A Suite of Thermodynamic and Transport Properties for Computational Simulations with Hydrogen Isotopes.
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Transportation system simulation is a widely accepted approach to evaluate the impact of transport policy deployment. In developing a transportation system deployment model, the energy impact of the model is extremely valuable for sustainability and validation. It is expected that different penetration levels of Connected-Autonomous Vehicles (CAVs) will impact travel behavior due to changes in potential factors such as congestion, miles traveled, etc. Along with such impact analyses, it is also important to further quantify the regional energy impact of CAV deployment under different factors of interest. The objective of this paper is to study the energy consumption of electrified vehicles in the future for different penetration levels of CAVs deployment in the City of Chicago. The paper will further provide a statistical analysis of the results to evaluate the impact of the different penetration levels on the different electrified powertrains used in the study.
This is a final report for the grant entitled, “The application of parallel kinetic simulations to laser and electron transport through plasmas”. The objectives of this grant were to significantly advance the fundamental understanding of the nonlinear optics of plasmas and electron transport in high-energy-density laboratory plasmas (HEDLP), including conditions of relevance to Inertial Fusion Energy (IFE). The ultimate goal was to use the understanding to determine how to fully control laser plasma interactions. The primary research tools were our own kinetic particle-in-cell software, OSIRIS, that includes kinetic physics and can run effectively on leadership class computing facilities. Therefore, one objective was to ensure that OSIRIS in continually improved so that it was more accurate and could effectively utilize state-of-the-art computing facilities. Another objective was to attract and train young researchers into the field of high energy density plasma physics. To meet the research objectives, the funds from this proposal were used to conduct research on stimulated Raman scattering (SRS) and enhance our PIC software OSIRIS. It was found that small normalized magnetic fields can in some cases mitigate SRS and that speckles can mutually interact through SRS. It was also found that it is possible for instabilities drive near quarter critical (e.g., the high frequency hybrid instability-HFHI) can generate light waves that propagate back down a density gradient where they can rescatter into the HFHI at 1/16 of the original quarter critical density.
Binary neutron star mergers play an important role in nuclear astrophysics: Their gravitational wave and electromagnetic signals carry information about the equation of state of cold matter above nuclear saturation density, and they may be one of the main sources of r-process elements in the Universe. Neutrino-matter interactions during and after merger impact the properties of these electromagnetic signals and the relative abundances of the produced r-process elements. Existing merger simulations are, however, limited in their ability to realistically model neutrino transport and neutrino-matter interactions. Here, we perform a comparison of the impact of the use of state-of-the art two-moment or Monte Carlo transport schemes on the outcome of merger simulations, for a single binary neutron star system with a short-lived neutron star remnant [(5–10) ms]. We also investigate the use of different reaction rates in the simulations. While the best transport schemes generally agree well on the qualitative impact of neutrinos on the system, differences in the behavior of the high-density regions can significantly impact the collapse time and the properties of the hot tidal arms in this metastable merger remnant. The chosen interaction rates and transport algorithm as well as recent improvements by Radice et al. to the two-moment algorithms can all contribute to changes at the (10–30)% level in the global properties of the merger remnant and outflows. Furthermore, the limitations of previous moment schemes fixed by Radice et al. also appear sufficient to explain the large difference that we observed in the production of heavy-lepton neutrinos in a previous comparison of Monte Carlo and moment schemes in the context of a low-mass binary neutron star system.
This data package contains model input and output files for local and global sensitivity analysis (SA) of a reactive transport model simulating redox cycling within a floodplain aquifer. The reaction network is implemented in CrunchFlow and focuses on spatially and temporally heterogeneous Fe cycling, though it contains several other species and redox pathways (37 aqueous species and 7 minerals in total). The package contains data from 600 Monte Carlo simulations (for global SA) and 104 one-at-a-time simulations (for local SA). It includes all input files required to run the CrunchFlow model, as well as limited model output – .csv files containing time series of primary species concentrations at 21 grid cells within the domain. These time series files contain the following species: H+, CO32-, SO42-, Cl-, Ca2+, Mg2+, Na+, K+, Fe(II), Fe(III), HS-, CH3COO-, O2(aq), S(aq), and Br-.These data were used to demonstrate the application of a novel form of global SA, distance-based generalized sensitivity analysis (DGSA) to a reactive transport model. The 2D model simulates the export of reduced species from pockets of fine-grained, organic-rich sediments embedded in a coarse sand aquifer. Stochastic simulations jointly varied 17 key model input parameters across several orders of magnitude, including the spatial variability of each parameter. DGSA on the model results reveal that the amplitude and variability of exported Fe(II) are most sensitive to the interaction between sand permeability and individual reaction rates. By contrast, the propagation of reducing conditions downgradient from the fine-grained lenses depends most heavily on the rate of dissolved organic carbon and sulfate release from the fines.
