Christophe Devals
École Polytechnique de Montréal
28 Papers
142 Citations
Christophe Devals is an academic researcher from École Polytechnique de Montréal. The author has contributed to research in topics: Finite element method & Turbine. The author has an hindex of 10, co-authored 28 publications. Previous affiliations of Christophe Devals include École Polytechnique.
Chat about Author
Papers
Hydrodynamics characterization of the maxblend impeller
Arash Iranshahi,Christophe Devals,Mourad Heniche,Louis Fradette,Philippe A. Tanguy,Katsuhide Takenaka +5 more
TL;DR: In this paper, the hydrodynamic characteristics of the Maxblend TM impeller have been investigated in the case of viscous Newtonian fluids, including power consumption, mixing evolution, and the effect of baffles in the laminar and transition flow regimes.
64
CFD analysis of several design parameters affecting the performance of the Maxblend impeller
TL;DR: It was found that the bottom clearance plays a significant role on the power consumption, and that the value of the Reynolds number and the power law index strongly affect the axial pumping efficiency and the shear rate profile.
45
Simulation-based investigation of unsteady flow in near-hub region of a Kaplan Turbine with experimental comparison
TL;DR: In this article, a detailed comparison of steady and unsteady turbulent flow simulation results in the U9 Kaplan turbine draft tube with experimental velocity and pressure measurements is presented, demonstrating a significant increase in precision of the flow modeling in the runner cone region.
38
Multi-fidelity shape optimization of hydraulic turbine runner blades using a multi-objective mesh adaptive direct search algorithm
TL;DR: A robust multi-fidelity design optimization methodology has been developed to integrate advantages of high- and low-f fidelity analyses, aiming to help designers reach more efficient turbine runners within reasonable computational time and cost.
31
Steady and unsteady flow computation in an elbow draft tube with experimental validation
TL;DR: This paper presents a study that assesses the predictive capacity of a combination of steady and unsteady RANS numerical computations to predict draft tube losses over the complete range of operation of a Francis turbine.
28