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All sourcesNASA NTRSDOE OSTI
NASA NTRS2007

Detector Noise Characterization and Performance of MODIS Thermal Emissive Bands

MODIS has 16 thermal emissive bands, a total of 160 individual detectors (10 for each spectral bands), located on the two cold focal plane assemblies (CFPA). MODIS TEB detectors were fully characterized pre-launch in a thermal vacuum (TV) environment using a NIST traceable blackbody calibration source (BCS) with temperatures ranging from 170 to 340K. On-orbit the TEB detectors are calibrated using an on-board blackbody (BB) on a scan-by-scan basis. For nominal on-orbit operation, the on-board BB temperature is typically controlled at 285K for Aqua MODIS and 290K for Terra MODIS. For the MODIS TEB calibration, each detector's noise equivalent temperature difference (NEdT) is often used to assess its performance and this parameter is a major contributor to the calibration uncertainty. Because of its impact on sensor calibration and data product quality, each MODIS TEB detector's NEdT is monitored on a daily basis at a fixed BB temperature and completely characterized on a regular basis at a number of BB temperatures. In this paper, we describe MODIS on-orbit TEB NEdT characterization activities, approaches, and results. We compare both pre-launch and on-orbit performance with sensor design specification and examine detector noise characterization impact on the calibration uncertainty. To date, 135 TEB detectors (out of a total of 160 detectors) in Terra MODIS (launched in December 1999) and 158 in Aqua MODIS (launched in May 2002) continue to perform with their NEdT below (or better than) their design specifications. A complete summary of all TEB noisy detectors, identified both pre-launch and on-orbit, is provided.

Xiong, X.↗
NASA NTRSDate not supplied

Quantum Hardware-Enabled Molecular Dynamics via Transfer Learning

The ability to perform ab initio molecular dynamics simulations using potential energy surfaces provided by quantum computers would open the door to virtually exact dynamics for a variety of chemical and biochemical systems, with impacts on catalysis and biophysics. Nonetheless, performing molecular dynamics on surfaces produced by quantum hardware has been hampered by the noisy energies typically produced by quantum computers and challenges associated with computing gradients and scaling to large systems interest. A recent set of advances in machine learning, known as transfer learning, provides a new path forward for molecular dynamics simulations on quantum hardware. Transfer learning offers a workaround, where one first trains models on larger, less accurate classical datasets and then refines them on smaller, more accurate quantum datasets. We explore this approach by training machine learning models to predict a molecule's potential energy based on its geometric structure using Behler-Parrinello neural networks. When successfully trained, the model enables energy gradient predictions necessary for dynamic simulations. To reduce the quantum resources needed, the model is initially trained with data derived from classical density functional theory and subsequently refined with a smaller dataset obtained from a variational quantum eigensolver optimization of the unitary coupled cluster ansatz. We show that this approach significantly reduces the size of the needed quantum training dataset while capturing the high accuracies needed within quantum chemistry simulations. The success of this two-step training method opens more opportunities to apply machine learning models on quantum data, a significant stride towards efficient quantum-classical hybrid computational models.

quantum computing↗
NASA NTRS1998

Modeling Climate-Biosphere Interactions in the Boreal Forest

The overall goal of this BOREAS Program was to develop, test, and apply a model of the carbon balance of boreal forest sites with a significant groundcover component (moss or lichen). The basic question addressed with this model was: What is the sensitivity of the boreal forest carbon balance to weather variability? More specifically: What are the differences in the sensitivities of carbon gains (photosynthesis) and carbon losses (respiration) of the various components of the ecosystem? Are there different seasonalities to their sensitivities (e.g., warmer springs will have one effect, warmer summers a different effect)? What are the effects of different patterns of successive weather years (wet/dry, warm/cool)? What, for example, would be the difference in effects of two "warmer than normal" months-one with each day warmer than normal, and the other with three normal weeks and one very hot week? Due to weather variability, how "noisy" will any carbon flux or carbon pool signal be that we might use to try to detect change? The project resulted in the development of a new boreal forest ecosystem model. This model was the first model in the BOREAS project to look closely at the role of mosses in the ecosystem carbon balance, and also was the first model in the BOREAS project to look closely at interannual variability in carbon fluxes. Along with the work of many other groups, TE-19 modeling analysis pointed to the need for a second, longer field season in 1996, with particular focus on the spring and fall transitions and on ground vegetation. BOREAS groups TE-19 (Frolking), TGB-1 (Crill) & TGB-3 (Moore & Roulet) analyzed BOREAS data and other published and unpublished data to develop a relationship between peatland ecosystem productivity and incoming radiation, which is quite distinct from the upland ecosystem relationships observed in other studies.

