Quantifying Thermal Model Accuracy in PBF-LB/M using Statistical Similarity Tests Against Thermographic Measurements

Numerical simulation models for Laser Powder Bed Fusion of metals (PBFLB/ 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 insitu 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 metrics and evaluate their applicability to PBF-LB/M. We also propose a multi-scale similarity assessment approach tailored to model fidelity and application.