Simulation of laser polishing for fused quartz

Nikityuk Y.V., Marchanko L.N., Serdyukov A.N., Bruttan I.V.
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Laser polishing is a promising technology for the finishing of fused quartz (fused silica or quartz glass) products, enabling the removal of subsurface defects induced by mechanical processing. However, the complexity and nonlinearity of the physical processes occurring during laser irradiation complicate the selection of optimal technological parameters. The present paper aims to develop, comparatively analyze, and apply high-precision predictive models for forecasting and optimizing the key performance indicators of the laser polishing process for quartz glass. A verified finite element model implemented in the ANSYS software environment produced a dataset of temperature and stress fields for various combinations of process parameters. This dataset was used to develop and validate four types of predictive models: Polynomial Regression, a Fuzzy Logic System, an Adaptive Neuro-Fuzzy Inference System (ANFIS), and a Multilayer Perceptron (MLP) neural network. The models’ quality was evaluated on a test set using the statistical metrics MAE, RMSE, MAPE, $R^2$, and  $R^2_{Adj}$. A comparative analysis of the models revealed the significant superiority of the MLP neural network, which demonstrated the highest prediction accuracy for all output parameters, achieving Adjusted $R^2$ ($R^2_{Adj}$.) values above 0.97 and a Mean Absolute Percentage Error (MAPE) in the range of 0.7–2.8%. This model was effectively utilized as a surrogate function in combination with a genetic algorithm to successfully identify the optimal process parameters. The constructed MLP neural network model functions as a reliable and high-precision tool, facilitating both prediction and the optimization of fused quartz polishing outcomes using a CO2 laser. This approach effectively approximates the complex nonlinear dependencies inherent in the process and can serve as a foundation for developing intelligent control and optimization systems for this technology.

Keywords: laser polishing, ANSYS, modeling, regression, fuzzy logic system, ANFIS, neural network model, optimization
Citation in English: Nikityuk Y.V., Marchanko L.N., Serdyukov A.N., Bruttan I.V. Simulation of laser polishing for fused quartz // Computer Research and Modeling, 2026, vol. 18, no. 2, pp. 399-421
Citation in English: Nikityuk Y.V., Marchanko L.N., Serdyukov A.N., Bruttan I.V. Simulation of laser polishing for fused quartz // Computer Research and Modeling, 2026, vol. 18, no. 2, pp. 399-421
DOI: 10.20537/2076-7633-2026-18-2-399-421
URL: http://crm-en.ics.org.ru/journal/article/3715/
Creative Commons License This work is licensed under a Creative Commons Attribution-NoDerivs 3.0 Unported License.

Copyright © 2026 Nikityuk Y.V., Marchanko L.N., Serdyukov A.N., Bruttan I.V.

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