| Abstract |
This thesis focuses on optimizing the laser drilling process simulation through the development and validation of advanced numerical models. Traditional simulations often rely on Fourier’s heat conduction law, which assumes an infinite speed of heat propagation—an assumption that becomes physically unrealistic in transient thermal environments such as laser drilling, where rapid temperature changes and steep thermal gradients are present. These limitations can result in significant discrepancies between simulation outcomes and actual physical behavior. To overcome these challenges, non-Fourier heat conduction models have been introduced, incorporating finite thermal wave speeds, time delays, and higher-order derivatives to more accurately represent complex, transient, and nonlinear heat transfer phenomena.
In parallel, fractional derivatives provide a robust framework for capturing non-local and memory-dependent effects that are often neglected in conventional models but are critical in laser drilling. By integrating fractional calculus, it becomes possible to more precisely predict temperature distributions and thermal responses, particularly in scenarios involving heterogeneous media, transient conduction, and thermal wave propagation. This enhanced modeling capability not only improves simulation accuracy but also supports the design and optimization of thermal systems across various applications. To this end, the present research investigates the integration of fractional calculus with non-Fourier models, utilizing meshfree methods for spatial discretization to offer a flexible and computationally efficient approach for simulating complex material behavior and deformation during laser drilling.
The primary objective of this thesis is to provide high-accuracy models of the laser drilling processes. Specific goals include:
1) Modeling and simulating metal removal during laser drilling using fractional non-Fourier models.
2) Estimating the transient development of the laser-drilled hole shape and the associated temperature distribution.
3) Validating the proposed numerical model against published studies and experimental data.
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