Search NASA⌕ Search

SEARCH · Search NASA

Results for “fluid model”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 199 records · Page 11
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Limit cycle oscillations in the zonal-flow-catalyzed interactions of ion-temperature-gradient turbulence

Limit-cycle oscillations are studied for ion temperature gradient turbulence, which, in the absence of large diamagnetic (mean) shear flows, saturates through energy transfer from unstable modes to large-scale stable modes via zonal-flow intermediary modes. Oscillations of zonal flow and turbulence levels are strongly constrained by the reactive, largely non-dissipative character of the zonal flows. Since existing predator–prey models for observed oscillations in experiments do not include energy transfer through zonal flows to stable modes, low-order fluid models with this physics are constructed and investigated. A simple three-wave truncation produces low-amplitude zonal flows that slowly oscillate around a zero mean, with turbulence oscillations between coupled wavenumbers that exceed linear frequencies by orders of magnitude. This inconsistency with experimental observations is caused by the weak non-linear drive of zonal flows in three-wave systems and the lack of multiple-wavenumber turbulent interactions. A more comprehensive model that preserves multiple wavenumber interactions within the context of conservative zonal-flow-mediated energy transfer to stable modes accurately reflects observed dynamics when the phase between stable and unstable modes is occasionally randomized.

Li, P. -Y. (ORCID:0000000295254171)↗
DOE OSTI2020

Reconstruction of Electron and Ion Distribution Functions in a Magnetotail Reconnection Diffusion Region

In the diffusion region of magnetotail reconnection, particle distributions are highly structured, exhibiting triangular shapes and multiple striations that deviate dramatically from the Maxwellian distribution. Fully kinetic simulations have been demonstrated to be capable of producing the essential structures of the observed distribution functions, yet are computationally not feasible for 3D global simulations. The fluid models used for large-scale simulations, on the other hand, do not have the kinetic physics necessary for describing reconnection accurately. Our study aims to bridge fully kinetic and fluid simulations by quantifying the information required to capture the non-Maxwellian features in the distributions underlying the closures used in the fluid code. Here, we compare the results of fully kinetic simulations with observed electron velocity distributions in a magnetotail reconnection diffusion region and use the maximum entropy model to reconstruct electron and ion distributions using various numbers of moments obtained from the simulation. Our results indicate that using only local moments, the maximum entropy model can reproduce many of the features of the distributions: (1) the electron outflow distribution with a tilted triangular structure is reproduced with 21 or more moments in agreement with Ng et al. and (2) counterstreaming distributions can be captured with the 35-moment model when the separation in velocity space between the populations is large.

58 GEOSCIENCES↗
DOE OSTI2023

Insights from high-fidelity modeling of industrial rotary bell atomization

The global automotive industry sprayed over 2.6 billion liters of paint in 2018, much of which through electrostatic rotary bell atomization, a highly complex process involving the fluid mechanics of rapidly rotating thin films tearing apart into micrometer-thin filaments and droplets. Coating operations account for 65% of the energy usage in a typical automotive assembly plant, representing 10,000s of gigawatt-hours each year in the United States alone. Optimization of these processes would allow for improved robustness, reduced material waste, increased throughput, and significantly reduced energy usage. Here, we introduce a high-fidelity mathematical and algorithmic framework to analyze rotary bell atomization dynamics at industrially relevant conditions. Our approach couples laboratory experiment with the development of robust non-Newtonian fluid models; devises high-order accurate numerical methods to compute the coupled bell, paint, and gas dynamics; and efficiently exploits high-performance supercomputing architectures. These advances have yielded insight into key dynamics, including i) parametric trends in film, sheeting, and filament characteristics as a function of fluid rheology, delivery rates, and bell speed; ii) the impact of nonuniform film thicknesses on atomization performance; and iii) an understanding of spray composition via primary and secondary atomization. These findings result in coating design principles that are poised to improve energy- and cost-efficiency in a wide array of industrial and manufacturing settings.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

