The Future of Transposition Models: From Isotropic Approximation to Physics Models
This presentation provides a high-level overview of the future of transposition models.
14 SOLAR ENERGY↗
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Results for “Physics Modeling”
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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A common model framework for advancing physics models in radiation hydrodynamic codes for inertial fusion energy
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70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
Enabling Advanced Snow Physics Within Land Surface Models Through an Interoperable Model‐Physics Coupling Framework
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Mahdi Navari↗
Physical models of active devices
Physical model of large-signal junction transistor
JUNCTION TRANSISTOR↗
A Software Toolkit to Study Systematic Uncertainties of the Physics Models of the Geant4 Simulation Package
The Geant4 simulation toolkit is used to model interactions between particles and matter. Geant4 employs a set of validated physics models that span a wide range of interaction energies. These models rely on measured cross-sections and phenomenological models with the physically motivated parameters that are tuned to cover many application domains. To study what uncertainties are associated with the Geant4 physics models we have designed and implemented a comprehensive, modular, user-friendly software toolkit that allows the variation of one or more parameters of one or more Geant4 physics models involved in simulation studies. It also enables analysis of multiple variants of the resulting physics observables of interest in order to estimate the uncertainties associated with the simulation model choices. Based on modern event-processing infrastructure software, the toolkit offers a variety of attractive features, e.g. exible run-time con gurable work ow, comprehensive bookkeeping, easy to expand collection of analytical components. Design, implementation technology, and key functionalities of the toolkit are presented in this paper and illustrated with selected results.
72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
Similarity Criteria for the Study of Removal of Spherical Non-metallic Inclusions in Physical Models of Continuous Casting Tundishes: A More Fundamental Approach
Physical modeling is widely used for studying steelmaking processes. The accuracy of this technique depends on the use of appropriate similarity criteria during experimental design. The present work deduced rigorously the similarity criteria for the study of spherical non-metallic inclusions in isothermal physical models of tundishes. Initially, macroscopic quantities were used to simplify the multiphase problem. Then, the similarity criteria were obtained from the dimensionless form of the exact equation of motion for an inclusion in Stokes regime. The validity range of these criteria was discussed and they were compared with common literature practice. Some practical considerations were also presented. This work clarifies various implicit assumptions usually adopted in literature. Additionally, a restrictive criterion to choose the density of the inclusion simulating particles was obtained, which can be satisfied, for example, by hollow glass particles in water models. This criterion is necessary to adequately describe the inclusion motion in regions where fluid elements suffer strong acceleration (e.g., inside nozzles, near flow controllers or in the entering fluid jet). Moreover, it was established an upper limit for the concentration of particles injected in the inlet nozzle of physical models, which do not simulate the phenomenon of inclusion aggregation.
36 MATERIALS SCIENCE↗
Quantitative metrics for evaluating thermonuclear design codes and physics models applied to the National Ignition Campaign
In this study, physics models and design codes for hot dense plasmas undergoing thermonuclear burn are evaluated objectively using statistical metrics that compare the difference between calculations and data relative to the experimental uncertainties. The analysis is applied to the National Ignition Campaign (NIC) because it is relevant, comprehensive, and well documented. The statistics confirm that a key process afflicting NIC performance is mix driven by hydrodynamic instabilities as approximated here using the KL model [G. Dimonte and R. Tipton, Phys. Fluids 18, 085101 (2006)]. New physics models are also presented for instability-driven magnetic fields [B. Srinivasan et al., Phys. Rev. Lett. 108, 165002 (2012)] and the Coulomb logarithm for electron–ion thermal relaxation [G. Dimonte and J. Daligault, Phys. Rev. Lett. 101, 135001 (2008)]. The plasma-generated magnetic fields improve the agreement between code and data in a statistically significant manner by reducing the electron thermal conduction in the hot-spot via the Hall term. The Coulomb logarithm is presented in a numerically practical form that incorporates recent theoretical advances. However, it does not improve the agreement between the code and data because the thermal relaxation is so fast in non-ignited NIC plasmas that the typical 20% error does not change the tight coupling between electrons and ions. Even with these improved physics models, the one-dimensional simulations presented here are not able to describe the high-convergence NIC implosions in a statistically acceptable manner. Of the heroic multi-dimensional simulations of Clark et al. [Phys. Plasmas 23, 056302 (2016)], only those in three-dimensions satisfy the statistical acceptance criterion.
70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
CO 2 rock physics modeling for reliable monitoring of geologic carbon storage
Monitoring, verification, and accounting (MVA) are crucial to ensure safe and long-term geologic carbon storage. Seismic monitoring is a key MVA technique that utilizes seismic data to infer elastic properties of CO 2 -saturated rocks. Reliable accounting of CO 2 in subsurface storage reservoirs and potential leakage zones requires an accurate rock physics model. However, the widely used CO 2 rock physics model based on the conventional Biot-Gassmann equation can substantially underestimate the influence of CO 2 saturation on seismic waves, leading to inaccurate accounting. We develop an accurate CO 2 rock physics model by accounting for both effects of the stress dependence of seismic velocities in porous rocks and CO 2 weakening on the rock framework. We validate our CO 2 rock physics model using the Kimberlina-1.2 model (a previously proposed geologic carbon storage site in California) and create time-lapse elastic property models with our new rock physics method. We compare the results with those obtained using the conventional Biot-Gassmann equation. Our innovative approach produces larger changes in elastic properties than the Biot-Gassmann results. Using our CO 2 rock physics model can replicate shear-wave speed reductions observed in the laboratory. Our rock physics model enhances the accuracy of time-lapse elastic-wave modeling and enables reliable CO 2 accounting using seismic monitoring.