Frolking, Steve↗
NASA NTRS1983

Investigation of several aspects of LANDSAT-4 data quality

No insurmountable problems in change detection analysis were found when portions of scenes collected simultaneously by LANDSAT 4 MSS and either LANDSAT 2 or 3. The cause of the periodic noise in LANDSAT 4 MSS images which had a RMS value of approximately 2DN should be corrected in the LANDSAT D instrument before its launch. Analysis of the P-tape of the Arkansas scene shows bands within the same focal plane very well registered except for the thermal band which was misregistered by approximately three 28.5 meter pixels in both directions. It is possible to derive tight confidence bounds for the registration errors. Preliminary analyses of the Sacramento and Arkansas scenes reveals a very high degree of consistency with earlier results for bands 3 vs 1, 3 vs 4, and 3 vs 5. Results are presented in table form. It is suggested that attention be given to the standard deviations of registrations errors to judge whether or not they will be within specification once any known mean registration errors are corrected. Techniques used for MTF analysis of a Washington scene produced noisy results.

Wrigley, R. C.↗
NASA NTRS1974

Modern control concepts in hydrology

Two approaches to an identification problem in hydrology are presented based upon concepts from modern control and estimation theory. The first approach treats the identification of unknown parameters in a hydrologic system subject to noisy inputs as an adaptive linear stochastic control problem; the second approach alters the model equation to account for the random part in the inputs, and then uses a nonlinear estimation scheme to estimate the unknown parameters. Both approaches use state-space concepts. The identification schemes are sequential and adaptive and can handle either time invariant or time dependent parameters. They are used to identify parameters in the Prasad model of rainfall-runoff. The results obtained are encouraging and conform with results from two previous studies; the first using numerical integration of the model equation along with a trial-and-error procedure, and the second, by using a quasi-linearization technique. The proposed approaches offer a systematic way of analyzing the rainfall-runoff process when the input data are imbedded in noise.

Duong, N.↗
NASA NTRS1975

Modern control concepts in hydrology

Two approaches to an identification problem in hydrology are presented, based upon concepts from modern control and estimation theory. The first approach treats the identification of unknown parameters in a hydrologic system subject to noisy inputs as an adaptive linear stochastic control problem; the second approach alters the model equation to account for the random part in the inputs, and then uses a nonlinear estimation scheme to estimate the unknown parameters. Both approaches use state-space concepts. The identification schemes are sequential and adaptive and can handle either time-invariant or time-dependent parameters. They are used to identify parameters in the Prasad model of rainfall-runoff. The results obtained are encouraging and confirm the results from two previous studies; the first using numerical integration of the model equation along with a trial-and-error procedure, and the second using a quasi-linearization technique. The proposed approaches offer a systematic way of analyzing the rainfall-runoff process when the input data are imbedded in noise.

Duong, N.↗
NASA NTRS2004

Reducing Errors by Use of Redundancy in Gravity Measurements

A methodology for improving gravity-gradient measurement data exploits the constraints imposed upon the components of the gravity-gradient tensor by the conditions of integrability needed for reconstruction of the gravitational potential. These constraints are derived from the basic equation for the gravitational potential and from mathematical identities that apply to the gravitational potential and its partial derivatives with respect to spatial coordinates. Consider the gravitational potential in a Cartesian coordinate system {x1,x2,x3}. If one measures all the components of the gravity-gradient tensor at all points of interest within a region of space in which one seeks to characterize the gravitational field, one obtains redundant information. One could utilize the constraints to select a minimum (that is, nonredundant) set of measurements from which the gravitational potential could be reconstructed. Alternatively, one could exploit the redundancy to reduce errors from noisy measurements. A convenient example is that of the selection of a minimum set of measurements to characterize the gravitational field at n3 points (where n is an integer) in a cube. Without the benefit of such a selection, it would be necessary to make 9n3 measurements because the gravitygradient tensor has 9 components at each point. The problem of utilizing the redundancy to reduce errors in noisy measurements is an optimization problem: Given a set of noisy values of the components of the gravity-gradient tensor at the measurement points, one seeks a set of corrected values - a set that is optimum in that it minimizes some measure of error (e.g., the sum of squares of the differences between the corrected and noisy measurement values) while taking account of the fact that the constraints must apply to the exact values. The problem as thus posed leads to a vector equation that can be solved to obtain the corrected values.

