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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 271 records · Page 15
All sourcesNASA NTRSDOE OSTI
NASA NTRS2020

Quantification of the Land Surface and Brown Ocean Influence on Tropical Cyclone Intensification Over Land

An investigation of TC Kelvin in February 2018 over northeast Australia was conducted to understand the mechanisms of the Brown Ocean effect (BOE), and to develop a comprehensive analysis framework for landfalling tropical cyclones (TCs) in the process. NASA’s Land Information System (LIS) coupled to the NASA Unified WRF (NU-WRF) system was employed as the numerical model framework for 12 land/soil moisture perturbation experiments. Impacts of soil moisture and surface enthalpy flux conditions on TC Kelvin were investigated by closely evaluating simulated track and intensity, midlevel atmospheric thermodynamic properties, vertical wind shear, total precipitable water (TPW), and surface moisture flux. The results suggest that there were recognized differentiations among the sensitivity simulations as a result of land surface (e.g., soil moisture and texture) conditions. However, the intensification of TC Kelvin over land was more strongly related to atmospheric moisture advection and the diurnal cycle of solar radiation (i.e., radiative cooling) than to overall soil moisture conditions or surface fluxes. The analysis framework employed here for TC Kelvin can serve as a foundation to specifically quantify the factors governing the BOE. It also demonstrates that the BOE is not a binary influence (i.e. all or nothing), but instead operates in a continuum from largely to minimally influential such that it could be utilized to help improve prediction of inland effects for all landfalling TCs.

Brown Ocean Effect↗
NASA NTRS2004

A Study of the Response of Deep Tropical Clouds to Mesoscale Processes: Sensitivities to Microphysics, Radiation, and Surface Fluxes - Part 2

The Goddard Cumulus Ensemble (GCE) model is used to examine the sensitivities of surface fluxes, explicit radiation, and ice microphysical processes on multi-day simulations of deep tropical convection over the Tropical Ocean Global Atmosphere Coupled Ocean-Atmosphere Response Experiment (TOGA COARE). The simulations incorporate large-scale advective temperature and moisture forcing, as well as large-scale momentum, that are updated every time step on a periodic lateral boundary grid. This study shows that when surface fluxes are eliminated, the mean atmosphere is much cooler and drier, convection and CAPE are much weaker, precipitation is less, and cloud coverage in stratiform regions much greater. Surface fluxes using the TOGA COARE flux algorithm are weaker than with the aerodynamic formulation, but closer to the observed fluxes. In addition, similar trends noted above for the case without surface fluxes are produced for the TOGA flux case, albeit to a much lesser extent. The elimination of explicit shortwave and longwave radiation is found to have only minimal effects on the mean thermodynamics, convection, and precipitation. However explicit radiation does have a significant impact on cloud temperatures and structure above 200 mb and on the overall mean vertical circulation. The removal of ice processes produces major changes in the structure of the cloud. Much of the liquid water is transported aloft and into anvils above the melting layer (600 mb), leaving narrow, but intense bands of rainfall in convective regions. The elimination of melting processes leads to greater hydrometeor mass below the melting layer, and produces a much warmer and moister boundary layer, leading to a greater mean CAPE. Finally, the elimination of the graupel species has only a small impact on mean total precipitation, thermodynamics, and dynamics of the simulation, but does produce much greater snow mass just above the melting layer. Some of these results differ from previous CRM studies of tropical systems, which is likely due to the type of simulated system, total time integration, and model setup.

Johnson, Daniel↗
DOE OSTI2020

Evaluating diffusion and the thermodynamic factor for binary ionic mixtures

Molecular dynamics (MD) simulations are a powerful tool for the calculation of transport properties in mixtures. Not only are MD simulations capable of treating multicomponent systems, they are also applicable over a wide range of temperatures and densities. In plasma physics, this is particularly important for applications such as inertial confinement fusion. While many studies have focused on the effect of plasma coupling on transport properties, here we focus on the effects of mixing. We compute the thermodynamic factor, a measure of ideal/non-ideal mixing, for three binary ionic mixtures. Here, we consider mixtures of hydrogen and carbon, hydrogen and argon, and argon and carbon, each at 500 randomly generated state points in the warm dense matter and plasma regimes. The calculated thermodynamic factors indicate different mixing behavior across phase space, which can significantly affect the corresponding mutual diffusion coefficients. As MD simulations are still computationally expensive, we apply modern data science tools to predict the thermodynamic factor over a large phase space. Further, we propose a more accurate approximation to the mutual diffusion coefficient than the commonly applied Darken relation.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2021

Curvature Energetics Determined by Alchemical Simulation on Four Topologically Distinct Lipid Phases

