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At least 505 records · Page 28

All sources NASA NTRS DOE OSTI

NASA NTRS2007

Calculating Nozzle Side Loads using Acceleration Measurements of Test-Based Models

As part of a NASA/MSFC research program to evaluate the effect of different nozzle contours on the well-known but poorly characterized "side load" phenomena, we attempt to back out the net force on a sub-scale nozzle during cold-flow testing using acceleration measurements. Because modeling the test facility dynamics is problematic, new techniques for creating a "pseudo-model" of the facility and nozzle directly from modal test results are applied. Extensive verification procedures were undertaken, resulting in a loading scale factor necessary for agreement between test and model based frequency response functions. Side loads are then obtained by applying a wide-band random load onto the system model, obtaining nozzle response PSD's, and iterating both the amplitude and frequency of the input until a good comparison of the response with the measured response PSD for a specific time point is obtained. The final calculated loading can be used to compare different nozzle profiles for assessment during rocket engine nozzle development and as a basis for accurate design of the nozzle and engine structure to withstand these loads. The techniques applied within this procedure have extensive applicability to timely and accurate characterization of all test fixtures used for modal test.A viewgraph presentation on a model-test based pseudo-model used to calculate side loads on rocket engine nozzles is included. The topics include: 1) Side Loads in Rocket Nozzles; 2) Present Side Loads Research at NASA/MSFC; 3) Structural Dynamic Model Generation; 4) Pseudo-Model Generation; 5) Implementation; 6) Calibration of Pseudo-Model Response; 7) Pseudo-Model Response Verification; 8) Inverse Force Determination; 9) Results; and 10) Recent Work.

Brown, Andrew M.↗

NASA NTRS2002

Site Distribution and Aliasing Effects in the Inversion for Load Coefficients and Geocenter Motion from GPS Data

Precise GPS measurements of elastic relative site displacements due to surface mass loading offer important constraints on global surface mass transport. We investigate effects of site distribution and aliasing by higher-degree (n greater than or equal 2) loading terms on inversion of GPS data for n = 1 load coefficients and geocenter motion. Covariance and simulation analyses are conducted to assess the sensitivity of the inversion to aliasing and mismodeling errors and possible uncertainties in the n = 1 load coefficient determination. We found that the use of center-of-figure approximation in the inverse formulation could cause 10- 15% errors in the inverted load coefficients. n = 1 load estimates may be contaminated significantly by unknown higher-degree terms, depending on the load scenario and the GPS site distribution. The uncertainty in n = 1 zonal load estimate is at the level of 80 - 95% for two load scenarios.

global positioning system↗

NASA NTRS2011

The Extravehicular Suit Impact Load Attenuation Study for Use in Astronaut Bone Fracture Prediction

The NASA Integrated Medical Model (IMM) assesses the risk, including likelihood and impact of occurrence, of all credible in-flight medical conditions. Fracture of the proximal femur is a traumatic injury that would likely result in loss of mission if it were to happen during spaceflight. The low gravity exposure causes decreases in bone mineral density which heightens the concern. Researchers at the NASA Glenn Research Center have quantified bone fracture probability during spaceflight with a probabilistic model. It was assumed that a pressurized extravehicular activity (EVA) suit would attenuate load during a fall, but no supporting data was available. The suit impact load attenuation study was performed to collect analogous data. METHODS: A pressurized EVA suit analog test bed was used to study how the offset, defined as the gap between the suit and the astronaut s body, impact load magnitude and suit operating pressure affects the attenuation of impact load. The attenuation data was incorporated into the probabilistic model of bone fracture as a function of these factors, replacing a load attenuation value based on commercial hip protectors. RESULTS: Load attenuation was more dependent on offset than on pressurization or load magnitude, especially at small offsets. Load attenuation factors for offsets between 0.1 - 1.5 cm were 0.69 +/- 0.15, 0.49 +/- 0.22 and 0.35 +/- 0.18 for mean impact forces of 4827, 6400 and 8467 N, respectively. Load attenuation factors for offsets of 2.8 - 5.3 cm were 0.93 +/- 0.2, 0.94 +/- 0.1 and 0.84 +/- 0.5, for the same mean impact forces. Reductions were observed in the 95th percentile confidence interval of the bone fracture probability predictions. CONCLUSIONS: The reduction in uncertainty and improved confidence in bone fracture predictions increased the fidelity and credibility of the fracture risk model and its benefit to mission design and operational decisions.

