Data correlation from investigations of a high- subsonic speed transport aircraft model in three major transonic wind tunnels.
C-5A aircraft model high subsonic speed tests, correlating data from three transonic wind tunnels
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C-5A aircraft model high subsonic speed tests, correlating data from three transonic wind tunnels
A sharp, smooth, 10-deg-included-angle cone was tested on twenty-one major wind tunnels of the United States and Western Europe to obtain correlation data on the effect of acoustic disturbances in wind tunnel flow on boundary layer transition Reynolds number. The cone is planned to be flight tested in order to obtain a basis of reference for the wind tunnel data over a nominal range of Mach numbers from 0.4 to approximately 2.0. Wind tunnel data obtained over a Mach number range from 0.2 to 4.6 are broadly characterized according to wind tunnel test section geometry and, in turn, to the types of acoustic disturbances associated with the geometry.
Handbook of correlative data on galactic cosmic rays, solar electromagnetic radiation, solar protons, geomagnetism, ionosphere, and neutral atmosphere
A modification to the Eigensystem Realization Algorithm (ERA) for modal parameter identification is presented in this paper. The ERA minimum order realization approach using singular value decomposition is combined with the philosophy of the Correlation Fit method in state space form such that response data correlations rather than actual response values are used for modal parameter identification. This new method, the ERA using data correlations (ERA/DC), reduces bias errors due to noise corruption significantly without the need for model overspecification. This method is tested using simulated five-degree-of-freedom system responses corrupted by measurement noise. It is found for this case that, when model overspecification is permitted and a minimum order solution obtained via singular value truncation, the results from the two methods are of similar quality.
The life of Hall Effect thrusters are primarily limited by plasma erosion and thermal related failures. NASA Glenn Research Center (GRC) in cooperation with the Jet Propulsion Laboratory (JPL) have recently completed development of a Hall thruster with specific emphasis to mitigate these limitations. Extending the operational life of Hall thursters makes them more suitable for some of NASA's longer duration interplanetary missions. This paper documents the thermal model development, refinement and correlation of results with thruster test data. Correlation was achieved by minimizing uncertainties in model input and recognizing the relevant parameters for effective model tuning. Throughout the thruster design phase the model was used to evaluate design options and systematically reduce component temperatures. Hall thrusters are inherently complex assemblies of high temperature components relying on internal conduction and external radiation for heat dispersion and rejection. System solutions are necessary in most cases to fully assess the benefits and/or consequences of any potential design change. Thermal model correlation is critical since thruster operational parameters can push some components/materials beyond their temperature limits. This thruster incorporates a state-of-the-art magnetic shielding system to reduce plasma erosion and to a lesser extend power/heat deposition. Additionally a comprehensive thermal design strategy was employed to reduce temperatures of critical thruster components (primarily the magnet coils and the discharge channel). Long term wear testing is currently underway to assess the effectiveness of these systems and consequently thruster longevity.
In this paper, we reinvestigate the solution for chaotic time series prediction problem using neural network approach. The nature of this problem is such that the data sequences are never repeated, but they are rather in chaotic region. However, these data sequences are correlated between past, present, and future data in high order. We use Cascade Error Projection (CEP) learning algorithm to capture the high order correlation between past and present data to predict a future data using limited weight quantization constraints. This will help to predict a future information that will provide us better estimation in time for intelligent control system. In our earlier work, it has been shown that CEP can sufficiently learn 5-8 bit parity problem with 4- or more bits, and color segmentation problem with 7- or more bits of weight quantization. In this paper, we demonstrate that chaotic time series can be learned and generalized well with as low as 4-bit weight quantization using round-off and truncation techniques. The results show that generalization feature will suffer less as more bit weight quantization is available and error surfaces with the round-off technique are more symmetric around zero than error surfaces with the truncation technique. This study suggests that CEP is an implementable learning technique for hardware consideration.