The relative curvature energetics of two lipids are tested using thermodynamic integration (TI) on four topologically distinct lipid phases. Simulations use TI to switch between choline headgroup lipids (POPC; that prefers to be flat) and ethanolamine headgroup lipids (POPE; that prefer, for example, the inner monolayer of vesicles). Here, the thermodynamical moving of the lipids between planar, inverse hexagonal (H II ), cubic (Q II ; Pn3m space group), and vesicle topologies reveals differences in material parameters that were previously challenging to access. The methodology allows for predictions of two important lipid material properties: the difference in POPC/POPE monolayer intrinsic curvature (ΔJ 0 ) and the difference in POPC/POPE monolayer Gaussian curvature modulus (Δ$\bar{κ_m}$), both of which are connected to the energetics of topological variation. Analysis of the TI data indicates that, consistent with previous experiment and simulation, the J 0 of POPE is more negative than POPC (ΔJ 0 = –0.018 ± 0.001 Å –1 ). The theoretical framework extracts significant differences in $\bar{κ_m}$ of which POPE is less negative than POPC by 2.0 to 4.0 kcal/mol. The range of these values is determined by considering subsets of the simulations, and disagreement between these subsets suggests separate mechanical parameters at very high curvature. Finally, the fit of the TI data to the model indicates that the position of the pivotal plane of curvature is not constant across topologies at high curvature. Overall, the results offer insights into lipid material properties, the limits of a single HC model, and how to test them using simulation.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

Influence of fuel ash on the recoverability of copper from the spent material of chemical looping combustion

Chemical looping combustion (CLC) is an advanced energy production technology that inherently separates the CO 2 generated. The oxygen needed for fuel conversion is supplied by the oxygen carrier. When using copper-based oxygen carriers, oxygen carrier attrition is a challenge to the process economics, unless the attrited copper that is mixed with fuel ash in the spent material can be recovered by, for instance, acid leaching. However, fuel ash may transform the attrited copper into certain complexes of low leachability (e.g., CuAl 2 O 4 ), hindering the copper recovery. In this study, the copper content in the spent material was first evaluated. The effects of ash composition and copper content on the occurrence mode of copper in spent material were predicted by thermodynamic modeling. Redox cycles of simulated spent materials based on various coal ashes were performed to reveal the characteristics of CuAl 2 O 4 /CuFe 2 O 4 formation. The CuO-Al 2 O 3 reaction was investigated under the temperatures and solid residence times experienced in CLC. The materials were analyzed by X-ray diffraction. The results suggest that the fuel ash with a high Al/Ca ratio may lower the recoverability of copper when the temperature is above 925 °C. The slow formation of CuFe 2 O 4 is not expected to affect the copper recovery.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
NASA NTRS2019

Hybrid Simulation of Solar-Wind-Like Turbulence

We present 2.5D hybrid simulations of the spectral and thermodynamic evolution of an initial state of magnetic field and plasma variables that in many ways represents solar wind fluctuations. In accordance with Helios near-Sun high-speed stream observations, we start with Alfvénic fluctuations along a mean magnetic field in which the fluctuations in the magnitude of the magnetic field are minimized. Since fluctuations in the radial flow speed are the dominant free energy in the observed fluctuations, we include a field-aligned v∥(k⊥) with an k(exp −1) spectrum of velocity fluctuations to drive the turbulent evolution. The flow rapidly distorts the Alfvénic fluctuations, yielding spectra (determined by spacecraft-like cuts) transverse to the field that become comparable to the k∥ fluctuations, as in spacecraft observations. The initial near constancy of the magnetic field is lost during the evolution; we show this also takes place observationally. We find some evolution in the anisotropy of the thermal fluctuations, consistent with expectations based on Helios data. We present 2D spectra of the fluctuations, showing the evolution of the power spectrum and cross-helicity. Despite simplifying assumptions, many aspects of simulations and observations agree. The greatly faster evolution in the simulations is at least in part due to the small scales being simulated, but also to the non-equilibrium initial conditions and the relatively low overall Alfvénicity of the initial fluctuations.

