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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 217 records · Page 12
All sourcesNASA NTRSDOE OSTI
NASA NTRS1995

2-kW Solar Dynamic Space Power System Tested in Lewis' Thermal Vacuum Facility

Working together, a NASA/industry team successfully operated and tested a complete solar dynamic space power system in a large thermal vacuum facility with a simulated sun. This NASA Lewis Research Center facility, known as Tank 6 in building 301, accurately simulates the temperatures, high vacuum, and solar flux encountered in low-Earth orbit. The solar dynamic space power system shown in the photo in the Lewis facility, includes the solar concentrator and the solar receiver with thermal energy storage integrated with the power conversion unit. Initial testing in December 1994 resulted in the world's first operation of an integrated solar dynamic system in a relevant environment.

Source record↗
NASA NTRS2024

Analysis of Hybrid Electric Aircraft Operations in the National Airspace System

This paper investigates the fuel burn and flight time impacts of hybrid electric aircraft operating in the National Airspace System. Future scenarios with hybrid electric flights and the same passenger travel capacity between city pairs as a baseline scenario, taken from historical data, were created. Aircraft that serviced select flights in the baseline scenario were replaced with hybrid electric aircraft based on the flight’s range and seat capacity. Additional hybrid electric flights were added to future scenarios when necessary to keep the future scenario passenger capacity equal or greater to that of the baseline scenario. The baseline and future scenarios were simulated in the NAS Digital Twin, a live, virtual, and constructive environment for building and executing simulations of the Nation Airspace System. Results showed that the future scenarios with hybrid electric flights saved fuel burn, but increased flight time. In the future scenarios, the additional hybrid electric flights did not cause any airports to exceed their operational capacity.

Simulation↗
NASA NTRSDate not supplied

Operating Hybrid Electric Aircraft in the National Airspace System

This paper investigates the fuel burn and flight time impacts of hybrid electric aircraft operating in the National Airspace System. Future scenarios with hybrid electric flights and the same passenger travel capacity between city pairs as a baseline scenario, taken from historical data, were created. Aircraft that serviced select flights in the baseline scenario were replaced with hybrid electric aircraft based on the flight’s range and seat capacity. Additional hybrid electric flights were added to future scenarios when necessary to keep the future scenario passenger capacity equal or greater to that of the baseline scenario. The baseline and future scenarios were simulated in the NAS Digital Twin, a live, virtual, and constructive environment for building and executing simulations of the Nation Airspace System. Results showed that the future scenarios with hybrid electric flights saved fuel burn, but increased flight time. In the future scenarios, the additional hybrid electric flights did not cause any airports to exceed their operational capacity.

hybrid electric aircraft↗
NASA NTRS2020

Parabolic Deformable Mirror Testbed for the ExoSpec Project

The ExoSpec Project is a NASA Headquarters directed work package that links four different tasks at Goddard Space Flight Center to enable future missions to more efficiently characterize directly imaged exoplanets. One of the tasks is the development of parabolic deformable mirrors to improve on the current state-of-the-art wavefront sensing and control implementations, which are baselined to have two flat deformable mirrors (DMs) with high actuator count. To effectively control both amplitude and phase aberrations, the flat DMs need to have a large separation, which poses packaging challenges to missions designed to image rocky exoplanets. To eliminate this large separation, the parabolic DM architecture makes the off-axis imaging elements in the optical train controllable. Simulations also show performance enhancements with the architecture change; larger bandwidths have been shown to be controllable with the parabolic DMs and the number of required actuators can be reduced. With a 32×32 pupil flat DM and two 16x16 parabolic DMs, we could obtain a 5 - 12λ/D dark hole at 35%bandwidth. In addition to addressing the packaging challenge faced by future coronagraph missions, reducing the number of actuators reduces both cost and risk of having the entire coronagraph instrument’s performance depend on two high-actuator count DMs. To test these simulations, Goddard is building a testbed and has a vendor developing the parabolic DM. Here we present these simulations, the current testbed performance, and the development plan to incorporate and test the parabolic DMs

