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相关论文: Reactive Particle-tracking Solutions to a Benchmar…

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Despite significant advances in particle imaging technologies over the past two decades, few advances have been made in particle tracking, i.e. linking individual particle positions across time series data. The state-of-the-art tracking…

软凝聚态物质 · 物理学 2022-01-25 Ella M. King , Zizhao Wang , David A. Weitz , Frans Spaepen , Michael P. Brenner

Particle filters flexibly represent multiple posterior modes nonparametrically, via a collection of weighted samples, but have classically been applied to tracking problems with known dynamics and observation likelihoods. Such generative…

机器学习 · 计算机科学 2024-04-16 Ali Younis , Erik Sudderth

Non-invasive flow measurement techniques, such as particle tracking velocimetry, resolve 3D velocity fields by pairing tracer particle positions in successive time steps. These trajectories are crucial for evaluating physical quantities…

数据分析、统计与概率 · 物理学 2024-07-08 Kairui Hao , Atharva Hans , Pavlos Vlachos , Ilias Bilionis

Modeling dispersed solid phases in fluids still represents a computational challenge when considering a small-scale coupling in wide systems, such as the atmosphere or industrial processes at high Reynolds numbers. A numerical method is…

流体动力学 · 物理学 2015-08-13 François Laenen , Giorgio Krstulovic , Jérémie Bec

This paper demonstrates particle tracking velocimetry performed for a model system wherein particle-laden liquid metal flow about a cylindrical obstacle was studied. We present the image processing methodology developed for particle…

Particle tracking in large-scale numerical simulations of turbulent flows presents one of the major bottlenecks in parallel performance and scaling efficiency. Here, we describe a particle tracking algorithm for large-scale parallel…

流体动力学 · 物理学 2022-05-31 Cristian C. Lalescu , Bérenger Bramas , Markus Rampp , Michael Wilczek

We study the tracking problem, namely, estimating the hidden state of an object over time, from unreliable and noisy measurements. The standard framework for the tracking problem is the generative framework, which is the basis of solutions…

机器学习 · 计算机科学 2010-01-19 Kamalika Chaudhuri , Yoav Freund , Daniel Hsu

A large number of powerful, high-quality, and open-source simulation packages exist to efficiently perform molecular dynamics simulations, and their prevalence has greatly accelerated discoveries across a wide range of scientific domains.…

软凝聚态物质 · 物理学 2024-05-01 Toler H. Webb , Daniel M. Sussman

Tracking multiple particles in noisy and cluttered scenes remains challenging due to a combinatorial explosion of trajectory hypotheses, which scales super-exponentially with the number of particles and frames. The transformer architecture…

机器学习 · 统计学 2025-06-12 Piyush Mishra , Philippe Roudot

Recent advances in random-walk particle-tracking have enabled direct simulation of mixing and reactions on particles by allowing the particles to interact with each other using a multi-point mass transfer scheme. The mass transfer scheme…

计算物理 · 物理学 2019-04-22 Nicholas B. Engdahl , Michael J. Schmidt , David A. Benson

Automatic lane tracking involves estimating the underlying signal from a sequence of noisy signal observations. Many models and methods have been proposed for lane tracking, and dynamic targets tracking in general. The Kalman Filter is a…

计算机视觉与模式识别 · 计算机科学 2017-06-29 Jiawei Huang , Zhaowen Wang

Particle-particle interactions in sedimenting systems have been investigated in the present study considering the many-body hydrodynamic and electrodynamic interactions. These interactions primarily occur in two modes: near-field and…

流体动力学 · 物理学 2016-05-04 Sagardip Majumder , Jayabrata Dhar , Suman Chakraborty

Methods to extract information from the tracking of mobile objects/particles have broad interest in biological and physical sciences. Techniques based on simple criteria of proximity in time-consecutive snapshots are useful to identify the…

数据分析、统计与概率 · 物理学 2015-03-13 M. Chertkov , L. Kroc , F. Krzakala , M. Vergassola , L. Zdeborová

A significant drawback of Lagrangian (particle-tracking) reactive transport models has been their inability to properly simulate interactions between solid and liquid chemical phases, such as dissolution and precipitation reactions. This…

With the advance of fluorescence imaging technologies, recently cell biologists are able to record the movement of protein vesicles within a living cell. Automatic tracking of the movements of these vesicles become key for qualitative…

定量方法 · 定量生物学 2015-06-09 Min Xu

The Eulerian advection-dispersion-reaction equation (ADRE) suffers the well-known scale-effect of reduced apparent reaction rates between chemically dissimilar fluids at larger scales (or dimensional averaging). The dispersion tensor in the…

流体动力学 · 物理学 2018-12-05 David A. Benson , Diogo Bolster , Stephen Pankavich

We present and study a Particle method for the stationary solutions of a class of transport equations. This method is inspired by non-stationary Particle methods, the time variable being replaced by one spatial variable. Particles…

数值分析 · 数学 2025-11-13 Rafael Bailo , Julie Binard , Pierre Degond , Pascal Noble

This work presents retQSS, a novel methodology for efficient modeling and simulation of particle systems in reticulated meshed geometries. On the simulation side, retQSS profits from the discrete-event nature of Quantized State System (QSS)…

计算物理 · 物理学 2021-09-17 Lucio Santi , Joaquín Fernández , Ernesto Kofman , Rodrigo Castro

The propagation of an initially localized perturbation via an interacting many-particle Hamiltonian dynamics is investigated. We argue that the propagation of the perturbation can be captured by the use of a continuous-time random walk…

统计力学 · 物理学 2012-09-11 V. Zaburdaev , S. Denisov , P. Hanggi

Numerical resolution of high-dimensional nonlinear PDEs remains a huge challenge due to the curse of dimensionality. Starting from the weak formulation of the Lawson-Euler scheme, this paper proposes a stochastic particle method (SPM) by…

数值分析 · 数学 2025-02-11 Zhengyang Lei , Sihong Shao , Yunfeng Xiong
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