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Graphics data conditioning program expedites engineering analysis of flight data and ensures timely correction of measurement errors. By adding interactive computer graphic displays to existing data conditioning programs, computational results are immediately visible, enabling on-line intervention and control of computer processing.
Mariner scientific data conditioning system which gathers and prepares data to be transmitted back to earth
Spatial mapping of 1D, 2D, and particularly 3D thermal boundary condition data is essential for accurate thermal simulation of spacecraft and launch vehicles. This information typically is available in simple ASCII file format but can be problematic to use for thermal simulations. Difficulties that can be encountered include the ability to directly use the available file format, transformation of the data into the desired reference coordinate system in 3D space, and accurate interpolation of the data onto the thermal calculation domain. This paper presents a streamlined approach to spatial mapping of complex unsymmetrical 3D cold wall heat flux data using the fields’ capability in Simcenter3D. A recent example of 3D thermal plume simulation at MSFC will be employed to illustrate the use of text, csv, and Excel files, specifying coordinate systems for transformation of data in 3D space, and use of the various interpolation schemes available for spatial mapping. Spatial boundary condition verification is also very important, and the spacecraft thermal analyst needs effective visualization tools to develop confidence in the boundary condition definitions. Visualization of the spacecraft plume raw field data, the calculated field data, and the interpolated field data onto the thermal calculation domain will be discussed, with a particular focus on real-time viewing of the interpolated data for available interpolation schemes. The objective of this paper is to outline the modeling techniques used with the integrated thermal analysis of a terrestrial lunar lander demonstrator. Specifically, the techniques outlined herein focus on spatial mapping of convective and radiative exhaust plume results from a computational fluid dynamics (CFD) analysis. Two cases were investigated, however, the modeling techniques that were utilized translate to both cases seamlessly. Those two cases were as follows: • Lunar lander demonstrator firing on-pad (worst case). • Lunar lander demonstrator hovering at an elevated position above the launch pad. For the purposes of information control, this paper will focus on the modeling techniques only, using altered or dimensionless data where necessary. BACKGROUND The thermal model examined in this paper is of the lunar lander demonstrator known as XL-1T (terrestrial), born from a collaborative effort between Masten Space Systems (MSS) and NASA, under NASA’s Lunar CATALYST (also known as Lunar Cargo Transportation and Landing by Soft Touchdown) initiative. The lander is a reusable vertical takeoff/vertical landing (VTVL) test bed which is controlled by four throttleable main engines utilizing green hypergolic propellants.
We describe the Presearch Data Conditioning (PDC) software component and its context in the Kepler Science Operations Center (SOC) pipeline. The primary tasks of this component are to correct systematic and other errors, remove excess flux due to aperture crowding, and condition the raw flux light curves for over 160,000 long cadence (~thirty minute) and 512 short cadence (~one minute) targets across the focal plane array. Long cadence corrected flux light curves are subjected to a transiting planet search in a subsequent pipeline module. We discuss the science algorithms for long and short cadence PDC: identification and correction of unexplained (i.e., unrelated to known anomalies) discontinuities; systematic error correction; and excess flux removal. We discuss the propagation of uncertainties from raw to corrected flux. Finally, we present examples of raw and corrected flux time series for flight data to illustrate PDC performance. Corrected flux light curves produced by PDC are exported to the Multi-mission Archive at Space Telescope [Science Institute] (MAST) and will be made available to the general public in accordance with the NASA/Kepler data release policy.
