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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 163 records · Page 9
All sourcesNASA NTRSDOE OSTI
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 NTRS1988

Miniature Remote Deadweight Calibrator

Miniature, computer-controlled deadweight calibrator developed to calibrate remotely force transducer located in cryogenic chamber. Used with microcomputer, calibration system automatically applies deadweight loads to skin-friction balance, records and reduces data, and prints out results. Actuator controller and interlocking-weight system key elements in precise, automatic transducer calibrator. Designed for full-scale load of 1,000 mg. Concept extended to accommodate other full-scale load ranges.

Supplee, Frank H., Jr.↗
NASA NTRS1993

Characterizing the uncertainty in holddown post load measurements

In order to understand unexpectedly erratic load measurements in the launch-pad supports for the space shuttle, the sensitivities of the load cells in the supports were analyzed using simple probabilistic techniques. NASA engineers use the loads in the shuttle's supports to calculate critical stresses in the shuttle vehicle just before lift-off. The support loads are measured with 'load cells' which are actually structural components of the mobile launch platform which have been instrumented with strain gauges. Although these load cells adequately measure vertical loads, the horizontal load measurements have been erratic. The load measurements were simulated in this study using Monte Carlo simulation procedures. The simulation studies showed that the support loads are sensitive to small deviations in strain and calibration. In their current configuration, the load cells will not measure loads with sufficient accuracy to reliably calculate stresses in the shuttle vehicle. A simplified model of the holddown post (HDP) load measurement system was used to study the effect on load measurement accuracy for several factors, including load point deviations, gauge heights, and HDP geometry.

Richardson, J. A.↗
NASA NTRS1993

Examining the accuracy of the space shuttle support loads using probabilistic analysis techniques

In order to understand unexpectedly erratic load measurements in the launch-pad supports for the space shuttle, the sensitivities of the load cells in the supports were analyzed using simple probabilistic techniques. NASA engineers use the loads in the shuttle's supports to calculate critical stresses in the shuttle vehicle just before lift-off. The support loads are measured with 'load cells' which are actually structural components of the mobile launch platform (MLP) which have been instrumented with strain gauges. Although these load cells adequately measure vertical loads, the horizontal load measurements have been erratic. The load measurements were simulated in this study using Monte Carlo simulation procedures. The simulation studies showed that the support loads are sensitive to small deviations in strain and calibration. In their current configuration, the load cells will not measure loads with sufficient accuracy to reliably calculate stresses in the shuttle vehicle.

Richardson, J.↗
NASA NTRS1998

Numerical Analysis of a Radiant Heat Flux Calibration System

A radiant heat flux gage calibration system exists in the Flight Loads Laboratory at NASA's Dryden Flight Research Center. This calibration system must be well understood if the heat flux gages calibrated in it are to provide useful data during radiant heating ground tests or flight tests of high speed aerospace vehicles. A part of the calibration system characterization process is to develop a numerical model of the flat plate heater element and heat flux gage, which will help identify errors due to convection, heater element erosion, and other factors. A 2-dimensional mathematical model of the gage-plate system has been developed to simulate the combined problem involving convection, radiation and mass loss by chemical reaction. A fourth order finite difference scheme is used to solve the steady state governing equations and determine the temperature distribution in the gage and plate, incident heat flux on the gage face, and flat plate erosion. Initial gage heat flux predictions from the model are found to be within 17% of experimental results.

Jiang, Shanjuan↗
NASA NTRS2016

Assessment of the Uniqueness of Wind Tunnel Strain-Gage Balance Load Predictions

A new test was developed to assess the uniqueness of wind tunnel strain-gage balance load predictions that are obtained from regression models of calibration data. The test helps balance users to gain confidence in load predictions of non-traditional balance designs. It also makes it possible to better evaluate load predictions of traditional balances that are not used as originally intended. The test works for both the Iterative and Non-Iterative Methods that are used in the aerospace testing community for the prediction of balance loads. It is based on the hypothesis that the total number of independently applied balance load components must always match the total number of independently measured bridge outputs or bridge output combinations. This hypothesis is supported by a control volume analysis of the inputs and outputs of a strain-gage balance. It is concluded from the control volume analysis that the loads and bridge outputs of a balance calibration data set must separately be tested for linear independence because it cannot always be guaranteed that a linearly independent load component set will result in linearly independent bridge output measurements. Simple linear math models for the loads and bridge outputs in combination with the variance inflation factor are used to test for linear independence. A highly unique and reversible mapping between the applied load component set and the measured bridge output set is guaranteed to exist if the maximum variance inflation factor of both sets is less than the literature recommended threshold of five. Data from the calibration of a six{component force balance is used to illustrate the application of the new test to real-world data.

