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NASA NTRSDate not supplied

Evaluation of CFD as a Surrogate for Wind Tunnel Testing - Experimental Uncertainty Quantification

A series of wind tunnel tests is being performed at the Unitary Plan Wind Tunnel at Langley Research Center to assess the validity of using computational fluid dynamics (CFD) as a surrogate for wind tunnel testing. In order to make proper comparisons, uncertainties in CFD results and experimental data must be well understood. The material presented will highlight the methods, assumptions, and elemental inputs used to achieve experimental uncertainty estimates for several variables of interest.The work performed to date has focused on gaining insight into random uncertainty via statistical analysis of repeat data and systematic uncertainty via Monte Carlo propagation analysis. These methods were combined using a second-order Monte Carlo propagation, resulting in a probability box (P-box) for each variable and at all conditions of interest. Figure 1 provides an example of one such P-box, showing the experimental uncertainty in a locally determined dynamic pressure (QC10) for one of many tunnel conditions evaluated during the Flow Survey experiment. This particular condition (Condition 27) has nominal set points of Mach number = 3.85, Reynolds number = 3x10(exp 6) ft(exp -1), total pressure = 5160 psfa, and total temperature = 150°F. The uncertainty in dynamic pressure at this condition is now well defined by this plot. Armed with this experimental data uncertainty, meaningful comparisons can be made with computational results, when their associated uncertainties are also considered.

Heather P Houlden↗

NASA NTRS2022

Effective Uncertainty Quantification for Multi-Angle Polarimetric Aerosol Remote Sensing Over Ocean

Multi-angle polarimetric (MAP) measurements can enable detailed characterization of aerosol microphysical and optical properties and improve atmospheric correction in ocean color remote sensing. Advanced retrieval algorithms have been developed to obtain multiple geophysical parameters in the atmosphere–ocean system. Theoretical pixel-wise retrieval uncertainties based on error propagation have been used to quantify retrieval performance and determine the quality of data products. However, standard error propagation techniques in high-dimensional retrievals may not always represent true retrieval errors well due to issues such as local minima and the nonlinear dependence of the forward model on the retrieved parameters near the solution. In this work, we analyze these theoretical uncertainty estimates and validate them using a flexible Monte Carlo approach. The Fast Multi-Angular Polarimetric Ocean coLor (FastMAPOL) retrieval algorithm, based on efficient neural network forward models, is used to conduct the retrievals and uncertainty quantification on both synthetic HARP2 (Hyper-Angular Rainbow Polarimeter 2) and AirHARP (airborne version of HARP2) datasets. In addition, for practical application of the uncertainty evaluation technique in operational data processing, we use the automatic differentiation method to calculate derivatives analytically based on the neural network models. Both the speed and accuracy associated with uncertainty quantification for MAP retrievals are addressed in this study. Pixel-wise retrieval uncertainties are further evaluated for the real AirHARP field campaign data. The uncertainty quantification methods and results can be used to evaluate the quality of data products, as well as guide MAP algorithm development for current and future satellite systems such as NASA’s Plankton, Aerosol, Cloud, ocean Ecosystem (PACE) mission.

PACE↗

NASA NTRSDate not supplied

Differential Equation Approximation Using Gradient-Boosted Quantile Regression

The operation of cyber-physical-human (CPH) systems is subject to various epistemic and aleatory uncertainties. Overall trustworthiness of CPH systems relies on the trustworthiness of its components and their interactions. It is important that computational models comprising the cyber component of CPH provide predictions accompanied by a measure of confidence in model outcomes. Uncertainty quantification (UQ) and propagation are especially important in safety critical CPH systems. Gradient-boosted trees is a modeling approach capable both of learning the dynamics of a system and performing UQ. In this paper, we devise a method for using gradient boosting to learn the dynamics of a second order differential equation and estimate uncertainty at the same time. We do this by creating a custom loss function that trains the model to approximate the second derivative of a noisy time series, and to penalize based on a parameter that corresponds to the desired quantile. The resulting gradient boosting model can simulate stochastic trajectories of the system given a single starting point, that is, it can estimate both the expected trajectory and its uncertainty. We show that the uncertainty estimation is well calibrated and that the model can learn the dynamics even in the presence of noise. We demonstrate the approach on a simple cartpole system.