DIII-D research to provide solutions for ITER and fusion energy

The DIII-D tokamak has elucidated crucial physics and developed projectable solutions for ITER and fusion power plants in the key areas of core performance, boundary heat and particle transport, and integrated scenario operation, with closing the core-edge integration knowledge gap being the overarching mission. New experimental validation of high-fidelity, multi-channel, non-linear gyrokinetic turbulent transport models for ITER provides strong confidence it will achieve Q ≥ 10 operation. Experiments identify options for easing H-mode access in hydrogen, and give new insight into the isotopic dependence of transport and confinement. Analysis of 2,1 islands in unoptimized low-torque IBS demonstration discharges suggests their onset time occurs randomly in the constant β phase, most often triggered by non-linear 3-wave coupling, thus identifying an NTM seeding mechanism to avoid. Pure deuterium SPI for disruption mitigation is shown to provide favorable slow cooling, but poor core assimilation, suggesting paths for improved SPI on ITER. At the boundary, measured neutral density and ionization source fluxes are strongly poloidally asymmetric, implying a 2D treatment is needed to model pedestal fuelling. Detailed measurements of pedestal and SOL quantities and impurity charge state radiation in detached divertors has validated edge fluid modelling and new self-consistent 'pedestal-to-divertor' integrated modeling that can be used to optimize reactors. New feedback adaptive ELM control minimizes confinement reduction, and RMP ELM suppression with sustained high core performance was obtained for the first time with the outer strike point in a W-coated, compact and unpumped small-angle slot divertor. Advances have been made in integrated operational scenarios for ITER and power plants. Wide pedestal intrinsically ELM-free QH-modes are produced with more reactor-relevant conditions, Low torque IBS with W-equivalent radiators can exhibit predator-prey oscillations in Te and radiation which need control. High-β P scenarios with q min > 2, q 95 –7.9, β N > 4, β T –3.3% and H 98y2 > 1.5 are sustained with high density ($\overline{n}$ = 7E19 m -3 , f G –1) for 6 τ E , improving confidence in steady-state tokamak reactors. Diverted NT plasmas achieve high core performance with a non-ELMing edge, offering a possible highly attractive core-edge integration solution for reactors.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2021

THERMAL STRESS ANALYSIS OF A SPENT NUCLEAR FUEL CANISTER

The potential for chloride induced stress corrosion cracking (CISCC) in spent nuclear fuel dry storage canisters is a current topic of research by the US Department of Energy Spent Fuel and Waste Science and Technology program. One of the important prerequisites for CISCC is a tensile residual stress state. This study utilizes computational models to provide an initial analysis of thermal stresses in a generic spent nuclear fuel canister. A STAR-CCM+ thermal fluid model provides a temperature profile analysis of the canister based on four different ambient temperature conditions. An ANSYS APDL finite element model incorporates the temperature profiles to analyze the thermal stresses in the canister. The calculated thermal stress magnitudes are in the range of 10 MPa to 80 MPa, which could be significant for crack propagation through the canister wall. The maximum thermal stress is not a concern for the structural failure of the canister, but it is high enough that it is a significant contribution to the total stress state of the canister wall, which also includes residual stress from fabrication, internal pressure from helium cover gas, and potential transient mechanical loads, such as earthquakes. This paper describes the initial finite element thermal stress analysis that was completed in 2020, reports the initial findings, and identifies areas where model refinement is still needed to complete this work in the future.

Jensen, Ben J.↗
DOE OSTI2020

Development and Validation of Physics-Based Sub-Models of High-Pressure Supercritical Fuel Injection at Diesel Conditions Insert