Lewandowski, Beth E.↗

NASA NTRS2011

On the Response of a Nonlinear Structure to High Kurtosis Non-Gaussian Random Loadings

This paper is a follow-on to recent work by the authors in which the response and high-cycle fatigue of a nonlinear structure subject to non-Gaussian loadings was found to vary markedly depending on the nature of the loading. There it was found that a non-Gaussian loading having a steady rate of short-duration, high-excursion peaks produced essentially the same response as would have been incurred by a Gaussian loading. In contrast, a non-Gaussian loading having the same kurtosis, but with bursts of high-excursion peaks was found to elicit a much greater response. This work is meant to answer the question of when consideration of a loading probability distribution other than Gaussian is important. The approach entailed nonlinear numerical simulation of a beam structure under Gaussian and non-Gaussian random excitations. Whether the structure responded in a Gaussian or non-Gaussian manner was determined by adherence to, or violations of, the Central Limit Theorem. Over a practical range of damping, it was found that the linear response to a non-Gaussian loading was Gaussian when the period of the system impulse response is much greater than the rate of peaks in the loading. Lower damping reduced the kurtosis, but only when the linear response was non-Gaussian. In the nonlinear regime, the response was found to be non-Gaussian for all loadings. The effect of a spring-hardening type of nonlinearity was found to limit extreme values and thereby lower the kurtosis relative to the linear response regime. In this case, lower damping gave rise to greater nonlinearity, resulting in lower kurtosis than a higher level of damping.

Rizzi, Stephen A.↗

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 NTRS2014

The Inclusion of Arbitrary Load Histories in the Strength Decay Model for Stress Rupture

Stress rupture is a failure mechanism where failures can occur after a period of time, even though the material has seen no increase in load. Carbon/epoxy composite materials have demonstrated the stress rupture failure mechanism. In a previous work, a model was proposed for stress rupture of composite overwrap pressure vessels (COPVs) and similar composite structures based on strength degradation. However, the original model was limited to constant load periods (holds) at constant load. The model was expanded in this paper to address arbitrary loading histories and specifically the inclusions of ramp loadings up to holds and back down. The broadening of the model allows for failures on loading to be treated as any other failure that may occur during testing instead of having to be treated as a special case. The inclusion of ramps can also influence the length of the "safe period" following proof loading that was previously predicted by the model. No stress rupture failures are predicted in a safe period because time is required for strength to decay from above the proof level to the lower level of loading. Although the model can predict failures during the ramp periods, no closed-form solution for the failure times could be derived. Therefore, two suggested solution techniques were proposed. Finally, the model was used to design an experiment that could detect the difference between the strength decay model and a commonly used model for stress rupture. Although these types of models are necessary to help guide experiments for stress rupture, only experimental evidence will determine how well the model may predict actual material response. If the model can be shown to be accurate, current proof loading requirements may result in predicted safe periods as long as 10(13) years. COPVs design requirements for stress rupture may then be relaxed, allowing more efficient designs, while still maintaining an acceptable level of safety.

