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We consider various methods of flow analysis in heavy ion collisions and compare experimental data on corresponding observables to the predictions of our saturation model proposed earlier. We demonstrate that, due to the nature of the…

Nuclear Theory · Physics 2009-11-07 Yuri V. Kovchegov , Kirill L. Tuchin

Predicting particle segregation has remained challenging due to the lack of a general model for the segregation velocity that is applicable across a range of granular flow geometries. Here, a segregation velocity model for dense granular…

Soft Condensed Matter · Physics 2025-10-22 Yifei Duan , Lu Jing , Paul B. Umbanhowar , Julio M. Ottino , Richard M. Lueptow

We study the packing fraction of clusters in free-falling streams of spherical and irregularly shaped particles using flash X-ray radiography. The estimated packing fraction of clusters is low enough to correspond to coordination numbers…

Soft Condensed Matter · Physics 2021-03-31 Yuuya Nagaashi , Akiko M. Nakamura , Sunao Hasegawa , Koji Wada

Mixture fraction-based models are widely employed for predicting turbulent non-premixed combustion processes due to their cost-effectiveness and well-established subfilter closure. In these models, the transport of reactive scalars in…

Fluid Dynamics · Physics 2023-10-26 Marco Davidovic , Heinz Pitsch

The one-dimensional contact process is analyzed by a cluster approximation. In this approach, the hierarchy of rate equations for the densities of finite length empty intervals are truncated under the assumption that adjacent intervals are…

Condensed Matter · Physics 2009-10-22 E. Ben-Naim , P. L. Krapivsky

The simulation of high-energy physics collision events is a key element for data analysis at present and future particle accelerators. The comparison of simulation predictions to data allows looking for rare deviations that can be due to…

High Energy Physics - Experiment · Physics 2024-07-16 Francesco Vaselli , Filippo Cattafesta , Patrick Asenov , Andrea Rizzi

In this work, we aim to deepen the understanding of inertial clustering and the role of sling events in high-Reynolds number ($Re$) particle-laden turbulence. To this end, we perform one-way coupled particle tracking in flow fields obtained…

Fluid Dynamics · Physics 2025-01-09 Lukas A. Codispoti , Daniel W. Meyer , Patrick Jenny

Forward models of the galaxy density field enable simulation based inference as well as field level inference of galaxy clustering. However, these analysis techniques require forward models that are both computationally fast and robust to…

Cosmology and Nongalactic Astrophysics · Physics 2025-04-30 Julia Stadler , Fabian Schmidt , Martin Reinecke

Inertial particles in turbulence form clusters, which strongly affect particle collisions and transport properties. Clustering models based on statistically stationary turbulence implicitly assume the instantaneous-equilibrium approximation…

Fluid Dynamics · Physics 2026-05-26 Taketo Tominaga , Ryo Onishi

In recent years, the problem of fuzzy clustering has been widely concerned. The membership iteration of existing methods is mostly considered globally, which has considerable problems in noisy environments, and iterative calculations for…

Machine Learning · Computer Science 2023-03-09 Jiang Xie , Qiao Deng , Shuyin Xia , Yangzhou Zhao , Guoyin Wang , Xinbo Gao

The recent advent of advanced microfabrication capabilities of microfluidic devices has driven attention towards the behavior of particles in inertial flows within microchannels for applications related to the separation and concentration…

Fluid Dynamics · Physics 2018-12-03 Mike Garcia , Sumita Pennathur

This paper studies a factor modeling-based approach for clustering high-dimensional data generated from a mixture of strongly correlated variables. Statistical modeling with correlated structures pervades modern applications in economics,…

Statistics Theory · Mathematics 2024-08-23 Shange Tang , Soham Jana , Jianqing Fan

In this paper, we establish a set of criteria which are applied to discuss various formulations under which Lagrangian stochastic models can be found. These models are used for the simulation of fluid particles in single-phase turbulence as…

Fluid Dynamics · Physics 2015-01-13 J. -P. Minier , S. Chibbaro , S. B. Pope

This paper introduces factored conditional filters, new filtering algorithms for simultaneously tracking states and estimating parameters in high-dimensional state spaces. The conditional nature of the algorithms is used to estimate…

Artificial Intelligence · Computer Science 2024-07-10 Dawei Chen , Samuel Yang-Zhao , John Lloyd , Kee Siong Ng

A pinned-free beam in axial fluid flow, subjected to feedback-based actuation at the pinned end, is investigated. The actuation may be a moment or a prescribed angle and it is proportional to the state (curvature, slope, or displacement) of…

Fluid Dynamics · Physics 2023-02-07 Sanders Aspelund , Ranjan Mukherjee , Aren Hellum

Filtered budgets for anelastic turbulence and a general expression of the turbulent sensible heat flux are derived for a multicomponent fluid with an arbitrary equation of state. A family of subgrid-scale closures is then found under the…

Fluid Dynamics · Physics 2026-01-26 Thomas Dubos

Generative modelling has seen significant advances through simulation-free paradigms such as Flow Matching, and in particular, the MeanFlow framework, which replaces instantaneous velocity fields with average velocities to enable efficient…

Machine Learning · Computer Science 2025-08-12 Yang Cao , Yubin Chen , Zhao Song , Jiahao Zhang

Convergence properties of the variational cluster approach with respect to the variational parameter space, cluster size, and boundary conditions of the reference system are investigated and discussed for bosonic many-body systems.…

Strongly Correlated Electrons · Physics 2010-06-21 Michael Knap , Enrico Arrigoni , Wolfgang von der Linden

Fluids with competing short-range attractions and long-range repulsions mimic dispersions of charge-stabilized colloids that can display equilibrium structures with intermediate range order (IRO), including particle clusters. Using…

Soft Condensed Matter · Physics 2015-05-01 Ryan B. Jadrich , Jonathan A. Bollinger , Keith P. Johnston , Thomas M. Truskett

We introduce a fast and explainable clustering method called CLASSIX. It consists of two phases, namely a greedy aggregation phase of the sorted data into groups of nearby data points, followed by the merging of groups into clusters. The…

Machine Learning · Computer Science 2024-02-16 Xinye Chen , Stefan Güttel
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