Work

Modeling Cavitation in Converging–Diverging Nozzle Using Computational Fluid Dynamics and Machine Learning Model

Year: 2025

Type: article

Abstract: Cavitation occurs when the pressure drops below the saturation pressure. In this study, computational fluid dynamics (CFD) is used to model the cavitation behavior in the Venturi tube under high pressure and to investigate the impact of geometric parameters on steam generation. In recent years, there has been a shift toward exploring machine learning as an alternative to traditional CFD. This work aims to establish an artificial neural network (ANN) using numerical analysis results to predict flow characteristics for various geometrical shapes of nozzles. This including the prediction of pressure drop and steam generation. The final results demonstrate a high accuracy in prediction.

Source: Chemical Engineering & Technology

DOI: 10.1002/ceat.12011

Authors: You‐Cheng Lu, Morteza Mohammadzaheri, Way Lee Cheng

Institutions: National Sun Yat-sen University, German University of Technology

Language: English

Topic: Cavitation Phenomena in Pumps

Subfield: Mechanics of Materials

Field: Engineering

Domain: Physical Sciences

Open Access status: hybrid

Estimated APC paid: $3,930

Funder: National Science and Technology Council