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At least 127 records · Page 7

Model-Based Prognostics

This tutorial will cover the basics of model-based prognostics, and include concepts such as modeling approaches, estimation and prediction algorithms, and how uncertainty is represented and quantified. Other topics covered will include structural model decomposition, system-level prognostics, prognostics of hybrid systems, and distributed prognostics. Several case studies, such as water recovery systems to the prediction of safety margins in the national airspace system will be used to explain different concepts of prognostics and demonstrate their application to real-world systems.

Roychoudhury, Indranil↗

Computational methods for structural load and resistance modeling

An automated capability for computing structural reliability considering uncertainties in both load and resistance variables is presented. The computations are carried out using an automated Advanced Mean Value iteration algorithm (AMV +) with performance functions involving load and resistance variables obtained by both explicit and implicit methods. A complete description of the procedures used is given as well as several illustrative examples, verified by Monte Carlo Analysis. In particular, the computational methods described in the paper are shown to be quite accurate and efficient for a material nonlinear structure considering material damage as a function of several primitive random variables. The results show clearly the effectiveness of the algorithms for computing the reliability of large-scale structural systems with a maximum number of resolutions.

Thacker, B. H.↗

The Role of Global Hydrologic Processes in Interannual and Long-Term Climate Variability

The earth's climate and its variability is linked inextricably with the presence of water on our planet. El Nino / Southern Oscillation-- the major mode of interannual variability-- is characterized by strong perturbations in oceanic evaporation, tropical rainfall, and radiation. On longer time scales, the major feedback mechanism in CO2-induced global warming is actually that due to increased water vapor holding capacity of the atmosphere. The global hydrologic cycle effects on climate are manifested through influence of cloud and water vapor on energy fluxes at the top of atmosphere and at the surface. Surface moisture anomalies retain the "memory" of past precipitation anomalies and subsequently alter the partitioning of latent and sensible heat fluxes at the surface. At the top of atmosphere, water vapor and cloud perturbations alter the net amount of radiation that the earth's climate system receives. These pervasive linkages between water, radiation, and surface processes present major complexities for observing and modeling climate variations. Major uncertainties in the observations include vertical structure of clouds and water vapor, surface energy balance, and transport of water and heat by wind fields. Modeling climate variability and change on a physical basis requires accurate by simplified submodels of radiation, cloud formation, radiative exchange, surface biophysics, and oceanic energy flux. In the past, we m safely say that being "data poor' has limited our depth of understanding and impeded model validation and improvement. Beginning with pre-EOS data sets, many of these barriers are being removed. EOS platforms with the suite of measurements dedicated to specific science questions are part of our most cost effective path to improved understanding and predictive capability. This talk will highlight some of the major questions confronting global hydrology and the prospects for significant progress afforded by EOS-era measurements.

Robertson, Franklin R.↗

Neutron star models

The current state of neutron star structure calculations is reviewed. Uncertainties in the equation of state for matter at and above nuclear density remain. The role of the delta resonance, pion condensates, and quark matter is reviewed. It is found that recent models yield stable neutron star masses which are consistent with observational estimates.

Canuto, V.↗

Performance and Reliability Optimization for Aerospace Systems subject to Uncertainty and Degradation

This report summarizes work performed by the Space Systems Laboratory (SSL) for NASA Langley Research Center in the field of performance optimization for systems subject to uncertainty. The objective of the research is to develop design methods and tools to the aerospace vehicle design process which take into account lifecycle uncertainties. It recognizes that uncertainty between the predictions of integrated models and data collected from the system in its operational environment is unavoidable. Given the presence of uncertainty, the goal of this work is to develop means of identifying critical sources of uncertainty, and to combine these with the analytical tools used with integrated modeling. In this manner, system uncertainty analysis becomes part of the design process, and can motivate redesign. The specific program objectives were: 1. To incorporate uncertainty modeling, propagation and analysis into the integrated (controls, structures, payloads, disturbances, etc.) design process to derive the error bars associated with performance predictions. 2. To apply modern optimization tools to guide in the expenditure of funds in a way that most cost-effectively improves the lifecycle productivity of the system by enhancing the subsystem reliability and redundancy. The results from the second program objective are described. This report describes the work and results for the first objective: uncertainty modeling, propagation, and synthesis with integrated modeling.

