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NASA NTRS2022

A Framework for Deep Learning Emulation of Numerical Models With a Case Study in Satellite Remote Sensing

Numerical models based on physics represent the state of the art in Earth system modeling and comprise our best tools for generating insights and predictions. Despite rapid growth in computational power, the perceived need for higher model resolutions overwhelms the latest generation computers, reducing the ability of modelers to generate simulations for understanding parameter sensitivities and characterizing variability and uncertainty. Thus, surrogate models are often developed to capture the essential attributes of the full-blown numerical models. Recent successes of machine learning methods, especially deep learning (DL), across many disciplines offer the possibility that complex nonlinear connectionist representations may be able to capture the underlying complex structures and nonlinear processes in Earth systems. A difficult test for DL-based emulation, which refers to function approximation of numerical models, is to understand whether they can be comparable to traditional forms of surrogate models in terms of computational efficiency while simultaneously reproducing model results in a credible manner. A DL emulation that passes this test may be expected to perform even better than simple models with respect to capturing complex processes and spatiotemporal dependencies. Here, we examine, with a case study in satellite-based remote sensing, the hypothesis that DL approaches can credibly represent the simulations from a surrogate model with comparable computational efficiency. Our results are encouraging in that the DL emulation reproduces the results with acceptable accuracy and often even faster performance. We discuss the broader implications of our results in light of the pace of improvements in high-performance implementations of DL and the growing desire for higher resolution simulations in the Earth sciences.

Bayesian Deep Learning↗

NASA NTRS2017

The Use of a Satellite Communications System for Command and Control of the National Aeronautics and Space Administration Surrogate Unmanned Aerial System Research Aircraft

The NASA Langley Research Center has transformed a Cirrus Design SR22 general aviation (GA) aircraft into an Unmanned Aerial Systems (UAS) Surrogate research aircraft which has served for several years as a platform for unmanned systems research and development. The aircraft is manned with a Safety Pilot and a Research Systems Operator (RSO) that allows for flight operations almost any-where in the national airspace system (NAS) without the need for a Federal Aviation Administration (FAA) Certificate of Authorization (COA). The UAS Surrogate can be remotely controlled from a modular, transportable ground control station (GCS) like a true UAS. Ground control of the aircraft is accomplished by the use of data links that allow the two-way passage of the required data to control the aircraft and provide the GCS with situational awareness. The original UAS Surrogate data-link system was composed of redundant very high frequency (VHF) data radio modems with a maximum range of approximately 40 nautical miles. A new requirement was developed to extend this range beyond visual range (BVR). This new requirement led to the development of a satellite communications system that provided the means to command and control the UAS Surrogate at ranges beyond the limits of the VHF data links. The system makes use of the Globalstar low earth orbit (LEO) satellite communications system. This paper will provide details of the development, implementation, and flight testing of the satellite data communications system on the UAS Surrogate research aircraft.

Howell, Charles T.↗

NASA NTRSDate not supplied

Dragonfly Rotor Optimization using Machine Learning Applied to an OVERFLOW Generated Airfoil Database

NASA’s 4th New Frontiers Mission is the Titan Dragonfly relocatable lander. This coaxial quadrotor vehicle will be launched on a rocket to Titan in 2028. Following a gravity assisted Earth flyby and an approximate 6-year transit, Dragonfly will enter the Titan atmosphere around 2034 with the goal of exploring Titan’s pre-biotic chemistry and habitability. The multirotor design for this unique application has continually evolved since 2016 with constraints such as Titan’s cryogenic atmosphere at 95 Kelvin (-288 F), gravity 14% that of Earth’s, atmospheric density 440% of standard sea-level air, and the inability to test the entire system together under all these conditions until the first flight on Titan. This paper focuses on rotor design aspects of the Dragonfly lander and introduces a novel framework for multirotor design optimization considering multiple flight conditions. The methodology leverages machine learning methods and is demonstrated in the context of Dragonfly. A new OVERFLOW Machine Learning Airfoil Performance (PALMO) database is first presented. PALMO is then wrapped inside a Bayesian optimization framework and applied to a 4-rotor system (one side of the Dragonfly lander). Training data is generated on each iteration of the optimization using the CAMRAD-II comprehensive analysis software to evaluate successive rotor designs in multiple relevant flight conditions. An optimal design for the 4-rotor system was found with approximately 900 rotor designs analyzed in CAMRAD-II, which required 9 million queries of the PALMO surrogate models. This demonstration case evaluated 10,000,000 potential candidate rotor designs in 5.5 hours on 114 CPU cores using uniform inflow, and in 27.8 hours using the prescribed wake model. This work thus enables mid-fidelity rotor design optimization without requiring access to high-performance computing.

