Projection-based embedded discrete fracture model (pEDFM) for flow and heat transfer in real-field geological formations with corner-point grid geometriesIn this work, the projection-based embedded discrete fracture model (pEDFM) for corner-point grid (CPG) geometry is developed for simulation of flow and heat transfer in fractured porous media.…Mousa HosseiniMehr, Janio Piguave Tomala, Cornelis Vuik et al.·May 12, 2021SaveLearn
Modeling multiple scattering transient of an ultrashort laser pulse by spherical particlesThe multiple scattering of an ultrashort laser pulse by a turbid dispersive medium (namely a cloud of bubbles in water) is investigated by means of Monte Carlo simulations. The theory of Gouesbet and…Geoffroy Chaussonnet, Loïc Mees, Miloš Šormaz et al.·May 12, 2021SaveLearn
Densest ternary sphere packingsWe present our exhaustive exploration of the densest ternary sphere packings (DTSPs) for 45 radius ratios and 237 kinds of compositions, which is a packing problem of three kinds of hard spheres with…Ryotaro Koshoji, Taisuke Ozaki·May 11, 2021SaveLearn
Random-batch list algorithm for short-range molecular dynamics simulationsWe propose a fast method for the calculation of short-range interactions in molecular dynamics simulations. The so-called random-batch list method is a stochastic version of the classical…Jiuyang Liang, Zhenli Xu, Yue Zhao·May 11, 2021SaveLearn
IE-GSTC Metasurface Field Solver using Surface Susceptibility Tensors with Normal PolarizabilitiesAn Integral Equation (IE) based electromagnetic field solver using metasurface susceptibility tensors is proposed and validated using variety of numerical examples in 2D. The proposed method solves…Tom. J. Smy, Ville Tiukuvaara, Shulabh Gupta·May 11, 2021SaveLearn
Nanowire networks: how does small-world character evolve with dimensionality?Networks of nanowires are currently under consideration for a wide range of electronic and optoelectronic applications. Nanowire devices are usually made by sequential deposition, which inevitably…Ryan K. Daniels, Simon A. Brown·May 11, 2021SaveLearn
pyGDM -- new functionalities and major improvements to the python toolkit for nano-optics full-field simulationspyGDM is a python toolkit for electro-dynamical simulations of individual nano-structures, based on the Green Dyadic Method (GDM). pyGDM uses the concept of a generalized propagator, which allows to…Peter R. Wiecha, Clément Majorel, Arnaud Arbouet et al.·May 10, 2021SaveLearn
Probabilistic forecast of multiphase transport under viscous and buoyancy forces in heterogeneous porous mediaIn this study, we develop a probabilistic approach to map the parametric uncertainty to the output state uncertainty in first-order hyperbolic conservation laws. We analyze this problem for nonlinear…Farzaneh Rajabi, Hamdi A. Tchelepi·May 9, 2021SaveLearn
A second-order numerical method for Landau-Lifshitz-Gilbert equation with large damping parametersA second order accurate numerical scheme is proposed and implemented for the Landau-Lifshitz-Gilbert equation, which models magnetization dynamics in ferromagnetic materials, with large damping…Yongyong Cai, Jingrun Chen, Cheng Wang et al.·May 8, 2021SaveLearn
Data-driven Langevin modeling of nonequilibrium processesGiven nonstationary data from molecular dynamics simulations, a Markovian Langevin model is constructed that aims to reproduce the time evolution of the underlying process. While at equilibrium the…Benjamin Lickert, Steffen Wolf, Gerhard Stock·May 7, 2021SaveLearn
Charge Carrier Transport Mechanism in Ta2O5, TaON and Ta3N5 Studied by Polaron Hopping and Bandlike ModelsTaON and Ta3N5 are considered promising materials for photocatalytic and photoelectrochemical water splitting. But their counterpart Ta2O5 does not have good photocatalytic performance. This may…Qianyu Zhao, Mengsi Cui, Taifeng Liu·May 7, 2021SaveLearn
Analytical derivatives of Neural NetworksWe propose a simple recursive algorithm that allows the computation of the first- and second-order derivatives with respect to the inputs of an arbitrary deep feed forward neural network (DFNN). The…Simone Rodini·May 6, 2021SaveLearn
Adaptive Multigrid Strategy for Geometry Optimization of Large-Scale Three Dimensional Molecular MechanicsIn this paper, we present an efficient adaptive multigrid strategy for the geometry optimization of large-scale three dimensional molecular mechanics. The resulting method can achieve significantly…Kejie Fu, Mingjie Liao, Yangshuai Wang et al.·May 6, 2021SaveLearn
