Behavioral Analysis of H1 Reconstruction in New Software Environments

The precise prediction of fluid behavior is required in many fields of engineering. Fluid flows are governed by a complex system of continuous partial differential equations (PDEs) which rarely have an exact analytical solution. Computational Fluid Dynamics (CFD) has emerged as a leading method of analyzing fluid flows, by numerically solving the respective PDEs. Current methods in finite volume schemes of CFD on unstructured meshes have two major sources of errors: noise in the reconstructed gradients and lack of cancellation during flux integration. Our new second-order “H1 reconstruction” scheme produces a smoother, more accurate gradient than traditional “Least-squares reconstruction” when applied to smooth solution data. We will be analyzing the behaviour of this new reconstruction when implemented in a different software environments. This would provide very valuable insights into the behaviour and adaptability of the new scheme. Successful application of our proposed new scheme entails substantial improvement in the accuracy for the flow solver of ANSYS Ltd. (FLUENT), with an affordable increase in computational cost.

Intern: 
Chandan Sejekan
Faculty Supervisor: 
Carl Ollivier-Gooch
Province: 
British Columbia
Partner: 
Sector: 
Partner University: 
Program: