TY - JOUR AU - Xu, Jinyang AU - Samsudeensadham, S. AU - Jaiswal, Anand Prakash AU - Magyar, Gergely AU - Lukács, Tamás AU - Geier, Norbert AU - Krishnaraj, Vijayan AU - Shen, Jiaxin AU - Shi, Zhe AU - Chen, Ming TI - A critical review on numerical modeling of cutting-induced damages for CFRP composites JF - COMPOSITE STRUCTURES J2 - COMPOS STRUCT VL - 378 PY - 2026 PG - 34 SN - 0263-8223 DO - 10.1016/j.compstruct.2025.119839 UR - https://m2.mtmt.hu/api/publication/36436314 ID - 36436314 N1 - Acknowledgments: The authors gratefully acknowledge the financial support of the National Natural Science Foundation of China (Grant No. 52175425) and the Explorers Program of Shanghai (Grant No. 24TS1414500). The work was also funded by the 10th Sino-Hungarian Intergovernmental Scientific and Technological Cooperation Project (Grant No. 2024-10-2). Moreover, this project supported by the Doctoral Excellence Fellowship Programme (DCEP) is partly funded by the National Research Development and Innovation Fund of the Ministry of Culture and Innovation and the Budapest University of Technology and Economics, under a grant agreement with the National Research, Development and Innovation Office. AB - Machining carbon fiber reinforced polymers (CFRPs) is facing huge challenges due to the generation of crucial damages, posing a fatal impact on structural performance and accuracy. To date, numerous studies have been performed to address the damage issues associated with cutting CFRPs through experimental and numerical ways. However, no review articles are reported so far to summarize the state-of-the-art advances achieved in the numerical modeling of cutting-induced damages for CFRPs. To fill this gap, this paper firstly overviews the fundamental characteristics of cutting-induced damages for CFRPs and then summarizes the potential numerical methods applied for CFRP machining. A particular focus is placed on detailing progress of the constitutive models, failure criteria, definition of tool-chip interaction and frictional behavior for CFRP machining. Moreover, a rigorous literature survey was conducted to report the recent advances in the modeling of orthogonal cutting damages and drilling-induced damages for CFRP composites. The thermo-mechanical effects and parametric effects on the cutting-induced damages as well as the numerical quantification/assessment are illustrated. Eventually, the future perspectives concerning the numerical prediction and estimation of cutting-induced damages for CFRPs are outlined. The paper can benefit both academia and industry to realize damage-free cutting of CFRP composites. LA - English DB - MTMT ER - TY - JOUR AU - Pomázi, Ákos AU - Magyar, Gergely AU - Toldy, Andrea TI - Methods for predicting the fire behaviour of fibre reinforced thermoset composites JF - POLYMER DEGRADATION AND STABILITY J2 - POLYM DEGRAD STABIL VL - 245 PY - 2026 PG - 11 SN - 0141-3910 DO - 10.1016/j.polymdegradstab.2025.111857 UR - https://m2.mtmt.hu/api/publication/36849868 ID - 36849868 N1 - This research was funded by the National Research, Development and Innovation Office (NKFIH K142517 and STARTING 150473). Project no TKP-6–6/PALY-2021 has been implemented with the support provided by the Ministry of Culture and Innovation of Hungary from the National Research, Development and Innovation Fund, financed under the TKP2021-NVA funding scheme. Ákos Pomázi is thankful for the support of the Michelberger Master Prize of the Hungarian Academy of Engineering. This research was partly supported by the Doctoral Excellence Fellowship Programme (DCEP) is funded by the National Research Development and Innovation Fund of the Ministry of Culture and Innovation and the Budapest University of Technology and Economics, under a grant agreement with the National Research, Development and Innovation Office. AB - Destructive tests are typically used to evaluate the fire performance of polymers and their composites, implying high material costs and long testing times. Developing numerical models to predict flammability requires advanced mathematical expertise, IT resources, and realistic input parameters. In this study, we aimed to predict the key flammability parameters based on the chemical structure of the resin matrices and fibre content of composites, providing a potential alternative to costly experimental methods. We employed Random Forest Classifier (RFC), XGBoost algorithms, and an artificial neural network (ANN) model to predict key