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NASA NTRS1990

Design of ceramic components with the NASA/CARES computer program

The ceramics analysis and reliability evaluation of structures (CARES) computer program is described. The primary function of the code is to calculate the fast-fracture reliability or failure probability of macro-scopically isotropic ceramic components. These components may be subjected to complex thermomechanical loadings, such as those found in heat engine applications. CARES uses results from MSC/NASTRAN or ANSYS finite-element analysis programs to evaluate how inherent surface and/or volume type flaws component reliability. CARES utilizes the Batdorf model and the two-parameter Weibull cumulative distribution function to describe the effects of multiaxial stress states on material strength. The principle of independent action (PIA) and the Weibull normal stress averaging models are also included. Weibull material strength parameters, the Batdorf crack density coefficient, and other related statistical quantities are estimated from four-point bend bar or uniform uniaxial tensile specimen fracture strength data. Parameter estimation can be performed for a single or multiple failure modes by using a least-squares analysis or a maximum likelihood method. Kolmogorov-Smirnov and Anderson-Darling goodness-to-fit-tests, 90 percent confidence intervals on the Weibull parameters, and Kanofsky-Srinivasan 90 percent confidence band values are also provided. Examples are provided to illustrate the various features of CARES.

Nemeth, Noel N.↗

NASA NTRS1990

Ceramics Analysis and Reliability Evaluation of Structures (CARES). Users and programmers manual

This manual describes how to use the Ceramics Analysis and Reliability Evaluation of Structures (CARES) computer program. The primary function of the code is to calculate the fast fracture reliability or failure probability of macroscopically isotropic ceramic components. These components may be subjected to complex thermomechanical loadings, such as those found in heat engine applications. The program uses results from MSC/NASTRAN or ANSYS finite element analysis programs to evaluate component reliability due to inherent surface and/or volume type flaws. CARES utilizes the Batdorf model and the two-parameter Weibull cumulative distribution function to describe the effect of multiaxial stress states on material strength. The principle of independent action (PIA) and the Weibull normal stress averaging models are also included. Weibull material strength parameters, the Batdorf crack density coefficient, and other related statistical quantities are estimated from four-point bend bar or unifrom uniaxial tensile specimen fracture strength data. Parameter estimation can be performed for single or multiple failure modes by using the least-square analysis or the maximum likelihood method. Kolmogorov-Smirnov and Anderson-Darling goodness-of-fit tests, ninety percent confidence intervals on the Weibull parameters, and Kanofsky-Srinivasan ninety percent confidence band values are also provided. The probabilistic fast-fracture theories used in CARES, along with the input and output for CARES, are described. Example problems to demonstrate various feature of the program are also included. This manual describes the MSC/NASTRAN version of the CARES program.

Nemeth, Noel N.↗

NASA NTRS1994

Comparison of plate and asthenospheric flow models for the thermal evolution of oceanic lithosphere

Although seafloor depth and heat flow for young oceanic lithosphere can be descibed by modeling the lithosphere as the boundary layer of a cooling halfspace, a long standing question has been why data at older ages deviate from those expected for a halfspace. Two classes of models have been proposed for these deviations. In one, heat added from below 'flattens' depth and heat flow. In the other, asthenospheric flow beneath the lithosphere perturbs the depths. We compare recent versions of the model classes: the GDH1 thin-lithosphere plate model (Stein and Stein, 1992) and an asthenospehric flow model (Phipps Morgan and Smith, 1992). The plate model fits heat flow data better than the flow model for all cases considered, and topographic data in all but one case. The flow model significantly overpredicts depths for the North Atlantic, because the assumed asthenospheric flow in the plate motion direction would yield deepening for old ages rather than the observed flattening. Overall, the GDH1 global average model does better than this flow model, whose parameters were fit to specific plates. Moreover, the plate models fit to specific plates do better than the flow model. Plate models thus appear more useful than this flow model, suggesting that deviations from a cooling halfspace are largely thermal in origin.

