SEARCH · Search NASA
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.
Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.
An update to a spacecraft transportation dynamic environments data base was developed based on data from recent transportation of spacecrafts. Vibration levels are significantly lower than those measured in 1966, while the shock response spectra are nearly the same. Ground shipping criteria and shipping practices, which have been very successful in preventing damage, are also summarized.
A revised gust-load formula with a new gust factor is derived to replace the gust-load formula and alleviation factor widely used in gust studies. The revised formula utilizes the same principles and retains the same simple form of the original formula but provides a more appropriate and acceptable basis for gust-load calculations. The gust factor is calculated on the basis of a one-minus-cosine gust shape and is presented as a function of a mass-ratio parameter in contrast to the ramp gust shape and wing loading, respectively, used for the alleviation factor. A summary of gust-velocity data from v-g records taken on civil transport airplanes from 1933 to 1950, reevaluated by the revised formula, is also presented.
MERRA-2 Stratospheric Composition Reanalysis of Aura Microwave Limb Sounder (M2-SCREAM) is a new reanalysis of stratospheric ozone, water vapor, hydrogen chloride (HCl), nitric acid (HNO 3 ) and nitrous oxide (N 2 O) between 2004 and the present (with a latency of several months). The assimilated fields are provided at a 50-km horizontal resolution and at a three-hourly frequency. M2-SCREAM assimilates version 4.2 Microwave Limb Sounder (MLS) profiles of the five constituents alongside total ozone column from the Ozone Monitoring Instrument. Dynamics and tropospheric water vapor are constrained by the MERRA-2 reanalysis. The assimilated species are in excellent agreement with the MLS observations, except for HNO 3 in polar night, where data are not assimilated. Comparisons against independent observations show that the reanalysis realistically captures the spatial and temporal variability of all the assimilated constituents. In particular, the standard deviations of the differences between M2-SCREAM and constituent mixing ratio data from The Atmospheric Chemistry Experiment Fourier Transform Spectrometer are much smaller than the standard deviations of the measured constituents. Evaluation of the reanalysis against aircraft data and balloon-borne frost point hygrometers indicates a faithful representation of small-scale structures in the assimilated water vapor, HNO 3 and ozone fields near the tropopause. Comparisons with independent observations and a process-based analysis of the consistency of the assimilated constituent fields with the MERRA-2 dynamics and with large-scale stratospheric processes demonstrate the utility of M2-SCREAM for scientific studies of chemical and transport variability on time scales ranging from hours to decades. Analysis uncertainties and guidelines for data usage are provided.
Low order equivalent system (LOES) models for the Tu-144 supersonic transport aircraft were identified from flight test data. The mathematical models were given in terms of transfer functions with a time delay by the military standard MIL-STD-1797A, "Flying Qualities of Piloted Aircraft," and the handling qualities were predicted from the estimated transfer function coefficients. The coefficients and the time delay in the transfer functions were estimated using a nonlinear equation error formulation in the frequency domain. Flight test data from pitch, roll, and yaw frequency sweeps at various flight conditions were used for parameter estimation. Flight test results are presented in terms of the estimated parameter values, their standard errors, and output fits in the time domain. Data from doublet maneuvers at the same flight conditions were used to assess the predictive capabilities of the identified models. The identified transfer function models fit the measured data well and demonstrated good prediction capabilities. The Tu-144 was predicted to be between level 2 and 3 for all longitudinal maneuvers and level I for all lateral maneuvers. High estimates of the equivalent time delay in the transfer function model caused the poor longitudinal rating.
Comparisons of airspeed, pressure altitude, and acceleration data between turbine and piston engine transport aircraft using NASA V-G and VGH recorders
We present the Point cLoud Algorithm for NEtwork Extraction of Discrete Fracture Networks (PLANE-DFN), a point cloud–based algorithm for automatic fracture network extraction designed to support discrete fracture network (DFN) modeling workflows. PLANE-DFN segments three-dimensional fracture planes from raw point cloud data using RANdom SAmple Consensus coupled with statistical outlier removal and density-based clustering to isolate individual fracture features. Each candidate plane is constrained against site-specific structural constraints based on strike and dip. After segmentation, each fracture is converted into a 2-D convex polygon suitable for meshing and simulation. The PLANE-DFN algorithm is validated by comparing geometric and flow and transport data against data from dfnWorks simulations with ensembles of plane-fit networks. We find that the flow and transport in plane-fit networks are comparable to dfnWorks-generated networks when realistic network geometry is maintained. The PLANE-DFN algorithm provides an automated and streamlined workflow to transform point clouds of data into DFN network geometry.
