Search NASA⌕ Search

SEARCH · Search NASA

Results for “EXTRAPOLATION”

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 343 records · Page 19
All sourcesNASA NTRSDOE OSTI
DOE OSTI2016

Toward a W4-F12 approach: Can explicitly correlated and orbital-based ab initio CCSD(T) limits be reconciled?

In the context of high-accuracy computational thermochemistry, the valence coupled cluster with all singles and doubles (CCSD) correlation component of molecular atomization energies presents the most severe basis set convergence problem, followed by the (T) component. In the present paper, we make a detailed comparison, for an expanded version of the W4-11 thermochemistry benchmark, between, on the one hand, orbital-based CCSD/AV{5,6}Z + d and CCSD/ACV{5,6}Z extrapolation, and on the other hand CCSD-F12b calculations with cc-pVQZ-F12 and cc-pV5Z-F12 basis sets. This latter basis set, now available for H–He, B–Ne, and Al–Ar, is shown to be very close to the basis set limit. Apparent differences (which can reach 0.35 kcal/mol for systems like CCl{sub 4}) between orbital-based and CCSD-F12b basis set limits disappear if basis sets with additional radial flexibility, such as ACV{5,6}Z, are used for the orbital calculation. Counterpoise calculations reveal that, while total atomization energies with V5Z-F12 basis sets are nearly free of BSSE, orbital calculations have significant BSSE even with AV(6 + d)Z basis sets, leading to non-negligible differences between raw and counterpoise-corrected extrapolated limits. This latter problem is greatly reduced by switching to ACV{5,6}Z core-valence basis sets, or simply adding an additional zeta to just the valence orbitals. Previous reports that all-electron approaches like HEAT (high-accuracy extrapolated ab-initio thermochemistry) lead to different CCSD(T) limits than “valence limit + CV correction” approaches like Feller-Peterson-Dixon and Weizmann-4 (W4) theory can be rationalized in terms of the greater radial flexibility of core-valence basis sets. For (T) corrections, conventional CCSD(T)/AV{Q,5}Z + d calculations are found to be superior to scaled or extrapolated CCSD(T)-F12b calculations of similar cost. For a W4-F12 protocol, we recommend obtaining the Hartree-Fock and valence CCSD components from CCSD-F12b/cc-pV{Q,5}Z-F12 calculations, but the (T) component from conventional CCSD(T)/aug’-cc-pV{Q,5}Z + d calculations using Schwenke’s extrapolation; post-CCSD(T), core-valence, and relativistic corrections are to be obtained as in the original W4 theory. W4-F12 is found to agree slightly better than W4 with ATcT (active thermochemical tables) data, at a substantial saving in computation time and especially I/O overhead. A W4-F12 calculation on benzene is presented as a proof of concept.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Influence of the complete basis set approximation, tight weighted-core, and diffuse functions on the DLPNO-CCSD(T1) atomization energies of neutral H,C,O-compounds

The impact of complete basis set extrapolation schemes (CBS), diffuse functions, and tight weighted core functions on enthalpies of formation predicted via the DLPNO-CCSD(T1) reduced Feller Peterson-Dixon approach has been examined for neutral H,C,O-compounds. All tested three-point (TZ/QZ/5Z) extrapolation schemes result in mean unsigned deviation (MUD) below 2 kJ mol -1 relative to the experiment. Here, the two-point QZ/5Z and TZ/QZ CBS 1/$l^3_{max}$ extrapolation schemes are inferior to their inverse power counterpart (1/($l_{max}$ + 1/2) 4 ) by 1.3 and 4.3 kJ mol -1 . The CBS extrapolated frozen core atomization energies are insensitive (within 1 kJ mol -1 ) to augmentation of the basis set with tight weighted core functions. The core-valence correlation effects converge already at triple-ζ, although double- ζ/triple- ζ CBS extrapolation performs better and is recommended. The effect of diffuse function augmentation converges slowly, and cannot be reproduced with double- ζ or triple- ζ calculations as these are plagued with basis set superposition and incompleteness errors.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2026

