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All sources NASA NTRS DOE OSTI

DOE OSTI2021

Multiplicative noise and the diffusion of conserved densities

Stochastic fluid dynamics governs the long time tails of hydrodynamic correlation functions, and the critical slowing down of relaxation phenomena in the vicinity of a critical point in the phase diagram. In this work we study the role of multiplicative noise in stochastic fluid dynamics. Multiplicative noise arises from the dependence of transport coefficients, such as the diffusion constants for charge and momentum, on fluctuating hydrodynamic variables. We study long time tails and relaxation in the diffusion of a conserved density (model B), and a conserved density coupled to the transverse momentum density (model H). Careful attention is paid to fluctuation-dissipation relations. We observe that multiplicative noise contributes at the same order as non-linear interactions in model B, but is a higher order correction to the relaxation of a scalar density and the tail of the stress tensor correlation function in model H.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

NASA NTRS1974

Variable features on Mars III - Comparison of Mariner 1969 and Mariner 1971 photography

Mariner 9 (M9) and Mariner 6 and 7 photography of common regions of Mars are compared, with appropriate attention to the photometric properties of the camera systems. The comparison provides a 2.5 yr time baseline for study of variable albedo features. We find the development of bright streaks and patches, a phenomenon unobserved through the entire M9 mission; the evolution of dark crater splotches into dark streaks; and a planetwide increase in splotchiness. Yet, a large number of splotches and albedo boundaries remain fixed over the same period. Many of the observations are interpreted in terms of a global fallout and subsequent local redistribution of bright fine particulates raised by global dust storms.

Veverka, J.↗

DOE OSTI2026

Employing Machine Learning for New Particle Formation Identification and Mechanistic Analysis: Insights From a Six‐Year Observational Study in the Southern Great Plains

We present a supervised machine learning (ML) framework to automatically identify new particle formation (NPF) events and analyze key atmospheric factors associated with their occurrence and growth. We applied ML to detect NPF events using start time and particle concentrations across size ranges, while identifying atmospheric variables including ambient temperature, relative humidity, solar radiation intensity (SRI), wind speed, wind direction, boundary layer height, total organics, sulfate, nitrate, total surface area concentration, sulfur dioxide, and turbulent kinetic energy (TKE). We analyzed a 6-year data set from the Atmospheric Radiation Measurement at the Southern Great Plains (SGP) site in Oklahoma, USA. Using long-term ground-based measurements, we identified NPF events and applied Random Forest Classifiers, which achieved 90%–95% prediction accuracy. Feature importance analysis highlighted SRI, relative humidity, and ambient temperature as the most influential variables, contributing normalized importances of 28%, 17%, and 10%. Partial Dependence Plots (PDPs) indicated that higher SRI and lower relative humidity were critical in promoting NPF formation at SGP. Seasonally, NPF events were more frequent in winter (42.1%) and spring (35.5%), and least in summer (4.0%). Particle growth rates also exhibited a seasonal variation, with the lowest in winter (below 2 nm hr −1 ) and highest in late spring and early summer (exceeding 5 nm hr −1 ). Temperature, turbulent kinetic energy, and aerosol properties were the primary factors of growth rate variability. This study advances predictive modeling of NPF, offers insights for future campaign deployments, and demonstrates the effectiveness of ML in understanding the formation and growth of atmospheric aerosols.

54 ENVIRONMENTAL SCIENCES↗

NASA NTRS1996

The Nature of Global Large-scale Sea Level Variability in Relation to Atmospheric Forcing: A Modeling Study

The relation between large-scale sea level variability and ocean circulation is studied using a numerical model. A global primitive equaiton model of the ocean is forced by daily winds and climatological heat fluxes corresponding to the period from January 1992 to February 1996. The physical nature of the temporal variability from periods of days to a year, are examined based on spectral analyses of model results and comparisons with satellite altimetry and tide gauge measurements.

ocean circulation circulation models ocean models ↗

NASA NTRS2013

Quantitative Comparison of the Variability in Observed and Simulated Shortwave Reflectance