Stein, Carol A.↗

DOE OSTI2024

Neutrinoless Double-Beta Decay Investigations of 82Se Using Three Shell Model Hamiltonians

Neutrinoless double-beta decay is considered one of the most promising processes that would help clarify some of the symmetry-breaking problems in our understanding of the observable universe. Recent studies of neutrinoless double-beta decay matrix elements have employed statistical approaches based on modified shell model effective Hamiltonians for 48Ca (Phys. Rev. C 106, 054302 (2022)) and 136Xe (Phys. Rev. C 107, 045501 (2023)). The analyses rely on inducing perturbations in the starting effective Hamiltonians to observe the behavior of a wide range of observables, besides the 0νββ) NME, that are compared with experimental data. Following a Bayesian model averaging approach, the range of probable values for the neutrinoless double-beta decay matrix elements is presented. In this paper, we present a similar study for 82Se, which is described in the same model space as 76Ge that is under experimental observation. Due to its faster calculation time compared to 76Ge, 82Se can be used as an appropriate substitute in our complex statistical study. Using the calculations performed for the statistical analysis of the neutrinoless double-beta decay matrix elements, we also search for the correlations between the observables that we can compare to experimental data.

Science & Technology - Other Topics↗

NASA NTRS1979

Elementary analytic models of climate. 1: The mean global heat balance

Climate models based on global radiative equilibrium are normally so complicated that they require extensive computer codes to provide adequate accuracy. However, by simply modifying the concept of a gray atmosphere, a reasonably correct mean global temperature is obtained. This elementary model is then used to estimate the effects of changes in the abundances of minor infrared absorbers and changes in the solar constant or earth albedo. When applied to a Budyko-Sellers zonally averaged model, the quasi-gray model could give a physical basis for the latitude dependence of outgoing radiation and of opacity due to H2O vapor content. The latter effect constitutes an important positive feedback on surface temperature.

Chamberlain, J. W.↗

NASA NTRS1991

The geomagnetic tail

A review is presented of the plasma sheet and lobe regions of the magnetotail, focusing principally on large-scale processes or microprocesses with some large-scale effects. Consideration is given to quiet and average structures, not necessarily related to activity phases, with quasi-steady convection aspects, and with the characteristics of dynamic phases including acceleration mechanisms and single particle aspects. Attention is given to various activity models, average and quiet time properties, properties and effects of magnetospheric convection, dynamics of the magnetotail, and the near tail, substorm current wedge.

Birn, Joachim↗

NASA NTRS2019

Assimilation of Satellite Soil Moisture for Improved Atmospheric Reanalyses

A newly developed, weakly coupled land and atmosphere data assimilation system for NASA’s Global Earth Observing System model is presented, and used to demonstrate the benefit of assimilating satellite soil moisture into an atmospheric reanalysis. Specifically, Advanced Scatterometer and Soil Moisture Ocean Salinity soil moisture retrievals are assimilated into a system that uses the same model, atmospheric assimilation system, and atmospheric observations as the Modern-Era Retrospective analysis for Research and Applications, version 2 (MERRA-2). The atmosphere is sensitive to soil moisture only under certain conditions. Hence, while the globally averaged model improvements were small, regionally, the soil moisture assimilation induced some substantial improvements. For example, in a large region spanning from western Europe across southern Russia, the soil moisture assimilation decreased the RMSE against independent station observations of daily maximum 2-m temperature (T(sup 2m, sub max)) by up to 0.4 K, and of 2-m specific humidity (q(exp 2m)) by up to 0.5 g/kg. Over all available stations, the mean T(sup 2m, sub max) RMSE was reduced from 2.82 to 2.79 K, while the mean q(exp 2m) RMSE was reduced from 1.25 to 1.20 g/kg. The soil moisture assimilation also reduced the mean RMSE across 29 flux tower sites from 34.2 to 32.6 Wm(exp −2) for latent heating, and from 37.7 to 36.5 Wm(exp −2) for sensible heating. For all variables evaluated, the soil moisture assimilation improved the model at monthly to seasonal, rather than daily, time scales. Based on the above experiments, it is recommended that satellite soil moisture be assimilated into future reanalyses, including the follow-on to MERRA-2.