The project sought to develop and validate accurate, physics-based, numerical submodels and implement them in computational fluid dynamics (CFD) software codes to enable accurate predictions of diesel sprays at pressures higher than the current systems. The combined experimental-computational effort has four main objectives: (1) acquire spatially and temporally resolved scalar measurements of fuel-oxidizer mixing in the near field of the fuel jet, (2) develop software modules to calculate thermo-physical properties of diesel surrogates and their mixtures with oxidizer of interest in real-gas operating regime, (3) integrate the real-fluid model into a commercial and an open-source CFD code to simulate fuel-air mixing in high-pressure diesel sprays, and (4) assess the robustness, accuracy, and uncertainty of the integrated CFD solvers in computing diesel sprays. Project accomplishments are consistent with the original goals of the project. Although we acquired spatially and temporally resolved scalar measurements, they were limited to refractive index difference and not to thermodynamic properties such as temperature and equivalence ratio. However, we successfully developed the theoretical background needed to acquire such measurements at diesel conditions and demonstrated the capability of the RSD for scalar measurements in a canonical turbulent jet flow replicating features of the diesel jet. Additional work will be needed to implement these procedures at high-pressure, high-temperature engine-like conditions of the CPFR. Mainly, we did not anticipate the need to find the liquid boundary and its statistical features or the state relationships between refractive index and thermodynamic properties, assuming the widely known Dale-Gladstone equation would suffice. Still, efforts devoted to these tasks were essential to fulfil the goals of the project and serves as the foundation on which many of the conclusions and key contributions of this project are based. Further assessment and application of the developed CFD codes is recommended to fully realize the benefits of this research.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2023

Earth Sciences Applications for Energy and Global Security: A Few Vignettes [Slides]

Understanding the physics of flow and transport in the subsurface environment is crucial to several National Security applications. In the Energy Security realm, some examples include characterizing radioactive waste disposal, exploring natural gas extraction and sequestering CO2. An example in the Global Security arena is to be able to distinguish between anthropogenic and naturally occurring seismic disturbances, the former being of particular concern as underground nuclear testing activity has seen an increase in recent years. A common theme across these applications is the ability to accurately model fluid flow in porous and/or fractured subsurface media. For decades, researchers have grappled with how to include the effects of uncertainties in these models, including but not limited to heterogeneity, unknown initial and boundary conditions and issues with scalability. More recently advances in computing and machine learning methodologies have allowed a broader exploration of the uncertainty space as we strive for real time decision making. I will present an overview of the field and discuss a few examples of how my own research in these topics has evolved over nearly two decades.

58 GEOSCIENCES↗
DOE OSTI2025

Multiphysics Running-In Simulations for Pebble-Bed Reactors with Griffin

Griffin, a Multiphysics Object-Oriented Simulation Environment (MOOSE)–based application targeting transient modeling of advanced reactors, has been used recently to model pebble-bed reactors (PBRs). The modeling effort has focused thus far on equilibrium core calculations. A new capability to simulate the running-in phase of PBR operation has been added to Griffin. This work demonstrates the new capability with a coupled multiphysics running-in simulation. Griffin computes power densities in the core at each time step of the running-in simulation and passes these to Pronghorn, which models fluid flow and heat transfer to calculate pebble surface temperatures. These surface temperatures are used along with the power densities in a heat conduction model to compute average fuel and moderator temperatures, which are passed back to Griffin and accounted for with temperature-dependent cross sections. This work also describes a novel methodology for determining appropriate pebble feed rates and control rod positioning during the running-in simulation. Furthermore, the RZ-geometry model used in this work requires minimal computational resources and can be used for optimization and uncertainty studies in future works.

Griffin↗
DOE OSTI2021

Code Development Supporting a Non-Thermal Source of High Fluence Warm X-Ray

A six-month research effort has advanced the hybrid kinetic-fluid modeling capability required for developing non-thermal warm x-ray sources on Z. The three particle treatments of quasi-neutral, multi-fluid, and kinetic are demonstrated in 1D simulations of an Ar gas puff. The simulations determine required resolutions for the advanced implicit solution techniques and debug hybrid particle treatments with equation-of-state and radiation transport. The kinetic treatment is used in preliminary analysis of the non-Maxwellian nature of a gas target. It is also demonstrates the sensitivity of the cyclotron and collision frequencies in determining the transition from thermal to non-thermal particle populations. Finally, a 2D Ar gas puff simulation of a Z shot demonstrates the readiness to proceed with realistic target configurations. The results put us on a very firm footing to proceed to a full LDRD which includes continued development transition criteria and x-ray yield calculation.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Modelling of edge plasma dynamics with active wall boundary conditions

