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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 1,243 records · Page 69
All sourcesNASA NTRSDOE OSTI
NASA NTRS2004

An Interpolation Method for Obtaining Thermodynamic Properties Near Saturated Liquid and Saturated Vapor Lines

The two most common approaches used to formulate thermodynamic properties of pure substances are fundamental (or characteristic) equations of state (Helmholtz and Gibbs functions) and a piecemeal approach that is described in Adebiyi and Russell (1992). This paper neither presents a different method to formulate thermodynamic properties of pure substances nor validates the aforementioned approaches. Rather its purpose is to present a method to generate property tables from existing property packages and a method to facilitate the accurate interpretation of fluid thermodynamic property data from those tables. There are two parts to this paper. The first part of the paper shows how efficient and usable property tables were generated, with the minimum number of data points, using an aerospace industry standard property package. The second part describes an innovative interpolation technique that has been developed to properly obtain thermodynamic properties near the saturated liquid and saturated vapor lines.

Nguyen, Huy H.↗
NASA NTRS1985

Determination of rarefied-flow aerodynamics of the Shuttle orbiter from flight measurements on STS-6 and STS-7

This report presents the flight data results from the High Resolution Accelerometer Package (HiRAP) experimment on the sixth and seventh Shuttle missions (i.e. STS-6 and STS-7). The data have been reduced to produce aerodynamic force coefficients, principally L/D in the rarefied flow regime. Also, a technique is used to extract approximate body-axis aerodynamic coefficients from the flight data. Comparisons of the rarefied transition flow aerodynamic behavior between the two sets of flight data indicate differences, primarily in the free-molecule flow coefficients; i.e. STS-7 shows a free-molecule flow behavior which correlates with diffuse surface reflection conditions, while STS-6 does not. The data have also been used to estimate the density profiles in the atmosphere. The atmospheric density is generated from 60 to 160 km from each flight. The density profiles produced have a primary wave structure and differences are observed between the two sets of flight data. A new rarefied transitional flow aerodynamic bridging formula has been generated from the flight data. Comparisons with the flight bridging formula and existing Monte Carlo and wind-tunnel data are made.

Blanchard, R. C.↗
NASA NTRS1985

FIT: Computer Program that Interactively Determines Polynomial Equations for Data which are a Function of Two Independent Variables

A computer program for interactively developing least-squares polynomial equations to fit user-supplied data is described. The program is characterized by the ability to compute the polynomial equations of a surface fit through data that are a function of two independent variables. The program utilizes the Langley Research Center graphics packages to display polynomial equation curves and data points, facilitating a qualitative evaluation of the effectiveness of the fit. An explanation of the fundamental principles and features of the program, as well as sample input and corresponding output, are included.

Arbuckle, P. D.↗
NASA NTRS2012

Restoration and Reexamination of Data from the Apollo 11, 12, 14, and 15 Dust, Thermal and Radiation Engineering Measurements Experiments

As part of an effort by the Lunar Data Node (LDN) we are restoring data returned by the Apollo Dust, Thermal, and Radiation Engineering Measurements (DTREM) packages emplaced on the lunar surface by the crews of Apollo 11, 12, 14, and 15. Also commonly known as the Dust Detector experiments, the DTREM packages measured the outputs of exposed solar cells and thermistors over time. They operated on the surface for up to nearly 8 years, returning data every 54 seconds. The Apollo 11 DTREM was part of the Early Apollo Surface Experiments Package (EASEP), and operated for a few months as planned following emplacement in July 1969. The Apollo 12, 14, and 15 DTREMs were mounted on the central station as part of the Apollo Lunar Surface Experiments Package (ALSEP) and operated from deployment until ALSEP shutdown in September 1977. The objective of the DTREM experiments was to determine the effects of lunar and meteoric dust, thermal stresses, and radiation exposure on solar cells. The LDN, part of the Geosciences Node of the Planetary Data System (PDS), operates out of the National Space Science Data Center (NSSDC) at Goddard Space Flight Center. The goal of the LDN is to extract lunar data stored on older media and/or in obsolete formats, restore the data into a usable digital format, and archive the data with PDS and NSSDC. For the DTREM data we plan to recover the raw telemetry, translate the raw counts into appropriate output units, and then apply calibrations. The final archived data will include the raw, translated, and calibrated data and the associated conversion tables produced from the microfilm, as well as ancillary supporting data (metadata) packaged in PDS format.

