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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 397 records · Page 22

All sources NASA NTRS DOE OSTI

DOE OSTI2024

gcamfaostat: An R package to prepare, process, and synthesize FAOSTAT data for global agroeconomic and multisector dynamic modeling

The gcamfaostat R package is designed for the preparation, processing, and synthesis of the Food and Agriculture Organization (FAO) Statistics (FAOSTAT) agroeconomic data. The primary purpose is to facilitate FAOSTAT data use in global economic and multisector dynamic models while ensuring transparency, traceability, and reproducibility. Here, we provide an overview of the development of gcamfaostat (v1.0) and demonstrate its capabilities in generating and maintaining agroeconomic data required for the Global Change Analysis Model (GCAM). Our initiative seeks to enhance the quality and accessibility of data for the global agroeconomic modeling community, with the aim of fostering more robust and harmonized outcomes in a collaborative, efficient, and open-source framework. One of the important features of the package is the possibility to construct the FAO Food Balance Sheets at the disaggregated commodity level (with over 500 commodities), which provides a comprehensive and detailed data input for a variety of analytical and modeling applications. The processed data and visualizations offered by gcamfaostat can also be valuable to a broader audience interested in gaining insights into the intricacies of global agriculture.

97 MATHEMATICS AND COMPUTING↗

NASA NTRS1989

Methods for local gravity field approximation

The most widely known modern method for estimating gravity field values from observed data is least-squares collocation. Its advantages are that it can make estimates at arbitrary locations based on irregularly spaced observations, and that it makes use of statistical information about errors in the input data while providing corresponding information about the quality of the output estimates. Disadvantages of collocation include the necessity of inverting square matrices of dimension equal to the number of data values and the need to assume covariance models for the gravity field and the data errors. Fourier methods are an important alternative to collocation; having the advantage of greater computational efficiency, but requiring data estimates to be on a regular grid and not using or providing statistical accuracy information. The GEOFAST algorithm is an implementation of collocation that achieves high computational efficiency by transforming the estimation equations into the frequency domain where an accurate approximation may be made to reduce the workload. The forward and inverse Fast Fourier Transforms (FFTs) are utilized. The accuracy and computational efficiency of the GEOFAST algorithm is demonstrated using two sets of synthetic gravity data: marine gravity for an ocean trench region including wavelengths longer than 200 km; and local land gravity containing wavelengths as short as 5 km. These results are discussed along with issues such as the advantages of first removing reference field models before carrying out the estimation algorithm.

Sailor, R. V.↗

NASA NTRS1989

First incremental buy for Increment 2 of the Space Transportation System (STS)

Thiokol manufactured and delivered 9 flight motors to KSC on schedule. All test flights were successful. All spent SRMs were recovered. Design, development, manufacture, and delivery of required transportation, handling, and checkout equipment to MSFC and to KSC were completed on schedule. All items of data required by DPD 400 were prepared and delivered as directed. In the system requirements and analysis area, the point of departure from Buy 1 to the operational phase was developed in significant detail with a complete set of transition documentation available. The documentation prepared during the Buy 1 program was maintained and updated where required. The following flight support activities should be continued through other production programs: as-built materials usage tracking on all flight hardware; mass properties reporting for all flight hardware until sample size is large enough to verify that the weight limit requirements were met; ballistic predictions and postflight performance assessments for all production flights; and recovered SRM hardware inspection and anomaly identification. In the safety, reliability, and quality assurance area, activities accomplished were assurance oriented in nature and specifically formulated to prevent problems and hardware failures. The flight program to date has adequately demonstrated the success of this assurance approach. The attention focused on details of design, analysis, manufacture, and inspection to assure the production of high-quality hardware has resulted in the absence of flight failures. The few anomalies which did occur were evaluated, design or manufacturing changes incorporated, and corrective actions taken to preclude recurrence.

Source record↗

NASA NTRS1992

Design of a precise and stable composite telescope structure for the Ultraviolet Coronagraph Spectrometer (UVCS)

The Ultraviolet Coronagraph Spectrometer is a state of the art instrument which will be flown aboard the ESA SOHO spacecraft in 1995. A major objective of the SOHO is to investigate the solar corona and the solar wind by measuring parameters of the plasma, both in the source and acceleration regions, and in interplanetary space. The UVCS will provide ultraviolet spectroscopic diagnostics of temperature, density, and outflow velocity for coronal ions located between the base of the solar corona and 10 solar radii. The requirements placed on the UVCS telescope structure by the science and the spacecraft are challenging. Obtaining this scientific data requires that the telescope maintain pointing stability within a few arc-seconds in a transient thermal environment and an imaging stability within a few microns. Strict mass allowances permit only 22 kg for the 2.5 meter long telescope structure out of a total instrument allotment of 124 kg. The instrument is required to have a high minimum natural frequency of 70 Hertz and withstand launch inertia loads in excess of 18-G's while kinematically supported.

