Interdisciplinary research in theoretical chemistry
University of Wisconsin Theoretical Chemistry Institute research program - quantum mechanics, statistical mechanics, biochemistry, numerical analysis, and electromagnetic theory
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Results for “statistical physics”
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.
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Results of the joint NASA/NOAA AMTS/HIRS2 sounding simulation test
The relative accuracies of atmospheric temperature profiles retrieved from HIRS2, the current operational infra-red temperature sounder, and AMTS, a proposed advanced high-spectral resolution infra-red sounder were compared. The sounding simulation test compared retrievals generated by GLAS, using their physical retrieval algorithm, and NESDIS, using their operational statistical regression algorithm, for both instruments under clear and cloudy conditions. Test results for both conditions are summarized in tables showing RMS temperature errors for 18 tropospheric layers, 4 stratospheric layers, and surface skin temperature. The improvement of the AMTS instrument over HIRS2, particularly for cloudy conditions is demonstrated. The GLAS retrievals are more accurate than the operational NESDIS retrieval, especially with increasing cloud cover.
Susskind, J.↗
NOAA/NASA Joint Simulation of AMTS and HIRS
Sounding simulation test was designed to compare the relative accuracies of atmospheric temperature profiles retrieved from HIRS2, the current operational infrared temperature sounder, and AMTS, a proposed advanced high spectral resolution infrared sounder. Retrievals generated by GLAS, using their physical retrieval algorithm, and NESDIS, using their operational statistical regression algorithm, for both instruments under clear and cloudy conditions were compared. In the cloudy portion of the test, MSU data, corresponding to the microwave component of the current operational sounding system, was used in conjunction with both instruments to aid in cloud seeding.
Susskind, J.↗
Large eddy simulations and direct numerical simulations of high speed turbulent reacting flows
The basic objective of this research is to extend the capabilities of Large Eddy Simulations (LES) and Direct Numerical Simulations (DNS) for the computational analyses of high speed reacting flows. In the efforts related to LES, we were primarily involved with assessing the performance of the various modern methods based on the Probability Density Function (PDF) methods for providing closures for treating the subgrid fluctuation correlations of scalar quantities in reacting turbulent flows. In the work on DNS, we concentrated on understanding some of the relevant physics of compressible reacting flows by means of statistical analysis of the data generated by DNS of such flows. In the research conducted in the second year of this program, our efforts focused on the modeling of homogeneous compressible turbulent flows by PDF methods, and on DNS of non-equilibrium reacting high speed mixing layers. Some preliminary work is also in progress on PDF modeling of shear flows, and also on LES of such flows.
Givi, P.↗
Capella: Structure and Abundances
This grant covers the analysis of EUVE spectra of the cool star binary system Capella. This project has also required the analysis of simultaneous Advanced Satellite for Cosmology and Astrophysics (ASCA) data. The ASCA spectrum of Capella could not be fit with standard models; by imposing models based on strong lines observed with EUVE, a problem wavelength region was identified. Correcting the problem required calculations of atomic collision strengths of higher principal quantum number than had ever been calculated. With these new models applied to the ASCA spectrum, better fits were obtained. Findings are that: (1) ASCA and EUVE spectra are both dominated by a region at 6 x 10(exp 6) K. (2) The high energy cut-off of the ASCA spectrum is consistent with emission from the highest ionization stages of EUVE, namely Fe XXIV. (3) EUVE requires a continuous emission measure distribution with more than two temperatures. (4) The ASCA spectra are of such high statistical significance that systematic uncertainties dominate, including atomic physics issues and calibration issues. (5) While the ASCA spectral fits achieve lower Chi(exp 2 with two-temperature fits, the EUVE-derived emission measure distribution models are also consistent with the spectra. (6) The Fe/H ratio obtained from the ASCA fit is within 20 % of the Fe/H abundance obtained from the summed spectra of Capella over 5 EUVE pointings, as well as the 1996 EUVE data. This result confirms our claims that quasi-continua composed of weak emission lines in the short wavelength spectrometer of EUVE are not major contributors to the measured Capella continuum. Other abundance ratios are also determined from the ASCA data, using models derived with EUVE. Si, Si, and Mg appear to be close to solar photospheric values, while the ratio of Ne/Fe is three to four times lower than solar photospheric values. Whether there is a general First Ionization Potential (FIP) effect or a specific neon anomaly cannot be determined from these data. (8) EUVE line ratios indicating low optical depth place limits on the extent to which the X-ray lines are optically, thick. While the brightest lines may be marginally thick, the ASCA spectrum is not of sufficient resolution to determine the optical depth in these lines.
