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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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Crack Growth Rate Data Analysis program used for cyclis crack-growth testing of compact tension specimens. Program digitizes data on crack-opening displacement vs. load and reduces these into data on crack-growth rate vs. stress-intensity excursion. Written in HP BASIC.
Results of the space shuttle approach and landing test are examined in order to assess landing gear characteristics and performance and verify landing dynamic analyses. The landing gears were instrumented with load-calibrated strain gages, a wheel-speed sensor, and strut stroke measurement devices. The mathematical procedure used in predicting the shuttle touchdown loads and dynamics is presented together with the comparisons between measured flight data and the analytical predictions. Conclusions from these data are also presented.
A summary of a NASA design analysis and test program on the buckling of large-scale, integrally-stiffened metallic cylinders is presented. The test article designs were developed based on proposed NASA launch vehicle cylinder designs and span a significant portion of the design space. Various loading conditions were applied to the cylinders and include different combinations of axial compression, bending, and internal pressure loads that simulate typical launch vehicle loading scenarios. The data gathered from this test program is being used to develop and validate new analysis-based knockdown factors and design guidelines for these stiffened metallic cylinders. In this paper, the test article designs and fabrication methods are described along with the test facilities and instrumentation. Selected test and finite element analysis results are presented and compared and are used to illustrate the typical response characteristics of the stiffened metallic cylinders considered. Overall, good qualitative agreement is found, however, several discrepancies in the results were identified across several of the tests. The discrepancies were investigated thoroughly and can be attributed to variations in the as-built skin and stiffener geometry, variations in the measured geometric imperfection, and modeling assumptions associated with the boundary conditions, and loading imperfections. Based on these findings, several refinements were made to the finite element models which significantly improved the correlation between the test and analysis results. These modeling refinements are described and the updated analysis results are presented.
This presentation investigates the application of Physics-Informed Neural Networks (PINNs) for the analysis of turbine blades in a transonic cascade. PINNs are a machine learning method trained on losses calculated from reconstructed governing equations, assigned boundary/initial conditions, and measured data. We reconstruct the 2-D flow field in a transonic turbine cascade in two ways: the traditional forward approach (without training/experimental data) and by training the PINN using experimental data. We then compare the PINN solutions to measured data. This is repeated for three different turbine blades with distinct loading characteristics. The experimental data used for training is the static pressure measurements along the suction and pressure sides of each blade. The PINN is trained utilizing all available data, half the available data, data from only the leading edge region, and data from only the trailing edge region. It's shown that the PINN can reconstruct the flow field in all cases with acceptable errors. Cases where the PINN is trained on all the data, and even half the data, resulted in the lowest errors. The exit Mach number is inferred for each case and compared to the experimentally calculated value.
The analysis of the chordwise load distribution and its sensitivity to the various system parameters represents the next phase of the overall study and is the subject of the present two volume report. The present volume is a compilation of all of the time history response data obtained during the test program previously described. The data have been tabulated in the form of Fourier coefficients for reasons of compactness and for ease by the user to reproduce the unsteady component of the individual pressures and the complete (unsteady plus steady state components) integrated load results. This data volume contains the individual pressure response time histories along the chord followed by the corresponding integrated load results. A further description of these data tables can be found in the text that follows.
This effort used a new and novel method of acquiring strains called Sub-pixel Digital Video Image Correlation (SDVIC) on impact damaged Kevlar/epoxy filament wound pressure vessels during a proof test. To predict the burst pressure, the hoop strain field distribution around the impact location from three vessels was used to train a neural network. The network was then tested on additional pressure vessels. Several variations on the network were tried. The best results were obtained using a single hidden layer. SDVIC is a fill-field non-contact computer vision technique which provides in-plane deformation and strain data over a load differential. This method was used to determine hoop and axial displacements, hoop and axial linear strains, the in-plane shear strains and rotations in the regions surrounding impact sites in filament wound pressure vessels (FWPV) during proof loading by internal pressurization. The relationship between these deformation measurement values and the remaining life of the pressure vessels, however, requires a complex theoretical model or numerical simulation. Both of these techniques are time consuming and complicated. Previous results using neural network methods had been successful in predicting the burst pressure for graphite/epoxy pressure vessels based upon acoustic emission (AE) measurements in similar tests. The neural network associates the character of the AE amplitude distribution, which depends upon the extent of impact damage, with the burst pressure. Similarly, higher amounts of impact damage are theorized to cause a higher amount of strain concentration in the damage effected zone at a given pressure and result in lower burst pressures. This relationship suggests that a neural network might be able to find an empirical relationship between the SDVIC strain field data and the burst pressure, analogous to the AE method, with greater speed and simplicity than theoretical or finite element modeling. The process of testing SDVIC neural network analysis and some encouraging preliminary results are presented in this paper. Details are given concerning the processing of SDVIC output data such that it may be used as back propagation neural network (BPNN) input data. The software written to perform this processing and the BPNN algorithm are also discussed. It will be shown that, with limited training, test results indicate an average error in burst pressure prediction of approximately six percent,
