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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 109 records · Page 6
All sourcesNASA NTRSDOE OSTI
NASA NTRS1982

Comparative analysis of operational forecasts versus actual weather conditions in airline flight planning, volume 4

The impact of more timely and accurate weather data on airline flight planning with the emphasis on fuel savings is studied. This volume of the report discusses the results of Task 4 of the four major tasks included in the study. Task 4 uses flight plan segment wind and temperature differences as indicators of dates and geographic areas for which significant forecast errors may have occurred. An in-depth analysis is then conducted for the days identified. The analysis show that significant errors occur in the operational forecast on 15 of the 33 arbitrarily selected days included in the study. Wind speeds in an area of maximum winds are underestimated by at least 20 to 25 kts. on 14 of these days. The analysis also show that there is a tendency to repeat the same forecast errors from prog to prog. Also, some perceived forecast errors from the flight plan comparisons could not be verified by visual inspection of the corresponding National Meteorological Center forecast and analyses charts, and it is likely that they are the result of weather data interpolation techniques or some other data processing procedure in the airlines' flight planning systems.

Keitz, J. F.↗
NASA NTRS1982

The use of VAS satellite data in weather analysis, prediction and diagnosis

Imagery available with the Goes satellite visible-IR spin-scan radiometer (VISSR) atmospheric sounders (VAS) are examined in terms of mid- and low-tropospheric moisture sensing and mesoscale soundings. The VAS can be operated in a Dwell Sounding mode (DS) involving preprogrammed scanning of a specific area using any number of combinations of 12 channels between 4-15 microns. A second, multi-spectral imaging mode (MSI) comprises operation of two IR channels simultaneously when time constraints are in effect. Case studies are presented to demonstrate the effectiveness of VAS imagery for characterizing mesoscale moisture conditions when identifying severe storms. The moisture patterns of the upper and lower troposphere are made visible, and a 6.7 micron channel image can be overlaid on a low level moisture field to delineate fields of potential instability.

Petersen, R. A.↗
NASA NTRS2007

Methods of Attenuation Correction for Dual-Wavelength and Dual-Polarization Weather Radar Data

In writing the integral equations for the median mass diameter and number concentration, or comparable parameters of the raindrop size distribution, it is apparent that the forms of the equations for dual-polarization and dual-wavelength radar data are identical when attenuation effects are included. The differential backscattering and extinction coefficients appear in both sets of equations: for the dual-polarization equations, the differences are taken with respect to polarization at a fixed frequency while for the dual-wavelength equations, the differences are taken with respect to frequency at a fixed polarization. An alternative to the integral equation formulation is that based on the k-Z (attenuation coefficient-radar reflectivity factor) parameterization. This-technique was originally developed for attenuating single-wavelength radars, a variation of which has been applied to the TRMM Precipitation Radar data (PR). Extensions of this method have also been applied to dual-polarization data. In fact, it is not difficult to show that nearly identical equations are applicable as well to dualwavelength radar data. In this case, the equations for median mass diameter and number concentration take the form of coupled, but non-integral equations. Differences between this and the integral equation formulation are a consequence of the different ways in which attenuation correction is performed under the two formulations. For both techniques, the equations can be solved either forward from the radar outward or backward from the final range gate toward the radar. Although the forward-going solutions tend to be unstable as the attenuation out to the range of interest becomes large in some sense, an independent estimate of path attenuation is not required. This is analogous to the case of an attenuating single-wavelength radar where the forward solution to the Hitschfeld-Bordan equation becomes unstable as the attenuation increases. To circumvent this problem, the equations can be expressed in the form of a final-value problem so that the recursion begins at the far range gate and proceeds inward towards the radar. Solving the problem in this way traditionally requires estimates of path attenuation to the final gate: in the case of orthogonal linear polarizations, the attenuations at horizontal and vertical polarizations (same frequency) are required while in the dual-wavelength case, attenuations at the two frequencies (same polarization) are required.

Meneghini, R.↗
NASA NTRS2011

A Compilation of Space Shuttle Sonic Boom Measurements

Sonic boom measurements have been obtained on 26 flights of the Space Shuttle system beginning with the launch of STS-1 on April 12, 1981, to the reentry-descent of STS-41 into EAFB on Oct. 10, 1990. A total of 23 boom measurements were acquired within the focus region off the Florida coast during 3 STS launch-ascents and 113 boom measurements were acquired during 23 STS reentry-descent to landing into Florida and California. Sonic boom measurements were made under, and lateral to, the vehicle ground track and cover the Mach-altitude range of about 1.3 to 23 and 54,000 feet to 243,000 feet, respectively. Vehicle operational data, flight profiles and weather data were also gathered during the flights. This STS boom database is contained in 26 documents, some are formal and referenceable but most internal documents. Another 38 documents, also non-referenceable, contain predicted sonic boom footprints for reentry-descent flights on which no measurements were made. The purpose of this report is to provide an overview of the STS sonic boom database and summarize the main findings.