Roberts, D. Aaron↗
NASA NTRS1998

A Quantitative Investigation of Entrainment and Detrainment in Numerically Simulated Convective Clouds: Simulations of Cumulonimbus Clouds - Pt. 2

Deep cumulonimbus clouds are simulated using a model that makes accurate diagnoses of entrainment and detrainment rates and of the properties of entrained and detrained air. Clouds generated by a variety of initial thermodynamic soundings are compared. In the simulations, updraft entrainment rates are large near and above cloud base, through the entire depth of the conditionally unstable layer. Stronger updrafts in a more unstable environment are better able to entrain relatively undisturbed environmental air, while weaker updrafts can entrain only air that has been modified by the clouds. When the maximum buoyancy is large, the updraft includes parcels with a wide range of buoyancies, while weaker clouds are more horizontally uniform. Strong downdrafts originate from levels at which updrafts detrain, and their mass flux depends on the mass flux of the updraft. The magnitude of mixing between cloud and environment, not the entrainment rate, varies inversely with the cloud radius. How much of the mixed air is entrained depends on the buoyancy.

Cohen, Charles↗
DOE OSTI2021

Drying model of a high salt content cementitious waste form: Effect of capillary forces and salt solution

Highlights: • Drying model for a high salt content cementitious waste form is developed. • Water vapor diffusion and capillary liquid flow are distinguished. • Capillary and salt solution effects are considered in vapor-liquid equilibrium. A water transport model coupling capillary liquid flow with vapor diffusion is developed to describe the drying process for a cementitious waste form with high salinity porewater. Vapor-liquid equilibrium is formulated as the driving force for vapor diffusion and the model accounts for pore capillary and high salinity effects on water thermodynamic activity. Pore filling and porewater surface tension as a function of pore size distribution and water saturation have been quantified for the material. Geochemical speciation modeling is used to simulate porewater activity as a function of composition over the range of saturation. The theoretical relationship between relative humidity and water saturation generally agrees with experimental measurement, and the developed model is capable of predicting drying rates under various external relative humidity conditions. The model was developed to be incorporated into reactive transport models considering the effects of drying such as salt redistribution and efflorescence.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Crossover from Rouse to Reptation Dynamics in Salt-Free Polyelectrolyte Complex Coacervates

Considerable interest in the dynamics and rheology of polyelectrolyte complex coacervates has been motivated by their industrial application as viscosity modifiers. A central question is the extent to which classical Rouse and reptation models can be applied to systems where electrostatic interactions play a critical role on the thermodynamics. By relying on molecular simulations, we present a direct analysis of the crossover from Rouse to reptation dynamics in salt-free complex coacervates as a function of chain length. This crossover shifts to shorter chain lengths as electrostatic interactions become stronger, which corresponds to the formation of denser coacervates. To distinguish the roles of Coulomb interactions and density, here we compare the dynamics of coacervates to those of neutral, semidilute solutions at the same density. Both systems exhibit a universal dynamical behavior in the connectivity-dominated (subdiffusion and normal diffusion) regimes, but the monomer relaxation time in coacervates is much longer and increases with increasing Bjerrum length. This is similar to the cage effect observed in glass-forming polymers, but the local dynamical slowdown is caused here by strong Coulomb attractions (ion pairing) between oppositely charged monomers. Our findings provide a microscopic framework for the quantitative understanding of coacervate dynamics and rheology.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Confronting Large‐Eddy Simulations With Stereo Camera Data by Means of Reconstructed Hemispheric Cloud Size Distributions

High-resolution hemispheric camera images at a meteorological site in western Germany are used to analyze the multi-dimensional spatial characteristics of continental cumulus cloud fields, and to evaluate Large-Eddy Simulations on this aspect. Traditional non-hemispheric cloud-detecting instruments provide additional reference data. The main model-observation comparison focuses on cloud size distributions (CSDs), employing two methods: (a) directly using three-dimensional model fields, direct CSDs, and (b) using rendered hemispheric images of the model fields as produced by a camera simulator based on path-tracing. In the latter method, both the real and rendered images are used to three-dimensionally reconstruct the cloud fields, yielding hemispheric CSDs. Advantages of hemispheric comparisons over more classic approaches include (a) fair comparisons between model and data, and (b) full use of the enhanced resolutions and hemispheric spatial coverage of the camera imagery. Basic evaluation of the simulations demonstrates good agreement on thermodynamic structure and its diurnal cycle. Cloud heights and cloud cover are intercompared between the model, camera data and other instrumentation, providing insight into their structural differences. A consistent alignment is found between the hemispheric CSDs from both the model and the cameras. Power law fits reveal structurally lower exponents in hemispheric CSDs compared to non-hemispheric CSDs, which particularly caution against directly comparing hemispheric CSDs to non-hemispheric distributions. This result is robust for sample size and fitting method. These findings inform future use of hemispheric camera systems for studying cumulus cloud field morphology and model evaluation.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

High-throughput approach for investigating interdiffusion in medium- and high-entropy alloys

