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In recent years, large-scale numerical simulations played an essential role in estimating the effects of explosion events in urban environments, for the purpose of ensuring the security and safety of cities. Such simulations are…

In three-dimensional discrete element method (DEM) simulations, the particle motions within a granular assembly can produce bewildering sequences of movements at the contacts between particle pairs. With frictional contacts, the…

Soft Condensed Matter · Physics 2018-12-27 Matthew R. Kuhn

To date, the simulation of organ deformations for applications like therapy planning or image-guided interventions is calculated by solving the elastodynamics equations. While efficient solvers have been proposed for fast simulations,…

Quantitative Methods · Quantitative Biology 2018-12-18 Felix Meister , Tiziano Passerini , Viorel Mihalef , Ahmet Tuysuzoglu , Andreas Maier , Tommaso Mansi

The semi-implicit (partly decoupled, also called staggered or fraction-step) time discretization is applied to compressible nonlinear dynamical models of viscoelastic solids in the Eulerian description, i.e.\ in the actual deforming…

Numerical Analysis · Mathematics 2025-10-14 Tomáš Roubíček

The scientific computation methods development in conjunction with artificial intelligence technologies remains a hot research topic. Finding a balance between lightweight and accurate computations is a solid foundation for this direction.…

Machine Learning · Computer Science 2025-07-03 Nikita Sakovich , Dmitry Aksenov , Ekaterina Pleshakova , Sergey Gataullin

This paper presents the first application of the direct parametrisation method for invariant manifolds to a fully coupled multiphysics problem involving the nonlinear vibrations of deformable structures subjected to an electrostatic field.…

Numerical Analysis · Mathematics 2023-12-25 Attilio Frangi , Alessio Colombo , Alessandra Vizzaccaro , Cyril Touzé

The micropolar Rayleigh-B{\'e}nard convection system, which consists of Navier-Stokes equations, the angular momentum equation, and the heat equation, is a strongly nonlinear, coupled, and saddle point structural multiphysics system. A…

Numerical Analysis · Mathematics 2025-12-03 Ming Cui , Akang Hou , Xiaoyu Dong

We consider the problem of estimating parameters in large-scale weakly nonlinear inverse problems for which the underlying governing equations is a linear, time-dependent, parabolic partial differential equation. A major challenge in…

Numerical Analysis · Mathematics 2016-05-04 Tania Bakhos , Arvind K. Saibaba , Peter K. Kitanidis

This paper presents an arbitrary order locking-free numerical scheme for linear elasticity on general polygonal/polyhedral partitions by using weak Galerkin (WG) finite element methods. Like other WG methods, the key idea for the linear…

Numerical Analysis · Mathematics 2015-08-18 Chunmei Wang , Junping Wang , Ruishu Wang , Ran Zhang

We propose a deep neural network (DNN) as a fast surrogate model for local stress (and in principle strain) calculation in inhomogeneous non-linear material systems. We show that the DNN predicts the local stresses with about 3.8% mean…

Materials Science · Physics 2021-03-17 Jaber Rezaei Mianroodi , Nima H. Siboni , Dierk Raabe

This work deals with Direct Numerical Simulations (DNS) and Large Eddy Simulations (LES) of turbulent gravity currents, performed by means of a Discontinuous Galerkin (DG) Finite Element method. In particular, a DG-LES approach in which the…

Computational Physics · Physics 2016-12-23 C. Bassi , A. Abbà , L. Bonaventura , L. Valdettaro

In this paper, we improve upon the discontinuous Galerkin (DG) method for Hamilton-Jacobi (HJ) equation with convex Hamiltonians in (Y. Cheng and C.-W. Shu, J. Comput. Phys. 223:398-415,2007) and develop a new DG method for directly solving…

Numerical Analysis · Mathematics 2015-06-17 Yingda Cheng , Zixuan Wang

We present the Neural Approximated Virtual Element Method to numerically solve elasticity problems. This hybrid technique combines classical concepts from the Finite Element Method and the Virtual Element Method with recent advances in deep…

Numerical Analysis · Mathematics 2025-07-09 Stefano Berrone , Moreno Pintore , Gioana Teora

In dynamical systems, it is advantageous to identify regions of flow which can exhibit maximal influence on nearby behaviour. Hyperbolic Lagrangian Coherent Structures have been introduced to obtain two-dimensional surfaces which maximise…

Fluid Dynamics · Physics 2022-07-25 Jack Tyler , Alexander Wittig

Apart from solving complicated problems that require a certain level of intelligence, fine-tuned deep neural networks can also create fast algorithms for slow, numerical tasks. In this paper, we introduce an improved version of [1]'s work,…

Robotics · Computer Science 2018-09-17 Peiyuan Liao , Jiajun Mao

Achieving large-scale kinetic modelling is a crucial task for the development and optimization of modern plasma devices. With the trend of decreasing pressure in applications such as plasma etching, kinetic simulations are necessary to…

The paper presents an approach for the identification of elasto-static parameters of a robotic manipulator using the virtual experiments in a CAD environment. It is based on the numerical processing of the data extracted from the finite…

Robotics · Computer Science 2013-11-27 Alexandr Klimchik , Anatol Pashkevich , Damien Chablat

Finite element schemes based on discontinuous Galerkin methods possess features amenable to massively parallel computing accelerated with general purpose graphics processing units (GPUs). However, the computational performance of such…

Computational Physics · Physics 2016-04-20 Axel Modave , Amik St-Cyr , Tim Warburton

Adding flexible polymers to a Newtonian solvent confers complex properties to the resulting solution. The additional complexity substantially increases the computational cost of numerical simulations, which often makes them prohibitively…

Fluid Dynamics · Physics 2026-04-30 Christian Amor , Adrián Corrochano , Marco Edoardo Rosti , Soledad Le Clainche

Differentiable programming is revolutionizing computational science by enabling automatic differentiation (AD) of numerical simulations. While first-order gradients are well-established, second-order derivatives (Hessians) for implicit…

Computational Engineering, Finance, and Science · Computer Science 2025-05-20 Tianju Xue