SEARCH · Engineering Papers

Results for “confidence measures”

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.

SourceResearch connectionFrom yearThrough year

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

At least 55 records · Page 3

All sources NASA NTRS DOE OSTI

NASA NTRS2003

Uniting Space, Ground and Underwater Measurements for Improved Estimates of Rain Rate

Global precipitation is monitored from a variety of platforms including space-borne, ground- and ocean-based platforms. Intercomparisons of these observations are crucial to validating the measurements and providing confidence for each measurement technique. Probability distribution functions of rain rates are used to compare satellite and ground-based radar observations. A preferred adjustment technique for improving rain rate distribution estimates is identified using measurements from ground-based radar and radar and rain gauges within the coverage area of the radar. The underwater measurement of rainfall shows similarities to radar measurements, but with intermediate spatial resolution and high temporal resolution. Reconciling these different measurement techniques provides understanding and confidence for all of the methods.

Amitai, E.↗

NASA NTRSDate not supplied

A Preliminary Study of Inter-Facility LWC Differences in Appendix C and Supercooled Large Drop Conditions due to Calibration Instruments

The simulation of clouds containing Supercooled Large Droplets has received increasing attention due to the introduction of Appendix O and future associated requirements for means of compliance. Supercooled Large Droplet conditions can cover four orders of magnitude in drop sizes, imposing a larger instrument measurement challenge than for Appendix C conditions. Wind tunnel facilities have adopted different instrumentation for liquid water content measurement, with fundamentally different principles of operation. In order to explore the comparability of the different instruments used for Appendix C and SLD measurement, and its impact on confidence in measurements used for means of compliance, a project was established to conduct a series of dedicated tests at three wind tunnel facilities. To date, liquid water content measurements have been completed using a Multi-Element sensor as the common instrument at two of the facilities. The data have provided preliminary information suggesting that substantial inter-facility differences likely exist in liquid water content estimates in Supercooled Large Droplet conditions that appear to be largely attributable to the choice of calibration instruments. These results are dependent on the assumption that the Multi-Element probe would produce equivalent measurements at the two facilities if the liquid water content were the same, regardless of other environmental differences that may exist between the two facilities. Planned further testing with other liquid water content measurement techniques may provide further information to confirm or refute the results of this study.

aircraft icing↗

NASA NTRSDate not supplied

A Preliminary Study of Inter-Facility LWC Differences in Appendix C and Supercooled Large Droplet Conditions due to Calibration Instruments

aircraft icing↗

NASA NTRS2021

Radar-Based Bayesian Estimation of Ice Crystal Growth Parameters within a Microphysical Model

The potential for polarimetric Doppler radar measurements to improve predictions of ice microphysical processes within an idealized model–observational framework is examined. In an effort to more rigorously constrain ice growth processes (e.g., vapor deposition) with observations of natural clouds, a novel framework is developed to compare simulated and observed radar measurements, coupling a bulk adaptive-habit model of vapor growth to a polarimetric radar forward model. Bayesian inference on key microphysical model parameters is then used, via a Markov chain Monte Carlo sampler, to estimate the probability distribution of the model parameters. The statistical formalism of this method allows for robust estimates of the optimal parameter values, along with (non-Gaussian) estimates of their uncertainty. To demonstrate this framework, observations from Department of Energy radars in the Arctic during a case of pristine ice precipitation are used to constrain vapor deposition parameters in the adaptive habit model. The resulting parameter probability distributions provide physically plausible changes in ice particle density and aspect ratio during growth. A lack of direct constraint on the number concentration produces a range of possible mean particle sizes, with the mean size inversely correlated to number concentration. Consistency is found between the estimated inherent growth ratio and independent laboratory measurements, increasing confidence in the parameter PDFs and demonstrating the effectiveness of the radar measurements in constraining the parameters. The combined Doppler and polarimetric observations produce the highest-confidence estimates of the parameter PDFs, with the Doppler measurements providing a stronger constraint for this case.

