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NASA NTRS2017

Pre-Test Assessment of the Upper Bound of the Drag Coefficient Repeatability of a Wind Tunnel Model

A new method is presented that computes a pre{test estimate of the upper bound of the drag coefficient repeatability of a wind tunnel model. This upper bound is a conservative estimate of the precision error of the drag coefficient. For clarity, precision error contributions associated with the measurement of the dynamic pressure are analyzed separately from those that are associated with the measurement of the aerodynamic loads. The upper bound is computed by using information about the model, the tunnel conditions, and the balance in combination with an estimate of the expected output variations as input. The model information consists of the reference area and an assumed angle of attack. The tunnel conditions are described by the Mach number and the total pressure or unit Reynolds number. The balance inputs are the partial derivatives of the axial and normal force with respect to all balance outputs. Finally, an empirical output variation of 1.0 microV/V is used to relate both random instrumentation and angle measurement errors to the precision error of the drag coefficient. Results of the analysis are reported by plotting the upper bound of the precision error versus the tunnel conditions. The analysis shows that the influence of the dynamic pressure measurement error on the precision error of the drag coefficient is often small when compared with the influence of errors that are associated with the load measurements. Consequently, the sensitivities of the axial and normal force gages of the balance have a significant influence on the overall magnitude of the drag coefficient's precision error. Therefore, results of the error analysis can be used for balance selection purposes as the drag prediction characteristics of balances of similar size and capacities can objectively be compared. Data from two wind tunnel models and three balances are used to illustrate the assessment of the precision error of the drag coefficient.

drag coefficient measurement↗

NASA NTRS1977

The estimation of pointing angle and normalized surface scattering cross section from GEOS-3 radar altimeter measurements

The statistical error of the pointing angle estimation technique is determined as a function of the effective receiver signal to noise ratio. Other sources of error are addressed and evaluated with inadequate calibration being of major concern. The impact of pointing error on the computation of normalized surface scattering cross section (sigma) from radar and the waveform attitude induced altitude bias is considered and quantitative results are presented. Pointing angle and sigma processing algorithms are presented along with some initial data. The intensive mode clean vs. clutter AGC calibration problem is analytically resolved. The use clutter AGC data in the intensive mode is confirmed as the correct calibration set for the sigma computations.

Brown, G. S.↗

NASA NTRS1986

On similarity solutions for turbulent and heated round jets

Commonly used empirical correlations for incompressible, heated round jets are shown to represent similarity solutions of the governing jet equations. These solutions give rise to self-similar eddy viscosities. Not all the similarity solutions are physically valid because some lead to zero eddy viscosities at the jet centerline. One physically valid solution is found to correlate best with round jet measurements and it gives a Gaussian error function description for the normalized mean velocity and temperature. Heat and momentum fluxes thus calculated are also in good agreement with measurements. Therefore, in addition to the classical similarity solution obtained by assuming constant eddy viscosity, another similarity solution to the jet equations is found where the eddy viscosity is self-similar.

So, R. M. C.↗

NASA NTRS2016

Mapping the Gas Turbulence in the Coma Cluster: Predictions for Astro-H

Astro-H will be able for the first time to map gas velocities and detect turbulence in galaxy clusters. One of the best targets for turbulence studies is the Coma cluster, due to its proximity, absence of a cool core, and lack of a central active galactic nucleus. To determine what constraints Astro-H will be able to place on the Coma velocity field, we construct simulated maps of the projected gas velocity and compute the second-order structure function, an analog of the velocity power spectrum. We vary the injection scale, dissipation scale, slope, and normalization of the turbulent power spectrum, and apply measurement errors and finite sampling to the velocity field. We find that even with sparse coverage of the cluster, Astro-H will be able to measure the Mach number and the injection scale of the turbulent power spectrum-the quantities determining the energy flux down the turbulent cascade and the diffusion rate for everything that is advected by the gas (metals, cosmic rays, etc.). Astro-H will not be sensitive to the dissipation scale or the slope of the power spectrum in its inertial range, unless they are outside physically motivated intervals. We give the expected confidence intervals for the injection scale and the normalization of the power spectrum for a number of possible pointing configurations, combining the structure function and velocity dispersion data. Importantly, we also determine that measurement errors on the line shift will bias the velocity structure function upward, and show how to correct this bias.

clusters: intracluster medium↗

NASA NTRS1989

An in-flight investigation of ground effect on a forward-swept wing airplane

A limited flight experiment was conducted to document the ground-effect characteristics of the X-29A research airplane. This vehicle has an aerodynamic platform which includes a forward-swept wing and close-coupled, variable incidence canard. The flight-test program obtained results for errors in the airdata measurement and for incremental normal force and pitching moment caused by ground effect. Correlations with wind-tunnel and computational analyses were made. The results are discussed with respect to the dynamic nature of the flight measurements, similar data from other configurations, and pilot comments. The ground-effect results are necessary to obtain an accurate interpretation of the vehicle's landing characteristics. The flight data can also be used in the development of many modern aircraft systems such as autoland and piloted simulations.

