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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 217 records · Page 12
All sourcesNASA NTRSDOE OSTI
NASA NTRS2023

A Remote Vehicle Operations Center’s Role in Collecting Human Factors Data

The National Aeronautics and Space Administration is supporting research to develop a prototype remote vehicle operations center at Langley Research Center to explore current and future advanced air mobility operations using small unmanned aerial systems vehicles as surrogates for future, larger-scale passenger carrying vehicles. Data collected within the Remote Operations for Autonomous Missions (ROAM) Unmanned Aerial Systems (UAS) Operations Center will be used to explore different roles and responsibilities of remote operators managing multiple autonomous vehicles, with the goal of exploring human-autonomy teaming concepts that enable m:N operations (i.e., m operators managing N vehicles). ROAM has developed into a world-class research, development, and technology (RD&T) environment that can support both the collection of human factors data and the command and control of remote vehicles in beyond visual line of sight conditions. Presented in this paper is an overview of ROAM, with a focus on the design components that support human factors data collection and a review of initial usability results of the facility.

Human factors↗
NASA NTRS1965

Gemini Program Mission Planning Report

This report defines the Gemini Program objectives and presents guidelines for the individual Gemini missions. It provides general space vehicle configuration data, and descriptions of planned missions. Contingency mission requirements and extravehicular operations to be performed during specific missions are described in the last two sections of the basic document. Data on spacecraft weights and Gemini Launch Vehicle performance capabilities are provided in Appendix A, while Appendix B provides descriptions of onboard experiments to be conducted during Gemini missions.

Source record↗
NASA NTRS1978

Load and dynamic assessment of B-52B-008 carrier aircraft for finned configuration 1 space shuttle solid rocket booster decelerator subsystem drop test vehicle. Volume 3: Pylon load data method 1

The pylon loading at the drop test vehicle and wing interface attach points is presented. The loads shown are determined using a stiffness method, which assumes the side stiffness of the foreward hook guide to be one-fourth of the fore and aft stiffness of each drag pin. The net effect of this assumption is that the forward hook guide reacts approximately 85% of the drop test vehicle yawing moment. For a comparison of these loads to previous X-15 analysis design loadings, see Volume 1 of this document.

Quade, D. A.↗
NASA NTRS1992

Free-decay time-domain modal identification for large space structures

Concept definition studies for the Modal Identification Experiment (MIE), a proposed space flight experiment for the Space Station Freedom (SSF), have demonstrated advantages and compatibility of free-decay time-domain modal identification techniques with the on-orbit operational constraints of large space structures. Since practical experience with modal identification using actual free-decay responses of large space structures is very limited, several numerical and test data reduction studies were conducted. Major issues and solutions were addressed, including closely-spaced modes, wide frequency range of interest, data acquisition errors, sampling delay, excitation limitations, nonlinearities, and unknown disturbances during free-decay data acquisition. The data processing strategies developed in these studies were applied to numerical simulations of the MIE, test data from a deployable truss, and launch vehicle flight data. Results of these studies indicate free-decay time-domain modal identification methods can provide accurate modal parameters necessary to characterize the structural dynamics of large space structures.

Kim, Hyoung M.↗
NASA NTRS2011

An Assessment of Ares I-X Aeroacoustic Measurements with Comparisons to Pre-Flight Wind Tunnel Test Results

During the recent successful launch of the Ares I-X Flight Test Vehicle, aeroacoustic data was gathered at fifty-seven locations along the vehicle as part of the Developmental Flight Instrumentation. Several of the Ares I-X aeroacoustic measurements were placed to duplicate measurement locations prescribed in pre-flight, sub-scale wind tunnel tests. For these duplicated measurement locations, comparisons have been made between aeroacoustic data gathered during the ascent phase of the Ares I-X flight test and wind tunnel test data. These comparisons have been made at closely matching flight conditions (Mach number and vehicle attitude) in order to preserve a one-to-one relationship between the flight and wind tunnel data. These comparisons and the current wind tunnel to flight scaling methodology are presented and discussed. The implications of using wind tunnel test data scaled under the current methodology to predict conceptual launch vehicle aeroacoustic environments are also discussed.