Crash deceleration pulse data from a crash dynamics program on general aviation airplanes and from transport crash data were analyzed. Structural airplane crash data and flight parameters at impact were correlated. Uncoupled equations for the normal and longitudinal floor impulses in the cabin area of the airplane were derived, and analytical expressions for structural crushing during impact and horizontal slide out were also determined. Agreement was found between experimental and analytical data for general aviation and transport airplanes over a relatively wide range of impact parameter. Two possible applications of the impulse data are presented: a postcrash evaluation of crash test parameters and an assumed crash scenario.
High data rate storage system B tape transport fits to existing hysteresis motor thus reducing flutter, lowering assembly cost, simplifying assembly process and increasing reliability. Motor may be used on any tape recorder or similar device having two speed ratio of up to 32 to 1.
Experimental data acquired over the past few years were gathered, and parametric fits made to these data. The following properties of electron transport were represented by simple functions of atomic number and energy: transmitted electron number, transmitted electron spectra, range, backscatter coefficient, angular distribution, energy deposition, bremsstrahlung intensity and energy spectra, and bremsstrahlung angular distribution and photon attenuation. The formulas cover the energy ranges of interest in space shielding problems (0.1 to 10.0 MeV). Procedures for using these formulas in practical situations are suggested.
Candidate data communication techniques are identified, including dedicated links, local buses, broadcast buses, multiplex buses, and mesh networks. The design methodology for mesh networks is then discussed, including network topology and node architecture. Several concepts of power distribution are reviewed, including current limiting and mesh networks for power. The technology issues of packaging, transmission media, and lightning are addressed, and, finally, the analysis tools developed to aid in the communication design process are described. There are special tools to analyze the reliability and connectivity of networks and more general reliability analysis tools for all types of systems.
An asynchronous, high-speed, fiber optic local area network originally developed for tactical environments with additional benefits for other environments such as spacecraft, and the like. The network supports ordinary data packet traffic simultaneously with synchronous T1 voice traffic over a common token ring channel; however, the techniques and apparatus of this invention can be applied to any deterministic class of packet data networks, including multitier backbones, that must transport stream data (e.g., video, SAR, sensors) as well as data. A voice interface module parses, buffers, and resynchronizes the voice data to the packet network employing elastic buffers on both the sending and receiving ends. Voice call setup and switching functions are performed external to the network with ordinary PABX equipment. Clock information is passed across network boundaries in a token passing ring by preceeding the token with an idle period of non-transmission which allows the token to be used to re-establish a clock synchronized to the data. Provision is made to monitor and compensate the elastic receiving buffers so as to prevent them from overflowing or going empty.
Astronauts are exposed to galactic cosmic rays (GCR), trapped protons, and possible solar particle events (SPE) during spaceflight. For such complicated mixtures of radiation types and kinetic energies, tissue equivalent proportional counters (TEPC's) represent a simple time-dependent approach for radiation monitoring. Of interest in radiation protection is the average quality factor of a radiation field defined as a function of linear energy transfer, LET, Q(sub ave)(LET). However TEPC's measure the average quality factors as a function of lineal energy (y), Q(sub ave)(y) defined as the average energy deposition in a volume divided by the average chord length of the volume. Lineal energy, y deviates from LET due to energy straggling, delta-ray escape or entry, and nuclear fragments produced in the detector. Using integrated space radiation models that includes the transport code HZETRN/BRYNTRN, the quantum nuclear interaction model, QMSFRG, and results from Monte-Carlo track simulations of TEPC's response to ions, we consider comparisons of model calculations to TEPC results from NASA missions in low Earth orbit and make predictions for lunar and Mars missions. Good agreement between the model and measured spectra from past NASA missions is found. A finding of this work is that TEPC's values for trapped or solar protons of Q(sub ave)(y) range from 1.9-2.5, overestimating Q(sub ave)(LET), which ranges from 1.4-1.6 with both quantities increasing with shielding depth due to nuclear secondaries Comparisons for the complete GCR spectra show that Q(sub ave)(LET) for GCR is approximately 3.5-4.5, while TEPC's measure 2.9-3.4 for Q(sub ave)(y) with the GCR values decreasing with depth as heavy ions are absorbed in shielding material. Our results support the use of TEPC's for space radiation environmental monitoring when computational analysis is used for proper data interpretation.
This document summarizes the progress of VTO Analysis projects supported during the fiscal year 2023. The VTO Analysis Program supports mission-critical technological, economic, and interdisciplinary analyses to assist in prioritizing VTO technology investments and to inform research portfolio planning. These efforts provide essential vehicle and market data, modeling and simulation, and integrated and applied analyses, using the unique capabilities, analytical tools, and expertise resident in the DOE’s national laboratory system. VTO Analysis projects also demonstrate additional capabilities and expertise provided by research partnerships that may include academia, the private sector, and non-profit organizations.
