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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 145 records · Page 8
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Power allocation by load aggregator with heterogeneous loads using weighted projection

With the recently increasing adoption of transactive energy markets, the role of a load aggregator is becoming increasingly important. Among the many tasks of an aggregator, the task of managing the electricity consumption among a group of grid-interactive efficient buildings according to the demand on the grid is taken up. Specifically, here, the task of allocating a certain amount of power among the participating customers while respecting their preferences and comfort is considered. Modeling this as an aggregate flexibility, the virtual battery conditions that are employed to verify the feasibility of a candidate power profile are derived. A feasible power profile, when allocated, satisfies specified comfort bands. To determine the ideal power requirement of the loads, the model-free control method is employed. The feasible power profile is allocated by embedding the customers’ preferences through weights, posing the power constraint as a hyperplane, and employing a weighted projection from the ideal power requirements onto the constraint plane to solve the considered task. The proposed method is computationally efficient and scalable to any number of heterogeneous thermostatically controlled loads in buildings.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2026

Stakeholder-guided holistic, Adaptive Framework for enhancing community Energy Resilience (SAFER) (Final Technical Report)

The Stakeholder-guided holistic, Adaptive Framework for enhancing community Energy Resilience (SAFER) project advances resilience science and engineering by addressing challenges in rural Kansas communities where aging infrastructure, extreme weather, and socioeconomic disparities heighten vulnerability to energy disruptions. Traditional approaches often focus on technical performance while overlooking community concerns and priorities. SAFER responds by integrating community perspectives with advanced analytical frameworks to create a holistic model for measuring and improving resilience. Project objectives included developing novel resilience metrics, advancing modeling frameworks that capture interdependencies across infrastructures, and embedding community-centric indicators directly into planning processes for distributed energy resources. The key technical innovations included the creation of self-organizing map (SOM)-based indices for objective resilience quantification, hetero-functional graph theory (HFGT) models linking power, water, transportation, and community assets, and graph neural network (GNN) tools for identifying critical nodes in complex systems. Community-centric energy planning was demonstrated through optimal siting and sizing of (photovoltaic) PV and battery storage, ensuring resilience enhancements also addressed energy burden and energy insecurity. SAFER engaged community partners in Dodge City and Ford County through surveys, focus groups, and workshops, generating more than 600 responses that established baseline measures of energy burden, financial insecurity, and willingness-to-pay to avoid outages. This data, organized in terms of a community capitals framework, informed the development of weighted reliability indices that better reflect community costs than traditional utility metrics. SAFER’s GNN-based critical node identification framework identified expert-labelled critical nodes with over 99% accuracy, while also uncovering additional functionalities essential for proactive resilience planning. The project’s models demonstrated that optimal PV and storage deployment could improve resilience indices by over 11 percent, with dispatch strategies further enhancing outcomes, confirming both the technical effectiveness and economic feasibility of these approaches. Through its combined emphasis on rigorous modeling, community-focused planning, and community engagement, SAFER advances the state of resilience research while delivering direct benefits to rural communities. The project provides tools, guidelines, and resilience heatmaps that help utilities, local governments, and residents better anticipate disruptions, prioritize investments, and strengthen the capacity to withstand and recover from energy-related hazards. Furthermore, the developed HFG and GNN frameworks are designed for transferability, allowing them to be adapted for resilience planning in other communities with minimal retraining. This inductive learning capability provides a scalable pathway to extend the SAFER project’s impact. Thus, creating a foundation for a nationally applicable model of infrastructure resilience. Additionally, the HFG can also be extended to include other FEMA community lifelines.

