Open Channel: Laminar, K-Epsilon, K-Omega and LES simulations

Introduction

Welcome to a hands-on exploration of open channel flows using OpenFoam, where we’ll demystify fluid dynamics through practical simulation. Open channels, pivotal in various engineering domains, present a rich ground for understanding real-world fluid flow and applying this knowledge in fields ranging from agriculture to dam engineering.

In this guide, we’ll traverse through four distinct turbulence models: Laminar, RANS k-ε, RANS k-ω, and Large Eddy Simulation (LES), each offering a unique perspective on fluid behavior within an open channel. Our aim is straightforward: to simulate, explore, and understand the nuances of fluid flow, providing you with both technical and intuitive insights into the world of fluid dynamics. Let’s embark on this insightful journey, unraveling the complexities of fluid flow together!

Figure 1: A schematic diagram of the open channel, illustrating its dimensions, boundary conditions, and the specified flow parameters. and a snapshot of the initial mesh used for the simulations, highlighting the mesh density and quality.

Mesh Generation with blockMesh

Our journey begins with mesh generation, utilizing OpenFoam’s blockMesh utility. The blockMeshDict file, residing in the system directory, is our map, guiding the creation of a structured hexahedral mesh. Key highlights from our blockMeshDict file include:

• Vertices Definition: The mesh is defined by 28 vertices, forming a structured grid in the domain.
• Blocks: Six blocks are defined, creating the mesh with specified cell counts in each direction.
• Edges: Arc edges are defined to accurately represent the cylindrical shape within our domain.
• Boundary Definitions: Various boundary patches such as inlet, outlet, cylinder, walls, atomosphere and bed are defined, each with specific types and faces associated.

Figure 2: A visual representation of the simulation domain, highlighting the initial distribution of water and defining the meshing regions.

The setFieldsDict file, nestled within the system folder, plays a pivotal role in shaping our simulation’s starting point. It is here that we define the initial distribution of water within our simulation domain, particularly through the alpha.water field, which denotes the water level.

• Default Field Values: Initially, the entire domain is devoid of water, represented by setting alpha.water to 0.
• Regions: A designated region, encapsulated by a box from (-5 -10 -10) to (10 10 2), is assigned an alpha.water value of 1. This implies the presence of water within this specific region, providing a realistic and predefined water level as our simulation commences.

Within the 0 folder, the alpha.water field is meticulously defined, representing the volume fraction of water within our domain. The alpha.water.orig file provides a detailed map of boundary conditions for this field:

• Internal Field: Uniformly initialized to 0 across the domain.
• Boundary Conditions:
  • Inlet: Employs a coded fixed value, enabling dynamic or condition-based inlet conditions.
  • Outlet: Adopts a zero gradient condition, permitting water to exit the domain without specific constraints.
  • Cylinder, Walls, Wall1, and Bed: All utilize a zero gradient condition, ensuring no preferential water volume fraction direction at these boundaries.
  • Atm: Implements an inletOutlet condition, allowing both inflow and outflow of water, contingent on flow conditions.

The velocity field, denoted as U, is initialized with a uniform value of (0 0 0) across the domain, with specific boundary conditions guiding the flow:

• Inlet: Defined with a fixed value of 2m/s.
• Walls and Bed: Adhere to no-slip conditions, crucial for simulating realistic flow interactions with solid boundaries.

Diving deeper, we define the physical properties of the fluids involved:

• Air: Defined in physicalProperties.air, air is modeled as a Newtonian fluid with a viscosity of 1.48×10⁻⁵ and a density of 1.
• Water: Specified in physicalProperties.water, water is also modeled as a Newtonian fluid but with a viscosity of 1×10−⁶ and a density of 1000.

Model Exploration

Navigating through the intricate waves of fluid dynamics, our journey brings us to explore various turbulence models, each offering a unique lens to view and understand the fluid flow within our open channel. In this section, we’ll briefly immerse ourselves into the four models utilized in our simulations: Laminar, RAS k-epsilon, RAS k-omega, and Large Eddy Simulation (LES).

• Laminar Model: Sailing through calm waters, the Laminar model provides a straightforward approach, ideal for simulating flows with minimal turbulence, offering a simplistic yet insightful perspective.
• RAS k-ε Model: Navigating through choppier waters, the k-epsilon model introduces us to a realm where turbulence is modeled using two equations, providing a balance between accuracy and computational efficiency.
• RAS k-ω Model: The k-omega model, renowned for its robustness in near-wall turbulence modeling, guides us through the intricate patterns formed close to the channel walls, enhancing our understanding of wall-bounded flows.
• LES Model: Embarking into the complex, the LES model allows us to visualize the larger, more coherent structures of turbulence, providing a detailed view of the chaotic motion within the fluid.

Note: All relevant files, including setup, boundary conditions, and model configurations, are available on the blog, providing you with a practical resource to dive deeper into each model’s setup and configuration.

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Results and Insights

As we anchor at the culmination of our simulation journey, a sea of data and visualizations from our laminar + three turbulence models awaits your exploration and analysis.

• Visual Dynamics: Each model, with its unique approach to turbulence, has painted a distinct picture of fluid flow within our open channel. From the serene flow in the Laminar model to the complex, swirling eddies in the LES model, the visual results provide a rich, visual tapestry of fluid dynamics in action.
• Comparative Analysis: Diving deeper, a comparative analysis of the models reveals intriguing insights into their predictive capabilities and limitations. The variations in flow patterns, turbulence intensity, and wall interactions across the models offer a comprehensive view, aiding in selecting the appropriate model for specific flow conditions.
• In-depth Video Analysis: A video analysis is available. Watch the Video to explore the dynamic world of open channel flows, witnessing the fluid intricacies and turbulence phenomena brought to life.

Conclusion

As we dock at the conclusion of our exploration through the open channel flows with OpenFoam, we reflect on the insights gleaned from each turbulence model, appreciating their unique portrayals of fluid dynamics. From the simplistic Laminar to the intricate LES, our journey has not only demystified the complexities of fluid flow but also provided a practical guide for simulation enthusiasts and professionals alike.

In closing, it’s worth noting that your insights, reflections, and future explorations are not only welcomed but eagerly anticipated. Together, let’s continue to navigate through the boundless expanses of knowledge and discovery, charting a course through the ever-expansive seas of learning and exploration!