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Machine Learning Based Modeling of Coating Properties and Corrosion of Borided AISI H1 Tool Steel

Yıl 2024, Cilt: 39 Sayı: 3, 625 - 638, 03.10.2024
https://doi.org/10.21605/cukurovaumfd.1560038

Öz

Due to the significant increases in hardness, wear, and corrosion resistance it provides, boronizing is one of the most commonly used thermochemical coating processes. In this study, the effect of process temperature and duration on coating thickness, surface roughness, microhardness, and corrosion rate in boronized hot work tool steel AISI H11 material with pack boronizing technique has been modeled and investigated using machine learning methods. Multiple linear, K-nearest neighbors, support vector machine, decision tree, random forest, and extreme gradient boosting regression algorithms were employed to create models, and their performances were compared using R2, mean absolute error, and mean squared error criteria. Coating thickness and hardness increase with process temperature and duration. However, process temperature has a more significant effect on these properties compared to duration. Upon examining the results of the regression model, it was observed that the effects of coating parameters on thickness and roughness cumulatively transformed into an effect on the corrosion rate. As a result of the study, optimum parameter values for corrosion resistance in boronized AISI H11 steel were determined to be 1000°C and 2.2 hours.

Kaynakça

  • 1. Ma, L., Luo, Y., Wang, Y., Du, W., Song, Z., Zhang, J., 2018. Fatigue and ratcheting assessment of AISI H11 at 500°C using constitutive theory coupled with damage rule. Fatigue Fract Eng Mater Struct, 41(3), 642-652.
  • 2. Tillmann, W., Grisales, D., Stangier, D., Butzke, T., 2019. Tribomechanical behaviour of TiAlN and CrAlN coatings deposited onto AISI H11 with different pre-treatments. Coatings, 9(8), 519.
  • 3. Gök, M.S., Küçük, Y., Erdoğan, A., Öge, M., Kanca, E., Günen, A., 2017. Dry sliding wear behavior of borided hot-work tool steel at elevated temperatures. Surf Coat Technol, 328, 54-62.
  • 4. Podgornik, B., Puš, G., Žužek, B., Leskovšek, V., Godec, M., 2018. Heat treatment optimization and properties correlation for H11-type hot-work tool steel. Metallurgical and Materials Transactions A, 49(2), 455-462.
  • 5. Šebek, M., Falat, L., Kováč, F., Petryshynets, I., Horňak, P., Girman, V., 2017. The effects of laser surface hardening on microstructural characteristics and wear resistance of AISI H11 hot work tool steel. Archives of Metallurgy and Materials, 62(3), 1721-1726.
  • 6. Davis, J.R., 2001. Surface engineering for corrosion and wear resistance, ASM International.
  • 7. Günen, A., Kanca, Y., Karahan, İ.H., Karakaş, M.S., Gök, M.S., Kanca, E., Çürük, A., 2018. A comparative study on the effects of different thermochemical coating techniques on corrosion resistance of STKM-13A steel. Metallurgical and Materials Transactions A, 49(11), 5833-5847.
  • 8. Deng, J., Wu, F., Lian, Y., Xing, Y., Li, S., 2012. Erosion wear of CrN, TiN, CrAlN, and TiAlN PVD nitride coatings. Int J Refract Metals Hard Mater, 35, 10-16.
  • 9. Salem, M., Le Roux, S., Dour, G., Lamesle, P., Choquet, K., Rézaï-Aria, F., 2019. Effect of aluminizing and oxidation on the thermal fatigue damage of hot work tool steels for high pressure die casting applications. Int J Fatigue, 119, 126-138.
  • 10. Peng, D.Q., Bai, X.D., Sun, H., Chen, B.S., 2007. Effect of copper ions implantation on corrosion behavior of zirconium in 1M H2SO4. Int J Refract Metals Hard Mater, 25(1), 32-38.
  • 11. Picas, J.A., Forn, A., Baile, M.T., Martı́n, E., 2005. Substrate effect on the mechanical and tribological properties of arc plasma physical vapour deposition coatings. Int J Refract Metals Hard Mater, 23(4-6), 330-334.
  • 12. Azadi, M., Rouhaghdam, A.S., Ahangarani, S., Mofidi, H.H., 2014. Mechanical behavior of TiN/TiC multilayer coatings fabricated by plasma assisted chemical vapor deposition on AISI H13 hot work tool steel. Surf Coat Technol, 245, 156-166.
  • 13. Qiu, L., Du, Y., Wang, S., Li, K., Yin, L., Wu, L., Zhong, Z., Albir, L., 2019. Mechanical properties and oxidation resistance of chemically vapor deposited TiSiN nanocomposite coating with thermodynamically designed compositions. Int J Refract Metals Hard Mater, 80, 30-39.
  • 14. Çiçek, A., Kara, F., Kivak, T., Ekici, E., 2013. Evaluation of machinability of hardened and cryo-treated AISI H13 hot work tool steel with ceramic inserts. Int J Refract Metals Hard Mater, 41, 461-469.
  • 15. Altinsoy, I., Efe, F.G.C., Ipek, M., Ozbek, I., Zeytin, S., Bindal, C., 2013. An investigation on borided AISI 1020 steel. AIP Conf Proc, 1569(1), 43-46.