Kilpatrick, Mark C.↗

NASA NTRS2000

Simple and Multiple Endmember Mixture Analysis in the Boreal Forest

Roberts, Dar A.↗

NASA NTRS2001

AVIRIS Land-Surface Mapping in Support of the Boreal Ecosystem-Atmosphere Study (BOREAS)

A key scientific objective of the original Boreal Ecosystem-Atmospheric Study (BOREAS) field campaign (1993-1996) was to obtain the baseline data required for modeling and predicting fluxes of energy, mass, and trace gases in the boreal forest biome. These data sets are necessary to determine the sensitivity of the boreal forest biome to potential climatic changes and potential biophysical feedbacks on climate. A considerable volume of remotely-sensed and supporting field data were acquired by numerous researchers to meet this objective. By design, remote sensing and modeling were considered critical components for scaling efforts, extending point measurements from flux towers and field sites over larger spatial and longer temporal scales. A major focus of the BOREAS follow-on program is concerned with integrating the diverse remotely sensed and ground-based data sets to address specific questions such as carbon dynamics at local to regional scales. The Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) has the potential of contributing to BOREAS through: (1) accurate retrieved apparent surface reflectance; (2) improved landcover classification; and (3) direct assessment of biochemical/biophysical information such as canopy liquid water and chlorophyll concentration through pigment fits. In this paper, we present initial products for major flux tower sites including: (1) surface reflectance of dominant cover types; (2) a land-cover classification developed using spectral mixture analysis (SMA) and Multiple Endmember Spectral Mixture Analysis (MESMA); and (3) liquid water maps. Our goal is to compare these land-cover maps to existing maps and to incorporate AVIRIS image products into models of photosynthetic flux.

Roberts, Dar A.↗

NASA NTRS2005

Lean Middleware

This paper describes an approach to achieving data integration across multiple sources in an enterprise, in a manner that is cost efficient and economically scalable. We present an approach that does not rely on major investment in structured, heavy-weight database systems for data storage or heavy-weight middleware responsible for integrated access. The approach is centered around pushing any required data structure and semantics functionality (schema) to application clients, as well as pushing integration specification and functionality to clients where integration can be performed on-the-fly .

Maluf, David A.↗

NASA NTRS2013

Human Machine Interface Programming and Testing

Human Machine Interface (HMI) Programming and Testing is about creating graphical displays to mimic mission critical ground control systems in order to provide NASA engineers with the ability to monitor the health management of these systems in real time. The Health Management System (HMS) is an online interactive human machine interface system that monitors all Kennedy Ground Control Subsystem (KGCS) hardware in the field. The Health Management System is essential to NASA engineers because it allows remote control and monitoring of the health management systems of all the Programmable Logic Controllers (PLC) and associated field devices. KGCS will have equipment installed at the launch pad, Vehicle Assembly Building, Mobile Launcher, as well as the Multi-Purpose Processing Facility. I am designing graphical displays to monitor and control new modules that will be integrated into the HMS. The design of the display screen will closely mimic the appearance and functionality of the actual modules. There are many different field devices used to monitor health management and each device has its own unique set of health management related data, therefore each display must also have its own unique way to display this data. Once the displays are created, the RSLogix5000 application is used to write software that maps all the required data read from the hardware to the graphical display. Once this data is mapped to its corresponding display item, the graphical display and hardware device will be connected through the same network in order to test all possible scenarios and types of data the graphical display was designed to receive. Test Procedures will be written to thoroughly test out the displays and ensure that they are working correctly before being deployed to the field. Additionally, the Kennedy Ground Controls Subsystem's user manual will be updated to explain to the NASA engineers how to use the new module displays.