McBride, Marie J.↗
NASA NTRS2001

Level 1 Processing of MODIS Direct Broadcast Data at the GSFC DAAC

The GSFC DAAC is working to test and package the MODIS Level 1 Processing software for Aqua Direct Broadcast data. This entails the same code base, but different lookup tables for Aqua and Terra. However, the most significant change is the use of ancillary attitude and ephemeris files instead of orbit/attitude information within the science data stream (as with Terra). In addition, we are working on Linux: ports of the algorithms, which could eventually enable processing on PC clusters. Finally, the GSFC DAAC is also working with the GSFC Direct Readout laboratory to ingest Level 0 data from the GSFC DB antenna into the main DAAC, enabling level 1 production in near real time in support of applications users, such as the Synergy project. The mechanism developed for this could conceivably be extended to other participating stations.

Lynnes, Christopher↗
DOE OSTI2025

Physics-informed machine learning for building performance simulation-A review of a nascent field

Building performance simulation (BPS) is critical for understanding building dynamics and behavior, analyzing the performance of the built environment, optimizing energy efficiency, improving demand flexibility, and enhancing building resilience. However, conducting BPS is not trivial. Traditional BPS relies on accurate building energy models, which are primarily physics-based and heavily dependent on detailed building information, expert knowledge, and case-by-case model calibrations, significantly limiting their scalability. With the development of sensing technology and the increased availability of data, there is growing attention and interest in data-driven BPS. However, purely data-driven models often suffer from limited generalization ability and a lack of physical consistency, resulting in poor performance in real-world applications. To address these limitations, recent studies have begun integrating physics priors into data-driven models, a methodology known as physics-informed machine learning (PIML). PIML is an emerging field where its definitions, methodologies, evaluation criteria, application scenarios, and future directions remain open. To bridge those gaps, this study systematically reviews the state-of-the-art PIML for BPS, offering a comprehensive definition of PIML and comparing it to traditional BPS approaches regarding data requirements, modeling effort, performance, and computational cost. We also summarize the commonly used methodologies, validation approaches, application domains, available data sources, open-source packages, and testbeds. In addition, this study provides a general guideline for selecting appropriate PIML models based on BPS applications. Finally, this study identifies key challenges and outlines future research directions, providing a solid foundation and valuable insights to advance R&D of PIML in BPS.

Jiang, Zixin↗
DOE OSTI2022

labquake_future_prediction

The labquake_future_prediction code is a collection of python modules and scripts that serves as supporting information for the article “Predicting future laboratory fault friction through deep learning” for publication in the journal of “Geophysical Research Letters”. It is designed to predict laboratory fault slips in the immediate future by scanning continuous acoustic emission (AE) waveforms recorded in laboratory biaxial shear experiments. The predictions are made with a deep learning model based on convolutional encoder-decoder (CED) models and the Transformer model primarily developed for Natural Language Processing (NLP). The deep learning model is trained with the tensorflow package using publicly available laboratory data sets in standard binary file format in numpy. The utility functions for reading data files, configuring model hyperparameters, constructing the CED and Transformer models, training and testing of the models are defined in python module files. The workflow of training the models for labquake future predictions and the multiple GPU’s rapid model hyperparameter optimization as described in the journal article, are demonstrated in accompanying python script files and Jupyter notebooks.