Robust Design Under Uncertainty in Quantum Error Mitigation

Error mitigation techniques are crucial to achieving near-term quantum advantage. Classical postprocessing of quantum computation outcomes is a popular approach for error mitigation, which includes methods, such as zero noise extrapolation, virtual distillation, and learning-based error mitigation. However, these techniques have limitations due to the propagation of uncertainty resulting from the finite shot number of a quantum measurement. In this work, we introduce general and unbiased methods for quantifying the uncertainty and error of error-mitigated observables based on the strategic sampling of error mitigation outcomes. We then extend our approach to demonstrate the optimization of performance and robustness of error mitigation under uncertainty. To illustrate our methods, we apply them to zero noise extrapolation and Clifford date regression in the ground state of the XY model simulated using depolarizing and International Business Machines Corporation (IBM) Toronto noise models, respectively. In particular, we optimize the choice of noise levels and the allocation of shots for zero noise extrapolation and the distribution of the training circuits for Clifford data regression. While our methods are readily applicable to any postprocessing-based error mitigation approach, in practice they must not be prohibitively expensive—even though they perform optimizations of the error mitigation hyperparameters requiring sampling of a statistical distribution of error mitigation outcomes. By leveraging surrogate-based optimization, we show that our methods can efficiently perform optimal design for a zero noise extrapolation implementation. We then further demonstrate the transferability of learned zero noise extrapolation hyperparameters to other similar circuits.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2017

FY17 Status Report on the Micromechanical Finite Element Modeling of Creep Fracture of Grade 91 Steel

Advanced reactors designed to operate at higher temperatures than current light water reactors require structural materials with high creep strength and creep-fatigue resistance to achieve long design lives. Grade 91 is a ferritic/martensitic steel designed for long creep life at elevated temperatures. It has been selected as a candidate material for sodium fast reactor intermediate heat exchangers and other advanced reactor structural components. This report focuses on the creep deformation and rupture life of Grade 91 steel. The time required to complete an experiment limits the availability of long-life creep data for Grade 91 and other structural materials. Design methods often extrapolate the available shorter-term experimental data to longer design lives. However, extrapolation methods tacitly assume the underlying material mechanisms causing creep for long-life/low-stress conditions are the same as the mechanisms controlling creep in the short-life/high-stress experiments. A change in mechanism for long-term creep could cause design methods based on extrapolation to be non-conservative. The goal for physically-based microstructural models is to accurately predict material response in experimentally-inaccessible regions of design space. An accurate physically-based model for creep represents all the material mechanisms that contribute to creep deformation and damage and predicts the relative influence of each mechanism, which changes with loading conditions. Ideally, the individual mechanism models adhere to the material physics and not an empirical calibration to experimental data and so the model remains predictive for a wider range of loading conditions. This report describes such a physically-based microstructural model for Grade 91 at 600° C. The model explicitly represents competing dislocation and diffusional mechanisms in both the grain bulk and grain boundaries. The model accurately recovers the available experimental creep curves at higher stresses and the limited experimental data at lower stresses, predominately primary creep rates. The current model considers only one temperature. However, because the model parameters are, for the most part, directly related to the physics of fundamental material processes, the temperature dependence of the properties are known. Therefore, temperature dependence can be included in the model with limited additional effort. The model predicts a mechanism shift for 600° C at approximately 100 MPa from a dislocation- dominated regime at higher stress to a diffusion-dominated regime at lower stress. This mechanism shift impacts the creep life, notch-sensitivity, and, likely, creep ductility of Grade 91. In particular, the model predicts existing extrapolation methods for creep life may be non-conservative when attempting to extrapolate data for higher stress creep tests to low stress, long-life conditions. Furthermore, the model predicts a transition from notchstrengthening behavior at high stress to notch-weakening behavior at lower stresses. Both behaviors may affect the conservatism of existing design methods.