Autonomous systems↗

NASA NTRS2014

Assessment of Satellite Ocean Colour Radiometry and Derived Geophysical Products

Standardization of methods to assess and assign quality metrics to satellite ocean color radiometry and derived geophysical products has become paramount with the inclusion of the marine reflectance and chlorophyll-a concentration (Chla) as essential climate variables (ECV; [1]) and the recognition that optical remote sensing of the oceans can only contribute to climate research if and when a continuous succession of satellite missions can be shown to collectively provide a consistent, long-term record with known uncertainties. In 20 years, the community has made significant advancements toward that objective, but providing a complete uncertainty budget for all products and for all conditions remains a daunting task. In the retrieval of marine water-leaving radiance from observed top-of-atmosphere radiance, the sources of uncertainties include those associated with propagation of sensor noise and radiometric calibration and characterization errors, as well as a multitude of uncertainties associated with the modeling and removal of effects from the atmosphere and sea surface. This chapter describes some common approaches used to assess quality and consistency of ocean color satellite products and reviews the current status of uncertainty quantification in the field. Its focus is on the primary ocean color product, the spectrum of marine reflectance Rrs, but uncertainties in some derived products such as the Chla or inherent optical properties (IOPs) will also be considered.

Ocean↗

NASA NTRS2007

Interannual and Decadal Variability of Ocean Surface Latent Heat Flux as Seen from Passive Microwave Satellite Algorithms

Ocean surface turbulent fluxes are critical links in the climate system since they mediate energy exchange between the two fluid systems (ocean and atmosphere) whose combined heat transport determines the basic character of Earth's climate. Deriving physically-based latent and sensible heat fluxes from satellite is dependent on inferences of near surface moisture and temperature from coarser layer retrievals or satellite radiances. Uncertainties in these "retrievals" propagate through bulk aerodynamic algorithms, interacting as well with error properties of surface wind speed, also provided by satellite. By systematically evaluating an array of passive microwave satellite algorithms, the SEAFLUX project is providing improved understanding of these errors and finding pathways for reducing or eliminating them. In this study we focus on evaluating the interannual variability of several passive microwave-based estimates of latent heat flux starting from monthly mean gridded data. The algorithms considered range from those based essentially on SSM/I (e.g. HOAPS) to newer approaches that consider additional moisture information from SSM/T-2 or AMSU-B and lower tropospheric temperature data from AMSU-A. On interannual scales, variability arising from ENSO events and time-lagged responses of ocean turbulent and radiative fluxes in other ocean basins (as well as the extratropical Pacific) is widely recognized, but still not well quantified. Locally, these flux anomalies are of order 10-20 W/sq m and present a relevant "target" with which to verify algorithm performance in a climate context. On decadal time scales there is some evidence from reanalyses and remotely-sensed fluxes alike that tropical ocean-averaged latent heat fluxes have increased 5-10 W/sq m since the early 1990s. However, significant uncertainty surrounds this estimate. Our work addresses the origin of these uncertainties and provides statistics on time series of tropical ocean averages, regional space / time correlation analysis, and separation of contributions by variations in wind and near surface humidity deficit. Comparison to variations in reanalysis data sets is also provided for reference.

Robertson, Franklin R.↗

NASA NTRS1985

Variation of cosmic rays and solar wind properties with respect to the heliospheric current sheet. I - Five-GeV protons and solar wind speed

One of the principal uncertainties in understanding the propagation of cosmic rays in the heliosphere is related to the role of latitudinal transport by gradient and curvature drifts. The steady state distribution of cosmic rays with respect to the heliospheric current sheet or in latitude may possibly provide some information regarding the existing problems. Newkirk and Lockwood (1981) have considered the current sheet with respect to its role as a natural surface of symmetry for the propagation of cosmic rays in the heliosphere. The present investigation represents an extension of this study. Central objectives are related to a determination of the gradient of 5-GeV cosmic rays with respect to the heliospheric current sheet at 1 AU, the possible effect of the solar cycle upon such gradients, and an evaluation of the ability of several theoretical models to explain the gradients.

