Machine learning assisted multiscale modeling of composite phase change materials for Li-ion batteries thermal managementIn this work, we develop a combined convolutional neural networks (CNNs) and finite element method (FEM) to examine the effective thermal properties of composite phase change materials (CPCMs)…Felix Kolodziejczyk, Bohayra Mortazavi, Timon Rabczuk et al.·Mar 24, 2021SaveLearn
A Massively Parallel Time-Domain Coupled Electrodynamics-Micromagnetics SolverWe present a new, high-performance coupled electrodynamics-micromagnetics solver for full physical modeling of signals in microelectronic circuitry. The overall strategy couples a finite-difference…Zhi Yao, Revathi Jambunathan, Yadong Zeng et al.·Mar 23, 2021SaveLearn
Towards Quantum Monte Carlo Forces on Heavier Ions: Scaling PropertiesQuantum Monte Carlo (QMC) forces have been studied extensively in recent decades because of their importance with spectroscopic observables and geometry optimization. Here we benchmark the accuracy…Juha Tiihonen, Raymond C. Clay, Jaron T. Krogel·Mar 23, 2021SaveLearn
Automated fragment identification for electron ionisation mass spectrometry: application to atmospheric measurements of halocarbonsNon-target screening consists in searching a sample for all present substances, suspected or unknown, with very little prior knowledge about the sample. This approach has been introduced more than a…Myriam Guillevic, Aurore Guillevic, Martin Vollmer et al.·Mar 23, 2021SaveLearn
Fractional Derivative Modification of a Drude ModelA modification of the Drude dispersive model based on fractional time derivative is presented. The dielectric susceptibility is calculated analytically and simulated numerically, showing a good…Karol Karpiński, Sylwia Zielińska - Raczyńska, David Ziemkiewicz·Mar 20, 2021SaveLearn
Accelerating GMRES with Deep Learning in Real-TimeGMRES is a powerful numerical solver used to find solutions to extremely large systems of linear equations. These systems of equations appear in many applications in science and engineering. Here we…Kevin Luna, Katherine Klymko, Johannes P. Blaschke·Mar 19, 2021SaveLearn
A flux reconstruction kinetic scheme for the Boltzmann equationIt is challenging to solve the Boltzmann equation accurately due to the extremely high dimensionality and nonlinearity. This paper addresses the idea and implementation of the first flux…Tianbai Xiao·Mar 18, 2021SaveLearn
Evolutional Deep Neural NetworkThe notion of an Evolutional Deep Neural Network (EDNN) is introduced for the solution of partial differential equations (PDE). The parameters of the network are trained to represent the initial…Yifan Du, Tamer A. Zaki·Mar 18, 2021SaveLearn
PythonFOAM: In-situ data analyses with OpenFOAM and PythonWe outline the development of a general-purpose Python-based data analysis tool for OpenFOAM. Our implementation relies on the construction of OpenFOAM applications that have bindings to data…Romit Maulik, Dimitrios Fytanidis, Bethany Lusch et al.·Mar 17, 2021SaveLearn
Machine learning methods for the prediction of micromagnetic magnetization dynamicsMachine learning (ML) entered the field of computational micromagnetics only recently. The main objective of these new approaches is the automatization of solutions of parameter-dependent problems in…Sebastian Schaffer, Norbert J. Mauser, Thomas Schrefl et al.·Mar 16, 2021SaveLearn
Predicting the phase behaviors of superionic water at planetary conditionsMost water in the universe may be superionic, and its thermodynamic and transport properties are crucial for planetary science but difficult to probe experimentally or theoretically. We use machine…Bingqing Cheng, Mandy Bethkenhagen, Chris J. Pickard et al.·Mar 16, 2021SaveLearn
The BLUES function method applied to partial differential equations and analytic approximants for interface growth under shearAn iteration sequence based on the BLUES (beyond linear use of equation superposition) function method is presented for calculating analytic approximants to solutions of nonlinear partial…Jonas Berx, Joseph O. Indekeu·Mar 15, 2021SaveLearn
Ab initio path integral Monte Carlo approach to the momentum distribution of the uniform electron gas at finite temperature without fixed nodesWe present extensive new ab intio path integral Monte Carlo results for the momentum distribution function n(k) of the uniform electron gas (UEG) in the warm dense matter (WDM)…Tobias Dornheim, Maximilian Böhme, Burkhard Militzer et al.·Mar 15, 2021SaveLearn
