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Stochastic linear modelling proposed in Tissot, M\'emin & Cavalieri (J. Fluid Mech., vol. 912, 2021, A51) is based on classical conservation laws subject to a stochastic transport. Once linearised around the mean flow and expressed in the…

Fluid Dynamics · Physics 2022-07-27 Gilles Tissot , André Cavalieri , Etienne Mémin

Hydrodynamic theories offer successful approaches that are capable of simulating the otherwise difficult-to-compute dynamics of quantum many-body systems. In this work we derive, within the positive-P phase-space formalism, a new stochastic…

Quantum Gases · Physics 2022-10-21 S. A. Simmons , J. C. Pillay , K. V. Kheruntsyan

This paper describes the results of our theoretical and numerical studies of hydrodynamic interactions in a suspension of spherical particles confined between two parallel planar walls, under creeping-flow conditions. We propose a novel…

Soft Condensed Matter · Physics 2009-11-11 S. Bhattacharya , J. Blawzdziewicz , E. Wajnryb

Spatial-temporal forecasting plays an important role in many real-world applications, such as traffic forecasting, air pollutant forecasting, crowd-flow forecasting, and so on. State-of-the-art spatial-temporal forecasting models take…

Machine Learning · Computer Science 2024-01-22 Xinyu Su , Jianzhong Qi , Egemen Tanin , Yanchuan Chang , Majid Sarvi

We study well-posedness for fluid-structure interaction driven by stochastic forcing. This is of particular interest in real-life applications where forcing and/or data have a strong stochastic component. The prototype model studied here is…

Analysis of PDEs · Mathematics 2021-04-27 Jeffrey Kuan , Suncica Canic

We develop a stochastic parametrization, based on a `simple' deterministic model for the dynamics of steady longshore currents, that produces ensembles that are statistically consistent with field observations of these currents. Unlike…

Data Analysis, Statistics and Probability · Physics 2016-12-06 Juan M. Restrepo , Shankar C. Venkataramani

A non-autonomous stochastic dynamical model approach is developed to describe the seasonal to interannual variability of the El Ni\~no-Southern Oscillation (ENSO). We determine the model coefficients by systematic statistical estimations…

Atmospheric and Oceanic Physics · Physics 2020-12-21 L. T. Giorgini , W. Moon , N. Chen , J. S. Wettlaufer

The predictability of the atmosphere at short and long time scales, associated with the coupling to the ocean, is explored in a new version of the Modular Arbitrary-Order Ocean-Atmosphere Model (MAOOAM), based on a 2-layer quasi-geostrophic…

Atmospheric and Oceanic Physics · Physics 2019-10-02 Stéphane Vannitsem , Roman Solé-Pomies , Lesley De Cruz

A system of stochastic differential equations is formulated describing the heat and salt content of a two-box ocean. Variability in the heat and salt content and in the thermohaline circulation between the boxes is driven by fast Gaussian…

Dynamical Systems · Mathematics 2019-01-25 William Barham , Ian Grooms

In this work, we present a mathematical and computational framework to model the dynamics of open lipid bilayer membranes interacting with ambient Stokes flow. The model explicitly couples the three-dimensional viscous fluid, the…

Numerical Analysis · Mathematics 2026-01-21 Han Zhou , Yuan-Nan Young , Yoichiro Mori

Stochastic methods are a crucial area in contemporary climate research and are increasingly being used in comprehensive weather and climate prediction models as well as reduced order climate models. Stochastic methods are used as…

Atmospheric and Oceanic Physics · Physics 2020-11-16 Christian L. E. Franzke , Terence J. O'Kane , Judith Berner , Paul D. Williams , Valerio Lucarini

Quantum Brownian motion plays a fundamental role in many areas of modern physics. In the path-integral formulation, the environmental quantum fluctuations driving the system dynamics can be characterized by auxiliary stochastic fields. For…

Statistical Mechanics · Physics 2019-08-07 Lu Han , Vladimir Chernyak , Yun-An Yan , Xiao Zheng , YiJing Yan

In this article we expand and develop the authors' recent proposed methodology for efficient stochastic superparameterization (SP) algorithms for geophysical turbulence. Geophysical turbulence is characterized by significant intermittent…

Computational Physics · Physics 2013-10-08 Ian Grooms , Andrew J Majda

The reduced sensitivity of mean Southern Ocean zonal transport with respect to surface wind stress magnitude changes, known as eddy saturation, is studied in an idealised analytical model. The model is based on the assumption of a balance…

Atmospheric and Oceanic Physics · Physics 2026-02-09 J. R. Maddison , D. P. Marshall , J. Mak , K. Maurer-Song

In this work it is shown how the immersed boundary method of (Peskin2002) for modeling flexible structures immersed in a fluid can be extended to include thermal fluctuations. A stochastic numerical method is proposed which deals with…

Soft Condensed Matter · Physics 2023-02-28 P. J. Atzberger , P. R. Kramer , C. S. Peskin

Periodic travelling waves at the free surface of an incompressible inviscid fluid in two dimensions under gravity are numerically computed for an arbitrary vorticity distribution. The fluid domain over one period is conformally mapped from…

Fluid Dynamics · Physics 2025-02-26 Alex Doak , Vera Mikyoung Hur , Jean-Marc Vanden-Broeck

Stratospheric aerosols play an important role in the earth system and can affect the climate on timescales of months to years. However, estimating the characteristics of partially observed aerosol injections, such as those from volcanic…

Machine Learning · Computer Science 2024-09-12 J. Hart , I. Manickam , M. Gulian , L. Swiler , D. Bull , T. Ehrmann , H. Brown , B. Wagman , J. Watkins

Conduits generated by the buoyant dynamics between two miscible, Stokes fluids with high viscosity contrast exhibit rich nonlinear wave dynamics. However, little is known about the fundamental wave dispersion properties of the medium. In…

Fluid Dynamics · Physics 2023-01-18 Yifeng Mao , Mark A. Hoefer

The Stokes-Einstein-Sutherland (SES) equation is at the foundation of statistical physics, relating a particle's diffusion coefficient and size with the fluid viscosity, temperature and the boundary condition for the particle-solvent…

Predicting spatio-temporal traffic flow presents significant challenges due to complex interactions between spatial and temporal factors. Existing approaches often address these dimensions in isolation, neglecting their critical…

Artificial Intelligence · Computer Science 2024-11-15 Weilin Ruan , Wenzhuo Wang , Siru Zhong , Wei Chen , Li Liu , Yuxuan Liang