14 SOLAR ENERGY↗
DOE OSTI2026

Towards a Verifiable Domain-Specific Language for Hardware-Accelerated Stencils

Defining a domain-specific language (DSL) that supports vector-calculus abstractions eases the porting of partial differential equation (PDE) solvers to specialized architectures. Sufficiently high-level abstractions empower users to express universal laws with sufficient generality that the laws must always hold true within their domain of validity. A broad class of PDE solvers employs stencil-based algorithms, the target domain of Berkeley Lab's stencil accelerator chip co-design project. First released as open-source in January 2026, the Formal software framework lays a foundation for defining an embedded DSL based on composable operators that implement mimetic numerical methods -- stencil algorithms that guarantee satisfaction of discrete versions of important vector calculus theorems. The Formal DSL will be the frontend to a new class of stencil-PDE accelerators developed jointly by LBNL, UHCL, and UC Berkeley through the DOE Competitive Portfolios for Computer Science Project. This offers the potential of an order of magnitude acceleration for this important category of computational methods to serve the DOE mission. Future work on the Formal DSL will facilitate software verification via type-safe templates that enable problem-specific correctness proofs relying upon generic function theory and carefully crafted unit tests.

Rouson, Damian↗
DOE OSTI2024

Impacts of Spatial Resolution in a High-Fidelity Capacity Expansion Model: An ERCOT Case Study

Capacity expansion models are important tools in examining the evolution of the electric power sector. Embedded in these tools are many modeling choices with consequential impacts on computational burden and associated analysis. In this study, we adjust the spatial resolution of the Regional Energy Deployment System (ReEDS) to understand the implications of higher-fidelity modeling on energy system projections and model solve times. The native ReEDS regions capture the contiguous United States in 134 balancing areas whereas the regions in the higher-resolution version are defined by over 3,000 U.S. counties. Using both resolutions, we conduct a case study of the Texas Interconnection (The Electric Reliability Council of Texas [ERCOT]) to explore differences in model projections and to inform appropriate applications of high spatial resolution in a large-scale, applied capacity expansion model.

county↗
DOE OSTI2021

Electron ptychography achieves atomic-resolution limits set by lattice vibrations

Transmission electron microscopes use electrons with wavelengths of a few picometers, potentially capable of imaging individual atoms in solids at a resolution ultimately set by the intrinsic size of an atom. However, owing to lens aberrations and multiple scattering of electrons in the sample, the image resolution is reduced by a factor of 3 to 10. By inversely solving the multiple scattering problem and overcoming the electron-probe aberrations using electron ptychography, we demonstrate an instrumental blurring of less than 20 picometers and a linear phase response in thick samples. The measured widths of atomic columns are limited by thermal fluctuations of the atoms. As a result, our method is also capable of locating embedded atomic dopant atoms in all three dimensions with subnanometer precision from only a single projection measurement.

42 ENGINEERING↗
NASA NTRS1973

Theoretical autophotogrammetry. I - The method of the photometric potential

The present work presents preliminary efforts at a mathematical formulation of a photogrammetric method suitable for computerized processing. A theory is derived for the extraction of surface topography from stereometric pairs of photographs. The theory can be applied to either convergent or near-orthographic-projection stereo. Scene brightness is treated as a scalar function defined on a general surface embedded in ordinary three-dimensional space (the actual topography). Correspondence of points is based on adjustments leading to photometric equivalence, while the adjustments are based on the local value of the photometric gradient.

Wildey, R. L.↗
NASA NTRS2000

EUVE Observations of the Jupiter System

This document is the final report for NASA Grant NAG5-4615, 'Satellie Atmosphere and Io Torus Observations', Nicholas M. Schneider, P.I., awarded to the University of Colorado, 8/l/97-3/31/00. The grant was originally awarded to Dr. Doyle T. Hall, who left the University of Colorado before the completion of the project. Io is the most volcanically active body in the solar system, and it is embedded deep within the strongest magnetosphere of any planet. This combination of circumstances leads to a host of scientifically compelling phenomena, including (1) an atmosphere out of proportion with such a small object, (2) a correspondingly large atmospheric escape rate, (3) a ring of dense plasma locked in a feedback loop with the atmosphere, and (4) a host of Io-induced emissions from radio bursts to UV auroral spots on Jupiter. This proposal seeks to continue our investigation into the physics connecting these phenomena, with emphasis on Io's atmosphere and plasma torus. The physical processes are clearly of interest for Io, and also other places in the solar system where they are important but not readily observable.