Coronagraph↗
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

Description of FY25 Theory and Simulation Performance Target: Development of an integrated modeling framework for fusion reactor design and assessment

The urgency to deliver fusion power is growing now more than ever, with increasing pressure for both public programs and private companies to meet milestones timelines and overcome significant remaining technical challenges to ensure growth of a nascent fusion industry in time to meet rapidly growing clean energy demands. With incredible advancements in computation and years of investment in fusion model development and validation, integrated modeling is poised to fill a key role in accelerating the timeline to a fusion pilot plant (FPP). Future fusion pilot plants will operate in regimes far beyond current experience, and device design will rely on physics-based prediction and extrapolation. Many concepts will also rely on simulation to assess safety (shielding, tritium management, materials activation and lifetimes), economics and scalability before the decision to build. Importantly, integrated simulation can be used to reveal and solve the complexities of system integration that may otherwise not be apparent in physical components or models developed in isolation. New experimental test facilities that produce relevant conditions to validate and resolve key technical challenges for various subsystems (materials, blankets, fuel cycle, etc.) have been repeatedly called for by the fusion community but are not yet realized. Integrated modeling has an important role in identifying realistic load conditions (thermal, electromagnetic, plasma, neutron and photon loads, etc.) and defining the components and experiments for these test facilities in order to ensure meaningful validation that sufficiently reduces modeling uncertainties and technical risk for the full integrated reactor. The Fusion REactor Design and Assessment (FREDA) SciDAC project is building a component-based integrated modeling framework & data structure to enable self-consistent, multi-fidelity, iterative optimization workflows for the fusion reactor design process. FREDA aims to shorten the time to viable designs by providing a set of flexible workflows to support the various stages of the design process using an integrated model hierarchy, ranging from the simple analytic descriptions to the highest fidelity, theory-based plasma and engineering modeling developed by the fusion and fission communities. These tools are expected to be needed for timely support of FPP design in the milestone program and in the FIRE collaboratives. The plasma simulation backbone of FREDA is IPS-FASTRAN with newly developed coupled Core-Edge Pedestal-SOL (CESOL) workflows, which is being extended to the far-SOL region up to the plasma facing components. FREDA incorporates the FERMI engineering modeling suite and will enable self-consistent evaluation of the thermal shields, limiters, blanket, magnets, and other surrounding structures with predictions of temperatures, erosion, dpa, activation, tritium generation and transport, creep, corrosion, material degradation, etc. Parametric generation of 3D CAD enables rapid iteration of component geometry in response to plasma and loading specifications.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
NASA NTRS2004

Redesign of the Human Metabolic Simulator

The National Aeronautics and Space Administration (NASA) is currently building a Human Metabolic Simulator (HMS) at the Johnson Space Center as part of the Advanced Life Support Air Revitalization Technology Evaluation Facility (ARTEF). The purpose of ARTEF is to evaluate Environmental Control and Life Support System Technologies for Advanced Missions. The HMS is needed to reproduce the primary metabolic effects of human respiration on an enclosed atmosphere when humans cannot be present and the impact of human presence on the system is required. A HMS was designed, built and successfully operated in 2000 but larger crew size requirements and the expense of upgrade of the current system necessitate redesign. This paper addresses the redesign. Several concepts were considered, ranging from chemical oxidation of a hydrocarbon like ethanol or ethyl acetate to carbon dioxide and water, oxidation of an iron-containing compound, or by using a fuel cell. For reasons of cost, simplicity, safety and other factors, the concept chosen includes: a molecular sieve packaged as an industrial oxygen concentrator to remove oxygen from the atmosphere, with direct carbon dioxide, water and heat injection. The water injection is done via heating water to steam with a heat exchanger and thermal effects are handled by directly adding heat to the air stream with a second heat exchanger. Both heat exchangers are supplied by a hot oil loop. The amount of oxygen removal, carbon dioxide addition, water addition and heat addition were calculated using metabolic profiles for respiration and heat, calculated using a series of empirical equations developed for International Space Station (ISS). Sketches of the Human Metabolic Simulator and the hot oil bath loop used to supply heat to the heat exchangers are included

