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At least 325 records · Page 18
All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

The Role of Subcloud Mesoscale Convergence in Sculpting Convective Updraft Width and Depth

The initiation of deep moist convection is governed in part by the horizontal width of updrafts near cloud base, which limits the deleterious effects of entrainment-driven dilution on buoyant thermals ascending through the free troposphere. However, the factors controlling cloud-base updraft width, which in turn dictates cloud depth, are not well understood. We track the evolving three-dimensional structure of the mesoscale subcloud forcing for vertical motion and near-cloud thermodynamic ingredients within a high-resolution ensemble of simulations of seven realistic daytime orographic convection initiation events to determine their relative roles in controlling cloud width and depth. Statistical analysis of approximately 5000 cloudy updraft samples indicates that the most important contributors to the width of cloudy updrafts across the ensemble are the depth and magnitude of the subcloud mesoscale ascent. However, the depth achieved by clouds is more consistently predicted by the near-cloud ambient relative humidity within the lower to middle free troposphere and convective available potential energy. Therefore, although the width of cloudy updrafts may be partly set at low levels by the mesoscale vertical mass and moisture flux, the likelihood of deep moist convection is governed by the generation of positive buoyancy within cumulus thermals and entrainment-driven dilution that reduces it. The persistence of the low-level mesoscale vertical forcing locally consolidates and vertically transports boundary layer moisture, helping to reduce updraft dilution. However, these factors vary in relative impacts on cloudy updrafts across individual cases, indicating multiple pathways for deep convection initiation.

Convective storms↗
DOE OSTI2024

Statistical mechanics and pressure of composite multimoded weakly nonlinear optical systems

Statistical mechanics can provide a versatile theoretical framework for investigating the collective dynamics of weakly nonlinear-wave settings that can be utterly complex to describe otherwise. In optics, composite systems arise due to interactions between different frequencies and polarizations. The purpose of this work is to develop a thermodynamic theory that takes into account the synergistic action of multiple components. We find that the type of the nonlinearity involved can have important implications in the thermalization process and, hence, can lead to different thermal equilibrium conditions. Importantly, we derive closed-form expressions for the actual optomechanical pressure that is exerted on the system. In particular, the total optomechanical pressure is the sum of the partial pressures due to each component. Our results can be applied to a variety of weakly nonlinear optical settings such as multimode fibers, bulk waveguides, photonic lattices, and coupled microresonators. We present two specific examples, where two colors interact in a one-waveguide array with either a cubic or quadratic nonlinearity.

Efremidis, Nikolaos K. (ORCID:0000000298300268)↗
DOE OSTI2024

Air separation and N 2 purification with Ba 0.15 Sr 0.85 FeO 3-$δ$ via a two-step thermochemical process

Thermochemical air separation to produce high-purity N 2 was demonstrated in a vertical tube reactor via a two-step reduction–oxidation cycle with an A-site substituted perovskite Ba 0.15 Sr 0.85 FeO 3–δ (BSF1585). BSF1585 particles were synthesized and characterized in terms of their chemical, morphological, and thermophysical properties. A thermodynamic cycle model and sensitivity analysis using computational heat and mass transfer models of the reactor were used to select the system operating parameters for a concentrating solar thermal-driven process. Thermal reduction up to 800 °C in air and temperature-swing air separation from 800 °C to minimum temperatures between 400 and 600 °C were performed in the reactor containing a 35 g packed bed of BSF1585. The reactor was characterized for dispersion, and air separation was characterized via mass spectrometry. Gas measurements indicated that the reactor produced N 2 with O 2 impurity concentrations as low as 0.02 % for > 30 min of operation. Additionally, a parametric study of air flow rates suggested that differences in observed and thermodynamically predicted O 2 impurities were due to imperfect gas transport in the bed. Temperature swing reduction/oxidation cycling experiments between 800 and 400 °C in air were conducted with no statistically significant degradation in N 2 purity over 50 cycles.

