SEARCH · Engineering Papers

Results for “DATA BASE MANAGEMENT”

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.

SourceResearch connectionFrom yearThrough year

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 937 records · Page 52

All sources NASA NTRS DOE OSTI

NASA NTRS1984

The Design and Usage of the New Data Management Features in NASTRAN

Two new data management features are installed in the April 1984 release of NASTRAN. These two features are the Rigid Format Data Base and the READFILE capability. The Rigid Format Data Base is stored on external files in card image format and can be easily maintained and expanded by the use of standard text editors. This data base provides the user and the NASTRAN maintenance contractor with an easy means for making changes to a Rigid Format or for generating new Rigid Formats without unnecessary compilations and link editing of NASTRAN. Each Rigid Format entry in the data base contains the Direct Matrix Abstraction Program (DMAP), along with the associated restart, DMAP sequence subset and substructure control flags. The READFILE capability allows an user to reference an external secondary file from the NASTRAN primary input file and to read data from this secondary file. There is no limit to the number of external secondary files that may be referenced and read.

Pamidi, P. R.↗

NASA NTRS1989

ATAM - Automated Trade Assessment Modeling

Automated Trade Assessment Modeling program, ATAM, one of software tools designed to assess candidate architectures for data-management system of Space Station. Designed to discriminate among candidates having equally acceptable performance and reliability characteristics. Utilizes data base, defined by user, containing information on candidate architecture. Assesses such trade factors of system as weight, power consumption, and life-cycle cost. Produces detailed parameter assessments as well as single figure of merit for candidate architecture. Written in Microsoft FORTRAN.

Vallone, Antonio↗

NASA NTRS1991

The Telecommunications and Data Acquisition Report

A compilation is presented of articles on developments in programs managed by JPL's Office of Telecommunications and Data Acquisition. In space communications, radio navigation, radio science, and ground based radio and radar astronomy, activities of the Deep Space Network are reported in planning, in supporting research and technology, in implementation, and in operations. Also included is standards activity at JPL for space data and information systems and reimbursable DSN work performed for other space agencies through NASA. In the search for extraterrestrial intelligence (SETI), implementation and operations are reported for searching the microwave spectrum.

Posner, Edward C.↗

NASA NTRS1994

ControlShell: A real-time software framework

The ControlShell system is a programming environment that enables the development and implementation of complex real-time software. It includes many building tools for complex systems, such as a graphical finite state machine (FSM) tool to provide strategic control. ControlShell has a component-based design, providing interface definitions and mechanisms for building real-time code modules along with providing basic data management. Some of the system-building tools incorporated in ControlShell are a graphical data flow editor, a component data requirement editor, and a state-machine editor. It also includes a distributed data flow package, an execution configuration manager, a matrix package, and an object database and dynamic binding facility. This paper presents an overview of ControlShell's architecture and examines the functions of several of its tools.

Schneider, Stanley A.↗

NASA NTRS1990

Method for concurrent execution of primitive operations by dynamically assigning operations based upon computational marked graph and availability of data

Computationally complex primitive operations of an algorithm are executed concurrently in a plurality of functional units under the control of an assignment manager. The algorithm is preferably defined as a computationally marked graph contianing data status edges (paths) corresponding to each of the data flow edges. The assignment manager assigns primitive operations to the functional units and monitors completion of the primitive operations to determine data availability using the computational marked graph of the algorithm. All data accessing of the primitive operations is performed by the functional units independently of the assignment manager.

Stoughton, John W.↗

NASA NTRSDate not supplied

Investigation and Evaluation of Advanced Spectrum Management Concepts for Aeronautical Communications

With the emergence of new aerial vehicles into the airspace and the continued growth of aviation operations, there will be an increasing demand for voice and data communications within the National Airspace System (NAS). The continued use of existing VHF and UHF frequency allocations is not a sustainable approach, and as a result, a new spectrum management solution is required to support future mission needs. The proposed spectrum management concepts leverage modern advancements such as artificial intelligence (AI) and big data to dynamically optimize the spectrum utilization based on the predicted communications demand throughout the airspace. This technical investigation considers both air-ground and air-air communications networks, and can be applied to both existing applications such as the air traffic control (ATC) system, as well as future applications, such as the emerging Advanced Air Mobility (AAM). To support the evaluation of the proposed concepts and technologies, a modeling and simulation capability is currently under development and will continue to evolve to support new and advanced airspace applications. It is anticipated that this proposed spectrum concept will better serve the spectrum needs of future NAS applications.