ABSTRACT We present neutrino-transport hydrodynamic simulations of electron-capture supernovae (ECSNe) in flash with new two-dimensional (2D) collapsing progenitor models. These progenitor models feature the 2D modelling of oxygen-flame propagation until the onset of core collapse. We perform axisymmetric simulations with six progenitor models that, at the time of collapse, span a range of propagating flame front radii. For comparison, we also perform a simulation with the same set-up using the canonical, spherically symmetrical progenitor model n8.8. We found that the variations in the progenitor models inherited from simulations of stellar evolution and flame propagation do not significantly alter the global properties of the neutrino-driven ECSN explosion, such as the explosion energy (∼1.36–1.48 × 1050 erg) and the mass (∼0.017–0.018 M⊙) and composition of the ejecta. Due to aspherical perturbations induced by the 2D flame, the ejecta contains a small amount (≲1.8 × 10−3 M⊙) of low-Ye (0.35 < Ye < 0.4) component. The baryonic mass of the protoneutron star is ∼1.34 M⊙ (∼1.357 M⊙) with the new (n8.8) progenitor models when simulations end at ∼400 ms and the discrepancy is due to updated weak-interaction rates in the progenitor evolutionary simulations. Our results reflect the nature of ECSN progenitors containing a strongly degenerate oxygen–neon–magnesium (ONeMg) core and suggest a standardized ECSN explosion initialized by ONeMg core collapse. Moreover, we carry out a rudimentary three-dimensional simulation and find that the explosion properties are fairly compatible with the 2D counterpart. Our paper facilitates a more thorough understanding of ECSN explosions following the ONeMg core collapse, though more three-dimensional simulations are still needed.
We apply Cattaneo's relaxation approach to the one-dimensional coupled Boussinesq groundwater flow and advection-diffusion-reaction equations, commonly used in engineering applications to simulate contaminant transport in the subsurface. The diffusion-type governing equations are reformulated as a hyperbolic system, augmented by an equation that can be interpreted as a momentum balance. The hyperbolization enables an efficient unified computation of the primary variable and its gradients, for example piezometric head and unit discharge in the Boussinesq equation. An augmented Roe scheme is used to solve the hyperbolic system. The hyperbolized system of equations is studied in a set of steady state and transient test cases with idealized geometry. These test cases confirm the equivalence of the hyperbolic system to its original formulation. The larger time step size of the hyperbolic equation is verified theoretically by means of a stability analysis and numerically in the test cases. Finally, a reach-scale application of flow and transport across a river meander is considered. This application case shows that the performance of the hyperbolic relaxation approach holds for more realistic groundwater flow and transport problems, relevant to water resources management.
The transition in the turbulence spectrum from ion-scale dominated regimes to multiscale transport regimes that couple ion and electron scales is studied with gyrokinetic simulations of turbulent transport. The simulations are based on DIII-D high-confinement mode (H-mode) plasma parameters in the tokamak pedestal. The transition is initiated by varying the ion temperature gradient. To our knowledge, no full multiscale simulations of pedestal-like transport have been done previously. The experimental parameters lie in a bifurcation region between the two regimes. At long wavelengths, a complex, ion-direction hybrid mode is the dominant linearly unstable drift wave, while an electron temperature gradient-driven mode is unstable at short wavelengths. In the transition from the multiscale branch to the ion-scale branch, the magnitude of the ion-scale poloidal wavenumber spectrum of the nonlinear turbulent energy flux increases and the magnitude of the high-wavenumber spectrum decreases. Here, the decrease in the electron-scale transport is due to nonlinear mixing with ion-scale fluctuations and the ion-scale-driven zonal flows. A shift in the total energy associated with the fluctuating electrostatic potential intensity from dominantly drift kinetic energy in the multiscale regime to dominantly potential intensity in the ion-scale regime is well-correlated with the trend in the total energy flux.