36 MATERIALS SCIENCE↗
DOE OSTI2018

Exploring the merging of the global land evaporation WACMOS-ET products based on local tower measurements

An inverse error variance weighting of the anomalies of three terrestrial evaporation (ET) products from the WACMOS-ET project based on FLUXNET sites is presented. The three ET models were run daily and at a resolution of 25 km for 2002–2007, and based on common input data when possible. The local weights, derived based on the variance of the difference between the tower ET anomalies and the modelled ET anomalies, were made dynamic by estimating them using a 61-day running window centred on each day. These were then extrapolated from the tower locations to the global landscape by regressing them on the main model inputs and derived ET using a neural network. Over the stations, the weighted scheme usefully decreased the random error component, and the weighted ET correlated better with the tower data than a simple average. The global extrapolation produced weights displaying strong seasonal and geographical patterns, which translated into spatiotemporal differences between the ET weighted and simple average ET products. However, the uncertainty of the weights after the extrapolation remained large. Out-sample prediction tests showed that the tower data set, mostly located at temperate regions, had limitations with respect to the representation of different biome and climate conditions. Therefore, even if the local weighting was successful, the extrapolation to a global scale remains problematic, showing a limited added value over the simple average. Overall, this study suggests that merging tower observations and ET products at the timescales and spatial scales of this study is complicated by the tower spatial representativeness, the products' coarse spatial resolution, the nature of the error in both towers and gridded data sets, and how all these factors affect the weights extrapolation from the tower locations to the global landscape.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2001

Genomic instability, bystander effect, cytoplasmic irradiation and other phenomena that may achieve fame without fortune

The possible risk of induced malignancies in astronauts, as a consequence of the radiation environment in space, is a factor of concern for long term missions. Cancer risk estimates for high doses of low LET radiation are available from the epidemiological studies of the A-bomb survivors. Cancer risks at lower doses cannot be detected in epidemiological studies and must be inferred by extrapolation from the high dose risks. The standard setting bodies, such as the ICRP recommend a linear, no-threshold extrapolation of risks from high to low doses, but this is controversial. A study of mechanisms of carcinogenesis may shed some light on the validity of a linear extrapolation. The multi-step nature of carcinogenesis suggests that the role of radiation may be to induce a mutation leading to a mutator phenotype. High energy Fe ions, such as those encountered in space are highly effective in inducing genomic instability. Experiments involving the single particle microbeam have demonstrated a "bystander effect", ie a biological effect in cells not themselves hit, but in close proximity to those that are, as well as the induction of mutations in cells where only the cytoplasm, and not the nucleus, have been traversed by a charged particle. These recent experiments cast doubt on the validity of a simple linear extrapolation, but the data are so far fragmentary and conflicting. More studies are necessary. While mechanistic studies cannot replace epidemiology as a source of quantitative risk estimates, they may shed some light on the shape of the dose response relationship and therefore on the limitations of a linear extrapolation to low doses.

NASA Discipline Radiation Health↗
DOE OSTI2015

THREE-DIMENSIONAL RADIO AND X-RAY MODELING AND DATA ANALYSIS SOFTWARE: REVEALING FLARE COMPLEXITY

Many problems in solar physics require analysis of imaging data obtained in multiple wavelength domains with differing spatial resolution in a framework supplied by advanced three-dimensional (3D) physical models. To facilitate this goal, we have undertaken a major enhancement of our IDL-based simulation tools developed earlier for modeling microwave and X-ray emission. The enhanced software architecture allows the user to (1) import photospheric magnetic field maps and perform magnetic field extrapolations to generate 3D magnetic field models; (2) investigate the magnetic topology by interactively creating field lines and associated flux tubes; (3) populate the flux tubes with user-defined nonuniform thermal plasma and anisotropic, nonuniform, nonthermal electron distributions; (4) investigate the spatial and spectral properties of radio and X-ray emission calculated from the model; and (5) compare the model-derived images and spectra with observational data. The package integrates shared-object libraries containing fast gyrosynchrotron emission codes, IDL-based soft and hard X-ray codes, and potential and linear force-free field extrapolation routines. The package accepts user-defined radiation and magnetic field extrapolation plug-ins. We use this tool to analyze a relatively simple single-loop flare and use the model to constrain the magnetic 3D structure and spatial distribution of the fast electrons inside this loop. We iteratively compute multi-frequency microwave and multi-energy X-ray images from realistic magnetic flux tubes obtained from pre-flare extrapolations, and compare them with imaging data obtained by SDO, NoRH, and RHESSI. We use this event to illustrate the tool's use for the general interpretation of solar flares to address disparate problems in solar physics.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2017