Nance, Donald K.↗
DOE OSTI2023

List Mode Data from the Modular Vehicle Detector System

In 2022 measurements were made with the Modular Vehicle Detectors (MVD) at the National Criticality Experiments Research Center (NCERC), located in the Device Assembly Facility (DAF) on the Nevada National Security Site (NNSS), Nevada. These detectors were supplied by the Naval Information Warfare Center (NIWC) Pacific. The MVDs were connected to an Advanced List Mode Module (ALMM) which records when an MVD detected a neutron. This is a summary of the measurement configurations as well as a list of the list-mode data files from each configuration. In addition to the measurements taken at NCERC additional measurements with the MVDs were taken at Los Alamos National Laboratory (LANL).

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
NASA NTRS1981

Axisymmetric & non-axisymmetric exhaust jet induced-effects on a V/STOL vehicle design. Part 1: Data presentation

A 1/8 scale jet-effects model was tested in the NASA Ames 11 ft transonic tunnel at static conditions and over a range of Mach numbers from 0.4 to 1.4. The data presented show that significant differences in aeropropulsion performance can be expected by varying the exhaust nozzle type and its geometric parameters on a V/STOL underwing nacelle installation.

Schnell, W. C.↗
NASA NTRS1990

Evaluation of two transport aircraft and several ground test vehicle friction measurements obtained for various runway surface types and conditions. A summary of test results from joint FAA/NASA Runway Friction Program

Tests with specially instrumented NASA Boeing 737 and 727 aircraft together with several different ground friction measuring devices were conducted for a variety of runway surface types and conditions. These tests are part of joint FAA/NASA Aircraft/Ground Vehicle Runway Friction Program aimed at obtaining a better understanding of aircraft ground handling performance under adverse weather conditions and defining relationships between aircraft and ground vehicle tire friction measurements. Aircraft braking performance on dry, wet, snow and ice-covered runway conditions is discussed as well as ground vehicle friction data obtained under similar runway conditions. For a given contaminated runway surface condition, the correlation between ground vehicles and aircraft friction data is identified. The influence of major test parameters on friction measurements such as speed, test tire characteristics, type and amount of surface contaminant, and ambient temperature are discussed. The effect of surface type on wet friction levels is also evaluated from comparative data collected on grooved and ungrooved concrete and asphalt surfaces.

Yager, Thomas J.↗
NASA NTRS2010

Large Field Photogrammetry Techniques in Aircraft and Spacecraft Impact Testing

The Landing and Impact Research Facility (LandIR) at NASA Langley Research Center is a 240 ft. high A-frame structure which is used for full-scale crash testing of aircraft and rotorcraft vehicles. Because the LandIR provides a unique capability to introduce impact velocities in the forward and vertical directions, it is also serving as the facility for landing tests on full-scale and sub-scale Orion spacecraft mass simulators. Recently, a three-dimensional photogrammetry system was acquired to assist with the gathering of vehicle flight data before, throughout and after the impact. This data provides the basis for the post-test analysis and data reduction. Experimental setups for pendulum swing tests on vehicles having both forward and vertical velocities can extend to 50 x 50 x 50 foot cubes, while weather, vehicle geometry, and other constraints make each experimental setup unique to each test. This paper will discuss the specific calibration techniques for large fields of views, camera and lens selection, data processing, as well as best practice techniques learned from using the large field of view photogrammetry on a multitude of crash and landing test scenarios unique to the LandIR.

