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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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All sourcesNASA NTRSDOE OSTI
NASA NTRSDate not supplied

Application of Machine Learning Techniques in Calibration and Data Reduction of Multi-Hole Probes

This work presents procedures for implementing machine learning methods into existing algorithms for multi-hole probe calibration and data reduction. It demonstrates that using artificial neural networks (ANNs) can decrease the amount of calibration data needed to achieve a specific calibration uncertainty by over 50%, while also significantly reducing data reduction times. Instead of surface fitting methods, ANNs are employed. Initially, directional calibration coefficients related to flow angles are computed based on pressure measurements, and then these flow angles serve as input parameters for subsequent ANNs to iteratively define Mach number, static pressure, and total pressure. In an alternative approach, new calibration coefficients directly relate pressure measurements from the five-hole probe to the quantities of interest, thereby eliminating the need for iterative algorithms used in conventional surface fitting methods. This method offers several advantages: an average increase of less than 1%in calibration uncertainty for flow angles and a significant reduction in data reduction times to a few seconds on average. Additionally, the methodology is confirmed to avoid both over- and under-fitting.

Machine Learning↗
NASA NTRSDate not supplied

Application of Machine Learning Techniques in Calibration and Data Reduction of Multi-Hole Probes

This work presents procedures to implement machine learning methods in the existing algorithms for multi-hole probe calibrations and data reduction. It is shown here, that utilizing artificial neural networks (ANNs) can reduce the amount of calibration data that needs to be acquired in order to obtain a specific calibration uncertainty, by more than 50% while simultaneously reducing data reduction times significantly. ANNs were used instead of the surface fitting methods, where first, the directional calibration coefficients related to the flow angles are calculated based on the pressure measurements, and then the flow angles are used as a set of the input parameters for the following ANNs to define Mach number and static and total pressure iteratively. In a second approach, novel calibration coefficients were used to directly relate the pressure measurements from five-hole probe to the quantities of interest thus, eliminating the need for iterative algorithms used in the conventional surface fitting methods. The advantageous features of this method are an average increase of less than 1% in the calibration uncertainty for flow angles and significant reduction of the data reduction times (few seconds). In addition, we confirmed the methodology to avoid over-fitting and under-fitting.

Machine Learning↗
NASA NTRS2013

Flow Control and Measurement in Electric Propulsion Systems: Towards an AIAA Reference Standard

Accurate control and measurement of propellant flow to a thruster is one of the most basic and fundamental requirements for operation of electric propulsion systems, whether they be in the laboratory or on flight spacecraft. Hence, it is important for the electric propulsion community to have a common understanding of typical methods for flow control and measurement. This paper addresses the topic of propellant flow primarily for the gaseous propellant systems which have dominated laboratory research and flight application over the last few decades, although other types of systems are also briefly discussed. While most flight systems have employed a type of pressure-fed flow restrictor for flow control, both thermal-based and pressure-based mass flow controllers are routinely used in laboratories. Fundamentals and theory of operation of these types of controllers are presented, along with sources of uncertainty associated with their use. Methods of calibration and recommendations for calibration processes are presented. Finally, details of uncertainty calculations are presented for some common calibration methods and for the linear fits to calibration data that are commonly used.

thrust measurement↗
NASA NTRS2007

A Comparison of Two Balance Calibration Model Building Methods

Simulated strain-gage balance calibration data is used to compare the accuracy of two balance calibration model building methods for different noise environments and calibration experiment designs. The first building method obtains a math model for the analysis of balance calibration data after applying a candidate math model search algorithm to the calibration data set. The second building method uses stepwise regression analysis in order to construct a model for the analysis. Four balance calibration data sets were simulated in order to compare the accuracy of the two math model building methods. The simulated data sets were prepared using the traditional One Factor At a Time (OFAT) technique and the Modern Design of Experiments (MDOE) approach. Random and systematic errors were introduced in the simulated calibration data sets in order to study their influence on the math model building methods. Residuals of the fitted calibration responses and other statistical metrics were compared in order to evaluate the calibration models developed with different combinations of noise environment, experiment design, and model building method. Overall, predicted math models and residuals of both math model building methods show very good agreement. Significant differences in model quality were attributable to noise environment, experiment design, and their interaction. Generally, the addition of systematic error significantly degraded the quality of calibration models developed from OFAT data by either method, but MDOE experiment designs were more robust with respect to the introduction of a systematic component of the unexplained variance.

