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Given that observational and numerical climate data are being produced at ever more prodigious rates, increasingly sophisticated and automated analysis techniques have become essential. Deep learning is quickly becoming a standard approach…

Fluid Dynamics · Physics 2017-09-12 A. Rupe , J. P. Crutchfield , K. Kashinath , Prabhat

Joint modeling of multiview graphs with a common set of nodes between views and auxiliary predictors is an essential, yet less explored, area in statistical methodology. Traditional approaches often treat graphs in different views as…

Methodology · Statistics 2026-03-24 Sharmistha Guha , Jose Rodriguez-Acosta , Ivo Dinov

Unstructured grid data are essential for modelling complex geometries and dynamics in computational physics. Yet, their inherent irregularity presents significant challenges for conventional machine learning (ML) techniques. This paper…

A new Lagrangian particle method for solving Euler equations for compressible inviscid fluid or gas flows is proposed. Similar to smoothed particle hydrodynamics (SPH), the method represents fluid cells with Lagrangian particles and is…

Numerical Analysis · Mathematics 2016-03-21 Hsin-Chiang Chen , Roman Samulyak , Wei Li

In order to solve the fluid-structure interaction problem of Newtonian fluid, a fluid-structure interaction approach is proposed based on Non-ordinary State-based Peridynamics (NOSB-PD) and Updated Lagrangian particle Hydrodynamics (ULPH),…

Fluid Dynamics · Physics 2024-07-29 Zhen Wang , Junsong Xiong , Xiang Liu , Lisheng Liu , Xin Lai

We study the use of the Euler characteristic for multiparameter topological data analysis. Euler characteristic is a classical, well-understood topological invariant that has appeared in numerous applications, including in the context of…

Algebraic Topology · Mathematics 2021-02-17 Gabriele Beltramo , Rayna Andreeva , Ylenia Giarratano , Miguel O. Bernabeu , Rik Sarkar , Primoz Skraba

Modeling and direct numerical simulation of particle-laden flows have a tremendous variety of applications in science and engineering across a vast spectrum of scales from pollution dispersion in the atmosphere, to fluidization in the…

In this article one introduces a formalism of classical mechanics where complex Lagrangian functions are admitted. The results include complex versions of the Lagrangian function, of the Euler-Lagrange equation, of the Hamilton principle, a…

Mathematical Physics · Physics 2026-02-03 Sergio Giardino

A phenomenological theory of the fluctuations of velocity occurring in a fully developed homogeneous and isotropic turbulent flow is presented. The focus is made on the fluctuations of the spatial (Eulerian) and temporal (Lagrangian)…

A new simulation method for solving fluid-structure coupling problems has been developed. All the basic equations are numerically solved on a fixed Cartesian grid using a finite difference scheme. A volume-of-fluid formulation (Hirt and…

Computational Physics · Physics 2015-05-20 Kazuyasu Sugiyama , Satoshi Ii , Shintaro Takeuchi , Shu Takagi , Yoichiro Matsumoto

A temporal complex network-based approach is proposed as a novel formulation to investigate turbulent mixing from a Lagrangian viewpoint. By exploiting a spatial proximity criterion, the dynamics of a set of fluid particles is geometrized…

Fluid Dynamics · Physics 2019-03-27 Giovanni Iacobello , Stefania Scarsoglio , J. G. M. Kuerten , Luca Ridolfi

Recent advancements have demonstrated that fully Eulerian methods can effectively model frictionless contact between deformable solids. Unlike traditional Lagrangian approaches, which require contact detection and resolution algorithms, the…

Soft Condensed Matter · Physics 2024-12-20 Flavio Lorez , Mohit Pundir

In this paper we develop new techniques for revealing geometrical structures in phase space that are valid for aperiodically time dependent dynamical systems, which we refer to as Lagrangian descriptors. These quantities are based on the…

Chaotic Dynamics · Physics 2013-08-05 Ana M. Mancho , Stephen Wiggins , Jezabel Curbelo , Carolina Mendoza

Analyzing large complex image collections in domains like forensics, accident investigation, or social media analysis involves interpreting intricate, overlapping relationships among images. Traditional clustering and classification methods…

Graphics · Computer Science 2025-10-24 Floris Gisolf , Zeno J. M. H. Geradts , Marcel Worring

With the advent of artificial intelligence and machine learning, various domains of science and engineering communities have leveraged data-driven surrogates to model complex systems through fusing numerous sources of information (data)…

Using the wave equation as an example, it is shown how to extend the hydrodynamic Lagrangian-picture method of constructing field evolution using a continuum of trajectories to second-order theories. The wave equation is represented through…

Fluid Dynamics · Physics 2015-05-28 Peter Holland

In numerical modeling of the Earth System, many processes remain unknown or ill represented (let us quote sub-grid processes, the dependence to unknown latent variables or the non-inclusion of complex dynamics in numerical models) but…

Data Analysis, Statistics and Probability · Physics 2019-03-19 Julien Brajard , Anastase Charantonis , Jérôme Sirven

Here a semi-implicit formulation of the gradient augmented level set method is presented. By tracking both the level set and it's gradient accurate subgrid information is provided,leading to highly accurate descriptions of a moving…

Numerical Analysis · Mathematics 2015-03-19 Ebrahim M. Kolahdouz , David Salac

Properties of data are frequently seen to vary depending on the sampled situations, which usually changes along a time evolution or owing to environmental effects. One way to analyze such data is to find invariances, or representative…

Machine Learning · Statistics 2012-09-26 Satoshi Hara , Takashi Washio

Physical systems are commonly represented as a combination of particles, the individual dynamics of which govern the system dynamics. However, traditional approaches require the knowledge of several abstract quantities such as the energy or…

Machine Learning · Computer Science 2022-09-07 Ravinder Bhattoo , Sayan Ranu , N. M. Anoop Krishnan