Miller, David W.↗

Modeling Meteor Flares for Spacecraft Safety

NASA's Meteoroid Environment Office (MEO) is tasked with assisting spacecraft operators and engineers in quantifying the threat the meteoroid environment poses to their individual missions. A more complete understanding of the meteoroid environment for this application requires extensive observations. One manner by which the MEO observes meteors is with dedicated video camera systems that operate nightly. Connecting the observational data from these video cameras to the relevant physical properties of the ablating meteoroids, however, is subject to sizable observational and theoretical uncertainties. Arguably the most troublesome theoretical uncertainty in ablation is a model for the structure of meteoroids, as observations clearly show behaviors wholly inconsistent with meteoroids being homogeneous spheres. Further complicating the interpretation of the observations in the context of spacecraft risk is the ubiquitous process of fragmentation and the flares it can produce, which greatly muddles any attempts to estimating initial meteoroid masses. In this talk a method of estimating the mass distribution of fragments in flaring meteors using high resolution video observations will be dis- cussed. Such measurements provide an important step in better understanding of the structure and fragmentation process of the parent meteoroids producing these flares, which in turn may lead to better constraints on meteoroid masses and reduced uncertainties in spacecraft risk.

Ehlert, Steven↗

Our Sun IV: The Standard Model and Helioseismology: Consequences of Uncertainties in Input Physics and in Observed Solar Parameters

Helioseismic frequency observations provide an extremely accurate window into the solar interior; frequencies from the Michaelson Doppler Imager (MDI) on the Solar and Heliospheric Observatory (SOHO) spacecraft, enable the adiabatic sound speed and adiabatic index to be inferred with an accuracy of a few parts in 10(exp 4) and the density with an accuracy of a few parts in 10(exp 3). This has become a Serious challenge to theoretical models of the Sun. Therefore, we have undertaken a self-consistent, systematic study of the sources of uncertainties in the standard solar models. We found that the largest effect on the interior structure arises from the observational uncertainties in the photospheric abundances of the elements, which affect the sound speed profile at the level of 3 parts in 10(exp 3). The estimated 4% uncertainty in the OPAL opacities could lead to effects of 1 part in 10(exp 3); the approximately 5%, uncertainty in the basic pp nuclear reaction rate would have a similar effect, as would uncertainties of approximately 15% in the diffusion constants for the gravitational settling of helium. The approximately 50% uncertainties in diffusion constants for the heavier elements would have nearly as large an effect. Different observational methods for determining the solar radius yield results differing by as much as 7 parts in 10(exp 4); we found that this leads to uncertainties of a few parts in 10(exp 3) in the sound speed int the solar convective envelope, but has negligible effect on the interior. Our reference standard solar model yielded a convective envelope position of 0.7135 solar radius, in excellent agreement with the observed value of 0.713 +/- 0.001 solar radius and was significantly affected only by Z/X, the pp rate, and the uncertainties in helium diffusion constants. Our reference model also yielded envelope helium abundance of 0.2424, in good agreement with the approximate range of 0.24 to 0.25 inferred from helioseismic observations; only extreme Z/X values yielded envelope helium abundance outside this range. We found that other current uncertainties, namely, in the solar age and luminosity, in nuclear rates other than the pp reaction, in the low-temperature molecular opacities, and in the low-density equation of state, have no significant effect on the quantities that can be inferred from helioseismic observations. The predicted pre-main-sequence lithium depletion is uncertain by a factor of 2. The predicted neutrino capture rate is uncertain by approximately 30% for the Cl-27 experiment and by approximately 3% for Ga-71 experiments, while the B-8 neutrino flux is uncertain by approximately 30%.

Boothroyd, Arnold I.↗

Mid-frequency Band Dynamics of Large Space Structures

High and low intensity dynamic environments experienced by a spacecraft during launch and on-orbit operations, respectively, induce structural loads and motions, which are difficult to reliably predict. Structural dynamics in low- and mid-frequency bands are sensitive to component interface uncertainty and non-linearity as evidenced in laboratory testing and flight operations. Analytical tools for prediction of linear system response are not necessarily adequate for reliable prediction of mid-frequency band dynamics and analysis of measured laboratory and flight data. A new MATLAB toolbox, designed to address the key challenges of mid-frequency band dynamics, is introduced in this paper. Finite-element models of major subassemblies are defined following rational frequency-wavelength guidelines. For computational efficiency, these subassemblies are described as linear, component mode models. The complete structural system model is composed of component mode subassemblies and linear or non-linear joint descriptions. Computation and display of structural dynamic responses are accomplished employing well-established, stable numerical methods, modern signal processing procedures and descriptive graphical tools. Parametric sensitivity and Monte-Carlo based system identification tools are used to reconcile models with experimental data and investigate the effects of uncertainties. Models and dynamic responses are exported for employment in applications, such as detailed structural integrity and mechanical-optical-control performance analyses.