Maglieri, Domenic J.↗
NASA NTRS2011

A Compilation of Space Shuttle Sonic Boom Measurements - Supplemental STS Sonic Boom Files

Supplemental STS Sonic Boom Files for NASA/CR-2011-217080. Data files included on CDROM formatted to ISO 9660 standards. Sonic boom measurements have been obtained on 26 flights of the Space Shuttle system beginning with the launch of STS-1 on April 12, 1981, to the reentry-descent of STS-41 into EAFB on Oct. 10, 1990. A total of 23 boom measurements were acquired within the focus region off the Florida coast during 3 STS launch-ascents and 113 boom measurements were acquired during 23 STS reentry-descent to landing into Florida and California. Sonic boom measurements were made under, and lateral to, the vehicle ground track and cover the Mach-altitude range of about 1.3 to 23 and 54,000 feet to 243,000 feet, respectively. Vehicle operational data, flight profiles and weather data were also gathered during the flights. This STS boom database is contained in 26 documents, some are formal and referenceable but most internal documents. Another 38 documents, also non-referenceable, contain predicted sonic boom footprints for reentry-descent flights on which no measurements were made. The purpose of this report is to provide an overview of the STS sonic boom database and summarize the main findings.

Maglieri, Domenic J.↗
NASA NTRS2012

Benefits of Sharing Information from Commercial Airborne Forward-Looking Sensors in the Next Generation Air Transportation System

The air transportation system of the future will need to support much greater traffic densities than are currently possible, while preserving or improving upon current levels of safety. Concepts are under development to support a Next Generation Air Transportation System (NextGen) that by some estimates will need to support up to three times current capacity by the year 2025. Weather and other atmospheric phenomena, such as wake vortices and volcanic ash, constitute major constraints on airspace system capacity and can present hazards to aircraft if encountered. To support safe operations in the NextGen environment advanced systems for collection and dissemination of aviation weather and environmental information will be required. The envisioned NextGen Network Enabled Weather (NNEW) infrastructure will be a critical component of the aviation weather support services, providing access to a common weather picture for all system users. By taking advantage of Network Enabled Operations (NEO) capabilities, a virtual 4-D Weather Data Cube with aviation weather information from many sources will be developed. One new source of weather observations may be airborne forward-looking sensors, such as the X-band weather radar. Future sensor systems that are the subject of current research include advanced multi-frequency and polarimetric radar, a variety of Lidar technologies, and infrared imaging spectrometers.

Schaffner, Philip R.↗
NASA NTRS2017

The International Heat Stress Genotype Experiment for Modeling Wheat Response to Heat: Field Experiments and AgMIP-Wheat Multi-Model Simulations

The data set contains a portion of the International Heat Stress Genotype Experiment (IHSGE) data used in the AgMIP-Wheat project to analyze the uncertainty of 30 wheat crop models and quantify the impact of heat on global wheat yield productivity. It includes two spring wheat cultivars grown during two consecutive winter cropping cycles at hot, irrigated, and low latitude sites in Mexico (Ciudad Obregon and Tlaltizapan), Egypt (Aswan), India (Dharwar), the Sudan (Wad Medani), and Bangladesh (Dinajpur). Experiments in Mexico included normal (November-December) and late (January-March) sowing dates. Data include local daily weather data, soil characteristics and initial soil conditions, crop measurements (anthesis and maturity dates, anthesis and final total above ground biomass, final grain yields and yields components), and cultivar information. Simulations include both daily in-season and end-of-season results from 30 wheat models.

Wheat; Field Experimental Data; Heat Stress; Simul↗
NASA NTRS2017

Joint Eglin Acoustics Week 2013 Data Report

Far-field acoustic measurements were obtained for the AH-64D, HH-60M and CV-22B at the Eglin AFB, Test Area C-72, in July/August 2013. The primary purpose for this flight test was to obtain a benchmark database of detailed acoustic source noise characteristics for the aircraft operating at typical mission gross weights over a range of typical mission operating conditions. Data were acquired for a range of steady-state level and descending flight conditions, hover, and a variety of unsteady maneuver conditions. Between 30 and 37 microphones were deployed during these tests. Vehicle position and state data, as well as weather data were acquired simultaneously with the acoustic data. This paper describes the test aircraft, onboard instrumentation, ground instrumentation, and the data acquired. Data from this test are available upon request and review.