Schneider, Nicholas M.↗
NASA NTRS2015

A Coordinated X-Ray and Optical Campaign of the Nearby Massive Binary Sigma Orionis Aa: X-Ray Variability - II

We present time-resolved and phase-resolved variability studies of an extensive X-ray high-resolution gratings spectral dataset of the Sigma Ori Aa binary system. The four observations, obtained with Chandra ACIS HETGS, have a total exposure time of approximately 479 kiloseconds and provide nearly complete binary phase coverage. Variability of the total X-ray flux in the range 5-25 angstroms is confirmed, with maximum amplitude of about plus or minus 15 percent within a single approximately 125 kiloseconds observation. Periods of 4.76 days and 2.04 days are found in the total X-ray flux, as well as an apparent overall increase in flux level throughout the 9-day observational campaign. Using 40 kiloseconds contiguous spectra derived from the original observations, we investigate variability of emission line parameters and ratios. Several emission lines are shown to be variable, including S XV, Si XIII, and Ne IX. For the first time, variations of the X-ray emission line widths as a function of the binary phase are found in a binary system, with the smallest widths at phi equals 0.0 when the secondary Aa2 is at inferior conjunction. We use the results of an SPH radiative transfer code model, customized for this project, to relate the presence of a low density cavity in the primary stellar wind embedded shock that is associated with the secondary star to the emission line width variability.

binaries: closeaEuro"binaries: eclipsingaEuro"star↗
DOE OSTI2025

Safe Physics-Informed Machine Learning for Dynamics and Control

This tutorial paper focuses on safe physics-informed machine learning in the context of dynamics and control, providing a comprehensive overview of how to integrate physical models and safety guarantees. As machine learning techniques enhance the modeling and control of complex dynamical systems, ensuring safety and stability remains a critical challenge, especially in safety-critical applications like autonomous vehicles, robotics, medical decision-making, and energy systems. We explore various approaches for embedding and ensuring safety constraints, including structural priors, Lyapunov and Control Barrier Functions, predictive control, projections, and robust optimization techniques. Additionally, we delve into methods for uncertainty quantification and safety verification, including reachability analysis and neural network verification tools, which help validate that control policies remain within safe operating bounds even in uncertain environments. The paper includes illustrative examples demonstrating the implementation aspects of safe learning frameworks that combine the strengths of data-driven approaches with the rigor of physical principles, offering a path toward the safe control of complex dynamical systems.

Drgona, Jan↗
NASA NTRS1991

Techniques and implementation of the embedded rule-based expert system using Ada

Ada is becoming an increasingly popular programming language for large Government-funded software projects. Ada with its portability, transportability, and maintainability lends itself well to today's complex programming environment. In addition, expert systems have also assured a growing role in providing human-like reasoning capability and expertise for computer systems. The integration of expert system technology with Ada programming language, specifically a rule-based expert system using an ART-Ada (Automated Reasoning Tool for Ada) system shell is discussed. The NASA Lewis Research Center was chosen as a beta test site for ART-Ada. The test was conducted by implementing the existing Autonomous Power EXpert System (APEX), a Lisp-base power expert system, in ART-Ada. Three components, the rule-based expert system, a graphics user interface, and communications software make up SMART-Ada (Systems fault Management with ART-Ada). The main objective, to conduct a beta test on the ART-Ada rule-based expert system shell, was achieved. The system is operational. New Ada tools will assist in future successful projects. ART-Ada is one such tool and is a viable alternative to the straight Ada code when an application requires a rule-based or knowledge-based approach.

Liberman, Eugene M.↗
NASA NTRS1986

SAGA: A project to automate the management of software production systems

Research into software development is required to reduce its production cost and to improve its quality. Modern software systems, such as the embedded software required for NASA's space station initiative, stretch current software engineering techniques. The requirements to build large, reliable, and maintainable software systems increases with time. Much theoretical and practical research is in progress to improve software engineering techniques. One such technique is to build a software system or environment which directly supports the software engineering process, i.e., the SAGA project, comprising the research necessary to design and build a software development which automates the software engineering process. Progress under SAGA is described.

