Turbulence Chapter 5: Scale-Resolving Simulations (SRS)
This chapter covers Scale-Resolving Simulation (SRS) methods, which aim to resolve the large turbulent structures in a flow while modeling the smaller ones. The summary includes classical LES, wall-modeled and embedded LES, hybrid models like DES and SBES, and scale-adaptive approaches such as SAS. Application notes and model selection guidelines are also included.
Turbulence Chapter 4: Laminar-turbulent Transition Modeling
This chapter focuses on the modeling of laminar–turbulent transition in RANS simulations. The transition region affects boundary layer behavior, drag, and heat transfer, and cannot be captured by fully turbulent models. Different transition mechanisms are introduced, followed by an overview of modern transition models based on intermittency, laminar kinetic energy, and empirical correlations. The summary includes Fluent-specific implementations and practical considerations for setup and mesh requirements.
Turbulence Chapter 3: Near-Wall Modeling
In this chapter, we journey into the turbulent zone right next to the wall — where sharp gradients, subtle balances, and small-scale chaos control the drag, heat transfer, and flow separation that engineers care about. We explore how near-wall turbulence is structured, how CFD models like wall functions or enhanced wall treatments handle it, and why roughness and mesh strategy matter more than you might expect. This is where the wall stops being just a boundary and becomes the real battleground of turbulence.
Turbulence Chapter 2: Turbulence Anisotropy in RANS
Reynolds-Stress Models (RSM) aim to capture the directional complexity of turbulence where simpler models fail. This post breaks down the theory behind RSM, explains when and why it’s needed, and offers intuitive analogies and stability tips — all framed through the Socratic questions we use throughout the course.
Turbulence Chapter 1: Review of RANS-Boussinesq Models & Statistical Turbulence Description
Turbulence modeling is at the core of modern Computational Fluid Dynamics (CFD), bridging the gap between theoretical fluid mechanics and practical engineering applications. This guide explores the fundamentals of turbulence, from the Reynolds-Averaged Navier-Stokes (RANS) approach and the Boussinesq hypothesis to improved RANS models like Realizable k-ε, RNG k-ε, and curvature-corrected models. With a focus on practical CFD applications, we delve into turbulence production limiters, near-wall treatments, and Fluent best practices. This structured study consolidates critical turbulence modeling concepts, equipping CFD engineers with the knowledge to select and implement the most suitable models for their simulations.
Interpolation and Mapping in Fluid-Structure Interaction: Connecting the Dots
Mapping and interpolation bridge the gap between incompatible fluid and structure meshes in FSI simulations. This post explores key techniques like bucket search algorithms, spline methods, and their real-world applications.
2-Way Fluid-Structure Interaction: From Explicit to Implicit Coupling and Beyond
Dive into fluid-structure interaction (FSI) methods, from coupling algorithms to remeshing and stabilization techniques. Discover how these tools power real-world simulations in engineering and science.
1-Way Coupling in Fluid-Structure Interaction: Wind, Cooling, and Structural Response
Dive into the world of physics coupling and discover how fluids and structures interact. This guide covers the basics of 1-way coupling, the monolithic vs. partitioned approach, and the key differences between explicit and implicit time discretization methods.
Fluid-Structure Interaction for Beginners: From Bridges to Blood Flow
In this post, we explore the world of Fluid-Structure Interaction (FSI), a key area of study that reveals how fluids and solids influence each other in systems like bridges, airplanes, and even the human body. From basic principles to real-world examples, this guide will help you understand how these forces shape the structures we interact with every day.