Duffield, Bruce↗
NASA NTRSDate not supplied

Introduction to the IMPACT Probabilistic Risk and Tradespace Analysis Tool for Medical System Design

Background: Probabilistic risk analysis (PRA) is a method for estimating risk in complex engineered systems that, at a basic level, focuses on what can go wrong and the likelihood and consequences of those occurrences. NASA has used PRA as an integral component of medical system risk estimation and design for spaceflight. IMPACT (Informing Mission Planning via Analysis of Complex Tradespaces) is a novel tool to meet these goals for exploration missions. Overview: IMPACT performs hundreds of thousands of Monte Carlo simulations of missions to build aggregate pictures of medical risk. These simulations are based on 120 possible medical conditions (the IMPACT Condition List) selected in a consensus-based process because they are of highest likelihood and/or consequence for exploration spaceflight. The conditions are then tied to clinical capabilities which can be used for management (e.g., inserting an IV) and then to over 600 specific resources needed to deliver a capability (e.g., an angiocath or an ultrasound). Different mission profiles can be simulated with user-specified inputs such as mission duration, destination, number of crew and pre-existing medical conditions, and EVA frequency. While the IMPACT evidence base is designed for exploration environments, these user inputs allow the tool to be used across a broad range of missions. IMPACT’s primary outcome metrics include loss of crew life (LOCL, a measure of in-flight mortality due to medical conditions), need for evacuation (RTDC, return to definitive care), and crew disability (TTL, task time lost based on how medical conditions impact the ability to perform over 1000 specific exploration mission crew tasks). In addition to modeling medical risk, IMPACT also accepts user-specified constraints, such as limitations of mass or volume, and will output a recommended clinical capability set and specific medical resources that meet the mission constraints. Discussion: This abstract will provide an introduction to IMPACT and describe the nature of the underlying medical evidence. It will also detail potential use cases for how this tool can be utilized by NASA or commercial spaceflight providers.

Ben Easter↗
DOE OSTI2026

Exploring Building Retrofit Strategies Using AutoBEM Under Future Weather Scenarios

This study evaluates the long-term effectiveness of energy conservation measures (ECMs) on building energy consumption using AutoBEM, a scalable modeling framework driven by the high-resolution Model America dataset. We simulated 18,951 buildings in Flagstaff, Arizona under four climate scenarios using Future Typical Meteorological Year (fTMY) weather files for six time periods spanning from 1980 to 2099. Six ECMs were analyzed across electricity and gas usage, including HVAC fuel-switching, insulation upgrades, and infiltration control. While some measures, such as reducing space infiltration by percentage, showed minimal or even negative impact on total energy savings at the aggregate level, they proved highly effective for specific building types. Conversely, HVAC electrification offers high gas reduction but shifts demand to electricity, highlighting critical trade-offs under different climate trajectories. Building-type-specific analysis under SSP5-RCP8.5 (2080–2099) revealed significant variation in ECM performance, underscoring the need for targeted retrofit strategies. This study demonstrates the power of combining fTMY projections with large-scale simulations to inform data-driven retrofit planning.

