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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 325 records · Page 18
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Real-Time Time-Dependent Density Functional Theory for Simulating Nonequilibrium Electron Dynamics

The explicit real-time propagation approach for time-dependent density functional theory (RT-TDDFT) has increasingly become a popular first-principles computational method for modeling various time-dependent electronic properties of complex chemical systems. Here, in this Perspective, we provide a nontechnical discussion of how this first-principles simulation approach has been used to gain novel physical insights into nonequilibrium electron dynamics phenomena in recent years. Following a concise overview of the RT-TDDFT methodology from a practical standpoint, we discuss our recent studies on the electronic stopping of DNA in water and the Floquet topological phase as examples. Our discussion focuses on how RT-TDDFT simulations played a unique role in deriving new scientific understandings. We then discuss existing challenges and some new advances at the frontier of RT-TDDFT method development for studying increasingly complex dynamic phenomena and systems.

Hamiltonians↗
DOE OSTI2020

Interactions Between the Amazonian Rainforest and Cumuli Clouds: A Large‐Eddy Simulation, High‐Resolution ECMWF, and Observational Intercomparison Study

Abstract The explicit coupling at meter and second scales of vegetation's responses to the atmospheric‐boundary layer dynamics drives a dynamic heterogeneity that influences canopy‐top fluxes and cloud formation. Focusing on a representative day during the Amazonian dry season, we investigate the diurnal cycle of energy, moisture and carbon dioxide at the canopy top, and the transition from clear to cloudy conditions. To this end, we compare results from a large‐eddy simulation technique, a high‐resolution global weather model, and a complete observational data set collected during the GoAmazon14/15 campaign. The overall model‐observation comparisons of radiation and canopy‐top fluxes, turbulence, and cloud dynamics are very satisfactory, with all the modeled variables lying within the standard deviation of the monthly aggregated observations. Our analysis indicates that the timing of the change in the daylight carbon exchange, from a sink to a source, remains uncertain and is probably related to the stomata closure caused by the increase in vapor pressure deficit during the afternoon. We demonstrate quantitatively that heat and moisture transport from the subcloud layer into the cloud layer are misrepresented by the global model, yielding low values of specific humidity and thermal instability above the cloud base. Finally, the numerical simulations and observational data are adequate settings for benchmarking more comprehensive studies of plant responses, microphysics, and radiation.

Vilà‐Guerau de Arellano, J.↗
DOE OSTI2020

The Role of the Mean State on MJO Simulation in CESM2 Ensemble Simulation

Here we examine the role of the mean state in the propagation of the Madden-Julian oscillation (MJO) over the Maritime Continent (MC). We use an ensemble of simulations made with a single model—the Community Earth System Model version 2—to assess the effect of the mean state that is unaffected by that of model components such as parameterization schemes. Results show that the background meridional moisture gradient is much steeper over the MC region in the periods with a stronger MJO propagation. Column water vapor budget of the MJO strongly suggests that the simulated mean state affects MJO via its impacts on moisture dynamics—a greater advection of mean moisture by MJO wind in the MC region is responsible for the anomalous MJO activity.

58 GEOSCIENCES↗
DOE OSTI2021

The Influence of Ocean Coupling on Simulated and Projected Tropical Cyclone Precipitation in the HighResMIP–PRIMAVERA Simulations

This study aims to quantify the impacts of atmosphere–ocean coupling on simulated and projected tropical cyclone (TC) precipitation globally. We used global climate model (GCM) simulations over 1950–2050 from the High Resolution Model Intercomparison Project (HighResMIP) and compared its fully coupled atmosphere–ocean GCMs (AOGCMs) with atmosphere-only GCMs (AGCMs). We find that ocean coupling generally leads to decreased TC precipitation over ocean and land. Large-scale sea surface temperature (SST) biases are critical drivers of the precipitation difference, with secondary contributions from local TC–ocean feedbacks via SST cold wakes. The two driving factors, attributed to ocean coupling in the AOGCMs, influence TC precipitation in association with decreased TC intensity and specific humidity. The AOGCMs and AGCMs consistently project TC precipitation increases in 2015–2050 relative to 1950–2014 over ocean for all basins, and for landfalling TCs in the North Atlantic and western North Pacific.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Evaluation of E3SM Simulated Aerosols and Aerosol‐Cloud Interactions Across GCM and Convection‐Permitting Scales