strain-gage balance↗
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 NTRS2010

Comparison of Iterative and Non-Iterative Strain-Gage Balance Load Calculation Methods

The accuracy of iterative and non-iterative strain-gage balance load calculation methods was compared using data from the calibration of a force balance. Two iterative and one non-iterative method were investigated. In addition, transformations were applied to balance loads in order to process the calibration data in both direct read and force balance format. NASA's regression model optimization tool BALFIT was used to generate optimized regression models of the calibration data for each of the three load calculation methods. This approach made sure that the selected regression models met strict statistical quality requirements. The comparison of the standard deviation of the load residuals showed that the first iterative method may be applied to data in both the direct read and force balance format. The second iterative method, on the other hand, implicitly assumes that the primary gage sensitivities of all balance gages exist. Therefore, the second iterative method only works if the given balance data is processed in force balance format. The calibration data set was also processed using the non-iterative method. Standard deviations of the load residuals for the three load calculation methods were compared. Overall, the standard deviations show very good agreement. The load prediction accuracies of the three methods appear to be compatible as long as regression models used to analyze the calibration data meet strict statistical quality requirements. Recent improvements of the regression model optimization tool BALFIT are also discussed in the paper.

Ulbrich, N.↗
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 NTRS2012

Influence of Primary Gage Sensitivities on the Convergence of Balance Load Iterations

The connection between the convergence of wind tunnel balance load iterations and the existence of the primary gage sensitivities of a balance is discussed. First, basic elements of two load iteration equations that the iterative method uses in combination with results of a calibration data analysis for the prediction of balance loads are reviewed. Then, the connection between the primary gage sensitivities, the load format, the gage output format, and the convergence characteristics of the load iteration equation choices is investigated. A new criterion is also introduced that may be used to objectively determine if the primary gage sensitivity of a balance gage exists. Then, it is shown that both load iteration equations will converge as long as a suitable regression model is used for the analysis of the balance calibration data, the combined influence of non linear terms of the regression model is very small, and the primary gage sensitivities of all balance gages exist. The last requirement is fulfilled, e.g., if force balance calibration data is analyzed in force balance format. Finally, it is demonstrated that only one of the two load iteration equation choices, i.e., the iteration equation used by the primary load iteration method, converges if one or more primary gage sensitivities are missing. This situation may occur, e.g., if force balance calibration data is analyzed in direct read format using the original gage outputs. Data from the calibration of a six component force balance is used to illustrate the connection between the convergence of the load iteration equation choices and the existence of the primary gage sensitivities.

Ulbrich, Norbert Manfred↗
NASA NTRS1983

Preliminary results of the first static calibration of the RSRA helicopter active-isolator rotor balance system

The helicopter version of the Rotor Systems Research Aircraft (RSRA) is designed to make simultaneous measurements of all rotor forces and moments in flight analogous to a wind tunnel balance. Loads are measured by a combination of load cells, strain gages, and hydropneumatic active isolators which use pressure gages to measure loads. Complete evaluation of system performance required calibration of the rotor force and moment measuring system when installed in the aircraft. Measurement system responses to rotor loads obtained during the first static calibration of the RSRA helicopter are plotted and discussed. Plots of the raw transducer data are included.