combustion parameters: peak heat release rate (pHRR), time to ignition (TTI), total heat release (THR) and the char residue (CR) solely based on chemical structure of the epoxy matrix and fibre content of the composite. After making the predictions, we assessed the performance of the models using consistent statistical indicators (mean absolute error (MAE), mean square error (MSE), and the determination parameter (R2)). LA - English DB - MTMT ER - TY - JOUR AU - Geier, Norbert AU - Magyar, Gergely TI - Advanced allowance planning of CFRP composites exploiting the pattern of chopped carbon fibre reinforcement clusters JF - PROCEDIA CIRP J2 - PROCEDIA CIRP VL - 131 PY - 2025 SP - 130 EP - 135 PG - 6 SN - 2212-8271 DO - 10.1016/j.procir.2024.09.021 UR - https://m2.mtmt.hu/api/publication/35802522 ID - 35802522 AB - Conventional allowance planning of carbon fibre-reinforced polymer composite plates that must be mechanically machined is based on mainly the analysis of the precision of composite manufacturing technologies. This approach neglects the impact of randomly oriented and positioned chopped fibre reinforcement clusters leading to unpredictable fibre cutting angles and inconsistent quality during machining. To address this issue, we developed an innovative allowance planning method for polymer composites reinforced with chopped fibres. Our approach optimizes the size of the non-uniform allowance to minimize machining-induced burrs on the machined edges by detecting fibre reinforcement clusters on the composite surface through digital image processing and employing a convolution-based optimization of geometric feature patterns. Validation through drilling experiments demonstrated that our method improved the average burr factor by 50% compared to a conventional allowance planning technique. Although the proposed method is recommended to be improved to manage the effects of three-dimensional fibre clusters on burr occurrence, it encourages a novel direction in allowance planning of composites having non-defined directional reinforcements. LA - English DB - MTMT ER - TY - CONF AU - Barcza, Bende AU - Magyar, Gergely AU - Szántó, Mátyás ED - Barabás, István TI - Alacsony paraméterszámú nyelvi modellek hatékony finomhangolása osztályozási feladatra T2 - OGÉT 2025 - XXXIII. Nemzetközi Gépészeti Konferencia PB - Erdélyi Magyar Műszaki Tudományos Társaság (EMT) C1 - Nagyvárad T3 - Nemzetközi Gépészeti Találkozó (OGÉT), ISSN 2068-1267 ; 33. PY - 2025 SP - 25 EP - 30 PG - 6 UR - https://m2.mtmt.hu/api/publication/36137134 ID - 36137134 LA - Hungarian DB - MTMT ER - TY - CHAP AU - Barcza, Bende AU - Magyar, Gergely AU - Szántó, Mátyás ED - Kiss, Bálint ED - Szirmay-Kalos, László TI - Development of a multi-objective optimisation software framework for EoL product DSP T2 - Proceedings of the Workshop on the Advances of Information Technology (WAIT 2025) PB - BME Irányítástechnika és Informatika Tanszék CY - Budapest SN - 9789634219811 PY - 2025 SP - 90 EP - 96 PG - 7 UR - https://m2.mtmt.hu/api/publication/36167075 ID - 36167075 LA - English DB - MTMT ER - TY - JOUR AU - Geier, Norbert AU - Magyar, Gergely TI - Machining-induced burr distribution along hole contours in unidirectional carbon fibre-reinforced polymer (UD-CFRP) composites JF - COMPOSITES PART C: OPEN ACCESS J2 - COMPOS PART C VL - 18 PY - 2025 PG - 11 SN - 2666-6820 DO - 10.1016/j.jcomc.2025.100640 UR - https://m2.mtmt.hu/api/publication/36297148 ID - 36297148 N1 - Funding Agency and Grant Number: Janos Bolyai Research Scholarship of the Hungarian Academy of Sciences [BO/00508/22/6]; Doctoral Excellence Fellowship Programme (DCEP) - National Research Development and Innovation Fund of the Ministry of Culture and Innovation; Budapest University of Technology and Economics, under a grant agreement with the National Research, Development and Innovation Office; Ministry of Culture and Innovation of Hungary from the National Research, Development and Innovation Fund [EKOP-24-4-II-BME- 157, EKOP-24-3-BME-383] Funding text: This research was partly supported by the Janos Bolyai Research Scholarship of the Hungarian Academy of Sciences No. BO/00508/22/6 and supported by the Doctoral Excellence Fellowship Programme (DCEP) is funded by the National Research Development and Innovation Fund of the Ministry of Culture and Innovation and the Budapest University of Technology and Economics, under a grant agreement with the National Research, Development and Innovation Office. The