Spatial distributions of Saharan dust are simulated by the Goddard 3D chemistry transport model driven by meteorological fields from the Goddard Earth Observing System Data Assimilation System, GEOS-2 DAS. An aerosol module accounts for gravitational settling and the aerosol source function is based on surface moisture content and wind speed. The simulated aerosol fields are compared with Total Ozone Mapping Spectrometer (TOMS) by P. Ginoux in this session. The main focus is how ventilation of the assimilation winds will impact the simulated aerosol vertical distribution. Excessive ventilation would transport too much aerosol in the upper troposphere and lead to errors in the long range transport as well as errors in any radiative forcing calculations derived from the simulated aerosol fields. Simulated aerosol fields using GEOS-1 DAS wind fields for September 1994 will be compared with lidar observations during the Lidar In-space Technology Experiment (LITE). The lidar return signal clearly delineates the vertical extent and horizontal variability of the aerosol layer allowing rigorous comparison with the simulated fields. A second focus is the simulation of aerosol scavenging due to moist processes. Three-dimensional precipitation fields can be derived from two possible sources: Assimilated precipitation fields from GEOS-DAS or fields obtained from the Special Sensor Microwave/imager (SSM/1). Of interest is the sensitivity of the modeled aerosol fields to the different precipitation fields driving the moist scavenging module.
# 2013–2014 Greater Fairbanks, Alaska, Transportation Survey The 2013–2014 Greater Fairbanks Transportation Survey obtained behavior data for regional travel demand modeling. The planning region in Alaska comprised the North Star Borough—known as the PM2.5 nonattainment region—and included the cities of Fairbanks and North Pole. ## Data Collection Agency The Alaska Department of Transportation and Public Facilities conducted the survey. ## Methodology Data collection occurred in two phases: the first in fall 2013 and the second in winter 2014. The first phase employed address-based sampling to recruit more than 1,700 households for a one-day personal travel survey, and a sub-sample participated with global position system (GPS) and on-board diagnostic (OBD) loggers installed in their vehicles (282 vehicles) for one week. The purpose of phase one was to better understand the impact of vehicle emissions on air quality in the PM2.5 nonattainment region. Many of the households participating in the vehicle GPS/OBD portion of phase one were asked to participate in phase two. ## Drive Cycle Processing and Filtering NREL has developed a GPS data filtration routine to filter erroneous data points in individual drive cycles sourced from GPS devices mounted in vehicles. Second-by-second drive cycle data collected from GPS-instrumented vehicles during this survey have passed through NREL's drive cycle processing and filtering routines. ## Survey Records Survey records include 135 households. ## More Information For more information about the survey, see the [Greater Fairbanks Transportation Survey Final Report](https://www.nrel.gov/media/docs/libraries/tsdc/greater-fairbanks-transportation-survey-final-report.pdf?sfvrsn=16ecd45b_1). ## Transportation Data For details on available travel survey data and variable definitions, see the [data dictionary](https://www.nrel.gov/media/docs/libraries/tsdc/akdot_data_dictionary.pdf?sfvrsn=16778e11_1). NREL-generated drive cycle data are also available for this survey. For details on available data and variable definitions, see the [drive cycle data dictionary](https://www.nrel.gov/media/docs/libraries/tsdc/drive_cycles_data_dictionary.pdf?sfvrsn=7de7e888_1). Transportation data are available as zipped files. [Download Winzip](http://www.winzip.com/downwz.htm).
# 2013–2014 Greater Fairbanks, Alaska, Transportation Survey The 2013–2014 Greater Fairbanks Transportation Survey obtained behavior data for regional travel demand modeling. The planning region in Alaska comprised the North Star Borough—known as the PM2.5 nonattainment region—and included the cities of Fairbanks and North Pole. ## Data Collection Agency The Alaska Department of Transportation and Public Facilities conducted the survey. ## Methodology Data collection occurred in two phases: the first in fall 2013 and the second in winter 2014. The first phase employed address-based sampling to recruit more than 1,700 households for a one-day personal travel survey, and a sub-sample participated with global position system (GPS) and on-board diagnostic (OBD) loggers installed in their vehicles (282 vehicles) for one week. The purpose of phase one was to better understand the impact of vehicle emissions on air quality in the PM2.5 nonattainment region. Many of the households participating in the vehicle GPS/OBD portion of phase one were asked to participate in phase two. ## Drive Cycle Processing and Filtering NREL has developed a GPS data filtration routine to filter erroneous data points in individual drive cycles sourced from GPS devices mounted in vehicles. Second-by-second drive cycle data collected from GPS-instrumented vehicles during this survey have passed through NREL's drive cycle processing and filtering routines. ## Survey Records Survey records include 135 households. ## More Information For more information about the survey, see the [Greater Fairbanks Transportation Survey Final Report](https://www.nrel.gov/media/docs/libraries/tsdc/greater-fairbanks-transportation-survey-final-report.pdf?sfvrsn=16ecd45b_1). ## Transportation Data For details on available travel survey data and variable definitions, see the [data dictionary](https://www.nrel.gov/media/docs/libraries/tsdc/akdot_data_dictionary.pdf?sfvrsn=16778e11_1). NREL-generated drive cycle data are also available for this survey. For details on available data and variable definitions, see the [drive cycle data dictionary](https://www.nrel.gov/media/docs/libraries/tsdc/drive_cycles_data_dictionary.pdf?sfvrsn=7de7e888_1). Transportation data are available as zipped files. [Download Winzip](http://www.winzip.com/downwz.htm).