Reeder, James R.↗

NASA NTRS2014

Overview of the 6 Meter HIAD Inflatable Structure and Flexible TPS Static Load Test Series

To support NASAs long term goal of landing humans on Mars, technologies which enable the landing of heavy payloads are being developed. Current entry, decent, and landing technologies are not practical for this class of payloads due to geometric constraints dictated by current launch vehicle fairing limitations. Therefore, past and present technologies are now being explored to provide a mass and volume efficient solution to atmospheric entry, including Hypersonic Inflatable Aerodynamic Decelerators (HIADs). At the beginning of 2014, a 6m HIAD inflatable structure with an integrated flexible thermal protection system (TPS) was subjected to a static load test series to verify the designs structural performance. The 6m HIAD structure was constructed in a stacked toroid configuration using nine inflatable torus segments composed of fiber reinforced thin films, which were joined together using adhesives and high strength textile woven structural straps to help distribute the loads throughout the inflatable structure. The 6m flexible TPS was constructed using multiple layers of high performance materials to protect the inflatable structure from heat loads that would be seen during atmospheric entry. To perform the static load test series, a custom test fixture was constructed. The fixture consisted of a structural tub rim with enough height to allow for displacement of the inflatable structure as loads were applied. The bottom of the tub rim had an airtight seal with the floor. The centerbody of the inflatable structure was attached to a pedestal mount as seen in Figure 1. Using an impermeable membrane seal draped over the test article, partial vacuum was pulled beneath the HIAD, resulting in a uniform static pressure load applied to the outer surface. During the test series an extensive amount of instrumentation was used to provide many data sets including: deformed shape, shoulder deflection, strap loads, cord loads, inflation pressures, and applied static load.In this overview, the 6m HIAD static load test series will be discussed in detail, including the 6m HIAD inflatable structure and flexible TPS design, test setup and execution, and finally initial results and conclusions from the test series.

inflatable aerodynamic decelerator↗

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 NTRS2017

Detection and Use of Load and Gage Output Repeats of Wind Tunnel Strain-Gage Balance Data

Criteria are discussed that may be used for the detection of load and gage output repeats of wind tunnel strain-gage balance data. First, empirical thresholds are introduced that help determine if the loads or electrical outputs of a pair of balance calibration or check load data points match. A threshold of 0.01 percent of the load capacity is suggested for the identification of matching loads. Similarly, a threshold of 0.1 microV/V is recommended for the identification of matching electrical outputs. Two examples for the use of load and output repeats are discussed to illustrate benefits of the implementation of a repeat point detection algorithm in a balance data analysis software package. The first example uses the suggested load threshold to identify repeat data points that may be used to compute pure errors of the balance loads. This type of analysis may reveal hidden data quality issues that could potentially be avoided by making calibration process improvements. The second example uses the electrical output threshold for the identification of balance fouling. Data from the calibration of a six-component force balance is used to illustrate the calculation of the pure error of the balance loads.

strain-gage balance↗

NASA NTRS2014

Overview of the 6m HIAD Inflatable Structure and Flexible TPS Static Load Test Series

To support NASAs long term goal of landing humans on Mars, technologies which enable the landing of heavy payloads are being developed. Current entry, decent, and landing technologies are not practical for this class of payloads due to geometric constraints dictated by current launch vehicle fairing limitations. Therefore, past and present technologies are now being explored to provide a mass and volume efficient solution to atmospheric entry, including Hypersonic Inflatable Aerodynamic Decelerators (HIADs). At the beginning of 2014, a 6m HIAD inflatable structure with an integrated flexible thermal protection system (TPS) was subjected to a static load test series to verify the designs structural performace. The 6m HIAD structure was constructed in a stacked toroid configuration using nine inflatable torus segments composed of fiber reinforced thin films, which were joined together using adhesives and high strength textile woven structural straps to help distribute the loads throughout the inflatable structure. The 6m flexible TPS was constructed using multiple layers of high performance materials to protect the inflatable structure from heat loads that would be seen during atmospheric entry. To perform the static load test series, a custom test fixture was constructed. The fixture consisted of a structural tub rim with enough height to allow for displacement of the inflatable structure as loads were applied. The bottom of the tub rim had an airtight seal with the floor. The centerbody of the inflatable structure was attached to a pedestal mount as seen in Figure 1. Using an impermeable membrane seal draped over the test article, partial vacuum was pulled beneath the HIAD, resulting in a uniform static pressure load applied to the outer surface. During the test series an extensive amount of instrumentation was used to provide many data sets including: deformed shape, shoulder deflection, strap loads, cord loads, inflation pressures, and applied static load.In this overview, the 6m HIAD static load test series will be discussed in detail, including the 6m HIAD inflatable structure and flexible TPS design, test setup and execution, and finally initial results and conclusions from the test series.

