Understanding Turbulent Systems

Progress in Particle Dynamics Modeling
Erscheinungsjahr 2025
ISBN: 978-3-031-84465-2
Verlag: Springer Nature Switzerland

Buch, Englisch, 284 Seiten, Format (B × H): 155 mm x 235 mm, Gewicht: 464 g

Reihe: Lecture Notes in Physics

This open access book provides a thorough introduction to modeling turbulent, dispersed, two-phase flows. It explains the physical phenomena and governing laws at play, followed by a clear and systematic overview of the statistical tools used to develop simplified or coarse-grained models.

With a pedagogical approach, the book uses practical examples to explain complex physical processes and stochastic methods, making it accessible to readers familiar with basic courses in statistical physics and applied mathematics. It also highlights emerging research areas and unexplored challenges in the field.

Designed as a self-contained resource, this book is ideal for graduate students and junior researchers in various branches of physics. At the same time, it serves as a valuable reference for experts seeking deeper insights into turbulent, dispersed, two-phase flows.

Zielgruppe

Research

Autoren/Hrsg.

Minier, Jean-Pierre

Henry, Christophe

Ferrand, Martin

Fachgebiete

• Technische Wissenschaften Maschinenbau | Werkstoffkunde Technische Mechanik | Werkstoffkunde Strömungslehre
• Naturwissenschaften Physik Thermodynamik Plasmaphysik
• Naturwissenschaften Physik Mechanik

Inhaltsverzeichnis

Introduction.- The physics of dispersed turbulent two-phase flows.- Reduced statistical descriptions and the probabilistic framework.- Statistical modeling of particle transport in turbulent flows.- Modeling the velocity of the fluid seen current formulations.- Modeling the velocity of the fluid seen new propositions.- Similarities and differences with complex fluids.- Fast variable elimination and local constitutive relations.- tatistical modeling of particle collisions in turbulent flows.- Conclusions and perspectives on the roads ahead.

Über Autor(innen)

Jean-Pierre Minier is a researcher in the Department of Fluid Mechanics, Energy, and Environment at EDF R&D and at CEREA in Chatou, France. His research focuses on dispersed two-phase flows and stochastic modeling. He is the editor of two books: on Stochastic Methods in Fluid Mechanics (Springer, 2014) and on Particles in Wall-Bounded Turbulent Flows: Deposition, Re-Suspension, and Agglomeration (Springer, 2017) and the lead author of three review articles published in Physics Reports (2001, 2016) and Progress in Energy and Combustion Science (2015). In addition, he has co-authored several other review articles.

Martin Ferrand is the deputy head of the CEREA laboratory (Centre d’Enseignement et de Recherches en Environnement Atmosphérique), a joint venture between EDF-R&D and École des Ponts ParisTech. He teaches fluid mechanics and computational fluid dynamics (CFD) at CEREA.

Martin earned a Master of Philosophy from the University of Manchester in 2010, focusing on the Smoothed Particle Method. Since then, he has developed physical and numerical models for the open-source CFD solver, , managing its development for five years. In 2022, he earned a PhD through validation of prior learning for his contributions to SPH and arbitrarily Eulerian-Lagrangian finite volumes. His current research explores atmospheric flows, particularly pollutant dispersion, using hybrid moment/PDF methods.

Christophe Henry is a researcher in Team Calisto at the Inria Center, Université Côte d’Azur, in Sophia Antipolis, France. He earned his PhD in 2012 from the University Pierre et Marie Curie (now Sorbonne University) and completed postdoctoral research in Gdansk, Poland, and Nice, France. In 2018, he joined the Inria Centre at Université Côte d’Azur and became a permanent researcher in 2021.

Christophe’s work focuses on developing Lagrangian stochastic models for simulating dispersed two-phase flows in wall-bounded turbulent systems. His research combines fluid dynamics, interface chemistry, and surface science with numerical modeling, including stochastic methods and their implementation.