# 2013–2014 Greater Fairbanks, Alaska, Transportation Survey The 2013–2014 Greater Fairbanks Transportation Survey obtained behavior data for regional travel demand modeling. The planning region in Alaska comprised the North Star Borough—known as the PM2.5 nonattainment region—and included the cities of Fairbanks and North Pole. ## Data Collection Agency The Alaska Department of Transportation and Public Facilities conducted the survey. ## Methodology Data collection occurred in two phases: the first in fall 2013 and the second in winter 2014. The first phase employed address-based sampling to recruit more than 1,700 households for a one-day personal travel survey, and a sub-sample participated with global position system (GPS) and on-board diagnostic (OBD) loggers installed in their vehicles (282 vehicles) for one week. The purpose of phase one was to better understand the impact of vehicle emissions on air quality in the PM2.5 nonattainment region. Many of the households participating in the vehicle GPS/OBD portion of phase one were asked to participate in phase two. ## Drive Cycle Processing and Filtering NREL has developed a GPS data filtration routine to filter erroneous data points in individual drive cycles sourced from GPS devices mounted in vehicles. Second-by-second drive cycle data collected from GPS-instrumented vehicles during this survey have passed through NREL's drive cycle processing and filtering routines. ## Survey Records Survey records include 135 households. ## More Information For more information about the survey, see the [Greater Fairbanks Transportation Survey Final Report](https://www.nrel.gov/media/docs/libraries/tsdc/greater-fairbanks-transportation-survey-final-report.pdf?sfvrsn=16ecd45b_1). ## Transportation Data For details on available travel survey data and variable definitions, see the [data dictionary](https://www.nrel.gov/media/docs/libraries/tsdc/akdot_data_dictionary.pdf?sfvrsn=16778e11_1). NREL-generated drive cycle data are also available for this survey. For details on available data and variable definitions, see the [drive cycle data dictionary](https://www.nrel.gov/media/docs/libraries/tsdc/drive_cycles_data_dictionary.pdf?sfvrsn=7de7e888_1). Transportation data are available as zipped files. [Download Winzip](http://www.winzip.com/downwz.htm).
# 2013–2014 Greater Fairbanks, Alaska, Transportation Survey The 2013–2014 Greater Fairbanks Transportation Survey obtained behavior data for regional travel demand modeling. The planning region in Alaska comprised the North Star Borough—known as the PM2.5 nonattainment region—and included the cities of Fairbanks and North Pole. ## Data Collection Agency The Alaska Department of Transportation and Public Facilities conducted the survey. ## Methodology Data collection occurred in two phases: the first in fall 2013 and the second in winter 2014. The first phase employed address-based sampling to recruit more than 1,700 households for a one-day personal travel survey, and a sub-sample participated with global position system (GPS) and on-board diagnostic (OBD) loggers installed in their vehicles (282 vehicles) for one week. The purpose of phase one was to better understand the impact of vehicle emissions on air quality in the PM2.5 nonattainment region. Many of the households participating in the vehicle GPS/OBD portion of phase one were asked to participate in phase two. ## Drive Cycle Processing and Filtering NREL has developed a GPS data filtration routine to filter erroneous data points in individual drive cycles sourced from GPS devices mounted in vehicles. Second-by-second drive cycle data collected from GPS-instrumented vehicles during this survey have passed through NREL's drive cycle processing and filtering routines. ## Survey Records Survey records include 135 households. ## More Information For more information about the survey, see the [Greater Fairbanks Transportation Survey Final Report](https://www.nrel.gov/media/docs/libraries/tsdc/greater-fairbanks-transportation-survey-final-report.pdf?sfvrsn=16ecd45b_1). ## Transportation Data For details on available travel survey data and variable definitions, see the [data dictionary](https://www.nrel.gov/media/docs/libraries/tsdc/akdot_data_dictionary.pdf?sfvrsn=16778e11_1). NREL-generated drive cycle data are also available for this survey. For details on available data and variable definitions, see the [drive cycle data dictionary](https://www.nrel.gov/media/docs/libraries/tsdc/drive_cycles_data_dictionary.pdf?sfvrsn=7de7e888_1). Transportation data are available as zipped files. [Download Winzip](http://www.winzip.com/downwz.htm).