Casting the Coronal Magnetic Field Reconstruction Tools in 3D Using the MHD Bifrost Model

Quantifying the coronal magnetic field remains a central problem in solar physics. Nowadays, the coronal magnetic field is often modeled using nonlinear force-free field (NLFFF) reconstructions, whose accuracy has not yet been comprehensively assessed. Here we perform a detailed casting of the NLFFF reconstruction tools, such as π -disambiguation, photospheric field preprocessing, and volume reconstruction methods, using a 3D snapshot of the publicly available full-fledged radiative MHD model. Specifically, from the MHD model, we know the magnetic field vector in the entire 3D domain, which enables us to perform a “voxel-by-voxel” comparison of the restored and the true magnetic fields in the 3D model volume. Our tests show that the available π -disambiguation methods often fail in the quiet-Sun areas dominated by small-scale magnetic elements, while they work well in the active region (AR) photosphere and (even better) chromosphere. The preprocessing of the photospheric magnetic field, although it does produce a more force-free boundary condition, also results in some effective “elevation” of the magnetic field components. This “elevation” height is different for the longitudinal and transverse components, which results in a systematic error in absolute heights in the reconstructed magnetic data cube. The extrapolations performed starting from the actual AR photospheric magnetogram are free from this systematic error, while other metrics are comparable with those for extrapolations from the preprocessed magnetograms. This finding favors the use of extrapolations from the original photospheric magnetogram without preprocessing. Our tests further suggest that extrapolations from a force-free chromospheric boundary produce measurably better results than those from a photospheric boundary.

79 ASTRONOMY AND ASTROPHYSICS↗
NASA NTRS2018

Deriving Three Dimensional Reservoir Bathymetry from Multi-Satellite Datasets

We evaluate different techniques that rebuild reservoir bathymetry by combining multi-satellite imagery of surface water elevation and extent. Digital elevation models (DEMs) are processed in two distinct ways in order to determine 3-D reservoir bathymetry. They are defined as (a) linear extrapolation and (b) linear interpolation. The first one linearly extrapolates the land slope, defining the bottom as the intersection of all extrapolated lines. The second linearly interpolates the uppermost and lowermost pixels of the reservoir's main river, repeating the process for all other tributaries. A visible bathymetry, resulting from the combination of radar altimetry and water extent masks, can be coupled with the DEM, improving the accuracy of techniques (a) and (b). Envisat-and Altika-based altimetric time series is combined to a Landsat-based water extent database over the2002-2016 period in order to generate the visible bathymetry, and topography is derived from the 3-arcsecHydroSHEDS DEM. Fourteen 3-D bathymetries derived from the combination of these techniques and datasets, plus the inclusion of upstream and downstream riverbed elevations, are evaluated over Lake Mead. Accuracy is measured using ground observations, and show that metrics improve as a function of added data requirement and processing. Best bathymetry estimates are obtained when the visible bathymetry, linear extrapolation technique and riverbed elevation are combined. Water storage variability is also evaluated and shows that best results are derived from the aforementioned combination. This study contributes to our understanding and representation of reservoir water impoundment impacts on the hydrological cycle.