Robert S. Schrom↗

DOE OSTI2021

Radar-Based Bayesian Estimation of Ice Crystal Growth Parameters within a Microphysical Model

The potential for polarimetric Doppler radar measurements to improve predictions of ice microphysical processes within an idealized model–observational framework is examined. In an effort to more rigorously constrain ice growth processes (e.g., vapor deposition) with observations of natural clouds, a novel framework is developed to compare simulated and observed radar measurements, coupling a bulk adaptive-habit model of vapor growth to a polarimetric radar forward model. Bayesian inference on key microphysical model parameters is then used, via a Markov chain Monte Carlo sampler, to estimate the probability distribution of the model parameters. The statistical formalism of this method allows for robust estimates of the optimal parameter values, along with (non-Gaussian) estimates of their uncertainty. To demonstrate this framework, observations from Department of Energy radars in the Arctic during a case of pristine ice precipitation are used to constrain vapor deposition parameters in the adaptive habit model. The resulting parameter probability distributions provide physically plausible changes in ice particle density and aspect ratio during growth. A lack of direct constraint on the number concentration produces a range of possible mean particle sizes, with the mean size inversely correlated to number concentration. Consistency is found between the estimated inherent growth ratio and independent laboratory measurements, increasing confidence in the parameter PDFs and demonstrating the effectiveness of the radar measurements in constraining the parameters. Furthermore, the combined Doppler and polarimetric observations produce the highest-confidence estimates of the parameter PDFs, with the Doppler measurements providing a stronger constraint for this case.

54 ENVIRONMENTAL SCIENCES↗

NASA NTRS2015

Isotopic Composition of Carbon Dioxide Released from Confidence Hills Sediment as Measured by the Sample Analysis at Mars (SAM) Quadrupole Mass Spectrometer

In October 2014, the Mars Science Laboratory (MSL) "Curiosity" rover drilled into the sediment at the base of Mount Sharp in a location namsed Cionfidence Hills (CH). CH marked the fifth sample pocessed by the Sample Analysis at Mars (SAM) instrument suite since Curiosity arrived in Gale Crater, with previous analyses performed at Rocknest (RN), John Klein (JK), Cumberland (CB), and Windjana (WJ). Evolved gas analysis (EGA) of all samples has indicated H2O as well as O-, C- and S-bearing phases in the samples, often at abundances that would be below the detection limit of the CheMin instrument. By examining the temperatures at which gases are evolved from samples, SAM EGA data can help provide clues to the mineralogy of volatile-bearing phases when their identities are unclear to CheMin. SAM may also detect gases evolved from amorphous material in solid samples, which is not suitable for analysis by CheMin. Finally, the isotopic composition of these gases may suggest possible formation scenarios and relationships between phases. We will discuss C isotope ratios of CO2 evolved from the CH sample as measured with SAM's quadrupole mass spectrometer (QMS) and draw comparisons to samples previously analyzed by SAM.

Franz, H. B.↗

NASA NTRS2008

Uncertainty and Sensitivity Analyses of a Two-Parameter Impedance Prediction Model

This paper presents comparisons of predicted impedance uncertainty limits derived from Monte-Carlo-type simulations with a Two-Parameter (TP) impedance prediction model and measured impedance uncertainty limits based on multiple tests acquired in NASA Langley test rigs. These predicted and measured impedance uncertainty limits are used to evaluate the effects of simultaneous randomization of each input parameter for the impedance prediction and measurement processes. A sensitivity analysis is then used to further evaluate the TP prediction model by varying its input parameters on an individual basis. The variation imposed on the input parameters is based on measurements conducted with multiple tests in the NASA Langley normal incidence and grazing incidence impedance tubes; thus, the input parameters are assigned uncertainties commensurate with those of the measured data. These same measured data are used with the NASA Langley impedance measurement (eduction) processes to determine the corresponding measured impedance uncertainty limits, such that the predicted and measured impedance uncertainty limits (95% confidence intervals) can be compared. The measured reactance 95% confidence intervals encompass the corresponding predicted reactance confidence intervals over the frequency range of interest. The same is true for the confidence intervals of the measured and predicted resistance at near-resonance frequencies, but the predicted resistance confidence intervals are lower than the measured resistance confidence intervals (no overlap) at frequencies away from resonance. A sensitivity analysis indicates the discharge coefficient uncertainty is the major contributor to uncertainty in the predicted impedances for the perforate-over-honeycomb liner used in this study. This insight regarding the relative importance of each input parameter will be used to guide the design of experiments with test rigs currently being brought on-line at NASA Langley.