Dragonfly↗

NASA NTRS1999

Measuring Directional Wave Spectra and Wind Speed with a Scanning Radar Altimeter

The geometry for the NASA Scanning Radar Altimeter (SRA) is shown. It transmits a 8-ns duration pulse at Ka-band (8.3 mm) and measures time of flight as it scans a 1 degree (two-way) beam from left to right across the aircraft ground track. The most recent configuration determines the surface elevation at 64 points spaced at uniform angular intervals of about 0.7 across a swath whose width is about 0.8 times the aircraft altitude. The system generates these raster lines of the surface topography beneath the aircraft at about a 10 Hz rate. In postflight processing the SRA wave topographic data are transformed with a two-dimensional Fast Fourier Transformation (FFT) and Doppler corrected to produce directional wave spectra. The SRA is not absolutely calibrated in power, but by measuring the relative fall-off of backscatter with increasing incidence angle, the SRA can also determine the mean square slope (mss) of the sea surface, a surrogate for wind speed. For the slope-dependent specular point model of radar sea surface scattering, an expression approximated by a geometric optics form, for the relative variation with incidence angle of the normalized backscatter radar cross section would be sigma (sup 0) (sub rel) = sec (exp 4) theta exp (-tan squared theta/mss) where theta is the off-nadir incidence angle.

Walsh, E. J.↗

NASA NTRS2019

Improving Accuracy of Structural Dynamic Modification with Augmented Residual Vectors

It is often important to perform sensitivity analysis to determine how a structural model will be impacted by design changes. Often, the structural analysts will manually make changes to the finite element model (FEM) to determine the effects. But when dealing with a large FEM with millions of degrees of freedom these manual changes can be cumbersome and calculation of the effects can computationally expensive. Therefore, it is desirable to determine the effects of model changes through approximation methods. One common technique is to determine the analytical sensitivity of the FEM model with respect to the given change. These analytical sensitivities are valid when small changes are made to the structural model, but invalid if large changes need to be assessed. Another approach is to use Structural Dynamic Modification (SDM) to create a surrogate model to analyze model changes. SDM is a widely-used sensitivity method and is used in applications of model updating, uncertainty quantification, and model design studies. SMD is valid for moderate (10-20 percent) changes in the structural model, but model approximations are often needed for large parameter changes (greater than 20 percent). Structural Dynamic Modification can be improved by using residual vectors to augment the surrogate model formulation from SDM. Adding the residual modes increases the fidelity of the surrogate model while keeping the computational cost low. This paper discusses the application and limitations of the augmented residual modes method to two structures: the Integrated Spacecraft and Payload Element (ISPE) of the Space Launch System (SLS) and the full SLS as it is configured during its Integrated Modal Test (IMT).