Chowdhury, Shovan [ORNL]↗
DOE OSTI2025

Designing reinforcement learning algorithms for building HVAC control: From experimental observation to simulation comparisons

Advanced supervisory-level control with reinforcement learning (RL) is regarded as a promising solution for HVAC systems to minimize energy consumption while maintaining thermal comfort and indoor air quality. However, most RL applications were conducted in the simulation environment rather than real-world HVAC systems. This paper developed a value-based RL controller termed Deep Q-Network (DQN) for a typical central HVAC system and evaluated its performance in a building test facility. By comparing DQN with a rule-based controller, the study not only demonstrated the cases where DQN could properly maintain indoor comfort but also discussed possible reasons why DQN failed in some other situations. Recognizing the limitations of value-based RL algorithms from the experimental tests, a simulation study was conducted to compare DQN with an alternative RL approach, an actor–critic algorithm termed Deep Deterministic Policy Gradient (DDPG). In scenarios with a relatively large action space, DDPG outperformed DQN by requiring fewer computational resources and achieving better thermal comfort, lower energy consumption, and more stable control actions. The findings suggest that the ability of DDPG to handle continuous control variables more effectively allows for faster convergence in training and more precise control in practice, which enhances the overall efficiency and reliability of the HVAC system.

Guo, Fangzhou↗
DOE OSTI2025

Resolving discrepancies in bang-time predictions for indirect-drive ICF experiments on the NIF: Insights from the Build-A-Hohlraum campaign

This study investigated discrepancies between measured and simulated x-ray drive in Indirect-Drive Inertial Confinement Fusion (ID-ICF) hohlraums at the National Ignition Facility. Despite advances in radiation-hydrodynamic simulations, a consistent “drive deficit” remains. Experimentally measured ID-ICF capsule bang-times are systematically 400–700 ps later than simulations predict. The Build-A-Hohlraum (BAH) campaign explored potential causes for this discrepancy by systematically varying hohlraum features, including laser entrance hole (LEH) windows, capsules, and gas fills. Overall, the agreement between simulated and experimental x-ray drive was found to be largely unaffected by these changes. The data allow us to exclude some hypotheses put forward to potentially explain the discrepancy. Errors in the local thermodynamic equilibrium (LTE) atomic modeling, errors in the modeling of LEH closure, and errors due to a lack of plasma species mix physics in simulations are shown to be inconsistent with our measurements. Instead, the data support the hypothesis that errors in NLTE emission modeling are a significant contributor to the discrepancy. X-ray emission in the 2–4 keV range is found to be approximately 30% lower than in simulations. This is accompanied by higher than predicted electron temperatures in the gold bubble region, pointing to errors in non-LTE modeling. Introducing an opacity multiplier of 0.87 on energy groups above 1.8 keV improves agreement with experimental data, reducing the bang-time discrepancy from 300 to 100 ps. These results underscore the need for refined NLTE opacity models to enhance the predictive power of hohlraum simulations.

Band emission↗
NASA NTRS2004

Orbiter/External Tank Mate 3-D Solid Modeling

This research and development project presents an overview of the work completed while attending a summer 2004 American Society of Engineering Education/National Aeronautics and Space Administration (ASEE/NASA) Faculty Fellowship. This fellowship was completed at the Kennedy Space Center, Florida. The scope of the project was to complete parts, assemblies, and drawings that could be used by Ground Support Equipment (GSE) personnel to simulate situations and scenarios commonplace to the space shuttle Orbiter/External Tank (ET) Mate (50004). This mate takes place in the Vehicle Assembly Building (VAB). These simulations could then be used by NASA engineers as decision-making tools. During the summer of 2004, parts were created that defined the Orbiter/ET structural interfaces. Emphasis was placed upon assemblies that included the Orbiter/ET forward attachment (EO-1), aft left thrust strut (EO-2), aft right tripod support structure (EO-3), and crossbeam and aft feedline/umbilical supports. These assemblies are used to attach the Orbiter to the ET. The Orbiter/ET Mate assembly was then used to compare and analyze clearance distances using different Orbiter hang angles. It was found that a 30-minute arc angle change in Orbiter hang angle affected distance at the bipod strut to Orbiter yoke fitting 8.11 inches. A 3-D solid model library was established as a result of this project. This library contains parts, assemblies, and drawings translated into several formats. This library contains a collection of the following files: sti for sterolithography, stp for neutral file work, shrinkwrap for compression. tiff for photoshop work, jpeg for Internet use, and prt and asm for Pro/Engineer use. This library was made available to NASA engineers so that they could access its contents to make angle, load, and clearance analysis studies. These decision-making tools may be used by Pro/Engineer users and non-users.