Jones, M. G.↗

NASA NTRSDate not supplied

Cryogenic Vacuum Chamber Testing of A Conductively-Cooled, High Temperature Superconducting Rotor for a 1.4 MW Electric Machine for Aeronautics Applications

This paper presents the second ever demonstration of a superconducting rotor cooled only via conductive connection to a cryocooler, i.e., without pumped or solid cryogens. The fullscale rotor was operated statically in its intended environment – about 1e-3 torr vacuum with only conductive cooling through mechanical connections to a cryocooler contained on the rotor. Stable operation of the rotor in a representative magnetic environment was demonstrated up to its rated direct current (57.2 A) and the designed temperature limit for the superconductor (62 K). Additional electrical measurements increased confidence that the superconducting coils functioned as intended. A collection of steady state temperature distributions was measured at operating and non-operating conditions. In all but one case, the observed temperature gradient between the cold tip and superconducting coils satisfies the design but with little margin. Opportunities to reduce the gradient are identified.

Electrified aircraft propulsion↗

NASA NTRSDate not supplied

Cryogenic Vacuum Chamber Testing of A Conductively-Cooled, High Temperature Superconducting Rotor for a 1.4 MW Electric Machine for Aeronautics Applications

This paper presents the first ever demonstration of a superconducting rotor cooled conductively without a cryogenic fluid or solid. The full-scale rotor was operated statically in its intended environment – about 1e-3 torr vacuum with only conductive cooling through mechanical connections to a cryocooler contained on the rotor. Stable operation of the rotor in a representative magnetic environment was demonstrated up to its rated direct current (57.2 A) and the designed temperature limit for the superconductor (62 K). Additional electrical measurements increased confidence that the superconducting coils functioned as intended. A collection of steady state temperature distributions was measured at operating and non-operating conditions. In all but one case, the observed temperature gradient between the cold tip and superconducting coils satisfies the design but with little margin. Opportunities to reduce the gradient are identified.

Electrified aircraft propulsion↗

NASA NTRS2013

An Updated TRMM Composite Climatology of Tropical Rainfall and Its Validation

An updated 15-yr Tropical Rainfall Measuring Mission (TRMM) composite climatology (TCC) is presented and evaluated. This climatology is based on a combination of individual rainfall estimates made with data from the primaryTRMMinstruments: theTRMM Microwave Imager (TMI) and the precipitation radar (PR). This combination climatology of passive microwave retrievals, radar-based retrievals, and an algorithm using both instruments simultaneously provides a consensus TRMM-based estimate of mean precipitation. The dispersion of the three estimates, as indicated by the standard deviation sigma among the estimates, is presented as a measure of confidence in the final estimate and as an estimate of the uncertainty thereof. The procedures utilized by the compositing technique, including adjustments and quality-control measures, are described. The results give a mean value of the TCC of 4.3mm day(exp -1) for the deep tropical ocean beltbetween 10 deg N and 10 deg S, with lower values outside that band. In general, the TCC values confirm ocean estimates from the Global Precipitation Climatology Project (GPCP) analysis, which is based on passive microwave results adjusted for sampling by infrared-based estimates. The pattern of uncertainty estimates shown by sigma is seen to be useful to indicate variations in confidence. Examples include differences between the eastern and western portions of the Pacific Ocean and high values in coastal and mountainous areas. Comparison of the TCC values (and the input products) to gauge analyses over land indicates the value of the radar-based estimates (small biases) and the limitations of the passive microwave algorithm (relatively large biases). Comparison with surface gauge information from western Pacific Ocean atolls shows a negative bias (~16%) for all the TRMM products, although the representativeness of the atoll gauges of open-ocean rainfall is still in question.

(GPCP) Global Precipitation Project analysis↗

NASA NTRS1977

The 64-meter antenna pedestal tilt at DSS 43, Tidbinbilla, Australia

The present and possible future effects of pedestal tilt at the deep space tracking station are discussed. Topics include causes of the tilt, its amplitude and rate of change, and the method of measurement used. The degree of confidence in the measurements made is also examined.

