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NASA NTRS2012

Model-Based Method for Sensor Validation

Fault detection, diagnosis, and prognosis are essential tasks in the operation of autonomous spacecraft, instruments, and in situ platforms. One of NASA s key mission requirements is robust state estimation. Sensing, using a wide range of sensors and sensor fusion approaches, plays a central role in robust state estimation, and there is a need to diagnose sensor failure as well as component failure. Sensor validation can be considered to be part of the larger effort of improving reliability and safety. The standard methods for solving the sensor validation problem are based on probabilistic analysis of the system, from which the method based on Bayesian networks is most popular. Therefore, these methods can only predict the most probable faulty sensors, which are subject to the initial probabilities defined for the failures. The method developed in this work is based on a model-based approach and provides the faulty sensors (if any), which can be logically inferred from the model of the system and the sensor readings (observations). The method is also more suitable for the systems when it is hard, or even impossible, to find the probability functions of the system. The method starts by a new mathematical description of the problem and develops a very efficient and systematic algorithm for its solution. The method builds on the concepts of analytical redundant relations (ARRs).

Vatan, Farrokh↗
NASA NTRS2011

An Icy Kuiper-Belt Around the Young Solar-Type Star HD 181327

HD 181327 is a young Main Sequence F5/F6 V star belonging to the Beta Pictoris moving group (age approx 12 Myr). It harbors an optically thin belt of circumstellar material at approx90 AU, presumed to result from collisions in a populat.ion of unseen planetesimals. Aims. We aim to study the dust properties in the belt in great details, and to constrain the gas-to-dust ratio. Methods. We obtained far-IR photometric observations of HD 181327 with the PACS instrument onboard the Herschel Space Observatory, complemented by new 3.2 nun observations carried with the ATCA array. The geometry of the belt is constrained with newly reduced HST /NICMOS scattered light images that break the degeneracy between the disk geometry and the dust properties. We then use the radiative transfer code GRaTer to compute a large grid of dust models, and we apply a Bayesian inference method to identify the grain models that best reproduce the SED. We attempt to detect the oxygen and ionized carbon fine-structure lines with Herschel/PACS spectroscopy, providing observables to our photochemical code ProDiMo. Results. The HST observations confirm that the dust is confined in a narrow belt. The continuum is detected with Herschel/PACS completing nicely the SED in the far-infrared. The disk is marginally resolved with both PACS and ATCA. A medium integration of the gas spectral lines only provides upper limits on the [OI] and [CII] line fluxes. We show that the HD 181327 dust disk consists of micron-sized grains of porous amorphous silicates and carbonaceous material surrounded by an import.ant layer of ice for a total dust mass of approx 0.05 stellar Mass. We discuss evidences that the grains consists of fluffy aggregates. The upper limits on the gas atomic lines do not provide unambiguous constraints: only if the PAH abundance is high, the gas mass must be lower than approx 17 Stellar Mass Conclusions. Despite the weak constraints on the gas disk, the age of HD 181327 and the properties of the dust disk suggest that it has passed the stage of gaseous planets formation. The dust reveals a population of icy planetesimals, similar to the primitive Edgeworth-Kuiper Belt, that may be a source for the future delivery of water and volatiles onto forming terrestrial planets.

Lebreton, J.↗
NASA NTRS2012

Accelerated Aging in Electrolytic Capacitors for Prognostics

The focus of this work is the analysis of different degradation phenomena based on thermal overstress and electrical overstress accelerated aging systems and the use of accelerated aging techniques for prognostics algorithm development. Results on thermal overstress and electrical overstress experiments are presented. In addition, preliminary results toward the development of physics-based degradation models are presented focusing on the electrolyte evaporation failure mechanism. An empirical degradation model based on percentage capacitance loss under electrical overstress is presented and used in: (i) a Bayesian-based implementation of model-based prognostics using a discrete Kalman filter for health state estimation, and (ii) a dynamic system representation of the degradation model for forecasting and remaining useful life (RUL) estimation. A leave-one-out validation methodology is used to assess the validity of the methodology under the small sample size constrain. The results observed on the RUL estimation are consistent through the validation tests comparing relative accuracy and prediction error. It has been observed that the inaccuracy of the model to represent the change in degradation behavior observed at the end of the test data is consistent throughout the validation tests, indicating the need of a more detailed degradation model or the use of an algorithm that could estimate model parameters on-line. Based on the observed degradation process under different stress intensity with rest periods, the need for more sophisticated degradation models is further supported. The current degradation model does not represent the capacitance recovery over rest periods following an accelerated aging stress period.