Black carbon (BC) aerosol is an important driver of Arctic warming, and China used to be a major contributor to the Arctic BC burden through long-range atmospheric transport. Here we show that China's contribution declined significantly from 2009 to 2022, primarily due to reductions in domestic BC emissions following the implementation of clean air policies. Global chemistry-transport model simulations indicate a relative decline of ∼3% yr −1 ( p < 0.05) in China's Arctic BC contribution, exceeding the decrease rate in the underlying emission inventory. Sensitivity simulations further suggest that climate change-induced shifts in atmospheric transport may have amplified this decline. Observations of aerosol absorption coefficients (σ ap ) at Arctic background observatories revealed steeper declines in σ ap when modeled China-to-total BC ratios were higher. Moreover, σ ap correlated positively with modeled BC from China, with stronger relationships as the modeled China-to-total BC ratios increased. Together, these results provide robust evidence that China's emission reductions have diminished its role in Arctic BC, contributing an estimated 0.02 W m −2 decrease in the direct radiative effect during the Arctic haze season.
The Plateau to River Groundwater Model (P2R Model) is a groundwater flow and contaminant fate and transport (F&T) simulation model used to support remedial activities conducted by CH2M HILL Plateau Remediation Company at the Hanford Site in Washington State. Figure 1-1 illustrates the P2R Model extents, discretization, and boundary conditions. The P2R Model is utilized in the Composite Analysis (CA) for the Hanford Site as the computational engine for computing F&T predictions as described in CP-60406, Hanford Site Composite Analysis Technical Approach Description: Groundwater. The model simulates contaminants of concern within the saturated zone of the uppermost aquifer beneath the Central Plateau and downgradient to the Columbia River. CP-57037, Model Package Report for the Plateau to River Model Version 8.3, documents the current version of the P2R Model including a description of the conceptual site model, model development and calibration, and limitations to the model application. The overall objective of the saturated zone modeling effort is to provide a basis for making informed remedial action decisions based on descriptions of current and expected future contaminant concentrations in groundwater at decision points within and downgradient of the Central Plateau of the Hanford Site. Specifically, the purpose of this environmental calculation is to describe the application of the hydraulic property fields and recharge parameters documented in ECF-HANFORD-20-0027, Null Space Monte Carlo Evaluation of the Plateau to River Model, to the CA flow and fate and transport simulation results to quantify the uncertainty in the simulated results due to input parameter selection. Use of numerical groundwater models is always accompanied with uncertainty in the results produced by a model because models are approximations of reality. Thus, by definition, models lack the detail to fully represent observed behavior. Use of numerical techniques, such as a NSMC analysis, can help in identifying and quantifying the potential uncertainties associated with a numerical model such as the P2R Model. The result of NSCM analysis is a set of F&T simulations that provide an estimate of the range of possible outcomes that are used to quantify the uncertainty in simulated concentrations produced using the base case simulations. The simulated concentrations from all simulations will support calculation of the uncertainty of the total dose calculated in a separate calculation.
We present a review, demonstration and simulation of phonon transport for the purposes of predicting materials performance at the mesoscale. We focus primarily on the development and implementation of a unified methodology to enable predictive heat transport. We report on the current state of the art as it pertains to deterministic phonon transport methodologies, discussing various topics concerning phonons. In application, we focus on the Self-Adjoint Angular Flux (SAAF) formulation of the Boltzmann transport equation for phonons, and develop the spatial, angular, and material property discretization required to accurately simulate the predictive physics of heat transport in dielectrics. We discuss thermal interfacial resistance and present our formulation of the diffuse mismatch model for simulating phonon interactions at internal boundaries. We have recently developed a deterministic, spectral phonon transport method for predicting effective thermal conductivity ($\kappa_{\textrm{eff}}$), using Bose-Einstein source terms coupled through an average material temperature. In this method, we introduce a closure term to the phonon transport system which acts as a redistribution function for the total energy of the system, and serves as a guide for the amount of non-equilibrium behavior occurring in the system. This method predicts thermal conductivity and equilibrium temperature distributions in homogeneous and heterogeneous materials using data generated by ab initio density functional theory methods. We employ polarization, density of states and full dispersion spectra to resolve thermal conductivity with numerous angular and spatial discretizations. Our implementation utilizes a Richardson iteration on a modified version of the phonon scattering source. The equations associated with this method are solved via a modification of traditional source iteration. We compare the performance of source iteration applied to an existing uncoupled, traditional SAAF method to our new method and comment on the iterative performance of each. We observe ballistic and diffusive phonon scattering as acoustic thickness of the domain changes, and are able to make comparisons between the accuracy and efficiency of both methods.
