Machine Learning-Assisted Topology Optimization for Enhanced Heat Transfer in Additive Manufacturing Components (Matohtam)
This research project aims to develop an optimized design framework for heat transfer devices using predictive algorithms and additive manufacturing.
The project at a glance
About
This research project aims to develop an optimized design framework for heat transfer devices using predictive algorithms and additive manufacturing. It focuses on improving thermal performance through machine learning to optimize heat dissipation or retention based on the physical design parameters. The project will create a novel framework for designing, analyzing, and manufacturing thermal metamaterials, combining machine learning, computer-aided design (CAD), computer-aided engineering (CAE), and additive manufacturing (AM) to enhance thermal management. Customization based on specific application requirements ensures tailored thermal solutions for particular boundary conditions, including optimizing electronics cooling and energy systems and reducing development time and manufacturing costs.
Project team