Celaya, Jose R.↗
NASA NTRS2012

The Ground Flash Fraction Retrieval Algorithm Employing Differential Evolution: Simulations and Applications

The ability to estimate the fraction of ground flashes in a set of flashes observed by a satellite lightning imager, such as the future GOES-R Geostationary Lightning Mapper (GLM), would likely improve operational and scientific applications (e.g., severe weather warnings, lightning nitrogen oxides studies, and global electric circuit analyses). A Bayesian inversion method, called the Ground Flash Fraction Retrieval Algorithm (GoFFRA), was recently developed for estimating the ground flash fraction. The method uses a constrained mixed exponential distribution model to describe a particular lightning optical measurement called the Maximum Group Area (MGA). To obtain the optimum model parameters (one of which is the desired ground flash fraction), a scalar function must be minimized. This minimization is difficult because of two problems: (1) Label Switching (LS), and (2) Parameter Identity Theft (PIT). The LS problem is well known in the literature on mixed exponential distributions, and the PIT problem was discovered in this study. Each problem occurs when one allows the numerical minimizer to freely roam through the parameter search space; this allows certain solution parameters to interchange roles which leads to fundamental ambiguities, and solution error. A major accomplishment of this study is that we have employed a state-of-the-art genetic-based global optimization algorithm called Differential Evolution (DE) that constrains the parameter search in such a way as to remove both the LS and PIT problems. To test the performance of the GoFFRA when DE is employed, we applied it to analyze simulated MGA datasets that we generated from known mixed exponential distributions. Moreover, we evaluated the GoFFRA/DE method by applying it to analyze actual MGAs derived from low-Earth orbiting lightning imaging sensor data; the actual MGA data were classified as either ground or cloud flash MGAs using National Lightning Detection Network[TM] (NLDN) data. Solution error plots are provided for both the simulations and actual data analyses.

Koshak, William↗
NASA NTRS2012

A Regional CO2 Observing System Simulation Experiment Using ASCENDS Observations and WRF-STILT Footprints

Knowledge of the spatiotemporal variations in emissions and uptake of CO2 is hampered by sparse measurements. The recent advent of satellite measurements of CO2 concentrations is increasing the density of measurements, and the future mission ASCENDS (Active Sensing of CO2 Emissions over Nights, Days and Seasons) will provide even greater coverage and precision. Lagrangian atmospheric transport models run backward in time can quantify surface influences ("footprints") of diverse measurement platforms and are particularly well suited for inverse estimation of regional surface CO2 fluxes at high resolution based on satellite observations. We utilize the STILT Lagrangian particle dispersion model, driven by WRF meteorological fields at 40-km resolution, in a Bayesian synthesis inversion approach to quantify the ability of ASCENDS column CO2 observations to constrain fluxes at high resolution. This study focuses on land-based biospheric fluxes, whose uncertainties are especially large, in a domain encompassing North America. We present results based on realistic input fields for 2007. Pseudo-observation random errors are estimated from backscatter and optical depth measured by the CALIPSO satellite. We estimate a priori flux uncertainties based on output from the CASA-GFED (v.3) biosphere model and make simple assumptions about spatial and temporal error correlations. WRF-STILT footprints are convolved with candidate vertical weighting functions for ASCENDS. We find that at a horizontal flux resolution of 1 degree x 1 degree, ASCENDS observations are potentially able to reduce average weekly flux uncertainties by 0-8% in July, and 0-0.5% in January (assuming an error of 0.5 ppm at the Railroad Valley reference site). Aggregated to coarser resolutions, e.g. 5 degrees x 5 degrees, the uncertainty reductions are larger and more similar to those estimated in previous satellite data observing system simulation experiments.