58 GEOSCIENCES↗
The DOE E3SM Model Version 2: Overview of the Physical Model and Initial Model Evaluation
Abstract This work documents version two of the Department of Energy's Energy Exascale Earth System Model (E3SM). E3SMv2 is a significant evolution from its predecessor E3SMv1, resulting in a model that is nearly twice as fast and with a simulated climate that is improved in many metrics. We describe the physical climate model in its lower horizontal resolution configuration consisting of 110 km atmosphere, 165 km land, 0.5° river routing model, and an ocean and sea ice with mesh spacing varying between 60 km in the mid‐latitudes and 30 km at the equator and poles. The model performance is evaluated with Coupled Model Intercomparison Project Phase 6 Diagnosis, Evaluation, and Characterization of Klima simulations augmented with historical simulations as well as simulations to evaluate impacts of different forcing agents. The simulated climate has many realistic features of the climate system, with notable improvements in clouds and precipitation compared to E3SMv1. E3SMv1 suffered from an excessively high equilibrium climate sensitivity (ECS) of 5.3 K. In E3SMv2, ECS is reduced to 4.0 K which is now within the plausible range based on a recent World Climate Research Program assessment. However, a number of important biases remain including a weak Atlantic Meridional Overturning Circulation, deficiencies in the characteristics and spectral distribution of tropical atmospheric variability, and a significant underestimation of the observed warming in the second half of the historical period. An analysis of single‐forcing simulations indicates that correcting the historical temperature bias would require a substantial reduction in the magnitude of the aerosol‐related forcing.
54 ENVIRONMENTAL SCIENCES↗
A physical model of Titan's clouds
A physical model of the formation and growth of aerosols in the atmosphere of Titan has been constructed in light of the observed correlation between variations in Titan's albedo and the sunspot cycle. The model was developed to fit spectral observations of deep methane bands, pressures, temperature distributions, and cloud structure, and is based on a one-dimensional physical-chemical model developed to simulate the earth's stratospheric aerosol layer. Sensitivity tests reveal the model parameters to be relatively insensitive to particle shape but sensitive to particle density, with high particle densities requiring larger aerosol mass production rates to produce compatible clouds. Solution of the aerosol continuity equations for particles of sizes 13 A to about 3 microns indicates the importance of a warm upper atmosphere and a high-altitude mass injection layer, and the production of aerosols at very low aerosol optical depths. Limits are obtained for the chemical production of aerosol mass and the eddy diffusion coefficient, and it is found that an increase in mass input causes a decrease in mean particle size.
Toon, O. B.↗
A physical model for downward burning
Elementary physical model for flammable materials combustion emphasizing downward burning
Adelberg, M.↗
Differentiable modelling to unify machine learning and physical models for geosciences
Process-based modelling offers interpretability and physical consistency in many domains of geosciences but struggles to leverage large datasets efficiently. Machine-learning methods, especially deep networks, have strong predictive skills yet are unable to answer specific scientific questions. Here, in this Perspective, we explore differentiable modelling as a pathway to dissolve the perceived barrier between process-based modelling and machine learning in the geosciences and demonstrate its potential with examples from hydrological modelling. ‘Differentiable’ refers to accurately and efficiently calculating gradients with respect to model variables or parameters, enabling the discovery of high-dimensional unknown relationships. Differentiable modelling involves connecting (flexible amounts of) prior physical knowledge to neural networks, pushing the boundary of physics-informed machine learning. It offers better interpretability, generalizability, and extrapolation capabilities than purely data-driven machine learning, achieving a similar level of accuracy while requiring less training data. Additionally, the performance and efficiency of differentiable models scale well with increasing data volumes. Under data-scarce scenarios, differentiable models have outperformed machine-learning models in producing short-term dynamics and decadal-scale trends owing to the imposed physical constraints. Differentiable modelling approaches are primed to enable geoscientists to ask questions, test hypotheses, and discover unrecognized physical relationships. Future work should address computational challenges, reduce uncertainty, and verify the physical significance of outputs.
58 GEOSCIENCES↗
A Software Toolkit to Study Systematic Uncertainties of the Physics Models of the Geant4 Simulation Package
The Geant4 toolkit is used to model interactions between particles and matter. Geant4 employs a set of validated physics models that span a wide range of interaction energies. These models are tuned to cover a large variety of possible applications. This raises the critical question of what uncertainties are associated with the Geant4 physics model, or group of models, involved in a simulation project. To address the challenge, we have designed and implemented a comprehen- sive, modular, user-friendly software toolkit that allows the variation of one or more parameters of one or more Geant4 physics models involved in simulation studies. It also enables analysis of multiple variants of the resulting physics observables of interest in order to estimate the uncertain- ties associated with the simulation model choices. Key functionalities of the toolkit are presented in this paper and are illustrated with selected results.