Kulikov, Igor↗
NASA NTRS2005

Monitoring a Complex Physical System using a Hybrid Dynamic Bayes Net

The Reverse Water Gas Shift system (RWGS) is a complex physical system designed to produce oxygen from the carbon dioxide atmosphere on Mars. If sent to Mars, it would operate without human supervision, thus requiring a reliable automated system for monitoring and control. The RWGS presents many challenges typical of real-world systems, including: noisy and biased sensors, nonlinear behavior, effects that are manifested over different time granularities, and unobservability of many important quantities. In this paper we model the RWGS using a hybrid (discrete/continuous) Dynamic Bayesian Network (DBN), where the state at each time slice contains 33 discrete and 184 continuous variables. We show how the system state can be tracked using probabilistic inference over the model. We discuss how to deal with the various challenges presented by the RWGS, providing a suite of techniques that are likely to be useful in a wide range of applications. In particular, we describe a general framework for dealing with nonlinear behavior using numerical integration techniques, extending the successful Unscented Filter. We also show how to use a fixed-point computation to deal with effects that develop at different time scales, specifically rapid changes occuring during slowly changing processes. We test our model using real data collected from the RWGS, demonstrating the feasibility of hybrid DBNs for monitoring complex real-world physical systems.

Lerner, Uri↗
NASA NTRS2010

Speech Acquisition and Automatic Speech Recognition for Integrated Spacesuit Audio Systems

A voice-command human-machine interface system has been developed for spacesuit extravehicular activity (EVA) missions. A multichannel acoustic signal processing method has been created for distant speech acquisition in noisy and reverberant environments. This technology reduces noise by exploiting differences in the statistical nature of signal (i.e., speech) and noise that exists in the spatial and temporal domains. As a result, the automatic speech recognition (ASR) accuracy can be improved to the level at which crewmembers would find the speech interface useful. The developed speech human/machine interface will enable both crewmember usability and operational efficiency. It can enjoy a fast rate of data/text entry, small overall size, and can be lightweight. In addition, this design will free the hands and eyes of a suited crewmember. The system components and steps include beam forming/multi-channel noise reduction, single-channel noise reduction, speech feature extraction, feature transformation and normalization, feature compression, model adaption, ASR HMM (Hidden Markov Model) training, and ASR decoding. A state-of-the-art phoneme recognizer can obtain an accuracy rate of 65 percent when the training and testing data are free of noise. When it is used in spacesuits, the rate drops to about 33 percent. With the developed microphone array speech-processing technologies, the performance is improved and the phoneme recognition accuracy rate rises to 44 percent. The recognizer can be further improved by combining the microphone array and HMM model adaptation techniques and using speech samples collected from inside spacesuits. In addition, arithmetic complexity models for the major HMMbased ASR components were developed. They can help real-time ASR system designers select proper tasks when in the face of constraints in computational resources.

Huang, Yiteng↗
NASA NTRS1998

Minimum Climb to Cruise Noise Trajectories Modeled for the High Speed Civil Transport