Eric J Knoblock↗

NASA NTRSDate not supplied

Investigation and Evaluation of Advanced Spectrum Management Concepts for Aeronautical Communications

Eric J Knoblock↗

NASA NTRS2015

Air Traffic Management Technology Demostration Phase 1 (ATD) Interval Management for Near-Term Operations Validation of Acceptability (IM-NOVA) Experiment

The Interval Management for Near-term Operations Validation of Acceptability (IM-NOVA) experiment was conducted at the National Aeronautics and Space Administration (NASA) Langley Research Center (LaRC) in support of the NASA Airspace Systems Program's Air Traffic Management Technology Demonstration-1 (ATD-1). ATD-1 is intended to showcase an integrated set of technologies that provide an efficient arrival solution for managing aircraft using Next Generation Air Transportation System (NextGen) surveillance, navigation, procedures, and automation for both airborne and ground-based systems. The goal of the IMNOVA experiment was to assess if procedures outlined by the ATD-1 Concept of Operations were acceptable to and feasible for use by flight crews in a voice communications environment when used with a minimum set of Flight Deck-based Interval Management (FIM) equipment and a prototype crew interface. To investigate an integrated arrival solution using ground-based air traffic control tools and aircraft Automatic Dependent Surveillance-Broadcast (ADS-B) tools, the LaRC FIM system and the Traffic Management Advisor with Terminal Metering and Controller Managed Spacing tools developed at the NASA Ames Research Center (ARC) were integrated into LaRC's Air Traffic Operations Laboratory (ATOL). Data were collected from 10 crews of current 757/767 pilots asked to fly a high-fidelity, fixed-based simulator during scenarios conducted within an airspace environment modeled on the Dallas-Fort Worth (DFW) Terminal Radar Approach Control area. The aircraft simulator was equipped with the Airborne Spacing for Terminal Area Routes (ASTAR) algorithm and a FIM crew interface consisting of electronic flight bags and ADS-B guidance displays. Researchers used "pseudo-pilot" stations to control 24 simulated aircraft that provided multiple air traffic flows into the DFW International Airport, and recently retired DFW air traffic controllers served as confederate Center, Feeder, Final, and Tower controllers. Analyses of qualitative data revealed that the procedures used by flight crews to receive and execute interval management (IM) clearances in a voice communications environment were logical, easy to follow, did not contain any missing or extraneous steps, and required the use of an acceptable workload level. The majority of the pilot participants found the IM concept, in addition to the proposed FIM crew procedures, to be acceptable and indicated that the ATD-1 procedures could be successfully executed in a nearterm NextGen environment. Analyses of quantitative data revealed that the proposed procedures were feasible for use by flight crews in a voice communications environment. The delivery accuracy at the achieve-by point was within +/-5 sec, and the delivery precision was less than 5 sec. Furthermore, FIM speed commands occurred at a rate of less than one per minute, and pilots found the frequency of the speed commands to be acceptable at all times throughout the experiment scenarios.

Kibler, Jennifer L.↗

NASA NTRS1993

AVIRIS and TIMS data processing and distribution at the land processes distributed active archive center

The U.S. Government has initiated the Global Change Research program, a systematic study of the Earth as a complete system. NASA's contribution of the Global Change Research Program is the Earth Observing System (EOS), a series of orbital sensor platforms and an associated data processing and distribution system. The EOS Data and Information System (EOSDIS) is the archiving, production, and distribution system for data collected by the EOS space segment and uses a multilayer architecture for processing, archiving, and distributing EOS data. The first layer consists of the spacecraft ground stations and processing facilities that receive the raw data from the orbiting platforms and then separate the data by individual sensors. The second layer consists of Distributed Active Archive Centers (DAAC) that process, distribute, and archive the sensor data. The third layer consists of a user science processing network. The EOSDIS is being developed in a phased implementation. The initial phase, Version 0, is a prototype of the operational system. Version 0 activities are based upon existing systems and are designed to provide an EOSDIS-like capability for information management and distribution. An important science support task is the creation of simulated data sets for EOS instruments from precursor aircraft or satellite data. The Land Processes DAAC, at the EROS Data Center (EDC), is responsible for archiving and processing EOS precursor data from airborne instruments such as the Thermal Infrared Multispectral Scanner (TIMS), the Thematic Mapper Simulator (TMS), and Airborne Visible and Infrared Imaging Spectrometer (AVIRIS). AVIRIS, TIMS, and TMS are flown by the NASA-Ames Research Center ARC) on an ER-2. The ER-2 flies at 65000 feet and can carry up to three sensors simultaneously. Most jointly collected data sets are somewhat boresighted and roughly registered. The instrument data are being used to construct data sets that simulate the spectral and spatial characteristics of the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) instrument scheduled to be flown on the first EOS-AM spacecraft. The ASTER is designed to acquire 14 channels of land science data in the visible and near-IR (VNIR), shortwave-IR (SWIR), and thermal-IR (TIR) regions from 0.52 micron to 11.65 micron at high spatial resolutions of 15 m to 90 m. Stereo data will also be acquired in the VNIR region in a single band. The AVIRIS and TMS cover the ASTER VNIR and SWIR bands, and the TIMS covers the TIR bands. Simulated ASTER data sets have been generated over Death Valley, California, Cuprite, Nevada, and the Drum Mountains, Utah using a combination of AVIRIS, TIMS, amd TMS data, and existing digital elevation models (DEM) for the topographic information.

