Search NASA⌕ Search

SEARCH · Search NASA

Results for “uncertainty characterization”

Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 523 records · Page 29

Photometric calibration of NGS/POSS and ESO/SRC plates using the NOAO PDS measuring engine. I - Stellar photometry

The PDS/Monet measuring engine at the National Optical Astronomy Observatory was used to obtain photometry of nearly 10,000 stars on the NGS/POSS and 2000 stars on the ESO/SRC Survey glass plates. These measurements have been used to show that global transformation functions exist that allow calibration of stellar photometry from any blue or red plate to equivalent Johnson B and Cousins R photoelectric magnitudes. The four transformation functions appropriate for the POSS O and E and ESO/SRC J and R plates were characterized, and it was found that, within the measurement uncertainties, they vary from plate to plate only by photometric zero-point offsets. A method is described to correct for the zero-point shifts and to obtain calibrated B and R photometry of stellar sources to an average accuracy of 0.3-0.4 mag within the range R between values of 8 and 19.5 for red plates in both surveys, B between values of 9 and 20.5 on POSS blue plates, and B between values of 10 and 20.5 on ESO/SRC blue plates. This calibration procedure makes it possible to obtain rapid photometry of very large numbers of stellar sources.

Cutri, Roc M.↗

The Primordial Inflation Explorer (PIXIE) Mission

The Primordial Inflation Explorer (PIXIE) is an Explorer-class mission to map the absolute intensity and linear polarization of the cosmic microwave background and diffuse astrophysical foregrounds over the full sky from frequencies 30 GHz to 6 THz (I cm to 50 I-tm wavelength). PIXIE uses a polarizing Michelson interferometer with 2.7 K optics to measure the difference spectrum between two orthogonal linear polarizations from two co-aligned beams. Either input can view either the sky or a temperature-controlled absolute reference blackbody calibrator. The multimoded optics and high etendu provide sensitivity comparable to kilo-pixel focal plane arrays, but with greatly expanded frequency coverage while using only 4 detectors total. PIXIE builds on the highly successful COBEIFIRAS design by adding large-area polarization-sensitive detectors whose fully symmetric optics are maintained in thermal equilibrium with the CMB. The highly symmetric nulled design provides redundant rejection of major sources of systematic uncertainty. The principal science goal is the detection and characterization of linear polarization from an inflationary epoch in the early universe, with tensor-to-scalar ratio r much less than 10(exp -3). PIXIE will also return a rich data set constraining physical processes ranging from Big Bang cosmology, reionization, and large-scale structure to the local interstellar medium. Keywords: cosmic microwave background, polarization, FTS, bolometer

Kogut, Alan J.↗

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.↗

Assessment of JVX Proprotor Performance Data in Hover and Airplane-Mode Flight Conditions

A 0.656-scale V-22 proprotor, the Joint Vertical Experimental (JVX) rotor, was tested at the NASA Ames Research Center in both hover and airplane-mode (high-speed axial flow) flight conditions, up to an advance ratio of 0.562 (231 knots). This paper examines the two principal data sets generated by those tests, and includes investigations of hub spinner tares, torque/thrust measurement interactions, tunnel blockage effects, and other phenomena suspected of causing erroneous measurements or predictions. Uncertainties in hover and high-speed data are characterized. The results are reported here to provide guidance for future wind tunnel tests, data processing, and data analysis.

Proprotor↗

New Global Ocean Color Sensor: OCI on PACE

- OCI will provide TOA radiances at ~1km spatial resolution, from 340nm (315nm?) to 2260nm, hyperspectral from 340nm to 890nm, 2 day global coverage - OCI will continue and enhance NASA’s earth system data records for ocean color (heritage sensors: SeaWiFS, MODIS, VIIRS) - OCI flight unit is close to being ready for testing (planned for March 2022 to September 2022) - OCI ETU (Engineering Test Unit) completed testing summer 2021, results look promising (see next presentation) - On-orbit calibration will combine successful trending approaches from previous sensors (2 solar diffusers, QVD, lunar gain trending, spectral trending) - New calibration approaches for OCI: large QVD, dim diffuser for linearity trending, lunar hysteresis trending - OCI will be characterized prelaunch with an ambitious goal of 0.5% relative uncertainty; absolute uncertainty will be about 2% (before vicarious calibration); expected on-orbit gain trending accuracy is 0.2% or better - More info on PACE and OCI can be found at https://pace.oceansciences.org/

