Session: 03-06 Fluid-Structure Interaction

Paper Number: 87636

87636 - FSI of a Cantilever Beam: FVM-FEM and Neural Network Analysis 

Fluid-structure interaction (FSI) problems are becoming highly complex as it has a wide range of applications, which assists to model many real-world problems. The finite volume method (FVM) enforces conservation of the governing physics over the designed control volume. Presently, the FVM is the most common discretization technique used within the computational fluid dynamics (CFD) domain. In this day, multiple techniques for simulating the strongly coupled fluid-structure systems numerically are constantly being researched as the CFD analysis approach evolves swiftly. We introduce a segmented neural network-based approach for learning FSI problems. The FSI simulation domain is discretized into two smaller sub-domains, i.e., fluid (FVM) and solid (FEM) domains, and utilizes an autonomous neural network for each. A python-based scientific library is used to couple the two networks which take care of boundary data communication, data mapping, and equation coupling. The coupled Ansys fluent-structural analysis data will be used for training the two neural networks. We solve the incompressible fluid flow over a flexible two-dimensional (2D) cantilever beam. The fluid (Air) is assumed to be at steady-state condition. The fluid-structure weak coupling is assumed to be one-directional as the flexible structure has no effects on the fluid flow. Changes in the geometrical and material properties of a solid structure such as bluff/curved - corners/surfaces, physical dimensions, young’s modulus of elasticity, and mass moment of inertia will affect the dynamics of the structure.

Presenting Author: Clinton Chijioke The University of Texas at El Paso