Newkirk, G., Jr.↗

NASA NTRS1994

Solar activity and coronal mass ejections on the western hemisphere of the Sun in mid-August 1989: Association with interplanetary observations at the ICE and IMP 8 spacecraft

During the 10-day period from August 12 to 21, 1989, a sequence of coronal mass ejections (CMEs) was observed above the west limb of the Sun by the Solar Maximum Mission (SMM) coronagraph. Most of these CMEs apparently originated in the vicinity of one particularly active region during its passage from near central meridian to behind the west limb of the Sun. We present observations made at 1 AU during this period by the International Cometary Explorer (ICE) (formerly International Sun Earth Explorer-3 (ISEE 3)) and Interplanetary Monitoring Platform (IMP 8) spacecraft which were separated by approximately 75 deg in heliolongitude. Following CMEs on August 12 associated with solar events at approximately W40 deg, IMP 8 (in Earth orbit) detected a strong shock followed by signatures in magnetic field, solar wind plasma, and energetic ion data which suggest that CME-related material ('ejecta') forming the shock driver engulfed the spacecraft. This spacecraft only observed weak shocks, and no ejecta, from later CMEs originating further west of the spacecraft. In contrast ICE, off the west limb at approximately W75 deg, observed the shock from the W40 deg event but failed to encounter the shock driver, whereas clear ejecta signatures were observed following events further west, closer to the spacecraft heliolongitude. The disappearance of these signatures (which include bidirectional energetic ion flows, bidirectional solar wind heat fluxes, quiet, enhanced magnetic fields and anomalously cool plasma) at IMP 8 and their emergence at ICE as the solar source region moved westward supports the association of such signatures with ejecta related to CMEs. The dual-spacecraft observations are also consistent with the conclusion of Richardson and Cane (1993) that ejecta at 1 AU typically extend approximately 50 degs in longitude from the solar source. Some plausible associations between particular intervals of ejecta signatures at ICE and individual CMEs are made. However, these associations are complicated by the large number of CMEs present, by intermittent ICE data coverage, and by uncertainties in the ejecta propagation speeds to the spacecraft.

Richardson, I. G.↗

NASA NTRS1994

Formal results regarding metric space techniques for the study of astrophysical maps

We extend a newly developed formal system for the description of astrophyscial maps. In this formalism, we consider the difference between maps to be the distance between elements of a pseudometric space (the space of all such maps). This Ansatz allows us to measure quantitatively the difference between any two maps and to order the space of all maps. For each physical characteristic of interest, this technique assigns an 'output' function to each map; the difference between the maps is then determined from the difference between their corresponding output functions. In this present study, we show that the results of this procedure are invariant under a class of transformations of the maps and the domains of the maps. In addition, we study the propagation of errors (observational uncertainties) through this formalism. We show that the uncertainties in the output functions can be controlled provided that the signal to noise ratios in the original astrophysical maps are sufficiently high. The results of this paper thus increase the effectiveness of this formal system for the description, classification, and analysis of astrophysical maps.