Wang, James S.↗
NASA NTRS2012

The Analysis of the Contribution of Human Factors to the In-Flight Loss of Control Accidents

In-flight loss of control (LOC) is currently the leading cause of fatal accidents based on various commercial aircraft accident statistics. As the Next Generation Air Transportation System (NextGen) emerges, new contributing factors leading to LOC are anticipated. The NASA Aviation Safety Program (AvSP), along with other aviation agencies and communities are actively developing safety products to mitigate the LOC risk. This paper discusses the approach used to construct a generic integrated LOC accident framework (LOCAF) model based on a detailed review of LOC accidents over the past two decades. The LOCAF model is comprised of causal factors from the domain of human factors, aircraft system component failures, and atmospheric environment. The multiple interdependent causal factors are expressed in an Object-Oriented Bayesian belief network. In addition to predicting the likelihood of LOC accident occurrence, the system-level integrated LOCAF model is able to evaluate the impact of new safety technology products developed in AvSP. This provides valuable information to decision makers in strategizing NASA's aviation safety technology portfolio. The focus of this paper is on the analysis of human causal factors in the model, including the contributions from flight crew and maintenance workers. The Human Factors Analysis and Classification System (HFACS) taxonomy was used to develop human related causal factors. The preliminary results from the baseline LOCAF model are also presented.

Ancel, Ersin↗
NASA NTRS2012

Analysis of Fine-Mode Aerosol Retrieval Capabilities by Different Passive Remote Sensing Instrument Designs

Remote sensing of aerosol optical properties is difficult, but multi-angle, multi-spectral, polarimetric instruments have the potential to retrieve sufficient information about aerosols that they can be used to improve global climate models. However, the complexity of these instruments means that it is difficult to intuitively understand the relationship between instrument design and retrieval success. We apply a Bayesian statistical technique that relates instrument characteristics to the information contained in an observation. Using realistic simulations of fine size mode dominated spherical aerosols, we investigate three instrument designs. Two of these represent instruments currently in orbit: the Multiangle Imaging SpectroRadiometer (MISR) and the POLarization and Directionality of the Earths Reflectances (POLDER). The third is the Aerosol Polarimetry Sensor (APS), which failed to reach orbit during recent launch, but represents a viable design for future instruments. The results show fundamental differences between the three, and offer suggestions for future instrument design and the optimal retrieval strategy for current instruments. Generally, our results agree with previous validation efforts of POLDER and airborne prototypes of APS, but show that the MISR aerosol optical thickness uncertainty characterization is possibly underestimated.

Knobelspiesse, Kirk↗
NASA NTRS2011

Reducing the Risk and Improving Mission Success for NASA's Human Mission to a Near-Earth Asteroid: How Many Robotic Surveyors?

NASA's recent attention and interest in sending a human mission to land on a Near-Earth asteroid raises the question of need for a robotic surveyor. This paper describes a Bayesian approach for comparing the productivity and cost-risk tradeoffs of sending (versus not sending) one or more robotic surveyor missions prior to a human mission to land on an asteroid. The probability of finding an asteroid suitable for landing was derived from an analysis of more than 1200 asteroids in order to define a quantitative estimate of suitability. The low cost of the surveyors relative to the human mission underlined the multi-surveyor strategy as relatively inexpensive insurance against the risks of encountering an unsuitable asteroid for landing on arrival by a human mission.

decision analysis↗
NASA NTRS2012

Towards Validation of an Adaptive Flight Control Simulation Using Statistical Emulation

Traditional validation of flight control systems is based primarily upon empirical testing. Empirical testing is sufficient for simple systems in which a.) the behavior is approximately linear and b.) humans are in-the-loop and responsible for off-nominal flight regimes. A different possible concept of operation is to use adaptive flight control systems with online learning neural networks (OLNNs) in combination with a human pilot for off-nominal flight behavior (such as when a plane has been damaged). Validating these systems is difficult because the controller is changing during the flight in a nonlinear way, and because the pilot and the control system have the potential to co-adapt in adverse ways traditional empirical methods are unlikely to provide any guarantees in this case. Additionally, the time it takes to find unsafe regions within the flight envelope using empirical testing means that the time between adaptive controller design iterations is large. This paper describes a new concept for validating adaptive control systems using methods based on Bayesian statistics. This validation framework allows the analyst to build nonlinear models with modal behavior, and to have an uncertainty estimate for the difference between the behaviors of the model and system under test.