Godfrey, G. S.↗
NASA NTRS1990

An intelligent simulation training system

The Department of Industrial Engineering at the University of Central Florida, Embry-Riddle Aeronautical University and General Electric (SCSD) have been funded by the State of Florida to build an Intelligent Simulation Training System. The objective was and is to make the system generic except for the domain expertise. Researchers accomplished this objective in their prototype. The system is modularized and therefore it is easy to make any corrections, expansions or adaptations. The funding by the state of Florida has exceeded $3 million over the past three years and through the 1990 fiscal year. UCF has expended in excess of 15 work years on the project. The project effort has been broken into three major tasks. General Electric provides the simulation. Embry-Riddle Aeronautical University provides the domain expertise. The University of Central Florida has constructed the generic part of the system which is comprised of several modules that perform the tutoring, evaluation, communication, status, etc. The generic parts of the Intelligent Simulation Training Systems (ISTS) are described.

Biegel, John E.↗
DOE OSTI2025

Coupled Induction Machine and HVAC Models for Simulating HVAC Performance Considering Grid Dynamics in Buildings

This paper presents the development of novel models that integrate induction machines with HVAC equipment, such as pumps, heat pumps, and chillers, to analyze the impact of electrical parameters on the operational performance of thermo-fluid systems. The proposed model employs a coupling technique that captures the dynamic interactions between induction machines and HVAC systems. By integrating electrical, thermal, and mechanical dynamics, the models provide a comprehensive framework for simulating real-world scenarios, including interactions with the electrical grid. This achievement was made possible through the development of a Computationally Efficient and Accurate Induction Machine (CEAIM) model. Implemented using the equation-based Modelica language, the CEAIM model has been validated against experimental results, manufacturer data sheets, and various operating conditions. Its performance has been compared with existing induction machine models in the Modelica Standard Library (MSL), demonstrating superior accuracy and computational efficiency. The CEAIM model predicts torque, speed, and power consumption with a coefficient of determination (R 2 ) ranging from 0.98 to 1 and a coefficient of variation of root mean square error (CVRMSE) between 0.27% and 6.67%. Additionally, CEAIM scales more efficiently than conventional MSL models, with a slower computational growth rate in large-scale simulations. After thorough validation of the CEAIM model, it was coupled with HVAC equipment as this approach provides a detailed multi-dimensional view of capturing electrical transients and mechanical performance. To support this, a case study was conducted to showcase its capabilities.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2026

Artificial Intelligence Thermostat to Detect Faults

Residential air conditioners and heat pumps often experience faults due to inadequate maintenance, which can severely reduce efficiency or even cause system failure. Common issues include dirty or clogged air filters and refrigerant leaks. These problems degrade performance and increase energy use and operating costs. This study presents a smart thermostat with embedded artificial intelligence to detect such faults and alert homeowners when maintenance is needed. The thermostat uses low-cost measurements—including return-air temperature, relative humidity, supply-air temperature, outdoor-air temperature, and condenser subcooling—to identify abnormal operations. Because different faults produce distinct response patterns, tailored algorithms are developed to recognize characteristic fault signatures. The investigation is built on a detailed co-simulation platform that couples EnergyPlus with the DOE/ORNL Heat Pump Design Model (HPDM). EnergyPlus represents the building’s dynamic environment, while HPDM is a high-fidelity, hardware-based model that can simulate fault-free performance as well as a wide range of faults, including gradual degradation such as minor refrigerant leakage. This platform provides a virtual training and testing environment that helps distinguish fault-induced behavior from normal operation and supports development of robust diagnostic algorithms. Using this framework, a Dynamic Bayesian Network was developed to identify two common faults—gradual refrigerant charge loss and indoor airflow blockage—and the AI-embedded thermostat was verified through annual building simulations.