This paper introduces an Earth system modeling testbed for predicting aerosols and aerosol‐cloud interactions (ACIs) at convection‐permitting scales. Using the Energy Exascale Earth System Model (E3SM) version 2 with a four‐mode Modal Aerosol Module, we conduct simulations at 3.25 km resolution on a regionally refined mesh (RRM) across four regions with distinct aerosol and cloud regimes. Results are compared with the standard 100 km E3SM configuration and evaluated against satellite, aircraft, and ground‐based observations. We find that increasing model resolution improves heavy precipitation simulation but amplifies positive bias in light drizzle at coarse resolution. These resolution‐induced changes affect cloud and aerosol properties to varying degrees across regions. Generally, cloud cover and liquid water path (LWP) show better agreement with satellite retrievals at 3.25 km, though surface‐based comparisons suggest otherwise. Aerosol composition remains poorly represented at both resolutions. The RRM increases Aitken mode aerosol number concentrations via enhanced new particle formation. However, accumulation mode aerosols are decreased at higher resolution as aerosol removals become more efficient. This partially contributes to fewer cloud condensation nuclei (CCN) and lower cloud droplet number concentrations (N d ), which produces larger model biases in some scenarios. These findings suggest that solely increasing horizontal resolution to kilometer scales is insufficient to broadly improve aerosol and cloud predictions without concurrent advancements in physical and chemical process representations. Nonetheless, the RRM moderately improves key ACI relationships such as CCN‐N d correlation, reflecting enhanced aerosol activation representation. The LWP‐N d relationship is also better captured by RRM, suggesting a better characterization of LWP adjustment.

Huang, Meng [Pacific Northwest National Laboratory↗
DOE OSTI2019

Quantum simulations of excited states with active-space downfolded Hamiltonians

Many-body techniques based on the double unitary coupled cluster ansatz (DUCC) can be used to downfold electronic Hamiltonians into low-dimensional active spaces. It can be shown that the resulting dimensionality reduced Hamiltonians are amenable for quantum computing. Recent studies performed for several benchmark systems using quantum phase estimation (QPE) algorithms demonstrated that these formulations can recover a significant portion of ground-state dynamical correlation effects that stem from the electron excitations outside of the active space. These results have also been confirmed in studies of ground-state potential energy surfaces using quantum simulators. In this letter, we study the effectiveness of the DUCC formalism in describing excited states. We also emphasize the role of the QPE formalism and its stochastic nature in discovering/identifying excited states or excited-state processes in situations when the knowledge about the true configurational structure of a sought after excited state is limited or postulated (due to the specific physics driving excited-state processes of interest). In this context, we can view the QPE algorithm as an engine for verifying various hypotheses for excited-state processes and providing statistically meaningful results that correspond to the electronic state(s) with the largest overlap with a postulated configurational structure. We illustrate these ideas on examples of strongly cor- related molecular systems, characterized by small energy gaps and high density of quasi-degenerate states around the Fermi level.

quantum chemistry, quantum computing, computationa↗
DOE OSTI2023

Bayesian Parameter Estimation of the k-ω Shear Stress Transport Model for Accurate Simulations of Impinging-Jet Heat Transfer