Curry, Robert E.↗

NASA NTRS1991

A control network of Triton

A control network for Triton has been computed using a bundle-type analytical triangulation program. The network contains 105 points that were measured on 57 Voyager-2 pictures. The adjustment contained 1010 observation equations and 382 normal equations and resulted in a standard measurement error of 13.36 microns. The coordinates of the control points, the camera orientation angles at the times when the pictures were taken, and Triton's mean radius were determined. A separate statistical analysis confirmed Triton's radius to be 1352.6 + or - 2.4 km. Attempts to tie the control network around the satellite were unsuccessful because discontinuities exist in high-resolution coverage between 66 deg and 289 deg longitude, north of 38 deg latitude, and south of 78 deg latitude.

Davies, Merton E.↗

DOE OSTI2024

Detecting Anomalies in Time Series Using Kernel Density Approaches

This paper introduces a novel anomaly detection approach tailored for time series data with exclusive reliance on normal events during training. Our key innovation lies in the application of kernel-density estimation (KDE) to scrutinize reconstruction errors, providing an empirically derived probability distribution for normal events post-reconstruction. This non-parametric density estimation technique offers a nuanced understanding of anomaly detection, differentiating it from prevalent threshold-based mechanisms in existing methodologies. In post-training, events are encoded, decoded, and evaluated against the estimated density, providing a comprehensive notion of normality. In addition, we propose a data augmentation strategy involving variational autoencoder-generated events and a smoothing step for enhanced model robustness. The significance of our autoencoder-based approach is evident in its capacity to learn normal representation without prior anomaly knowledge. Through the KDE step on reconstruction errors, our method addresses the versatility of anomalies, departing from assumptions tied to larger reconstruction errors for anomalous events. Our proposed likelihood measure then distinguishes normal from anomalous events, providing a concise yet comprehensive anomaly detection solution. The extensive experimental results support the feasibility of our proposed method, yielding significantly improved classification performance by nearly 10% on the UCR benchmark data.

Frehner, Robin↗

NASA NTRS1982

Dynamic modeling of structures from measured complex modes

A technique is presented to use a set of identified complex modes together with an analytical mathematical model of a structure under test to compute improved mass, stiffness and damping matrices. A set of identified normal modes, computed from the measured complex modes, is used in the mass orthogonality equation to compute an improved mass matrix. This eliminates possible errors that may result from using approximated complex modes as normal modes. The improved mass matrix, the measured complex modes and the higher analytical modes are then used to compute the improved stiffness and damping matrices. The number of degrees-of-freedom of the improved model is limited to equal the number of elements in the measured modal vectors. A simulated experiment shows considerable improvements, in the system's analytical dynamic model, over the frequency range of the given measured modal information.

Ibrahim, s. R.↗

NASA NTRS1985

Dynamic Modeling of Structures from Measured Complex Modes

Ibrahim, S. R.↗

NASA NTRS1987

Performability modeling based on real data: A casestudy

Described is a measurement-based performability model based on error and resource usage data collected on a multiprocessor system. A method for identifying the model structure is introduced and the resulting model is validated against real data. Model development from the collection of raw data to the estimation of the expected reward is described. Both normal and error behavior of the system are characterized. The measured data show that the holding times in key operational and error states are not simple exponentials and that a semi-Markov process is necessary to model the system behavior. A reward function, based on the service rate and the error rate in each state, is then defined in order to estimate the performability of the system and to depict the cost of different types of errors.

Hsueh, M. C.↗

NASA NTRS1988

Performability modeling based on real data: A case study

Described is a measurement-based performability model based on error and resource usage data collected on a multiprocessor system. A method for identifying the model structure is introduced and the resulting model is validated against real data. Model development from the collection of raw data to the estimation of the expected reward is described. Both normal and error behavior of the system are characterized. The measured data show that the holding times in key operational and error states are not simple exponentials and that a semi-Markov process is necessary to model system behavior. A reward function, based on the service rate and the error rate in each state, is then defined in order to estimate the performability of the system and to depict the cost of apparent types of errors.