Wang, Kun↗
DOE OSTI2022

EQ_phase_detection

The EQ_phase_detection software is designed to scan continuous daily waveforms to detect earthquake phase arrivals from local to regional (150 km) events. The detections are made with a deep learning encoder-decoder model. When the model detects an earthquake in the waveforms, a second model is implemented to classify the first arriving motions. Both deep learning models are trained with the Tensorflow package using publicly available benchmark data sets. The software input is a path to a directory that contains waveforms in mseed format and the associated response files in xml format. The output is a data table of time stamped detections, signal amplitude, signal-to-noise ratio, and softmax probability of the detection in a generic format applicable to post-processing association algorithms for event locations. Additionally, the p-wave and s-wave waveforms are saved in a data table for rapid access when producing improved locations using correlation-based techniques. The software is designed for multiprocessing with multiple GPU’s for rapid processing of large data sets. The configuration file provides flexibility in the trained models implemented and allows access to multiple models trained for different sampling rates or input dimensions. This is particularly useful for regions with multiple networks that do not have the same data parameters.

Johnson, Christopher↗
DOE OSTI2025

Synapse v1.0

Synapse (SYNergistic software platform for AI, Physics Simulations, and Experiments) is a software package meant to deploy real-time guidance from simulations during experimental campaigns, The software package contains functionalities to collect data from simulations (e.g. running at NERSC) and experiments (e.g. from the BELLA facility at LBNL) into a database, train ML surrogate models from this data, and display the predictions of the surrogate model in the control room of an experimental facility, so as to guide on-going experimental campaign. This software was developed as part of an on-going LDRD.

Lehe, Remi [Lawrence Berkeley National Laboratory ↗
DOE OSTI2021

Real Time - Optimal Power Flow Based Distributed Energy Resources Management System (DERMS) (CRADA Number CRD-20-16909 Final Report)

The integration of behind-the-meter distributed energy resources (DERs) into distribution systems brings transformative changes to power systems. This requires operators and planners to find solutions to modernize electric grids and to effectively manage DERs for grid services. NREL developed novel DER management algorithms (referred to as Real-Time Optimal Power Flow, RT-OPF) through U.S. Department of Energy (DOE)-funded efforts, including Advanced Research Projects Agency–Energy (ARPA-E) Network Optimized Distributed Energy Systems (NODES) funding. This cutting-edge control technology aims to modernize distribution systems with large amounts of DER integration, which will help utilities solve issues brought by renewable integration and build resilient and renewable-based electric grids nationwide. Utilidata worked with NREL to investigate the commercialization opportunity of this RT-OPF-based distributed energy resource management system (DERMS). In this project, NREL performs the technology transfer of the RT-OPF to Utilidata to help them fully understand the RT-OPF solution, to identify potential engineering hurdles, and to assess the expected commercial value of various RT-OPF use cases and deployment. The technology transfer work includes two major tasks. First, NREL performs an in-depth knowledge transfer of the entire RT-OPF solution to Utilidata to help them gain an extensive and detailed understanding of the complete RT-OPF solution. In this task, NREL provides exhaustive information (e.g., documentation, code packages, laboratory and field trial data, performance results) while conducting in-depth training sessions to provide a thorough explanation of the entire solution. NREL hosts meetings to present different topics related to the RT-OPF solution, and question-and-answer sessions are included in each meeting to better explain the RT-OPF-related work. Second, the RT-OPF simulations are performed in a laboratory environment. The main objectives of this task are to walk through with Utilidata engineers how to set up a simulation of RT-OPF, identifying each RT-OPF code block/component in operation, learning how these components interact with each other, and eventually running RT-OPF simulations under various system conditions. This task helps Utilidata engineers understand performance limitations and constraints while also quantifying the commercial value of the RT-OPF for different use cases. Based on these two tasks, Utilidata engineers should be able to define and prioritize the next steps of RT-OPF implementation with an eye toward commercial success and scalability of the solution. The next steps are expected to be part of a new project following the conclusion of this project.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2023

PSY (PowerSystems.jl) [SWR-23-105]