The Climate Absolute Radiance and Refractivity Observatory (CLARREO) is a climate observation system that has been designed to monitor the Earth's climate with unprecedented absolute radiometric accuracy and SI traceability. Climate Observation System Simulation Experiments (OSSEs) have been generated to simulate CLARREO hyperspectral shortwave imager measurements to help define the measurement characteristics needed for CLARREO to achieve its objectives. To evaluate how well the OSSE-simulated reflectance spectra reproduce the Earth s climate variability at the beginning of the 21st century, we compared the variability of the OSSE reflectance spectra to that of the reflectance spectra measured by the Scanning Imaging Absorption Spectrometer for Atmospheric Cartography (SCIAMACHY). Principal component analysis (PCA) is a multivariate decomposition technique used to represent and study the variability of hyperspectral radiation measurements. Using PCA, between 99.7%and 99.9%of the total variance the OSSE and SCIAMACHY data sets can be explained by subspaces defined by six principal components (PCs). To quantify how much information is shared between the simulated and observed data sets, we spectrally decomposed the intersection of the two data set subspaces. The results from four cases in 2004 showed that the two data sets share eight (January and October) and seven (April and July) dimensions, which correspond to about 99.9% of the total SCIAMACHY variance for each month. The spectral nature of these shared spaces, understood by examining the transformed eigenvectors calculated from the subspace intersections, exhibit similar physical characteristics to the original PCs calculated from each data set, such as water vapor absorption, vegetation reflectance, and cloud reflectance.

Roberts, Yolanda, L.↗

NASA NTRS1999

The Role of Data Assimilation in the Study of Regional and Global Variability of the Hydrological Cycle

In the coming years, researchers will have at their disposal a host of new observations from advanced space-based sensors (e.g. the Tropical Rainfall Measuring Mission, EOS Terra and PM missions) providing, among other things, a more complete and accurate description of various components of the Earth's hydrological cycle. Also, increasingly more sophisticated and comprehensive geophysical models will provide researchers better tools for simulating the hydrological cycle, and for carrying out mechanistic studies of the role of moist processes in the climate system. In addition, new data sets generated with global four-dimensional data assimilation (4DDA) systems will provide comprehensive and complete information on both the state and forcing of the climate system. Ideally, the 4DDA systems optimally incorporate all relevant information from the observations together with a first guess from a state-of-the-art geophysical model to produce a "best" estimate of the climate state. Furthermore, to the extent that the assimilating models are realistic and are constrained by the observations, they should provide reliable estimates of the associated physical processes or climate forcing fields. While operational weather centers now have a considerable history of providing reliable estimates of the basic atmospheric state variables, the associated processes or diagnostic fields (which are less well constrained by the observations and sensitive to errors in the model's physical parameterizations) are still considered experimental and of uncertain quality. In this study we will examine the current generation of reanalysis products to assess the capabilities of 4DDA systems to represent components of the hydrological cycle. The focus is on the role of the model in providing consistent estimates of moist processes. We will also assess whether current observations provide sufficient constraints on these model- generated fields.

Schubert, Siegfried↗

NASA NTRS1980

Theoretical mean colors for RR Lyrae variables

A hydrodynamically pulsating 0.6 solar mass model of a typical RR Lyrae variable was studied with a radiation transport-hydrodynamic computer program to predict theoretical T sub 3 and colors at many phases and to find the proper methods for getting mean colors and the consequent mean effective temperatures. The variable Eddington radiation approximation method was used with gray and with multifrequency absorption coefficients to represent the radiation flow in the outer optically thin layers. Comparison between observed and computed B-V colors indicate that these low Z population 2 models are reasonably accurate using King 1A composition opacities. The well known Oke, Giver, and Searle relation between B-V and T sub e reproduced. Mean colors were found by four different averaging methods. The method that gives a mean color and the mean T sub e closest to the nonpulsating model was the separate intensity means of B and V.

