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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 235 records · Page 13
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Risk-controlled Expansion Planning with Distributed Resources (REPAIR) v1.0

The Risk-controlled Expansion Planning with Distributed Resources (REPAIR) is an innovative tool to support decisions around utility grid planning to prevent and mitigate the impact of outages caused by routine equipment failures (reliability) or by extreme events (resilience), such as storms, earthquakes or wildfires that long term interruption of service. REPAIR is a risk-based optimization and decision-making model allowing informed and transparent "cost vs risk" decisions regarding infrastructural planning of electric utilities. The model considers long-term resilience and reliability planning strategies that rely on traditional infrastructure upgrade (e.g. circuit hardening, reinforcement, new substations, etc.) or new investment alternatives, such as DERs.

Heleno, Miguel [Lawrence Berkeley National Laborat↗
DOE OSTI2025

Graph-Learning-Assisted State and Event Tracking for Solar-Penetrated Power Grids with Heterogeneous Data Sources

Unlike transmission systems, distribution systems do not typically contain sufficient metering to enable real-time state estimation. The lack of sufficient real-time measurements prohibits accurate and timely monitoring of the state of distribution systems. As a result, control and optimal operation of distribution systems, especially those containing large numbers of renewable generation units are not possible without proper data and information about the current state of the system. The main motivation of this project is to address this shortcoming by developing an approach which provides “predicted” real-time measurements so that they can be used to execute a distribution system state estimator. Thus, the objective of the project is to make the distribution systems fully observable, such that the hosting capacity for solar generation can be accurately estimated, and unnecessary solar curtailments can be avoided. In order to accomplish this goal, the project investigated the use of a grid-model-informed machine learning (ML) tool which integrates heterogeneous data streams obtained from AMI meters, SCADA as well as PMU measurements and created synchronous measurement snapshots for the state estimator (SE); and developed a hybrid robust SE which provides not only accurate state estimates but also real-time feedback for the ML model refinement.

14 SOLAR ENERGY↗
NASA NTRS1994

CFD analyses for advanced pump design

As one of the activities of the NASA/MSFC Pump Stage Technology Team, the present effort was focused on using CFD in the design and analysis of high performance rocket engine pumps. Under this effort, a three-dimensional Navier-Stokes code was used for various inducer and impeller flow field calculations. An existing algebraic grid generation procedure was-extended to allow for nonzero blade thickness, splitter blades, and hub/shroud cavities upstream or downstream of the (main) blades. This resulted in a fast, robust inducer/impeller geometry/grid generation package. Problems associated with running a compressible flow code to simulate an incompressible flow were resolved; related aspects of the numerical algorithm (viz., the matrix preconditioning, the artificial dissipation, and the treatment of low Mach number flows) were addressed. As shown by the calculations performed under the present effort, the resulting code, in conjunction with the grid generation package, is an effective tool for the rapid solution of three-dimensional viscous inducer and impeller flows.

Dejong, F. J.↗
NASA NTRS1995

Computational System For Rapid CFD Analysis In Engineering

Computational system comprising modular hardware and software sub-systems developed to accelerate and facilitate use of techniques of computational fluid dynamics (CFD) in engineering environment. Addresses integration of all aspects of CFD analysis process, including definition of hardware surfaces, generation of computational grids, CFD flow solution, and postprocessing. Incorporates interfaces for integration of all hardware and software tools needed to perform complete CFD analysis. Includes tools for efficient definition of flow geometry, generation of computational grids, computation of flows on grids, and postprocessing of flow data. System accepts geometric input from any of three basic sources: computer-aided design (CAD), computer-aided engineering (CAE), or definition by user.