14 SOLAR ENERGY↗
DOE OSTI2020

Weak scaling of the contact distance between two fluctuating interfaces with system size

A pair of flat parallel surfaces, each freely diffusing along the direction of their separation, will eventually come into contact. If the shapes of these surfaces also fluctuate, then contact will occur when their centers-of-mass remain separated by a nonzero distance ℓ. An example of such a situation is the motion of interfaces between two phases at conditions of thermodynamic coexistence, and in particular the annihilation of domain wall pairs under periodic boundary conditions. Here we present a general approach to calculate the probability distribution of the contact distance ℓ and determine how its most likely value ℓ* depends on the surfaces' lateral size L. Using the Edward-Wilkinson equation as a model for interfaces, we demonstrate that ℓ* scales weakly with system size, i.e., the dependence of ℓ* on L for both (1+1)- and (2+1)-dimensional interfaces is such that lim L→∞ (ℓ*/L) = 0. In particular, for (2+1)-dimensional interfaces ℓ* is an algebraic function of logL, a result that is confirmed by computer simulations of slab-shaped domains formed under periodic boundary conditions. Overall, this weak scaling implies that such domains remain topologically intact until ℓ becomes very small compared to the lateral size of the interface, contradicting expectations from equilibrium thermodynamics.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
NASA NTRS2020

The NASA MODIS-VIIRS Continuity Cloud Optical Properties Products

The NASA Aqua MODIS and Suomi National Polar-Orbiting Partnership (SNPP) Visible Infrared Imaging Radiometer Suite (VIIRS) climate data record continuity cloud properties products (CLDPROP) were publicly released in April 2019 with an update later that year (Version 1.1). These cloud products, having heritage with the NASA Moderate-resolution Imaging Spectroradiometer (MODIS) MOD06 cloud optical properties product and the NOAA GOES-R Algorithm Working Group (AWG) Cloud Height Algorithm (ACHA), represent an effort to bridge the multispectral imager records of NASA’s Earth Observing System (EOS) and NOAA’s current generation of operational weather satellites to achieve a continuous, multi-decadal climate data record for clouds that can extend well into the 2030s. CLDPROP offers a “continuity of approach,” applying common algorithms and ancillary datasets to both MODIS and VIIRS, including utilizing only a subset of spectral channels available on both sensors to help mitigate instrument differences. The initial release of the CLDPROP_MODIS and CLDPROP_VIIRS data records spans the SNPP observational record (2012-present). Here, we present an overview of the algorithms and an evaluation of the intersensor continuity of the core CLDPROP_MODIS and CLDPROP_VIIRS cloud optical property datasets, i.e., cloud thermodynamic phase, optical thickness, effective particle size, and derived water path. The evaluation includes analyses of pixel-level MODIS/VIIRS co-locations as well as spatial and temporal aggregated statistics, with a focus on identifying and understanding the root causes of individual dataset discontinuities. The results of this evaluation will inform future updates to the CLDPROP products and help scientific users determine the appropriate use of the product datasets for their specific needs.

satellite remote sensing↗
DOE OSTI2023

Atomistic simulations and machine learning of solute grain boundary segregation in Mg alloys at finite temperatures

Understanding solute segregation thermodynamics is the first step in investigating grain boundary (GB) properties, such as strong yttrium (Y) effects on grain growth and texture evolution in micro-scale polycrystalline magnesium (Mg) alloys. To estimate the average GB segregation behavior in low-solute-concentration Mg alloys (e.g., 2 at.% Y), a state-of-the-art spectral approach is applied based on a per-site segregation energy spectrum for Y solute atoms at zero K obtained from molecular statistics (MS) simulations of ~10 4 GB sites in Mg symmetric tilt GBs (STGBs). Although selected MS simulation results are consistent with verification by density functional theory (DFT) calculations, estimates of average segregation tendency based on the zero-K energy spectrum deviate from experimental observations. To resolve this problem, thermodynamic integration (TI) methods based on molecular dynamics (MD) simulations are used to determine the per-site segregation free energies of Y at representative GB sites, which show contributions beyond harmonic approximations can be important for certain GB sites at high temperatures. A surrogate model of per-site segregation free energy is constructed from a small set of TI data points using stacking cross-validation regressors and physics-informed descriptors. This model is applied to predict the Y segregation free energy spectra for thousands of GB sites in Mg STGBs with uncertainty quantification. Finally, the average segregation tendency predicted by the spectral approach based on the free energy spectra agrees well (within the uncertainty range) with experimental observations for micro-scale polycrystalline Mg alloys at typical thermomechanical processing temperatures (500 ~ 800 K), where thermodynamic equilibrium states are likely to be achieved due to fast diffusion.