A self-consistent 2D model is presented for transport in boundary plasma and plasma-facing material walls. Plasma dynamics in the domain is represented by a 2D collisional plasma fluid model in the edge-plasma code UEDGE, and transport of hydrogen and heat in the wall is represented by a system of reaction–diffusion equations in the 1D wall code FACE. To account for variation of parameters along the wall, in the coupled model multiple instances of the FACE code run in parallel. Here, the coupled model provides a tool for investigating a range of dynamic plasma–material interactions phenomena in 2D. For demonstration of its capability, one application of particular interest is the role of active wall in tokamak strike point sweeping proposed for mitigation of divertor heat loads. In the present study, the coupled calculations are applied to investigation of the impact of heat and hydrogen transport in the material wall on the divertor plasma and target heat load during sweeping of the target strike point for parameters of a high-power tokamak.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2024

Electrically Powered High-Salinity Brine Separation Using Dimethyl Ether

Dewatering highly saline aqueous streams, from mining and geothermal leachates to industrial wastewater, is essential for effective resource recovery and safe disposal. Membraneless water extraction (MWE) uses a low-polarity solvent to separate water from concentrated aqueous solutions. In this study, we design a new MWE that uses dimethyl ether (DME) to selectively extract water from high-salinity brines, leveraging the volatility of DME to achieve rapid solvent recovery. By separating water and dissolved salts at a liquid–liquid interface, MWE minimizes the deleterious effects of scaling on vulnerable membrane and heat exchanger surfaces, reducing the need for extensive pretreatment and expensive materials. We begin by developing a computational framework for a multistage counterflow liquid–liquid contactor, which extracts water into DME, coupled with a multistage solvent regenerator that uses vapor compression to efficiently separate the desalinated water from the DME extractant. Excess Gibbs free energy and equation of state frameworks are used to model fluid phase equilibria in water–DME–sodium chloride (NaCl) mixtures, with interaction parameters estimated from experimental data. Incorporating equilibrium calculations into a system-scale computational model, we examine the performance of MWE using DME for the first time. Our analysis demonstrates that MWE can concentrate seawater desalination brine (>1.0 mol NaCl kg –1 ) to zero-liquid discharge salinities, with an energy consumption of under 50 kW h per m 3 of water extracted with a solvent recovery ratio greater than 99.9%. We highlight the importance of staging the vapor compression process to simultaneously minimize energy consumption while enabling brine concentration and product water solvent contamination. Finally, the thermodynamic framework developed here allows for the robust evaluation of new MWE solvents and systems for critical brine concentration and fractional precipitation applications.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

Coherent fluctuations in a partially magnetized small magnetron discharge operating on molecular nitrogen

We report experimental data on rotating plasma disturbances in a quasi-steady direct-current magnetron discharge operating with molecular nitrogen at pressures of 27, 40, 67, and 133 Pa. Experiments with a segmented anode measuring the local current flow reveal up to 12 coherent structures (“spokes”) propagating in the +E×B and −E×B azimuthal directions. The current–voltage characteristics are studied and found to follow a negative resistance profile at the lower discharge currents. The existence of coherent structures and the number of spokes observed depend on the discharge current and operating pressure. Lower pressures are more favorable to the retrograde −E×B spoke rotation, which is observed in the 27, 40, and 67 Pa discharges. The results are interpreted with a gradient-driven drift wave model, and using the dispersion relation, we show that the propagation direction depends on the orientation of the local electric field within the plasma. Using an electron fluid model, we show how experimental conditions can lead to field reversals that generate −E×B spoke rotation in the lower pressure discharges.

Physics↗
DOE OSTI2025

Ponderomotive electron physics captured in a single-fluid extended magnetohydrodynamics model

The ponderomotive force, arising from the interaction between electromagnetic waves and plasma, plays a critical role in laser fusion, astrophysical plasmas, and laser diagnostics. Traditionally, modeling this force requires multi-fluid or particle-in-cell simulations due to its strong coupling to electron-scale dynamics. In this work, we demonstrate that a one-fluid, two-temperature extended magnetohydrodynamics (XMHD) model—augmented with a generalized Ohm's law (GOL) including electron inertia—can accurately reproduce key ponderomotive effects. We derive the ponderomotive force within this framework using a phasor-based approach and then validate its nonlinear manifestations through direct numerical simulations in the PERSEUS code, where steepening and density modulation phenomena typically associated with kinetic-scale models are reproduced. These results and prior work establish XMHD as a robust and efficient alternative for modeling nonlinear laser–plasma dynamics, bridging the gap between ideal MHD and fully kinetic approaches.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2026