Clara Draper↗

NASA NTRS2013

Analysis of Present Day and Future OH and Methane Lifetime in the ACCMIP Simulations

Results from simulations performed for the Atmospheric Chemistry and Climate Modeling Intercomparison Project (ACCMIP) are analysed to examine how OH and methane lifetime may change from present day to the future, under different climate and emissions scenarios. Present day (2000) mean tropospheric chemical lifetime derived from the ACCMIP multi-model mean is 9.8+/-1.6 yr (9.3+/-0.9 yr when only including selected models), lower than a recent observationally-based estimate, but with a similar range to previous multi-model estimates. Future model projections are based on the four Representative Concentration Pathways (RCPs), and the results also exhibit a large range. Decreases in global methane lifetime of 4.5 +/- 9.1% are simulated for the scenario with lowest radiative forcing by 2100 (RCP 2.6), while increases of 8.5+/-10.4% are simulated for the scenario with highest radiative forcing (RCP 8.5). In this scenario, the key driver of the evolution of OH and methane lifetime is methane itself, since its concentration more than doubles by 2100 and it consumes much of the OH that exists in the troposphere. Stratospheric ozone recovery, which drives tropospheric OH decreases through photolysis modifications, also plays a partial role. In the other scenarios, where methane changes are less drastic, the interplay between various competing drivers leads to smaller and more diverse OH and methane lifetime responses, which are difficult to attribute. For all scenarios, regional OH changes are even more variable, with the most robust feature being the large decreases over the remote oceans in RCP8.5. Through a regression analysis, we suggest that differences in emissions of non-methane volatile organic compounds and in the simulation of photolysis rates may be the main factors causing the differences in simulated present day OH and methane lifetime. Diversity in predicted changes between present day and future OH was found to be associated more strongly with differences in modelled temperature and stratospheric ozone changes. Finally, through perturbation experiments we calculated an OH feedback factor (F) of 1.24 from present day conditions (1.50 from 2100 RCP8.5 conditions) and a climate feedback on methane lifetime of 0.33+-0.13 yr/K, on average. Models that did not include interactive stratospheric ozone effects on photolysis showed a stronger sensitivity to climate, as they did not account for negative effects of climate-driven stratospheric ozone recovery on tropospheric OH, which would have partly offset the overall OH/methane lifetime response to climate change.

atmospheric composition↗

DOE OSTI2021

Interplay Between Crustal‐Scale Thrusting, High Metamorphic Heating Rates, and the Development of Inverted Thermal‐Metamorphic Gradients: Numerical Models and Examples From the Caledonides of Northern Scotland

Abstract Understanding the processes that produce high prograde metamorphic heating rates and the development of inverted metamorphic sequences in collisional thrust belts remains a fundamental challenge for tectonics and metamorphic petrology. New 2D finite element models of crustal‐scale thrusts with variable slip rates (10, 20, 35, 50 km Myr −1 ) are used to examine how thrust sheet emplacement contributes to these processes. In the models, average prograde heating rates of 31–118 °C Myr −1 are observed in the footwall, with maximum transient heating rates of ∼167 °C Myr −1 occurring at the highest slip rate. Also, thrust sheet emplacement produces an inverted thermal gradient in the model footwall. At slip rates of 10 km Myr −1 , heating magnitudes >200 °C are observed >7 km structurally beneath the thrust plane. At slip rates of 20–50 km Myr −1 , models produce thermal penetration depths of 4–5 km for similar heating magnitudes. Petrologically determined heating rates for thrust footwalls in the Scandian orogenic wedge of northern Scotland mostly yield rates consistent with model results (10–230 °C Myr −1 ). The model‐derived magnitude of inverted thermal gradients is also similar to those indicated in texturally determined deformation temperature transects across the Scandian orogenic wedge (100 °C–180 °C). Combined, these results indicate that high heating rates can be produced by fault slip at typical plate velocities. Additionally, this implies that crustal‐scale thrusts are likely to produce inverted metamorphic sequences in most systems, provided that P‐T conditions during slip allow for metamorphic or recrystallization processes that would preserve evidence for such features.