Brickhouse, Nancy S.↗
Direct Numerical Simulation of Supersonic Turbulent Boundary Layers
The talk will present some initial results from the direct numerical simulation (DNS) of compressible turbulent boundary layers. We solve numerically the compressible Navier-Stokes equations using a method based on Spalart's transformation for the incompressible turbulent boundary layer. This allows the spatially developing boundary layer to be transformed to a calculation with periodic boundary conditions in the streamwise and spanwise directions. The equations are solved using Fourier expansions in the horizontal directions and B-splines in the wall-normal direction. The first simulation is at Mach 2.5 with a momentum thickness Reynolds number based on wall viscosity of R(sub theta(sup 1)) = 825. We are examining the physics of the compressible boundary layer using turbulence statistics and budget equations. The turbulence statistics include: rms (root mean square) and mean profiles, energy spectra, and two-point correlations. It is found that there are large density gradients which require significantly more resolution than the incompressible case.
Guarini, Stephen↗
Spatial Distribution of Large Cloud Drops
By analyzing aircraft measurements of individual drop sizes in clouds, we have shown in a companion paper (Knyazikhin et al., 2004) that the probability of finding a drop of radius r at a linear scale l decreases as l(sup D(r)) where 0 less than or equal to D(r) less than or equal to 1. This paper shows striking examples of the spatial distribution of large cloud drops using models that simulate the observed power laws. In contrast to currently used models that assume homogeneity and therefore a Poisson distribution of cloud drops, these models show strong drop clustering, the more so the larger the drops. The degree of clustering is determined by the observed exponents D(r). The strong clustering of large drops arises naturally from the observed power-law statistics. This clustering has vital consequences for rain physics explaining how rain can form so fast. It also helps explain why remotely sensed cloud drop size is generally biased and why clouds absorb more sunlight than conventional radiative transfer models predict.
Marshak, A.↗
Spatial Distribution of Large Cloud Drops
The analysis of aircraft measurements of individual drop sizes in clouds suggests that for sufficiently small volumes the mean number of cloud drops with a given radius is proportional to volume powered by a drop-size dependent exponent. For abundant small drops present, the exponent is 1 as assumed in conventional approach. However, for rarer large drops, the exponents fall below unity. We show striking examples of the spatial distribution of large cloud drops using models that simulate the observed power laws. In contrast to currently used models that assume homogeneity and therefore a Poisson distribution of cloud drops, these models show strong drop clustering, the more so the larger the drops. The degree of clustering is determined by the observed exponents. The strong clustering of large drops arises naturally from the observed power-law statistics. This clustering has vital consequences for rain physics explaining how rain can form so fast and also helps explain why remotely sensed cloud drop size is generally biased.