Adams, Fred C.↗

NASA NTRS2000

A Probabilistic Framework for the Validation and Certification of Computer Simulations

The paper presents a methodology for quantifying, propagating, and managing the uncertainty in the data required to initialize computer simulations of complex phenomena. The purpose of the methodology is to permit the quantitative assessment of a certification level to be associated with the predictions from the simulations, as well as the design of a data acquisition strategy to achieve a target level of certification. The value of a methodology that can address the above issues is obvious, specially in light of the trend in the availability of computational resources, as well as the trend in sensor technology. These two trends make it possible to probe physical phenomena both with physical sensors, as well as with complex models, at previously inconceivable levels. With these new abilities arises the need to develop the knowledge to integrate the information from sensors and computer simulations. This is achieved in the present work by tracing both activities back to a level of abstraction that highlights their commonalities, thus allowing them to be manipulated in a mathematically consistent fashion. In particular, the mathematical theory underlying computer simulations has long been associated with partial differential equations and functional analysis concepts such as Hilbert spares and orthogonal projections. By relying on a probabilistic framework for the modeling of data, a Hilbert space framework emerges that permits the modeling of coefficients in the governing equations as random variables, or equivalently, as elements in a Hilbert space. This permits the development of an approximation theory for probabilistic problems that parallels that of deterministic approximation theory. According to this formalism, the solution of the problem is identified by its projection on a basis in the Hilbert space of random variables, as opposed to more traditional techniques where the solution is approximated by its first or second-order statistics. The present representation, in addition to capturing significantly more information than the traditional approach, facilitates the linkage between different interacting stochastic systems as is typically observed in real-life situations.

Ghanem, Roger↗

NASA NTRS2015

Spacecraft Charging Sensitivity to Material Properties

Evaluating spacecraft charging behavior of a vehicle in the space environment requires knowledge of the material properties relevant to the charging process. Implementing surface and internal charging models requires a user to specify a number of material electrical properties including electrical resistivity parameters (dark and radiation induced), dielectric constant, secondary electron yields, photoemission yields, and breakdown strength in order to correctly evaluate the electric discharge threat posed by the increasing electric fields generated by the accumulating charge density. In addition, bulk material mass density and/or chemical composition must be known in order to analyze radiation shielding properties when evaluating internal charging. We will first describe the physics of spacecraft charging and show how uncertainties in material properties propagate through spacecraft charging algorithms to impact the results obtained from charging models. We then provide examples using spacecraft charging codes to demonstrate their sensitivity to material properties. The goal of this presentation is to emphasize the importance in having good information on relevant material properties in order to best characterize on orbit charging threats.

Minow, Joseph I.↗

NASA NTRS2014

Stardust Interstellar Preliminary Examination X: Impact Speeds and Directions of Interstellar Grains on the Stardust Dust Collector

On the basis of an interstellar dust model compatible with Ulysses and Galileo observations, we calculate and predict the trajectories of interstellar dust (ISD) in the solar system and the distribution of the impact speeds, directions, and flux of ISD particles on the Stardust Interstellar Dust Collector during the two collection periods of the mission. We find that the expected impact velocities are generally low (less than 10 km per second) for particles with the ratio of the solar radiation pressure force to the solar gravitational force beta greater than 1, and that some of the particles will impact on the cometary side of the collector. If we assume astronomical silicates for particle material and a density of 2 grams per cubic centimeter, and use the Ulysses measurements and the ISD trajectory simulations, we conclude that the total number of (detectable) captured ISD particles may be on the order of 50. In companion papers in this volume, we report the discovery of three interstellar dust candidates in the Stardust aerogel tiles. The impact directions and speeds of these candidates are consistent with those calculated from our ISD propagation model, within the uncertainties of the model and of the observations.

interstellar↗

NASA NTRS2016

Model-Based Fatigue Prognosis of Fiber-Reinforced Laminates Exhibiting Concurrent Damage Mechanisms

