2026-08-14 –, Room 4
Many modern manufacturing techniques rely heavily on lasers and more often than not, the behavior of heat in these systems plays a key role in determining whether a finished product is of acceptable quality. In this talk, I present how it's possible to construct a bespoke finite-element method solver for the heat equation, starting from first principles and building on the work of Ferrite.jl and DifferentialEquations.jl. The solver is then validated against experimental results and I show how access to the inner workings facilitates the extension of the code base to tackle related problems such as computing surface hardness after laser processing.
In doing research on laser-based manufacturing techniques, particularly more recent ones such as directed energy deposition, when the cost of materials and time meets with the large parameter space of the problem, simulation becomes a necessity.
While commercial solutions do exist, they typically abstract away the inner workings of the physics taking place. In consequence, building a custom solver can be a great way to understand both the physics and the computer science involved.
Starting from first principles, I show how I implemented the transient heat equation into the Ferrite.jl framework and how DifferentialEquations.jl can be used to efficiently solve the ordinary differential equations required for temperature, while taking into consideration the non-linear boundary conditions including radiation. The solver is then validated against experimental results obtained in the laboratory.
Finally, I show how exposing the inner workings of the solver makes the implementation of additional functionality, such as computing the hardness of the processed material much easier.
- PhD student at the Faculty of Physics of the University of Bucharest.
- Research assistant at the Center of Advanced Laser Technologies (CETAL) of the National Institute for Laser Plasma and Radiation (Romania).