Barson, Steven L.↗
NASA NTRS2001

Computational Aeroacoustic Analysis System Development

Many industrial and commercial products operate in a dynamic flow environment and the aerodynamically generated noise has become a very important factor in the design of these products. In light of the importance in characterizing this dynamic environment, Rocketdyne has initiated a multiyear effort to develop an advanced general-purpose Computational Aeroacoustic Analysis System (CAAS) to address these issues. This system will provide a high fidelity predictive capability for aeroacoustic design and analysis. The numerical platform is able to provide high temporal and spatial accuracy that is required for aeroacoustic calculations through the development of a high order spectral element numerical algorithm. The analysis system is integrated with well-established CAE tools, such as a graphical user interface (GUI) through PATRAN, to provide cost-effective access to all of the necessary tools. These include preprocessing (geometry import, grid generation and boundary condition specification), code set up (problem specification, user parameter definition, etc.), and postprocessing. The purpose of the present paper is to assess the feasibility of such a system and to demonstrate the efficiency and accuracy of the numerical algorithm through numerical examples. Computations of vortex shedding noise were carried out in the context of a two-dimensional low Mach number turbulent flow past a square cylinder. The computational aeroacoustic approach that is used in CAAS relies on coupling a base flow solver to the acoustic solver throughout a computational cycle. The unsteady fluid motion, which is responsible for both the generation and propagation of acoustic waves, is calculated using a high order flow solver. The results of the flow field are then passed to the acoustic solver through an interpolator to map the field values into the acoustic grid. The acoustic field, which is governed by the linearized Euler equations, is then calculated using the flow results computed from the flow solver.

Hadid, A.↗
NASA NTRS2012

NASA Tech Briefs, August 2012

Topics covered include: Mars Science Laboratory Drill; Ultra-Compact Motor Controller; A Reversible Thermally Driven Pump for Use in a Sub-Kelvin Magnetic Refrigerator; Shape Memory Composite Hybrid Hinge; Binding Causes of Printed Wiring Assemblies with Card-Loks; Coring Sample Acquisition Tool; Joining and Assembly of Bulk Metallic Glass Composites Through Capacitive Discharge; 670-GHz Schottky Diode-Based Subharmonic Mixer with CPW Circuits and 70-GHz IF; Self-Nulling Lock-in Detection Electronics for Capacitance Probe Electrometer; Discontinuous Mode Power Supply; Optimal Dynamic Sub-Threshold Technique for Extreme Low Power Consumption for VLSI; Hardware for Accelerating N-Modular Redundant Systems for High-Reliability Computing; Blocking Filters with Enhanced Throughput for X-Ray Microcalorimetry; High-Thermal-Conductivity Fabrics; Imidazolium-Based Polymeric Materials as Alkaline Anion-Exchange Fuel Cell Membranes; Electrospun Nanofiber Coating of Fiber Materials: A Composite Toughening Approach; Experimental Modeling of Sterilization Effects for Atmospheric Entry Heating on Microorganisms; Saliva Preservative for Diagnostic Purposes; Hands-Free Transcranial Color Doppler Probe; Aerosol and Surface Parameter Retrievals for a Multi-Angle, Multiband Spectrometer LogScope; TraceContract; AIRS Maps from Space Processing Software; POSTMAN: Point of Sail Tacking for Maritime Autonomous Navigation; Space Operations Learning Center; OVERSMART Reporting Tool for Flow Computations Over Large Grid Systems; Large Eddy Simulation (LES) of Particle-Laden Temporal Mixing Layers; Projection of Stabilized Aerial Imagery Onto Digital Elevation Maps for Geo-Rectified and Jitter-Free Viewing; Iterative Transform Phase Diversity: An Image-Based Object and Wavefront Recovery; 3D Drop Size Distribution Extrapolation Algorithm Using a Single Disdrometer; Social Networking Adapted for Distributed Scientific Collaboration; General Methodology for Designing Spacecraft Trajectories; Hemispherical Field-of-View Above-Water Surface Imager for Submarines; and Quantum-Well Infrared Photodetector (QWIP) Focal Plane Assembly.