PowerSystems.jl is a package to organize and manipulate data for the study of energy systems with diverse modeling requirements. This software serves two main purposes: to reduce the burden of large power system data set development, and to promote reproducible research and simulation. PowerSystems.jl implements an abstract hierarchy to represent and customize power systems data and includes data containers for quasi-static and dynamic simulation applications. Key features include efficient management of large quantities of time series data, optimized serialization, and comprehensive validation capabilities. For further information regarding the Sienna modeling framework at NREL, see: https://www.nrel.gov/analysis/sienna.html

Lara Aguilar, Jose Daniel↗
NASA NTRS1975

Detailed design package for design of a video system providing optimal visual information for controlling payload and experiment operations with television

A detailed description of a video system for controlling space shuttle payloads and experiments is presented in the preliminary design review and critical design review, first and second engineering design reports respectively, and in the final report submitted jointly with the design package. The material contained in the four subsequent sections of the package contains system descriptions, design data, and specifications for the recommended 2-view system. Section 2 contains diagrams relating to the simulation test configuration of the 2-view system. Section 3 contains descriptions and drawings of the deliverable breadboard equipment. A description of the recommended system is contained in Section 4 with equipment specifications in Section 5.

Source record↗
NASA NTRS1978

Ultraviolet photometry from the Orbiting Astronomical Observatory. XXVIII - Ultraviolet light curves for Alpha Lupi and BW Vulpeculae

Photometric data from the Wisconsin Experiment Package on OAO-2 have been used to construct light curves at three ultraviolet wavelengths for Alpha Lup and at seven wavelengths for BW Vul. Both stars are well-known variables of the Beta Cephei (Beta Canis Majoris) type. The light curves for Alpha Lup are in good agreement with the radial-velocity period. A temperature variation of 400-500 K is derived. The BW Vul light curves confirm recent ephemerides based on a secularly varying period and show a stillstand near light maximum at some wavelengths. Both stars exhibit increasing light amplitude at the shortest ultraviolet wavelengths. There is little evidence for cycle-to-cycle variations on a time scale of the order of 1 day.

Lesh, J. R.↗
NASA NTRS1978

The Space Shuttle Orbiter and aerodynamic testing

The concept of utilizing the Space Shuttle Orbiter as an aerodynamic flight research vehicle is discussed. The orbiter's planned flight frequency and its complex flight control system provide an unprecedented flight research potential. This paper defines the orbiter's flight environment and applicable baseline systems, their capabilities and limitations, as well as those instrument systems required to augment the baseline capability. These required systems, which are being developed under NASA's Orbiter Experiments Program (OEX) are the Aerodynamic Coefficient Identification Package (ACIP), Shuttle Entry Air Data System (SEADS), and the Shuttle Upper Atmosphere Mass Spectrometer (SUMS). Finally, the need for and capability of launching payloads from the orbiter to extend the research potential beyond the orbiter configuration and/or environment is defined.

Siemers, P. M., III↗
NASA NTRS1980

Solar-heating and cooling system design package

Package of information includes design data, performance specifications, drawings, hazard analysis, and spare parts list for commercially produced system installed in single-family dwelling in Akron, Ohio. System uses air flat-plate collectors, 12000 kg rock storage and backup heat pump. Solar portion requires 0.7 kW, and provides 35% of average total heating load including hot water. Information aids persons considering installing solar home-heating systems.

Source record↗
NASA NTRS1981

Integrated Analysis Capability pilot computer program

An integrated analysis capability (IAC) computer software package was developed for the design analysis and performance evaluation of large space systems. The IAC aids the user in coupling the required technical disciplines (initially structures, thermal and controls), providing analysis solution paths which reveal critical interactive effects in order to study loads, stability and mission performance. Existing technical software modules, having a wide existing user community, are combined with the interface software to bridge between the different technologies and mathematical modeling techniques. The package is supported by executive, data management and interactive graphics software, with primary development within the superminicomputer environment.

Vos, R. G.↗