Thigpen, J. Ryan↗

NASA NTRS1989

Report on the 2-D Model Intercomparison Workshop held January 11-16, 1987 in Fort Myers Beach, Florida, chapter 2

In the attempts to understand the processes which affect ozone in the stratosphere, and to predict future ozone levels, a variety of computer models were developed and employed. To oversimplify somewhat, the models range from 1-D models with intricately detailed photochemistry but only the crudest representation of transport, to 3-D general circulation models with intricately detailed dynamics and no photochemistry at all. Each of these has its appropriate uses. It was felt that there was much to be gained from intermediate models incorporating an extensive treatment of photochemistry with a dynamical framework which at least recognizes that atmospheric motions are advective as well as diffusive, and that both chemistry and dynamics are subject to latitudinal and seasonal variations. Thus the 2-D, zonally averaged models have begun to play a larger role in the last seven years, both in attempting to understand observed distributions of trace species and in attempting to assess the probable effects of antropogenic perturbations. There are many choices to be made in developing the model. It was the purpose of the 2-D model Intercomparison Workshop to permit discussion of the choices made and the behavior of the resulting models. The goal was not to identify a best set of choices, but rather to identify areas in which the models are sensitive to the choices made, and to develop a sense of where these models as a class do well or poorly in simulating the observed atmosphere.

Guthrie, Paul D.↗

NASA NTRS1983

Infrared limb-darkening effects for the earth-atmosphere system

An infrared radiative transfer model has been developed for evaluating anisotropic functions in the longwave region (5-50 microns) due to limb-darkening effects in the earth's atmosphere. An accurate narrow-band model of absorption has been used for computing transmission functions of the atmosphere. Absorption due to all major and minor atmospheric constituents has been taken into account including the continuum absorption due to water vapor. Anisotropic functions have been calculated for several latitudinal and seasonal climatological-average model atmospheres. The effects of the variability of various meteorological parameters, e.g. surface temperature, surface relative humidity, and cloud-top height have been examined. It has been found that the variability of cloud parameters has the largest effect on the infrared anisotropic functions.

Gupta, S. K.↗

DOE OSTI2020

Influence of Time and Frequency Domain Wave Forcing on the Power Estimation of a Wave Energy Converter Array

Industry-specific tools for analyzing and optimizing the design of wave energy converters (WECs) and associated power systems are essential to advancing marine renewable energy. This study aims to quantify the influence of phase information on the device power output of a virtual WEC array. We run the phase-resolving wave model FUNWAVE-TVD (Total Variation Diminishing) to generate directional waves at the PacWave South site offshore from Newport, Oregon, where future WECs are expected to be installed for testing. The two broad cases presented correspond to mean wave climates during warm months (March–August) and cold months (September–February). FUNWAVE-TVD time series of sea-surface elevation are then used in WEC-Sim, a time domain numerical model, to simulate the hydrodynamic response of each device in the array and estimate their power output. For comparison, WEC-Sim is also run with wave energy spectra calculated from the FUNWAVE-TVD simulations, which do not retain phase information, and with wave spectra computed using the phase-averaged model Simulating WAves Nearshore (SWAN). The use of spectral data in WEC-Sim requires a conversion from frequency to time domain by means of random superposition of wave components, which are not necessarily consistent because of the linear assumption implicit in this method. Thus, power response is characterized by multiple realizations of the wave climates.

13 HYDRO ENERGY↗

NASA NTRS2021

Evaluation of Clouds, Radiation, and Precipitation in CMIP6 Models Using Global Weather States Derived from ISCCP-H Cloud Property Data

A clustering methodology is applied to cloud optical depth cloud top pressure (TAU-PC) histograms from the new, 1-degree resolution, ISCCP-H dataset, to derive an updated global Weather State (WS) dataset. Then, PC-TAU histograms from current-climate CMIP6 model simulations are assigned to the ISCCP-H WSs along with their concurrent radiation and precipitation properties, to evaluate model cloud, radiation, and precipitation properties in the context of the Weather States. The new ISCCP-H analysis produces WSs that are very similar to those previously found in the lower resolution ISCCP-D dataset. The main difference lies in the splitting of the ISCCP-D thin stratocumulus WS between the ISCCP-H shallow cumulus and stratocumulus WSs, which results in the reduction by one of the total WS number. The evaluation of the CMIP6 models against the ISCCP-H Weather States, shows that, in the ensemble mean, the models are producing an adequate representation of the frequency and geographical distribution of the WSs, with measurable improvements compared to the WSs derived for the CMIP5 ensemble. However, the frequency of shallow cumulus clouds continues to be underestimated, and, in some WSs the good agreement of the ensemble mean with observations comes from averaging models that significantly overpredict and underpredict the ISCCP-H WS frequency. In addition, significant biases exist in the internal cloud properties of the model WSs, such as the model underestimation of cloud fraction in middle-top clouds and secondarily in midlatitude storm and stratocumulus clouds, that result in an underestimation of cloud SW cooling in those regimes.