Abstract Simulations for DIII‐D high confinement mode plasmas with the multifluid code UEDGE show a strong role of poloidal E × B drifts on divertor heat transport, challenging the paradigm of conduction‐limited scrape‐off layer (SOL) transport. While simulations with reduced drift magnitude are well aligned with the assumption that electron heat conduction dominates the SOL heat transport, simulations with drifts predict that the poloidal convective E × B heat transport dominates over electron heat conduction in both attached and detached conditions. As poloidal E × B flow propagates across magnetic field lines, poloidal transport with shallow magnetic pitch angles can reach values that are of the same order as would be provided by sonic flows parallel to the field lines. These flows can lead to strong convection‐dominated divertor heat transport, increasing the poloidal volume of radiative power front, consistent with previous measurements at DIII‐D. Due to these convective flows, the Lengyel integral approach, assuming zero convective fraction, is expected to provide a pessimistic estimate for the radiative capability of impurities in the divertor. For the DIII‐D simulations shown here, the Lengyel integral approach underestimates the radiated power by a factor of 6, indicating that, for reliable DIII‐D divertor power exhaust predictions, full two‐dimensional (2D) calculations, including drifts, would be necessary.
ALGE is a three-dimensional, finite-difference aqueous transport model that simulates pollutant fate and transport in lakes, rivers, bays, and estuaries by solving the prognostic equations of mass, momentum, and energy. Its current modeling capabilities include transport of dissolved tracer for a series of predefined basins across the continental United States. Recently, an inverse method (also known as backtracking) has been added to ALGE to provide a possible source of a pollutant should one be detected by a sensor in a body of water and a source is not known. This inverse method is a three step process that uses an algorithm to inverse the flow. We demonstrate the new model’s capabilities through simulating the 2021 Piney Point spill in Tampa Bay, Florida (USA). This involves moving tracer backwards from its detection points, encompassing a potential source area, and applying Bayes’ Theorem and $\frac{𝜒}{𝑄}$ to reduce the area within which the true source could be located.
We present a comprehensive analysis of super-Eddington black hole accretion simulations that solve the GRMHD equations coupled with angle-discretized radiation transport. The simulations span a range of accretion rates, two black hole spins, and two magnetic field topologies, and include resolution studies as well as comparisons with nonradiative models. Super-Eddington accretion flows consistently develop geometrically thick disks supported by radiation pressure, regardless of magnetic field configuration. Radiation generated in the inner disk drives substantial outflows, forming conical funnel regions that limit photon escape and result in very low radiation efficiency. The accretion flows are highly turbulent, with thermal energy transport dominated by radiation advection rather than diffusion. Angular momentum is primarily carried outward by Maxwell stress, with turbulent Reynolds stress playing a subdominant role. Both strong and weak jets are produced. Strong jets arise from sufficient net vertical magnetic flux and rapid black hole spin, and they can effectively evacuate the funnel, enabling radiation to escape through strong geometric beaming. In contrast, weak jets fail to clear the funnel, which becomes obscured by radiation-driven outflows and leads to distinct observational signatures. Spiral structures are observed in the plunging region, behaving like density waves. These super-Eddington models are applicable to a variety of astronomical systems, including ultraluminous X-ray sources, little red dots, and black hole transients.
Agent-based models (ABMs) in transportation modeling simulate activity and travel decisions at the disaggregate level of households and individuals. To do this, ABMs require detailed and realistic information on agents’ socioeconomic and demographic characteristics. Various synthetic population generators have been proposed to address this need. However, most of those currently in practice are cross-sectional in nature and do not account for the dynamics within households and individuals as they progress through life events over time. This is a major shortcoming, as literature has shown that transportation decisions are affected by the transition between and co-occurrence of life cycle events. While some demographic evolution simulators have been proposed to address this issue, they are developed using cross-sectional data and capture only a small set of life cycle events and their interdependence. Addressing these drawbacks, we propose a demographic microsimulator (DEMOS) that captures the “continuum of life” by considering a range of household- and individual-level life cycle events. DEMOS is developed using the Panel Survey of Income Dynamics, one of the world’s longest-running longitudinal surveys. The DEMOS submodels consider key life cycle events that are influenced by agents’ demographic variables. DEMOS is applied to evolve the population of the San Francisco Bay Area over a 9-year horizon. Results demonstrate how DEMOS generates life trajectories and how DEMOS outputs match the observed demographic trends. DEMOS is expected to enable longitudinal analysis in the context of ABMs and expand ABMs analyses relating to dynamic processes such as household-level vehicle transactions.