Stewart, Eric C.↗

NASA NTRS2017

Passive Earth Entry Vehicle Landing Test

Two full-scale passive Earth Entry Vehicles (EEV) with realistic structure, surrogate sample container, and surrogate Thermal Protection System (TPS) were built at NASA Langley Research Center (LaRC) and tested at the Utah Test and Training Range (UTTR). The main test objective was to demonstrate structural integrity and investigate possible impact response deviations of the realistic vehicle as compared to rigid penetrometer responses. With the exception of the surrogate TPS and minor structural differences in the back shell construction, the two test vehicles were identical in geometry and both utilized the Integrated Composite Stiffener Structure (ICoSS) structural concept in the forward shell. The ICoSS concept is a lightweight and highly adaptable composite concept developed at NASA LaRC specifically for entry vehicle TPS carrier structures. The instrumented test vehicles were released from a helicopter approximately 400 m above ground. The drop height was selected such that at least 98% of the vehicles terminal velocity would be achieved. While drop tests of spherical penetrometers and a low fidelity aerodynamic EEV model were conducted at UTTR in 1998 and 2000, this was the first time a passive EEV with flight-like structure, surrogate TPS, and sample container was tested at UTTR for the purpose of complete structural system validation. Test results showed that at a landing vertical speed of approximately 30 m/s, the test vehicle maintained structural integrity and enough rigidity to penetrate the sandy clay surface thus attenuating the landing load, as measured at the vehicle CG, to less than 600 g. This measured deceleration was found to be in family with rigid penetrometer test data from the 1998 and 2000 test campaigns. Design implications of vehicle structure/soil interaction with respect to sample container and sample survivability are briefly discussed.

Kellas, Sotiris↗

NASA NTRS2023

Efficient Calibration of Expensive Computational Models

Accounting for uncertainty when calibrating expensive computational models is a common challenge faced by scientists and engineers. Often Bayesian techniques are adopted to estimate a probability density function over the model parameters given noisy empirical data. The methods used to perform this type of probabilistic calibration are computationally prohibitive in that they require a large number of evaluations of the expensive model. In these cases, surrogate modeling -- that is, using a fast-to-evaluate, lower fidelity stand-in for the original computational model -- may be the only option to alleviate this computational burden. However, the upfront cost of generating training data to build a surrogate model can itself be expensive. As such, it is important to be judicious when selecting training points at which the full-fidelity model is evaluated. Here, an active learning approach is proposed that enables efficient selection of training points using approximate samples of the calibrated parameter probability density function. In this way, the training points can be concentrated in regions where the calibration algorithm requires high model accuracy.

active learning↗

NASA NTRS1997

A Novel, Poly-Etalon, Fabry-Perot for Planetary Research

In an effort to develop a mechanically robust, high throughput and solid state spectrometer several liquid crystal Fabry-Perot etalons were constructed. The etalons were tested for spectral response, radiation resistance and optical transmission. The first year of this project was spent developing and understanding the properties of the liquid crystal etalons; in the second year an intensified all-sky imaging system was developed around a pair of LC etalons. The imaging system, developed jointly with SRI International represents a unique brassboard to demonstrate the use of LC etalons as tunable filters. The first set of etalons constructed in year one of this project were tested for spectral response and throughput while etalon surrogates were exposed to proton radiation simulating the exposure of an object in Low Earth Orbit (LEO). The 2" diameter etalons had a measure finesse of approximately 10 and were tunable over five orders. Liquid crystals exposed to proton irradiation showed no signs of damage. In year two two larger diameter (3") etalons were constructed with gaps of 3 and 5 microns. This pair of etalons is for use in a high resolution, all-sky spectral imager. The WATUMI imager system follows the heritage of all sky, narrow band, intensified imagers however it includes two LC Fabry-Perot etalons to provide tunability and the ability to switch wavelengths rapidly, an import consideration in auroral airglow imaging. This work also resulted in two publications and one poster presentation. The instrument will be uniquely capable, with superior throughput and speed, to measure optical airglow of multiple emission lines in harsh conditions.

Kerr, Robert B.↗

NASA NTRSDate not supplied

Probabilistic Calibration of Expensive Models using Efficiently Trained Surrogates

Calibration of computational models in the presence of uncertainty is often cast as a Bayesian inference problem and solved via sampling methods, e.g., Markov chain Monte Carlo. When the computational model is expensive, this task becomes intractable due to the large number of samples required to accurately estimate the posterior distribution of the calibration parameters. A popular solution to this problem is to use machine learning to develop a faster-to-evaluate, lower-fidelity substitute for the original model to serve as a surrogate while solving the inference problem. Although considered an offline cost, generating training data to construct this surrogate model can still be an expensive task in practice. An active learning algorithm is presented that focuses training on improving surrogate accuracy specifically in and around the bulk of the posterior distribution, as this is where the model is exercised during calibration. Candidate samples are drawn from families of distributions related to an approximation of the posterior. The sample maximizing predictive variance is then selected for evaluation by the original computational model, yielding a label for the training point. Iterating this approach increases efficiency relative to space filling designs (e.g., Latin hypercube sampling) by avoiding low probability points. Practical considerations are discussed, including the benefits of using a sequential Monte Carlo sampling approach, convergence heuristics, and the importance of both exploration and exploitation given that the true posterior is unknown a priori.