Atomistic simulations↗
DOE OSTI2025

Simultaneous inference of equation of state parameters and unknown data errors with uncertainty quantification via hierarchical Bayesian posterior maximization

Equations of state (EOSs) are a key component in running hydrodynamic simulations as they relate the thermodynamic states for the material. The Davis reactants EOS is commonly used for modeling high explosives (HEs), and the EOS model parameters are calibrated using material specific data. The calibrations are often performed with uncertainty quantification via Bayesian inference to account for uncertainty in the data and generate ensembles of likely parameters. However, there are relatively few HE data sets to use for calibration and many are historical and lack error information. In this work, we simultaneously calibrate the Davis reactants EOS model parameters and unknown data error terms for the high explosive PBX 9501. To quantify the uncertainty in the models and the data, we use a Bayesian framework for the calibration and compute the hierarchical Bayesian posterior distribution with both a posteriori maximization approach and Markov Chain Monte Carlo. In general, we find that, given our assumptions, the two approaches result in similar calibrated parameters, posterior covariance matrices, and insights about the parameters but that the posterior maximization requires far less computational resources.

97 MATHEMATICS AND COMPUTING↗
NASA NTRSDate not supplied

Isolating the Surface Type Influence on Arctic Cloud Properties

In response to anthropogenic climate change, substantial declines in sea ice have been observed. An urgent question is whether and how clouds respond to the changing Arctic surface. Due to the important radiative influence of clouds, the response of clouds to sea ice cover change constitutes a potentially important climate feedback within the Arctic. The sign of this feedback is strongly influenced by the seasonality of the cloud response to sea ice loss. Given the importance of this phenomenon, previous research focused on using observations of inter-annual variability to quantify the cloud-sea ice relationship. However, the reliance on inter-annual variability to assess the covariance between clouds and sea ice make it challenging to control for the influence of large-scale meteorology on the clouds. We have devised an approach that applies an in situ, airborne observational strategy to quantify the influence of surface type on Arctic clouds to satellite data. Our event-based method composites cloud property differences for ocean, marginal ice zone, and sea ice surface types for >5000 MIZ crossing events. We find that cloud properties in non-summer months below ~1.5 km are influenced by surface type such that greater cloud fraction and water content are found over ocean relative to sea ice regions. Results are statistically significantly at the 95% confidence level. During summer, the surface type does not influence the cloud properties. The primary cause of the surface type dependent cloud property differences is the thermodynamic profiles differences that occur between the two surface types: namely, ocean footprints are warmer, moister, have more positive surface turbulent fluxes and are less stable than their sea ice counterparts. We find that the differences in thermodynamic profiles by surface type that correspond to the cloud property differences also explains a significant portion of the variability across events. Our analysis provides evidence that the influence of surface type on cloud properties fundamentally occurs due to the inherent surface temperature differences between the surface types. Significant surface type influences on cloud properties are only found in the presence of surface temperature differences between the surface types and only non-summer months meet this criterion. A conceptual model of this process is as follows, fundamental properties of the ocean and sea ice surface types (e.g., surface albedo, heat capacity/thermal inertia, surface roughness, and thermal conductance) lead to systematic differences in the surface temperature by surface type. In response to this surface temperature difference, atmosphere boundary layer processes (including turbulent mixing and radiation) communicate the surface temperature differences to the lower atmosphere driving the greater stability over sea ice than ocean. These differences in the background thermodynamic state profiles between the surface types yield atmospheric conditions that are more conducive to cloud development over ocean than sea ice. The details of these boundary layer processes are sensitive to the surface type but may not be fundamental to the resulting thermodynamic structure and cloud differences. Thus, our results indicate that to accurately model that cloud response to sea ice loss in climate models the surface type properties that yield the systematic differences in ocean and sea ice temperature (e.g., surface albedo, surface turbulent fluxes parameters, and thermal conductance) must be accurately represented.