Mah, G. R.↗

DOE OSTI2023

Building 438 Drainage Channel Soil Sampling and Analysis Plan (February 2023)

This Soil Sampling and Analysis Plan (SAP) was prepared by the Environmental Function Area (EFA)/Technical Services Department (TSD) of the Environment, Safety & Health (ES&H) Directorate for the Project Management Office (PMO) for the proposed Building 438 Drainage Channel Project (project) located near Building 438 (B438) in the southern portion, Building 433 (B433) in the middle portion, and Building 543 (B543) in the northern portion (project area as shown on Figure 1). The purpose of the SAP was to describe the procedures for collection and analysis of environmental samples and evaluation of analytical data (chemical and radiological) to determine management options of excavated soil during project construction in accordance with Lawrence Livermore National Laboratory’s (LLNL) Soils Screening and Management Plan (SSMP) (LLNL 2022), which is consistent with U.S. Environmental Protection Agency (EPA) guidance for developing Data Quality Objectives for environmental data (EPA 2006). The SAP was developed in accordance with the SSMP and based on preliminary design information provided to EFA by PMO.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2021

CSISAR--Complete System Integrated SAR

The CSISAR tool is GUI based and very simple to use. The algorithms are robust, and the unique processing flows, that the user is stepped through, virtually eliminate the possibility of error in GEOINT production. An integrated data manager is a key part of the CSISAR system. This data manager keeps track of the data available to a user and informs the user of what data is available and what can be done with that data. This keeps the user from having to be trained in the nuances of the algorithms. CSISAR also has an integrated product manager, which helps the user identify, view and manage previously made products. CSISAR was originally developed in 2010-2011 as a Windows based system. It was updated in 2015 to be a Linux based system. This SAND report is intended to make the Product Description and User’s Guide for CSISAR (originally included within the software) more widely available. New is a brief addition of Linux-specific installation details.

97 MATHEMATICS AND COMPUTING↗

NASA NTRS2022

Vermont & New Hampshire Ecological Forecasting: Monitoring Trends in Tree Defoliation Due to Lymantria dispar Outbreaks to Predict Future Hardwood Tree Mortality and Health Impacts

The invasive, herbivorous insect Lymantria dispar is a major defoliator of hardwood trees in the northeastern United States. Established populations of L. dispar typically rest at low levels but undergo recurring outbreaks that cause tree mortality if they occur in quick succession or are combined with other stressors on tree health. Widespread defoliation events disrupt local wildlife, economies, and livelihoods. Accurate monitoring of defoliation events is necessary to implement effective land management practices that support tree health. There are challenges to accurately monitoring L. dispar outbreaks that include the ephemeral character of defoliation disturbances and the difficulties of conducting large-scale surveys of L. dispar populations using existing aerial and ground-based data collection methods. To better monitor the impact of L. dispar on forests in Vermont and New Hampshire, the NASA DEVELOP team partnered with organizations responsible for supporting land and invasive species management including the Forest Ecosystem Monitoring Cooperative, the Vermont Agency of Agriculture, Food and Markets, the University of New Hampshire Cooperative Extension, and the New Hampshire Division of Forests and Lands, Forest Health Program. The team used NASA Earth observations collected by the Terra, Soil Moisture Active Passive (SMAP), Shuttle Radar Topography Mission (SRTM), Landsat 7, and Landsat 8 satellites along with ancillary datasets to map historical tree defoliation from 2012 to 2021. In support of partners’ future land management efforts, the team created a Google Earth Engine tool that displays annual defoliation extent.

Seamore Zhu↗

DOE OSTI2020

Enhanced Tensor Completion Based Approaches for State Estimation in Distribution Systems

Grid state estimation is essential for effective control and management of distribution systems. While weighted least squares has been the conventional method for state estimation, sparsity-aware methods have become popular due to their superior performance with limited data. Matrix completion and compressed sensing-based state estimation approaches exploit the underlying smoothness in the state variables. However, classic matrix completion methods do not take into account the temporal correlation of system states. Compressed sensing methods, on the other hand, require an appropriate choice of sparsifying basis that may not be easy to identify. This paper proposes a blocktensor completion based framework which uses an alternative approach to estimate voltage phasor, power injections and branch currents. This approach utilizes the temporal correlation of the system states in a tensor trace-norm minimization formulation with power flow equations as constraints. Herein, feature scaling is introduced in the problem formulation to benefit from the improved sensitivity of the tensor trace norm to the matrix columns in the scaled unfoldings of the tensor. Weighted tensor norm is utilized to exploit the structures of the different unfoldings of the state measurement tensor to improve the voltage estimation. The estimation accuracy is further improved by alternatively estimating the tensor columns and increasing the available data at each stage in the tensor completion process. The proposed methods are evaluated on the IEEE-33, 37 test systems and a 100- node test system. The proposed methods are shown to provide significant performance gains relative to the classic matrix and tensor completion based approaches.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2021