uncertainty quantification↗

NASA NTRS2000

Uncertainty Analysis of Decomposing Polyurethane Foam

Sensitivity/uncertainty analyses are necessary to determine where to allocate resources for improved predictions in support of our nation's nuclear safety mission. Yet, sensitivity/uncertainty analyses are not commonly performed on complex combustion models because the calculations are time consuming, CPU intensive, nontrivial exercises that can lead to deceptive results. To illustrate these ideas, a variety of sensitivity/uncertainty analyses were used to determine the uncertainty associated with thermal decomposition of polyurethane foam exposed to high radiative flux boundary conditions. The polyurethane used in this study is a rigid closed-cell foam used as an encapsulant. Related polyurethane binders such as Estane are used in many energetic materials of interest to the JANNAF community. The complex, finite element foam decomposition model used in this study has 25 input parameters that include chemistry, polymer structure, and thermophysical properties. The response variable was selected as the steady-state decomposition front velocity calculated as the derivative of the decomposition front location versus time. An analytical mean value sensitivity/uncertainty (MV) analysis was used to determine the standard deviation by taking numerical derivatives of the response variable with respect to each of the 25 input parameters. Since the response variable is also a derivative, the standard deviation was essentially determined from a second derivative that was extremely sensitive to numerical noise. To minimize the numerical noise, 50-micrometer element dimensions and approximately 1-msec time steps were required to obtain stable uncertainty results. As an alternative method to determine the uncertainty and sensitivity in the decomposition front velocity, surrogate response surfaces were generated for use with a constrained Latin Hypercube Sampling (LHS) technique. Two surrogate response surfaces were investigated: 1) a linear surrogate response surface (LIN) and 2) a quadratic response surface (QUAD). The LHS techniques do not require derivatives of the response variable and are subsequently relatively insensitive to numerical noise. To compare the LIN and QUAD methods to the MV method, a direct LHS analysis (DLHS) was performed using the full grid and timestep resolved finite element model. The surrogate response models (LIN and QUAD) are shown to give acceptable values of the mean and standard deviation when compared to the fully converged DLHS model.

Hobbs, Michael L.↗

NASA NTRS2004

CoSSIR: A New Instrument for Exploring the Utility of Submillimeter-wave Radiometry for Earth Observation

The Conical Scanning Submillimeter-wave Imaging Radiometer (CoSSIR) has been developed to study the application of submillimeter-wave radiometry for remote sensing of cirrus clouds and humidity sounding. Measurements of the global distribution of ice cloud mass and particle size are important for understanding the Earth s energy budget and for evaluating global climate models. The spatial variability and the wide variety of cloud particle shapes and sizes make ice clouds particularly difficult to measure. Ice clouds are essentially undetectable at microwave frequencies due to the low dielectric of ice and small size of the particles relative to wavelength. However, submillimeter wavelengths demonstrate significant response to the presence of ice clouds thus this frequency regime is applicable to measuring ice clouds. Another potentially viable application for submillimeter-wave radiometry is humidity and temperature sounding. The principle of sounding at submillimeter wavelengths is similar to that at microwavelengths. Submillimeter-wave radiometry has the advantage of achieving finer spatial resolution using a smaller antenna aperture which is an important consideration for spaceborne observatories. Submillimeter-wave radiometry also offers the potential of sounding over land and as a surrogate measurement for precipitation. CoSSIR is a new instrument to explore these applications. The CoSSIR is designed to fly aboard the ER-2 aircraft and its modest size (approximately 100 kg) permits it to be configured for other aircraft. A dual-axes gimbals mechanism provides conical, across-track, and along-track scanning capability. In its present configuration CoSSIR has fifteen channels between 183 GHz and 640 GHz. Three channels are centered about the 183 GHz water vapor absorption line, four channels are centered about the 380 GHz water vapor absorption line, and three dual-polarized channels are centered about the 487 GHz oxygen absorption line. Two channels are located in atmospheric windows at 220 GHz and 640 GHz. All channels are single-linear polarized with the exception of those near 487 GHz. Calibration is achieved by periodically observing two blackbody radiators; one blackbody is heated to approximately 325 K and the other is approximately 250 K during flight. Details of the instrument design as well as measurements from the Cirrus Regional Study of Tropical Anvils and Cirrus Layers - Florida Area Cirrus Experiment will be presented.