The proposed U.S. High Speed Civil Transport (HSCT) will revolutionize commercial air travel by providing economical supersonic passenger service to destinations worldwide. Unlike the high-bypass turbofan engines that propel today's subsonic airliners, HSCT engines will have much higher jet exhaust speeds. Jet noise, caused by the turbulent mixing of high-speed exhaust with the surrounding air, poses a significant challenge for HSCT engine designers. To resolve this challenge, engineers have designed advanced mixer rejector nozzles that reduce HSCT jet noise to airport noise certification levels by entraining and mixing large quantities of ambient air with the engines' jet streams. Although this works well during the first several minutes of flight, far away from the airport, as the HSCT gains speed and climbs, poor ejector inlet recovery and ejector ram drag contribute to poor thrust, making it advantageous to turn off the ejector. Doing so prematurely, however, can cause unacceptable noise levels to propagate to the ground, even when the aircraft is many miles from the airport. This situation lends itself ideally to optimization, where the aircraft trajectory, throttle setting, and ejector setting can be varied (subject to practical aircraft constraints) to minimize the noise propagated to the ground. A method was developed at the NASA Lewis Research Center that employs a variation of the classic energy state approximation: a trajectory analysis technique historically used to minimize climb time or fuel burned in many aircraft problems. To minimize the noise on the ground at any given throttle setting, high aircraft altitudes are desirable; but the HSCT may either climb quickly to high altitudes using a high, noisy throttle setting or climb more slowly at a lower, quieter throttle setting. An optimizer has been programmed into NASA's existing aircraft and noise analysis codes to balance these options by dynamically choosing the best altitude-velocity path and throttle setting history. The noise level standard, or metric, used in the optimizer should be one that accurately reflects the subjective annoyance levels of ground-based observers under the flight path. A variety of noise metrics are available, many of which are practical for airport-vicinity noise certification. Unlike airport noise, however, the HSCT's climb noise will be characterized by relatively low noise levels, long durations, and low-frequency spectra. The noise metrics used in these calculations are based on the recommendations of researchers at the NASA Langley Research Center, who have correlated the flyover noise annoyance levels of actual laboratory subjects with a variety of measurements. Analysis of data from this optimizer has shown that significant reductions in noise may be obtained with trajectory optimization. And since throttling operations are performed in the subsonic portion of the climb path (where thrust is plentiful), only small penalties in HSCT range or fuel performance occur.

Berton, Jeffrey J.↗
NASA NTRS1997

Study and Simulation of Enhancements for TCP (Transmission Control Protocol) Performance Over Noisy, High-Latency Links

The designers of the TCP/IP protocol suite explicitly included support of satellites in their design goals. The goal of the Internet Project was to design a protocol which could be layered over different networking technologies to allow them to be concatenated into an internet. The results of this project included two protocols, IP and TCP. IP is the protocol used by all elements in the network and it defines the standard packet format for IP datagrams. TCP is the end-to-end transport protocol commonly used between end systems on the Internet to derive a reliable bi-directional byte-pipe service from the underlying unreliable IP datagram service. Satellite links are explicitly mentioned in Vint Cerf's 2-page article which appeared in 1980 in CCR [2] to introduce the specifications for IP and TCP. In the past fifteen years, TCP has been demonstrated to work over many differing networking technologies, including over paths including satellites links. So if satellite links were in the minds of the designers from the beginning, what is the problem? The problem is that the performance of TCP has in some cases been disappointing. A goal of the authors of the original specification of TCP was to specify only enough behavior to ensure interoperability. The specification left a number of important decisions, in particular how much data is to be sent when, to the implementor. This was deliberately' done. By leaving performance-related decisions to the implementor, this would allow the protocol TCP to be tuned and adapted to different networks and situations in the future without the need to revise the specification of the protocol, or break interoperability. Interoperability would continue while future implementations would be allowed flexibility to adapt to needs which could not be anticipated at the time of the original protocol design.

Shepard, Timothy J.↗
NASA NTRS2006

System Would Detect Foreign-Object Damage in Turbofan Engine

A proposed data-fusion system, to be implemented mostly in software, would further process the digitized and preprocessed outputs of sensors in a turbofan engine to detect foreign-object damage (FOD) [more precisely, damage caused by impingement of such foreign objects as birds, pieces of ice, and runway debris]. The proposed system could help a flight crew to decide what, if any, response is necessary to complete a flight safely, and could aid mechanics in deciding what post-flight maintenance action might be needed. The sensory information to be utilized by the proposed system would consist of (1) the output of an accelerometer in an engine-vibration-monitoring subsystem and (2) features extracted from a gas path analysis. ["Gas path analysis" (GPA) is a term of art that denotes comprehensive analysis of engine performance derived from readings of fuel-flow meters, shaft-speed sensors, temperature sensors, and the like.] The acceleration signal would first be processed by a wavelet-transform-based algorithm, using a wavelet created for the specific purpose of finding abrupt FOD-induced changes in noisy accelerometer signals. Two additional features extracted would be the amplitude of vibration (determined via a single- frequency Fourier transform calculated at the rotational speed of the engine), and the rate of change in amplitude due to an FOD-induced rotor imbalance. This system would utilize two GPA features: the fan efficiency and the rate of change of fan efficiency with time. The selected GPA and vibrational features would be assessed by two fuzzy-logic inference engines, denoted the "Gas Path Expert" and the "Vibration Expert," respectively (see Figure 1). Each of these inference engines would generate a "possibility" distribution for occurrence of an FOD event: Each inference engine would assign, to its input information, degrees of membership, which would subsequently be transformed into basic probability assignments for the gas path and vibration components. The outputs of the inference engines would be fused by use of Dempster s combination algorithm (more precisely, an algorithm, based on the Dempster-Shafer-Yager theory of evidence, for fusing uncertain or imprecise information) to provide a reduced body of information to a human or computer decision maker. Figure 2 depicts some outputs generated in response to simulated accelerometer and GPA signals

