期刊信息
Computers & Fluids
https://www.sciencedirect.com/journal/computers-and-fluids
影响因子:
2.500
出版商:
Elsevier
ISSN:
0045-7930
浏览:
18569
关注:
1
征稿
Computers & Fluids is multidisciplinary. The term 'fluid' is interpreted in the broadest sense. Hydro- and aerodynamics, high-speed and physical gas dynamics, turbulence and flow stability, multiphase flow, rheology, tribology, aeroacoustics and fluid-structure interaction are all of interest, provided that computer technique plays a significant role in the associated studies or design methodology.

Applications will be found in most branches of engineering and science: mechanical, civil, chemical, aeronautical, medical, geophysical, nuclear and oceanographic. These will involve problems of air, sea and land vehicle motion and flow physics, energy conversion and power, chemical reactors and transport processes, ocean and atmospheric effects and pollution, biomedicine, noise and acoustics, and magnetohydrodynamics amongst others.

The development of numerical methods relevant to fluid flow computations, computational analysis of flow physics and fluid interactions and novel applications to flow systems and to design are pertinent to Computers & Fluids.

The journal also accepts papers dealing with uncertainty quantification in fluid flow simulations, reduced-order and surrogate models for fluid flows, optimization and control.

Papers dealing with machine learning approaches applied to fluid flow modeling are welcome, provided they show excellent scientific character. In particular, the authors are encouraged to perform comparisons with traditional numerical reconstruction methods, to provide a clear presentation of training vs validation cases, together with sufficient diversity in these cases, to analyze the physical consistency/theoretical analysis of the ML model, and to discuss the limitations of the method as well as its merits.
最后更新 Dou Sun 在 2024-07-14
Special Issues
Special Issue on Innovations in Modeling and Numerical Methods for Evolutionary PDEs: Theory and Applications
截稿日期: 2025-03-31

This special issue focuses on the modern enhancements introduced for the numerical solution of evolutionary PDEs of interest in a wide range of physical relevant situations as computational fluid and solid mechanics, oceanography, plasma physics, material science, mathematical biology and computational astrophysics. Evolutionary PDEs are characterized by many computational difficulties due to the huge range of involved space and time scales and the complex mathematical structure behind their behavior, thus their solution remains still a major challenge nowadays. Here, advanced mathematical models and advanced numerical algorithms for their robust and effective solution will be presented, with a particular interest for modern high order schemes on Cartesian or unstructured grids, structure preserving numerical methods and PDE models, Lagrangian methods, mesh generation and optimization techniques, kinetic methods, and challenging realistic applications. Guest editors: Dr. Elena GaburroAffiliation: Inria center at the University of Bordeaux, Talence, FranceAreas of expertise: Numerical methods for Hyperbolic Partial Differential Equations, High order Finite Volume and Discontinuous Galerkin schemes, Lagrangian methods, Structure preserving schemes, Unstructured meshes Prof. Remi AbgrallAffiliation: University of Zurich, Zurich, SwitzerlandAreas of expertise: Scientific computing, Numerical methods for Partial Differential Equations, Multiphase flows, Fluid dynamics, Finite element methods Prof. Michael DumbserAffiliation: University of Trento, Trento, ItalyAreas of expertise: Numerical methods for Partial Differential Equations, High order schemes on Cartesian and unstructured meshes, Structure preserving schemes, Continuum mechanics, Semi-implicit methods Dr. Simone ChiocchettiAffiliation: University of Stuttgart, Stuttgart, GermanyAreas of expertise: Hyperbolic partial differential equations, High performance computing, Continuum mechanics, High order schemes on Cartesian and unstructured meshes, Unstructured mesh generation Dr. Maria KazoleaAffiliation: Inria center at the University of Bordeaux, Talence, FranceAreas of expertise: Scientific computing, Dispersive models, Free surface flows, PDE modelling and interaction with numerical schemes, High order methods on unstructured grids Manuscript submission information: Guest Editor Invitation Only Open for Submission: from 01-Sep-2024 to 31-Mar-2025
最后更新 Dou Sun 在 2024-02-01
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