Genser, Krzysztof↗
Validation of Physics Models of Geant4 using Data from CMS Experiment
CMS has tuned its simulation program and has chosen a specific physics model of GEANT4 by comparing the simulation results with dedicated test beam experiments. CMS continues to validate the physics models inside GEANT4 using the test beam data as well as collision data. Several physics lists (collection of physics models) inside the most recent version of GEANT4 provide good agreement of the energy response, resolution of pions and protons. The validation results from these studies are used to make the choice of physics list and GEANT4 version for the CMS experiment.
72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
A Physical Model to Estimate Snowfall over Land using AMSU-B Observations
In this study, we present an improved physical model to retrieve snowfall rate over land using brightness temperature observations from the National Oceanic and Atmospheric Administration's (NOAA) Advanced Microwave Sounder Unit-B (AMSU-B) at 89 GHz, 150 GHz, 183.3 +/- 1 GHz, 183.3 +/- 3 GHz, and 183.3 +/- 7 GHz. The retrieval model is applied to the New England blizzard of March 5, 2001 which deposited about 75 cm of snow over much of Vermont, New Hampshire, and northern New York. In this improved physical model, prior retrieval assumptions about snowflake shape, particle size distributions, environmental conditions, and optimization methodology have been updated. Here, single scattering parameters for snow particles are calculated with the Discrete-Dipole Approximation (DDA) method instead of assuming spherical shapes. Five different snow particle models (hexagonal columns, hexagonal plates, and three different kinds of aggregates) are considered. Snow particle size distributions are assumed to vary with air temperature and to follow aircraft measurements described by previous studies. Brightness temperatures at AMSU-B frequencies for the New England blizzard are calculated using these DDA calculated single scattering parameters and particle size distributions. The vertical profiles of pressure, temperature, relative humidity and hydrometeors are provided by MM5 model simulations. These profiles are treated as the a priori data base in the Bayesian retrieval algorithm. In algorithm applications to the blizzard data, calculated brightness temperatures associated with selected database profiles agree with AMSU-B observations to within about +/- 5 K at all five frequencies. Retrieved snowfall rates compare favorably with the near-concurrent National Weather Service (NWS) radar reflectivity measurements. The relationships between the NWS radar measured reflectivities Z(sub e) and retrieved snowfall rate R for a given snow particle model are derived by a histogram matching technique. All of these Z(sub e)-R relationships fall in the range of previously established Z(sub e)-R relationships for snowfall. This suggests that the current physical model developed in this study can reliably estimate the snowfall rate over land using the AMSU-B measured brightness temperatures.
Kim, Min-Jeong↗
Economic and Physical Modeling of Land Use in GCAM 3.0 and an Application to Agricultural Productivity, Land, and Terrestrial Carbon
We explore the impact of changes in agricultural productivity on global land use and terrestrial carbon using the new agriculture and land use modeling approach developed for Global Change Assessment Model (GCAM) version 3.0. This approach models economic land use decisions with regional, physical, and technological specificity while maintaining economic and physical integration with the rest of the GCAM model. Physical land characteristics and quantities are tracked explicitly, and crop production practices are modeled discretely to facilitate coupling with physical models. Economic land allocation is modeled with non-linear functions in a market equilibrium rather than through a constrained optimization. In this paper, we explore three scenarios of future agriculture productivity in all regions of the globe over this century, ranging from a high growth to a zero growth level. The higher productivity growth scenario leads to lower crop prices, increased production of crops in developing nations, preservation of global forested lands and lower terrestrial carbon emissions. The scenario with no productivity improvement results in higher crop prices, an expansion of crop production in the developed world, loss of forested lands globally, and higher terrestrial carbon emissions.
Wise, Marshall A.↗
Numerical Simulation of Recirculating Flow and Physical Model of Slag–Metal Behavior in an RH Reactor: Application to Desulfurization
Computational fluid dynamics (CFD) techniques and a 1:7.5 physical model of an RH degasser have been used to evaluate the flow of gas and metal inside an RH reactor for vacuum degassing of liquid steel. The effect of gas injection on the gas spatial distribution, steel circulation rate and flow field inside the ladle, snorkels and vacuum chamber have been assessed. N-pentane oil was employed to evaluate the average residence time as well as the slag droplet size distribution. The predicted radial gas distribution and liquid circulation rate have been validated against experimental data from a physical model. The results with incorporation of the virtual mass force coefficient of 0.25 and the turbulence dispersion force showed better predictions of gas distribution in the up-snorkel as well as circulation rate. Full-scale simulations were performed, and the predicted circulation rate was significantly affected by the argon bubble expansion. Data from these simulations were used to analyze the degree of desulfurization performed by the addition of desulfurizing agents inside the vacuum chamber. A model of the kinetics of desulfurization based on the results from the physical model and CFD simulation and on slag dispersion inside liquid steel yields degrees of desulfurization similar to the industrial trials reported in the literature.
36 MATERIALS SCIENCE↗