Acree, C. W., Jr.↗
NASA NTRS2014

Design and Development of the SMAP Microwave Radiometer Electronics

The SMAP microwave radiometer will measure land surface brightness temperature at L-band (1413 MHz) in the presence of radio frequency interference (RFI) for soil moisture remote sensing. The radiometer design was driven by the requirements to incorporate internal calibration, to operate synchronously with the SMAP radar, and to mitigate the deleterious effects of RFI. The system design includes a highly linear super-heterodyne microwave receiver with internal reference loads and noise sources for calibration and an innovative digital signal processor and detection system. The front-end comprises a coaxial cable-based feed network, with a pair of diplexers and a coupled noise source, and radiometer front-end (RFE) box. Internal calibration is provided by reference switches and a common noise source inside the RFE. The RF back-end (RBE) downconverts the 1413 MHz channel to an intermediate frequency (IF) of 120 MHz. The IF signals are then sampled and quantized by high-speed analog-to-digital converters in the radiometer digital electronics (RDE) box. The RBE local oscillator and RDE sampling clocks are phase-locked to a common reference to ensure coherency between the signals. The RDE performs additional filtering, sub-band channelization, cross-correlation for measuring third and fourth Stokes parameters, and detection and integration of the first four raw moments of the signals. These data are packetized and sent to the ground for calibration and further processing. Here we discuss the novel features of the radiometer hardware particularly those influenced by the need to mitigate RFI.

radio frequency interference↗
NASA NTRS2005

Shock Location Dominated Transonic Flight Loads on the Active Aeroelastic Wing

During several Active Aeroelastic Wing research flights, the shadow of the over-wing shock could be observed because of natural lighting conditions. As the plane accelerated, the shock location moved aft, and as the shadow passed the aileron and trailing-edge flap hinge lines, their associated hinge moments were substantially affected. The observation of the dominant effect of shock location on aft control surface hinge moments led to this investigation. This report investigates the effect of over-wing shock location on wing loads through flight-measured data and analytical predictions. Wing-root and wing-fold bending moment and torque and leading- and trailing-edge hinge moments have been measured in flight using calibrated strain gages. These same loads have been predicted using a computational fluid dynamics code called the Euler Navier-Stokes Three Dimensional Aeroelastic Code. The computational fluid dynamics study was based on the elastically deformed shape estimated by a twist model, which in turn was derived from in-flight-measured wing deflections provided by a flight deflection measurement system. During level transonic flight, the shock location dominated the wing trailing-edge control surface hinge moments. The computational fluid dynamics analysis based on the shape provided by the flight deflection measurement system produced very similar results and substantially correlated with the measured loads data.

Lokos, William A.↗
NASA NTRS2007

Lessons Learned from the Aquarius Radiometer Engineering Model

The Aquarius instrument is a combination microwave radiometer and scatterometer operating in the L-band for the measurement of sea surface salinity (SSS) over the open-ocean. "The Aquarius science goals are to observe and model the processes that relate salinity variations to climatic changes in the global cycling of water and to understand how these variations influence the general ocean circulation. By measuring salinity globally and synoptically every month for 3 years, Aquarius will provide an unprecedented new view of the ocean's role in climate." (http://aquarius.asfc.nasa.gov on Jan. 4, 2007). To launch in 2009, Aquarius will provide 8-day global coverage and monthly-averaged salinity maps at approx.120-km spatial resolution. Because the microwave emissivity of the ocean surface is weakly dependent upon salinity, the Aquarius radiometer remain sufficiently stable to provide accurate salinity measurements. An engineering model (EM) of one radiometer receiver was developed and tested for functionality and performance at NASA's Goddard Space Flight Center. It was tested for long-term stability starting July 27,2006. Two discrepancies where found at the start of testing and a four-month correction process ensued. This paper covers the testing and debugging of the EM radiometer through resolution of the problems. The radiometer is required to have calibration stability of less than or equal to 0.15 K over 7 days. The radiometer is in a three-beam push-broom configuration with each beam being an independent three-state Dicke radiometer (antenna, reference load, and additive noise). Internal noise diodes and reference loads provide periodic and rapid calibration of the receiver. Front-end loss contributions must be corrected as the lossy components are outside the calibration loop. A key design feature for obtaining stability is active thermal control of the front-end lossy components and the RF receiver. The thermal stability is predicted to be about 0.1 C over an orbit and no more than 1 C over a year. The radiometric stability requirement is 0.13 K rms 1 7 days without using temperature corrections. Temperature corrections and post-launch calibration are expected to extend the stability period through the life of the mission.