Davis, C. G.↗

NASA NTRS1996

Studies of Tidal and Planetary Wave Variability in the Middle Atmosphere using UARS and Correlative MF Radar Data

The goals of this research effort have been to use MF radar and UARS/HRDI wind measurements for correlative studies of large-scale atmospheric dynamics, focusing specifically on the tidal and various planetary wave structures occurring in the middle atmosphere. We believed that the two data sets together would provide the potential for much more comprehensive studies than either by itself, since they jointly would allow the removal of ambiguities in wave structure that are difficult to resolve with either data set alone. The joint data were to be used for studies of wave structure, variability, and the coupling of these motions to mean and higher-frequency motions.

Fritts, David C.↗

NASA NTRS1999

Variability of Convective Precipitation from TRMM Microwave Imager (TMI)

Tropical precipitation generally occurs in two distinguishable forms: convective and stratiform. The two different types of precipitation systems have considerably different vertical profiles of latent heat release that has a crucial role in driving the circulation of the atmosphere. Thus, it is very important to study the variability of convective and stratiform precipitation. This paper presents variability of convective precipitation estimated from TRMM Microwave Imager (TMI). The convective/stratiform precipitation areas are classified using a combined texture-based and polarization-based algorithm. Surface rainfall rates are retrieved using the Goddard Profiling algorithm (Gprof). We will examine the spatial and temporal variability of convective precipitation for 1998. In addition, convective precipitation computed from TMI will be compared with those from the space borne Precipitation Radar (PR) and the ground-based radars for several cases.

Hong, Ye↗

DOE OSTI2024

Enhanced Sampling of Crystal Nucleation with Graph Representation Learnt Variables

In this study, we present a graph neural network-based learning approach using an autoencoder setup to derive low-dimensional variables from features observed in experimental crystal structures. These variables are then biased in enhanced sampling to observe state-to-state transitions and reliable thermodynamic weights. Our approach uses simple convolution and pooling methods. To verify the effectiveness of our protocol, we examined the nucleation of various allotropes and polymorphs of iron and glycine from their molten states. Our graph latent variables when biased in well-tempered metadynamics consistently show transitions between states and achieve accurate free energy calculations in agreement with experiments, both of which are indicators of dependable sampling. This underscores the strength and promise of our graph neural net variables for improved sampling. Furthermore, the protocol shown here should be applicable for other systems and with other sampling methods.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

NASA NTRS1986

Solar Ultraviolet Spectral Irradiance Monitor (SUSIM)

The solar ultraviolet spectral irradiance monitor (SUSIM) measures the ultraviolet flux from the entire Sun with high absolute accuracy over the wavelength range 120 to 400 nm with a resolution of 0.1 nm. SUSIM consists of two identical double dispersion scanning spectrometers with 5 photodiodes, 2 photon counters, and a deuterium lamp calibration source, all sealed in a canister pressurized to 1.1 atmosphere of argon. One spectrometer is used almost continuously during sunlight, the other is used once per day as a calibration check. The observations will yield improved absolute measurements of the ultraviolet solar fluxes, provide an accurate reference for studies of variability of the solar fluxes on the time scales of the solar cycle and longer, and measure shorter term changes as well. These measurements complement the ACR measurements of the total solar irradiance. The data will be used to study the physical behavior of the Sun and the Earth's atmosphere, weather, and climate.

Moore, R.↗

NASA NTRS1990

The effect of latent heat release on synoptic-to-planetary wave interactions and its implication for satellite observations: Theoretical modeling