Littell, Justin D.↗
NASA NTRS1976

Titan/Centaur D-1TTC-5 Helios B flight data report

The fourth operational flight of the newest NASA unmanned launch vehicle is reported. The spacecraft was the Helios B, the second of two solar probes designed and built by the Federal Republic of Germany. The primary mission objective, to place the Helios spacecraft on a heliocentric orbit in the ecliptic plane with a perihelion distance of 0.29 AU, was successfully accomplished. After successful injection of the Helios spacecraft, a series of experiments were performed with the Centaur stage to demonstrate its operational capabilities. All objectives of the extended mission phase were successfully met. This report presents the analysis of the launch vehicle flight data for the primary mission phase of the TC-5 flight.

Adams, K. A.↗
NASA NTRS1989

Current status of Joint FAA/NASA Runway Friction Program

Tests with specially instrumented NASA B-737 and FAA B-727 aircraft together with several different ground friction measuring devices have been conducted for a variety of runway surface types and wetness conditions. This effort is part of the Joint FAA/NASA Aircraft Ground Vehicle Runway Friction Program aimed at obaining a better understanding of aircraft ground handling performance under adverse weather conditions and defining relationships between aircraft and ground vehicle tire friction measurements. Aircraft braking performance on dry, wet, snow-, and ice-covered runway conditions is discussed together with ground vehicle friction data obtained under similar runway conditions. For the wet, compacted snow- and ice-covered runway conditions, the relationship between ground vehicles and aircraft friction data is identified. The influence of major test parameters on friction measurements such as speed, test tire characteristics, and surface contaminant type are discussed. The test results indicate that use of properly maintained and calibrated ground vehicles for monitoring runway friction conditions should be encouraged particularly under adverse weather conditions. The current status of the runway friction program is summarized and future test plans are identified.

Yager, Thomas J.↗
NASA NTRS1989

Aircraft and ground vehicle friction measurements obtained under winter runway conditions

Tests with specially instrumented NASA B-737 and B-727 aircraft together with several different ground friction measuring devices have been conducted for a variety of runway surface types and wetness conditions. This effort is part of the Joint FAA/NASA Aircraft/Ground Vehicle Runway Friction Program aimed at obtaining a better understanding of aircraft ground handling performance under adverse weather conditions, and defining relationships between aircraft and ground vehicle tire friction measurements. Aircraft braking performance on dry, wet, snow-, and ice-covered runway conditions is discussed together with ground vehicle friction data obtained under similar runway conditions. For the wet, compacted snow- and ice-covered runway conditions, the relationship between ground vehicles and aircraft friction data is identified. The influence of major test parameters on friction measurements such as speed, test tire characteristics, and surface contaminant-type are discussed. The test results indicate that use of properly maintained and calibrated ground vehicles for monitoring runway friction conditions should be encouraged particularly under adverse weather conditions.

Yager, Thomas J.↗
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]

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.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2025

Identifying Vehicle Signals in Continuous Seismic Data Using Unsupervised Machine-Learning Techniques

Seismic sensors deployed near roadways effectively capture ground vibrations generated by passing vehicles. Although both traditional and machine‐learning algorithms have been utilized for analyzing such signals, independent validation of detected vehicle events remains limited. We applied two unsupervised machine‐learning algorithms, uniform manifold approximation and projection for dimension reduction, and hierarchical density‐based spatial clustering of applications with noise, to continuous seismic data collected along a road on the main campus of Oak Ridge National Laboratory. The algorithms identified seven distinct cluster labels across the entire dataset. By comparing these cluster labels with precipitation records from a nearby weather station and image‐derived labels from a local camera system, we identified one cluster associated with rainfall and another with vehicle activity. Our algorithms identified a greater number of vehicle‐related labels compared to the camera‐derived labels because seismic data are unaffected by poor lighting conditions. The arrival times of the newly detected vehicle signals corresponded well with the road’s speed limit, supporting our findings. Our algorithm outperformed the short‐term average/long‐term average method and k‐means clustering. Our results suggest that seismic data, when analyzed with machine‐learning algorithms, can complement existing vehicle monitoring systems, particularly under challenging environmental conditions.

Chai, Chengping [Oak Ridge National Laboratory (OR↗