Immersed-Boundary Mesh for Moving CFD Boundaries
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Solution Overview
Problem
Current computational fluid dynamics (CFD) methods face challenges in accurately analyzing fluid systems with moving boundaries, particularly due to difficulties in generating and automating meshes for complex geometries, which can lead to reduced solution accuracy and increased computing time.
Innovation Solution
The method employs an immersed-boundary computational mesh combined with an Arbitrary Lagrangian Eulerian (ALE) numerical solution technique, using 'ghost cells' to treat moving boundaries without significant cell distortion, allowing for precise tracking of boundary motion and improved solution accuracy and stability.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional CFD methods are used to analyze fluid systems with moving boundaries, then the analysis can be performed, but mesh generation becomes complex and automated mesh generation is difficult, leading to reduced solution accuracy and increased computing time
Solution Approach 1:
The computational domain is divided into interior cells and boundary cells, with boundary cells further divided into moving cell faces and ghost cells. This segmentation allows the moving boundary to be treated separately from the interior fluid domain, simplifying mesh generation while maintaining accuracy at the boundary interface.
Solution Approach 2:
Ghost cells are introduced as intermediary elements between the moving boundary and the interior cells. These ghost cells contain fictitious values that are used to enforce boundary conditions without requiring the actual mesh to conform to the moving boundary geometry, thereby simplifying automated mesh generation.
2Measurement precision
If the mesh is distorted to fit moving boundaries, then boundary motion can be tracked, but cell distortion increases leading to reduced solution accuracy
Solution Approach 1:
The method dynamically distinguishes between interior vertices that move with the fluid and moving boundary vertices that move with the boundary. This dynamic treatment allows accurate tracking of boundary motion while maintaining a relatively static mesh structure in the interior, minimizing cell distortion.
Solution Approach 2:
Instead of distorting the actual mesh to follow the moving boundary, the method creates a copy of the boundary motion through ghost cells and fictitious values. This copying approach allows the physical mesh to remain static while the computational model accounts for boundary motion through the ghost cell values and boundary condition enforcement.
3Loss of time
If automated mesh generation is used for complex geometries, then mesh generation time is reduced, but solution accuracy decreases due to mesh irregularity
Solution Approach 1:
The method applies different quality requirements to different regions: the interior mesh can be generated automatically with standard quality, while the boundary region uses ghost cells and special treatment to maintain accuracy. This local differentiation allows automated generation throughout the domain while preserving solution accuracy at the moving boundary interface.
Data Source
AI summary
A method for treating boundary cells over a time-step in a computational fluid dynamic process employing a computational mesh representation of a fluid system characterized by governing equations and having at least one moving boundary comprises: identifying interior cells, boundary cell faces, boundary vertices, interior vertices and vertex locations at the beginning of the time step; applying a calculation process that includes determining cell volumes based on Lagrangian locations of the interior and boundary vertices and calculating the value of at least one system thermodynamic property; calculating at least one flux value across one or more boundary cell volumes by returning the interior vertices to their initial locations.