The project objectives are to develop process models to investigate the interaction of planetary and synoptic-scale waves including the effects of latent heat release (precipitation), nonlinear dynamics, physical and boundary-layer processes, and large-scale topography; to determine the importance of latent heat release for temporal variability and time-mean behavior of planetary and synoptic-scale waves; to compare the model results with available observations of planetary and synoptic wave variability; and to assess the implications of the results for monitoring precipitation in oceanic-storm tracks by satellite observing systems. Researchers have utilized two different models for this project: a two-level quasi-geostrophic model to study intraseasonal variability, anomalous circulations and the seasonal cycle, and a 10-level, multi-wave primitive equation model to validate the two-level Q-G model and examine effects of convection, surface processes, and spherical geometry. It explicitly resolves several planetary and synoptic waves and includes specific humidity (as a predicted variable), moist convection, and large-scale precipitation. In the past year researchers have concentrated on experiments with the multi-level primitive equation model. The dynamical part of that model is similar to the spectral model used by the National Meteorological Center for medium-range forecasts. The model includes parameterizations of large-scale condensation and moist convection. To test the validity of results regarding the influence of convective precipitation, researchers can use either one of two different convective schemes in the model, a Kuo convective scheme or a modified Arakawa-Schubert scheme which includes downdrafts. By choosing one or the other scheme, they can evaluate the impact of the convective parameterization on the circulation. In the past year researchers performed a variety of initial-value experiments with the primitive-equation model. Using initial conditions typical of climatological winter conditions, they examined the behavior of synoptic and planetary waves growing in moist and dry environments. Surface conditions were representative of a zonally averaged ocean. They found that moist convection associated with baroclinic wave development was confined to the subtropics.

Branscome, Lee E.↗

DOE OSTI2021

Five percent measurement of the gravitational constant in the Large Magellanic Cloud

We perform a novel test of General Relativity by measuring the gravitational constant in the Large Magellanic Cloud (LMC). The LMC contains six well-studied Cepheid variable stars in detached eclipsing binaries. Radial velocity and photometric observations enable a complete orbital solution, and precise measurements of the Cepheids’ periods permit detailed stellar modelling. Both are sensitive to the strength of gravity, the former via Kepler’s third law and the latter through the gravitational free-fall time. We jointly fit the observables for stellar parameters and the gravitational constant. Performing a full Markov Chain Monte Carlo analysis of the parameter space including all relevant nuisance parameters, we constrain the gravitational constant in the Large Magellanic Cloud relative to the Solar System to be G LMC /G SS = $0.93{^{+0.05}_{-0.04}}$. We discuss the implications of this 5% measurement of Newton’s constant in another galaxy for dark energy and modified gravity theories. This result excludes one Cepheid, CEP-1812, which is an outlier and needs further study: it is either a highly unusual system to which our model does not apply, or it prefers G LMC < G SS at 2.6σ. We also obtain new bounds on critical parameters that appear in semi-analytic descriptions of stellar processes. In particular, we measure the mixing length parameter to be $α = 0.90{^{+0.36}_{-0.26}}$ (when assumed to be constant across our sample), and obtain constraints on the parameters describing turbulent dissipation and convective flux.

79 ASTRONOMY AND ASTROPHYSICS↗

NASA NTRS1979

Design study and performance analysis of a high-speed multistage variable-geometry fan for a variable cycle engine

A design technology study was performed to identify a high speed, multistage, variable geometry fan configuration capable of achieving wide flow modulation with near optimum efficiency at the important operating condition. A parametric screening study of the front and rear block fans was conducted in which the influence of major fan design features on weight and efficiency was determined. Key design parameters were varied systematically to determine the fan configuration most suited for a double bypass, variable cycle engine. Two and three stage fans were considered for the front block. A single stage, core driven fan was studied for the rear block. Variable geometry concepts were evaluated to provide near optimum off design performance. A detailed aerodynamic design and a preliminary mechanical design were carried out for the selected fan configuration. Performance predictions were made for the front and rear block fans.

Sullivan, T. J.↗

DOE OSTI2025

Storage-Induced Collapse of Lignin Macromolecular Structure and Its Impacts on the Biorefinery

Lignin plays a vital role in the economics of biorefineries, serving as a source of process energy and a feedstock for sustainable fuels and chemical production. While understanding lignin’s chemical composition is crucial, emerging evidence suggests that a more comprehensive understanding of its macromolecular structure is critical to explaining its complex behavior in the biorefinery. This study investigated the partial collapse of the lignin network in corn stover feedstock after harvest and storage as a result of the microbial digestion of hemicellulose. Fluorescence microscopy was used to detect the collapse of lignin in terms of lignin’s inter-molecular interaction and the re-orientation of lignin’s chromophores, by the changes in lignin’s fluorescence lifetime, anisotropy, and the number of effective emitters. With minimal sample perturbation, our in-situ microscopic results revealed lignin's coil-globule transition phenomena, which was only previously predicted by molecular dynamics modeling extracted lignin in solvent. This collapse of lignin macromolecular structure was confirmed by results from NMR, IR, Raman, and powder X-ray diffraction. We also investigated the impact of this storage-induced collapse on the downstream biorefinery processes. Our study revealed that the two major approaches for lignin valorization in the lignin-first biorefinery model, namely monomer extraction and milled wood lignin extraction, were negatively impacted by the lignin collapse. As changes during storage are a source of feedstock variability, our study highlights the importance of understanding the effect of feedstock handling on biorefinery operations and economics.

