Multidisciplinary Optimization of Axial Turbine Blade Based on CFD Modelling and FEA Analysis

Bahr Ennil, Ali; M A Elfaghi, Abdulhafid

Abstract

The turbine blade is designed to achieve expansion at high efficiency levels. For improving the turbine efficiency, different aerodynamic design optimisations are performed. On the other hand, the aerodynamic design must be enhanced to match the mechanical design. This research proposes a novel design optimisation method for both aerodynamic and mechanical requirements. A multidisciplinary optimisation approach is used to improve the reliability of the turbine design, which included the use of Computational Fluid Dynamics (CFD) models and Finite Element Analysis (FEA). The primary objective is to guarantee that the aerodynamically optimised blade profile could efficiently withstand mechanical stress. The multidisciplinary optimisation approach is successful in reducing total equivalent pressures from 49.72 MPa to 41.73 MPa while keeping the turbine's overall efficiency at an impressive level of 80.95%. These Results highlight the effectiveness of using a multidisciplinary optimization method to successfully improve the efficiency of a turbine blade profile while simultaneously ensuring its ability to withstand the needed mechanical loads. Using a multidisciplinary optimisation method, the turbine maintains an impressively high efficiency of approximately 83%, with only a marginal reduction of 1.8% compared to the efficiency achieved solely through aerodynamic blade optimisation.

Citation

Bahr Ennil, A., & M A Elfaghi, A. (2024). Multidisciplinary Optimization of Axial Turbine Blade Based on CFD Modelling and FEA Analysis. Journal of Advanced Research in Applied Mechanics and Computational Fluid Dynamics, 120(1), 40-49. https://doi.org/10.37934/aram.120.1.4049

• Journal Article Type: Article
• Acceptance Date: Jun 4, 2024
• Online Publication Date: Jul 10, 2024
• Publication Date: Jun 30, 2024
• Deposit Date: Jul 22, 2024
• Publicly Available Date: Jul 25, 2024
• Journal: Journal of Advanced Research in Applied Mechanics and Computational Fluid Dynamics
• Print ISSN: 2394-7055
• Publisher: Advanced Research Publications
• Peer Reviewed: Peer Reviewed
• Volume: 120
• Issue: 1
• Pages: 40-49
• DOI: https://doi.org/10.37934/aram.120.1.4049