A filter-dependent granular temperature model from large-scale CFD-DEM data

The computational study of strongly-coupled, gas–solid flows at scales relevant to most environmental and engineering applications requires the use of ‘coarse-grained’ methodologies such as the two-fluid model, particle-in-cell approach or the multiphase Reynolds Averaged Navier–Stokes equations. While these strategies enable computations at desirable length- and time-scales, they rely heavily on models to capture important flow physics that occur at scales smaller than the mesh. To date, the models that do exist are based on a limited set of flow conditions, such as very dilute particle phase. To this end, we leverage a large-scale repository of CFD-DEM data to develop filter-size dependent models for the mean variance in particle volume fraction, a quantity commonly used to assess the degree of clustering, and the granular temperature, a key quantity for accurately predicting gas–solid flows. In conclusion, because of its filter-size dependence, the granular temperature model can be directly translated to coarse-grained approaches and tied directly to grid size.

AMReX↗
DOE OSTI2021

Continuum gyrokinetic simulations of edge plasmas in single-null geometries

The first continuum gyrokinetic calculations of electrostatic ion scale turbulence are presented for the case of a diverted tokamak geometry. The simulation model solves the long-wavelength limit of the full-F gyrokinetic equation for ion species coupled to the quasi-neutrality equation for electrostatic potential variations, where a fluid model is used for an electron response. Furthermore, in order to facilitate simulations of highly-anisotropic microturbulence in the presence of strong magnetic shear and a magnetic X-point, a numerical algorithm utilizing a locally field-aligned multiblock coordinate system has been developed and implemented in the 5D finite-volume code COGENT. In this approach, the toroidal direction is divided into blocks, such that within each block, the cells are field-aligned and a non-matching grid interface is allowed at block boundaries. The toroidal angle corresponds to the “coarse” field-aligned coordinate, whereas the poloidal cross section, comprised of the radial and poloidal directions, is finely gridded to resolve short-scale perpendicular turbulence structures and to support accurate re-mapping (interpolation) at block boundaries. The 5D simulations explore cross-separatrix ion scale turbulence in the presence of a self-consistent radial electric field and address the effects of magnetic-shear stabilization in the X-point region.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2023

Improved melt model for power flow

Accelerators that drive z-pinch experiments transport current densities in excess of 1 MA/cm 2 in order to melt or ionize the target and implode it on axis. These high current densities stress the transmission lines upstream from the target, where rapid electrode heating causes plasma formation, melt, and possibly vaporization. These plasmas negatively impact accelerator efficiency by diverting some portion of the current away from the target, referred to as “current loss”. Simulations that are able to reproduce this behavior may be applied to improving the efficiency of existing accelerators and to designing systems operating at ever higher current densities. The relativistic particle-in-cell code CHICAGO ® is the primary code for modeling power flow on Sandia National Laboratories’ Z accelerator. We report here on new algorithms that incorporate vaporization and melt into the standard power-flow simulation framework. Taking a hybrid approach, the CHICAGO® kinetic/multi-fluid treatment has been expanded to include vaporization while the quasi-neutral equation-of-motion has been updated for melt at high current-densities. For vaporization, a new one-dimensional substrate model provides a more accurate calculation of electrode thermal, mass, and magnetic field diffusion as well as a means of emitting absorbed contaminants and vaporized metal ions. A quasi-fluid model has been implemented expressly to mimic the motion of imploding liners for accurate inductance histories. For melt, a multi-ion Hall-MHD option has been implemented and benchmarked against Alegra MHD. This new model is described with sufficient detail to reproduce these algorithms in any hybrid kinetic code. Physics results from the new code are also presented. A CHICAGO ® Hall-MHD simulation of a radial transmission line demonstrates that Hall physics, not included in Alegra, has no significant impact on the diffusion of electrode material. When surface contaminant desorption is mocked in as a hydrogen surface plasma, both the surface and bulk-material plasmas largely compress under the influence of the j × B force. Similar results are seen in Alegra, which also shows magnetic and material diffusion scaling with peak current. Test vaporization simulations using MagLIF and a power-flow experimental geometry show Fe + ions diffuse only a few hundred µm from the electrodes, so present models of Z power flow remain valid.

