Next Article in Journal
Exploration of Axial Fan Design Space with Data-Driven Approach
Previous Article in Journal
Multiscale Simulation of the Hydroabrasive Erosion of a Pelton Bucket: Bridging Scales to Improve the Accuracy
Open AccessArticle

Adjoint-Based Multi-Point and Multi-Objective Optimization of a Turbocharger Radial Turbine

Von Karman Institute for Fluid Dynamics, Turbomachinery and Propulsion Department, Waterloosesteenweg 72, 1640 Sint-Genesius-Rode, Belgium
*
Author to whom correspondence should be addressed.
This paper is an extended version of our paper published in the Proceedings of the 13th European Conference on Turbomachinery Fluid Dynamics and Thermodynamics, Lausanne, Switzerland, 8–12 April 2019; Paper No. 48.
Int. J. Turbomach. Propuls. Power 2019, 4(2), 10; https://doi.org/10.3390/ijtpp4020010
Received: 3 May 2019 / Revised: 10 May 2019 / Accepted: 16 May 2019 / Published: 21 May 2019
This paper presents a gradient-based design optimization of a turbocharger radial turbine for automotive applications. The aim is to improve both the total-to-static efficiency and the moment of inertia of the turbine wheel. The search for the optimal designs is accomplished by a high-fidelity adjoint-based optimization framework using a fast sequential quadratic programming algorithm. The proposed method is able to produce improved Pareto-optimal designs, which are trade-offs between the two competing objectives, in only a few iterations. This is realized by redesigning the blade shape and the meridional flow channel for the respective target while satisfying imposed aerodynamic constraints. Furthermore, a comparative study with an evolutionary algorithm suggests that the gradient-based method has found the global Pareto front at a computational cost which is about one order of magnitude lower. View Full-Text
Keywords: adjoint; multi-objective optimization; computational fluid dynamics; inertia; radial turbines adjoint; multi-objective optimization; computational fluid dynamics; inertia; radial turbines
Show Figures

Figure 1

MDPI and ACS Style

Mueller, L.; Verstraete, T. Adjoint-Based Multi-Point and Multi-Objective Optimization of a Turbocharger Radial Turbine. Int. J. Turbomach. Propuls. Power 2019, 4, 10.

Show more citation formats Show less citations formats
Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.

Article Access Map

1
Back to TopTop