HydroSHEDS↗
DOE OSTI2015

Effect of spatial sampling from European flux towers for estimating carbon and water fluxes with artificial neural networks

Abstract Empirical modeling approaches are frequently used to upscale local eddy covariance observations of carbon, water, and energy fluxes to regional and global scales. The predictive capacity of such models largely depends on the data used for parameterization and identification of input‐output relationships, while prediction for conditions outside the training domain is generally uncertain. In this work, artificial neural networks (ANNs) were used for the prediction of gross primary production (GPP) and latent heat flux (LE) on local and European scales with the aim to assess the portion of uncertainties in extrapolation due to sample selection. ANNs were found to be a useful tool for GPP and LE prediction, in particular for extrapolation in time (mean absolute error MAE for GPP between 0.53 and 1.56 gC m −2 d −1 ). Extrapolation in space in similar climatic and vegetation conditions also gave good results (GPP MAE 0.7–1.41 gC m −2 d −1 ), while extrapolation in areas with different seasonal cycles and controlling factors (e.g., the tropical regions) showed noticeably higher errors (GPP MAE 0.8–2.09 gC m −2 d −1 ). The distribution and the number of sites used for ANN training had a remarkable effect on prediction uncertainty in both, regional GPP and LE budgets and their interannual variability. Results obtained show that for ANN upscaling for continents with relatively small networks of sites, the error due to the sampling can be large and needs to be considered and quantified. The analysis of the spatial variability of the uncertainty helped to identify the meteorological drivers driving the uncertainty.

Papale, Dario↗
DOE OSTI2017

Fluxes all of the time? A primer on the temporal representativeness of FLUXNET: FLUXES ALL OF THE TIME?

FLUXNET, the global network of eddy covariance flux towers, provides the largest synthesized data set of CO 2 , H 2 O, and energy fluxes. To achieve the ultimate goal of providing flux information “everywhere and all of the time,” studies have attempted to address the representativeness issue, i.e., whether measurements taken in a set of given locations and measurement periods can be extrapolated to a space- and time-explicit extent (e.g., terrestrial globe, 1982–2013 climatological baseline). This study focuses on the temporal representativeness of FLUXNET and tests whether site-specific measurement periods are sufficient to capture the natural variability of climatological and biological conditions. FLUXNET is unevenly representative across sites in terms of the measurement lengths and potentials of extrapolation in time. Similarity of driver conditions among years generally enables the extrapolation of flux information beyond measurement periods. Yet such extrapolation potentials are further constrained by site-specific variability of driver conditions. Several driver variables such as air temperature, diurnal temperature range, potential evapotranspiration, and normalized difference vegetation index had detectable trends and/or breakpoints within the baseline period, and flux measurements generally covered similar and biased conditions in those drivers. About 38% and 60% of FLUXNET sites adequately sampled the mean conditions and interannual variability of all driver conditions, respectively. For long-record sites (≥15 years) the percentages increased to 59% and 69%, respectively. However, the justification of temporal representativeness should not rely solely on the lengths of measurements. Whenever possible, site-specific consideration (e.g., trend, breakpoint, and interannual variability in drivers) should be taken into account.

58 GEOSCIENCES↗
DOE OSTI2024

Reassessment of Birch's Law on hcp‐Fe From Ultrasonic Sound Velocity Measurement and Implications on the Velocity Profiles of Earth's Inner Core

Here, we performed in situ X-ray diffraction and ultrasonic sound velocity measurements on hcp-Fe up to 15 GPa, 873 K in a multi-anvil apparatus. The elastic moduli and their pressure and temperature derivatives were determined by fitting the velocity and density data to the third-order finite strain equations, yielding K S0 = 169.0(57) GPa, K$^{′}_{S0}$ = 5.4(6), (∂K S /∂T) P = −0.031(3) GPa/K, G 0 = 104.5(27) GPa, G$^{′}_{0}$ = 1.7(2), (∂G/∂T) P = −0.060(2) GPa/K. Within the experimental P-T range, we find significant temperature effect on the density-velocity (ρ − V P or S ) relations and caution the use of the temperature-independent Birch's law for extrapolation to core conditions. Furthermore, temperature-induced velocity decrease is more significant in V S than in V P , offering a possible explanation for the high Poisson's ratio in the core. Extrapolations based on our results together with previous experimental data suggest that V P of hcp-Fe aligns with PREM at Earth's core conditions, while Vs and density are approximately 10% and 2.7% higher than PREM, respectively.

