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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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At least 829 records · Page 46
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Toward Understanding the Simulated Phase Partitioning of Arctic Single-Layer Mixed-Phase Clouds in E3SM

21 Mixed-phase clouds are widespread in the Arctic and have substantial impacts on the 22 surface energy budget, sea ice extent, and regional climate. Significant changes are found in the 23 modeled phase partitioning of Arctic mixed-phase clouds in the newly developed U.S. 24 Department of Energy (DOE) Energy Exascale Earth System Model (E3SM) Atmosphere Model 25 version 1 (EAMv1) compared to its predecessor (CAM5/EAMv0). The mixed-phase clouds 26 simulated by EAMv1 is overly dominated by super-cool liquid which is often underestimated by 27 CAM5. Compared to CAM5, EAMv1 has made several important changes in its cloud physical 28 parameterizations, including using CLUBB to unify shallow convection, PBL turbulence, and 29 cloud macrophysics, as well as updating the MG two-moment cloud microphysics scheme and 30 using the CNT heterogeneous ice nucleation scheme to replace the Meyers scheme for mixed- 31 phase clouds. To understand which of the newly-implemented physical parameterizations is 32 responsible for the change of modeled mixed-phase cloud phase partitioning in EAMv1, 33 sensitivity tests are conducted by utilizing the short-term hindcast approach and results are 34 compared to the observations from the ARM Mixed-Phase Arctic Cloud Experiment (M-PACE) 35 field campaign. 36 It is found that although each scheme contributes to the decrease of cloud ice water 37 content (IWC) and increase of cloud liquid water content (LWC), only the combined effect of 38 CLUBB and CNT can explain the significant underestimation of IWC. By examining the budgets 39 of cloud microphysical processes, CLUBB is found to play a dominant role due to the fact that 40 CLUBB does not diagnoses cloud ice phase water in its assumed joint PDF method and thus may 41 not provide sufficient cloud ice to initialize ice phase microphysical processes such as the growth 42 of ice crystals through vapor deposition. Although a more effective heterogeneous ice nucleation 43 may alleviate the underestimation of IWC, the ice phase process in CLUBB requires urgent 44 attention in the future model development.

Zhang, Meng↗
DOE OSTI2025

Convergence of Cloud Droplet Spectral Relative Dispersion During Entrainment‐Mixing Based on Particle‐Resolved Direct Numerical Simulations

Entrainment-mixing processes critically impact cloud microphysical properties, but their effects on the relative dispersion (d) of cloud droplet size distributions (CDSDs) remain elusive. A direct numerical simulation model is initialized with different CDSDs to fill the gap. These results show that d decreases for broad CDSDs and increases for narrow ones, ultimately converging to approximately 0.5 regardless of initial CDSDs during the evaporation-dominated mixing stage. The supersaturation fluctuation and the shape of CDSDs jointly influence the convergence behavior of d. Further sensitivity tests show that the initial microphysical/dynamical/thermodynamical conditions exert negligible effects on the final converged value of d but affect the convergence rate (k). The k generally increases with increasing droplet number concentration and dissipation rate, and increases with decreasing liquid water content, relative humidity of entrained air, and mixing fraction of cloudy air. A conceptual model with two timescales is proposed; k and the timescales are negatively correlated, meaning that slow mixing and/or evaporation process results in slow convergence of d. In conclusion, this finding provides an important reference for improving understanding and parameterization of d during the entrainment-mixing processes.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2016

Understanding misfit strain releasing mechanisms via molecular dynamics simulations of CdTe growth on {112}zinc-blende CdS

Molecular dynamics simulations have been used to analyse microstructures of CdTe films grown on {112} surfaces of zinc-blende CdS. Interestingly, CdTe films grow in <331> orientations as opposed to <112> epitaxial orientations. At the CdTe-{331}/CdS-{112} interface, however, there exists an axis that is parallel to the <110> orientation of both CdS and CdTe. It is the direction orthogonal to this <110> that becomes different, being <116> for CdTe and <111> for CdS, respectively. Missing CdTe-{110} planes are found along the <110> axis, suggesting that the misfit strain is released by the conventional misfit dislocation mechanism along this axis. In the orthogonal axis, the misfit strain is found to be more effectively released by the new grain orientation mechanism. Our finding is supported by literature experimental observations of the change of growth direction when Cd 0.96 Zn 0.04 Te films are deposited on GaAs. Lastly the analyses of energetics clearly demonstrate the cause for the formation of the new orientation, and the insights gained from our studies can help understand the grain structures experimentally observed in lattice mismatched systems.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2020

A Clustering-Based Scenario Generation Framework for Power Market Simulation with Wind Integration

A critical step in stochastic optimization models of power system analysis is to select a set of appropriate scenarios and significant numbers of scenario generation methods exist in the literature. This paper develops a clustering based scenario generation method, which aims to improve the performance of existing scenario generation techniques by grouping a set of correlated wind sites into clusters according to their cross-correlations. Copula based models are utilized to model spatiotemporal correlations and the Gibbs sampling is then used to generate scenarios for day-ahead markets. Our results show that the generated scenarios based on clustered wind sites outperform existing approaches in terms of reliability and sharpness and can reduce the total computational time for scenario generation and reduction significantly. The clustering-based framework can therefore provide a better support for real-world market simulations with high wind penetration.

data visualization↗
DOE OSTI2026

Direct numerical simulations of activation and deactivation in turbulent atmospheric clouds