Hsueh, M. C.↗

DOE OSTI2026

Integration of GOES Data for Solar Resource Assessment of the Contiguous United States

The National Solar Radiation Database (NSRDB), produced by the National Laboratory of the Rockies (NLR), provides high-resolution solar resource data for the contiguous United States (CONUS) using Geostationary Operational Environmental Satellite (GOES) East and West observations. This study evaluates the integration of multi-satellite data within the GOES-East/West overlap regions, where conventional longitude-based selection methods often produce an artificial boundary seam. Our results demonstrate that an advanced blending algorithm, which incorporates sun-satellite scattering angles and satellite viewing zenith angles, improves NSRDB accuracy and creates a spatially continuous dataset. Validation against ground-based irradiance measurements reveals reductions in both percentage error (PE) and normalized Root Mean Square Error (nRMSE), particularly in the central United States. The dynamical integration of multi-satellite data provides a robust foundation for more precise modeling of solar resource and improved spatiotemporal analysis of solar ramp across the CONUS.

14 SOLAR ENERGY↗

NASA NTRS1990

An in-flight investigation of ground effect on a forward-swept wing airplane

A limited flight experiment was conducted to document the ground effect characteristics of the X-29A research aircraft. This vehicle has an aerodynamic platform which includes a forward-swept wing and close-coupled, variable incidence canard. The flight-test program obtained results for errors in the air data measurement and for incremental normal force and pitching moment caused by ground effect. Correlations with wind-tunnel and computational analyses were made. The results are discussed with respect to the dynamic nature of the flight measurements, similar data from other configurations, and pilot comments. The ground effect results are necessary to obtain an accurate interpretation of the vehicle's landing characteristics. The flight data can also be used in the development of many modern aircraft systems such as autoland and piloted simulation.

Curry, Robert E.↗

NASA NTRS2000

A Factorial Data Rate and Dwell Time Experiment in the National Transonic Facility

This report is an introductory tutorial on the application of formal experiment design methods to wind tunnel testing, for the benefit of aeronautical engineers with little formal experiment design training. It also describes the results of a Study to determine whether increases in the sample rate and dwell time of the National Transonic Facility data system Would result in significant changes in force and moment data. Increases in sample rate from 10 samples per second to 50 samples per second were examined, as were changes in dwell time from one second per data point to two seconds. These changes were examined for a representative aircraft model in a range of tunnel operating conditions defined by angles of attack from 0 deg to 3.8 degrees, total pressure from 15.0 psi to 24.1 psi, and Mach numbers from 0.52 to 0.82. No statistically significant effect was associated with the change in sample rate. The change in dwell time from one second to two seconds affected axial force measurements, and to a lesser degree normal force measurements. This dwell effect comprises a "rectification error" caused by incomplete cancellation of the positive and negative elements of certain low frequency dynamic components that are not rejected by the one-Hz low-pass filters of the data system. These low frequency effects may be due to tunnel circuit phenomena and other sources. The magnitude of the dwell effect depends on dynamic pressure, with angle of attack and Mach number influencing the strength of this dependence. An analysis is presented which suggests that the magnitude of the rectification error depends on the ratio of measurement dwell time to the period of the low-frequency dynamics, as well as the amplitude of the dynamics The essential conclusion of this analysis is that extending the dwell time (or, equivalently, replicating short-dwell data points) reduces the rectification error.

DeLoach, R.↗

NASA NTRS2002

Phase-Shifting Liquid Crystal Interferometers for Microgravity Fluid Physics

The initial focus of this project was to eliminate both of these problems in the Liquid Crystal Point-Diffraction Interferometer (LCPDI). Progress toward that goal will be described, along with the demonstration of a phase shifting Liquid Crystal Shearing Interferometer (LCSI) that was developed as part of this work. The latest LCPDI, other than a lens to focus the light from a test section onto a diffracting microsphere within the interferometer and a collimated laser for illumination, the pink region contained within the glass plates on the rod-mounted platform is the complete interferometer. The total width is approximately 1.5 inches with 0.25 inches on each side for bonding the electrical leads. It is 1 inch high and there are only four diffracting microspheres within the interferometer. As a result, it is very easy to align, achieving the first goal. The liquid crystal electro-optical response time is a function of layer thickness, with thinner devices switching faster due to a reduction in long-range viscoelastic forces between the LC molecules. The LCPDI has a liquid crystal layer thickness of 10 microns, which is controlled by plastic or glass microspheres embedded in epoxy 'pads' at the corners of the device. The diffracting spheres are composed of polystyrene/divinyl benzene polymer with an initial diameter of 15 microns. The spheres deform slightly when the interferometer is assembled to conform to the spacing produced by the microsphere-filled epoxy spacer pads. While the speed of this interferometer has not yet been tested, previous LCPDIs fabricated at the Laboratory for Laser Energetics switched at a rate of approximately 3.3 Hz, a factor of 10 slower than desired. We anticipate better performance when the speed of these interferometers is tested since they are approximately three times thinner. Phase shifting in these devices is a function of the AC voltage level applied to the liquid crystal. As the voltage increases, the dye in the liquid crystal tends to become more transparent, thus introducing a rather large amount of error into the phase-shifting measurement. While that error can be greatly reduced by normalization, we prefer eliminating the source of the error. To that end, we have pursued development of a 'blend' of custom dyes that will not exhibit these properties. That goal has not yet been fully achieved. Guardalben, et al, presented a similar set of interferograms in a paper partially funded by this grant. Shearing interferometers are a second class of common path interferometers. Typically they consist of a thick glass plate optimized for equal reflection from the front and back surface. While not part of the original thrust of the project, through the course of laboratory work, we demonstrated a prototype of a shearing interferometer capable of phase shifting using a commercial liquid crystal retardation plate. A schematic of this liquid crystal shearing interferometer (LCSI) and a sample set of interferograms are in the reference. This work was also supported by the U.S. Department of Energy Office of Inertial Confinement Fusion under Cooperative Agreement No. DE-FC03-92SF19460, the University of Rochester, and the New York State Energy Research and Development Authority. The support of DOE does not constitute an endorsement by DOE of the views expressed in this article. Additional information is included in the original extended abstract.