Racette, P. E.↗

NASA NTRS2004

Long-Lag, Wide-pulse Gamma-Ray Bursts

Currently, the best available probe of the early phase of gamma-ray burst (GRB) jet attributes is the prompt gamma-ray emission, in which several intrinsic and extrinsic variables determine GRB pulse evolution. Bright, usually complex bursts have many narrow pulses that are difficult to model due to overlap. However, the relatively simple, long spectral lag, wide-pulse bursts may have simpler physics and are easier to model. In this work we analyze the temporal and spectral behavior of wide pulses in 24 long-lag bursts, using a pulse model with two shape parameters - width and asymmetry - and the Band spectral model with three shape parameters. We find that pulses in long-lag bursts are distinguished both temporally and spectrally from those in bright bursts: the pulses in long spectral lag bursts are few in number, and approximately 100 times wider (10s of seconds), have systematically lower peaks in vF(v), harder low-energy spectra and softer high-energy spectra. We find that these five pulse descriptors are essentially uncorrelated for our long-lag sample, suggesting that at least approximately 5 parameters are needed to model burst temporal and spectral behavior. However, pulse width is strongly correlated with spectral lag; hence these two parameters may be viewed as mutual surrogates. We infer that accurate formulations for estimating GRB luminosity and total energy will depend on several gamma-ray attributes, at least for long-lag bursts. The prevalence of long-lag bursts near the BATSE trigger threshold, their predominantly low vF(v) spectral peaks, and relatively steep upper power-law spectral indices indicate that Swift will detect many such bursts.

Norris, J. P.↗

NASA NTRS2014

Raising Nuclear Thermal Propulsion (NTP) Technology Readiness Above 3

NTP development is currently supported by the NASA program office "Advanced Exploration Systems". The concept is a main propulsion option being considered for human missions to Mars in the 2030's. Major NTP development took place in the 1960's and 1970's under the Rover/NERVA program. The technology had matured to TRL 6 and was preparing to go to TRL 7 with a prototype flight engine before the program was cancelled. Over the last 40 years, a variety of continuations started, but only lasted a few years each. The Rover/NERVA infrastructure is almost all gone. The only remains are a few pieces of hardware, final reports and a few who worked the Rover/NERVA. Two types of nuclear fuel are being investigated to meet the current engine design specific impulse of 900 seconds compared to approximately 850 seconds demonstrated during Rover/NERVA. One is a continuation of composite fuel with new coatings to better control mid-band corrosion. The other type is a CERMET fuel made of Tungsten and UO2. Both fuels are being made from Rover/NERVA lessons learned, but with slightly different recipes to increase fuel endurance at higher operating temperatures. The technology readiness level (TRL) of these current modified reactor fuels is approximately TRL 3. To keep the development cost low and help mature the TRL level past 4 quickly, a few special non-nuclear test facilities have been made to test surrogate fuel, with depleted uranium, as coupons and full length elements. Both facilities utilize inductive heating and are licensed to handle depleted uranium. TRL 5 requires exposing the fuel to a nuclear environment and TRL 6 requires a prototype ground or flight engine system test. Currently, three different NTP ground test facility options are being investigated: exhaust scrubber, bore hole, and total exhaust containment. In parallel, a prototype flight demonstration test is also being studied. The first human mission to Mars in the 2030's is currently 2033. For an advanced propulsion concept to be seriously considered for use, the engine development plans need to show it is feasible and affordable to reach TRL 8 by 2027 and can be qualified for human mission use.

