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Related papers: Mixed Layer Mesoscales for OGCMs: Model developmen…

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This paper presents a novel methodology for the direct numerical modeling and simulation of turbulent flows. The kinetic model equation is firstly extended to turbulent flow with the account of coupled evolution of kinetic, thermal, and…

Computational Physics · Physics 2025-03-11 Xiaojian Yang , Kun Xu

The Massachusetts Institute of Technology General Circulation Model (MITgcm) is widely used by the climate science community to simulate planetary atmosphere and ocean circulations. A defining feature of the MITgcm is that it has been…

Fluid turbulence is characterized by strong coupling across a broad range of scales. Furthermore, besides the usual local cascades, such coupling may extend to interactions that are non-local in scale-space. As such the computational…

We present a multiparticle collision dynamics (MPC) implementation of layered immiscible fluids $A$ and $B$ of different shear viscosities separated by planar interfaces. The simulated flow profile for imposed steady shear motion and the…

Soft Condensed Matter · Physics 2021-09-07 Zihan Tan , Vania Calandrini , Jan K. G. Dhont , Gerhard Nägele , Roland G. Winkler

Regional dynamics of Bay of Bengal is studied using Open Boundary Condition (OBC) in Modular Ocean Model (MOM) to understand the effect of primary and secondary mesoscale features on various bulk ocean products and turbulent fluxes. A…

Atmospheric and Oceanic Physics · Physics 2021-05-07 Siddhesh Tirodkar , Mousumi Sarkar , Rajesh Chauhan , Manasa R. Behera , Sridhar Balasubramanian

The relationship between velocities, tractions, and intercellular stresses in the migrating epithelial monolayer are currently unknown. Ten years ago, a method known as Monolayer Stress Microscopy (MSM) was suggested from which the…

Biological Physics · Physics 2020-06-04 Yoav Green , Jeffrey J. Fredberg , James P. Butler

Flow Matching (FM) models achieve remarkable results in generative tasks. Building upon diffusion models, FM's simulation-free training paradigm enables simplicity and efficiency but introduces a train-inference gap: model outputs cannot be…

Machine Learning · Computer Science 2026-01-30 Zhaoyi Li , Jingtao Ding , Yong Li , Shihua Li

We develop a family of expanded mixed Multiscale Finite Element Methods (MsFEMs) and their hybridizations for second-order elliptic equations. This formulation expands the standard mixed Multiscale Finite Element formulation in the sense…

Numerical Analysis · Mathematics 2012-05-22 Lijian Jiang , Dylan Copeland , J. David Moulton

Trajectory inference seeks to recover the temporal dynamics of a population from snapshots of its (uncoupled) temporal marginals, i.e. where observed particles are not tracked over time. Prior works addressed this challenging problem under…

Machine Learning · Computer Science 2025-02-27 Anming Gu , Edward Chien , Kristjan Greenewald

Mesoscale eddies produce lateral (2D) fluxes that need to be parameterized in eddy-permitting (1/4-degree) global ocean models due to insufficient horizontal resolution. Here, we systematically apply methods from the 3D LES community to…

Atmospheric and Oceanic Physics · Physics 2025-01-10 Pavel Perezhogin , Arun Balakrishna , Rahul Agrawal

Machine-learning (ML) techniques provide a new and encouraging perspective for constructing turbulence models for Reynolds-averaged Navier--Stokes (RANS) simulations. In this study, an iterative ML-RANS computational framework is proposed…

Fluid Dynamics · Physics 2021-07-27 Weishuo Liu , Jian Fang , Stefano Rolfo , Charles Moulinec , David R Emerson

Global climate models (GCMs), typically run at ~100-km resolution, capture large-scale environmental conditions but cannot resolve convection and cloud processes at kilometer scales. Convection-permitting models offer higher-resolution…

Atmospheric and Oceanic Physics · Physics 2026-05-12 Hungjui Yu , Lander Ver Hoef , Kristen L. Rasmussen , Imme Ebert-Uphoff

The transport of scalar quantities passively advected by velocity fields with a small-scale component can be modeled at meso-scale level by means of an effective drift and an effective diffusivity, which can be determined by means of…

Chaotic Dynamics · Physics 2009-11-11 M. Cencini , A. Mazzino , S. Musacchio , A. Vulpiani

We review some recent coarse-graining and multi-scale methods, but also put forward some new ideas for addressing such issues. We find that, if one is guided by nonequilibrium statistical mechanics and thermodynamics, it is possible to…

Soft Condensed Matter · Physics 2009-11-06 Patrick Ilg , Vlasis Mavrantzas , Hans Christian Öttinger

We study the mean-square displacement (MSD) of a tracer particle diffusing in a granular gas of inelastic hard spheres under homogeneous cooling state (HCS). Tracer and granular gas particles are in general mechanically different. Our…

Statistical Mechanics · Physics 2026-01-29 Santos Bravo Yuste , Rubén Gómez González , Vicente Garzó

Discrete mesoscale network models, in which explicitly modeled polymer chains are replaced by implicit pairwise potentials, are capable of predicting the macroscale mechanical response of polymeric materials such as elastomers and gels,…

Soft Condensed Matter · Physics 2024-07-16 Robert J. Wagner , Meredith N. Silberstein

Linear mixed-effects model (LMM) is a cornerstone of longitudinal data analysis, but is limited to adeptly make heterogeneous analyses predictable under both group-specific fixed effects and subject-specific random effects. To address this…

Methodology · Statistics 2026-03-10 Xinkai Yue , Xiaodong Yan , Haohui Han , Liya Fu

Normal-mode oscillation frequencies computed from stellar models differ from those which would be measured from stars with identical interior structures, because of modelling errors in the near-surface layers. These frequency differences…

Solar and Stellar Astrophysics · Physics 2021-10-20 J. M. Joel Ong , Sarbani Basu , Ian W. Roxburgh

As wind farms continue to grow in size, mesoscale effects such as blockage and gravity waves become increasingly important. Allaerts & Meyers (J. Fluid Mech., 2019) proposed an atmospheric perturbation model (APM) that can simulate the…

Fluid Dynamics · Physics 2023-10-31 Koen Devesse , Luca Lanzilao , Johan Meyers

Mixture of Experts (MoE) achieve parameter-efficient scaling through sparse expert routing, yet their internal representations remain poorly understood compared to dense models. We present a systematic comparison of MoE and dense model…

Machine Learning · Computer Science 2026-03-09 Marmik Chaudhari , Nishkal Hundia , Idhant Gulati