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In microfluidic systems, droplets undergo intricate deformations as they traverse flow-focusing junctions, posing a challenging task for accurate measurement, especially during short transit times. This study investigates the physical…

Discrete particle simulations are widely used to study large-scale particulate flows in complex geometries where particle-particle and particle-fluid interactions require an adequate representation but the computational cost has to be kept…

Computational Engineering, Finance, and Science · Computer Science 2017-11-02 Christoph Rettinger , Ulrich Rüde

Understanding the spontaneous emergence of dislocation patterns during plastic deformation is a long standing challenge in dislocation theory. During the past decades several phenomenological continuum models of dislocation patterning were…

Materials Science · Physics 2016-06-22 Istvan Groma , Michael Zaiser , Peter Dusan Ispanovity

Particulate Stokesian flows describe the hydrodynamics of rigid or deformable particles in Stokes flows. Due to highly nonlinear fluid-structure interaction dynamics, moving interfaces, and multiple scales, numerical simulations of such…

Computational Physics · Physics 2019-07-03 Gokberk Kabacaoglu , George Biros

Crystal plasticity models are a powerful tool for predicting the deformation behaviour of polycrystalline materials accounting for the underlying grain morphology and texture. These models typically have a large number of parameters, an…

Materials Science · Physics 2023-12-20 Hugh Dorward , David M. Knowles , Eralp Demir , Mahmoud Mostafavi , Matthew J. Peel

Bayesian filtering is a well-known problem that aims to estimate plausible states of a dynamical system from observations. Among existing approaches to solve this problem, particle filters are theoretically exact for non-linear dynamics and…

Machine Learning · Computer Science 2026-05-20 Thomas Savary , François Rozet , Gilles Louppe

Gaussian processes are a powerful framework for quantifying uncertainty and for sequential decision-making but are limited by the requirement of solving linear systems. In general, this has a cubic cost in dataset size and is sensitive to…

Multiscale modeling is a systematic approach to describe the behavior of complex systems by coupling models from different scales. The approach has been demonstrated to be very effective in areas of science as diverse as materials science,…

Computational Physics · Physics 2020-01-08 Ting Wang , Kenneth W. Leiter , Petr Plechac , Jaroslaw Knap

In many applications, flow measurements are usually sparse and possibly noisy. The reconstruction of a high-resolution flow field from limited and imperfect flow information is significant yet challenging. In this work, we propose an…

Computational Physics · Physics 2020-01-17 Luning Sun , Jian-Xun Wang

3D Gaussian Splatting (3DGS) has become an emerging tool for dynamic scene reconstruction. However, existing methods focus mainly on extending static 3DGS into a time-variant representation, while overlooking the rich motion information…

Computer Vision and Pattern Recognition · Computer Science 2024-03-19 Zhiyang Guo , Wengang Zhou , Li Li , Min Wang , Houqiang Li

Granular intrusion is commonly observed in natural and human-made settings. Unlike typical solids and fluids, granular media can simultaneously display fluid-like and solid-like characteristics in a variety of intrusion scenarios. This…

Soft Condensed Matter · Physics 2021-07-16 Shashank Agarwal , Andras Karsai , Daniel I Goldman , Ken Kamrin

We present a multiscale simulation algorithm for amorphous materials, which we illustrate and validate in a canonical case of dense granular flow. Our algorithm is based on the recently proposed Spot Model, where particles in a dense random…

Soft Condensed Matter · Physics 2009-11-11 Chris H. Rycroft , Martin Z. Bazant , Gary S. Grest , James W. Landry

Dynamical system state estimation and parameter calibration problems are ubiquitous across science and engineering. Bayesian approaches to the problem are the gold standard as they allow for the quantification of uncertainties and enable…

Data Analysis, Statistics and Probability · Physics 2024-11-12 Kairui Hao , Ilias Bilionis

We investigate active learning in Gaussian Process state-space models (GPSSM). Our problem is to actively steer the system through latent states by determining its inputs such that the underlying dynamics can be optimally learned by a…

Machine Learning · Computer Science 2021-08-03 Hon Sum Alec Yu , Dingling Yao , Christoph Zimmer , Marc Toussaint , Duy Nguyen-Tuong

Dynamic scene reconstruction represents a fundamental yet demanding challenge in computer vision and robotics. While recent progress in 3DGS-based methods has advanced dynamic scene modeling, obtaining high-fidelity rendering and accurate…

Computer Vision and Pattern Recognition · Computer Science 2026-05-12 Yinan Deng , Jianyu Dou , Jiahui Wang , Jingyu Zhao , Yi Yang , Yufeng Yue

Dynamic scene reconstruction is a long-term challenge in the field of 3D vision. Recently, the emergence of 3D Gaussian Splatting has provided new insights into this problem. Although subsequent efforts rapidly extend static 3D Gaussian to…

Computer Vision and Pattern Recognition · Computer Science 2024-10-11 Ruijie Zhu , Yanzhe Liang , Hanzhi Chang , Jiacheng Deng , Jiahao Lu , Wenfei Yang , Tianzhu Zhang , Yongdong Zhang

Stressed dislocation pattern formation in crystal plasticity at finite deformation is demonstrated for the first time. Size effects are also demonstrated within the same mathematical model. The model involves two extra material parameters…

Materials Science · Physics 2018-12-04 Rajat Arora , Amit Acharya

One of the challenges encountered by computational simulations at exascale is the reliability of simulations in the face of hardware and software faults. These faults, expected to increase with the complexity of the computational systems,…

Fluid Dynamics · Physics 2019-02-19 Marc T. Henry de Frahan , Ray W. Grout

We consider a two-phase Darcy flow in a fractured porous medium consisting in a matrix flow coupled with a tangential flow in the fractures, described as a network of planar surfaces. This flow model is also coupled with the mechanical…

Numerical Analysis · Mathematics 2021-07-15 Francesco Bonaldi , Konstantin Brenner , Jérôme Droniou , Roland Masson

Crystal plasticity is the result of the motion and interaction of dislocations. There is, however, still a major gap between microscopic and mesoscopic simulations and continuum crystal plasticity models. Only recently a higher dimensional…

Materials Science · Physics 2010-10-15 Thomas Hochrainer , Michael Zaiser , Peter Gumbsch
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