Given the lack of fusion-relevant component test facilities, current estimates of the thermo-fluid performance of plasma-facing components are based for the most part on numerical simulations. A major source of uncertainty in these simulations is the semiempirical turbulence (closure) models for the Reynolds stresses appearing in the governing Reynolds-averaged Navier-Stokes equations, which involve a set of constants that depend upon the flow. The objective of this study is to evaluate Bayesian parameter estimation of turbulence closure constants in ANSYS Fluent to model heat transfer in impinging jets. The Bayesian statistical calibration produces a probability distribution for these constants from experimental data; the maximum a posteriori estimates are then taken to be the calibrated constants, or parameters. The turbulence model constants are calibrated using an experimental study of a submerged jet of air impinging on a flat heated surface at Reynolds numbers Re = O(10 4 ) and impingement distance in jet diameters H/d = 2. Numerical predictions using the calibrated model parameters are then compared with those generated using the default constants. Predictions obtained with model parameters calibrated on datasets of two different sizes are compared to evaluate the effect of the number of calibration samples. Lastly, the extrapolative ability of the calibrated model is examined by predictions at a Re beyond the calibration values.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2021

Numerical simulation of the hot-tail runaway electron production mechanism using CQL3D and comparison with Smith–Verwichte analytical model

Abstract The hot-tail mechanism of runaway electron (RE) production (Harvey et al 2000 Phys. Plasmas 7 4590) is the primary source of RE in the case of rapidly cooling tokamak plasma. Quantifying this mechanism is very important as it can provide most of the post-thermal-quench (TQ) current, or a seed current for the secondary source of RE through the avalanche mechanism. An analytic model which omits pitch-angle scattering is often used in literature for estimating the hot-tail RE density (Smith and Verwichte 2008 Phys. Plasmas 15 072502). In the present study, we use the CQL3D bounce-averaged Fokker–Planck code (Harvey and McCoy 1992 Proc. IAEA Technical Committee Meeting on Advances in Simulation and Modeling of Thermonuclear Plasmas p 527) to test the limits of validity of the model. In particular, we examine the cases of Z = 1 and Z = 18 ions, for sets of different initial temperature, density, electric field and the characteristic time of temperature decay. We show that for Z = 1 plasma, the ratio of RE density computed by CQL3D to that estimated from the model is within 0.6–6.0 in studied cases. For the Z = 18 case, this factor is systematically a much smaller number, typically 0.02–0.6. We suggest a simple correction to the model that narrows down the range of this ratio to 0.3–3.8 in all of the cases, including Z = 1 and Z = 18 plasmas.

Physics↗
DOE OSTI2020

Fast Approximate Methods for Modified Gravity Cosmological Simulations

The accelerated expansion of the Universe poses a major theoretical puzzle. Although the assumption of a non-zero cosmological constant provides a minimal extension of general relativity that is consistent with observational data, many theories of modified gravity have been suggested as possible alternatives. Predictions of structure formation for these models in the fully nonlinear regime are very expensive and it is difficult, if not impossible, to explore such a huge space of models and parameters using high-resolution N-body simulations. Even in the mildly nonlinear regime, perturbative methods can become extremely complex. We explore whether simplified dynamical approximations, applicable for a certain set of cosmological probes, can be used to investigate models of modified gravity with acceptable accuracy in the latter instance. For the case of chameleon gravity, we find that these methods can indeed be used to explore the region around the baryon acoustic oscillation scale, k ~ 0:1 hMpc-1 but not much further.

cosmology↗
DOE OSTI2020

Perturbation theory for modeling galaxy bias: validation with simulations of the Dark Energy Survey

We describe perturbation theory (PT) models of galaxy bias for applications to photometric galaxy surveys. We model the galaxy-galaxy and galaxy-matter correlation functions in configuration space and validate against measurements from mock catalogs designed for the Dark Energy Survey (DES). We find that an effective PT model with five galaxy bias parameters provides a good description of the 3D correlation functions above scales of 4 Mpc/$h$ and $z < 1$. Our tests show that at the projected precision of the DES-Year 3 analysis, two of the non-linear bias parameters can be fixed to their co-evolution values, and a third (the $k^2$ term for higher derivative bias) set to zero. The agreement is typically at the 2 percent level over scales of interest, which is the statistical uncertainty of our simulation measurements. To achieve this level of agreement, our {\it fiducial} model requires using the full non-linear matter power spectrum (rather than the 1-loop PT one). We also measure the relationship between the non-linear and linear bias parameters and compare them to their expected co-evolution values. We use these tests to motivate the galaxy bias model and scale cuts for the cosmological analysis of the Dark Energy Survey; our conclusions are generally applicable to all photometric surveys.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2022