In order to achieve the ambitious objectives of the Mars 2020 (M2020) mission, in particular the ability to autonomously traverse more challenging terrains more efficiently, new surface mobility software was developed for Enhanced Navigation (ENav). That decision was made early in the project, before most of the new surface flight software (FSW) existed, which created a need for a separate framework where the new navigation algorithms could be quickly prototyped and tested, before more realistic FSW-based testbeds became available. The JPL robotics team chose the Robot Operating System [1] (ROS) as the environment in which to test the new ENav algorithms. This made it possible to write the algorithms in the C language required by the FSW, so they could be directly ported over to the flight module later on, while leveraging all the C++ libraries and tools provided by ROS for simulation and testing. The ENav algorithms were developed as a separate C library, and stubs were used to replace any FSW-specific code, such as Event Reporting (EVRs) and data products (DPs). A ROS simulator was developed to generate a rich set of varied 3D terrains representative of the candidate Mars landing sites and simulate the physics of the rover motion, the point cloud perceived by the rover’s stereo vision system, and the new thinking-while-driving (TWD) navigation logic which directs the rover to drive autonomously to user-specified waypoints. To simulate the rover motion and perception, a ROS node was developed that uses a software library called HyperDrive Sim (HDSim), which is a wrapper for the Rover Sequencing and Visualization Program [2] (RSVP). That library provides roverterrain settling, realistic slip modelling, and camera rendering capability based on the rover’s NavCam machine vision models. To simulate the navigation logic, a ROS node was created that initializes and runs the ENav algorithms in a way that mimics the FSW execution, while also providing the capability to load and replay data products, including re-running the recorded inputs through the ENav algorithms for testing. An engineering Graphical User Interface (GUI) was also developed to visualize various elements, such as the rover pose during the drive, the simulated and perceived terrain, the selected local and global paths to the goal, the evaluated candidate paths and the reasons why they were rejected, the keep-in and keep-out zones (KIOZs), etc. Finally, an advanced Monte Carlo (MC) framework that can run many simulations in parallel on the Cloud and automatically generate reports that capture the key ENav performance metrics was developed to evaluate the system in a statisticallymeaningful way. This paper provides an overview of the ROSbased simulator used for testing the M2020 ENav algorithms.
Increasingly, carbon composite structures are being used in aerospace applications. Their highstrength, high-stiffness, and low-weight properties make them good candidates for replacing many aerospace structures currently made of aluminum or steel. Recently, many of the aircraft engine manufacturers have developed new commercial jet engines that will use composite fan cases. Instead of using traditional composite layup techniques, these new fan cases will use a triaxially braided pattern, which improves case performance. The impact characteristics of composite materials for jet engine fan case applications have been an important research topic because Federal regulations require that an engine case be able to contain a blade and blade fragments during an engine blade-out event. Once the impact characteristics of these triaxial braided materials become known, computer models can be developed to simulate a jet engine blade-out event, thus reducing cost and time in the development of these composite jet engine cases. The two main problems that have arisen in this area of research are that the properties for these materials have not been fully determined and computationally efficient computer models, which incorporate much of the microscale deformation and failure mechanisms, are not available. The research reported herein addresses some of the deficiencies present in previous research regarding these triaxial braided composite materials. The current research develops new techniques to accurately quantify the material properties of the triaxial braided composite materials. New test methods are developed for the polymer resin composite constituent and representative composite coupons. These methods expand previous research by using novel specimen designs along with using a noncontact measuring system that is also capable of identifying and quantifying many of the microscale failure mechanisms present in the materials. Finally, using the data gathered, a new hybrid micromacromechanical computer model is created to simulate the behavior of these composite material systems under static and ballistic impact loading using the test data acquired. The model also quantifies the way in which the fiber/matrix interface affects material response under static and impact loading. The results show that the test methods are capable of accurately quantifying the polymer resin under a variety of strain rates and temperature for three loading conditions. The resin strength and stiffness data show a clear rate and temperature dependence. The data also show the hydrostatic stress effects and hysteresis, all of which can be used by researchers developing composite constitutive models for the resins. The results for the composite data reveal noticeable differences in strength, failure strain, and stiffness in the different material systems presented. The investigations into the microscale failure mechanisms provide information about the nature of the different material system behaviors. Finally, the developed computer model predicts composite static strength and stiffness to within 10 percent of the gathered test data and also agrees with composite impact data, where available.
