Stochastic Constrained Extended System Dynamics for Solving Charge Equilibration ModelsWe present a new stochastic extended Lagrangian solution to charge equilibration that eliminates self-consistent field (SCF) calculations, eliminating the computational bottleneck in solving the…Songchen Tan, Itai Leven, Dong An et al.·May 21, 2020SaveLearn
Gaussian process analysis of Electron Energy Loss Spectroscopy (EELS) data: parallel reconstruction and kernel controlAdvances in hyperspectral imaging modes including electron energy loss spectroscopy (EELS) in scanning transmission electron microscopy (STEM) bring forth the challenges of exploratory and…Sergei V. Kalinin, Andrew R. Lupini, Rama K. Vasudevan et al.·May 21, 2020SaveLearn
SPARC: Simulation Package for Ab-initio Real-space CalculationsWe present SPARC: Simulation Package for Ab-initio Real-space Calculations. SPARC can perform Kohn-Sham density functional theory calculations for isolated systems such as molecules as well as…Qimen Xu, Abhiraj Sharma, Benjamin Comer et al.·May 21, 2020SaveLearn
Magnetic-field modeling with surface currents: Physical and computational principles of bfieldtoolsSurface currents provide a general way to model static magnetic fields in source-free volumes. To facilitate the use of surface currents in magneto-quasistatic problems, we have implemented a set of…Antti J. Mäkinen, Rasmus Zetter, Joonas Iivanainen et al.·May 20, 2020SaveLearn
Magnetic-field modeling with surface currents: Implementation and usage of bfieldtoolsWe present a novel open-source Python software package, bfieldtools, for magneto-quasistatic calculations with current densities on surfaces of arbitrary shape. The core functionality of the software…Rasmus Zetter, Antti J. Mäkinen, Joonas Iivanainen et al.·May 20, 2020SaveLearn
High Rayleigh number variational multiscale large eddy simulations of Rayleigh-Bénard ConvectionThe variational multiscale (VMS) formulation is used to develop residual-based VMS large eddy simulation (LES) models for Rayleigh-Bénard convection. The resulting model is a mixed model that…David Sondak, Thomas M. Smith, Roger P. Pawlowski et al.·May 20, 2020SaveLearn
Numerical study of extreme mechanical force exerted by a turbulent flow on a bluff body by direct and rare-event sampling techniquesThis study investigates, by means of numerical simulations, extreme mechanical force exerted by a turbulent flow impinging on a bluff body, and examines the relevance of two distinct rare-event…Thibault Lestang, Freddy Bouchet, Emmanuel Lévêque·May 19, 2020SaveLearn
Numerical Simulations of Electrohydrodynamics flow model based on Burgers' Equation with Transport of BubblesIn this paper we present numerical models for electrodynamical flows with time-dependent electrical fields with transport of bubbles. Such models are applied in e-jet printing, e.g., additive…Jürgen Geiser, Paul Mertin·May 19, 2020SaveLearn
The OpenKIM Processing Pipeline: A Cloud-Based Automatic Materials Property Computation EngineThe Open Knowledgebase of Interatomic Models (OpenKIM) project is a framework intended to facilitate access to standardized implementations of interatomic models for molecular simulations along with…Daniel S. Karls, Matthew Bierbaum, Alexander A. Alemi et al.·May 18, 2020SaveLearn
Automating Turbulence Modeling by Multi-Agent Reinforcement LearningThe modeling of turbulent flows is critical to scientific and engineering problems ranging from aircraft design to weather forecasting and climate prediction. Over the last sixty years numerous…Guido Novati, Hugues Lascombes de Laroussilhe, Petros Koumoutsakos·May 18, 2020SaveLearn
A non-reflective boundary condition for LBM based on the assumption of non-equilibrium symmetryIn this study a new type of non-reflective boundary condition (NRBC) for the Lattice Boltzmann Method (LBM) is proposed; the Non-equilibrium Symmetry Boundary Condition (NSBC). The idea behind this…R. Euser, C. Vuik·May 18, 2020SaveLearn
Physics-informed Neural Networks for Solving Inverse Problems of Nonlinear Biot's Equations: Batch TrainingIn biomedical engineering, earthquake prediction, and underground energy harvesting, it is crucial to indirectly estimate the physical properties of porous media since the direct measurement of those…Teeratorn Kadeethum, Thomas M Jørgensen, Hamidreza M Nick·May 18, 2020SaveLearn