Arctic radiation budget↗
DOE OSTI2021

Bayesian Learning of Adatom Interactions from Atomically Resolved Imaging Data

Atomic structures and adatom geometries of surfaces encode information about the thermodynamics and kinetics of the processes that lead to their formation, and which can be captured by a generative physical model. In this work, we develop a workflow based on a machine-learning-based analysis of scanning tunneling microscopy images to reconstruct the atomic and adatom positions, and a Bayesian optimization procedure to minimize statistical distance between the chosen physical models and experimental observations. We optimize the parameters of a 2- and 3-parameter Ising model describing surface ordering and use the derived generative model to make predictions across the parameter space. For concentration dependence, we compare the predicted morphologies at different adatom concentrations with the dissimilar regions on the sample surfaces that serendipitously had different adatom concentrations. The proposed workflow can be used to reconstruct the thermodynamic models and associated uncertainties from the experimental observations of materials microstructures. The code used in the manuscript is available at https://github.com/saimani5/Adatom_interactions.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Electrons matter in ferromagnetic criticality

When elemental iron is cooled from high temperatures, magnetic moments carried by its d-electrons begin a continuous transition to a state of parallel aligned moments below its Curie temperature TC of about 1040 K. As established in the mid-1900s, the statistical physics of this second order phase transition is universal, independent of the ordering temperature, material structure and chemical composition as well as the character of moment-bearing electrons. Finally, the thermodynamics of the phase transition is determined solely by symmetries of the transition’s order parameter – magnetization in the case of a ferromagnet.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Investigation of high-pressure turbulent jets using direct numerical simulation

Direct numerical simulations of free round jets at a Reynolds number (Re D ) of 5000, based on jet diameter (D) and jet-exit bulk velocity (U e ), are performed to study jet turbulence characteristics at supercritical pressures. The jet consists of nitrogen (N 2 ) that is injected into N 2 at the same temperature. To understand turbulent mixing, a passive scalar is transported with the flow at unity Schmidt number. Two sets of inflow conditions that model jets issuing from either a smooth contraction nozzle (laminar inflow) or a long pipe nozzle (turbulent inflow) are considered. By changing one parameter at a time, the simulations examine the jet-flow sensitivity to the thermodynamic condition (characterized in terms of the compressibility factor ($Z$) and the normalized isothermal compressibility), inflow condition and ambient pressure (p ∞ ) spanning perfect- to real-gas conditions. The inflow affects flow statistics in the near field (containing the potential core closure and the transition region) as well as further downstream (containing fully developed flow with self-similar statistics) at both atmospheric and supercritical p ∞ . The sensitivity to inflow is larger in the transition region, where the laminar-inflow jets exhibit dominant coherent structures that produce higher mean strain rates and higher turbulent kinetic energy than in turbulent-inflow jets. Decreasing $Z$ at a fixed supercritical p ∞ enhances pressure and density fluctuations (non-dimensionalized by local mean pressure and density, respectively), but the effect on velocity fluctuations depends also on the local flow dynamics. When $Z$ is reduced, large mean strain rates in the transition region of laminar-inflow jets significantly enhance velocity fluctuations (non-dimensionalized by local mean velocity) and scalar mixing, whereas the effects are minimal in jets from turbulent inflow.

42 ENGINEERING↗
DOE OSTI2021

Thermodynamics of order and randomness in dopant distributions inferred from atomically resolved imaging

Abstract Exploration of structure-property relationships as a function of dopant concentration is commonly based on mean field theories for solid solutions. However, such theories that work well for semiconductors tend to fail in materials with strong correlations, either in electronic behavior or chemical segregation. In these cases, the details of atomic arrangements are generally not explored and analyzed. The knowledge of the generative physics and chemistry of the material can obviate this problem, since defect configuration libraries as stochastic representation of atomic level structures can be generated, or parameters of mesoscopic thermodynamic models can be derived. To obtain such information for improved predictions, we use data from atomically resolved microscopic images that visualize complex structural correlations within the system and translate them into statistical mechanical models of structure formation. Given the significant uncertainties about the microscopic aspects of the material’s processing history along with the limited number of available images, we combine model optimization techniques with the principles of statistical hypothesis testing. We demonstrate the approach on data from a series of atomically-resolved scanning transmission electron microscopy images of Mo x Re 1- x S 2 at varying ratios of Mo/Re stoichiometries, for which we propose an effective interaction model that is then used to generate atomic configurations and make testable predictions at a range of concentrations and formation temperatures.