Gale, G.↗

DOE OSTI2021

ACCRUE—An Integral Index for Measuring Experimental Relevance in Support of Neutronic Model Validation

A key challenge for the introduction of any design changes, e.g., advanced fuel concepts, first-of-a-kind nuclear reactor designs, etc., is the cost of the associated experiments, which are required by law to validate the use of computer models for the various stages, starting from conceptual design, to deployment, licensing, operation, and safety. To achieve that, a criterion is needed to decide on whether a given experiment, past or planned, is relevant to the application of interest. This allows the analyst to select the best experiments for the given application leading to the highest measures of confidence for the computer model predictions. The state-of-the-art methods rely on the concept of similarity or representativity, which is a linear Gaussian-based inner-product metric measuring the angle—as weighted by a prior model parameters covariance matrix—between two gradients, one representing the application and the other a single validation experiment. This manuscript emphasizes the concept of experimental relevance which extends the basic similarity index to account for the value accrued from past experiments and the associated experimental uncertainties, both currently missing from the extant similarity methods. Accounting for multiple experiments is key to the overall experimental cost reduction by prescreening for redundant information from multiple equally-relevant experiments as measured by the basic similarity index. Accounting for experimental uncertainties is also important as it allows one to select between two different experimental setups, thus providing for a quantitative basis for sensor selection and optimization. The proposed metric is denoted by ACCRUE, short for Accumulative Correlation Coefficient for Relevance of Uncertainties in Experimental validation. Using a number of criticality experiments for highly enriched fast metal systems and low enriched thermal compound systems with accident tolerant fuel concept, the manuscript will compare the performance of the ACCRUE and basic similarity indices for prioritizing the relevance of a group of experiments to the given application.

97 MATHEMATICS AND COMPUTING↗

NASA NTRS1993

Measurements of the cosmic microwave background temperature at 1.47 GHz

We have used a radio-frequency-gain total-power radiometer to measure the intensity of the cosmic microwave background (CMB) at a frequency of 1.47 GHz (20.4 cm wavelength) from White Mountain, California in 1988 September and from the South Pole in 1989 December. The CMB thermodynamic temperature, T(CMB), is 2.27 +/- 0.25 K (68 percent confidence limit) measured from White Mountain and 2.26 +/- 0.20 K from the South Pole site. The combined result is 2.26 +/- 0.19 K. The correction for Galactic emission has been derived from scaled low-frequency maps and constitutes the main source of error. The atmospheric signal is extrapolated from our zenith scan measurements at higher frequencies. These results are consistent with our previous measurement at 1.41 GHz and about 2.5 sigma from the 2.74 +/- 0.01 K global average CMB temperature.

Bensadoun, M.↗

DOE OSTI2024

Updated uranium reference material 231 Pa/ 235 U consensus model ages for nuclear forensics

Radiochronometry provides the model age of nuclear materials, which is useful for understanding the production history of materials found outside of regulatory control. Certified reference materials (CRMs) are important for radiochronometry to increase confidence in measurement quality; however, the absence of 231 Pa/ 235 U CRMs necessitates that nuclear forensic laboratories measure the 231 Pa/ 235 U model ages of preexisting uranium reference materials. Here, in this work, new consensus 231 Pa/ 235 U model ages are reported from three nuclear forensic laboratories for three reference materials using current analytical methods. These updated consensus values can be used for quality control of 231 Pa/ 235 U model age measurements.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

DOE OSTI2023

Geothermal Play Fairway Analysis, Part 2: GIS methodology

Play Fairway Analysis (PFA) in geothermal exploration originates from a systematic methodology developed within the petroleum industry and is based on a geologic, geophysical, and hydrologic framework of identified geothermal systems. We tailored this methodology to study the geothermal resource potential of the Snake River Plain and surrounding region, but it can be adapted to other geothermal resource settings. We adapted the PFA approach to geothermal resource exploration by cataloging the critical elements controlling exploitable hydrothermal systems, establishing risk matrices that evaluate these elements in terms of both probability of success and level of knowledge, and building a code-based ‘processing model’ to process results. A geographic information system was used to compile a range of different data types, which we refer to as elements (e.g., faults, vents, heat flow, etc.), with distinct characteristics and measures of confidence. Discontinuous discrete data (points, lines, or polygons) for each element were transformed into continuous interpretive 2D grid surfaces called evidence layers. Because different data types have varying uncertainties, most evidence layers have an accompanying confidence layer which reflects spatial variations in these uncertainties. Risk layers, as defined here, are the product of evidence and confidence layers, and are the building blocks used to construct Common Risk Segment (CRS) maps for heat, permeability, and seal, using a weighted sum for permeability and heat, but a different approach with seal. CRS maps quantify the variable risk associated with each of these critical components. In a final step, the three CRS maps were combined into a Composite Common Risk Segment (CCRS) map, using a modified weighted sum, for results that reveal favorable areas for geothermal exploration. Additional maps are also presented that do not mix contributions from evidence and confidence (to allow an isolated view of evidence and confidence), as well as maps that calculate favorability using the product of components instead of a weighted sum (to highlight where all components are present). Our approach helped to identify areas of high geothermal favorability in the western and central Snake River Plain during the first phase of study and helped identify more precise local drilling targets during the second phase of work. By identifying favorable areas, this methodology can help to reduce uncertainty in geothermal energy exploration and development.