He, Yuning↗
NASA NTRS2011

Search for Gravitational Waves Associated with the August 2006 Timing Glitch of the Vela Pulsar

The physical mechanisms responsible for pulsar timing glitches are thought to excite quasinormal mode oscillations in their parent neutron star that couple to gravitational-wave emission, In August 2006, a timing glitch was observed in the radio emission of PSR B0833-45, the Vela pulsar. At the time of the glitch, the two colocated Hanford gravitational-wave detectors of the Laser Interferometer Gravitational-wave observatory (LIGO) were operational and taking data as part of the fifth LIGO science run (S5). We present the first direct search for the gravitational-wave emission associated with oscillations of the fundamental quadrupole mode excited by a pulsar timing glitch. No gravitational-wave detection candidate was found. We place Bayesian 90% confidence upper limits of 6,3 x 10(exp -21) to 1.4 x 10(exp -20) on the peak: intrinsic strain amplitude of gravitational-wave ring-down signals, depending on which spherical harmonic mode is excited. The corresponding range of energy upper limits is 5.0 x 10(exp 44) to 1.3 x 10(exp 45) erg.

Camp, J. B.↗
NASA NTRS2012

Safety Risk Knowledge Elicitation in Support of Aeronautical R and D Portfolio Management: A Case Study

Aviation is a problem domain characterized by a high level of system complexity and uncertainty. Safety risk analysis in such a domain is especially challenging given the multitude of operations and diverse stakeholders. The Federal Aviation Administration (FAA) projects that by 2025 air traffic will increase by more than 50 percent with 1.1 billion passengers a year and more than 85,000 flights every 24 hours contributing to further delays and congestion in the sky (Circelli, 2011). This increased system complexity necessitates the application of structured safety risk analysis methods to understand and eliminate where possible, reduce, and/or mitigate risk factors. The use of expert judgments for probabilistic safety analysis in such a complex domain is necessary especially when evaluating the projected impact of future technologies, capabilities, and procedures for which current operational data may be scarce. Management of an R&D product portfolio in such a dynamic domain needs a systematic process to elicit these expert judgments, process modeling results, perform sensitivity analyses, and efficiently communicate the modeling results to decision makers. In this paper a case study focusing on the application of an R&D portfolio of aeronautical products intended to mitigate aircraft Loss of Control (LOC) accidents is presented. In particular, the knowledge elicitation process with three subject matter experts who contributed to the safety risk model is emphasized. The application and refinement of a verbal-numerical scale for conditional probability elicitation in a Bayesian Belief Network (BBN) is discussed. The preliminary findings from this initial step of a three-part elicitation are important to project management practitioners as they illustrate the vital contribution of systematic knowledge elicitation in complex domains.

Shih, Ann T.↗
NASA NTRS2012

The Rise and Fall of Star Formation Histories of Blue Galaxies at Redshifts 0.2 < z < 1.4

Popular cosmological scenarios predict that galaxies form hierarchically from the merger of many progenitor, each with their own unique star formation history (SFH). We use the approach recently developed by Pacifici et al. to constrain the SFHs of 4517 blue (presumably star-forming) galaxies with spectroscopic redshifts in the range O.2 < z < 1:4 from the All-Wavelength Extended Groth Strip International Survey (AEGIS). This consists in the Bayesian analysis of the observed galaxy spectral ' energy distributions with a comprehensive library of synthetic spectra assembled using state-of-the-art models of star formation and chemical enrichment histories, stellar population synthesis, nebular emission and attenuation by dust. We constrain the SFH of each galaxy in our sample by comparing the observed fluxes in the B, R,l and K(sub s) bands and rest-frame optical emission-line luminosities with those of one million model spectral energy distributions. We explore the dependence of the resulting SFH on galaxy stellar mass and redshift. We find that the average SFHs of high-mass galaxies rise and fall in a roughly symmetric bell-shaped manner, while those of low-mass galaxies rise progressively in time, consistent with the typically stronger activity of star formation in low-mass compared to high-mass galaxies. For galaxies of all masses, the star formation activity rises more rapidly at high than at low redshift. These findings imply that the standard approximation of exponentially declining SFHs wIdely used to interpret observed galaxy spectral energy distributions is not appropriate to constrain the physical parameters of star-forming galaxies at intermediate redshifts.