Torso, James A.↗
NASA NTRS1999

Fractal Characterization of Hyperspectral Imagery

Two Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) hyperspectral images selected from the Los Angeles area, one representing urban and the other, rural, were used to examine their spatial complexity across their entire spectrum of the remote sensing data. Using the ICAMS (Image Characterization And Modeling System) software, we computed the fractal dimension values via the isarithm and triangular prism methods for all 224 bands in the two AVIRIS scenes. The resultant fractal dimensions reflect changes in image complexity across the spectral range of the hyperspectral images. Both the isarithm and triangular prism methods detect unusually high D values on the spectral bands that fall within the atmospheric absorption and scattering zones where signature to noise ratios are low. Fractal dimensions for the urban area resulted in higher values than for the rural landscape, and the differences between the resulting D values are more distinct in the visible bands. The triangular prism method is sensitive to a few random speckles in the images, leading to a lower dimensionality. On the contrary, the isarithm method will ignore the speckles and focus on the major variation dominating the surface, thus resulting in a higher dimension. It is seen where the fractal curves plotted for the entire bandwidth range of the hyperspectral images could be used to distinguish landscape types as well as for screening noisy bands.

Qiu, Hon-Iie↗
NASA NTRS2009

Aqua MODIS Thermal Emissive Band On-Orbit Calibration, Characterization, and Performance

The NASA's Earth Observing System Aqua Moderate Resolution Imaging Spectroradiometer (MODIS) has continued to operate with satisfactory performance since its launch in May 2002, exceeding its nominal six-year design lifetime. Its continuous Earth observations have been used to generate many science data products for studies of the Earth's, system. MODIS has 36 spectral bands; 20 reflective solar bands and 16 thermal emissive bands (TEBs). All TEB observations are made at 1-km nadir spatial resolution with spectral wavelengths from 3.7 to 14.4 pm. Primary applications of MODIS TEB 'include surface, cloud, and atmospheric temperatures, water vapor, and cloud top altitude. MODIS TEB on-orbit calibration uses a quadratic algorithm with its calibration coefficients derived using an onboard blackbody (BB). This paper will present Aqua MODIS TEB on-orbit calibration, characterization, and performance over its six-year mission. Examples of instrument thermal behavior, BB temperature stability, detector short-term stability, and changes in long-term response (or system gain) will be presented. Comparisons will also be made with Terra MODIS, launched in December 1999. On-orbit results show that Aqua MODIS and its focal plane temperatures have behaved normally. BB temperature has remained extremely stable with typical scan -to-scan variations of less than +/-0.15 mK. Most TEB detectors continue to exceed their specified signal-to-noise ratio requirements, exhibiting excellent short-term stability and calibration accuracy. Excluding a few noisy detectors, either identified prelaunch or occurring postlaunch, on-orbit changes in TEB responses have been less than 0.5% on an annual basis. By comparison; the overall Aqua TEB performance has been better than that of Terra MODIS,

Xiong, Xiaoxiong↗
NASA NTRSDate not supplied

A Multilevel Approach For SolvingLarge-Scale QUBO Problems With Noisy Hybrid Quantum Approximate Optimization