radiometer↗

Quantifying the Sun’s Magnetic Stress With the Photospheric Flows

We address the problem of constraining the mechanisms by which a massive amount of energy erupts from the sun at multiple scales, and how the corona is heated to high temperature. These mechanisms are highly dependent on how the magnetic field is stressed. As recommended in Klimchuk et al. white paper, translational and rotational motions of the photospheric magnetic elements are important drivers of the coronal heating that must be accurately characterized. Yet despite an abundance of photospheric observations, many uncertainties remain in measuring these flows that entangle and twist the magnetic field. This white paper states the current capacities for mapping the sun’s photospheric flows, with an emphasis on how to quantify the magnetic stress that builds up free energy and heats the corona. It also provides research avenues on how to go beyond our current limitations, so that the sun’s energy transport between the photosphere and the corona can be more accurately determined.

Raphael Attié↗

Evaluation of IMERG Satellite Precipitation Over the Land-Coast-Ocean Continuum – Part Ii: Quantification

To understand and manage water systems under a changing climate and meet an increasing demand for water, a quantitative understanding of precipitation is most important in coastal regions. The capabilities of the Integrated Multi-satellitE Retrievals for Global Precipitation Measurement (IMERG) V06B product for precipitation quantification are examined over three coastal regions of the United States: the West Coast, the Gulf of Mexico, and the East Coast, all of which are characterized by different topographies and precipitation climatologies. A novel uncertainty analysis of IMERG is proposed that considers environmental and physical parameters such as elevation and distance to the coastline. The IMERG performance is traced back to its components, i.e., passive microwave (PMW), infrared (IR), and morphing-based estimates. The analysis is performed using high-resolution, high-quality Ground Validation Multi-Radar/Multi-Sensor (GV-MRMS) rainfall estimates as ground reference at the native resolution of IMERG of 30 min and 0.1°. IMERG Final (IM-F) quantification performance heavily depends on the respective contribution of PMW, IR, and morph components. IM-F and its components overestimate the contribution of light rainfall (<1 mm h−1) and underestimate the contribution of high rainfall rates (>10 mm h−1) to the total rainfall volume. Strong regional dependencies are highlighted, especially over the West Coast, where the proximity of complex terrain to the coastline challenges precipitation estimates. Other major drivers are the distance from the coastline, elevation, and precipitation types, especially over the land and coast surface types, that highlight the impact of precipitation regimes.

Atmosphere↗

Global Sensitivity Analysis Using the Ultra‐Low Resolution Energy Exascale Earth System Model

Abstract For decades, Arctic temperatures have increased twice as fast as average global temperatures. As a first step toward quantifying parametric uncertainty in Arctic climate, we performed a variance‐based global sensitivity analysis (GSA) using a fully coupled, ultra‐low resolution (ULR) configuration of version 1 of the U.S. Department of Energy's Energy Exascale Earth System Model (E3SMv1). Specifically, we quantified the sensitivity of six quantities of interests (QOIs), which characterize changes in Arctic climate over a 75 year period, to uncertainties in nine model parameters spanning the sea ice, atmosphere, and ocean components of E3SMv1. Sensitivity indices for each QOI were computed with a Gaussian process emulator using 139 random realizations of the random parameters and fixed preindustrial forcing. Uncertainties in the atmospheric parameters in the Cloud Layers Unified by Binormals (CLUBB) scheme were found to have the most impact on sea ice status and the larger Arctic climate. Our results demonstrate the importance of conducting sensitivity analyses with fully coupled climate models. The ULR configuration makes such studies computationally feasible today due to its low computational cost. When advances in computational power and modeling algorithms enable the tractable use of higher‐resolution models, our results will provide a baseline that can quantify the impact of model resolution on the accuracy of sensitivity indices. Moreover, the confidence intervals provided by our study, which we used to quantify the impact of the number of model evaluations on the accuracy of sensitivity estimates, have the potential to inform the computational resources needed for future sensitivity studies.