dynamics↗

Reduced Complexity Model Intercomparison Project Phase 2: Synthesizing Earth System Knowledge for Probabilistic Climate Projections

Over the last decades, climate science has evolved rapidly across multiple expert domains. Our best tools to capture state-of-the-art knowledge in an internally self-consistent modelling framework are the increasingly complex fully coupled Earth System Models (ESMs). However, computational limitations and the structural rigidity of ESMs mean that the full range of uncertainties across multiple domains are difficult to capture with ESMs alone. The tools of choice are instead more computationally efficient reduced complexity models (RCMs), which are structurally flexible and can span the response dynamics across a range of domain-specific models and ESM experiments. Here we present Phase 2 of the Reduced Complexity Model Intercomparison Project (RCMIP Phase 2), the first comprehensive intercomparison of RCMs that are probabilistically calibrated with key benchmark ranges from specialized research communities. Unsurprisingly, but crucially, we find that models which have been constrained to reflect the key benchmarks better reflect the key benchmarks. Under the low-emissions SSP1-1.9 scenario, across the RCMs, median peak warming projections range from 1.3 to 1.7°C (relative to 1850-1900, using an observationally-based historical warming estimate of 0.8°C between 1850-1900 and 1995-2014). Further developing methodologies to constrain these projection uncertainties seems paramount given the international community's goal to contain warming to below 1.5°C above pre-industrial in the long-term. Our findings suggest that users of RCMs should carefully evaluate their RCM, specifically its skill against key benchmarks and consider the need to include projections benchmarks either from ESM results or other assessments to reduce divergence in future projections.

Climate↗

Higher Flux from the Young Sun as an Explanation for Warm Temperatures for Early Earth and Mars

Observations indicate that the Earth was at least warm enough for liquid water to exist as far back as 4 Gyr ago, namely, as early as half a billion years after the formation of the Earth; in fact, there is evidence suggesting that Earth may have been even warmer then than it is now. These relatively warm temperatures required on early Earth are in apparent contradiction to the dimness of the early Sun predicted by the standard solar models. This problem has generally been explained by assuming that Earth's early atmosphere contained huge amounts of carbon dioxide (CO2), resulting in a large enough greenhouse effect to counteract the effect of a dimmer Sun. However, recent work places an upper limit of 0.04 bar on the partial pressure of CO2 in the period from 2.75 to 2.2 Gyr ago, based on the absence of siderite in paleosols; this casts doubt on the viability of a strong CO2 greenhouse effect on early Earth. The existence of liquid water on early Mars has been even more of a puzzle; even the maximum possible CO2 greenhouse effect cannot yield warm enough Martian surface temperatures. These problems can be resolved simultaneously for both Earth and Mars, if the early Sun was brighter than predicted by the standard solar models. This could be accomplished if the early Sun was slightly more massive than it is now, i.e., if the solar wind was considerably stronger in the past than at present. A slightly more massive young Sun would have left fingerprints on the internal structure of the present Sun. Today, helioseismic observations exist that can measure the internal structure of the Sun with very high precision. The task undertaken here was to compute solar models with the highest precision possible at this time, starting with slightly greater initial masses. These were evolved to the present solar age, where comparisons with the helioseismic observations could be made. Our computations also yielded the time evolution of the solar flux at the planets - a key input to the climates of early Earth and Mars. Early solar mass loss is not the only influence that can alter the internal structure of the present Sun. There are minor uncertainties in the physics of the solar models and in the key observed solar parameters that also affect the present Sun's internal structure. It was therefore imperative to obtain an understanding of the effects of these other uncertainties, in order to disentangle them from the fingerprints that might be left by early solar mass loss. From these considerations, our work was divided into two parts: (1) We first computed the evolution of standard solar models with input parameters varied within their uncertainties, to determine their effect on the observable helioseismic quantities; (2) We then computed non-standard solar models with higher initial masses to test against the helioseismological observations.

Sackmann, I.-Juliana↗

Design of robust failure detection filters

An essential aspect of the design of control systems for large, flexible spacecraft is fault tolerance. Because it is anticipated that a large number of sensors and actuators will be required to realize good control over these assemblies, the detection and isolation of component failures cannot be based on direct comparisons among replicated components. Instead, the notion of 'analytic redundancy' must be employed for the FDI function. Unfortunately this makes the FDI function sensitive to modeling errors which are certain to exist in the large space structure problem due to model truncation and parameter uncertainty. This paper addresses the robustness to model error of one method of FDI residual generation - the failure detection filter. Initial designs were found to be extremely sensitive to modeling error. The sources of this sensitivity are analyzed and modifications to the design are suggested. The improved filter is shown to have much better visibility of the failure signatures relative to the background due to modeling error.