DeLoach, Richard↗
NASA NTRSDate not supplied

Comparison of Two Load Prediction Methods for Strain-Gage Balances

Data from a high-capacity semi-span balance is used to perform a detailed comparison of the load prediction accuracy of two strain-gage balance load prediction methods. Both methods independently obtain their load prediction equations from multivariate least squares fits of balance calibration data. The first method is called Non-Iterative Method. This approach directly uses regression models of the individual load components of a balance for the load prediction. The second method is called Iterative Method. This alternate approach uses a load iteration equation for the load prediction that is constructed from the regression models of the gage outputs of the balance. Basic characteristics of the two methods are reviewed. Afterwards, both methods are applied to calibration and check load data of the chosen balance. Finally, selected analysis results are compared. These comparisons confirmed that the load prediction accuracy of the two methods is the same for all practical purposes.

wind tunnel test↗
NASA NTRSDate not supplied

Comparison of Two Load Prediction Methods for Strain-Gage Balances

Data from a five-component semi-span balance is used to perform a systematic comparison of the load prediction accuracy of two load prediction methods. Both methods independently obtain the load prediction equations from multivariate least squares fits of balance calibration data. The first method is called the Non-Iterative Method. This approach directly uses regression models of the individual load components of a balance for the load prediction. The second method is called the Iterative Method. This alternate approach uses a load iteration equation for the load prediction that is constructed from the regression coefficients of the gage outputs of the balance. Basic characteristics of the two methods are reviewed. Afterwards, both methods are applied to calibration, check load, and wind tunnel test data of a five-component semi-span balance. Selected analysis results are compared. These comparisons confirm that the accuracy of the two methods is the same for all practical purposes.

strain-gage balance↗
NASA NTRS1994

Calibration of the COBE FIRAS instrument

The Far-Infrared Absolute Spectrophotometer (FIRAS) instrument on the Cosmic Background Explorer (COBE) satellite was designed to accurately measure the spectrum of the cosmic microwave background radiation (CMBR) in the frequency range 1-95/cm with an angular resolution of 7 deg. We describe the calibration of this instrument, including the method of obtaining calibration data, reduction of data, the instrument model, fitting the model to the calibration data, and application of the resulting model solution to sky observations. The instrument model fits well for calibration data that resemble sky condition. The method of propagating detector noise through the calibration process to yield a covariance matrix of the calibrated sky data is described. The final uncertainties are variable both in frequency and position, but for a typical calibrated sky 2.6 deg square pixel and 0.7/cm spectral element the random detector noise limit is of order of a few times 10(exp -7) ergs/sq cm/s/sr cm for 2-20/cm, and the difference between the sky and the best-fit cosmic blackbody can be measured with a gain uncertainty of less than 3%.

Fixsen, D. J.↗
NASA NTRS1978

A flight evaluation of a trailing anemometer for low-speed calibrations of airspeed systems on research aircraft

Research airspeed systems on three low-speed general aviation airplanes were calibrated by the trailing anemometer method. Each airplane was fitted with an NASA pitot-static pressure tube mounted on either a nose or wing boom. The uncalibrated airspeed systems contained residual static-pressure position errors which were too large for high-accuracy flight research applications. The trailing anemometer calibration was in agreement with the tower flyby calibration for the one aircraft for which the comparison was made. The continuous deceleration technique for the trailing anemometer method offers reduced test time with no appreciable loss of accuracy for airspeed systems with pitot-static system lag characteristics similar to those described.

Fisher, B. D.↗
NASA NTRS2015

Improved Regression Analysis of Temperature-Dependent Strain-Gage Balance Calibration Data

An improved approach is discussed that may be used to directly include first and second order temperature effects in the load prediction algorithm of a wind tunnel strain-gage balance. The improved approach was designed for the Iterative Method that fits strain-gage outputs as a function of calibration loads and uses a load iteration scheme during the wind tunnel test to predict loads from measured gage outputs. The improved approach assumes that the strain-gage balance is at a constant uniform temperature when it is calibrated and used. First, the method introduces a new independent variable for the regression analysis of the balance calibration data. The new variable is designed as the difference between the uniform temperature of the balance and a global reference temperature. This reference temperature should be the primary calibration temperature of the balance so that, if needed, a tare load iteration can be performed. Then, two temperature{dependent terms are included in the regression models of the gage outputs. They are the temperature difference itself and the square of the temperature difference. Simulated temperature{dependent data obtained from Triumph Aerospace's 2013 calibration of NASA's ARC-30K five component semi{span balance is used to illustrate the application of the improved approach.

wind tunnel testing↗
NASA NTRS2013

Hidden Connections between Regression Models of Strain-Gage Balance Calibration Data

Hidden connections between regression models of wind tunnel strain-gage balance calibration data are investigated. These connections become visible whenever balance calibration data is supplied in its design format and both the Iterative and Non-Iterative Method are used to process the data. First, it is shown how the regression coefficients of the fitted balance loads of a force balance can be approximated by using the corresponding regression coefficients of the fitted strain-gage outputs. Then, data from the manual calibration of the Ames MK40 six-component force balance is chosen to illustrate how estimates of the regression coefficients of the fitted balance loads can be obtained from the regression coefficients of the fitted strain-gage outputs. The study illustrates that load predictions obtained by applying the Iterative or the Non-Iterative Method originate from two related regression solutions of the balance calibration data as long as balance loads are given in the design format of the balance, gage outputs behave highly linear, strict statistical quality metrics are used to assess regression models of the data, and regression model term combinations of the fitted loads and gage outputs can be obtained by a simple variable exchange.