Marshak, Alexander↗
A New Approach to using a Cloud-Resolving Model to Study the Interactions between Clouds, Precipitation and Aerosols
Numerical cloud models, which are based the non-hydrostatic equations of motion, have been extensively applied to cloud-scale and mesoscale processes during the past four decades. Because cloud-scale dynamics are treated explicitly, uncertainties stemming from convection that have to be parameterized in (hydrostatic) large-scale models are obviated, or at least mitigated, in cloud models. Global models will use the non-hydrostatic framework when their horizontal resolution becomes about 10 kilometers, the theoretical limit for the hydrostatic approximation. This juncture will be reached one to two decades from now. Over the past generation, voluminous datasets on atmospheric convection have been accumulated from radar, instrumented aircraft, satellites, and rawinsonde measurements in field campaigns, enabling the detailed evaluation of models. Improved numerical methods have resulted in more accurate and efficient dynamical cores in models. Improvements have been made in the parameterizations of microphysical processes, radiation, boundary-layer effects, and turbulence; however, microphysical parameterizations remain a major source of uncertainty in all classes of atmospheric models. In recent years, exponentially increasing computer power has extended cloud-resolving-model integrations from hours to months, the number of computational grid points from less than a thousand to close to ten million. Three-dimensional models are now more prevalent. Much attention is devoted to precipitating cloud systems where the crucial 1-kilometer scales are resolved in horizontal domains as large as 10,000 kilometers in two dimensions, and 1,000 x 1,000 square kilometers in three-dimensions. Cloud models now provide statistical information useful for developing more realistic physically-based parameterizations for climate models and numerical weather prediction models. A review of developments and applications of cloud models in the past, present and future will be presented in this talk. In particular, a new approach to using cloud-resolving models to study the interactions between clouds, precipitation and aerosols will be presented.
Tao, Wei-Kuo↗
A New Approach to Using a Cloud-resolving Model to Study the Interactions Between Clouds, Precipitation and Aerosols
Numerical cloud models, which are based the non-hydrostatic equations of motion, have been extensively applied to cloud-scale and mesoscale processes during the past four decades. Because cloud-scale dynamics are treated explicitly, uncertainties stemming from convection that have to be parameterized in (hydrostatic) large-scale models are obviated, or at least mitigated, in cloud models. Global models will use the non-hydrostatic framework when their horizontal resolution becomes about 10 km, the theoretical limit for the hydrostatic approximation. This juncture will be reached one to two decades from now. Over the past generation, voluminous datasets on atmospheric convection have been accumulated from radar, instrumented aircraft, satellites, and rawinsonde measurements in field campaigns, enabling the detailed evaluation of models. Improved numerical methods have resulted in more accurate and efficient dynamical cores in models. Improvements have been made in the parameterizations of microphysical processes, radiation, boundary-layer effects, and turbulence; however, microphysical parameterizations remain a major source of uncertainty in all classes of atmospheric models. In recent years, exponentially increasing computer power has extended cloud-resolving-model integrations from hours to months, the number of computational grid points from less than a thousand to close to ten million. Three-dimensional models are now more prevalent. Much attention is devoted to precipitating cloud systems where the crucial 1-km scales are resolved in horizontal domains as large as l0,OOO km in two-dimensions, and 1,OOO x 1,OOO km2 in three-dimensions. Cloud models now provide statistical information useful for developing more realistic physically-based parameterizations for climate models and numerical weather prediction models. A review of developments and applications of cloud models in the past, present and future will be presented in this talk. In particular, a new approach to using cloud-resolving models to study the interactions between clouds, precipitation and aerosols will be presented.
Tao, Wei-Kuo↗
Online Tools for Astronomy and Cosmochemistry
Over the past year, the Webnucleo Group at Clemson University has been developing a web site with a number of interactive online tools for astronomy and cosmochemistry applications. The site uses SHP (Simplified Hypertext Preprocessor), which, because of its flexibility, allows us to embed almost any computer language into our web pages. For a description of SHP, please see http://www.joeldenny.com/ At our web site, an internet user may mine large and complex data sets, such as our stellar evolution models, and make graphs or tables of the results. The user may also run some of our detailed nuclear physics and astrophysics codes, such as our nuclear statistical equilibrium code, which is written in fortran and C. Again, the user may make graphs and tables and download the results.