TPS↗

NASA NTRS2018

Adjustments and Uncertainty Quantification for SLS Aerodynamic Sectional Loads

This paper presents a method for adjusting sectional loads to match target values for integrated force and moment coefficients. In a typical application, the sectional load profile for one flight condition is calculated from Computational Fluid Dynamics (CFD) while the integrated forces and moments are measured in a wind tunnel experiment. These two methods do not generally result in identical predictions, and this leads to an inherent inconsistency between different data products. This paper aims to provide a procedure to remove that inconsistency. A sectional load profile for a launch vehicle splits the rocket into slices along its length and calculates the aerodynamic loading on each slice, which leads to a one-dimensional aerodynamic load profile that is used for structural analysis. Adjusting sectional loads, also known as line loads, is a nontrivial matter due to several consistency constraints. For example, the adjusted sectional normal force profile must be consistent with both the integrated normal force and pitching moment. To avoid such inconsistency issues, this paper presents a method using a Proper Orthogonal Decomposition (POD) to generate basis functions to adjust the sectional load profiles. As a corollary, this correction method enables the creation of an uncertainty quantification for sectional loads that is consistent with the dispersed integrated force and moment database and its uncertainty quantification. Several extensions to this technique, such as applying the method to the surface pressures, are considered.

Quantification↗

NASA NTRS2002

Site distribution and aliasing effects in the inversion for load coefficients and geocenter motion from GPS data

Precise GPS measurements of elastic relative site displacements due to surface mass loading offer important constraints on global surface mass transport. We investigate effects of site distribution and aliasing by higher- degree (n ≥ 2) loading terms on inversion of GPS data for n = 1 load coefficients and geocenter motion. Covariance and simulation analyses are conducted to assess the sensitivity of the inversion to aliasing and mismodeling errors and possible uncertainties in the n = 1 load coefficient determination. We found that the use of center-of-figure approximation in the inverse formulation could cause 10– 15% errors in the inverted load coefficients. n = 1 load estimates may be contaminated significantly by unknown higher-degree terms, depending on the load scenario and the GPS site distribution. The uncertainty in n = 1 zonal load estimate is at the level of 80–95% for two load scenarios.

Webb, Frank H.↗

NASA NTRS2024

Mock Truss-Braced Wing Loads Calibration Research Utilizing Fiber-Optic Sensors

In support of the National Aeronautics and Space Administration Advanced Air Transonic Transport Truss-Braced Wing structural research, the Armstrong Flight Research Center Flight Loads Laboratory is performing pathfinder tests on a small, scaled test article (dubbed the mock Truss-Braced Wing) to study the application of a loads calibration on a truss-braced wing structure. The addition of a truss to the wing structure, as opposed to a purely cantilever beam setup, changes the strain-gage-based loads calibration techniques. In a truss-braced configuration, the internal shear and moments, inboard of the truss-wing connection, are not directly representative of the external aerodynamic loading as is the case for a traditional cantilever configuration. A 3-axis load cell was used at the wing-to-strut interface to estimate the load sharing between the two structural members. Crosstalk within the 3-axis load cell is added to the measurement uncertainties of the calibration effort, and the results, including crosstalk uncertainties, are presented. The calibration tests presented in this report are used as a pathfinder for developing an understanding how to perform loads calibration on a truss-braced wing structural configuration. The use of distributed fiber-optic strain sensors is leveraged to provide a near-full-span strain profile along the leading and trailing edge of the wing structure for strain-based loads calibration.

