output
20042026
most citedScikit-learn: Machine Learning in Python

63.6k citations

Showing 2019Show all

20 papers · 1 filter

cs.SE2019★ 6 cited

Predicting Performance of Software Configurations: There is no Silver Bullet

Alexander Grebhahn, Norbert Siegmund, Sven Apel

Many software systems offer configuration options to tailor their functionality and non-functional properties (e.g., performance). Often, users are interested in the (performance-)…

physics.comp-ph2019★ 2 cited

A meshfree formulation for large deformation analysis of flexoelectric structures accounting for the surface effects

Xiaoying Zhuang, S. S. Nanthakumar, Timon Rabczuk

In this work, we present a compactly supported radial basis function (CSRBF) based meshfree method to analyse geometrically nonlinear flexoelectric nanostructures considering surfa…

physics.app-ph2019★ 10 cited

Aromatic molecular junctions between graphene sheets: a molecular dynamics screening for enhanced thermal conductance

Alessandro Di Pierro, Maria Mar Bernal, Diego Martinez +3

The proper design and synthesis of molecular junctions for the purpose of establishing percolative networks of conductive nanoparticles represent an opportunity to develop more eff…

stat.ML2019★ 2.1k cited

An Energy Approach to the Solution of Partial Differential Equations in Computational Mechanics via Machine Learning: Concepts, Implementation and Applications

Esteban Samaniego, Cosmin Anitescu, Somdatta Goswami +5

Partial Differential Equations (PDE) are fundamental to model different phenomena in science and engineering mathematically. Solving them is a crucial step towards a precise knowle…

cs.CY2019★ 3 cited

Elementary Interactions An Approach in Decision Tool Development

Heinrich Söbke, Andrea Lück

Multi-Criteria Decision Analysis (MCDA) is an established methodology to support decision making of multi-objective problems. For conducting a MCDA, in most cases a set of objectiv…

stat.ML2019★ 2 cited

Transfer learning enhanced physics informed neural network for phase-field modeling of fracture

Somdatta Goswami, Cosmin Anitescu, Souvik Chakraborty +1

We present a new physics informed neural network (PINN) algorithm for solving brittle fracture problems. While most of the PINN algorithms available in the literature minimize the…

cs.CE2019★ 10 cited

A surrogate model for computational homogenization of elastostatics at finite strain using the HDMR-based neural network approximator

Vien Minh Nguyen-Thanh, Lu Trong Khiem Nguyen, Timon Rabczuk +1

We propose a surrogate model for two-scale computational homogenization of elastostatics at finite strains. The macroscopic constitutive law is made numerically available via an ex…

cond-mat.mtrl-sci2019★ 179 cited

Outstanding strength, optical characteristics and thermal conductivity of graphene-like BC and BCN semiconductors

Bohayra Mortazavi, Masoud Shahrokhi, Mostafa Raeisi +3

Carbon based two-dimensional (2D) materials with honeycomb lattices, like graphene, polyaniline carbon-nitride (CN) and boron-carbide (BC) exhibit exceptional physical prop…

math.NA2019★ 27 cited

Isogeometric Analysis for Surface PDEs with Extended Loop Subdivision

Qing Pan, Timon Rabczuk, Gang Xu +1

We investigate the isogeometric analysis for surface PDEs based on the extended Loop subdivision approach. The basis functions consisting of quartic box-splines corresponding to ea…

math.NA2019

Threshold shift method for reliability-based design optimization

Somdatta Goswami, Souvik Chakraborty, Rajib Chowdhury +1

We present a novel approach, referred to as the 'threshold shift method' (TSM), for reliability based design optimization (RBDO). The proposed approach is similar in spirit with th…

cond-mat.mes-hall2019★ 147 cited

Enhancement in hydrogen storage capacities of light metal functionalized Boron Graphdiyne nanosheets

T. Hussain, B. Mortazavi, H. Bae +3

The recent experimental synthesis of the two-dimensional (2D)boron-graphdiyne (BGDY) nanosheet has motivated us to investigate its structural, electronic,and energy storage propert…

cond-mat.mes-hall2019★ 50 cited

Theoretical realization of two-dimensional M3(C6X6)2(M= Co, Cr, Cu, Fe, Mn, Ni, Pd, Rh and X= O, S, Se) metal-organic frameworks

Bohayra Mortazavi, Masoud Shahrokhi, Tanveer Hussain +2

Most recently, Cu-hexahydroxybenzene MOF was for the time experimentally realized, through a kinetically controlled approach. Cu-HHB belongs to the family of conductive MOFs with a…

cond-mat.mes-hall2019★ 64 cited

Nanoporous graphene: a 2D semiconductor with anisotropic mechanical, optical and thermal conduction properties

Bohayra Mortazavi, Mohamed E. Madjet, Masoud Shahrokhi +3

Nanoporous graphene (NPG), consisting of ordered arrays of nanopores separated by graphene nanoribbons was recently realized using a bottom-up synthesis method (Science 360(2018),…

cond-mat.mes-hall2019★ 37 cited

Thermal bridging of graphene nanosheets via covalent molecular junctions. a Non-Equilibrium Green Functions Density Functional Tight-Binding study

Diego Martinez, Alessandro di Pierro, Alessandro Pecchia +7

Despite the uniquely high thermal conductivity of graphene is well known, the exploitation of graphene into thermally conductive nanomaterials and devices is limited by the ineffic…

physics.geo-ph2019★ 380 cited

A phase-field modeling approach of fracture propagation in poroelastic media

Shuwei Zhou, Xiaoying Zhuang, Timon Rabczuk

This paper proposes a phase field model for fracture in poroelastic media. The porous medium is modeled based on the classical Biot poroelasticity theory and the fracture behavior…

cond-mat.soft2019★ 372 cited

Phase field modelling of crack propagation, branching and coalescence in rocks

Shuwei Zhou, Xiaoying Zhuang, Hehua Zhu +1

We present a phase field model (PFM) for simulating complex crack patterns including crack propagation, branching and coalescence in rock. The phase field model is implemented in C…

cs.CE2019★ 446 cited

Phase field modeling of quasi-static and dynamic crack propagation: COMSOL implementation and case studies

Shuwei Zhou, Timon Rabczuk, Xiaoying Zhuang

The phase-field model (PFM) represents the crack geometry in a diffusive way without introducing sharp discontinuities. This feature enables PFM to effectively model crack propagat…

cs.CE2019★ 173 cited

A NURBS-based Inverse Analysis for Reconstruction of Nonlinear Deformations of Thin Shell Structures

N. Vu-Bac, T. X. Duong, T. Lahmer +4

This article presents original work combining a NURBS-based inverse analysis with both kinematic and constitutive nonlinearities to recover the applied loads and deformations of th…

physics.comp-ph2019★ 51 cited

A Multiscale Multisurface Constitutive Model for The Thermo-Plastic Behavior of Polyethylene

N. Vu-Bac, P. Areias, T. Rabczuk

We present a multiscale model bridging length and time scales from molecular to continuum levels with the objective of predicting the yield behavior of amorphous glassy polyethylen…

physics.comp-ph2019★ 312 cited

A multi-material level set-based topology optimization of flexoelectric composites

Hamid Ghasemi, Harold S. Park, Timon Rabczuk

We present a computational design methodology for topology optimization of multi-material-based flexoelectric composites. The methodology extends our recently proposed design metho…