Prognostics of large composite structures is a topic of increasing interest in the field of structural health monitoring for aerospace, civil, and mechanical systems. Along with recent advancements in real-time structural health data acquisition and processing for damage detection and characterization, model-based stochastic methods for life prediction are showing promising results in the literature. Among various model-based approaches, particle-filtering algorithms are particularly capable in coping with uncertainties associated with the process. These include uncertainties about information on the damage extent and the inherent uncertainties of the damage propagation process. Some efforts have shown successful applications of particle filtering-based frameworks for predicting the matrix crack evolution and structural stiffness degradation caused by repetitive fatigue loads. Effects of other damage modes such as delamination, however, are not incorporated in these works. It is well established that delamination and matrix cracks not only co-exist in most laminate structures during the fatigue degradation process but also affect each other's progression. Furthermore, delamination significantly alters the stress-state in the laminates and accelerates the material degradation leading to catastrophic failure. Therefore, the work presented herein proposes a particle filtering-based framework for predicting a structure's remaining useful life with consideration of multiple co-existing damage-mechanisms. The framework uses an energy-based model from the composite modeling literature. The multiple damage-mode model has been shown to suitably estimate the energy release rate of cross-ply laminates as affected by matrix cracks and delamination modes. The model is also able to estimate the reduction in stiffness of the damaged laminate. This information is then used in the algorithms for life prediction capabilities. First, a brief summary of the energy-based damage model is provided. Then, the paper describes how the model is embedded within the prognostic framework and how the prognostics performance is assessed using observations from run-to-failure experiments

Prognostics↗

NASA NTRS2017

Precomputing Process Noise Covariance for Onboard Sequential Filters

Process noise is often used in estimation filters to account for unmodeled and mismodeled accelerations in the dynamics. The process noise covariance acts to inflate the state covariance over propagation intervals, increasing the uncertainty in the state. In scenarios where the acceleration errors change significantly over time, the standard process noise covariance approach can fail to provide effective representation of the state and its uncertainty. Consider covariance analysis techniques provide a method to precompute a process noise covariance profile along a reference trajectory using known model parameter uncertainties. The process noise covariance profile allows significantly improved state estimation and uncertainty representation over the traditional formulation. As a result, estimation performance on par with the consider filter is achieved for trajectories near the reference trajectory without the additional computational cost of the consider filter. The new formulation also has the potential to significantly reduce the trial-and-error tuning currently required of navigation analysts. A linear estimation problem as described in several previous consider covariance analysis studies is used to demonstrate the effectiveness of the precomputed process noise covariance, as well as a nonlinear descent scenario at the asteroid Bennu with optical navigation.

onboard↗

NASA NTRS2017

Real-Time Prediction of Safety Margins in the National Airspace

Underlying all operations in the National Airspace System (NAS) is the concept of safety. Safety, as defined by acceptable levels of risk, is to be maintained at all times. The real-time safety monitoring (RTSM) framework is under development to provide an automated system to quantify safety in the NAS, estimate the current level of safety, and predict the future evolution of safety and the occurrence of events that pose an increased risk to flights so that these occurrences can be managed strategically rather than mitigated reactively. This paper presents the mathematical framework, the models, and the monitoring and prediction algorithms used to achieve this. RTSM computes safety as expressed through a set of safety margins based on user-defined safety metrics, thresolds, and events. Sources of uncertainty are modeled and propagated through the predictions in order to compute the probabilistic evolution of safety and the probability of events that introduce increased risk to operations. A prototype implementation is discussed and results demonstrating feasibility are presented. The results highlight the kinds of predictions that can be computed and the fidelity that is currently achieved.

national airspace system↗

NASA NTRSDate not supplied

Monte Carlo simulations of neutrino and charged lepton propagation in the Earth with nuPyProp

An accurate modeling of neutrino flux attenuation and the distribution of leptons they produce in transit through the Earth is an essential component to determine neutrino flux sensitivities of underground, sub-orbital and space-based detectors. Through neutrino oscillations over cosmic distances, astrophysical neutrino sources are expected to produce nearly equal fluxes of electron, muon and tau neutrinos. Of particular interest are tau neutrinos that interact in the Earth at modest slant depths to produce leptons. Some leptons emerge from the Earth and decay in the atmosphere to produce extensive air showers. Future balloon-borne and satellite-based opticalCherenkov neutrino telescopes will be sensitive to upward air showers from tau neutrino induced lepton decays. We present nuPyProp, a python code that is part of the nuSpaceSim package. nuPyProp generates look-up tables for exit probabilities and energy distributions for (see paper for proper equation) propagation in the Earth. This flexible code runs with either stochastic or continuous electromagnetic energy losses for the lepton transit through the Earth. Current neutrino cross section models and energy loss models are included along with templates for user input of other models. Results from nuPyProp are compared with other recent simulation packages for neutrino and charged lepton propagation. Sources of modeling uncertainties are described and quantified.