3D Simulations Capture the Persistent Low-Mode Asymmetries Evident in Laser-Direct-Drive Implosions on OMEGA

Spherical implosions in Inertial Confinement Fusion (ICF) are inherently sensitive to perturbations that may arise from experimental constraints and errors. Control and mitigation of low-mode (long wavelengths) perturbations is a key milestone to improving implosion performances. Here, we present the first 3-D radiation-hydrodynamic simulations of directly driven ICF implosions with an inline package for polarized Crossed-Beam Energy Transfer (CBET). Simulations match bang times, yields (separately accounting for laser-induced high modes and fuel age), hot spot flow velocities and direction, for which polarized CBET contributes to the systematic flow orientation evident in the OMEGA implosion database. Current levels of beam mispointing, imbalance, target offset and asymmetry from polarized CBET degrade yields by more than 40%. The effectiveness of two mitigation strategies for low-modes is explored.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2021

A Kinetic Monte Carlo Approach for Simulating Cascading Transmission Line Failure

In this work, cascading transmission line failures are studied through a dynamical model of the power system operating under fixed conditions. The power grid is modeled as a stochastic dynamical system where first-principles electromechanical dynamics are excited by small Gaussian disturbances in demand and generation around a specified operating point. In this context, a single line failure is interpreted in a large deviation context as a first escape event across a surface in phase space defined by line security constraints. The resulting system of stochastic differential equations admits a transverse decomposition of the drift, which leads to considerable simplification in evaluating the quasipotential (rate function) and, consequently, computation of exit rates. Tractable expressions for the rate of transmission line failure in a restricted network are derived from large deviation theory arguments and validated against numerical simulations. Extensions to realistic settings are considered, and individual line failure models are aggregated into a Markov model of cascading failure inspired by chemical kinetics. Cascades are generated by traversing a graph composed of weighted edges representing transitions to degraded network topologies. Numerical results indicate that the Markov model can produce cascades with qualitative power-law properties similar to those observed in empirical cascades.

Kinetic Monte Carlo, rare events, Cascading Failur↗
DOE OSTI2021

Novel Geochemistry Determined from High Pressure, High Temperature Simulation Experiments of Hydraulic Fracture Test Site 2

A standard method in unconventional oil and gas production is the process of hydraulic fracturing followed by a shut-in period, during which the fracture fluid remains pressurized in the reservoir for up to three weeks before production begins. Despite this widely used process, very little is known about what occurs in the reservoir during this shut-in process. In order to properly delineate potential reservoir reactions that may occur during shut-in that would lead to corrosion and scaling events, experiments were conducted in high pressure, high temperature reactors to simulate conditions of the Wolfcamp Formation in the Delaware Basin. Experimental design allowed the assessment of the effect of proppant, microbiology, and time on the mineralogy and fluid chemistry in the reservoir. Results suggest the biggest impact on fluid chemistry and shale mineralogy during shut-in is time. Analyses demonstrate dissolution of the shale material, with maximum dissolved ions occurring after 7 days of the shut-in period. After 21 days, results suggest precipitation occurs. The Delaware Basin is demonstrated to be high in sulfate content, which further increases in the fluid due to dissolution reactions during shut-in. The pressure vessel experiments suggest there was no significant contribution to reactions from microbiology during the shut-in period. Furthermore, early production samples demonstrate a significant selection of the microorganism Caminicella, a genus of which has previously been correlated to corrosion and sulfide production. Results suggest shut-in conditions may provide high sulfate concentrations that could later be utilized by a shifted microbial community to drive potential well infrastructure failure. This is the first study to incorporate microbiology, mineralogy, and fluid chemistry to investigate the fundamental geochemical reactions that occur during shut-in and early phase production of the Delaware Downloaded from http://onepetro.org/URTECONF/proceedings-pdf/21URTC/2-21URTC/D021S032R001/2477425/urtec-2021-5219-ms.pdf/1 by Carol Worster on 28 February 2022 Basin. Results from this study can complement observations from the Hydraulic Fracture Test Site 2 observations