Source record↗
NASA NTRS2019

Sketch-To-Solution: An Exploration of Viscous CFD with Automatic Grids

Numerical simulation of the Reynolds-averaged Navier–Stokes (RANS) equations has become a critical tool for the design of aerospace vehicles. However, the issues that affect the grid convergence of three dimensional RANS solutions are not completely understood, as documented in the AIAA Drag Prediction Workshop series. Grid adaption methods have the potential for increasing the automation and discretization error control of RANS solutions to impact the aerospace design and certification process. The realization of the CFD Vision 2030 Study includes automated management of errors and uncertainties of physics-based, predictive modeling that can set the stage for ensuring a vehicle is in compliance with a regulation or specification by using analysis without demonstration in flight test (i.e., certification or qualification by analysis). For example, the Cart3D inviscid analysis package has automated Cartesian cut-cell gridding with output-based error control. Fueled by recent advances in the fields of anisotropic grid adaptation, error estimation, and geometry modeling, a similar work flow is explored for viscous CFD simulations; where a CFD application engineer provides geometry, boundary conditions, and flow parameters, and the sketch-to-solution process yields a CFD simulation through automatic, error-based, grid adaptation.

Kleb, William L.↗
NASA NTRSDate not supplied

Improved Heat Transfer Prediction for High-Speed Flows over Blunt Bodies using Adaptive Mixed-Element Unstructured Grids

Aerothermodynamic prediction is important for the design and analysis of many aerospace vehicles. Computational Fluid Dynamics (CFD) tools used for these predictions commonly rely on structured shock-aligned grids due to the strong shocks exhibited at high speeds. This work details the incorporation of an improved HLLE++ scheme for both perfect gas and thermochemical nonequilibrium flows which robustly captures shock waves on both non-shock-aligned and shock-aligned grids. The HLLE++ scheme reduces the impact of eigenvalue limiting on flow solutions which is required for Roe's scheme for high Mach number flows. An adapted grid approach is also demonstrated using mixed-element unstructured grids to improve heat prediction. Thin prismatic boundary layers are used with tetrahedra in the farfield and for capturing shock waves. Various results are presented for hypersonic flows over blunt bodies including cylinders, spheres, and capsules.

CFD↗
NASA NTRSDate not supplied

Improved Heat Transfer Prediction for High-Speed Flows over Blunt Bodies using Adaptive Mixed-Element Unstructured Grids

Aerothermodynamic prediction is important for the design and analysis of many aerospace vehicles. Computational Fluid Dynamics (CFD) tools used for these predictions commonly rely on structured shock-aligned grids due to the strong shocks exhibited at high speeds. This work details the incorporation of an improved HLLE++ scheme for both perfect gas and thermochemical nonequilibrium flows which robustly captures shock waves on both non-shock-aligned and shock-aligned grids. The HLLE++ scheme reduces the impact of eigenvalue limiting on flow solutions which is required for Roe's scheme for high Mach number flows. An adapted grid approach is also demonstrated using mixed-element unstructured grids to improve heat prediction. Thin prismatic boundary layers are used with tetrahedra in the farfield and for capturing shock waves. Various results are presented for hypersonic flows over blunt bodies including cylinders, spheres, and capsules.

CFD↗
NASA NTRS2001

The State of NASA's Information Power Grid

This viewgraph presentation transfers the concept of the power grid to information sharing in the NASA community. An information grid of this sort would be characterized as comprising tools, middleware, and services for the facilitation of interoperability, distribution of new technologies, human collaboration, and data management. While a grid would increase the ability of information sharing, it would not necessitate it. The onus of utilizing the grid would rest with the users.

