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A growing body of literature has been leveraging techniques of machine learning (ML) to build novel approaches to approximating the solutions to partial differential equations. Noticeably absent from the literature is a systematic…

Numerical Analysis · Mathematics 2026-05-19 Jonah A. Reeger

In this work, we consider the interaction of a 3D incompressible fluid with a 2D flexible shell that occupies (a part of) the boundary of the fluid domain. We assume that the shell is perfectly elastic while the fluid is governed by the…

Analysis of PDEs · Mathematics 2026-05-15 Dominic Breit , Prince Romeo Mensah , Sebastian Schwarzacher , Pei Su

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

We explore the dynamical behaviour of cosmological models involving a scalar field (with an exponential potential and a canonical kinetic term) and a matter fluid with spatial curvature included in the equations of motion. Using…

General Relativity and Quantum Cosmology · Physics 2016-10-13 Mateja Gosenca , Peter Coles

Biological systems are non-linear, include unobserved variables and the physical principles that govern their dynamics are partly unknown. This makes the characterization of their behavior very challenging. Notably, their activity occurs on…

Quantitative Methods · Quantitative Biology 2025-06-27 Andréa Ducos , Audrey Denizot , Thomas Guyet , Hugues Berry

Langevin equations or generalized Langevin equations (GLEs) are popular models for describing the motion of a particle in a fluid medium in an effective manner. Here we examine particles immersed in an inherently nonequilibrium fluid, i.e.,…

Soft Condensed Matter · Physics 2024-05-03 Jeanine Shea , Gerhard Jung , Friederike Schmid

Invariants of general linear system of two hyperbolic partial differential equations (PDEs) are derived under transformations of the dependent and independent variables by real infinitesimal method earlier. Here a subclass of the general…

Classical Analysis and ODEs · Mathematics 2015-08-14 A. Aslam , M. Safdar , F. M. Mahomed

The dynamics of viscous thin-film particle-laden flows down inclined surfaces are commonly modeled with one of two approaches: a diffusive flux model or a suspension balance model. The diffusive flux model assumes that the particles migrate…

We present a nonlinear dynamical approximation method for time-dependent Partial Differential Equations (PDEs). The approach makes use of parametrized decoder functions, and provides a general, and principled way of understanding and…

Numerical Analysis · Mathematics 2025-05-20 Daan Bon , Benjamin Caris , Olga Mula

A model system for classical fluids out of equilibrium, referred to as DPD solid (Dissipative Particles Dynamics), is studied by analytical and simulation methods. The time evolution of a DPD particle is described by a fluctuating heat…

Statistical Mechanics · Physics 2009-11-10 Marisol Ripoll , Matthieu H. Ernst

We study a system of parabolic equations consisting of a double nonlinear parabolic equations of Forchheimer type coupled with a semilinear parabolic equations. The system describes a fluid-like driven system for active-passive pedestrian…

Analysis of PDEs · Mathematics 2019-12-30 T. K. Thoa Thieu , Matteo Colangeli , Adrian Muntean

Active diffusiophoresis - swimming through interaction with a self-generated, neutral, solute gradient - is a paradigm for autonomous motion at the micrometer scale. We study this propulsion mechanism within a linear response theory.…

Statistical Mechanics · Physics 2015-05-30 Benedikt Sabass , Udo Seifert

In this paper, we present the Partial Integral Equation (PIE) representation of linear Partial Differential Equations (PDEs) in one spatial dimension, where the PDE has spatial integral terms appearing in the dynamics and the boundary…

Numerical Analysis · Mathematics 2022-12-19 Sachin Shivakumar , Amritam Das , Matthew Peet

We propose a systematic expansion method which is applied to freely evolving granular fluids contained in sufficiently small systems. Restricting ourselves to small systems, we show that there exists a small parameter which characterizes a…

Statistical Mechanics · Physics 2007-05-23 J. Wakou

We present a framework for fine-tuning flow-matching generative models to enforce physical constraints and solve inverse problems in scientific systems. Starting from a model trained on low-fidelity or observational data, we apply a…

Machine Learning · Computer Science 2026-01-28 Jan Tauberschmidt , Sophie Fellenz , Sebastian J. Vollmer , Andrew B. Duncan

We consider the problem of solving partial differential equations (PDEs) in domains with complex microparticle geometry that is impractical, or intractable, to model explicitly. Drawing inspiration from volume rendering, we propose tackling…

Graphics · Computer Science 2025-06-11 Bailey Miller , Rohan Sawhney , Keenan Crane , Ioannis Gkioulekas

Recent works have shown that deep neural networks can be employed to solve partial differential equations, giving rise to the framework of physics informed neural networks. We introduce a generalization for these methods that manifests as a…

Numerical Analysis · Mathematics 2021-03-25 Remco van der Meer , Cornelis Oosterlee , Anastasia Borovykh

In this paper a family of non-autonomous scalar parabolic PDEs over a general compact and connected flow is considered. The existence or not of a neighbourhood of zero where the problems are linear has an influence on the methods used and…

Dynamical Systems · Mathematics 2021-03-22 Rafael Obaya , Ana Sanz

In this work we derive a class of geometric flow equations for metric-scalar systems. Thereafter, we construct them from some general string frame action by performing volume-preserving fields variations and writing down the associated…

High Energy Physics - Theory · Physics 2022-05-18 Davide De Biasio , Dieter Lust

Spatial reaction-diffusion models have been employed to describe many emergent phenomena in biological systems. The modelling technique most commonly adopted in the literature implements systems of partial differential equations (PDEs),…

Quantitative Methods · Quantitative Biology 2015-10-05 Christian A. Yates , Mark B. Flegg
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