15 GEOTHERMAL ENERGY↗

DOE OSTI2020

Imprecise global sensitivity analysis using bayesian multimodel inference and importance sampling

Global Sensitivity Analysis (GSA) aims to understand the relative importance of uncertain input variables to model response. Conventional GSA involves calculating sensitivity (Sobol’) indices for a model with known model parameter distributions. However, model parameters are affected by aleatory and epistemic uncertainty, with the latter often caused by lack of data. In this paper, we propose a new framework to quantify uncertainty in probability model-form and model parameters resulting from small datasets and integrate these uncertainties into Sobol’ index estimates. First, the process establishes, through Bayesian multimodel inference, a set of candidate probability models and their associated probabilities. Imprecise Sobol’ indices are calculated from these probability models using an importance sampling reweighting approach. This results in probabilistic Sobol’ indices, whose distribution characterizes uncertainty in the sensitivity resulting from small dataset size. The imprecise Sobol’ indices thus provide a measure of confidence in the sensitivity estimate and, moreover, can be used to inform data collection efforts targeted to minimize the impact of uncertainties. Through an example studying the parameters of a Timoshenko beam, we show that these probabilistic Sobol’ indices converge to the true/deterministic Sobol’ indices as the dataset size increases and hence, distribution-form uncertainty reduces. The approach is then applied to assess the sensitivity of the out-of-plane properties of an E-glass fiber composite material to its constituent properties. This second example illustrates the approach for an important class of materials with wide-ranging applications when data may be lacking for some input parameters.

42 ENGINEERING↗

DOE OSTI2021

Galaxy Zoo DECaLS: Detailed visual morphology measurements from volunteers and deep learning for 314,000 galaxies

We present Galaxy Zoo DECaLS: detailed visual morphological classifications for Dark Energy Camera Legacy Survey images of galaxies within the SDSS DR8 footprint. Deeper DECaLS images (r = 23.6 versus r = 22.2 from SDSS) reveal spiral arms, weak bars, and tidal features not previously visible in SDSS imaging. To best exploit the greater depth of DECaLS images, volunteers select from a new set of answers designed to improve our sensitivity to mergers and bars. Galaxy Zoo volunteers provide 7.5 million individual classifications over 314 000 galaxies. 140 000 galaxies receive at least 30 classifications, sufficient to accurately measure detailed morphology like bars, and the remainder receive approximately 5. All classifications are used to train an ensemble of Bayesian convolutional neural networks (a state-of-the-art deep learning method) to predict posteriors for the detailed morphology of all 314 000 galaxies. We use active learning to focus our volunteer effort on the galaxies which, if labelled, would be most informative for training our ensemble. When measured against confident volunteer classifications, the trained networks are approximately 99 per cent accurate on every question. Morphology is a fundamental feature of every galaxy; our human and machine classifications are an accurate and detailed resource for understanding how galaxies evolve.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2022

Putting AlphaFold models to work with phenix.process_predicted_model and ISOLDE

AlphaFold has recently become an important tool in providing models for experimental structure determination by X-ray crystallography and cryo-EM. Large parts of the predicted models typically approach the accuracy of experimentally determined structures, although there are frequently local errors and errors in the relative orientations of domains. Importantly, residues in the model of a protein predicted by AlphaFold are tagged with a predicted local distance difference test score, informing users about which regions of the structure are predicted with less confidence. AlphaFold also produces a predicted aligned error matrix indicating its confidence in the relative positions of each pair of residues in the predicted model. The phenix.process_predicted_model tool downweights or removes low-confidence residues and can break a model into confidently predicted domains in preparation for molecular replacement or cryo-EM docking. These confidence metrics are further used in ISOLDE to weight torsion and atom–atom distance restraints, allowing the complete AlphaFold model to be interactively rearranged to match the docked fragments and reducing the need for the rebuilding of connecting regions.

59 BASIC BIOLOGICAL SCIENCES↗