Piepmeier, Jeffrey↗
NASA NTRS2013

Calibration Variable Selection and Natural Zero Determination for Semispan and Canard Balances

Independent calibration variables for the characterization of semispan and canard wind tunnel balances are discussed. It is shown that the variable selection for a semispan balance is determined by the location of the resultant normal and axial forces that act on the balance. These two forces are the first and second calibration variable. The pitching moment becomes the third calibration variable after the normal and axial forces are shifted to the pitch axis of the balance. Two geometric distances, i.e., the rolling and yawing moment arms, are the fourth and fifth calibration variable. They are traditionally substituted by corresponding moments to simplify the use of calibration data during a wind tunnel test. A canard balance is related to a semispan balance. It also only measures loads on one half of a lifting surface. However, the axial force and yawing moment are of no interest to users of a canard balance. Therefore, its calibration variable set is reduced to the normal force, pitching moment, and rolling moment. The combined load diagrams of the rolling and yawing moment for a semispan balance are discussed. They may be used to illustrate connections between the wind tunnel model geometry, the test section size, and the calibration load schedule. Then, methods are reviewed that may be used to obtain the natural zeros of a semispan or canard balance. In addition, characteristics of three semispan balance calibration rigs are discussed. Finally, basic requirements for a full characterization of a semispan balance are reviewed.

Ulbrich, Norbert M.↗
NASA NTRS2019

Comparison of Electrical Output Format Options for the Analysis of Strain-Gage Balance Calibration Data

Fundamental characteristics of three gage output formats are discussed that may be used to both interpret and analyze wind tunnel strain-gage balance data. The first output format uses raw outputs, i.e., absolute voltage measurements, for the analysis. This choice requires an intercept term in the regression model of the outputs if the Iterative Method is chosen for the load prediction. Raw outputs can be used for the analysis of all known output characteristics as long as the Iterative Method is applied. However, raw outputs cannot be used to analyze data of a balance with bi-directional outputs if the Non-Iterative Method is chosen for the analysis. The second output format, i.e., difference type 1, uses the difference between raw outputs and the natural zeros of the balance gages for the analysis. In this case, the use of the intercept term becomes optional. Analysis results for difference type 1 will exactly match analysis results obtained by using raw outputs as long as identical math models are used for the regression analysis. In addition, difference type 1 may be used to analyze data of a balance with bi directional outputs if an analyst prefers to process data using the Non-Iterative Method. The third output format, i.e., difference type 2, uses the difference between raw outputs and the outputs of the zero load point of a load series for the data analysis. The application of this format is only recommended if the maximum magnitude of all tare loads of a given balance calibration data set is less than two percent of capacity. Data from the calibration of a force balance is used to illustrate the application of the three gage output formats.

Wind Tunnel Strain-Gage Balance↗
NASA NTRS2026

Mechanical Design and Operation of a Novel Lunar Environment Structural Test Rig (LESTR)

The Lunar Environment Structural Test Rig (LESTR) was developed to address a critical gap in mechanical property data for metal alloy wire materials under lunar-relevant conditions down to 40 K. Conventional aerospace material databases provide thermophysical properties for bulk metals over a wide temperature range, but validated mechanical and physical property data below 77 K, particularly for small-diameter wires, remain limited and are generally the exception rather than the rule. These conditions are essential for Artemis mission hardware such as shape memory alloy (SMA) rover tires. LESTR’s design requirements were to combine a high-stiffness electrodynamic load frame with closed- cycle cryogenic cooling, high-vacuum capability (10–6 torr), and noncontact optical strain measurement to enable tensile, four-point bend, and fatigue testing of wires or other materials and geometries at temperatures from 40 to 125 K. These considerable requirements were merged with the need to lower the barrier of testing for the end user as measured in terms of cost-per-test cycle, safety improvement, and reduction in upkeep costs associated with state-of-the-art solutions associated with cryomechanical material characterization. The system incorporates modular gripping and alignment fixtures; precision thermal management using cryocoolers and embedded heaters; and integrated instrumentation for displacement, load, temperature, and vacuum control. Calibration procedures establish correlations between tooling and specimen temperature, ensuring accurate thermal conditions across the design envelope unbound by cryofluid conditions in heritage immersion-based test systems. Initial validation tests using Inconel (Special Metals Corp.) wire demonstrated accurate ultimate strength and post-yield behavior. The load frame operation was also verified under representative service conditions, including thermal cycling and prolonged fatigue loading. By generating mechanical property data at ultralow temperatures, LESTR fills a critical gap in existing materials databases and provides a scalable platform for iterative alloy development and durability assessment for planetary hardware. This capability supports NASA’s long-term objectives for surface exploration by enabling design confidence for components operating in extreme cryogenic environments.

LESTR↗