Semi-empirical model optimization for dynamic stall prediction

• Grant number: 22/14372-6
• Support Opportunities: Scholarships in Brazil - Scientific Initiation
• Start date: May 01, 2023
• End date: April 30, 2024
• Field of knowledge: Engineering - Aerospace Engineering - Aerospace Structures
• Principal Investigator: Flávio Donizeti Marques
• Grantee: Allan Henrique Kamimura
• Host Institution: Escola de Engenharia de São Carlos (EESC). Universidade de São Paulo (USP). São Carlos , SP, Brazil

Abstract

The search for more flexible aeroelasticity structures drive the study of dynamic stall phenomena. In this research project, the objective is to obtain the optimal parameters of a Beddoes e Leishman semi-empirical model to predict aerodynamic loads caused by the dynamic stall for a serie of aerodynamic profiles. For this purpose, an algorithm using Genetic Algorithm (GA) and supervised machine learning will be implemented. Also, an architeture to integrate the algorith and the dynamic stall numerical model will be implemented. The computacional results will be validated against the experimental results found on the literature.