Griffin, DeVon W.↗

NASA NTRS1987

A method for remote sensing the emissivity, fractional cloud cover and cloud top temperature of high-level, thin clouds

A methodology for retrieving the emissivity, cloud cover and cloud top temperature of high-level, thin clouds is developed and described. In the thermal infrared windows, the outgoing radiances from the earth's atmosphere contain information about cloud emissivity and cloud top temperature. This information is clearly demonstrated in the brightness temperature difference curves of two window channels. For the purpose of illustration, two window channels centered at 810 and 930 cm are chosen to construct the brightness temperature difference curves for a range of cloud top temperatures. These curves vary for different cloud top temperatures, and along each of these curves the emissivity changes. The brightness temperature difference method is used in a simulation study to demonstrate the feasibility of retrieving the cloud top temperature and emissivity by the utilization of measurements in two window channels. As expected, a perfect retrieval is found if perfect measurements and ideal atmospheric conditions are assumed. If a random error, which has a normal distribution with a mean of zero and standard deviation of + or - 0.5 C, is imposed to the measurements, a reasonable retrieval is found for emissivity greater than 0.3. The algorithm has been applied to a limited amount of HIRS2 data, which has 3.7, 3.98 and 11 micron channels. The cloud top temperature, emissivity and cloud cover are determined by using these channels.

Wu, Man-Li C.↗

DOE OSTI2020

Effective Missing Value Imputation Methods for Building Monitoring Data

To understand behaviors of natural and man-made events, such as energy consumption of buildings, which accounts for 40% of energy uses in the US, we deploy automated monitoring devices to record periodic observations. However, such experimental and observation data often contains problems and irregularities that have to be cleaned up before analyses. Due to various conditions affecting sensor operations, the communication channels, recording steps, or the recording media, the recorded data might have missing values, errors, or anomalous values. An effective way to clean up these problems is to replace these missing values, errors and anomalous values with expected values, a process generally known as imputation. In this work, we survey commonly used missing value imputation techniques and compare their performance on a set of building monitoring data. To compare the different types of sensor measurements with widely varying characteristics, we use normalized root mean squared error (NRMSE) as the key metric for the effectiveness of the imputation methods. We additionally consider periodicity and run time when considering comparing methods. Through extensive testing, we find that for small gap sizes, up to 8 consecutive missing values, linear interpolation performs the best; for larger gaps stretching up to 48 consecutive missing values, K-nearest neighbors provides the most accurate imputations; for even larger gaps, more computational intensive methods, such as matrix factorization, achieve the smallest NRMSE. Additionally, we observe that these computationally intensive algorithms not only provide accurate imputations for large gaps, but are also more robust across all types of sensors.

Cho, B↗

NASA NTRS1972

Reciprocal - MSE and SNR as distinct performance measures in below-threshold communication.

The possible advantages of using algorithms that are minimum mean-square-error (MSE) optimal, or other averaging-type demodulators with frequency position modulation (FPM), are investigated. An attempt is made to describe the performance of the optimal and various suboptimal demodulators in terms of three parameters which depend on SNR and bandwidth expansion. The performance measures investigated are the reciprocal of the normalized mean-square error and the output SNR, which are different in the below-threshold region. The former is compared to the rate-distortion bound. The possible advantage of averaging-type discriminators from the point of view of the threshold is discussed.

Bar-David, I.↗