A Bayesian inference strategy has been used to estimate uncertain inputs to global impurity transport code (GITR) modeling predictions of tungsten erosion and migration in the linear plasma device, PISCES-A. This allows quantification of GITR output uncertainty based on the uncertainties in measured PISCES-A plasma electron density and temperature profiles (n e , T e ) used as inputs to GITR. The technique has been applied for comparison to dedicated experiments performed for high (4 × 10 22 m –2 s –1 ) and low (5 × 10 21 m –2 s –1 ) flux 250 eV He–plasma exposed tungsten (W) targets designed to assess the net and gross erosion of tungsten, and corresponding W impurity transport. The W target design and orientation, impurity collector, and diagnostics, have been designed to eliminate complexities associated with tokamak divertor plasma exposures (inclined target, mixed plasma species, re-erosion, etc) to benchmark results against the trace impurity transport model simulated by GITR. The simulated results of the erosion, migration, and re-deposition of W during the experiment from the GITR code coupled to materials response models are presented. Specifically, the modeled and experimental W I emission spectroscopy data for a 429.4 nm line and net erosion through the target and collector mass difference measurements are compared. Furthermore, the methodology provides predictions of observable quantities of interest with quantified uncertainty, allowing estimation of moments, together with the sensitivities to plasma temperature and density.
Accurate modeling of mixing in large-eddy simulation (LES) / transported probability density function (PDF) modeling of turbulent combustion remains an outstanding issue. The issue is particularly salient in turbulent premixed combustion under extreme conditions such as high-Karlovitz number Ka. Here, the present study addresses this issue by conducting an a priori analysis of a power-law scaling based mixing timescale model for the transported PDF model. A recently produced DNS dataset of a high-Ka turbulent jet flame is used for the analysis. A power-law scaling is observed for a scaling factor used to model the sub-filter scale mixing timescale in this high-Ka turbulent premixed DNS flame when the LES filter size is much greater than the characteristic thermal thickness of a laminar premixed flame. The sensitivity of the observed power-law scaling to the different viewpoints (local or global) and to the different scalars for the data analysis is examined and the dependence of the model parameters on the dimensionless numbers Ka and Re (the Reynolds number) is investigated. Different model formulations for the mixing timescale are then constructed and assessed in the DNS flame. The proposed model is found to be able to reproduce the mixing timescale informed by the high-Ka DNS flame significantly better than a previous model.
In this paper, we show that a nonequilibrium steady state (NESS) exists at late times in open quantum systems with weak nonlinearity by following its nonequilibrium dynamics with a perturbative analysis. We consider an oscillator chain containing three-types of anharmonicity: cubic α- and quartic β-type Fermi–Pasta–Ulam–Tsingou (FPUT) nearest-oscillator interactions and the on-site (pinned) Klein–Gordon (KG) quartic self-interaction. Assuming weak nonlinearity, we introduce a stochastic influence action approach to the problem and obtain the energy flows in different junctures across the chain. The formal results obtained here can be used for quantum transport problems in weakly nonlinear quantum systems. For α-type anharmonicity, we observe that the first-order corrections do not play any role in the thermal transport in the NESS of the configuration we considered. For KG and β-types anharmonicity, we work out explicitly the case of two weakly nonlinearly coupled oscillators, with results scalable to any number of oscillators. We examine the late-time energy flows from one thermal bath to the other via the coupled oscillators, and show that both the zeroth- and the first-order contributions of the energy flows become constant in time at late times, signaling the existence of a late-time NESS to first order in nonlinearity. Our perturbative calculations provide a measure of the strength of nonlinearity for nonlinear open quantum systems, which may help control the mesoscopic heat transport distinct from or close to linear transport. Furthermore, our results also give a benchmark for the numerical challenge of simulating heat transport. Our setup and predictions can be implemented and verified by investigating heat flow in an array of Josephson junctions in the limit of large Josephson energy with the platform of circuit QED.