Physics-Informed Neural Network Method for Solving One-Dimensional Advection Equation Using PyTorchNumerical solutions to the equation for advection are determined using different finite-difference approximations and physics-informed neural networks (PINNs) under conditions that allow an…Shashank Reddy Vadyala, Sai Nethra Betgeri·Mar 15, 2021SaveLearn
Contour Exploration with Potentiostatic KinematicsWe introduce a method of exploring potential energy contours in complex dynamical systems based on potentiostatic kinematics wherein the systems are evolved with minimal changes to their potential…Michael J. Waters, James M. Rondinelli·Mar 14, 2021SaveLearn
A Modified Batch Intrinsic Plasticity Method for Pre-training the Random Coefficients of Extreme Learning MachinesIn extreme learning machines (ELM) the hidden-layer coefficients are randomly set and fixed, while the output-layer coefficients of the neural network are computed by a least squares method. The…Suchuan Dong, Zongwei Li·Mar 14, 2021SaveLearn
Physics-Informed Neural Networks for Solving Multiscale Mode-Resolved Phonon Boltzmann Transport EquationBoltzmann transport equation (BTE) is an ideal tool to describe the multiscale phonon transport phenomena, which are critical to applications like microelectronics cooling. Numerically solving phonon…Ruiyang Li, Eungkyu Lee, Tengfei Luo·Mar 14, 2021SaveLearn
Data-driven low-fidelity models for multi-fidelity Monte Carlo sampling in plasma micro-turbulence analysisThe linear micro-instabilities driving turbulent transport in magnetized fusion plasmas (as well as the respective nonlinear saturation mechanisms) are known to be sensitive with respect to various…Julia Konrad, Ionut-Gabriel Farcas, Benjamin Peherstorfer et al.·Mar 12, 2021SaveLearn
Quasi-Helmholtz Decomposition, Gauss' Laws and Charge Conservation for Finite Element Particle-in-CellDevelopment of particle in cell methods using finite element based methods (FEMs) have been a topic of renewed interest; this has largely been driven by (a) the ability of finite element methods to…Scott O'Connor, Zane D. Crawford, O. H. Ramachandran et al.·Mar 11, 2021SaveLearn
Saddle point method for transient processes in waveguidesA modification of the saddle point method is proposed for computation of non-stationary wave processes (pulses) in waveguides. The dispersion diagram of the waveguide is continued analytically. A set…A. V. Shanin, A. I. Korolkov, K. S. Kniazeva·Mar 11, 2021SaveLearn
Compression of Far-Fields in the Fast Multipole Method via Tucker DecompositionTucker decomposition is proposed to reduce the memory requirement of the far-fields in the fast multipole method (FMM)-accelerated surface integral equation simulators. It is particularly used to…Cheng Qian, Mingyu Wang, Abdulkadir C. Yucel·Mar 10, 2021SaveLearn
A Bayesian Multiscale Deep Learning Framework for Flows in Random MediaFine-scale simulation of complex systems governed by multiscale partial differential equations (PDEs) is computationally expensive and various multiscale methods have been developed for addressing…Govinda Anantha Padmanabha, Nicholas Zabaras·Mar 8, 2021SaveLearn
Training Data Set Refinement for the Machine Learning Potential of Li-Si Alloys via Structural Similarity AnalysisMachine learning potential enables molecular dynamics simulations of systems beyond the capability of classical force fields. The traditional approach to develop structural sets for training machine…Nan Xu, Chen Li, Mandi Fang et al.·Mar 7, 2021SaveLearn
Efficiency gains of a multi-scale integration method applied to a scale-separated model for rapidly rotating dynamosNumerical geodynamo simulations with parameters close to an Earth-like regime would be of great interest for understanding the dynamics of the Earth's liquid outer core and the associated geomagnetic…Krasymyr Tretiak, Meredith Plumley, Michael Calkins et al.·Mar 5, 2021SaveLearn
Electronic structures and topological phases of magnetic layered materials MnBi2Te4, MnBi2Se4 and MnSb2Te4First-principles calculations are performed to study the electronic structures and topological phases of magnetic layered materials MnBi2Te4, MnBi2Se4 and MnSb2Te4 under different film thicknesses,…Ping Li, Jiangying Yu, Ying Wang et al.·Mar 5, 2021SaveLearn