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Staff profile

Overview

Soheil Navvabi

Research Postgraduate - Computational Mechanics Node

Affiliations
Affiliation
Research Postgraduate - Computational Mechanics Node in the Department of Engineering

Research interests

  • My research focuses on the optimisation of internal structures for wind turbine blades, an essential component in advancing sustainable energy technologies. Specifically, I am working on developing an innovative computational framework that combines the strengths of the Discontinuous Galerkin Finite Element Method (DG FEM) and Reinforcement Learning (RL).
  • By leveraging the flexibility and efficiency of DG FEM, particularly with adaptive mesh algorithms, my research aims to establish a robust and reliable structural analysis method capable of accurately evaluating complex designs. Coupling this with RL as the optimisation layer enables our framework to intelligently explore various design possibilities, dynamically adjusting parameters to identify optimal solutions efficiently.
  • The ultimate goal of my research is to create a comprehensive optimisation system capable of determining the ideal stack of composite material layers for wind turbine blades. This system will not only decide the optimal number and order of layers but also discern whether certain layers are necessary at all. This unique integration of DG FEM and RL holds great promise for delivering a flexible, cost-effective, and high-performing approach to structural optimisation, significantly contributing to the enhancement of wind energy systems.