Johnston, William E.↗
NASA NTRS1998

NASA's Participation in the National Computational Grid

Over the last several years it has become evident that the character of NASA's supercomputing needs has changed. One of the major missions of the agency is to support the design and manufacture of aero- and space-vehicles with technologies that will significantly reduce their cost. It is becoming clear that improvements in the process of aerospace design and manufacturing will require a high performance information infrastructure that allows geographically dispersed teams to draw upon resources that are broader than traditional supercomputing. A computational grid draws together our information resources into one system. We can foresee the time when a Grid will allow engineers and scientists to use the tools of supercomputers, databases and on line experimental devices in a virtual environment to collaborate with distant colleagues. The concept of a computational grid has been spoken of for many years, but several events in recent times are conspiring to allow us to actually build one. In late 1997 the National Science Foundation initiated the Partnerships for Advanced Computational Infrastructure (PACI) which is built around the idea of distributed high performance computing. The Alliance lead, by the National Computational Science Alliance (NCSA), and the National Partnership for Advanced Computational Infrastructure (NPACI), lead by the San Diego Supercomputing Center, have been instrumental in drawing together the "Grid Community" to identify the technology bottlenecks and propose a research agenda to address them. During the same period NASA has begun to reformulate parts of two major high performance computing research programs to concentrate on distributed high performance computing and has banded together with the PACI centers to address the research agenda in common.

Feiereisen, William J.↗
DOE OSTI2026

An Online Tool for Preliminary Design and Techno-Economic Analysis of District Geothermal Heating and Cooling Systems

District geothermal heating and cooling systems (DGHCS) have significant benefits for reducing energy consumption as well as building- and grid-level peak electric demand. Currently, no publicly available tools are available to effectively design and conduct techno-economic analysis of DGHCS. GeoWISE was originally developed for preliminary design and techno-economic analysis of geothermal heating and cooling systems in an individual commercial or residential building. This paper introduces recent upgrades of GeoWISE that allow users to design and conduct techno-economic analysis of DGHCS. Several new features are implemented in GeoWISE to allow selection and specification of multiple new or existing buildings. A database of information for over 125 million existing U.S. buildings was used in GeoWISE that allows users easily locate existing buildings of interest based on street addresses, and optionally edit information of the buildings (e.g., footprint, vintage, principal functions, number of floors, window-to-wall ratio). Unique energy simulation models of the selected buildings are then automatically created using the Automatic Building Energy Modeling (AutoBEM) and EnergyPlus simulations are performed to predict thermal loads of the buildings. A simplified DGHCS is then designed and simulated to predict its energy use. A central borehole heat exchanger (BHE) of the DGHCS is sized using the RowWise algorithm of GHEDesigner to meet the thermal loads within user-specified land areas for installing BHE. The upgraded GeoWISE reports the needed capacity of heating and cooling equipment in each building, design of the central BHE, energy consumption reduction, and energy cost saving resulting from using DGHCS compared with conventional HVAC systems. A case study is showcased using the upgraded GeoWISE to design and conduct techno-economic analysis of a simplified DGHCS.

Prem Anand Jayaprabha, Jyothis Anand [ORNL] (ORCID↗
DOE OSTI2026

Control Room of the Future Testbed Workshop – After-Action Report

The U.S. Department of Energy’s Office of Electricity is supporting a one-year, multi-laboratory effort to define the needs and requirements for a Control Room of the Future testbed, or CROFT. The effort responds to increasing grid complexity driven by large new loads, dynamic generation resources, and the growing adoption of advanced technologies and tools, including artificial intelligence (AI) and machine learning (ML). To support safe, secure, and effective grid modernization, CROFT will focus on how emerging technologies and tools can be rigorously evaluated in realistic operational settings, with attention to human-machine interaction, cognitive load, and workforce readiness. The project team includes Argonne National Laboratory, Idaho National Laboratory, National Laboratory of the Rockies, and Pacific Northwest National Laboratory. As part of the scoping effort, the team conducted two industry-focused workshops: one at DTECH on February 5, 2026, informed by prior industry interviews, and a second on May 4, 2026, adjacent to IEEE T&D. These engagements brought together utilities, vendors, consultants, national laboratories, academia, and government stakeholders to identify and prioritize use cases, barriers, validation needs, data-sharing constraints, and near- and longer-term requirements. This feedback will directly inform CROFT’s architecture and research focus areas, ensuring the testbed is grounded in real-world operational needs and designed to evaluate emerging technologies and tools in realistic control-room environments.