36 MATERIALS SCIENCE↗
DOE OSTI2015

Analysis of Sunyaev–Zel'dovich effect mass–observable relations using South Pole Telescope observations of an X-ray selected sample of low-mass galaxy clusters and groups

We use microwave observations from the South Pole Telescope (SPT) to examine the Sunyaev-Zel'dovich effect (SZE) signatures of a sample of 46 X-ray selected groups and clusters drawn from similar to 6 deg(2) of the XMM-Newton Blanco Cosmology Survey. These systems extend to redshift z = 1.02 and probe the SZE signal to the lowest X-ray luminosities (>= 10(42) erg s(-1)) yet; these sample characteristics make this analysis complementary to previous studies. We develop an analysis tool, using X-ray luminosity as a mass proxy, to extract selection-bias-corrected constraints on the SZE significance and Y-500 mass relations. The former is in good agreement with an extrapolation of the relation obtained from high-mass clusters. However, the latter, at low masses, while in good agreement with the extrapolation from the high-mass SPT clusters, is in tension at 2.8 sigma with the Planck constraints, indicating the low-mass systems exhibit lower SZE signatures in the SPT data. We also present an analysis of potential sources of contamination. For the radio galaxy point source population, we find 18 of our systems have 843 MHz Sydney University Molonglo Sky Survey sources within 2 arcmin of the X-ray centre, and three of these are also detected at significance >4 by SPT. Of these three, two are associated with the group brightest cluster galaxies, and the third is likely an unassociated quasar candidate. We examine the impact of these point sources on our SZE scaling relation analyses and find no evidence of biases. We also examine the impact of dusty galaxies using constraints from the 220 GHz data. The stacked sample provides 2.8 sigma significant evidence of dusty galaxy flux, which would correspond to an average underestimate of the SPT Y-500 signal that is (17 +/- 9) per cent in this sample of low-mass systems. Finally, we explore the impact of future data from SPTpol and XMM-XXL, showing that it will lead to a factor of 4 to 5 tighter constraints on these SZE mass-observable relations.

Liu, J.↗
DOE OSTI2020

Quantified limits of the nuclear landscape

The chart of the nuclides is limited by particle drip lines beyond which nuclear stability to proton or neutron emission is lost. Predicting the range of particle-bound isotopes poses an appreciable challenge for nuclear theory as it involves extreme extrapolations of nuclear masses well beyond the regions where experimental information is available. Still, quantified extrapolations are crucial for a wide variety of applications, including the modeling of stellar nucleosynthesis. We use microscopic nuclear global mass models, current mass data, and Bayesian methodology to provide quantified predictions of proton and neutron separation energies as well as Bayesian probabilities of existence throughout the nuclear landscape all the way to the particle drip lines. Here, we apply nuclear density functional theory with several energy density functionals. We also consider two global mass models often used in astrophysical nucleosynthesis simulations. To account for uncertainties, Bayesian Gaussian processes are trained on the separation-energy residuals for each individual model, and the resulting predictions are combined via Bayesian model averaging. This framework allows to account for systematic and statistical uncertainties and propagate them to extrapolative predictions. We establish and characterize the drip-line regions where the probability that the nucleus is particle- bound decreases from 1 to 0. In these regions, we provide quantified predictions for one- and two-nucleon separation energies. According to our Bayesian model averaging analysis, 7759 nuclei with Z ≤ 119 have a probability of existence ≥ 0.5. The extrapolation results obtained in this study will be put through stringent tests when new experimental information on existence and masses of exotic nuclei becomes available. In this respect, the quantified landscape of nuclear existence obtained in this study should be viewed as a dynamical prediction that will be fine-tuned when new experimental information and improved global mass models become available.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2015

B -meson decay constants from 2 + 1 -flavor lattice QCD with domain-wall light quarks and relativistic heavy quarks