Yosui Akaike↗

NASA NTRSDate not supplied

Quantifying the Sensitivity of Condition Incidence Parameters in the Evidence Library

One approach to quantifying spaceflight risk at NASA makes use event driven probabilistic techniques. The Medical Extensible Dynamic Probabilistic Risk Assessment Tool (MEDPRAT) is such a tool that estimates medical risk metrics via simulation and enables optimization of medical resources subject to mission constraints [1]. Previous analyses have informed medical set composition, exercise countermeasures, and water intake, where each analysis quantifies the risk associated with proposed variations in system design. As future mission profiles extend beyond Low-Earth Orbit (LEO) and lengthen in duration, understanding these risks and contributing factors is critical. MEDPRAT employs Monte Carlo sampling techniques to simulate missions and track the occurrence of medical events. These events follow fault-tree-like progressions through levels of severity and mitigation via medical treatment to many possible outcomes and these are reported throughout the mission. Making this possible, are the medical databases that contain evidence gathered by the Human Research Program (HRP). Quantifying the impact of uncertainty or variability in the input data is an important step in evaluating the credibility of modeling and simulation results. In this work, we investigate the sensitivity of medical risk metrics with respect to the condition incidence parameters within the Evidence Library (EL) [2] as the medical database input for MEDPRAT. The medical conditions, contained in the EL, are equipped with incidence rates that describe the likelihood that the condition will occur. These incidence rates reflect historical spaceflight data or when appropriate, terrestrial data. In this presentation, we will explore how uncertainty in these rates propagate to the medical risk described by MEDPRAT. These results identify the conditions and parameters with the largest contribution to medical risks.

Ian Lim↗

NASA NTRS1996

Effect of Correlated Precision Errors on Uncertainty of a Subsonic Venturi Calibration

An uncertainty analysis performed in conjunction with the calibration of a subsonic venturi for use in a turbine test facility produced some unanticipated results that may have a significant impact in a variety of test situations. Precision uncertainty estimates using the preferred propagation techniques in the applicable American National Standards Institute/American Society of Mechanical Engineers standards were an order of magnitude larger than precision uncertainty estimates calculated directly from a sample of results (discharge coefficient) obtained at the same experimental set point. The differences were attributable to the effect of correlated precision errors, which previously have been considered negligible. An analysis explaining this phenomenon is presented. The article is not meant to document the venturi calibration, but rather to give a real example of results where correlated precision terms are important. The significance of the correlated precision terms could apply to many test situations.

Hudson, S. T.↗

NASA NTRS1985

Charge and energy dependence of the residence time of cosmic ray nuclei below 15 GeV/nucleon

The relative abundance of nuclear species measured in cosmic rays at Earth has often been interpreted with the simple leaky box model. For this model to be consistent an essential requirement is that the escape length does not depend on the nuclear species. The discrepancy between escape length values derived from iron secondaries and from the B/C ratio was identified by Garcia-Munoz and his co-workers using a large amount of experimental data. Ormes and Protheroe found a similar trend in the HEAO data although they questioned its significance against uncertainties. They also showed that the change in the B/C ratio values implies a decrease of the residence time of cosmic rays at low energies in conflict with the diffusive convective picture. These conclusions crucially depend on the partial cross section values and their uncertainties. Recently new accurate cross sections of key importance for propagation calculations have been measured. Their statistical uncertainties are often better than 4% and their values significantly different from those previously accepted. Here, these new cross sections are used to compare the observed B/C+O and (Sc to Cr)/Fe ratio to those predicted with the simple leaky box model.

Soutoul, A.↗