project has been partly implemented with the support provided by the Ministry of Culture and Innovation of Hungary from the National Research, Development and Innovation Fund, financed under the EKOP-24-4-II-BME- 157 and EKOP-24-3-BME-383 funding scheme. The authors acknowledge the support of Norbert Ibriksz, Gyorgy Poka, Daniel Istvan Poor and Csongor Pereszlai in the experimental work. AB - Machining-induced burr formation in carbon fibre-reinforced polymer (CFRP) composites is difficult to predict and control, mainly due to the anisotropy and inhomogeneity of the fibrous composite, as well as the rapid tool condition change due to the abrasive tool wear. The main aim of this study is to develop a model to determine the density and distribution functions of risky fibre cutting angles where machining-induced burrs are expected to be formed when hole-machining CFRPs. Four models were introduced, and their adequacy was analysed. The coefficients of the models were determined using datasets of three previous research projects (i.e., 2 380 808 data points) and validated through a fourth one (208 571 data points) where hole machining experiments were carried out using different tools, parameters and setups. The normality of the risky fibre cutting angles was tested through the Shapiro-Wilk and Kolmogorov-Smirnov statistical tests, and the distribution was found to be not Gaussian. The developed trigonometric model shows a good fit to the data points, i.e., the determination coefficient is at least 0.949 for each dataset. The results indicate that machining-induced burr formation is most probable at a fibre cutting angle of 118–133°, and 60 % of burr occurrences fall within the 110°–160° range when the critical fibre cutting angle is 133° These findings provide a foundation for the industrial adoption of advanced machining strategies for fibrous polymer composites, enabling a significant reduction of machining‑induced burrs in CFRPs. LA - English DB - MTMT ER - TY - CONF AU - Magyar, Gergely AU - Geier, Norbert TI - A szálvágási szög és forgácsolásindukált sorja közötti összefüggés vizsgálata szénszálerősítésű polimer kompozitban T2 - OGÉT 2024 - XXXII. Nemzetközi Gépészeti Konferencia PB - Erdélyi Magyar Műszaki Tudományos Társaság (EMT) C1 - Kolozsvár T3 - Nemzetközi Gépészeti Találkozó (OGÉT), ISSN 2068-1267 ; 32. PY - 2024 SP - 225 EP - 229 PG - 5 UR - https://m2.mtmt.hu/api/publication/34976244 ID - 34976244 LA - Hungarian DB - MTMT ER - TY - JOUR AU - Geier, Norbert AU - Magyar, Gergely AU - Giner, Jakob AU - Lukács, Tamás AU - Póka, György TI - Carbon fibre detection in polymer composites reinforced by chopped carbon fibres through digital image processing and machine learning JF - JOURNAL OF COMPOSITE MATERIALS J2 - J COMPOS MATER VL - 58 PY - 2024 IS - 21 SP - 2379 EP - 2395 PG - 17 SN - 0021-9983 DO - 10.1177/00219983241268861 UR - https://m2.mtmt.hu/api/publication/35156746 ID - 35156746 N1 - Faculty of Mechanical Engineering, Department of Manufacturing Science and Engineering, Budapest University of Technology and Economics, Budapest, Hungary Division of Factory Planning and Production Management, Fraunhofer Austria Research GmbH, Vienna, Austria Correspondence Address: Geier, N.; Faculty of Mechanical Engineering, Hungary; email: geier.norbert@gpk.bme.hu Funding details: European Commission, EC Funding details: National Research, Development and Innovation Office Funding details: 739592 Funding details: Magyar Tudományos Akadémia, MTA, ÚNKP-23-5-BME-409, ÚNKP-23-3-I-BME-201, BO/00508/22/6 Funding text 1: The research reported in this paper and carried out at BME has been supported by the National Laboratory of Artificial Intelligence funded by the NRDIO under the auspices of the Ministry for Innovation and Technology. This research was partly supported by the J\\u00E1nos Bolyai Research Scholarship of the Hungarian Academy of Sciences No. BO/00508/22/6 and by the New National Excellence Program of the Ministry for Innovation and Technology No. \\u00DANKP-23-5-BME-409 and \\u00DANKP-23-3-I-BME-201. Work for this paper was supported by the European Commission through the H2020 project EPIC under grant No. 739592. This project supported by the Doctoral Excellence Fellowship Programme (DCEP) is partly funded by the National Research Development and Innovation Fund of the Ministry of Culture and Innovation and the Budapest University of Technology and Economics, under a grant agreement with the National