58 GEOSCIENCES↗
DOE OSTI2026

An Approach for Simulating Transport of Nonspherical, Sublimating Particles in Rarefied Gas Flows via the Direct Simulation Monte Carlo Method

This paper extends the particle Green’s function approach of Gallis et al. [Phys. Fluids 13, 3482–3492 (2001)] to compute the force and heat transfer on nonspherical, sublimating particles in rarefied gas flows. Green’s functions are derived for rods and plates, which are representative of ice particle shapes, and a numerical procedure is developed for computing the Green’s functions for a general discretized convex shape. Additionally, a sublimation model is developed to simulate the evolution of ice particles in rarefied gas flows. These models are implemented in a direct simulation Monte Carlo code and demonstrated for the case of ice-particle-laden hypersonic flow over a ramp.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2020

Investigation of Mixing Law Efficacy for Gaseous Hydrodynamic Simulations

A computational simulation of various mixing laws for gaseous equations of state using planar traveling shocks for multiple mixtures in three dimensions is analyzed against nominal experimental data. Numerical simulations utilize the Sandia National Laboratories shock hydrodynamic code CTH and other codes including the thermochemical equilibrium code TIGER and the uncertainty qualification and sensitivity analysis code DAKOTA. The mixtures are a 1:1 and a 1:3 molar mixture of helium and sulfur hexafluoride. The mixing laws to be analyzed are the ideal gas law, Amagat's Law, Dalton's Law, the BKW EOS, the EXP6 EOS, and the JCZ3 EOS. Examination of the experimental data with TIGER revealed that the shock strength should not be strong enough to turn the mixture non-ideal as the compressibility factor z was essentially unity (z ≈ 1.02). Experimental results show that none of the equations of state are able to accurately predict the properties of the shocked mixture; similar discrepancies have been observed in previous works. Kinetic molecular theory appears to introduce a parameter which offers an explanation regarding the discrepancies. Implementation of the KMT pararneter into the EOS is left for future work.

42 ENGINEERING↗
DOE OSTI2020

Simulating the Trajectory and Biomass Growth of Free-Floating Macroalgal Cultivation Platforms along the U.S. West Coast

Trajectory tracking and macroalgal growth models were coupled to support a novel macroalgae-harvesting concept known as the Nautical Off-shore Macroalgal Autonomous Device (NOMAD). The NOMAD consists of 5 km long carbon-fiber longlines that are seeded and free float southward along the U.S. West Coast for approximately 3 months before harvesting off the California coast, taking advantage of favorable environmental conditions. The trajectory and macroalgal growth models were applied to answer planning questions pertinent to the techno-economic analysis such as identifying the preferred release location, approximate pathway, timing until harvest, and estimated growth. Trajectories were determined with the General NOAA Operational Modeling Environment (GNOME) model, using 11 years of current and wind data, determining probabilities by running nearly 40,000 Monte Carlo simulations varying the start time and location. An accompanying macroalgal growth model was used to estimate the growth of macroalgae based on the trajectory tracks and environmental forcing products, including light, temperature and nutrients. Model results show that NOMAD lines transit south in the months of April to September due to seasonal currents, taking approximately 3 months to reach Southern California. During transit, NOMAD lines are dispersed but typically avoid beaching or passing through marine sanctuaries. NOMAD lines can yield up to 30 kg wet weight per meter of cultivation line.

09 BIOMASS FUELS↗