43 PARTICLE ACCELERATORS↗
DOE OSTI2024

Integrated modeling of boron powder injection for real-time plasma-facing component conditioning

An integrated modeling framework for investigating the application of solid boron (B) powder injection for real-time surface conditioning of plasma-facing components (PFCs) in tokamak environments is presented. Utilizing the DIII-D impurity powder dropper (IPD) setup, this study simulates B powder injection scenarios ranging from milligrams to tens of milligrams per second, corresponding to boron flux rates of 10 20 –10 21 B/s in standard L-mode conditions. The comprehensive modeling approach combines EMC3-EIRENE for simulating the deuterium plasma background and the Dust Injection Simulator (DIS) for the ablation and transport of the boron powder particles. EMC3 trace impurity fluid modeling results show substantial boron transport to the inboard lower divertor, predominantly influenced by the main ion plasma flow. The dependency on powder particle size (5-250 µm) was found to be insignificant for the scenario considered. The effects of erosion and redeposition were considered to reconcile the discrepancies with experimental observations, which saw substantial deposition on the outer divertor plasma-facing components. For this purpose, the WallDYN3D code was updated to include boron sources within the plasma domain and integrated into the modeling framework. The mixed-material migration modeling shows evolving boron deposition patterns, suggesting the formation of mixed B-C layers or predominantly B coverage depending on the powder mass flow rate. While the modeling outcomes at lower B injection rates tend to align with DIII-D experimental observations, the prediction of near-pure boron layers at higher rates has yet to be experimentally verified in the carbon environment of the DIII-D tokamak. The extensive reach of boron layers found in the modeling suggests the need for modeling that encompasses the entire wall geometry for more accurate experimental correlations. This integrated approach sets a precedent for analyzing and applying real-time in-situ boron coating techniques in advanced tokamak scenarios, potentially extendable to ITER.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2021

A physics-informed and hierarchically regularized data-driven model for predicting fluid flow through porous media

This paper presents a new deep learning data-driven model for predicting structure dependent pore-fluid velocity fields in rock. The model is based on a Convolutional Auto-Encoder (CAE) artificial neural network capable of learning from image data generated by direct numerical simulations of fluid flow through pore-structures, such as by Lattice Boltzmann or molecular dynamics methods. The main novelty of the model in comparison to previous CAE-based data-driven approaches consists of three parts. The first is a methodology for decomposing the full-domain of the porous media into sub-regions, or “sub-domains”, in order to reduce the overall size of the CAE, batch process the sub-domains in parallel, and enable the CAE to learn local and generalizable nonlinear mappings of pore-fluid velocities. The second consists of embedding the finite difference solutions of the incompressible Navier-Stokes and continuity equations into convolutional layers prior to the CAE in order to provide the CAE with knowledge of fluid dynamics physics (PhyFlow). The third main novelty is that the training of the CAE is regularized with a hierarchical loss function that encourages the learning of fluid flow patterns (in a way similar to ranked modes in principal component analysis), ranking from most to least important. This is shown to increase the stability in learning, reduce over-fitting, and promote interpretability of the CAE neural network layers (HierCAE). The comprehensive new data-driven model, which we call the PhyFlow-HierCAE model, is shown to exhibit improved accuracy and generalizability of flow field predictions over conventional CAE models, attributable to the embedded physical knowledge and the hierarchical regularization, as well as realize orders of magnitude speed-ups in computation times as a surrogate for the direct numerical simulations. Examples of training and forward predictions on unseen pore-structures are provided and evaluated for data from Lattice Boltzmann and molecular dynamics simulations of pore-fluid flow. The model is shown to be a fast and accurate emulator (or “surrogate”) for predicting effective permeability of unseen pore-structures based on learning from relatively small direct numerical simulation datasets.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