54 ENVIRONMENTAL SCIENCES↗

Statistical Approaches for the Definition of Landslide Rainfall Thresholds and their Uncertainty Using Rain Gauge and Satellite Data

Models for forecasting rainfall-induced landslides are mostly based on the identification of empirical rainfall thresholds obtained exploiting rain gauge data. Despite their increased availability, satellite rainfall estimates are scarcely used for this purpose. Satellite data should be useful in ungauged and remote areas, or should provide a significant spatial and temporal reference in gauged areas. In this paper, the analysis of the reliability of rainfall thresholds based on rainfall remote sensed and rain gauge data for the prediction of landslide occurrence is carried out. To date, the estimation of the uncertainty associated with the empirical rainfall thresholds is mostly based on a bootstrap resampling of the rainfall duration and the cumulated event rainfall pairs (D,E) characterizing rainfall events responsible for past failures. This estimation does not consider the measurement uncertainty associated with D and E. In the paper, we propose (i) a new automated procedure to reconstruct ED conditions responsible for the landslide triggering and their uncertainties, and (ii) three new methods to identify rainfall threshold for the possible landslide occurrence, exploiting rain gauge and satellite data. In particular, the proposed methods are based on Least Square (LS), Quantile Regression (QR) and Nonlinear Least Square (NLS) statistical approaches. We applied the new procedure and methods to define empirical rainfall thresholds and their associated uncertainties in the Umbria region (central Italy) using both rain-gauge measurements and satellite estimates. We finally validated the thresholds and tested the effectiveness of the different threshold definition methods with independent landslide information. The NLS method among the others performed better in calculating thresholds in the full range of rainfall durations. We found that the thresholds obtained from satellite data are lower than those obtained from rain gauge measurements. This is in agreement with the literature, where satellite rainfall data underestimate the 'ground' rainfall registered by rain gauges.

landslide prediction↗

Stochastic finite volume method for uncertainty quantification of transient flow in gas pipeline networks

We develop a weakly intrusive framework to simulate the propagation of uncertainty in solutions of generic hyperbolic partial differential equation systems on graph-connected domains with nodal coupling and boundary conditions. The method is based on the Stochastic Finite Volume (SFV) approach and can be applied for uncertainty quantification (UQ) of the dynamical state of fluid flow over actuated transport networks. The numerical scheme has specific advantages for modeling intertemporal uncertainty in time-varying boundary parameters, which cannot be characterized by strict upper and lower (interval) bounds. We describe the scheme for a single pipe, and then formulate the controlled junction Riemann problem (JRP) that enables the extension to general network structures. In conclusion, we demonstrate the method's capabilities and performance characteristics using a standard benchmark test network.

97 MATHEMATICS AND COMPUTING↗

Ensemble Kalman inversion of induced polarization data

SUMMARY This paper explores the applicability of ensemble Kalman inversion (EKI) with level-set parametrization for solving geophysical inverse problems. In particular, we focus on its extension to induced polarization (IP) data with uncertainty quantification. IP data may provide rich information on characteristics of geological materials due to its sensitivity to characteristics of the pore–grain interface. In many IP studies, different geological units are juxtaposed and the goal is to delineate these units and obtain estimates of unit properties with uncertainty bounds. Conventional inversion of IP data does not resolve well sharp interfaces and tends to reduce and smooth resistivity variations, while not readily providing uncertainty estimates. Recently, it has been shown for DC resistivity that EKI is an efficient solver for inverse problems which provides uncertainty quantification, and its combination with level set parametrization can delineate arbitrary interfaces well. In this contribution, we demonstrate the extension of EKI to IP data using a sequential approach, where the mean field obtained from DC resistivity inversion is used as input for a separate phase angle inversion. We illustrate our workflow using a series of synthetic and field examples. Variations with uncertainty bounds in both DC resistivity and phase angles are recovered by EKI, which provides useful information for hydrogeological site characterization. Although phase angles are less well-resolved than DC resistivity, partly due to their smaller range and higher percentage data errors, it complements DC resistivity for site characterization. Overall, EKI with level set parametrization provides a practical approach forward for efficient hydrogeophysical imaging under uncertainty.