Multiparameter monitoring visual displays for Apollo prelaunch checkout
Test matrix technique for checkout and launching of Apollo-Saturn spacecraft
Plasma wave data are compared with ISEE 1's position in the electron foreshock for an interval with unusually constant (but otherwise typical) solar wind magnetic field and plasma characteristics. For this period, temporal variations in the wave characteristics can be confidently separated from sweeping of the spatially varying foreshock back and forth across the spacecraft. The spacecraft's location, particularly the coordinate D(sub f) downstream from the foreshock boundary (often termed DIFF), is calculated by using three shock models and the observed solar wind magnetometer and plasma data. Scatterplots of the wave field versus D(sub f) are used to constrain viable shock models, to investigate the observed scatter in the wave fields at constant D(sub f), and to test the theoretical predictions of linear instability theory. The scatterplots confirm the abrupt onset of the foreshock waves near the upstream boundary, the narrow width in D(sub f) of the region with high fields, and the relatively slow falloff of the fields at large D(sub f), as seen in earlier studies, but with much smaller statistical scatter. The plots also show an offset of the high-field region from the foreshock boundary. It is shown that an adaptive, time-varying shock model with no free parameters, determined by the observed solar wind data and published shock crossings, is viable but that two alternative models are not. Foreshock wave studies can therefore remotely constrain the bow shock's location. The observed scatter in wave field at constant D(sub f) is shown to be real and to correspond to real temporal variations, not to unresolved changes in D(sub f). By comparing the wave data with a linear instability theory based on a published model for the electron beam it is found that the theory can account qualitatively and semiquantitatively for the abrupt onset of the waves near D(sub f) = 0, for the narrow width and offset of the high-field region, and for the decrease in wave intensity with increasing D(sub f). Quantitative differences between observations and theory remain, including large overprediction of the wave fields and the slower than predicted falloff at large D(sub f) of the wave fields. These differences, as well as the unresolved issue of the electron beam speed in the high-field region of the foreshock, are discussed. The intrinsic temporal variability of the wave fields, as well as their overprediction based on homogeneous plasma theory, are indicative of stochastic growth physics, which causes wave growth to be random and varying in sign, rather than secular.
The BOReal Ecosystem-Atmosphere Study Tower Flux (BOREAS TF-4) team collected energy, carbon dioxide, and water vapor flux data at the BOREAS Southern Study Area-Young Jack Pine (SSA-YJP) site during the growing season of 1994. In addition, meteorological data were collected both above and within the canopy. The data are available in tabular ASCII files.
No abstract available
A collection of computer programs for aircraft system identification is described and demonstrated. The programs, collectively called System IDentification Programs for AirCraft, or SIDPAC, were developed in MATLAB as m-file functions. SIDPAC has been used successfully at NASA Langley Research Center with data from many different flight test programs and wind tunnel experiments. SIDPAC includes routines for experiment design, data conditioning, data compatibility analysis, model structure determination, equation-error and output-error parameter estimation in both the time and frequency domains, real-time and recursive parameter estimation, low order equivalent system identification, estimated parameter error calculation, linear and nonlinear simulation, plotting, and 3-D visualization. An overview of SIDPAC capabilities is provided, along with a demonstration of the use of SIDPAC with real flight test data from the NASA Glenn Twin Otter aircraft. The SIDPAC software is available without charge to U.S. citizens by request to the author, contingent on the requestor completing a NASA software usage agreement.
Tests were performed on two spiral bevel gear sets in the NASA Glenn Spiral Bevel Gear Fatigue Test Rig to simulate the fielded failures of spiral bevel gears installed in a helicopter. Gear sets were tested until damage initiated and progressed on two or more gear or pinion teeth. During testing, gear health monitoring data was collected with two different health monitoring systems. Operational parameters were measured with a third data acquisition system. Tooth damage progression was documented with photographs taken at inspection intervals throughout the test. A software tool was developed for fusing the operational data and the vibration based gear condition indicator (CI) data collected from the two health monitoring systems. Results of this study illustrate the benefits of combining the data from all three systems to indicate progression of damage for spiral bevel gears. The tool also enabled evaluation of the effectiveness of each CI with respect to operational conditions and fault mode.
The DUNE experiment will produce vast amounts of metadata, which describe the data coming from the read-out of the primary DUNE detectors. Various databases will make up the overall DB architecture for this metadata. ProtoDUNE at CERN is the largest existing prototype for DUNE and serves as a testing ground for - among other things - possible database solutions for DUNE. The subset of all metadata that is accessed during offline data reconstruction and analysis is referred to as ‘conditions data’ and it is stored in a dedicated database. As offline data reconstruction and analysis will be deployed on HTC and HPC resources, conditions data is expected to be accessed at very high rates. It is therefore crucial to store it in a granularity that matches the expected access patterns allowing for extensive caching. This requires a good understanding of the sources and use cases of conditions data. This contribution will briefly summarize the database architecture deployed at ProtoDUNE and explain the various sources of conditions data. We will present how the conditions data is retrieved and streamed from the databases and how it is handled to match expected access patterns.
