An automatic method for optimizing Venturi shape in cavitation flows
Paper in proceeding, 2017

In order to lower the energy consumption of the fibrillation stage for the pulp and paper industry, a new technology need to be innovated and developed. The current research work deals with a new innovative concept based on creating cavitation in the pulp flow. A venturi nozzle is designed and optimized, where hydrodynamic cavitation is achieved by the so called Venturi effect. This paper focuses on the development of an automatic method for venturi shape optimization. The process of cavitation is hard to control and can cause high mechanical wear, therefore an optimization study of the venturi shape is performed with two main objectives. Firstly, to achieve cavitation that is sustained for as long as possible downstream and secondly to avoid cavitation at the walls. The developed method is a type of two-level optimization based on neural networks and evolutionary optimization. A number of simulations are executed and the optimization is then performed on a solver approximation instead of the real solver, which considerably reduces computation time. The obtained results show the optimal venturi configuration and the relative importance of each shape parameter. The optimal configuration is a clear improvement of the baseline configuration and an improvement also compared to all of the tested samples, thereby validating the optimization method.

Cavitation

Neural networks

Pulp & paper

Venturi nozzle

Optimization

Author

Vijay Shankar

Luleå University of Technology

Anton Lundberg

Student at Chalmers

Kristian Bartholdsson Frenander

Student at Chalmers

Lars Landström

Taraka Pamidi

Luleå University of Technology

Örjan Johansson

Luleå University of Technology

International Conference on Fluid Flow, Heat and Mass Transfer

2369-3029 (eISSN)

Vol. 2017 160

4th International Conference on Fluid Flow, Heat and Mass Transfer, FFHMT 2017
Toronto, Canada,

Subject Categories

Aerospace Engineering

Other Engineering and Technologies not elsewhere specified

Vehicle Engineering

DOI

10.11159/ffhmt17.160

More information

Latest update

10/14/2021