Research, Development and Innovation Office. Funding text 2: The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This work was supported by the by the NRDIO, Hungarian Academy of Sciences; No. BO/00508/22/6, Ministry for Innovation and Technology; No. \\u00DANKP-23-5-BME-409 and \\u00DANKP-23-3-I-BME-201, European Commission through the H2020 project EPIC under grant No. 739592, Ministry of Culture and Innovation and the Budapest University of Technology and Economics. AB - Mechanical and thermodynamical properties and thus machinability of carbon fibre reinforced polymer composites significantly depend on the fibre orientation relative to the load direction. However, the orientations of the fibre groups in polymer composites reinforced by chopped carbon fibres are stochastic; therefore, the properties and machinability of such composites are challenging to plan, predict and optimise. We developed four different and novel approaches for fibre detection in polymer composites reinforced by chopped carbon fibres: (i) detecting the fibres through naked eye supported manual drawing, (ii) digital image processing of optical images, (iii) machine learning-based fibre detection, and (iv) rectangle fitting on the outputs of the automated processes using the Chaudhuri and Samal method. The applicability of the novel approaches was tested through optically captured images of polymer composites reinforced by chopped carbon fibres. The developed methods are each capable of detecting fibre groups at the top and bottom of the composite plate with certain limitations. The rectangle fitting approaches performed the best from the point of view of correctly identifying of fibre groups, followed by the machine learning-based and the conventional digital image processed, respectively. As a result of this study, the machining process planning and condition monitoring of polymer composites reinforced by chopped carbon fibres is more deeply supported. LA - English DB - MTMT ER - TY - CONF AU - Magyar, Gergely AU - Szalay, Tibor AU - Geier, Norbert TI - EVALUATION OF THE RELATIONSHIP BETWEEN FIBRE CUTTING ANGLE AND DRILLING-INDUCED BURR OCCURRENCE IN CARBON FIBRE REINFORCED POLYMER (CFRP) COMPOSITES T2 - Proceedings of the Technological Forum SN - 9788087583524 PY - 2024 SP - 86 EP - 90 PG - 5 UR - https://m2.mtmt.hu/api/publication/35928846 ID - 35928846 LA - English DB - MTMT ER - TY - JOUR AU - Geier, Norbert AU - Patra, Karali AU - Anand, Ravi Shankar AU - Ashworth, Sam AU - Balázs, Barnabás Zoltán AU - Lukács, Tamás AU - Magyar, Gergely AU - Tamás-Bényei, Péter AU - Xu, Jinyang AU - Davim, J Paulo TI - A critical review on mechanical micro-drilling of glass and carbon fibre reinforced polymer (GFRP and CFRP) composites JF - COMPOSITES PART B-ENGINEERING J2 - COMPOS PART B-ENG VL - 254 PY - 2023 PG - 21 SN - 1359-8368 DO - 10.1016/j.compositesb.2023.110589 UR - https://m2.mtmt.hu/api/publication/33628631 ID - 33628631 N1 - Funding Agency and Grant Number: 9th Sino-Hungarian Intergovernmental Scientific and Technological Cooperation Project [2019-2.1.11-TET-2020-00203]; Janos Bolyai Research Scholarship of the Hungarian Academy of Sciences [2021-07]; New National Excellence Program of the Ministry for Culture and Innovation from the source of the National Research, Development and Innovation Fund [BO/00508/22/6, BO/00658/21/6]; Ministry of Innovation and Technology of Hungary from the National Research, Development and Innovation Fund [1JNKP-22-5-BME-327, 1JNKP-22-5-BME-309]; [BME-NVA-02]; [TKP2021] Funding text: This research was implemented thanks to the support of the 2019-2.1.11-TET-2020-00203 project, which encourages scientific and technological cooperation between China and Hungary and the 9th Sino-Hungarian Intergovernmental Scientific and Technological Cooperation Project (Grant No. 2021-07). This research was partly supported by the Janos Bolyai Research Scholarship of the Hungarian Academy of Sciences No. BO/00508/22/6 and BO/00658/21/6. Moreover, by 1JNKP-22-5-BME-327 and 1JNKP-22-5-BME-309 New National Excellence Program of the Ministry for Culture and Innovation from the source of the National Research, Development and Innovation Fund. The research reported in this paper is part of project no. BME-NVA-02, implemented with the support provided by the Ministry of Innovation and Technology of Hungary from the National Research, Development and Innovation Fund, financed under the TKP2021 funding scheme. LA - English DB - MTMT ER -