The trace of heat: on the predictive power of modeling transient diffusion

Published

June 26, 2025

Author(s)

Vijaya Holla, Timothy Redford, Philipp Kopp, Stefan Kollmannsberger

Abstract

The paper at hand evaluates the validity of the transient heat equation with phase change and temperature-dependent coefficients as a model to predict the evolution of melt pools for rapid turnaround scan strategies in a laser powder bed fusion (PBF-LB) additive manufacturing (AM) process. In such scenarios, residual heat effects due to short laser-off times between tracks significantly impact the melt pool morphology. Results show that the conduction model accurately captures the rapidly evolving melt pool morphologies under these conditions. This is a fundamental discovery, as the ability to predict such dynamic scenarios has previously only been attributed to much more involved models which include fluid-like effects that otherwise require computational fluid dynamics (CFD). However, the presented validation (e.g., validated comparison to surface topography measurements) clearly demonstrates that a large portion of the observed effects is actually captured by the heat diffusion equation, including a common model of phase change. As a proof of concept for an application of this insight, feedforward control is investigated. Therein, the validated model predicts the melt pool morphology for a modified scan strategy with an increased pause time between the tracks that reduces melt pool distortions observed in the original configuration.

Citation

Progress in Additive Manufacturing

Volume

10

Pub Type

Journals

Download Paper

https://doi.org/10.1007/s40964-025-01147-9

Local Download

Keywords

Thermal simulation, Model validation, Laser optimization, Turnaround effects

Citation

Holla, V. , Redford, T. , Kopp, P. and Kollmannsberger, S. (2025), The trace of heat: on the predictive power of modeling transient diffusion, Progress in Additive Manufacturing, [online], https://doi.org/10.1007/s40964-025-01147-9, https://tsapps.nist.gov/publication/get_pdf.cfm?pub_id=959720 (Accessed September 7, 2025)