Meyer, B. S.↗
A New Approach to using a Cloud-Resolving Model to Study the Interactions between Clouds, Precipitation and Aerosols
Numerical cloud models, which are based the non-hydrostatic equations of motion, have been extensively applied to cloud-scale and mesoscale processes during the past four decades. Because cloud-scale dynamics are treated explicitly, uncertainties stemming from convection that have to be parameterized in (hydrostatic) large-scale models are obviated, or at least mitigated, in cloud models. Global models will use the non-hydrostatic framework when their horizontal resolution becomes about 10 km, the theoretical limit for the hydrostatic approximation. This juncture will be reached one to two decades from now. Over the past generation, voluminous datasets on atmospheric convection have been accumulated from radar, instrumented aircraft, satellites, and rawinsonde measurements in field campaigns, enabling the detailed evaluation of models. Improved numerical methods have resulted in more accurate and efficient dynamical cores in models. Improvements have been made in the parameterizations of microphysical processes, radiation, boundary-layer effects, and turbulence; however, microphysical parameterizations remain a major source of uncertainty in all classes of atmospheric models. In recent years, exponentially increasing computer power has extended cloud-resolving-model integrations from hours to months, the number of computational grid points from less than a thousand to close to ten million. Three-dimensional models are now more prevalent. Much attention is devoted to precipitating cloud systems where the crucial 1-km scales are resolved in horizontal domains as large as 10,000 km in two-dimensions, and 1,000 x 1,000 square kilometers in three-dimensions. Cloud models now provide statistical information useful for developing more realistic physically-based parameterizations for climate models and numerical weather prediction models. A review of developments and applications of cloud models in the past, present and future will be presented in this talk. In particular, a new approach to using cloud-resolving models to study the interactions between clouds, precipitation and aerosols will be presented.
Tao, Wei-Kuo↗
Transport in the Subtropical Lowermost Stratosphere during CRYSTAL-FACE
We use in situ measurements of water vapor (H2O), ozone (O3), carbon dioxide (CO2), carbon monoxide (CO), nitric oxide (NO), and total reactive nitrogen (NO(y)) obtained during the CRYSTAL-FACE campaign in July 2002 to study summertime transport in the subtropical lowermost stratosphere. We use an objective methodology to distinguish the latitudinal origin of the sampled air masses despite the influence of convection, and we calculate backward trajectories to elucidate their recent geographical history. The methodology consists of exploring the statistical behavior of the data by performing multivariate clustering and agglomerative hierarchical clustering calculations, and projecting cluster groups onto principal component space to identify air masses of like composition and hence presumed origin. The statistically derived cluster groups are then examined in physical space using tracer-tracer correlation plots. Interpretation of the principal component analysis suggests that the variability in the data is accounted for primarily by the mean age of air in the stratosphere, followed by the age of the convective influence, and lastly by the extent of convective influence, potentially related to the latitude of convective injection [Dessler and Sherwuud, 2004]. We find that high-latitude stratospheric air is the dominant source region during the beginning of the campaign while tropical air is the dominant source region during the rest of the campaign. Influence of convection from both local and non-local events is frequently observed. The identification of air mass origin is confirmed with backward trajectories, and the behavior of the trajectories is associated with the North American monsoon circulation.
Pittman, Jasna V.↗
Transport in the Subtropical Lowermost Stratosphere during the Cirrus Regional Study of Tropical Anvils and Cirrus Layers-Florida Area Cirrus Experiment
We use in situ measurements of water vapor (H2O), ozone (O3), carbon dioxide (CO2), carbon monoxide (CO), nitric oxide (NO), and total reactive nitrogen (NOy) obtained during the CRYSTAL-FACE campaign in July 2002 to study summertime transport in the subtropical lowermost stratosphere. We use an objective methodology to distinguish the latitudinal origin of the sampled air masses despite the influence of convection, and we calculate backward trajectories to elucidate their recent geographical history. The methodology consists of exploring the statistical behavior of the data by performing multivariate clustering and agglomerative hierarchical clustering calculations and projecting cluster groups onto principal component space to identify air masses of like composition and hence presumed origin. The statistically derived cluster groups are then examined in physical space using tracer-tracer correlation plots. Interpretation of the principal component analysis suggests that the variability in the data is accounted for primarily by the mean age of air in the stratosphere, followed by the age of the convective influence, and last by the extent of convective influence, potentially related to the latitude of convective injection (Dessler and Sherwood, 2004). We find that high-latitude stratospheric air is the dominant source region during the beginning of the campaign while tropical air is the dominant source region during the rest of the campaign. Influence of convection from both local and nonlocal events is frequently observed. The identification of air mass origin is confirmed with backward trajectories, and the behavior of the trajectories is associated with the North American monsoon circulation.