Interdiffusion experiments are usually time-consuming and tedious since diffusion couples must be annealed at several temperatures for a long time. The efforts required to study interdiffusion in multicomponent alloys increase dramatically as multiple diffusion couples are required to cover broad composition ranges and determine the diffusivities of individual elements in different chemical environments. To circumvent this challenge, we present a high-throughput approach applicable to single-phase and compositionally complex alloys, which are assumed to approximate ideal solid solutions. Here, a simple diffusion-multiple experiment combined with a physically based kinetic model is proposed to efficiently determine the diffusion coefficients of the constituent elements in quaternary CrFeCoNi alloys. Compared with tracer diffusivities reported in the literature, the results, thus, obtained do not differ by more than a factor of 2 and were obtained from a single interdiffusion experiment. In contrast, the diffusivities simulated with commercial mobility and thermodynamic databases are strongly overestimated by a factor ranging from 1 to 16. Therefore, our approach enables high-throughput determination of diffusivities and can help in the design of alloys for high-temperature applications where diffusion plays a key role.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Accurate and efficient parameterization of an atomic cluster expansion (ACE) potential for ammonia under extreme conditions

We present a machine learning interatomic potential for ammonia designed to capture its complex multiphase behavior, including both molecular and superionic phases. The potential is based on the atomic cluster expansion (ACE) formulation and has been parameterized to facilitate high-fidelity molecular dynamics simulations of ammonia under extreme conditions, for pressures up to 100 GPa and for temperatures above 500 K and up to 6000 K. A diverse range of configurations was generated through high-quality ab initio molecular dynamics simulations, covering insulating and superionic ice phases, liquid ammonia, molecular nitrogen (N 2 ) and hydrogen (H 2 ), and metastable compounds that form upon dissociation, including $NH^{+}_{4}$, $H^{+}_{3}$, N 2 H 4 , and N 3 H. We demonstrate that the ammonia ACE potential accurately reproduces experimental and density functional theory predicted isotherms and Hugoniots. Crucially, the potential is able to capture the intricate phase behavior of ammonia, including the transition from insulating molecular fluid to the superionic phase. This work provides a robust interatomic potential that can be used for large-scale, accurate simulations of ammonia under extreme thermodynamic conditions, offering a powerful tool for investigating its behavior in various phases and applications.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

An atomic cluster expansion (ACE) potential for water under extreme conditions

We present a machine learning interatomic potential for water designed to capture its complex multiphase behavior, including both molecular and superionic ice phases. The potential is based on the atomic cluster expansion (ACE) formulation and has been parameterized to enable high-fidelity molecular dynamics simulations of water under extreme conditions, for pressures up to 100 GPa and for temperatures between 500 and 6000 K. A diverse range of configurations was generated through ab initio molecular dynamics (AI-MD) simulations, covering insulating and superionic ice phases, liquid water, and dissociated plasma phase. We demonstrate that the H 2 O ACE potential accurately reproduces experimental and DFT predicted isotherms and Hugoniots. Crucially, the potential is able to capture the intricate phase behavior of water, including the transition from molecular fluid to the appropriate solid ice phases, and the superionic ice phases. This work provides a robust interatomic potential that can be used for large-scale, accurate simulations of water under extreme thermodynamic conditions.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2024

CIGS Technology Advancement via Fundamental Modeling of Defect/Impurity Interactions (Final Technical Report)

The primary goals of the proposed work were to provide modeling tools (and the associated insight which comes along with model development) for design and optimization of CuIn x Ga 1-x Se 2 (CIGS) and CdSeTe (CST) solar cell manufacturing processes and to establish the foundation for comprehensive end-to-end predictive modeling tools to enable optimization of thin film photovoltaic technology for performance, cost, yield, and reliability. The initial focus of efforts within this project was to develop coupled process/optical/device models for CIGS PV technology and to work with Siva Power to apply that TCAD (technology computer-aided design) system to improve the efficiency and reduce manufacturing costs for CIGS solar cells. Our approach to that end was to generate an extensive database of DFT calculations and to use those calculations via statistical thermodynamics methods and Monte Carlo simulation to develop and characterize models for the behavior of native defects as well as intentional and unintentional impurities, including the redistribution of the primary components of CIGS films. Increased effort went toward coupling those models for defect behavior and composition evolution to the performance of multicrystalline CIGS solar cells via prediction of doping level and recombination lifetime as function of manufacturing process. In the second budget period, the project pivoted to developing a similar system for the CdSeTe system, focused especially on understanding the role of Se/Te alloy concentration. Execution of the project resulted in the successful development of TCAD systems for both CIGS and CdSeTe thin film PV within the Synopsys Sentaurus framework by utilizing the Alagator interface. In the first budget period of the project, we developed quantitative models for the major components of CIGS PV and implemented them within a framework that couples process, optical, and device simulation. From the insights we have gained, we identified novel opportunities for enhancing CIGS solar cell performance and have laid the groundwork to further optimize the layer structure, composition profile, and thermal cycles for substantially improved efficiency and lower manufacturing costs. For the CIGS system, process changes to achieve greater than 1% absolute enhancement in efficiency were identified, but testing of those approaches was stymied by lack of a domestic CIGS manufacturing partner after the closure of Siva Power as well as Miasole. For CdSeTe, a fully capable TCAD system only became ready to apply near the end of the project period, so substantial opportunities remain to apply those models to enhance the leading thin film PV technology.