Geochemistry & Geophysics↗

A systematic study and framework of fringe projection profilometry with improved measurement performance for in-situ LPBF process monitoring

Fringe Projection Profilometry (FPP) is a cost-effective and non-invasive technology that has been shown to measure finer features. Here, in this work, we developed an in-situ FPP method to measure the dynamic topography of powder bed and printed layer during Laser Powder Bed Fusion (LPBF) additive manufacturing (AM) process. A systematic study towards developing a comprehensive framework of LPBF-specific FPP is demonstrated to enhance and evaluate the performance of applying FPP for in-situ LPBF monitoring, including 1) a modified sensor model with localized correction; 2) improved phase unwrapping with FFT filtering 3) quantitative uncertainty analysis; and 4) experimental validation with ex-situ characterization. The developed LPBF-specific FPP system and methods are implemented on a commercial LPBF-AM machine, achieving better accuracy, more robustness, and increased field of view while maintaining sufficient measurement range and decent resolution, in contrast to literature methods. The established FPP framework will facilitate the development of closed-loop control strategies for advancing LPBF based AM.

42 ENGINEERING↗

Uncertainty propagation in pore water chemical composition calculation using surrogate models

Performance assessment in deep geological nuclear waste repository systems necessitates an extended knowledge of the pore water chemical conditions prevailing in host-rock formations. In the last two decades, important progress has been made in the experimental characterization and thermodynamic modeling of pore water speciation, but the influence of experimental artifacts and uncertainties of thermodynamic input parameters are seldom evaluated. In this respect, we conducted an uncertainty propagation study in a reference geochemical model describing the pore water chemistry of the Callovian-Oxfordian clay formation. Nineteen model input parameters were perturbed, including those associated to experimental characterization (leached anions, exchanged cations, cation exchange selectivity coefficients) and those associated to generic thermodynamic databases (solubilities). A set of 13 quantities of interest were studied by the use of polynomial chaos expansions built non-intrusively with a least-squares forward stepwise regression approach. Training and validation sets of simulations were carried out using the geochemical speciation code PHREEQC. The statistical results explored the marginal distribution of each quantity of interest, their bivariate correlations as well as their global sensitivity indices. The influence of the assumed distributions for input parameters uncertainties was evaluated by considering two parametric domain sizes.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Voltage Probability Density Function Shaping Control Strategy Considering Grid Operational Uncertainties

It is well-known that power systems operation always affected by various uncertainties which make the bus voltage a random process that can be characterized by its probability density function (PDF) at any time instant. In this context, this paper presents a novel PDF-based voltage control framework for power systems. By modeling voltage as a stochastic process, we formulate a stochastic differential equationthat captures grid uncertainties. The associated Fokker-Planck-Kolmogorov equation is derived to describe the evolution of the voltage PDF, which enables the formulation of a PDF-shaping control strategy. To simplify the PDF control formulation, a B-spline neural network is introduced for real-time estimation and regulation of the voltage distribution. The proposed PDF control law updates voltage references for energy storage systems and synchronous generators using real-time PDF measurements and feedback signals. The proposed method is validated on a modified Kundur’s two-area system. Simulation results demonstrate that the controller can significantly improve the voltage stability under stochastic conditions, highlighting its effectiveness in modern inverter-rich grids.