25 ENERGY STORAGE↗
DOE OSTI2022

Identification of high-dielectric constant compounds from statistical design

Abstract The discovery of high-dielectric materials is crucial to increasing the efficiency of electronic devices and batteries. Here, we report three previously unexplored materials with very high dielectric constants (69 < ϵ < 101) and large band gaps (2.9 < E g (eV) < 5.5) obtained by screening materials databases using statistical optimization algorithms aided by artificial neural networks (ANN). Two of these new dielectrics are mixed-anion compounds (Eu 5 SiCl 6 O 4 and HoClO) and are shown to be thermodynamically stable against common semiconductors via phase diagram analysis. We also uncovered four other materials with relatively large dielectric constants (20 < ϵ < 40) and band gaps (2.3 < E g (eV) < 2.7). While the ANN training-data are obtained from the Materials Project, the search-space consists of materials from the Open Quantum Materials Database (OQMD)—demonstrating a successful implementation of cross-database materials design. Overall, we report the dielectric properties of 17 materials calculated using ab initio calculations, that were selected in our design workflow. The dielectric materials with high-dielectric properties predicted in this work open up further experimental research opportunities.

36 MATERIALS SCIENCE↗
NASA NTRS2006

Analysis of Rapidly Developing Low Cloud Ceilings in a Stable Environment

Forecasters at the Space Meteorology Group (SMG) issue 30 to 90 minute forecasts for low cloud ceilings at the Space Shuttle Landing Facility (TTS) to support Space Shuttle landings. Mission verification statistics have shown ceilings to be the number one forecast challenge for SMG. More specifically, forecasters at SMG are concerned with any rapidly developing clouds/ceilings below 8000 ft in a stable, capped thermodynamic environment. Therefore, the Applied Meteorology Unit (AMU) was tasked to examine archived events of rapid stable cloud formation resulting in ceilings below 8000 ft, and document the atmospheric regimes favoring this type of cloud development. The AMU examined the cool season months of November to March during the years of 1993-2003 for days that had low-level inversions and rapid, stable low cloud formation that resulted in ceilings violating the Space Shuttle Flight Rules. The AMU wrote and modified existing code to identify inversions from the morning (-10 UTC) Cape Canaveral, FL rawinsonde (XMR) during the cool season and output pertinent sounding information. They parsed all days with cloud ceilings below 8000 ft at TTS, forming a database of possible rapidly-developing low ceiling events. Days with precipitation or noticeable fog burn-off situations were excluded from the database. In the first phase of this work, only the daytime hours were examined for possible ceiling development events since low clouds are easier to diagnose with visible satellite imagery. Phase II of this work includes expanding the database to include nighttime cases which is underway as this abstract is being written. For the nighttime cases, the AMU will analyze both the 00 UTC soundings and the 10 UTC soundings to examine those data for the presence of a low-level inversion. The 00 UTC soundings will probably not have a surface-based inversion, but the presence of inversions or "neutral" layers aloft and below 8,000 ft will most likely help define the stable regime, being a thermodynamically "capped" environment. Occurrences of elevated low-level inversions or stable layers will be highlighted in conjunction with nights that experienced a possible development or onset of cloud ceilings below 8,000 ft. Using these criteria to narrow down the database, the AMU will then use archived IR satellite imagery for these possible events. This presentation summarizes the composite meteorological conditions for 20 daytime event days with rapid low cloud ceiling formation and 48 non-events days consisting of advection or widespread low cloud ceilings and describes two sample cases of daytime rapidly-developing low cloud ceilings. The authors will also summarize the work from the nighttime cases and describe a representative sample case from this data set.

Bauman, William H., III↗
NASA NTRS1991

Thermodynamics of acetylene van der Waals dimerization

Integrated band intensities of the 620/cm absorption in (C2H2)2 are measured by FTIR spectroscopy at constant acetylene pressure between 198 and 273 K. These data, in conjunction with ab initio results for (C2H2)2, are used for the statistical evaluation of the equilibrium constant Kp(T) for acetylene-cluster dimerization. The present results are used to clarify the role of molecular clusters in chemical systems at or near equilibrium, in particular in Titan's stratosphere.