Gerrish, Harold P., Jr.↗

NASA NTRS2017

A Ratio of Spore to Viable Organisms: A Case Study of the JPL-SAF Cleanroom

Spacecraft surfaces that are destined to land on potential life-harboring celestial bodies are required to be rigorously cleaned and continuously monitored for spore bioburden as a proxy for spacecraft cleanliness. The NASA standard assay (NSA), used for spacecraft bioburden estimates, specifically measures spores that are cultivable, aerobic, resistant to heat shock, and grow at 30 C in a nutrient-rich medium. Since the vast majority of microorganisms cannot be cultivated using the NSA, it is necessary to utilize state-of-the art molecular techniques to better understand the presence of all viable microorganisms, not just those measured with the NSA. In this study, the nutrient-deprived low biomass cleanrooms, where spacecraft are assembled, were used as a surrogate for spacecraft surfaces to measure the ratio of NSA spores in relation to the total viable microorganism population in order to make comparisons with the 2006 Space Studies Board (SSB) estimate of 1 spore per approximately 50,000 viable organisms. Ninety-eight surface wipe samples were collected from the Spacecraft Assembly Facility (SAF) cleanroom at the Jet Propulsion Laboratory (JPL) over a 6-month period. The samples were processed and analyzed using classical microbiology along with molecular methodology. Traditional microbiology plating methods were used to determine the cultivable bacterial, fungal, and spore populations. Molecular assays were used to determine the total organisms (TO, dead and live) and the viable organisms (VO, live). The TO was measured using adenosine triphosphate (ATP) and quantitative polymerase chain reaction (qPCR) assays. The VO was measured using internal ATP, propidium monoazide (PMA)-qPCR, and flow cytometry (after staining for viable microorganisms) assays. Based on the results, it was possible to establish a ratio between spore counts and VO for each viability assay. The ATP-based spore to VO ratio ranged from 149-746, and the bacterial PMA-qPCR assay-based ratio ranged from 314-1,491 VO, per spore. The most conservative estimate came from fluorescent-assisted cell sorting (FACS), which estimated the ratio to be 12,091 VO per 1 NSA spore. Since archaeal (less than 1%) and fungal (approximately 2%) populations were negligible, the spore to VO ratios were based on bacterial population estimates. The most conservative ratio from this study can be used as a replacement for the SSB estimate on nutrient-deprived (oligotrophic) desiccated spacecraft surfaces, to estimate the VO from NSA measurements without utilizing state-of-the art molecular methods that are costly and require more biomass than is typically found on spacecraft surfaces.

Hendrickson, Ryan↗

NASA NTRS2017

Comprehensive Measurement of Microbial Burden in Nutrient-Deprived Cleanrooms

Spacecraft surfaces that are destined to land on potential life-harboring celestial bodies are required to be rigorously cleaned and continuously monitored for spore bioburden as a proxy for spacecraft cleanliness. The NASA standard spore assay (NSA), used for spacecraft bioburden estimates, specifically measures spores that are cultivable, aerobic, resistant to heat shock, and grow at 30˚C in a nutrient-rich medium. Since the vast majority of microorganisms cannot be cultivated using the NSA assay, it is necessary to utilize state-of-the art molecular techniques to better understand the presence of all viable microorganisms, not just those measured with the NSA. In this study, the nutrient-deprived low biomass cleanrooms, where spacecraft are assembled, were used as a surrogate to spacecraft surfaces to measure the ratio of NSA spores in relation to the total viable microorganism population to compare with a 2006 space studies report that estimates that for every 1 spore there is approximately 50,000 viable organisms. Ninety-eight surface wipe samples were collected from the spacecraft assembly facility (SAF) cleanroom at the Jet Propulsion Laboratory (JPL) over a 6-month period. The samples were processed and analyzed using classical microbiology along with molecular assays. Traditional microbiology plating methods were used to determine the cultivable bacterial, fungal, and spore populations. Molecular assays were used to determine the total organisms (TO, dead and live) and the viable organisms (VO, live). The TO was measured using adenine triphosphate (ATP) and quantitative polymerase chain reaction (qPCR) assays. The VO was measured using internal ATP, propidium monoazide (PMA)-qPCR, and flow cytometry (after staining for viable microorganisms) assays. Based on the results, it was possible to establish a ratio between spore counts and VO for each viability assay. The ATP based spore to VO ratio ranged from 149 – 746 and the bacterial PMA-qPCR assay based ratio ranged from 314 – 1491 VO. The most conservative estimate came from FACS, which estimated the ratio to be 12,091 VO per 1 NSA spore. Since archaeal (<1%) and fungal (~2%) populations were negligible, the spore to VO ratios were based on bacterial population estimates. The most conservative ratio from this study can be used as a replacement for the SSB estimate on nutrient-deprived (oligotrophic) desiccated spacecraft surfaces, to estimate the VO from NSA measurements without utilizing state-of-the art molecular methods that are costly and require more biomass than is typically found of spacecraft surfaces.