Foster, Thomas Garrison↗

DOE OSTI2023

Blockchain for Fault-Tolerant Grid Operations

Radial topology and vast geographic coverage make distribution systems prone to widespread power outages upon the failure of a single (or multiple) upstream component. Fault-handling algorithms depend heavily on correct estimations of the system’s state to effectively isolate the affected area and reduce the number of affected customers while maintaining operational safety. The work described here leverages the core features of distributed, consensus-based decision-making processes and the immutability of blockchain, and demonstrates their value in improving fault-tolerant grid operations. In this work, blockchain was used to create a trusted data-sharing platform that enables independent actors to reconstruct the system state; this enables distributed resources to make intelligent decisions with limited knowledge. Although the process requires data sharing, its algorithms have been designed to limit the amount of private information that is exchanged, which helps preserve business-sensitive data and maintain customer privacy. In addition, by reducing the information that must be shared, the communication requirements are also reduced; (however, an in-depth analysis of the communication requirements is beyond the scope of this project). The proposed use cases are intended to represent a foundational basis for third parties to develop functional solutions that can eventually be deployed in the field. To further provide guidance, the envisioned use cases have incorporated design requirements that consider the blockchain characteristics and a need to limit information from surrounding resources, which preserve the assumption and the possibility that such resources could belong to different entities. This report presents a detailed design of the three use cases with the tools needed to enable the analysis being tested. The implemented gross error detection method can detect mismatches when the error exceeds 3.8 times the sensor’s rated accuracy. Detection of the circuit breaker state successfully identified the correct states across all simulation tests. A distribution-system power-flow solution in the simulator OpenDSS generally possesses a convergency tolerance of 0.01% on the voltage magnitude. The evaluation of possible reconnection using voltage magnitude—preserving the data ownership—has a voltage magnitude difference smaller than 0.001% from the OpenDSS result. The results preserving data ownership have a difference within the expected power flow tolerance with full knowledge of the system, which surpasses expectations.

24 POWER TRANSMISSION AND DISTRIBUTION↗

NASA NTRS2019

Reusing Data and Metadata to Create New Metadata Through Machine-Learning & Other Programmatic Methods

Recent improvements in natural language processing (NLP) enable metadata to be created programmatically from reused original metadata or even the dataset itself. Transfer-learning applied to NLP has greatly improved performance and reduced training data requirements. In this talk, we’ll compare machine-generated metadata to human-generated metadata and discuss characteristics of metadata and data archives that affect suitability for machine-learning reuse of metadata. Where as human-generated metadata is often populated once, populated from the perspective of data supplier, populated by many individuals with different words for the same thing, and limited in length, machine-generated metadata can be updated any number of times, generated from the perspective of any user, constrained to a standardized set of terms that can be evolved over time, and be any length required. Machine-learning generated metadata offers benefits but also additional needs in terms of version control, process transparency, human-computer interaction, and IT requirements. As a successful example, we’ll discuss how a dataset of abstracts and associated human-tagged keywords from a standardized list of several thousand keywords were used to create a machine-learning model that predicted keyword metadata for open-source code projects on code.nasa.gov. We’ll also discuss a less successful example from data.nasa.gov to show how data archive architecture and characteristics of initial metadata can be strong controls on how easy it is to leverage programmatic methods to reuse metadata to create additional metadata.

Gosses, Justin↗

NASA NTRS1988

Definition of common support equipment and space station interface requirements for IOC model technology experiments

A study was conducted to identify the common support equipment and Space Station interface requirements for the IOC (initial operating capabilities) model technology experiments. In particular, each principal investigator for the proposed model technology experiment was contacted and visited for technical understanding and support for the generation of the detailed technical backup data required for completion of this study. Based on the data generated, a strong case can be made for a dedicated technology experiment command and control work station consisting of a command keyboard, cathode ray tube, data processing and storage, and an alert/annunciator panel located in the pressurized laboratory.

Russell, Richard A.↗

DOE OSTI2021

AN AUTOMATED MACHINE LEARNING-GENETIC ALGORITHM FRAMEWORK WITH ACTIVE LEARNING FOR DESIGN OPTIMIZATION

The use of machine learning (ML)-based surrogate models is a promising technique to significantly accelerate simulation-driven design optimization of internal combustion (IC) engines, due to the high computational cost of running computational fluid dynamics (CFD) simulations. However, training the ML models requires hyperparameter selection, which is often done using trial-and-error and domain expertise. Another challenge is that the data required to train these models are often unknown a priori. In this work, we present an automated hyperparameter selection technique coupled with an active learning approach to address these challenges. The technique presented in this study involves the use of a Bayesian approach to optimize the hyperparameters of the base learners that make up a super learner model. In addition to performing hyperparameter optimization (HPO), an active learning approach is employed, where the process of data generation using simulations, ML training, and surrogate optimization is performed repeatedly to refine the solution in the vicinity of the predicted optimum. The proposed approach is applied to the optimization of a compression ignition engine with control parameters relating to fuel injection, in-cylinder flow, and thermodynamic conditions. It is demonstrated that by automatically selecting the best values of the hyperparameters, a 1.6% improvement in merit value is obtained, compared to an improvement of 1.0% with default hyperparameters. Overall, the framework introduced in this study reduces the need for technical expertise in training ML models for optimization while also reducing the number of simulations needed for performing surrogate-based design optimization.

