GPU Ray Tracing for the Analysis of Light Deflection in Inhomogeneous Refractive Index Fields of Hot Tailored Forming
Pascal Kern1, Max Brower-Rabinowitsch1, Lennart Hinz1
1Institute of Measurement and Automatic Control, Stiftung Gottfried Wilhelm Leibniz Universität Hannover, An der Universität 1, D-30823 Garbsen, Germany.
Sensors (Basel, Switzerland)
|April 28, 2025
Summary
This study addresses geometric deviations in hot-forming hybrid parts by simulating air refractive index fluctuations. It improves optical quality control by optimizing measurement positions and reducing uncertainty.
Area of Science:
- Manufacturing Engineering
- Optical Metrology
- Materials Science
Background:
- Hybrid bulk metal parts are crucial for modern engineering but exhibit complex shrinkage due to thermal expansion differences.
- Hot-forming processes induce significant temperature gradients, causing air density fluctuations and an inhomogeneous refractive index field (IRIF).
- IRIF adversely affects optical geometry reconstruction accuracy by deflecting light during in situ quality monitoring.
Purpose of the Study:
- To predict the magnitude and orientation of refractive index fluctuations during hot-forming.
- To assess the impact of IRIF on optical measurement accuracy using a ray tracing simulation.
- To optimize measurement strategies for enhanced quality control in hybrid part production.
Main Methods:
- Utilized existing simulation data for inhomogeneous refractive index fields (IRIF).
- Employed a GPU-accelerated ray tracing framework to simulate light deflection.
- Analyzed simulation results to determine optimal measurement positions and quantify uncertainties.
Main Results:
- Quantified the impact of IRIF on optical measurements during hot-forming.
- Demonstrated the effectiveness of simulation-based approaches in predicting refractive index variations.
- Identified optimized measurement positions to mitigate light deflection effects.
Conclusions:
- Simulation of IRIF is crucial for understanding and compensating for optical measurement errors in hot-forming.
- The developed method enables reduced and quantified uncertainties in surface reconstruction.
- This approach significantly improves the reliability of in situ quality control for hybrid bulk metal parts.


