Multi-objective Geometry Optimization of a Gas Cyclone Using Triple-Fidelity Co-Kriging Surrogate Models

Cyclone separators are widely used in a variety of industrial applications. A low-mass loading gas cyclone is characterized by two performance parameters, namely the Euler and Stokes numbers. These parameters are highly sensitive to the geometrical design parameters defining the cyclone. Optimizing the cyclone geometry therefore is a complex problem. Testing a large number of cyclone geometries is impractical due to time constraints. Experimental data and even computational fluid dynamics simulations are time-consuming to perform, with a single simulation or experiment taking several weeks. Simpler analytical models are therefore often used to expedite the design process. However, this comes at the cost of model accuracy. Existing techniques used for cyclone shape optimization in literature do not take multiple fidelities into account. This work combines cheap-to-evaluate well-known mathematical models of cyclones, available data from computational fluid dynamics simulations and experimental data to build a triple-fidelity recursive co-Krigingmodel. This model can be used as a surrogate with a multi-objective optimization algorithm Communicated by Zenon Mroz. B Prashant Singh [email protected] 1 Division of Scientific Computing (TDB), Department of Information Technology, Uppsala Universitet, Box 337, 751 05 Uppsala, Sweden 2 Department of Information Technology (INTEC), Ghent University-imec, Technologiepark-Zwijnaarde 15, 9052 Gent, Belgium 3 Mechanical Power Engineering Department, Faculty of Engineering at El-Mattaria, Helwan University, Masaken El-Helmia P.O., Cairo 11718, Egypt 4 Department of Mechanical Engineering, Research Group Fluid Mechanics and Thermodynamics, Vrije Universiteit Brussel, Pleinlaan 2, 1050 Brussels, Belgium