Ulbrich, Norbert↗
NASA NTRS2010

Model Robust Calibration: Method and Application to Electronically-Scanned Pressure Transducers

This article presents the application of a recently developed statistical regression method to the controlled instrument calibration problem. The statistical method of Model Robust Regression (MRR), developed by Mays, Birch, and Starnes, is shown to improve instrument calibration by reducing the reliance of the calibration on a predetermined parametric (e.g. polynomial, exponential, logarithmic) model. This is accomplished by allowing fits from the predetermined parametric model to be augmented by a certain portion of a fit to the residuals from the initial regression using a nonparametric (locally parametric) regression technique. The method is demonstrated for the absolute scale calibration of silicon-based pressure transducers.

Walker, Eric L.↗
NASA NTRS1992

AVIRIS study of Death Valley evaporite deposits using least-squares band-fitting methods

Minerals found in playa evaporite deposits reflect the chemically diverse origins of ground waters in arid regions. Recently, it was discovered that many playa minerals exhibit diagnostic visible and near-infrared (0.4-2.5 micron) absorption bands that provide a remote sensing basis for observing important compositional details of desert ground water systems. The study of such systems is relevant to understanding solute acquisition, transport, and fractionation processes that are active in the subsurface. Observations of playa evaporites may also be useful for monitoring the hydrologic response of desert basins to changing climatic conditions on regional and global scales. Ongoing work using Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) data to map evaporite minerals in the Death Valley salt pan is described. The AVIRIS data point to differences in inflow water chemistry in different parts of the Death Valley playa system and have led to the discovery of at least two new North American mineral occurrences. Seven segments of AVIRIS data were acquired over Death Valley on 31 July 1990, and were calibrated to reflectance by using the spectrum of a uniform area of alluvium near the salt pan. The calibrated data were subsequently analyzed by using least-squares spectral band-fitting methods, first described by Clark and others. In the band-fitting procedure, AVIRIS spectra are fit compared over selected wavelength intervals to a series of library reference spectra. Output images showing the degree of fit, band depth, and fit times the band depth are generated for each reference spectrum. The reference spectra used in the study included laboratory data for 35 pure evaporite spectra extracted from the AVIRIS image cube. Additional details of the band-fitting technique are provided by Clark and others elsewhere in this volume.

Crowley, J. K.↗
NASA NTRSDate not supplied

An Improved Weighted Least Squares Algorithm for the Analysis of Strain-Gage Balance Calibration Data

An improved version of an algorithm is presented that uses a weighted least squares fit of balance calibration data for the generation of the balance load prediction equations. The weighted least squares fit assigns a weighting factor between zero and one to each calibration data point that depends on a simple count of the number of intentionally loaded balance gages. The greater the number of the loaded gages is, the smaller a data point's weighting factor becomes. This strategy has two advantages. First, single-component loads become more influential during the regression analysis of the calibration data. In addition, the negative influence of load schedule asymmetries on the regression analysis results can more effectively be controlled. The original algorithm of 2017 was improved in 2020. Now, gage output differences relative to the natural zeros are exclusively used as input for the determination of the number of intentionally loaded gages. The improved weighted least squares fit can be applied with both the Non-Iterative Method and the Iterative Method that are used for the balance load prediction in the aerospace testing community. Machine calibration data of a force balance is used to illustrate benefits of the application of the improved weighted least squares fit of balance calibration data.

strain-gage balance↗
NASA NTRS1978

A highly accurate method for the determination of mass and center of mass of a spacecraft

An extremely accurate method for the measurement of mass and the lateral center of mass of a spacecraft has been developed. The method was needed for the Voyager spacecraft mission requirement which limited the uncertainty in the knowledge of lateral center of mass of the spacecraft system weighing 750 kg to be less than 1.0 mm (0.04 in.). The method consists of using three load cells symmetrically located at 120 deg apart on a turntable with respect to the vertical axis of the spacecraft and making six measurements for each load cell. These six measurements are taken by cyclic rotations of the load cell turntable and of the spacecraft, about the vertical axis of the measurement fixture. This method eliminates all alignment, leveling, and load cell calibration errors for the lateral center of mass determination, and permits a statistical best fit of the measurement data. An associated data reduction computer program called MASCM has been written to implement this method and has been used for the Voyager spacecraft.