DiscretizationNet: A Machine-Learning based solver for Navier-Stokes Equations using Finite Volume DiscretizationOver the last few decades, existing Partial Differential Equation (PDE) solvers have demonstrated a tremendous success in solving complex, non-linear PDEs. Although accurate, these PDE solvers are…Rishikesh Ranade, Chris Hill, Jay Pathak·May 17, 2020SaveLearn
Deep-learning of Parametric Partial Differential Equations from Sparse and Noisy DataData-driven methods have recently made great progress in the discovery of partial differential equations (PDEs) from spatial-temporal data. However, several challenges remain to be solved, including…Hao Xu, Dongxiao Zhang, Junsheng Zeng·May 16, 2020SaveLearn
A Combined Data-driven and Physics-driven Method for Steady Heat Conduction Prediction using Deep Convolutional Neural NetworksWith several advantages and as an alternative to predict physics field, machine learning methods can be classified into two distinct types: data-driven relying on training data and physics-driven…Hao Ma, Xiangyu Hu, Yuxuan Zhang et al.·May 16, 2020SaveLearn
An invertible crystallographic representation for general inverse design of inorganic crystals with targeted propertiesRealizing general inverse design could greatly accelerate the discovery of new materials with user-defined properties. However, state-of-the-art generative models tend to be limited to a specific…Zekun Ren, Siyu Isaac Parker Tian, Juhwan Noh et al.·May 15, 2020SaveLearn
Performance of the BGSDC integrator for computing fast ion trajectories in nuclear fusion reactorsModelling neutral beam injection (NBI) in fusion reactors requires computing the trajectories of large ensembles of particles. Slowing down times of up to one second combined with nanosecond time…Krasymyr Tretiak, James Buchanan, Rob Akers et al.·May 15, 2020SaveLearn
High-order gas-kinetic scheme with parallel computation for direct numerical simulation of turbulent flowsThe performance of high-order gas-kinetic scheme (HGKS) has been investigated for the direct numerical simulation (DNS) of isotropic compressible turbulence up to the supersonic regime. Due to the…Guiyu Cao, Liang Pan, Kun Xu·May 15, 2020SaveLearn
Computing the heat conductivity of fluids from density fluctuationsEquilibrium molecular dynamics simulations, in combination with the Green-Kubo (GK) method, have been extensively used to compute the thermal conductivity of liquids. However, the GK method relies on…Bingqing Cheng, Daan Frenkel·May 15, 2020SaveLearn
Comparison of Macro- and Microscopic Solutions of the Riemann Problem II. Two-Phase Shock TubeThe Riemann problem is one of the basic building blocks for numerical methods in computational fluid mechanics. Nonetheless, there are still open questions and gaps in theory and modelling for…Timon Hitz, Steven Joens, Matthias Heinen et al.·May 14, 2020SaveLearn
Negative thermal expansion induced suppression of wear in dry sliding frictionSurface temperature is among crucial factors, which control wear during sliding dry contact. Using computer modeling, we study the possibility to achieve close to zero rate of surface wear during…Aleksandr S. Grigoriev, Evgeny V. Shilko, Andrey I. Dmitriev et al.·May 14, 2020SaveLearn
Fluid-structure interaction with H(div)-conforming finite elementsIn this paper a novel application of the (high-order) H(div)-conforming Hybrid Discontinuous Galerkin finite element method for monolithic fluid-structure interaction (FSI) is presented. The…Michael Neunteufel, Joachim Schöberl·May 13, 2020SaveLearn
Shedding Light on Moire Excitons: A First-Principles PerspectiveMoire superlattices in van der Waals (vdW) heterostructures could trap strongly bonded and long lived interlayer excitons. Assumed to be localized, these moire excitons could form ordered quantum dot…Hongli Guo, Xu Zhang, Gang Lu·May 13, 2020SaveLearn
Magnetic circular dichroism spectra from resonant and damped coupled cluster response theoryA computational expression for the Faraday A term of magnetic circular dichroism (MCD) is derived within coupled cluster response theory and alternative computational expressions for the B term are…Rasmus Faber, Simone Ghidinelli, Christof Hättig et al.·May 13, 2020SaveLearn
On the derivatives of feed-forward neural networksIn this paper we present a C++ implementation of the analytic derivative of a feed-forward neural network with respect to its free parameters for an arbitrary architecture, known as back-propagation.…Rabah Abdul Khalek, Valerio Bertone·May 12, 2020SaveLearn