Pittman, Jasna V.↗
Small-Scale Drop-Size Variability: Empirical Models for Drop-Size-Dependent Clustering in Clouds
By analyzing aircraft measurements of individual drop sizes in clouds, it has been shown in a companion paper that the probability of finding a drop of radius r at a linear scale l decreases as l(sup D(r)), where 0 less than or equals D(r) less than or equals 1. This paper shows striking examples of the spatial distribution of large cloud drops using models that simulate the observed power laws. In contrast to currently used models that assume homogeneity and a Poisson distribution of cloud drops, these models illustrate strong drop clustering, especially with larger drops. The degree of clustering is determined by the observed exponents D(r). The strong clustering of large drops arises naturally from the observed power-law statistics. This clustering has vital consequences for rain physics, including how fast rain can form. For radiative transfer theory, clustering of large drops enhances their impact on the cloud optical path. The clustering phenomenon also helps explain why remotely sensed cloud drop size is generally larger than that measured in situ.
Marshak, Alexander↗
Symbolic Processing Combined with Model-Based Reasoning
A computer program for the detection of present and prediction of future discrete states of a complex, real-time engineering system utilizes a combination of symbolic processing and numerical model-based reasoning. One of the biggest weaknesses of a purely symbolic approach is that it enables prediction of only future discrete states while missing all unmodeled states or leading to incorrect identification of an unmodeled state as a modeled one. A purely numerical approach is based on a combination of statistical methods and mathematical models of the applicable physics and necessitates development of a complete model to the level of fidelity required for prediction. In addition, a purely numerical approach does not afford the ability to qualify its results without some form of symbolic processing. The present software implements numerical algorithms to detect unmodeled events and symbolic algorithms to predict expected behavior, correlate the expected behavior with the unmodeled events, and interpret the results in order to predict future discrete states. The approach embodied in this software differs from that of the BEAM methodology (aspects of which have been discussed in several prior NASA Tech Briefs articles), which provides for prediction of future measurements in the continuous-data domain.
James, Mark↗
Error and Uncertainty Quantification in the Numerical Simulation of Complex Fluid Flows
The failure of numerical simulation to predict physical reality is often a direct consequence of the compounding effects of numerical error arising from finite-dimensional approximation and physical model uncertainty resulting from inexact knowledge and/or statistical representation. In this topical lecture, we briefly review systematic theories for quantifying numerical errors and restricted forms of model uncertainty occurring in simulations of fluid flow. A goal of this lecture is to elucidate both positive and negative aspects of applying these theories to practical fluid flow problems. Finite-element and finite-volume calculations of subsonic and hypersonic fluid flow are presented to contrast the differing roles of numerical error and model uncertainty. for these problems.
Barth, Timothy J.↗
The Digital Twin Paradigm for Future NASA and U.S. Air Force Vehicles
Future generations of NASA and U.S. Air Force vehicles will require lighter mass while being subjected to higher loads and more extreme service conditions over longer time periods than the present generation. Current approaches for certification, fleet management and sustainment are largely based on statistical distributions of material properties, heuristic design philosophies, physical testing and assumed similitude between testing and operational conditions and will likely be unable to address these extreme requirements. To address the shortcomings of conventional approaches, a fundamental paradigm shift is needed. This paradigm shift, the Digital Twin, integrates ultra-high fidelity simulation with the vehicle s on-board integrated vehicle health management system, maintenance history and all available historical and fleet data to mirror the life of its flying twin and enable unprecedented levels of safety and reliability.
Glaessgen, Edward H.↗