is focused on how marine renewable energy could be used to power the emerging coastal and offshore mCDR industry. James's presentation is focused on the power needs in this field and the areas were marine energy could be advantageous such as in high latitude ocean monitoring, passive seawater pump systems, and powering electrodialysis based mCDR, which can handle highly variable power inputs like those from wave energy.

16 TIDAL AND WAVE POWER↗
DOE OSTI2022

Issues in Bi-Directional Interoperability between BIM and BEM

The state-of-the-art interoperability between Building Information Modeling (BIM) and Building Energy Modeling (BEM) is mainly one-way. BEM software like EnergyPlus takes design input from BIM and simulates the energy consumption of the building. BIM, however, is unable to leverage energy simulation results from BEM smoothly. This lack of bi-directional interoperability between BIM and BEM prevents buildings from seeking more energy-efficient design options and limits BIM applications in optimal generative design. In this research, the authors have conducted the following activities related to two-way interoperability between BIM and BEM: (1) surveyed its current status through literature review, (2) investigated barriers to the bi-directional interoperability, and (3) suggested possible approaches to enable bi-directional interoperability and research outlook in the field. As a result, the authors have identified three main barriers to BIM BEM interoperability, namely, inefficient collaboration, limited scope in information transformation, and lack of BEM to BIM transformation. Future directions are suggested to address these barriers.

building design↗