Significant knowledge gaps remain in our understanding of turbulence–cloud–aerosol interactions in the Earth's atmosphere, and direct numerical simulation (DNS) has increasingly become an indispensable tool to fill such critical knowledge gaps. Here, this study is an extension of our previous DNS model [Gao et al., J. Geophys. Res.: Atmos., 123(4), 2194–2214 (2018)], with a focus on the activation of aerosol particles into cloud droplets and deactivation of cloud droplets into aerosol particles in a microscale cloud environment. The effects of turbulence intensity, particle curvature, and solute, as well as the initial distributions of the aerosol particles (monodisperse or polydisperse) are investigated. The governing equations for the flow of air, temperature, and water vapor mixing ratio are solved numerically in the Eulerian fashion, assuming homogeneous and isotropic turbulence. The dynamics of the aerosol and cloud particles are calculated with the Lagrangian particle tracking method. The results show that the deviations of the thermodynamic variables from their respective means are significantly reduced, the activation process appears to be delayed, and the deactivation process occurs more rapidly, as the turbulence intensity is increased. The inclusion of particle curvature and solute effects, as well as polydispersity, tends to retard the activation of aerosols into cloud droplets. It is also observed that fluctuations in supersaturation broaden the spread of particle radii, and the broadening is followed by a narrowing as turbulent homogenization reduces thermodynamic fluctuations over time.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Enhancing the formation of ionic defects to study the ice Ih/XI transition with molecular dynamics simulations

Ice Ih, the common form of ice in the biosphere, contains proton disorder. Its proton-ordered counterpart, ice XI, is thermodynamically stable below 72 K. However, the formation of ice XI is kinetically hindered, and experimentally it is obtained by doping with KOH. Doping creates ionic defects that promote the migration of protons and the associated change in proton configuration. In this article, we mimic the effect of doping with a bias potential that enhances the formation of ionic defects in molecular dynamics simulations. The recombination of the ions thus formed proceeds through fast migration of the hydroxide along hydrogen bond loops, providing a physical and expedite way to change the proton configuration. Here, a key ingredient of this approach is a machine learning potential trained with density functional theory data and capable of modelling molecular dissociation. We exemplify the usefulness of this idea by studying the order-disorder transition using an appropriate order parameter that distinguishes the proton environments in ice Ih and XI. We calculate the changes in free energy, enthalpy, and entropy associated with the transition. Our estimated entropy agrees with experiment within the error bars of the calculation.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2023

Overview of recent observations and simulations from the American WAKE experimeNt (AWAKEN) field campaign

The American WAKE experimeNt (AWAKEN) is a large-scale field campaign focused on gathering new detailed observations of wind farm–atmosphere interactions for improved understanding of wind farm physics and overall performance. The field campaign, centered around five wind farms in northern Oklahoma, began in September 2022 and will run through at least October 2023. This paper summarizes some of the initial observations and simulations performed as part of the AWAKEN project.

17 WIND ENERGY↗
DOE OSTI2015

Capacitive charge storage at an electrified interface investigated via direct first-principles simulations [Direct Simulation of Capacitive Charging of Graphene and Implications for Supercapacitor Design]

Understanding the impact of interfacial electric fields on electronic structure is crucial to improving the performance of materials in applications based on charged interfaces. Supercapacitors store energy directly in the strong interfacial field between a solid electrode and a liquid electrolyte; however, the complex interplay between the two is often poorly understood, particularly for emerging low-dimensional electrode materials that possess unconventional electronic structure. Typical descriptions tend to neglect the specific electrode-electrolyte interaction, approximating the intrinsic “quantum capacitance” of the electrode in terms of a fixed electronic density of states. Instead, we introduce a more accurate first-principles approach for directly simulating charge storage in model capacitors using the effective screening medium method, which implicitly accounts for the presence of the interfacial electric field. Applying this approach to graphene supercapacitor electrodes, we find that results differ significantly from the predictions of fixed-band models, leading to improved consistency with experimentally reported capacitive behavior. The differences are traced to two key factors: the inhomogeneous distribution of stored charge due to poor electronic screening and interfacial contributions from the specific interaction with the electrolyte. Lastly, our results are used to revise the conventional definition of quantum capacitance and to provide general strategies for improving electrochemical charge storage, particularly in graphene and similar low-dimensional materials.

25 ENERGY STORAGE↗
DOE OSTI2016

Reinventing atomic magnetic simulations with spin-orbit coupling

We propose a powerful extension to the combined molecular and spin dynamics method that fully captures the coupling between the atomic and spin subsystems via spin-orbit interactions. Moreover, the foundation of this method lies in the inclusion of the local magnetic anisotropies that arise as a consequence of the lattice symmetry breaking due to phonons or crystallographic defects. By using canonical simulations of bcc iron with the system coupled to a phonon heat bath, we show that our extension enables the previously unachievable angular momentum exchange between the atomic and spin degrees of freedom.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2017

Simulation–Extrapolation for Bias Correction with Exposure Uncertainty in Radiation Risk Analysis Utilizing Grouped Data

Summary In observational epidemiological studies, the exposure that is received by an individual often cannot be precisely observed, resulting in measurement error, and a common approach to dealing with measurement error is regression calibration (RC). Use of RC, which requires assumptions about the distribution of unknown error-free (true) variables, leads to concern about the possibility of bias due to misspecification of that distribution. The simulation–extrapolation (SIMEX) method, in contrast, does not require a distributional assumption. However, analyses of large cohorts may be performed by using grouped or person-year data, and application of SIMEX to grouped data is not straightforward, particularly when there is a mixture of classical and Berkson measurement errors. We compared RC and SIMEX with grouped data analyses to assess robustness of the RC method to misspecification of the true dose distribution. We also applied SIMEX assuming mixtures of classical and Berkson errors and compared the results with those obtained by using RC for classical error only. SIMEX had less bias than RC and performed well regardless of the true dose distribution, whereas RC based on a misspecified true dose distribution showed greater bias than when based on the correctly specified true dose distribution.

Misumi, Munechika↗