Pacifici, Camilla↗
NASA NTRS2011

Heterogeneity in Short Gamma-Ray Bursts

We analyze the Swift/BAT sample of short gamma-ray bursts, using an objective Bayesian Block procedure to extract temporal descriptors of the bursts' initial pulse complexes (IPCs). The sample comprises 12 and 41 bursts with and without extended emission (EE) components, respectively. IPCs of non-EE bursts are dominated by single pulse structures, while EE bursts tend to have two or more pulse structures. The medians of characteristic timescales - durations, pulse structure widths, and peak intervals - for EE bursts are factors of approx 2-3 longer than for non-EE bursts. A trend previously reported by Hakkila and colleagues unifying long and short bursts - the anti-correlation of pulse intensity and width - continues in the two short burst groups, with non-EE bursts extending to more intense, narrower pulses. In addition we find that preceding and succeeding pulse intensities are anti-correlated with pulse interval. We also examine the short burst X-ray afterglows as observed by the Swift/XRT. The median flux of the initial XRT detections for EE bursts (approx 6 X 10(exp -10) erg / sq cm/ s) is approx > 20 x brighter than for non-EE bursts, and the median X-ray afterglow duration for EE bursts (approx 60,000 s) is approx 30 x longer than for non-EE bursts. The tendency for EE bursts toward longer prompt-emission timescales and higher initial X-ray afterglow fluxes implies larger energy injections powering the afterglows. The longer-lasting X-ray afterglows of EE bursts may suggest that a significant fraction explode into more dense environments than non-EE bursts, or that the sometimes-dominant EE component efficiently p()wers the afterglow. Combined, these results favor different progenitors for EE and non-EE short bursts.

Norris, Jay P.↗
NASA NTRS2012

Thermal Behavior of Unusual Local-Scale Features on Vesta

On Vesta, the thermal behavior of areas of unusual albedo seen at the local scale can be related to physical properties that can provide information about the origin of those materials. Dawn's Visible and Infrared Mapping Spectrometer (VIR) hyperspectral cubes are used to retrieve surface temperatures and emissivities, with high accuracy as long as temperatures are greater than ~180 K. Data acquired in the Survey phase (23 July through 29 August 2011) show several unusual surface features: 1) high-albedo (bright) and low-albedo (dark) material deposits, 2) spectrally distinct ejecta and pitted materials, 3) regions suggesting finer-grained materials. Some of the unusual dark and bright features were re-observed by VIR in the subsequent High-Altitude Mapping Orbit (HAMO) and Low-Altitude Mapping Orbit (LAMO) phases at increased pixel resolution. In particular, bright and dark surface materials on Vesta, and pitted materials, are currently being investigated by the Dawn team. In this work we present temperature maps and emissivities of several local-scale features that were observed by Dawn under different illumination conditions and different local solar times. To calculate surface temperatures, we applied a Bayesian approach to nonlinear inversion based on the Kirchhoff law and the Planck function, and whose results were compared with those provided by the application of alternative methods. Data from the IR channel of VIR show that bright regions generally correspond to regions with lower thermal emission, i.e. lower temperature, while dark regions correspond to areas with higher thermal emission, i.e. higher temperature. This behavior confirms that many of the dark appearances in the VIS mainly reflect albedo variations, and not, for example, shadowing. During maximum daily insolation, dark features in the equatorial region may rise to temperatures greater than 270 K, while brightest features stop at roughly 258 K for similar local solar times. However, pitted materials, showing relatively low reflectance, have significantly lower temperatures, as a result of differences in composition and/or structure (e.g, average grain size of the surface regolith, porosity, etc.). To complement this work, we provide preliminary values of thermal inertia for some bright and dark features.

Tosi, Federico↗
NASA NTRS2012

Metallicities of Emission-Line Galaxies from HST ACS PEARS and HST WFC3 ERS Grism Spectroscopy at 0.6 is less than z is less than 2.4