Owoyele, Opeoluwa↗

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 OSTI2023

A Data Deposition Platform for Sharing Nuclear Magnetic Resonance Data

Nuclear magnetic resonance (NMR) data are rarely deposited in open databases, leading to loss of critical scientific knowledge. Existing data reporting methods (images, tables, lists of values) contain less information than raw data, and are poorly standardized. Together, these issues limit FAIR (findable, accessible, interoperable, reusable) access to these data, which in turn creates barriers for compound dereplication and the development of new data-driven discovery tools. Existing NMR databases are either not designed for natural products data, or employ complex deposition interfaces that disincentivize deposition. Journals, including the Journal of Natural Products (JNP), are now requiring data submission as part of the publication process, creating the need for a streamlined, user-friendly mechanism to deposit and distribute NMR data. Recently, our team reported the development of the Natural Products Magnetic Resonance Database (NP-MRD; www.np-mrd.org). Here in this paper we present a new data deposition platform for the NP-MRD project that is designed to enable users to deposit NMR data for published or submitted manuscripts in under five minutes. This platform includes a suite of automated data extraction and standardization tools, together with a simple-to-use web-based interface and detailed error reporting to simplify the data deposition process and is available at www.np-mrd.org/submissions.

96 KNOWLEDGE MANAGEMENT AND PRESERVATION↗

DOE OSTI2020

Finding, Organizing, and Preserving Legacy Nuclear Test Monitoring Data—Examples from the Livermore Nevada Network

A challenge for geophysical research is the relatively short time for which continuous digital data have been available. There are many events of research interest where much of the data were collected by analog or temporary digital means. These legacy data require special efforts to find, organize, and preserve for future research. Here, we focus on one type of legacy data, nuclear explosions, and associated events (e.g., collapses, aftershocks) of high interest for nuclear monitoring research and development. For nuclear tests conducted in Nevada, the Lawrence Livermore Nevada Network recorded valuable data on a variety of formats. In this article, we briefly review this network, and describe one set of data that previously was available via CD-ROM by request, and since 2018 has become available through Incorporated Research Institutions for Seismology as assembled dataset 18-001.

58 GEOSCIENCES↗

NASA NTRS1981

Objective analysis of observational data from the FGGE observing systems

An objective analysis procedure for updating the GLAS second and fourth order general atmospheric circulation models using observational data from the first GARP global experiment is described. The objective analysis procedure is based on a successive corrections method and the model is updated in a data assimilation cycle. Preparation of the observational data for analysis and the objective analysis scheme are described. The organization of the program and description of the required data sets are presented. The program logic and detailed descriptions of each subroutine are given.

Baker, W.↗

NASA NTRS1994

Using expert systems to analyze ATE data

The proliferation of automatic test equipment (ATE) is resulting in the generation of large amounts of component data. Some of this component data is not accurate due to the presence of noise. Analyzing this data requires the use of new techniques. This paper describes the process of developing an expert system to analyze ATE data and provides an example rule in the CLIPS language for analyzing trip thresholds for high gain/high speed comparators.

Harrington, Jim↗

NASA NTRS1995

Structural Optimization Methodology for Rotating Disks of Aircraft Engines

In support of the preliminary evaluation of various engine technologies, a methodology has been developed for structurally designing the rotating disks of an aircraft engine. The structural design methodology, along with a previously derived methodology for predicting low-cycle fatigue life, was implemented in a computer program. An interface computer program was also developed that gathers the required data from a flowpath analysis program (WATE) being used at NASA Lewis. The computer program developed for this study requires minimum interaction with the user, thus allowing engineers with varying backgrounds in aeropropulsion to successfully execute it. The stress analysis portion of the methodology and the computer program were verified by employing the finite element analysis method. The 10th- stage, high-pressure-compressor disk of the Energy Efficient Engine Program (E3) engine was used to verify the stress analysis; the differences between the stresses and displacements obtained from the computer program developed for this study and from the finite element analysis were all below 3 percent for the problem solved. The computer program developed for this study was employed to structurally optimize the rotating disks of the E3 high-pressure compressor. The rotating disks designed by the computer program in this study were approximately 26 percent lighter than calculated from the E3 drawings. The methodology is presented herein.

Armand, Sasan C.↗