San Martin, A. M.↗

Assessment of NASA GISS CMIP5 and Post-CMIP5 Simulated Clouds and TOA Radiation Budgets Using Satellite Observations. Part I: Cloud Fraction and Properties

Although many improvements have been made in phase 5 of the Coupled Model Intercomparison Project (CMIP5), clouds remain a significant source of uncertainty in general circulation models (GCMs) because their structural and optical properties are strongly dependent upon interactions between aerosol/cloud microphysics and dynamics that are unresolved in such models. Recent changes to the planetary boundary layer (PBL) turbulence and moist convection parameterizations in the NASA GISS Model E2 atmospheric GCM(post-CMIP5, hereafter P5) have improved cloud simulations significantly compared to its CMIP5 (hereafter C5) predecessor. A study has been performed to evaluate these changes between the P5 and C5 versions of the GCM, both of which used prescribed sea surface temperatures. P5 and C5 simulated cloud fraction (CF), liquid water path (LWP), ice water path (IWP), cloud water path (CWP), precipitable water vapor (PWV), and relative humidity (RH) have been compared to multiple satellite observations including the Clouds and the Earth's Radiant Energy System-Moderate Resolution Imaging Spectroradiometer (CERES-MODIS, hereafter CM), CloudSat- Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO; hereafter CC), Atmospheric Infrared Sounder (AIRS), and Advanced Microwave Scanning Radiometer for Earth Observing System (AMSR-E). Although some improvements are observed in the P5 simulation on a global scale, large improvements have been found over the southern midlatitudes (SMLs), where correlations increased and both bias and root-mean-square error (RMSE) significantly decreased, in relation to the previous C5 simulation, when compared to observations. Changes to the PBL scheme have resulted in improved total column CFs, particularly over the SMLs where marine boundary layer (MBL) CFs have increased by nearly 20% relative to the previous C5 simulation. Globally, the P5 simulated CWPs are 25 gm22 lower than the previous C5 results. The P5 version of the GCM simulates PWV and RH higher than its C5 counterpart and agrees well with the AMSR-E and AIRS observations. The moister atmospheric conditions simulated by P5 are consistent with the CF comparison and provide a strong support for the increase in MBL clouds over the SMLs. Over the tropics, the P5 version of the GCM simulated total column CFs and CWPs are slightly lower than the previous C5 results, primarily as a result of the shallower tropical boundary layer in P5 relative to C5 in regions outside the marine stratocumulus decks.

General circulation models↗

Prediction of Natural Frequency and Buckling Load Variability due to Uncertainty in Material Properties by Convex Modeling

Composite materials are widely used in various types of engineering structures. To a large extent, the properties of composite materials are dependent on the fabrication process. But even the composite materials manufactured by the same process may demonstrate differences in their elastic properties. For design purposes, one should be aware of the potential variations in load-carrying capacity and dynamic behavior of such structures that can arise due to the uncertainty in elastic moduli. A more realistic analysis of composite structures should be performed with the variations of the elastic moduli being taken into consideration at the same time. The present paper is a generalization of a study where the influence of uncertainty in elastic moduli on the axial buckling load was discussed. Here, we consider another case of buckling, shells under uniform external pressure. In addition, this paper deals with the variability of natural frequencies by use of convex modeling, which is apparently the first study of this kind in the literature. A numerical approach to the uncertainty problem is nonlinear programming, which we apply to solve the same problem to generate a set of comparable numerical data. The results from both methods show good agreement throughout. Thus, the effectiveness of the analytic convex modeling is clearly demonstrated. The bounds of he natural frequency and the buckling load provide the designer with a better view of the vibrational behavior and the actual load carrying capacities possessed by the composite structure.

Li, Y. W.↗

Evaluation of predictive accuracy in structural dynamic models

The evaluation of the predictive accuracy of dynamic models for future large space structures is addressed. Mass and stiffness uncertainties derived from a comparison of analytical and experimental modes are used to evaluate the uncertainty of response predictions based on the analytical model.

Hasselman, T. K.↗

Substructure Versus Property-Level Dispersed Modes Calculation

This paper calculates the effect of perturbed finite element mass and stiffness values on the eigenvectors and eigenvalues of the finite element model. The structure is perturbed in two ways: at the "subelement" level and at the material property level. In the subelement eigenvalue uncertainty analysis the mass and stiffness of each subelement is perturbed by a factor before being assembled into the global matrices. In the property-level eigenvalue uncertainty analysis all material density and stiffness parameters of the structure are perturbed modified prior to the eigenvalue analysis. The eigenvalue and eigenvector dispersions of each analysis (subelement and property-level) are also calculated using an analytical sensitivity approximation. Two structural models are used to compare these methods: a cantilevered beam model, and a model of the Space Launch System. For each structural model it is shown how well the analytical sensitivity modes approximate the exact modes when the uncertainties are applied at the subelement level and at the property level.