Galaxies selected on the basis of their emission line strength. show low metallicities, regardless of their redshifts. We conclude this from a sample of faint galaxies at redshifts between 0.6 < z < 2.4, selected by their prominent emission lines in low resolution grism spectra in the optiCa.i with the Advanced Camera for Surveys (ACS) on the Hubble Space Telescope (HST) and in the near-infrared using Wide-Field Camera 3 (WFC3). Using a sample of 11 emission line galaxies (ELGs) at 0.6 < z < 2.4 with luminosities of -22 approx < MB approx -19 which have [OII], H-Beta, and [OIII] line flux measurements from the combination of two grism spectral surveys, we use the R23 method to derive the gas-phase oxygen abundances: 7.5 <12+log(0/H)<8.5. The galaxy stellar masses are derived using Bayesian based Markov Chain Monte Carlo (pi MC(exp 2)) fitting of their Spectral Energy Distribution (SED), and span the mass range 8.1 < log(M(stellar)/M(solar)) < 10.1. These galaxies show a mass-metal1icity (M-L) and Luminosity-Metallicity (LZ) relation, which is offset by -<J.6 dex in meta1licity at given absolute magnitude and stellar mass relative to the local SDSS galaxies, as well as continuum selected DEEP2 samples at similar redshifts. The emission-line selected galaxies most resemble the local "green peas" galaxies and Lyman-alpha galaxies at z approx = 0.3 and z approx = 2.3 in the M-Z and L-Z relations and their morphologies. The G - M(sub 20) morphology analysis shows that 10 out of 11 show disturbed morphology, even as the star-forming regions are compact. These galaxies may be intrinsically metal poor, being at early stages of formation, or the low metallicities may be due to gas infall and accretion due to mergers.

Xia, Lifang↗
NASA NTRS2012

Assimilating Remote Sensing Observations of Leaf Area Index and Soil Moisture for Wheat Yield Estimates: An Observing System Simulation Experiment

Observing system simulation experiments were used to investigate ensemble Bayesian state updating data assimilation of observations of leaf area index (LAI) and soil moisture (theta) for the purpose of improving single-season wheat yield estimates with the Decision Support System for Agrotechnology Transfer (DSSAT) CropSim-Ceres model. Assimilation was conducted in an energy-limited environment and a water-limited environment. Modeling uncertainty was prescribed to weather inputs, soil parameters and initial conditions, and cultivar parameters and through perturbations to model state transition equations. The ensemble Kalman filter and the sequential importance resampling filter were tested for the ability to attenuate effects of these types of uncertainty on yield estimates. LAI and theta observations were synthesized according to characteristics of existing remote sensing data, and effects of observation error were tested. Results indicate that the potential for assimilation to improve end-of-season yield estimates is low. Limitations are due to a lack of root zone soil moisture information, error in LAI observations, and a lack of correlation between leaf and grain growth.

Nearing, Grey S.↗
NASA NTRS2013

The Challenges of Credible Thermal Protection System Reliability Quantification

The paper discusses several of the challenges associated with developing a credible reliability estimate for a human-rated crew capsule thermal protection system. The process of developing such a credible estimate is subject to the quantification, modeling and propagation of numerous uncertainties within a probabilistic analysis. The development of specific investment recommendations, to improve the reliability prediction, among various potential testing and programmatic options is then accomplished through Bayesian analysis.

Green, Lawrence L.↗
NASA NTRS2013

NASA Orbital Debris Large-Object Baseline Population in ORDEM 3.0

The NASA Orbital Debris Program Office (ODPO) has created and validated high fidelity populations of the debris environment for the latest Orbital Debris Engineering Model (ORDEM 3.0). Though the model includes fluxes of objects 10 um and larger, this paper considers particle fluxes for 1 cm and larger debris objects from low Earth orbit (LEO) through Geosynchronous Transfer Orbit (GTO). These are validated by several reliable radar observations through the Space Surveillance Network (SSN), Haystack, and HAX radars. ORDEM 3.0 populations were designed for the purpose of assisting, debris researchers and sensor developers in planning and testing. This environment includes a background derived from the LEO-to-GEO ENvironment Debris evolutionary model (LEGEND) with a Bayesian rescaling as well as specific events such as the FY-1C anti-satellite test, the Iridium 33/Cosmos 2251 accidental collision, and the Soviet/Russian Radar Ocean Reconnaissance Satellite (RORSAT) sodium-potassium droplet releases. The environment described in this paper is the most realistic orbital debris population larger than 1 cm, to date. We describe derivations of the background population and added specific populations. We present sample validation charts of our 1 cm and larger LEO population against Space Surveillance Network (SSN), Haystack, and HAX radar measurements.

Krisco, Paula H.↗