We calculate the B-meson decay constants f B , f B s , and their ratio in unquenched lattice QCD using domain-wall light quarks and relativistic b quarks. We use gauge-field ensembles generated by the RBC and UKQCD collaborations using the domain-wall fermion action and Iwasaki gauge action with three flavors of light dynamical quarks. We analyze data at two lattice spacings of a ≈ 0.11, 0.086 fm with unitary pion masses as light as M π ≈ 290 MeV; this enables us to control the extrapolation to the physical light-quark masses and continuum. For the b quarks we use the anisotropic clover action with the relativistic heavy-quark interpretation, such that discretization errors from the heavy-quark action are of the same size as from the light-quark sector. We renormalize the lattice heavy-light axial-vector current using a mostly nonperturbative method in which we compute the bulk of the matching factor nonperturbatively, with a small correction, that is close to unity, in lattice perturbation theory. We also improve the lattice heavy-light current through O(α s a). We extrapolate our results to the physical light-quark masses and continuum using SU(2) heavy-meson chiral perturbation theory, and provide a complete systematic error budget. We obtain f B 0 = 199.5(12.6) MeV, f B + =195.6(14.9) MeV, f B s =235.4(12.2) MeV, f B s /f B 0 =1.197(50), and f B s /f B + =1.223(71), where the errors are statistical and total systematic added in quadrature. Finally, these results are in good agreement with other published results and provide an important independent cross-check of other three-flavor determinations of B-meson decay constants using staggered light quarks.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2017

Robust approaches to quantification of margin and uncertainty for sparse data

Characterizing the tails of probability distributions plays a key role in quantification of margins and uncertainties (QMU), where the goal is characterization of low probability, high consequence events based on continuous measures of performance. When data are collected using physical experimentation, probability distributions are typically fit using statistical methods based on the collected data, and these parametric distributional assumptions are often used to extrapolate about the extreme tail behavior of the underlying probability distribution. In this project, we character- ize the risk associated with such tail extrapolation. Specifically, we conducted a scaling study to demonstrate the large magnitude of the risk; then, we developed new methods for communicat- ing risk associated with tail extrapolation from unvalidated statistical models; lastly, we proposed a Bayesian data-integration framework to mitigate tail extrapolation risk through integrating ad- ditional information. We conclude that decision-making using QMU is a complex process that cannot be achieved using statistical analyses alone.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2015

Challenges of accelerated aging techniques for elastomer lifetime predictions

Elastomers are often degraded when exposed to air or high humidity for extended times (years to decades). Lifetime estimates normally involve extrapolating accelerated aging results made at higher than ambient environments. Several potential problems associated with such studies are reviewed, and experimental and theoretical methods to address them are provided. The importance of verifying time–temperature superposition of degradation data is emphasized as evidence that the overall nature of the degradation process remains unchanged versus acceleration temperature. The confounding effects that occur when diffusion-limited oxidation (DLO) contributes under accelerated conditions are described, and it is shown that the DLO magnitude can be modeled by measurements or estimates of the oxygen permeability coefficient (P Ox ) and oxygen consumption rate (Φ). P Ox and Φ measurements can be influenced by DLO, and it is demonstrated how confident values can be derived. In addition, several experimental profiling techniques that screen for DLO effects are discussed. Values of Φ taken from high temperature to temperatures approaching ambient can be used to more confidently extrapolate accelerated aging results for air-aged materials, and many studies now show that Arrhenius extrapolations bend to lower activation energies as aging temperatures are lowered. Furthermore, best approaches for accelerated aging extrapolations of humidity-exposed materials are also offered.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
NASA NTRS1991

Sonic boom predictions for three generic models using a solution-adaptive full-potential code

The TranAir full-potential code, which utilizes a solution-adaptive, unstructured Cartesian grid, was used to compute near-field pressure signatures of three generic supersonic configurations: a cone-cylinder, a low aspect ratio rectangular wing, and a delta-wing/body. TranAir pressure signatures are extrapolated to near- and mid-field distances using a quasi-linear extrapolation technique. Results are compared with existing wind tunnel data and, where possible, with extrapolated experimental data and quasi-linear Whitham-method results. In general, the extrapolated TranAir data is in good agreement with experimental and Whitham-method pressure signatures, but peak pressures are slightly under-predicted. It is thought that computed data obtained too near to the model was the main reason for the discrepancies. Flow-field grid structure was also found to be important in obtaining accurate offbody data.

Madson, Michael D.↗