Campbell, Roy H.↗
NASA NTRS1992

An Embedded Rule-Based Diagnostic Expert System in Ada

Ada is becoming an increasingly popular programming language for large Government-funded software projects. Ada with it portability, transportability, and maintainability lends itself well to today's complex programming environment. In addition, expert systems have also assumed a growing role in providing human-like reasoning capability expertise for computer systems. The integration is discussed of expert system technology with Ada programming language, especially a rule-based expert system using an ART-Ada (Automated Reasoning Tool for Ada) system shell. NASA Lewis was chosen as a beta test site for ART-Ada. The test was conducted by implementing the existing Autonomous Power EXpert System (APEX), a Lisp-based power expert system, in ART-Ada. Three components, the rule-based expert systems, a graphics user interface, and communications software make up SMART-Ada (Systems fault Management with ART-Ada). The rules were written in the ART-Ada development environment and converted to Ada source code. The graphics interface was developed with the Transportable Application Environment (TAE) Plus, which generates Ada source code to control graphics images. SMART-Ada communicates with a remote host to obtain either simulated or real data. The Ada source code generated with ART-Ada, TAE Plus, and communications code was incorporated into an Ada expert system that reads the data from a power distribution test bed, applies the rule to determine a fault, if one exists, and graphically displays it on the screen. The main objective, to conduct a beta test on the ART-Ada rule-based expert system shell, was achieved. The system is operational. New Ada tools will assist in future successful projects. ART-Ada is one such tool and is a viable alternative to the straight Ada code when an application requires a rule-based or knowledge-based approach.

Jones, Robert E.↗
NASA NTRS2016

Challenges and Progress in Aerodynamic Design of Hybrid Wingbody Aircraft with Embedded Engines

We summarize the contributions to high-fidelity capabilities for analysis and design of hybrid wingbody (HWB) configurations considered by NASA. Specifically, we focus on the embedded propulsion concepts of the N2-B and N3-X configurations, some of the future concepts seriously investigated by the NASA Fixed Wing Project. The objective is to develop the capability to compute the integrated propulsion and airframe system realistically in geometry and accurately in flow physics. In particular, the propulsion system (including the entire engine core-compressor, combustor, and turbine stages) is vastly more difficult and costly to simulate with the same level of fidelity as the external aerodynamics. Hence, we develop an accurate modeling approach that retains important physical parameters relevant to aerodynamic and propulsion analyses for evaluating the HWB concepts. Having the analytical capabilities at our disposal, concerns and issues that were considered to be critical for the HWB concepts can now be assessed reliably and systematically; assumptions invoked by previous studies were found to have serious consequences in our study. During this task, we establish firmly that aerodynamic analysis of a HWB concept without including installation of the propulsion system is far from realistic and can be misleading. Challenges in delivering the often-cited advantages that belong to the HWB are the focus of our study and are emphasized in this report. We have attempted to address these challenges and have had successes, which are summarized here. Some can have broad implications, such as the concept of flow conditioning for reducing flow distortion and the modeling of fan stages. The design optimization capability developed for improving the aerodynamic characteristics of the baseline HWB configurations is general and can be employed for other applications. Further improvement of the N3-X configuration can be expected by expanding the design space. Finally, the support of the System Analysis and Integration Element under the NASA Fixed Wing Project has enabled the development and helped deployment of the capabilities shown in this report.