Gui, Yonghao [ORNL] (ORCID:0000000250435534)↗

An upgraded frequency-selectable laser source (FLS) calibrator for CMB bandpass characterization

One of the biggest challenges for Cosmic Microwave Background (CMB) experiments comes from the uncertainty in instrument bandpass calibration. Uncertainties in bandpass can limit foreground removal and spectral fitting, which are critical for inflationary and galaxy cluster measurements. CMB experiments currently use Fourier Transform Spectrometers (FTSes) to measure instrument bandpasses. However, FTS systems are currently systematics-limited, so significant improvements in bandpass measurements require novel calibrators. To this end, we developed a Frequency-selectable Laser Source (FLS) calibrator, which uses a laser with adjustable frequency coupled to a system that allows for laser power attenuation. Following initial testing with the first FLS prototype, we developed an upgraded version of the calibrator with improved performance. We present the upgrades to the FLS calibrator, the characterization of the upgraded calibrator and new laser source, and plans for testing with microwave instruments in the field.

Saunders, Lauren J. [Fermilab] (ORCID:000000016367↗

Assessment of Uncertainty-Based Screening Volumes for NASA Robotic LEO and GEO Conjunction Risk Assessment

Conjunction Assessment operations require screening assets against the space object catalog by placing a pre-determined spatial volume around each asset and predicting when another object will violate that volume. The selection of the screening volume used for each spacecraft is a trade-off between observing all conjunction events that may pose a potential risk to the primary spacecraft and the ability to analyze those predicted events. If the screening volumes are larger, then more conjunctions can be observed and therefore the probability of a missed detection of a high risk conjunction event is small; however, the amount of data which needs to be analyzed increases. This paper characterizes the sensitivity of screening volume size to capturing typical orbit uncertainties and the expected number of conjunction events observed. These sensitivities are quantified in the form of a trade space that allows for selection of appropriate screen-ing volumes to fit the desired concept of operations, system limitations, and tolerable analyst workloads. This analysis will specifically highlight the screening volume determination and selection process for use in the NASA Conjunction Assessment Risk Analysis process but will also provide a general framework for other Owner / Operators faced with similar decisions.

Narvet, Steven W.↗

Frequency-Selectable Laser Source (FLS) Calibrator for CMB Bandpass Characterization

One of the biggest challenges for Cosmic Microwave Background (CMB) experiments comes from our detector bandpass calibration. Uncertainties in bandpass can severely limit our measurements by limiting foreground removal and spectral fitting, which is particularly important for high-$\ell$ observations like cluster science using the Sunyaev-Zeldovich (SZ) effect. Currently, CMB experiments typically use a Fourier Transform Spectrometer (FTS) to measure the detector bandpasses. However, the resolution of the FTS is dependent on the length of the interferometer arms, leading to a need for increasingly large FTS instruments as CMB experiments require tighter constraints on detector bandpasses. Additionally, systematic effects like shifts in bandpass shape from uneven illumination from the FTS further limit the calibration uncertainties. As a complement to the FTS, we have developed a Frequency-selectable Laser Source (FLS) calibrator, which uses a laser with adjustable frequency housed in a calibrator that allows for varying degrees of laser power attenuation. We present several tests used to characterize the first prototype design of the FLS calibrator, as well as the improvements to the calibrator design currently underway.

Saunders, Lauren [Fermilab]↗

Acoustic Liner Drag: Measurement Uncertainty Reduction and Application to Novel Perforate Geometries

In addition to developing acoustic liner concepts and characterizing their performance, the NASA Langley Liner Physics Team has investigated issues related to liner drag. A method to quantify relative drag of liner configurations was developed and employed to understand the effects of various liner features. It was observed that perforate shape could have a marked effect on the measured liner drag and led to the discovery of a low-drag geometry that cut the drag penalty between a perforate and a smooth wall by approximately 50%. Investigations of novel perforates to further reduce drag were stymied by measurement uncertainty that prevented further resolution of drag differences between configurations. The current study details efforts to understand the causes of this uncertainty and describe changes made to testing methods to reduce it. Previously evaluated perforates were retested with these improvements in the NASA Langley Grazing Flow Impedance Tube to determine their relative drag at a flow speed of Mach 0.5 without acoustic excitation. Their performance was compared to the previously identified low-drag geometry to see if further drag reductions could be realized.

drag↗