Quantum approximate optimization is one ofthe promising candidates for useful quantum computation,particularly in the context of finding approximate solutionsto Quadratic Unconstrained Binary Optimization (QUBO)problems. However, the existing quantum processing units(QPUs) are of relatively small size, and canonical mappingsof QUBO via the Ising model require one qubit per vari-able, rendering direct large-scale optimization infeasible.In classical optimization, a general strategy for addressingmany large-scale problems is via multilevel/multigrid meth-ods, where the large target problem is iteratively coarsenedand the global solution is constructed from multiple small-scale optimization runs. In this work, we experimentallytest how existing QPUs perform when used as a sub-solverwithin such a multilevel strategy. To this aim, we com-bine and extend (via additional classical processing steps)the recently proposed Noise-Directed Adaptive Remapping(NDAR) and Quantum Relax&Round (QRR) algorithms.We first demonstrate the effectiveness of our heuristicextensions on Rigetti’s superconducting transmon deviceAnkaa-2. We find approximate solutions to10instances offully connected82-qubit Sherrington-Kirkpatrick graphswith random integer-valued coefficients obtaining normal-ized approximation ratios (ARs) in the range∼0.98−1.0,and the same class with real-valued coefficients (ARs∼0.94−1.0). Then, we implement the extended NDAR andQRR algorithms as subsolvers in the multilevel algorithmfor6large-scale graphs with at most∼27,000variables.In practice, the QPU (with classical post-processing steps)is used to find approximate solutions to dozens of at most82-qubit problems, which are iteratively used to constructthe global solution. We observe that quantum optimizationresults are competitive in terms of the quality of solutionswhen compared to classical heuristics used as subsolverswithin the multilevel approach.Reproducibility: source code and data are available at[TBA upon acceptance]

quantum computing↗
NASA NTRS1992

Efficient transfer of images over networks

Effective remote observing requires sending large images over long distances. The usual approach to the transfer problem is to require high bandwidth transmission links, which are expensive to install and operate. An alternative approach is to use existing low-bandwidth connections, such as phone lines or the Internet, in a highly efficient manner by compressing the images. The combined use of existing low-cost infrastructure and standard networking software means that remote observing can be made practical even for small observatories with limited network resources. The authors have implemented such a scheme based on the H-transform compression method developed for astronomical images, which are often resistant to compression because they are noisy. The H-transform can be used for either lossy or lossless compression, and compression factors of at least 10 can be achieved with no noticeable losses in the astrometric or photometric properties of the compressed images. The H-transform allows us to organize the information in an image so that the 'useful' information can be sent first, followed by the noise, which makes up the bulk of the transmission. The receiver can invert a partially received set of H-coefficients, creating an image that improves with time. The H-transform is particularly well-suited to this style of incremental reconstruction, because the spatially localized nature of the basis functions of the H-transorm prevents the appearance of artifacts such as ringing around point sources and edges. The authors' implementation uses the WIYN Telescope Control System's TCP-based communications protocol. An 800x800 16-bit astronomical image was sent over a 2400 baud connection, which would normally take about 71 minutes; after only 60 seconds, the partially received H-transform produced an image that did not differ appreciably from the original. This poster presents a quantification of the efficiencies, as well as examples of images reconstructed from partial data.

Percival, J. W.↗
NASA NTRS2001

Accuracy Assessment of Response Surface Approximations for Supersonic Turbine Design

There is a growing trend to employ CFD tools to supply the necessary information for design optimization of fluid dynamics components/systems. Such results are prone to uncertainties due to reasons including discretization. errors, incomplete convergence of computational procedures, and errors associated with physical models such as turbulence closures. Based on this type of information, gradient-based optimization algorithms often suffer from the noisy calculations, which can seriously compromise the outcome. Similar problems arise from the experimental measurements. Global optimization techniques, such as those based on the response surface (RS) concept are becoming popular in part because they can overcome some of these barriers. However, there are also fundamental issues related to such global optimization technique such as RS. For example, in high dimensional design spaces, typically only a small number of function evaluations are available due to computational and experimental costs. On the other hand, complex features of the design variables do not allow one to model the global characteristics of the design space with simple quadratic polynomials. Consequently a main challenge is to reduce the size of the region where we fit the RS, or make it more accurate in the regions where the optimum is likely to reside. Response Surface techniques using either polynomials or and Neural Network (NN) methods offer designers alternatives to conduct design optimization. The RS technique employs statistical and numerical techniques to establish the relationship between design variables and objective/constraint functions, typically using polynomials. In this study, we aim at addressing issues related to the following questions: (1) How to identify outliers associated with a given RS representation and improve the RS model via appropriate treatments? (2) How to focus on selected design data so that RS can give better performance in regions critical to design optimization? (3) How to combine NN and polynomial techniques for improving the accuracy of the RS model?