design optimization↗
NASA NTRS2016

Assurance of Fault Management: Risk-Significant Adverse Condition Awareness

Fault Management (FM) systems are ranked high in risk-based assessment of criticality within flight software, emphasizing the importance of establishing highly competent domain expertise to provide assurance for NASA projects, especially as spaceflight systems continue to increase in complexity. Insight into specific characteristics of FM architectures seen embedded within safety- and mission-critical software systems analyzed by the NASA Independent Verification Validation (IVV) Program has been enhanced with an FM Technical Reference (TR) suite. Benefits are aimed beyond the IVV community to those that seek ways to efficiently and effectively provide software assurance to reduce the FM risk posture of NASA and other space missions. The identification of particular FM architectures, visibility, and associated IVV techniques provides a TR suite that enables greater assurance that critical software systems will adequately protect against faults and respond to adverse conditions. The role FM has with regard to overall asset protection of flight software systems is being addressed with the development of an adverse condition (AC) database encompassing flight software vulnerabilities.Identification of potential off-nominal conditions and analysis to determine how a system responds to these conditions are important aspects of hazard analysis and fault management. Understanding what ACs the mission may face, and ensuring they are prevented or addressed is the responsibility of the assurance team, which necessarily should have insight into ACs beyond those defined by the project itself. Research efforts sponsored by NASAs Office of Safety and Mission Assurance defined terminology, categorized data fields, and designed a baseline repository that centralizes and compiles a comprehensive listing of ACs and correlated data relevant across many NASA missions. This prototype tool helps projects improve analysis by tracking ACs, and allowing queries based on project, mission type, domain component, causal fault, and other key characteristics. The repository has a firm structure, initial collection of data, and an interface established for informational queries, with plans for integration within the Enterprise Architecture at NASA IVV, enabling support and accessibility across the Agency. The development of an improved workflow process for adaptive, risk-informed FM assurance is currently underway.

Software Verification & Validation↗
NASA NTRSDate not supplied

Gas-Particle Interaction Model Development in Plume Surface Interaction Erosion and Cratering

The development of a predictive simulation capability for extra-terrestrial Plume Surface Interaction (PSI) environments is undertaken by the Fluid Dynamics Branch at NASA/MSFC under the Game Changing Development (GCD) Program funded by NASA’s Space Technology Mission Directorate (STMD). Predictive simulation capability for propulsive Martian and Lunar landing PSI requires accurate modeling of the complex high-speed plume impingement and resulting gas/particle-cloud and ejecta stream formation. Physics modeling gap analysis during formulation of the PSI project scope identified two particular phenomena of first order importance in gas-particle interactions that lacked existing modeling formulations. The first arises from the lack of models capturing the unsteady drag forces imparted on particles by the rapidly expanding supersonic compressible flow. The second addresses the fluctuating forces and dispersions imparted on both the particle and the fluid resulting from the interference and wake turbulence generated by close proximity particle clouds, dubbed the Particle Turbulent Kinetic Energy(PTKE). Their first order significance has been identified in experiments, but simulation models currently do not exist for either effect. The development of models and the eventual implementation into the Eulerian Gas-Granular Flow Solver (GGFS) simulation tools was constructed as one of four major tasks of the PSI project. In this process, data on particle kinetics and gas-particle interactions are collected from carefully designed experiments of particles embedded in jets. The effects observed in the experiments are then replicated in high-fidelity particle-resolved CFD simulations to inform the formulation of improvements to particle phase drag models for implementations in the more efficient Eulerian-Lagrangian CFD simulations. The resulting models are ultimately ported to the Eulerian-Eulerian models applied for most efficient simulations in PSI production application tools. This paper describes the activities and accomplishments of the past year in the gas-particle interaction modeling task of the PSI project.

Jeff West↗
DOE OSTI2023

Thermopile Energy Harvesting for Subsurface Wellbore Sensors (Final Report)