Venkateswaran, Kasthuri↗

NASA NTRS2011

Full-Scale Crash Test of an MD-500 Helicopter

A full-scale crash test was successfully conducted in March 2010 of an MD-500 helicopter at NASA Langley Research Center s Landing and Impact Research Facility. The reasons for conducting this test were threefold: 1 To generate data to be used with finite element computer modeling efforts, 2 To study the crashworthiness features typically associated with a small representative helicopter, and 3 To compare aircraft response to data collected from a previously conducted MD-500 crash test, which included an externally deployable energy absorbing (DEA) concept. Instrumentation on the airframe included accelerometers on various structural components of the airframe; and strain gages on keel beams, skid gear and portions of the skin. Three Anthropomorphic Test Devices and a specialized Human Surrogate Torso Model were also onboard to collect occupant loads for evaluation with common injury risk criteria. This paper presents background and results from this crash test conducted without the DEA concept. These results showed accelerations of approximately 30 to 50 g on the airframe at various locations, little energy attenuation through the airframe, and moderate to high probability of occupant injury for a variety of injury criteria.

Littell, Justin↗

NASA NTRS1980

An alternative approach to the numerical simulation of steady inviscid flow

A numerical procedure for the efficient simulation of steady inviscid flow is described and its utility demonstrated. Application of the surrogate equation technique allows the formulation of stable, fully conservative, type dependent finite difference equations for use in obtaining numerical solutions to systems of first order partial differential equations, such as the steady state Euler equations or their various approximations. Computational results are presented for the full Euler equations and for the transonic disturbance equations. For the latter case, a computational efficiency greater than that obtained by means of the standard perturbation potential approach is indicated.

Johnson, G. M.↗

NASA NTRS2005

Long-Lag, Wide-pulse Gamma-Ray Bursts

The best available probe of the early phase of gamma-ray burst (GRB) jet attributes is the prompt gamma-ray emission, in which several intrinsic and extrinsic variables determine observed GRB pulse evolution, including at least: jet opening angle, profiles of Lorentz factor and matter/field density, distance of emission region from central source, and viewing angle. Bright, usually complex bursts have many narrow pulses that are difficult to model due to overlap. However, the relatively simple, long spectral lag, wide-pulse bursts may have simpler physics and are easier to model. We have analyzed the temporal and spectral behavior of wide pulses in 24 long-lag bursts from the BATSE sample, using a pulse model with two shape parameters - width and asymmetry - and the Band spectral model with three shape parameters. We find that pulses in long-lag bursts are distinguished both temporally and spectrally from those in bright bursts: the pulses in long spectral lag bursts are few in number, and approximately 100 times wider (10s of seconds), have systemtically lower peaks in nu*F(nu), harder low-energy spectra and softer high-energy spectra. These five pulse descriptors are essentially uncorrelated for our long-lag sample, suggesting that at least approximately 5 parameters are needed to model burst temporal and spectral behavior, roughly commensurate with the theoretical phase space. However, we do find that pulse width is strongly correlated with spectral lag; hence these two parameters may be viewed as mutual surrogates. The prevalence of long-lag bursts near the BATSE trigger threshold, their predominantly low nu*F(nu) spectral peaks, and relatively steep upper power-law spectral indices indicate that Swiift will detect many such bursts.

Norris, J. P.↗