Papila, Nilay↗
NASA NTRSDate not supplied

Error Sources and Mitigation Strategies for Thermocouples Integrated in Flexible Thermal Protection System Materials

Brief Presenter Biography:Ruth Miller is an aer-ospace systems engineer in the Entry Systems and Ve-hicle Development Branch at NASA Ames Research Center.Introduction:The flexible thermal protection sys-tem (FTPS) on NASA’s Low-Earth Orbit Flight Test of an Inflatable Decelerator (LOFTID) vehicle will be in-strumented with thermocouples (TCs) to measure the in-depth thermal response during entry into Earth’s atmos-phere[1, 2]. Accurate flight temperature measurements are critical for verifying vehicle performance during the flight test and reducing uncertainties in the thermal models.However,the deployable nature of inflatable decelerator technology presents challengesfor integrat-ing TCs, specifically the TCsneed to be compactableand cannot damage the FTPSnor the inflatable structure(IS).Unlike traditional rigid aeroshells, routing TCsthrough the thickness of the FTPS could cause signifi-cant damage during packing of the deployable aeroshellbecause the different layers may shift small amounts in relation to each other imparting strain on the TCsand FTPS materials. The LOFTID TCleads are routed from the measurement location back to the data acquisition system in the vehicle centerbody within the same FTPS layer that they are monitoring the temperature. This ap-proach eliminates the need to put holes in the FTPS lay-ers,butas a consequence,the insulated TCleads travel for an appreciable distance through a region that will expose them to high temperaturesand large thermal gra-dients.LOFTID’s TCswere baselined to be commercially available Type K TCswith a binder impregnated glass braid insulation. These TCswere chosen because they had been used successfully on IRVE-3 and in ground-based arc jet testing. Additionally, these TCsdid notdamage the FTPS nor IS during packing and deploy-ment testing. However, the glass braid insulation is only rated to a maximum continuous use temperature of 482ºC. For reference, the duration of the heat pulse on the LOFTID vehicle is on the order of minutes and themaximum predicted temperaturebeneaththe outermost FTPS layersis 1350ºC.Ground-based testing in a tube furnace at NASA Ames Research Centerwas conducted to determine if the baseline TCsrouted through FTPS samples would survive and provide accurate temperature measure-mentsat LOFTID flight-relevant temperatures[3].The test results showed large measurement errors occurred beginning at approximately 400°C due to conductive deposits on the TCinsulation electrically shorting the TCleads.The conductive deposits and thus electrical shorting weredetermined to be caused by twoerror sources:1.The organic binder on the TCinsulation carbon-izingin a high temperature, low oxygen envi-ronment2.Decomposition products from the FTPSperme-atingthe braided TC insulationFurther testing in the tube furnace demonstrated that heat cleaning the TCinsulation effectivelyremovedthe organic binder andeliminatedthe first error source.The second error sourcewas shown to be mitigated by the addition of amica wraparound each individual TCleadtoact as an impermeable barrier.To understand the applicability of theground-based tube furnace test results to flight,anarc jet testseriesat Boeing’s Large Core Arc Tunnel (LCAT) facilitywas conducted[4].The error sourcesand mitigation strate-giesidentified in the tube furnace testing were substan-tiatedin the arc jet testing.However, the arc jet testing also revealed three new error sources:1.Glass TCinsulation meltingwhich resultsin electrical shorting of the TCeither through di-rect contact between the two leads or through the electrically conductive FTPS materials2.TCwire meltingwhich results in a noisy and/or open-loop TCresponse3.Type K TCwire green-rotwhich results in large calibration errors Scope of the Presentation:This presentation will include a brief discussion onthe effect of electrical shorting on the output of a TC(i.e. how to identify elec-trical shorting in TCdataand what the associated erroris).The tube furnace and arc jet test resultswill be dis-cussedand the solutions LOFTID is implementing to mitigate the error sourcesidentified in the tube furnace and arc jet testingwill be presented.Additionally, futureresearch and development work to eliminateTCerror sourcesfor future missionswill be recommended.

R A Miller↗