Francisco Peña↗

NASA NTRSDate not supplied

Applicability of Loads Estimation Techniques Using Sparse Acceleration Sensor Data to Spacecraft Structural Health Monitoring

The use of structural health monitoring systems on spacecraft structures can play a crucial role in ensuring the safety, reliability, and longevity of the structure by gathering and analyzing onboard sensor data. Of specific importance is monitoring for excessive loading at critical interfaces as any off-nominal structural excitations experienced by spacecraft structures can cause early unpredicted high structural life consumption or damage. The availability and cost of flight-certified sensors along with the size of spacecraft structures and allowable payload mass drives the need for a method to estimate loads using sparsely-located sensors. Numerous approaches such as physics-based, statistical learning, and physics-enhanced statistical learning algorithms have gained popularity among structural prognostics applications. However, developing noise-robust prediction models to assess loads and structural life predictions from a sparse multi-sensor data acquisition system can be a challenging task. This paper discusses the evaluation of physics-based versus machine-learning algorithms for predicting loads and structural life at mission critical locations on the spacecraft structure using a finite element loads analysis with the application of simulated noise and noise reduction techniques. To estimate the loads from accelerations, the physics-based algorithm leverages a loads transformation matrix from a Craig-Bampton reduced finite element model. A System Equivalent Reduction Expansion Process (SEREP) and a pseudo-inverse approach are considered to expand from the onboard sensor degrees of freedom to the Craig-Bampton model degrees of freedom. The machine learning algorithm provides a data driven solution/mapping of the sensor accelerations to the loads at the mission critical locations using a high dimensionality analysis. Although these strategies produce comparable loads prediction without noise, the limitations of these strategies with incorporating simulated noise and noise reduction techniques with low signal to noise ratio signals are evaluated. The study demonstrates the immense potential of statistical learning algorithms for sparse structural prognostic models and enhancing signal denoising techniques. These findings also highlight the need for noise-resilient prognostic models and low-noise data acquisition systems onboard spacecraft structures.

Spacecraft Structural Health Monitoring↗

DOE OSTI2016

Collectively loading programs in a multiple program multiple data environment

Techniques are disclosed for loading programs efficiently in a parallel computing system. In one embodiment, nodes of the parallel computing system receive a load description file which indicates, for each program of a multiple program multiple data (MPMD) job, nodes which are to load the program. The nodes determine, using collective operations, a total number of programs to load and a number of programs to load in parallel. The nodes further generate a class route for each program to be loaded in parallel, where the class route generated for a particular program includes only those nodes on which the program needs to be loaded. For each class route, a node is selected using a collective operation to be a load leader which accesses a file system to load the program associated with a class route and broadcasts the program via the class route to other nodes which require the program.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2017

Observed Temperature Effects on Load Cells

Researchers at Oak Ridge National Laboratory subjected load cells to a range of temperatures beyond their compensated range to characterize the temperature effect on the minimum dead load output over their entire operating temperature range. In modern front-end nuclear fuel cycle facilities, load cells are often used in UF6 feed and withdrawal stations to monitor the material being fed to or withdrawn from the cylinders. Load cells exhibit some temperature dependence; however, manufacturers try to minimize temperature effects by compensating load cells over a range of temperatures (typically from -10 °C to +40 °C (+14 °F to +104 °F)). Load cells in modern UF6 feed and withdrawal stations tend to operate beyond this range: down to -25 °C and up to 80 °C (-13 °F to 176 °F). While load cell data sheets often include specifications for the temperature effect on the minimum dead load output and the sensitivity over the compensated range, they do not include specifications for expected effects outside of this range. In this paper, we discuss our test setup and preliminary results of testing load cells representative of those that may be used in UF6 feed and withdrawal stations.

Mattingly, Gavin↗

DOE OSTI2018

Collectively loading programs in a multiple program multiple data environment

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2019

System and method for electric load identification and classification employing support vector machine

A method identifies electric load types of a plurality of different electric loads. The method includes providing a support vector machine load feature database of a plurality of different electric load types; sensing a voltage signal and a current signal for each of the different electric loads; determining a load feature vector including at least six steady-state features with a processor from the sensed voltage signal and the sensed current signal; and identifying one of the different electric load types by relating the load feature vector including the at least six steady-state features to the support vector machine load feature database.

Lu, Bin↗