Robust in situ power harvesting underlies all efforts to enable downhole autonomous sensors for real-time and long-term monitoring of CO 2 plume movement and permeance, wellbore health, and induced seismicity. This project evaluated the potential use of downhole thermopile arrays, known as thermoelectric generators (TEGs), as power sources to charge sensors for in situ real-time, long-term data capture and transmission. Real-time downhole monitoring will enable “Big Data” techniques and machine learning, using massive amounts of continuous data from embedded sensors, to quantify short- and long-term stability and safety of enhanced oil recovery and/or commercial-scale geologic CO 2 storage. This project evaluated possible placement of the TEGs at two different wellbore locations: on the outside of the casing; or on the production tubing. TEGs convert heat flux to electrical power, and in the borehole environment, would convert heat flux into or out of the borehole into power for downhole sensors. Such heat flux would be driven by pumping of cold or hot fluids into the borehole—for instance, injecting supercritical CO 2 —creating a thermal pulse that could power the downhole sensors. Hence, wireless power generation could be accomplished with in situ TEG energy harvesting. This final report summarizes the project’s efforts that accomplished the creation of a fully operational thermopile field unit, including selection of materials, laboratory benchtop experiments and thermal-hydrologic modeling for design and optimization of the field-scale power generation test unit. Finally, the report describes the field unit that has been built and presents results of performance and survivability testing. The performance and survivability testing evaluated the following: 1) downhole power generation in response to a thermal gradient produced by pumping a heated fluid down a borehole and through the field unit; and 2) component survivability and operation at elevated temperature and pressure conditions representative of field conditions. The performance and survivability testing show that TEG arrays are viable for generating ample energy to power downhole sensors, although it is important to note that developing or connecting to sensors was beyond the scope of this project. This project’s accomplishments thus traversed from a low Technical Readiness Level (TRL) on fundamental concepts of the application and modeling to TRL-5 via testing of the fully integrated field unit for power generation in relevant environments. A fully issued United States Patent covers the wellbore power harvesting technology and applications developed by this project.

47 OTHER INSTRUMENTATION↗
DOE OSTI2026

Insights from a coupled thermo-hydro-mechanical analysis of a layered high-temperature thermal energy storage reservoir

Coupled thermal-hydraulic-mechanical (THM) modeling is applied to investigate the performance of a seasonal high-temperature aquifer thermal energy storage operation based on data and conditions from current site investigations at the Geostorage Forsthaus pilot project in Bern (Switzerland). The model includes subhorizontal sand lenses of various lengths and dips that are embedded in a low permeability clay matrix. Thermal energy storage is simulated by seasonal injection and withdrawal of hot (up to 90 °C) water from a main well, with reservoir pressure regulated by two auxiliary wells at a distance of about 70 m from the main well. The results show how targeted injection into deeper permeable storage formations, along with active deep well pressure control, can effectively minimize geomechanical impact and the potential risk of damaging subsurface storage and sealing formations, or even surface facilities. With such pressure control, the subsurface mechanical responses are dominated by thermal strain and stress, which can be monitored with subsurface fiber optics. The study demonstrates how coupled THM modeling can be applied for the design of a safe and efficient thermal energy storage operation, and how subsurface fiber optic monitoring can be applied for performance confirmation, allowing for more confident operational forecasting.

Rutqvist, Jonny↗
DOE OSTI2025

Exploring Continuous Seismic Data at an Industry Facility Using Unsupervised Machine Learning

Seismic data recorded at industrial sites contain valuable information on anthropogenic activities. With advances in machine learning and computing power, new opportunities have emerged to explore the seismic wavefield in these complex environments. We applied two unsupervised machine learning algorithms to analyze continuous seismic data collected from an industrial facility in Texas, United States. The Uniform Manifold Approximation and Projection for Dimension Reduction algorithm was used to reduce the dimensionality of the data and generate 2D embeddings. Then, the Hierarchical Density-Based Spatial Clustering of Applications with Noise method was employed to automatically group these embeddings into distinct signal clusters. Our analysis of over 1400 hr (around 59 days) of continuous seismic data revealed five and seven signal clusters at two separate stations. At both stations, we identified clusters associated with background noise and vehicle traffic, with the latter’s temporal patterns aligning closely with the facility’s work schedule. Furthermore, the algorithms detected signal clusters from unknown sources and underline the ability of unsupervised machine learning for uncovering previously unrecognized patterns. Our analysis demonstrates the effectiveness of unsupervised approaches in examining continuous seismic data without requiring prior knowledge or pre-existing labels.

58 GEOSCIENCES↗