Colussi, A. J.↗
DOE OSTI2023

Thermodynamic investigation of the NaCl-KCl salt system from 25 to 950 °C

NaCl-KCl molten salt system has been proposed as a primary component of several promising heat transfer eutectics and fuel host for Generation IV molten salt reactors (MSR). In this work, several key thermodynamic parameters, including high temperature enthalpies, isobaric heat capacities (C p ) and molar enthalpies of mixing (ΔH mix ), of the NaCl -KCl system (NaCl, 75mol% NaCl – 25mol% KCl, 51mol% NaCl – 49mol% KCl, 25mol% NaCl – 75mol% KCl, and KCl) were measured by high temperature drop calorimetry (HTDC) utilizing laser sealed nickel and aluminum crucibles. Salts were checked for phase purity by X-ray diffraction (XRD), and water content by Karl Fischer coulometric titrimetry and thermogravimetric analysis (TGA). Thermo-mechanical analysis (TMA) utilizing custom-built boron nitride (BN) crucibles was employed to determine temperatures of phase transitions (solid $\rightarrow$ liquid) for the salts and plotted against the pseudobinary phase diagram for the NaCl-KCl system. Small deviations (3-10 %) were found among C p values obtained from HTDC, differential scanning calorimetry (DSC), and NIST, comparable to the average uncertainty based on two standard deviations of measured data that are ~6% for DSC and ~3% for HTDC. Additionally, the measured enthalpies and C p values of mixed NaCl-KCl salts (e.g., 51mol% NaCl – 49mol% KCl eutectic) were shown to behave as statistical mixtures of its pure endmembers, consistent with ΔH mix = ~ 0 kJ/mol at 800 °C, and a regular interaction parameter of Ω = 1.20 ± 0.76 kJ/mol. In conclusion, this study represents a step towards improved accuracy and precision in determinations of thermodynamic parameters of molten salts by using DSC, TMA, and HTDC, in completion of the Molten Salt Thermal Properties Database (MSTDB).

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
NASA NTRS1984

Statistical analysis and use of the VAS radiance data

Special radiosonde soundings at 75 km spacings and 3 hour intervals provided an opportunity to learn more about mesoscale data and storm-environment interactions. Relatively small areas of intense convection produce major changes in surrounding fields of thermodynamic, kinematic, and energy variables. The Red River Valley tornado outbreak was studied. Satellite imagery and surface data were used to specify cloud information needed in the radiative heating/cooling calculations. A feasibility study for computing boundary layer winds from satellite-derived thermal data was completed. Winds obtained from TIROS-N retrievals compared very favorably with corresponding values from concurrent rawisonde thermal data, and both sets of thermally-derived winds showed good agreements with observed values.

Fuelberg, H. E.↗
DOE OSTI2020

Variable-density effects in incompressible non-buoyant shear-driven turbulent mixing layers

The asymmetries that arise when a mixing layer involves two miscible fluids of differing densities are investigated using incompressible (low-speed) direct numerical simulations. The simulations are performed in the temporal configuration with very large domain sizes, to allow the mixing layers to reach prolonged states of fully turbulent self-similar growth. Imposing a mean density variation breaks the mean symmetry relative to the classical single-fluid temporal mixing layer problem. Unlike prior variable-density mixing layer simulations in which the streams are composed of the same fluids with dissimilar thermodynamic properties, the density variations are presently due to compositional differences between the fluid streams, leading to different mixing dynamics. Variable-density (non-Boussinesq) effects introduce strong asymmetries in the flow statistics that can be explained by the strongest turbulence increasingly migrating to the lighter fluid side as free-stream density difference increases. Interface thickness growth rates also reduce, with some thickness definitions particularly sensitive to the corresponding changes in alignment between density and streamwise velocity profiles. Additional asymmetries in the sense of statistical distributions of densities at a given position within the mixing layer reveal that fine scales of turbulence are preferentially sustained in lighter fluid, which also is where fastest mixing occurs. These effects influence statistics involving density fluctuations, which have important implications for mixing and more complicated phenomena that are sensitive to the mixing dynamics, such as combustion.

42 ENGINEERING↗