Clouds↗

NASA NTRS2022

Unique Observational Constraints on the Seasonal and Longitudinal Variability of the Earth’s Planetary Albedo and Cloud Distribution Inferred From EPIC Measurements

Thorough comparison to observations is key to developing a credible climate model forecasting capability. Deep Space Climate Observatory (DSCOVR) measurements of Earth’s reflected solar and emitted thermal radiation provide a unique observational perspective that permits a more reliable model/data comparison than is possible with the otherwise available satellite data. The uniqueness is in the DSCOVR satellite’s viewing geometry, which enables continuous viewing of the Earth’s sunlit hemisphere from its Lissajous orbit around the Lagrangian L1 point. The key instrument is the Earth Polychromatic Imaging Camera (EPIC), which views the Earth’s sunlit hemisphere with 1024-by-1024-pixel imagery in 10 narrow spectral bands from 317 to 780 nm, acquiring up to 22 high spatial resolution images per day. The additional feature is that the frequency of EPIC image acquisition is nearly identical to that of the climate GCM data generation scheme where climate data for the entire globe are ‘instantaneously’ calculated at 1-h radiation time-step intervals. Implementation of the SHS (Sunlit Hemisphere Sampling) EPIC-view geometry for the in-line GCM output data sampling establishes a precise self-consistency in the space-time data sampling between EPIC observational and GCM output data generation and sampling. The remaining problem is that the GCM generated data are radiative fluxes, while the EPIC measurements are backscatter-dependent radiances. Radiance to flux conversion is a complex problem with no simple way to convert GCM radiative fluxes into spectral radiances. The more expedient approach is to convert the EPIC spectral radiances into broadband radiances by MODIS/CERES-based regression relationships and then into solar radiative fluxes using the CERES angular distribution models. Averaging over the sunlit hemisphere suppresses the meteorological weather noise, but preserves the intra-seasonal larger scale variability. Longitudinal slicing by the Earth’s rotation permits a self-consistent model/data comparison of the longitudinal model/data differences in the variability of the reflected solar radiation. Ancillary EPIC Composite data provide additional cloud property information for climate model diagnostics. Comparison of EPIC-derived seasonal and longitudinal variability of the Earth’s planetary albedo with the GISS ModelE2 results shows systematic overestimate of cloud reflectivity over the Pacific Ocean with corresponding underestimates over continental land areas.

DSCOVR↗

DOE OSTI2022

Reconstructing High Resolution ESM Data Through a Novel Fast Super Resolution Convolutional Neural Network (FSRCNN)

In this work, we present the first application of a fast super resolution convolutional neural network (FSRCNN) based approach for downscaling earth system model (ESM) simulations. Unlike other SR approaches, FSRCNN uses the same input feature dimensions as the low resolution input. This allows it to have smaller convolution layers, avoiding over-smoothing, and reducing computational costs. We adapt the FSRCNN to improve reconstruction on ESM data, we term the FSRCNN-ESM. We use high-resolution (~0.25°) monthly averaged model output of five surface variables over North America from the US Department of Energy's Energy Exascale Earth System Model's control simulation. These high-resolution and corresponding coarsened low-resolution (~1°) pairs of images are used to train the FSRCNN-ESM and evaluate its use as a downscaling approach. We find that FSRCNN-ESM outperforms FSRCNN and other super-resolution methods in reconstructing high resolution images producing finer spatial scale features with better accuracy for surface temperature, surface radiative fluxes, and precipitation.