Chow, E. Y.↗
NASA NTRS2020

Use of an Internal Mercury-Argon Lamp for the Calibration of Raman Frequency in Large Raman Images of Astromaterials

Raman imaging is an emerging tool for the analysis of meteorites, as it is capable of describing mineralogy, carbon composition/speciation, and crystal orientation all within a petrographic context. Adequately examining the heterogeneous composition of a meteorite, while maintaining low laser powers needed to prevent damage to meteorite mineralogy and organics, often requires the collection of large Raman images with long collection times on the timescale of days. However, the frequency calibration of the Raman instrument/spectrometer drifts on long timescales resulting in low frequency precision for the Raman spectra comprising a large Raman image. This decrease in frequency precision can compromise the analysis of geological markers that can provide important information on a meteorite sample. We examine, in detail, the change in bandwidth and frequency of the Raman bands and Hg-Ar emission lines in our Raman images as a function of time and laboratory temperature. To overcome the drift in calibration, we utilize a commercial WITec Raman instrument with an internal Hg-Ar calibration lamp to individually calibrate each spectrum in the Raman image. Our instrument, known as “Ratatoskr”, uses a beam splitter in place of the customary mirror to facilitate collection of Hg-Ar calibration lines concurrent with Raman spectra. We show that using the internal calibration we can improve the frequency precision for the spectra in our Raman images from ~±0.15 cm(exp -1) to ~±0.05 cm(exp -1) for Raman spectra collected over multiple days. This is important as it improves measurements of mineral chemistry, latent strain, and other features that are dependent upon accurate peak position determination. We also examine the spectral signal-to-noise ratio needed to minimize the frequency error when fitting bands to Gaussian/Lorentzian profiles. We then use our results to suggest a general method for calibrating the frequency of Raman spectra in large Raman images.

Jakubek, Ryan S.↗
NASA NTRS1981

Photographic photometry with Iris diaphragm photometers

A general method is presented for solving problems encountered in the analysis of Iris diaphragm photometer (IDP) data. The method is used to derive the general shape of the calibration curve, allowing both a more accurate fit to the IDP data for comparison stars and extrapolation to magnitude ranges for which no comparison stars are measured. The profile of starlight incident and the characteristic curve of the plate are both assumed and then used to derive the profile of the star image. An IDP reading is then determined for each star image. A procedure for correcting the effects of a nonconstant background fog level on the plate is also demonstrated. Additional applications of the method are made in the appendix to determine the relation between the radius of a photographic star image and the star's magnitude, and to predict the IDP reading of the 'point of optimum density'.

Schaefer, B. E.↗
NASA NTRS1976

Effects of edge-rounding on geodesic lenses

A method that eliminates the need for a mathematical model is described for measuring the absolute light intensity radiated from volume chemiluminescent and fluorescent sources. This technique applies to a uniform cylindrical luminous volume, which is the geometry most often practical for the study of flowing chemiluminescent and fluorescent fluids. In this method, the necessary integration over a luminous volume is carried out experimentally, using a calibrated piston source that has as its head a disk of uniform luminosity. The relatively small total error in absolute light intensity measurements with the piston source technique represents a significant improvement over competing comparison methods. The construction of a piston source to fit the cross section of a particular cylindrical volume is straightforward, and its calibration against a standard source can be readily made while exercising normal precautions.

Wood, V. E.↗
NASA NTRS1995

Metafitting: Weight optimization for least-squares fitting of PTTI data

For precise time intercomparisons between a master frequency standard and a slave time scale, we have found it useful to quantitatively compare different fitting strategies by examining the standard uncertainty in time or average frequency. It is particularly useful when designing procedures which use intermittent intercomparisons, with some parameterized fit used to interpolate or extrapolate from the calibrating intercomparisons. We use the term 'metafitting' for the choices that are made before a fitting procedure is operationally adopted. We present methods for calculating the standard uncertainty for general, weighted least-squares fits and a method for optimizing these weights for a general noise model suitable for many PTTI applications. We present the results of the metafitting of procedures for the use of a regular schedule of (hypothetical) high-accuracy frequency calibration of a maser time scale. We have identified a cumulative series of improvements that give a significant reduction of the expected standard uncertainty, compared to the simplest procedure of resetting the maser synthesizer after each calibration. The metafitting improvements presented include the optimum choice of weights for the calibration runs, optimized over a period of a week or 10 days.

Douglas, Rob J.↗