Shen, Bo [ORNL] (ORCID:0000000336600393)↗
NASA NTRS1978

Building wakes in disturbed layers

The wind profiles in the wakes of buildings in a disturbed shear layer are investigated for conditions experienced during aircraft take-off and landing. Experiments were conducted in a pipe flow apparatus in which an equilibrium flow is disturbed by pipe roughness, simulating obstacles upwind of a building, with the disturbed flow made to flow past a second obstacle, simulating a building. Velocity and turbulence profiles of disturbed and equilibrium flows upstream and downstream of the obstacles are presented. It is concluded that the integrated momentum flow of a boundary layer behind an obstacle can be greater than the upstream momentum flow, if the exponent of the upstream velocity profile is sufficiently high and the boundary layer has been disturbed by upstream obstacles. The rise of the turbulence level behind the obstacle is also dependent on the profile exponent in a disturbed layer.

Logan, E.↗
DOE OSTI2025

Effect of Solvents on Lignin–Surface Interactions via Molecular Dynamics Simulations

Lignin, an essential building block of lignocellulosic biomass, is a potential abundant source of aromatic monomers for the polymer and chemical industry. Reductive catalytic fractionation (RCF) is one promising process that can produce high yields of phenolic monomers and oligomers from lignin under different catalytic conditions. An important choice in optimizing RCF is the selection of solvent; however, detailed insights into solvent effects on lignin behaviors and interactions remain limited. Here, in this work, we perform all-atom molecular dynamics simulations to study the solvation of lignin, solvent-mediated conformational changes, and the interaction of solvated lignin oligomers with model surfaces. We focus on the behavior of an oligomeric lignin model compound in methanol, ethanol, a binary mixture of ethanol and water, and water at both the RCF reaction temperature (473 K) and room temperature. Analysis of structural features of lignin suggests that these three organic solvent systems favorably solvate lignin, resulting in a more extended conformation suitable for catalytic conversion to valuable chemicals. We further introduce model palladium (Pd) and carbon (C) surfaces to understand how solvent choice impacts adsorption onto a representative catalytic surface and support, and to quantify the competition among the reactant and solvent molecules for the surface. Unbiased simulations suggest strong adsorption of lignin on both Pd and C surfaces at 473 K, with notable solvent-mediated differences in adsorption energies. Additionally, our findings indicate that lignin adsorption is promoted by the entropy change resulting from the displacement of solvent molecules from the surface. This study provides a molecular perspective of adsorption of lignin onto varying surfaces, which is a step towards understanding and optimizing the catalytic conversion of lignin into valuable chemicals.

adsorption↗
NASA NTRS1997

A Study of the Role of Clouds in the Relationship Between Land Use/Land Cover and the Climate and Air Quality of the Atlanta Area

The goal of Project ATLANTA is to derive a better scientific understanding of how land cover changes associated with urbanization affect local and regional climate and air quality. Clouds play a significant role in this relationship. Using GOES images, we found that in a 63-day period (5 July-5 September 1996) there were zero days which were clear for the entire daylight period. Days which are cloud-free in the morning become partly cloudy with small cumulus clouds in the afternoon in response to solar heating. This result casts doubt on the applicability of California-style air quality models which run in perpetual clear skies. Days which are clear in the morning have higher ozone than those which are cloudy in the morning. Using the RAMS model, we found that urbanization increases the skin surface temperature by about 1.0-1.5 C on average under cloudy conditions, with an extreme of +3.5 C. Clouds cool the surface due to their shading effect by 1.5-2.0 C on average, with an extreme of 5.0 C. RAMS simulates well the building stage of the cumulus cloud field, but does poorly in the decaying phase. Next year's work: doing a detailed cloud climatology and developing improved RAMS cloud simulations.

Kidder, Stanley Q.↗