FEDFLEET: FY 2020 Fleet Data Submissions Status Update [Slides]

This presentation presents a brief overview of the current status of the collection of federal motor vehicle fleet data for fiscal year (FY) 2020 through the Federal Automotive Statistical Tool (FAST). FAST is a web-based information system sponsored by GSA's Office of Government-wide Policy and DOE's Federal Energy Management Program to collect information about the US federal government's fleet of motor vehicles. The presentation covers current status of data collection for FY 2020, the review and feedback process for those submissions, timeline of finalizing the information, and a preliminary high-level overview of the information.

99 GENERAL AND MISCELLANEOUS↗

DOE OSTI2021

FY 2020 Federal Fleet Data Submissions: Status Update [PowerPoint]

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

DOE OSTI2024

Scaling Ensembles of Data-Intensive Quantum Chemical Calculations for Millions of Molecules

Deep learning models are efficient computational tools that can accelerate the inverse design of molecules with desired functional properties by generating predictions at a fraction of the time required by traditional quantum chemical approaches. To ensure that a model maintains accuracy and transferability across broad regions of the chemical space explored during the inverse design, it must be trained on massively large volumes of simulation data. This requires running large-scale ensemble quantum chemical calculations on high-performance computing (HPC) systems for data collection. However, the efficient execution of such large ensemble calculations and the management of large volumes of output data require tools that can judiciously utilize computational resources and manage metadata overhead on the file system. Therefore, we present a high-performance, scalable, ensemble management framework for performing data-intensive quantum chemical electronic structure calculations for organic molecules. This framework provides abstractions to plug different ab initio, first principles, and first principles-based semi-empirical methods and executes them efficiently at large scale on HPC systems. It dynamically distributes tasks to resources and uses tiered storage for managing large collections of files. We employed this framework to process over ten million organic molecules and generate open-source datasets that provide UV-vis absorption spectra by running time-dependent density-functional tight-binding calculations. It is the largest database containing molecular optical spectra that were simulated with quantum chemical methods in a consistent manner.

Mehta, Kshitij↗

DOE OSTI2021

A Multirange Vehicle Speed Prediction With Application to Model Predictive Control-Based Integrated Power and Thermal Management of Connected Hybrid Electric Vehicles

Abstract Connectivity and automated driving technologies have opened up new research directions in the energy management of vehicles which exploit look-ahead preview and enhance the situational awareness. Despite this advancement, the vehicle speed preview that can be obtained from vehicle-to-vehicle/infrastructure (V2V/I) communications is often limited to a relatively short time-horizon. The vehicular energy systems, specifically those of the electrified vehicles, consist of multiple interacting power and thermal subsystems that respond over different time-scales. Consequently, their optimal energy management can greatly benefit from long-term speed prediction beyond that available through V2V/I communications. Accurately extending the look-ahead preview, on the other hand, is fundamentally challenging due to the dynamic nature of the traffic environment. To address this challenge, we propose a data-driven multirange vehicle speed prediction strategy for arterial corridors with signalized intersections, providing the vehicle speed preview for three different ranges, i.e., short-, medium-, and long-range. The short-range preview is obtained by V2V/I communications. The medium-range preview is realized using a neural network (NN), while the long-range preview is predicted based on a Bayesian network (BN). The predictions are updated in real-time based on the current state of traffic and incorporated into a multihorizon model predictive control (MH-MPC) for integrated power and thermal management (iPTM) of connected vehicles. The results of design and evaluation of the performance of the proposed data-informed MH-MPC for iPTM of connected hybrid electric vehicles (HEVs) using traffic data for real-world city driving are reported.

Automation & Control Systems↗

NASA NTRS1984

The Potential of AI Techniques for Remote Sensing

The current status of artificial intelligence AI technology is discussed along with imagery data management, database interrogation, and decision making. Techniques adapted from the field of artificial intelligence (AI) have significant, wide ranging impacts upon computer-assisted remote sensing analysis. AI based techniques offer a powerful and fundamentally different approach to many remote sensing tasks. In addition to computer assisted analysis, AI techniques can also aid onboard spacecraft data processing and analysis and database access and query.

J E Estes↗