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NIST - National Institute of Standards and Technology
12/12/2025 | Press release | Distributed by Public on 12/13/2025 03:56
Quantifying Thermal Model Accuracy in PBF-LB/M Using Statistical Similarity Tests Against Thermographic Measurements
Published
December 12, 2025
Author(s)
Vijaya Holla, Brandon Lane, Jesse Redford, Philipp Kopp, Stefan Kollmannsberger
Abstract
Numerical simulation models for laser powder bed fusion of metals (PBF-LB/M) vary in complexity and fidelity, ranging from high-fidelity models that capture melt pool dynamics to simplified models suited for part-scale temperature predictions and process optimizations. Validation against experimental data is essential to build confidence in their predictive capabilities. However, for in-situ thermographic measurements, a direct comparison is challenging due to the data's size and the multi-scale nature of the process. Similarities must be analyzed at different spatial and temporal scales based on the model's fidelity and its intended application. For example, agreement between a thermal simulation and measurement in a steady-state scenario does not guarantee accuracy during transient phases. Statistical similarity measures provide a quantitative means to assess model-measurement agreement, highlighting regions of high and low similarity. In this work, we validate a thermal simulation model, discretized using the space-time finite element method, against thermographic camera measurements using various similarity measures and evaluate their applicability to PBF-LB/M. We also propose a multi-scale similarity assessment approach tailored to model fidelity and application.
Citation
Integrating Materials and Manufacturing Innovation
Pub Type
Journals
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Keywords
thermal simulation, Model-measurement comparison, Similarity tests, Space-time finite element method, thermography, additive manufacturing, laser powder bed fusion
Citation
Holla, V. , Lane, B. , Redford, J. , Kopp, P. and Kollmannsberger, S. (2025), Quantifying Thermal Model Accuracy in PBF-LB/M Using Statistical Similarity Tests Against Thermographic Measurements, Integrating Materials and Manufacturing Innovation, [online], https://doi.org/10.1007/s40192-025-00430-5, https://tsapps.nist.gov/publication/get_pdf.cfm?pub_id=960461 (Accessed December 13, 2025)
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NIST - National Institute of Standards and Technology published this content on December 12, 2025, and is solely responsible for the information contained herein. Distributed via Public Technologies (PUBT), unedited and unaltered, on December 13, 2025 at 09:56 UTC. If you believe the information included in the content is inaccurate or outdated and requires editing or removal, please contact us at [email protected]