On the numerical evaluation of real-time path integrals: Double exponential integration and the Maslov correctionOoura's double exponential integration formula for Fourier transforms is applied to the oscillatory integrals occuring in the path-integral description of real-time Quantum Mechanics. Due to an…R. Rosenfelder·May 6, 2021SaveLearn
A fluid simulation system based on the MPS methodFluid flow simulation is a highly active area with applications in a wide range of engineering problems and interactive systems. Meshless methods like the Moving Particle Semi-implicit (MPS) are a…André Luiz Buarque Vieira-e-Silva, Caio José dos Santos Brito, Francisco Paulo Magalhães Simões et al.·May 4, 2021SaveLearn
Model discovery in the sparse sampling regimeTo improve the physical understanding and the predictions of complex dynamic systems, such as ocean dynamics and weather predictions, it is of paramount interest to identify interpretable models from…Gert-Jan Both, Georges Tod, Remy Kusters·May 2, 2021SaveLearn
General Implicit Iterative Method for Unified Gas-kinetic SchemeIn order to further enhance the computational efficiency of the implicit unified gas-kinetic scheme (IUGKS, JCP 315 (2016) 16-38) for multi-scale flow simulation, a two-step IUGKS is proposed in this…Xiaocong Xu, Yajun Zhu, Chang Liu et al.·May 2, 2021SaveLearn
Applying physics-based loss functions to neural networks for improved generalizability in mechanics problemsPhysics-Informed Machine Learning (PIML) has gained momentum in the last 5 years with scientists and researchers aiming to utilize the benefits afforded by advances in machine learning, particularly…Samuel J. Raymond, David B. Camarillo·Apr 30, 2021SaveLearn
Speeding up Python-based Lagrangian Fluid-Flow Particle Simulations via Dynamic Collection Data StructuresArray-like collection data structures are widely established in Python's scientific computing-ecosystem for high-performance computations. The structure maps well to regular, gridded lattice…Christian Kehl, Erik van Sebille, Angus Gibson·Apr 30, 2021SaveLearn
A Gradient-based Deep Neural Network Model for Simulating Multiphase Flow in Porous MediaSimulation of multiphase flow in porous media is crucial for the effective management of subsurface energy and environment related activities. The numerical simulators used for modeling such…Bicheng Yan, Dylan Robert Harp, Rajesh J. Pawar·Apr 30, 2021SaveLearn
High-Dimensional Neural Network Potentials for Magnetic Systems Using Spin-Dependent Atom-Centered Symmetry FunctionsMachine learning potentials have emerged as a powerful tool to extend the time and length scales of first principles-quality simulations. Still, most machine learning potentials cannot distinguish…Marco Eckhoff, Jörg Behler·Apr 29, 2021SaveLearn
A Feynman-Kac based numerical method for the exit time probability of a class of transport problemsThe exit time probability, which gives the likelihood that an initial condition leaves a prescribed region of the phase space of a dynamical system at, or before, a given time, is arguably one of the…Minglei Yang, Guannan Zhang, Diego del-Castillo-Negrete et al.·Apr 29, 2021SaveLearn
SGOOP-d: Estimating kinetic distances and reaction coordinate dimensionality for rare event systems from biased/unbiased simulationsUnderstanding kinetics including reaction pathways and associated transition rates is an important yet difficult problem in numerous chemical and biological systems especially in situations with…Sun-Ting Tsai, Zachary Smith, Pratyush Tiwary·Apr 28, 2021SaveLearn
Discovering nonlinear resonances through physics-informed machine learningFor an ensemble of nonlinear systems that model, for instance, molecules or photonic systems, we propose a method that finds efficiently the configuration that has prescribed transfer properties.…G. D. Barmparis, G. P. Tsironis·Apr 27, 2021SaveLearn
Steepest-descent algorithm for simulating plasma-wave caustics via metaplectic geometrical opticsThe design and optimization of radiofrequency-wave systems for fusion applications is often performed using ray-tracing codes, which rely on the geometrical-optics (GO) approximation. However, GO…Sean M. Donnelly, Nicolas A. Lopez, I. Y. Dodin·Apr 27, 2021SaveLearn