Numerical Optimization of Heat Exchanger Design Using Physics Informed Neural Networks (PINNs) and Fluid Structure Interaction (FSI)
Identyfikator grantu: PT01169
Kierownik projektu: Moizuddin Khaja
Politechnika Gdańska
Wydział Inżynierii Mechanicznej i Okrętownictwa
Gdańsk
Data otwarcia: 2024-05-10
Streszczenie projektu
This project aims to enhance the efficiency of heat exchangers through the development of a PINN model that optimizes the design based on specific operational requirements. The project will initially validate the model using documented analytical, numerical, and experimental results for simple geometries. As complexity is added, the model will be validated through numerical methods and ultimately through experimental approaches for the most complex designs.
The project seeks to not only optimize the heat exchanger configurations but also to analyze the interdependencies between various design parameters when changes are implemented. This dual approach will allow for a comprehensive understanding of the variables affecting heat exchanger efficiency and will aid in developing more robust designs.
The project seeks to not only optimize the heat exchanger configurations but also to analyze the interdependencies between various design parameters when changes are implemented. This dual approach will allow for a comprehensive understanding of the variables affecting heat exchanger efficiency and will aid in developing more robust designs.