09 BIOMASS FUELS↗

DOE OSTI2022

Nonperturbative negative geometries: amplitudes at strong coupling and the amplituhedron

The amplituhedron determines scattering amplitudes in planar N = 4 super Yang-Mills by a single “positive geometry” in the space of kinematic and loop variables. We study a closely related definition of the amplituhedron for the simplest case of four-particle scattering, given as a sum over complementary “negative geometries”, which provides a natural geometric understanding of the exponentiation of infrared (IR) divergences, as well as a new geometric definition of an IR finite observable F(g, z) — dually interpreted as the expectation value of the null polygonal Wilson loop with a single Lagrangian insertion — which is directly determined by these negative geometries. This provides a long-sought direct link between canonical forms for positive (negative) geometries, and a completely IR finite post-loop-integration observable depending on a single kinematical variable z, from which the cusp anomalous dimension Γ cusp (g) can also be straightforwardly obtained. We study an especially simple class of negative geometries at all loop orders, associated with a “tree” structure in the negativity conditions, for which the contributions to F(g, z) and Γ cusp can easily be determined by an interesting non-linear differential equation immediately following from the combinatorics of negative geometries. This lets us compute these “tree” contributions to F(g, z) and Γ cusp for all values of the ‘t Hooft coupling. The result for Γ cusp remarkably shares all main qualitative characteristics of the known exact results obtained using integrability.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

NASA NTRS1985

Solar Ultraviolet Spectral Irradiance Monitor (SUSIM)

The solar ultraviolet spectral irradiance monitor (SUSIM) measures the ultraviolet flux from the entire Sun with high absolute accuracy over the wavelength range 120 to 400 nm with a resolution of 0.1 nm. SUSIM consists of two identical double dispersion scanning spectrometers with 5 photodiodes, 2 photon counters, and a deuterium lamp calibration source, all sealed in a canister pressurized to 1.1 atmosphere of argon. One spectrometer is used almost continuously during sunlight, the other is used once per day as a calibration check. The observations will yield improved absolute measurements of the ultraviolet solar fluxes, provide an accurate reference for studies of variability of the solar fluxes on the time scales of the solar cycle and longer, and measure shorter term changes as well. These measurements complement the active cavity radiometer (ACR) measurements of the total solar irradiance. The data will be used to study the physical behavior of the Sun and the Earth's atmosphere, weather, and climate.

Moore, R. L.↗

NASA NTRS1987

Transport and photochemical modeling. Studies of atmospheric species

A program of research studies related to the photochemistry, radiative transfer, and dynamics of the stratosphere is described. Investigations were conducted in two broad areas: (1) studies of the stratospheric processes and their response to external perturbations, and (2) analysis of satellite measurements in conjunction with theoretical models. Contemporary one dimensional photochemical, radiative-convective model was used to assess the impact of perturbations such as solar flux variability, increases in atmospheric carbon dioxide, chlorofluoromethanes and other greenhouse gases. Data from satellite experiments such as LIMS and SBUV, were used along with theoretical models to develop a climatology of trace species in the stratosphere. The consistency of contemporary ozone photochemistry was examined in the light of LIMS data. Research work also includes analysis of stratospheric nitrogen dioxide distributions from different satellite experiments, investigation of the wintertime latitudinal gradients in NO2, estimation of the stratospheric odd nitrogen level and its variability, and studies related to the changes in ozone in the Antarctic, and mid latitude Southern Hemisphere.

Natarajan, M.↗