Hybrid cross correlation telemetry data processing system design for decoding pulse frequency modulation
The use of an orbiting antenna in a VLBI experiment complicates the data correlation, due to the spacecraft motion and the presence of the satellite-to-ground link. For this experiment, using a TDRSS satellite, a multistep method was used to calculate delay and phase for correlation and fringe-fitting. Data from three sources: 1510-089, NRAO 530 (1730-130), and 174l-038 were successfully correlated. The maximum projected baseline achieved was 1.4 earth diameters, for NRAO 530, with baselines longer than one earth diameter obtained for all three sources. Fringe visibilities for the maximum projected baselines were: 0.15 (1510-089), 0.05 (NRAO 530), and 0.50 (1741-038). The coherence of baselines to the orbiting antenna was 84 percent for 700 seconds. For a dedicated orbiting VLBI observatory (e.g., QUASAT), excellent coherence can be expected for integration times of several hundred seconds and observing frequencies as high as 20-30 GHz.
This paper introduces a general version of the information matrix consisting of the autocorrelation and cross-correlation matrices of the shifted input and output data. Based on the concept of data correlation, a new system realization algorithm is developed to create a model directly from input and output data. The algorithm starts by computing a special type of correlation matrix derived from the information matrix. The special correlation matrix provides information on the system-observability matrix and the state-vector correlation. A system model is then developed from the observability matrix in conjunction with other algebraic manipulations. This approach leads to several different algorithms for computing system matrices for use in representing the system model. The relationship of the new algorithms with other realization algorithms in the time and frequency domains is established with matrix factorization of the information matrix. Several examples are given to illustrate the validity and usefulness of these new algorithms.
A brief wind-tunnel/flight data correlation for the Boeing 737-100 airplane was made. The results showed excellent agreement between wind-tunnel and flight trimmed drag polars at Mach numbers less than 0.67. The wind-tunnel data predicted larger drag increments due to compressibility and a lift-curve slope about 9 percent higher than flight.
The quality of static pressure ports has historically been shown to be capable of biasing the resulting measurements of static pressure over the surface. Some of the flaws in the port quality can be recognized visually through magnified imaging of the port with a microscope. Through digital analyses of images of a large quantity of existing pressure ports and estimation of the deviations from the true static pressure for each port, a correlation could potentially be constructed to estimate whether a port will generate a significant error based upon its surface-level appearance. This presentation pursues this hypothesis through attempted correlation of subsonic data collected on the 4-inch-diameter cone cylinder during the 2019 characterization tests in the NASA Glenn Research Center's 8- by 6-Foot Supersonic Wind Tunnel (8x6 SWT).
Design of automatic data correlation system for Earth Resources Program
OGO 3 search coil magnetometer data correlated with magnetopause crossing by ATS 1 satellite, discussing OGO 3 crossing of outer magnetosphere into interplanetary medium
Program summary for implementation of automatic data correlation system for Earth Resources Program
The design, development, and testing of an engineering model nominal 20-millipound thrust monopropellant hydrazine resistojet program is divided into six basic tasks. Included in these tasks are analyses, design, test, and data correlation of the electrothermal hydrazine thruster (EHT). A brief summary is provided of the analyses conducted for the EHT and the design of the engineering model thruster. Some of the results of the engineering model tests are then compared with the analytical performance models generated early in the program.
Wind tunnel tests were conducted to determine the aerodynamic heating created by gaps in the reusable surface insulation (RSI) thermal protection system (TPS) for the space shuttle. The effects of various parameters of the RSI on convective heating characteristics are described. The wind tunnel tests provided a data base for accurate assessment of gap heating. Analysis and correlation of the data provide methods for predicting heating in the RSI gaps on the space shuttle.
Computer program plots flight test data /stored on magnetic tape during the flight/ with comparative data from other tapes /design and post-flight predictions/. Information as to which measurements are on each tape, the order in which they appear, and the exact time span is supplied by the source of the data.
Heat transfer data measured in gaps typical of those under consideration for joints in space shuttle reusable surface insulation protection systems have been assimilated, analyzed and correlated. The data were obtained in four NASA facilities. Several types of gaps were investigated with emphasis on simple butt joints. Gap widths ranged from 0.07 to 0.7 cm and depths ranged from 1 to 6 cm. Laminar, transitional and turbulent boundary layer flows over the gap opening were investigated. Three-dimensional heating variations were observed within gaps in the absence of external flow pressure gradients. Heat transfer correlation equations were obtained for several of the tests. Thermal protection system performance with and without gaps was compared for a representative shuttle entry trajectory.