Stewart, Eric C.↗

Neural network uncertainty assessment using Bayesian statistics: a remote sensing application

Neural network (NN) techniques have proved successful for many regression problems, in particular for remote sensing; however, uncertainty estimates are rarely provided. In this article, a Bayesian technique to evaluate uncertainties of the NN parameters (i.e., synaptic weights) is first presented. In contrast to more traditional approaches based on point estimation of the NN weights, we assess uncertainties on such estimates to monitor the robustness of the NN model. These theoretical developments are illustrated by applying them to the problem of retrieving surface skin temperature, microwave surface emissivities, and integrated water vapor content from a combined analysis of satellite microwave and infrared observations over land. The weight uncertainty estimates are then used to compute analytically the uncertainties in the network outputs (i.e., error bars and correlation structure of these errors). Such quantities are very important for evaluating any application of an NN model. The uncertainties on the NN Jacobians are then considered in the third part of this article. Used for regression fitting, NN models can be used effectively to represent highly nonlinear, multivariate functions. In this situation, most emphasis is put on estimating the output errors, but almost no attention has been given to errors associated with the internal structure of the regression model. The complex structure of dependency inside the NN is the essence of the model, and assessing its quality, coherency, and physical character makes all the difference between a blackbox model with small output errors and a reliable, robust, and physically coherent model. Such dependency structures are described to the first order by the NN Jacobians: they indicate the sensitivity of one output with respect to the inputs of the model for given input data. We use a Monte Carlo integration procedure to estimate the robustness of the NN Jacobians. A regularization strategy based on principal component analysis is proposed to suppress the multicollinearities in order to make these Jacobians robust and physically meaningful.

Neural Networks (Computer)↗

Research in robust control for hypersonic aircraft

The research during the second reporting period has focused on robust control design for hypersonic vehicles. An already existing design for the Hypersonic Winged-Cone Configuration has been enhanced. Uncertainty models for the effects of propulsion system perturbations due to angle of attack variations, structural vibrations, and uncertainty in control effectiveness were developed. Using H(sub infinity) and mu-synthesis techniques, various control designs were performed in order to investigate the impact of these effects on achievable robust performance.

Calise, A. J.↗

An Inversion of Gravity and Topography for Mantle and Crustal Structure on Mars

Analysis of the gravity and topography of Mars presently provides our primary quantitative constraints on the internal structure of Mars. We present an inversion of the long-wavelength (harmonic degree less than or equal to 10) gravity and topography of Mars for lateral variations of mantle temperature and crustal thickness. Our formulation incorporates both viscous mantle flow (which most prior studies have neglected) and isostatically compensated density anomalies in the crust and lithosphere. Our nominal model has a 150-km-thick high-viscosity surface layer over an isoviscous mantle, with a core radius of 1840 km. It predicts lateral temperature variations of up to a few hundred degrees Kelvin relative to the mean mantle temperature, with high temperature under Tharsis and to a lesser extent under Elysium and cool temperatures elsewhere. Surprisingly, the model predicts crustal thinning beneath Tharsis. If correct, this implies that thinning of the crust by mantle shear stresses dominates over thickening of the crust by volcanism. The major impact basins (Hellas, Argyre, Isidis, Chryse, and Utopia) are regions of crustal thinning, as expected. Utopia is also predicted to be a region of hot mantle, which is hard to reconcile with the surface geology. An alternative model for Utopia treats it as a mascon basin. The Utopia gravity anomaly is consistent with the presence of a 1.2 to 1.6 km thick layer of uncompensated basalt, in good agreement with geologic arguments about the amount of volcanic fill in this area. The mantle thermal structure is the dominant contributor to the observed geoid in our inversion. The mantle also dominates the topography at the longest wavelengths, but shorter wavelengths (harmonic degrees greater than or equal to 4) are dominated by the crustal structure. Because of the uncertainty about the appropriate numerical values for some of the model's input parameters, we have examined the sensitivity of the model results to the planetary structural model (core radius and core and mantle densities), the mantle's viscosity stratification, and the mean crustal thickness. The model results are insensitive to the specific thickness or viscosity contrast of the high-viscosity surface layer and to the mean crustal thickness in the range 25 to 100 km. Models with a large core radius or with an upper mantle low-viscosity zone require implausibly large lateral variations in mantle temperature.

Kiefer, Walter S.↗