Conner, David A.↗
NASA NTRS2020

Development of a Display Tool to Quality Control Weather Balloon Data for Space Launch Vehicles Using Python

Continuous atmospheric data analysis is an important factor for space launch vehicle design and operations. The balloon quality control tool was developed by NASA’s Marshall Space Flight Center (MSFC) Natural Environments Branch (NEB) for monitoring quality control processes and verifying the automated flags created on the balloon data sets analyzed. The data sets currently analyzed are comprised of high-resolution and low-resolution balloon data from NASA Kennedy Space Center (KSC), co-located on the United States Air Force’s Eastern range (ER) at the Cape Canaveral Air Force Station. The NEB was tasked to perform a quality assessment of these data sets and needed a tool to confirm the quality control (QC) flags produced from an automated process and add additional QC flags if necessary. This Graphical User Interface (GUI) was developed to visualize all of the data from these balloon sets, display any flags from the automated QC process, and add additional flags to variables if necessary. The GUI was developed in Python 3.6 utilizing different packages available such as pandas for data analysis and manipulation, NumPy for high-performance multidimensional array and tools to compute with and manipulate arrays, Matplotlib for plotting data and Tkinter to build the GUI.

Jessica K Headley↗
NASA NTRS2020

Development of a Display Tool to Quality Control Weather Balloon Data for Space Launch Vehicles

Continuous atmospheric data analysis is an important factor for space launch vehicle design and operations. The balloon quality control tool was developed by NASA’s Marshall Space Flight Center (MSFC) Natural Environments Branch (NEB) for monitoring quality control processes and verifying the automated flags created on the balloon data sets analyzed. The data sets currently analyzed are comprised of high-resolution and low-resolution balloon data from NASA Kennedy Space Center (KSC), co-located on the United States Air Force’s Eastern range (ER) at the Cape Canaveral Air Force Station. The NEB was tasked to perform a quality assessment of these data sets and needed a tool to confirm the quality control (QC) flags produced from an automated process and add additional QC flags if necessary. This Graphical User Interface (GUI) was developed to visualize all of the data from these balloon sets, display any flags from the automated QC process, and add additional flags to variables if necessary. The GUI was developed in Python 3.6 utilizing different packages available such as pandas for data analysis and manipulation, NumPy for high-performance multidimensional array and tools to compute with and manipulate arrays, Matplotlib for plotting data and Tkinter to build the GUI.

Jessica K Headley↗
NASA NTRS1981

Airborne meteorological data-collection system

Aircraft position and weather data are collected, formatted, and relayed to ground from in-flight commercial jets. Data Acquisition and Control Unit in plane receives information from standard avionics data units, and provides scaling and storage. Normally, eight sets of data are acquired in 1 hour period and transmitted to satellite at precise time. Besides meteorological applications, system can locate and reroute aircraft into favorable winds to conserve fuel or aid search for downed planes.

Bagwell, J. W.↗
NASA NTRS2001

Convection Weather Detection by General Aviation Pilots with Convectional and Data-Linked Graphical Weather Information Sources

This study compares how well general aviation (GA) pilots detect convective weather in flight with different weather information sources. A flight test was conducted in which GA pilot test subjects were given different in-flight weather information cues and flown toward convective weather of moderate or greater intensity. The test subjects were not actually flying the aircraft, but were given pilot tasks representative of the workload and position awareness requirements of the en route portion of a cross country GA flight. On each flight, one test subject received weather cues typical of a flight in visual meteorological conditions (VMC), another received cues typical of flight in instrument meteorological conditions (IMC), and a third received cues typical of flight in IMC but augmented with a graphical weather information system (GWIS). The GWIS provided the subject with near real time data-linked weather products, including a weather radar mosaic superimposed on a moving map with a symbol depicting the aircraft's present position and direction of track. At several points during each flight, the test subjects completed short questionnaires which included items addressing their weather situation awareness and flight decisions. In particular, test subjects were asked to identify the location of the nearest convective cells. After the point of nearest approach to convective weather, the test subjects were asked to draw the location of convective weather on an aeronautical chart, along with the aircraft's present position. This paper reports preliminary results on how accurately test subjects provided with these different weather sources could identify the nearest cell of moderate or greater intensity along their route of flight. Additional flight tests are currently being conducted to complete the data set.

Chamberlain, James P.↗
NASA NTRS2000

Parallel integrated frame synchronizer chip

A parallel integrated frame synchronizer which implements a sequential pipeline process wherein serial data in the form of telemetry data or weather satellite data enters the synchronizer by means of a front-end subsystem and passes to a parallel correlator subsystem or a weather satellite data processing subsystem. When in a CCSDS mode, data from the parallel correlator subsystem passes through a window subsystem, then to a data alignment subsystem and then to a bit transition density (BTD)/cyclical redundancy check (CRC) decoding subsystem. Data from the BTD/CRC decoding subsystem or data from the weather satellite data processing subsystem is then fed to an output subsystem where it is output from a data output port.

Ghuman, Parminder Singh↗