BACKGROUND: This study was conducted with the primary interest of providing data that would inform Vibration Isolation and Stabilization (VIS) system design and performance for the European Enhanced Exploration Exercise Device (E4D). In preparation for the International Space Station (ISS) in-flight demonstration, a list of critical Human Health Countermeasures (HHC) exercises was compiled [1]. The goal of this study was to assess the ground reaction forces and moments imposed by an exercising subject in each of the six VIS Degrees of Freedom (DOFs) during a comprehensive set of these critical exercises performed on the E4D. METHODS AND RESULTS: The ISS in-flight demonstration list of critical exercises included seated aerobic rowing, bent-over rowing, cycling, front squats, back squats, conventional deadlifts, Romanian deadlifts, heel raises, overhead presses, reverse chops, and power clean presses. At the NASA Johnson Space Center (JSC) Prototype Immersive Technology (PIT) laboratory, motion capture data were collected on critical E4D exercises for six subjects. At the NASA JSC Active Response Gravity Offload System (ARGOS) facility, additional motion capture and load cell data were collected on offloaded trials for four subjects. Select data were extrapolated to represent a 5th percentile female subject and a 95th percentile male subject. A previous investigation comparing the forces obtained from the load cell and from motion capture based data found a satisfactory level of agreement between the two measurements [2]. The motion capture based data were analyzed for this study since it is driven by the subject’s trajectory alone, automatically excluding any forces exerted on the subject by the ARGOS offloading harness. The OpenSim [3, 4] biomechanical simulation inverse kinematics tool was used to calculate the joint angles based on the locations of motion capture markers placed at key positions on the subject’s body. An OpenSim plugin was then used to obtain the forces and moments generated by the subject during each trial, with the moments computed relative to the equilibrium location of the subject’s feet [5]. The force of gravity was also removed to simulate the loads generated by the exercise when performed in microgravity. The load plots for each trial were generated and visually analyzed to obtain the magnitudes of the peak loads for each exercise in each DOF. The typical period of exercise for each trial was also estimated and used to calculate the frequency for each trial. The exercise loads data was then organized in multiple ways to capture different aspects of the data. As a result of this study, we present a summary of the load magnitudes observed during these critical exercises utilizing the E4D.
This is an effort aimed at validating recent hover prediction methods. The experimental basis for this validation work is an extensive set of loads, wake and performance data, which were obtained from a pressure instrumented model UH-60 rotor tested at the Sikorsky hover test facility and at Duits-Nederlandse Windtunnel (DNW). This model was equipped with replaceable tips - including a tapered and a BERP-type tip - which permitted studies of the effects of rotor geometry. The central prediction method studied is a free-wake, vortex embedded, full-potential CFD method - called HELIX-I. It is found that the HELIX-I code produces very good comparisons with the data including wake, surface pressure and performance. Comparisons with the measured radial load distributions have permitted an improved understanding of the wake resolution modelling requirements of CFD methods. Since HELIX-I is a combined Eulerian/Lagrangian method, limited comparisons are also made with a Lagrangian boundary element code (called EHPIC) and an Eulerian Navier-Stokes code (called TURNS). In most cases all methods produce good comparisons with the data. It is found that the HELIX-I code provides a good compromise between the speed of boundary integral methods and the comprehensive nature of Navier-Stokes methods.
Data on performance and rotor loads for a teetering-rotor, AH-1G helicopter flown with a main rotor that had the NLR-1T airfoil as the blade-section contour are presented. The test envelope included hover, forward-flight speed sweeps from 35 to 85 m/sec, and collective-fixed maneuvers at about 0.25 tip-speed ratio. The data set for each test point described vehicle flight state, control positions, rotor loads, power requirements, and blade motions. Rotor loads are reviewed primarily in terms of peak-to-peak and harmonic content. Lower frequency components predominated for most loads and generally increased with increased airspeed, but not necessarily with increased maneuver load factor.
Cyclic plastic stresses in notched aluminum alloy sheets under constant-amplitude repeated tension and reversed loading - fatigue life data
Composite tensile failure modes, discussing failure load prediction, experimental data and statistical analysis of stress concentration effects
Analog-to-digital converter converts 10 volt full scale input signal into 13 bit digital output. Advantages include high sensitivity, linearity, low quantitizing error, high resistance to mechanical shock and vibration loads, and temporary data storage capabilities.
Composite tensile-failure modes, discussing failure load prediction, experimental data and statistical analysis of stress concentration effects
The effect of collector, guard-ring potential imbalance on the observed collector-current-density J, collector-to-emitter voltage V characteristic was evaluated in a planar, fixed-space, guard-ringed thermionic converter. The J,V characteristic was swept in a period of 15 msec by a variable load. A computerized data acquisition system recorded test parameters. The results indicate minimal distortion of the J,V curve in the power output quadrant for the nominal guard-ring circuit configuration. Considerable distortion, along with a lowering of the ignited-mode striking voltage, was observed for the configuration with the emitter shorted to the guard ring. A limited-range performance map of an etched-rhenium, niobium, planar converter was obtained by using an improved computer program for the data acquisition system.
Human skeletal muscle may be regarded as an electro-mechanical transducer. Its physiological input is a neural signal originating at the alpha motoneurons in the spinal cord and its output is force and muscle contraction, these both being dependent on the external load. Some experimental data taken during voluntary efforts around the ankle joint and by direct electrical stimulation of the nerve are described. Some of these experiments are simulated by an analog model, the input of which is recorded physiological soleus muscle EMG. The output is simulated foot torque. Limitations of a linear model and effect of some nonlinearities are discussed.
A computer program is presented for thin-wire antennas and scatters in a homogeneous conducting medium. The anaylsis is performed in the real or complex frequency domain. The program handles insulated and bare wires with finite conductivity and lumped loads. The output data includes the current distribution, impedance, radiation efficiency, gain, absorption cross section, scattering cross section, echo area and the polarization scattering matrix. The program uses sinusoidal bases and Galerkin's method.