58 GEOSCIENCES↗

DOE OSTI2026

$Ξ$ 𝑏 → $Ξ$ form factors from lattice QCD and standard-model predictions for $Ξ$ 𝑏 → $Ξ$⁢𝜇 + ⁢𝜇 − and $Ξ$ 𝑏 → $Ξ$⁢𝛾 decays

We present the first lattice QCD determination of the $Ξ$ 𝑏 → $Ξ$ vector, axial-vector, and tensor form factors, which are relevant for the theory of rare decays including $Ξ$ 𝑏 → $Ξ$⁢ℓ + ⁢ℓ − and $Ξ$ 𝑏 → $Ξ$⁢𝛾. The calculation is performed with 2+1 flavors of domain-wall fermions at three different lattice spacings and pion masses in the range from approximately 430 to 230 MeV. The bottom quark is implemented using an anisotropic clover action. Three-point functions with a wide range of source-sink separations and model averaging are used to extract the ground-state contributions. We fit the dependence of the form factors on the momentum transfer, the pion mass, and the lattice spacing using modified 𝑧 expansions that account for subthreshold branch cuts, and apply dispersive bounds and asymptotic behavior constraints to achieve controlled uncertainties in the full semileptonic kinematic region. Using our form factor results, we present standard model predictions for the $Ξ$$^{−}_{𝑏}$ → $Ξ$ − ⁢𝛾 and $Ξ$$^{−}_{𝑏}$ → $Ξ$ − ⁢𝜇 + ⁢𝜇 − branching fractions and two angular observables.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

NASA NTRS2004

Error Modeling of Multi-baseline Optical Truss: Application to SIM Metrology Truss Field Dependent Error - Part II

The current design of the Space Interferometry Mission (SIM) employs a 19 laser-metrology-beam system (also called L19 external metrology truss) to monitor changes of distances between the fiducials of the flight system's multiple baselines. The function of the external metrology truss is to aid in the determination of the time-variations of the interferometer baseline. The largest contributor to truss error occurs in SIM wide-angle observations when the articulation of the siderostat mirrors (in order to gather starlight from different sky coordinates) brings to light systematic errors due to offsets at levels of instrument components (which include comer cube retro-reflectors, etc.). This error is labeled external metrology wide-angle field-dependent error. Physics-based model of field-dependent error at single metrology gauge level is developed and linearly propagated to errors in interferometer delay. In this manner delay error sensitivity to various error parameters or their combination can be studied using eigenvalue/eigenvector analysis. Also validation of physics-based field-dependent model on SIM testbed lends support to the present approach. As a first example, dihedral error model is developed for the comer cubes (CC) attached to the siderostat mirrors. Then the delay errors due to this effect can be characterized using the eigenvectors of composite CC dihedral error. The essence of the linear error model is contained in an error-mapping matrix. A corresponding Zernike component matrix approach is developed in parallel, first for convenience of describing the RMS of errors across the field-of-regard (FOR), and second for convenience of combining with additional models. Average and worst case residual errors are computed when various orders of field-dependent terms are removed from the delay error. Results of the residual errors are important in arriving at external metrology system component requirements. Double CCs with ideally co-incident vertices reside with the siderostat. The non-common vertex error (NCVE) is treated as a second example. Finally combination of models, and various other errors are discussed.

comer cube retro-reflector↗

NASA NTRS1982

A heuristic mathematical model for the dynamics of sensory conflict and motion sickness

The etiology of motion sickness is now usually explained in terms of a qualitatively formulated sensory conflict hypothesis. By consideration of the information processing task faced by the central nervous system in estimating body spatial orientation and in controlling active body movement using an internal model referenced control strategy, a mathematical model for sensory conflict generation is developed. The model postulates a major dynamic functional role for sensory conflict signals in movement control, as well as in sensory motor adaptation. It accounts for the role of active movement in creating motion sickness symptoms in some experimental circumstances, and in alleviating them in others. The relationship between motion sickness produced by sensory rearrangement and that resulting from external motion disturbances is explicitly defined. A nonlinear conflict averaging model describes dynamic aspects of experimentally observed subjective discomfort sensation, and suggests resulting behavior.

Oman, C. M.↗