The DUNE experiment will produce vast amounts of metadata, which describe the data coming from the read-out of the primary DUNE detectors. Various databases will make up the overall DB architecture for this metadata. ProtoDUNE at CERN is the largest existing prototype for DUNE and serves as a testing ground for - among other things - possible database solutions for DUNE. The subset of all metadata that is accessed during offline data reconstruction and analysis is referred to as ‘conditions data’ and it is stored in a dedicated database. As offline data reconstruction and analysis will be deployed on HTC and HPC resources, conditions data is expected to be accessed at very high rates. It is therefore crucial to store it in a granularity that matches the expected access patterns allowing for extensive caching. This requires a good understanding of the sources and use cases of conditions data. This contribution will briefly summarize the database architecture deployed at ProtoDUNE and explain the various sources of conditions data. We will present how the conditions data is retrieved and streamed from the databases and how it is handled to match expected access patterns.
Data are presented to show the extent to which the maximum lift coefficient and consequently the minimum speed of an airplane, determined by flight tests, may vary with test conditions. The data show that cl-max may vary as much as 14 percent, depending on the altitude and wing loading at which the tests were made, the position or motion of the propeller, and the rate at which the angle of attack is changing when the maximum lift coefficient is obtained. The variation of the maximum lift coefficient with these factors, which are under the control of the test engineer, shows the need of standardizing the test procedure. A further variation is shown with wing conditions as affected by weathering and vibration, factors that cannot be completely controlled.
Graphical data from wind tunnel tests of variable cycle engine coannular exhaust nozzles are given. Specifically, aerodynamic data for takeoff conditions are presented.
This publication presents an annotated accident dataset which fuses traffic data from radar detection sensors, weather condition data, and light condition data with traffic accident data (as illustrated in Fig. 1) in a format that is easy to process using machine learning tools, databases, or data workflows. The purpose of this data is to analyze, predict, and detect traffic patterns when accidents occur. Each file contains a timeseries of traffic speeds, flows, and occupancies at the sensor nearest to the accident, as well as 5 neighboring sensors upstream and downstream. It also contains information about the accident type, date, and time. In addition to the accident data, we provide baseline data for typical traffic patterns during a given time of day. Overall, the dataset contains 6 months of annotated traffic data from November 2020 to April 2021. During this timeframe, and 361 accidents occurred in the monitored area around Chattanooga, Tennessee. This dataset served as the basis for a study on topology-aware automated accident detection for a companion publication [1].
Tabulated data from wind tunnel tests conducted to evaluate the aerodynamic performance of an advanced coannular exhaust nozzle for a future supersonic propulsion system are presented. Tests were conducted with two test configurations: (1) a short flap mechanism for fan stream control with an isentropic contoured flow splitter, and (2) an iris fan nozzle with a conical flow splitter. Both designs feature a translating primary plug and an auxiliary inlet ejector. Tests were conducted at takeoff and simulated cruise conditions. Data were acquired at Mach numbers of 0, 0.36, 0.9, and 2.0 for a wide range of nozzle operating conditions. At simulated supersonic cruise, both configurations demonstrated good performance, comparable to levels assumed in earlier advanced supersonic propulsion studies. However, at subsonic cruise, both configurations exhibited performance that was 6 to 7.5 percent less than the study assumptions. At takeoff conditions, the iris configuration performance approached the assumed levels, while the short flap design was 4 to 6 percent less. Data are provided through test run 25.
Data from the near-equatorial magnetosphere are analyzed by comparing the plasma composition during storm conditions with the composition during extended periods of low magnetic activity. It is found that at L less than or equal to 5, the O(+) is typically comparable to the H(+) in density and is often the dominant species, particularly during quiet times and at the inner edge of the region of significant fluxes. The He(+) in most cases contributes a significant fraction of the density and is sometimes the second most abundant species, following the O(+). Another finding is that both the He(+)/H(+) and the O(+)/H(+) ratios peak at the lowest L values and are, on the average, higher during quiet times than they are during the early main phase of major magnetic storms; this is seen as suggesting that charge exchange may be a significant loss process at low L. It is pointed out that the mean energies of the H(+), He(+), and O(+) ions often decrease gradually with decreasing L toward the inner edge of the energetic particle population.