artificial intelligence↗
NASA NTRS2001

Toward an Efficient Icing CFD Process Using an Interactive Software Toolkit: Smagglce 2D

Two-dimensional CID analysis for iced airfoils can be a labor-intensive task. The software toolkit SmaggIce 2D is being developed to help streamline the CID process and provide the unique features needed for icing. When complete, it will include a combination of partially automated and fully interactive tools for all aspects of the tasks leading up to the flow analysis: geometry preparation, domain decomposition. block boundary demoralization. gridding, and linking with a flow solver. It also includes tools to perform ice shape characterization, an important aid in determining the relationship between ice characteristics and their effects on aerodynamic performance. Completed tools, work-in-progress, and planned features of the software toolkit are presented here.

Vickerman, Mary B.↗
NASA NTRS2002

Toward an Efficient Icing CFD Process Using an Interactive Software Toolkit--SmaggIce 2D

Two-dimensional CFD analysis for iced airfoils can be a labor-intensive task. The software toolkit SmaggIce 2D is being developed to help streamline the CFD process and provide the unique features needed for icing. When complete, it will include a combination of partially automated and fully interactive tools for all aspects of the tasks leading up to the flow analysis: geometry preparation, domain decomposition, block boundary discretization. gridding, and linking with a flow solver. It also includes tools to perform ice shape characterization, an important aid in determining the relationship between ice characteristics and their effects on aerodynamic performance. Completed tools, work-in-progress, and planned features of the software toolkit are presented here.

Vickerman, Mary B.↗
NASA NTRSDate not supplied

Kamodo’s Satellite Constellation Mission Planning Tool

Kamodo provides a functional model-agnostic interface to a growing collection of Heliophysics model outputs. The CCMC, in collaboration with the Geospace Dynamics Constellation Science Team, has recently developed Kamodo’s satellite constellation mission planning tool to perform reconstructions in any pair of dimensions, including time. The ‘reconstruction’ tool enables users to fly any 4-dimensional grid of satellites through a given model data set, reconstructing what the given constellation would observe during the mission. This capability facilitates determination of what satellite configuration is best for a given science question, even allowing comparison across multiple models. This tool, written in Python, is built upon Kamodo’s flythrough tool, which in turn depends on a growing network of model-specific interfaces. Since each model interface is designed with model-agnostic syntax, the flythrough tool and the satellite constellation mission planning tool also feature model-agnostic syntax. In this work, we will describe the basic analysis choices available in the tool and provide a variety of sample workflows. The tool is freely available at https://github.com/nasa/Kamodo for the public. We invite the community to use the reconstruction tool and adapt the provided workflows for their mission planning, and to contribute their own workflows to share with others.

software↗
NASA NTRSDate not supplied

SM25C-2002: Kamodo’s Satellite Constellation Mission Planning Tool

Kamodo provides a functional model-agnostic interface to a growing collection of Heliophysics model outputs. The CCMC, in collaboration with the Geospace Dynamics Constellation Science Team, has recently developed Kamodo’s satellite constellation mission planning tool to perform reconstructions in any pair of dimensions, including time. The ‘reconstruction’ tool enables users to fly any 4-dimensional grid of satellites through a given model data set, reconstructing what the given constellation would observe during the mission. This capability facilitates determination of what satellite configuration is best for a given science question, even allowing comparison across multiple models. This tool, written in Python, is built upon Kamodo’s flythrough tool, which in turn depends on a growing network of model-specific interfaces. Since each model interface is designed with model-agnostic syntax, the flythrough tool and the satellite constellation mission planning tool also feature model-agnostic syntax. In this work, we will describe the basic analysis choices available in the tool and provide a variety of sample workflows. The tool is freely available at https://github.com/nasa/Kamodo for the public. We invite the community to use the reconstruction tool and adapt the provided workflows for their mission planning, and to contribute their own workflows to share with others.

python↗