14 SOLAR ENERGY↗
DOE OSTI2025

Model form and sensitivity analysis of CALPHAD-based nucleation models in b-stabilized Ti alloys

Accurate prediction of α-phase nucleation and growth in β-stabilized titanium alloys is crucial for designing heat treatments to optimize mechanical properties in additively manufactured lightweight components. Ideally, predictions of nucleation and growth would incorporate both top-down observations of past experimental heat treatments and bottom-up modeling of phase transformations; however, the appropriate method of combining these information sources is not self-evident. Combining top-down and bottom-up information requires a unified form of model that can connect between spatiotemporal scales, as well as sets of fitting parameters that can be identified by each data source. The selection of which parameters to fit to which data source can be made based on expert opinion, or by performing a sensitivity analysis. In solid-solid nucleation, direct observation of the nucleation and growth process is challenging. Most data on the heat treatment-controlled phase transformations are not in-situ. To predict the process and outcome of the nucleation, growth and coarsening of precipitates, theoretical models of the nucleation pathway are used to bridge the gap. Many sources of uncertainty affect the modeling of this nucleation process. It can be influenced by small variations in the thermomechanical processing history, chemical composition, and initial microstructure. If molecular dynamics (MD) simulations are used to determine thermodynamic quantities and inform CALPHAD modeling, additional uncertainty can be introduced and accounted for using Bayesian methods. Top-down uncertainties require additional steps to quantify. The influence of nucleation model form on the sensitivity of predictions to input parameters and physical conditions is the focus of this study. Classical nucleation theory (CNT) allows modeling to formulate the nucleation as homogeneous or, more commonly, heterogeneous. Non-classical nucleation models are also increasingly explored as a means of reconciling top-down and bottom-up data. In this study, the sensitivity of the intragranular nucleation of α in a β-annealed, slow-cooled aging (BASCA) heat treatment of β-stabilized Ti5553 alloy is explored using CNT and both heterogeneous and homogeneous assumptions. The Kampmann-Wagner Numerical model of precipitate nucleation and growth is employed. Using open-source tools (pyCalphad and thermodynamic modeling of TiMo as a surrogate system, a sensitivity analysis is performed to measure variations in key parameters, including chemical driving force, interfacial energy, and diffusivity, as they relate to predictions of precipitate number density. The inclusion of top-down and bottom-up data in selection of nucleation model form is discussed.

Rodriguez Negron, A. M.↗
DOE OSTI2024

Diurnal evolution of non-precipitating marine stratocumuli in a large-eddy simulation ensemble

Abstract. We explore the cloud system evolution of non-precipitating marine stratocumuli with a focus on the impacts of the diurnal cycle and free-tropospheric (FT) humidity based on an ensemble of 244 large-eddy simulations generated by perturbing initial thermodynamic profiles and aerosol conditions. Cases are categorized based on their degree of decoupling and the cloud liquid water path (LWPc, based on model columns with cloud optical depths greater than one). A budget analysis method is proposed to analyze the evolution of cloud water in both coupled and decoupled boundary layers. More coupled clouds start with a relatively low LWPc and cloud fraction (fc) but experience the least decrease in LWPc and fc during the daytime. More decoupled clouds undergo greater daytime reduction in LWPc and fc, especially those with higher LWPc at sunrise because they suffer from faster weakening of net radiative cooling. During the nighttime, a positive correlation between FT humidity and the LWPc emerges, consistent with higher FT humidity reducing both radiative cooling and the humidity jump, both of which reduce entrainment and increase LWPc. The LWPc is more likely to decrease during the nighttime for a larger LWPc and greater inversion base height (zi), conditions under which entrainment dominates as turbulence develops. In the morning, the rate of the LWPc reduction depends on the LWPc at sunrise, zi, and the degree of decoupling, with distinct contributions from subsidence and radiation.

Chen, Yao-Sheng (ORCID:0000000208354132)↗