  • 16. Arslan, D., Uzun, R.O., 2021. Microwave boriding to improve the corrosion resistance of AISI 304L austenitic stainless steel. Iğdır Üniversitesi Fen Bilimleri Enstitüsü Dergisi, 11(1), 490-499.
  • 17. Gómez-Vargas, O.A., Solis-Romero, J., Figueroa-López, U., Ortiz-Domínguez, M., Oseguera-Peña, J., Neville, A., 2016. Boro-nitriding coating on pure iron by powder-pack boriding and nitriding processes. Mater Lett, 176, 261-264.
  • 18. Su, Z.G., Tian, X., An, J., Lu, Y., Yang, Y.L., Sun, S.J., 2009. Investigation on boronizing of N80 tube steel. ISIJ International, 49(11), 1776-1783.
  • 19. Gunes, I., Yıldız, I., 2016. Investigation of adhesion and tribological behavior of borided AISI 310 stainless steel. Matéria (Rio de Janeiro), 21(1), 61-71.
  • 20. Hernández-Sánchez, E., Velázquez, J.C., Castrejón-Flores, José. L., Chino-Ulloa, A., Avila, I.P.T., Carrera-Espinoza, R., Yescas-Hernández, J.A., Orozco-Alvarez, C., 2019. Tribological behavior of borided AISI 316L steel with reduced friction coefficient and enhanced wear resistance. Mater Trans, 60(1), 156-164.
  • 21. Kara, G., Purcek, G., Yanar, H., 2017. Improvement of wear behaviour of titanium by boriding. Industrial Lubrication and Tribology, 69(1), 65-70.
  • 22. Zuno-Silva, J., Ortiz-Domínguez, M., Simón-Marmolejo, I., Martínez-Martínez, L.E., Flores-Rentería, M.A., Arenas-Flores, A., Cruz-Avilés, A., 2018. The powder-pack boriding process: a microstructure comparison of boride layers formed on AISI 4150 and M2 steels. Microscopy and Microanalysis, 24(S1), 1064-1065.
  • 23. Bayça, S.U., Bican, O., 2022. Increasing corrosion resistance of AISI 1010 steel by boride coatings. Materials and Corrosion, 73(12), 2032-2040.
  • 24. Flores-Renteria, M.A., Ortiz-Dominguez, M., Simon-Marmolejo, I., Martinez-Martinez, L.E., Zuno-Silva, J., 2018. Microstructural characterization of nitro-boriding coating on ARMCO® pure iron. Microscopy and Microanalysis, 24(S1), 2240-2241.
  • 25. Medvedovski, E., Leal Mendoza, G., Vargas, G., 2021. Influence of boronizing on steel performance under erosion-abrasion-corrosion conditions simulating downhole oil production. Corrosion and Materials Degradation, 2(2), 293-324.
  • 26. Medvedovski, E., Leal Mendoza, G., Vargas, G., 2021. Influence of boronizing on steel performance under erosion-abrasion-corrosion conditions simulating downhole oil production. Corrosion and Materials Degradation, 2(2), 293-324.
  • 27. Gurgenc, T., Altay, O., Ulas, M., Ozel, C., 2020. Extreme learning machine and support vector regression wear loss predictions for magnesium alloys coated using various spray coating methods. J Appl Phys, 127(18).
  • 28. Pashkov, D.M., Belyak, O.A., Guda, A.A., Kolesnikov, V.I., 2022. Reverse engineering of mechanical and tribological properties of coatings: results of machine learning algorithms. Physical Mesomechanics, 25(4), 296-305.
  • 29. Paturi, U.M.R., Reddy, N.S., Cheruku, S., Narala, S.K.R., Cho, K.K., Reddy, M.M., 2021. Estimation of coating thickness in electrostatic spray deposition by machine learning and response surface methodology. Surf Coat Technol, 422, 127559.
  • 30. Kamnis, S., Sfikas, A.K., Gonzalez, S., 2022. Design of high entropy alloys for thermal spray processes using machine learning, ITSC 2022, 522-533.
  • 31. Jokar, M., Guo, X., Frankel, G.S., 2022. Machine learning approaches to model galvanic corrosion of coated al alloy systems. Corrosion, 78(12), 1176-1189.
  • 32. Kolesnikov, V.I., Pashkov, D.M., Belyak, O.A., Guda, A.A., Danilchenko, S.A., Manturov, D.S., Novikov, E.S., Kudryakov, O.V., Guda, S.A., Soldatov, A.V., Kolesnikov, I.V., 2023. Design of double layer protective coatings: finite element modeling and machine learning approximations. Acta Astronaut, 204, 869-877.
  • 33. Kariofillis, G.K., Kiourtsidis, G.E., Tsipas, D.N., 2006. Corrosion behavior of borided AISI H13 hot work steel. Surf Coat Technol, 201(1-2), 19-24.
  • 34. Kulka, M., 2019. Trends in thermochemical techniques of boriding. In Current Trends in Boriding, 17-98.
  • 35. Günen, A., 2020. Properties and high temperature dry sliding wear behavior of boronized inconel 718. Metallurgical and Materials Transactions A, 51(2), 927-939.
  • 36. Jiang, J., Wang, Y., Zhong, Q., Zhou, Q., Zhang, L., 2011. Preparation of Fe2B boride coating on low-carbon steel surfaces and its evaluation of hardness and corrosion resistance. Surf Coat Technol, 206(2-3), 473-478.
  • 37. Tavakoli, H., Mousavi Khoie, S.M., 2010. An electrochemical study of the corrosion resistance of boride coating obtained by thermo-reactive diffusion. Mater Chem Phys, 124(2-3), 1134-1138.
  • 38. Wang, H., Zhao, Y., Yuan, X., Chen, K., Xu, R., 2013. Effects of boronizing treatment on corrosion resistance of 65Mn steel in two acid mediums. Phys Procedia, 50, 124-130.
  • 39. Günen, A., 2020. Properties and corrosion resistance of borided AISI H11 tool steel. J Eng Mater Technol, 142(1), 011010.
  • 40. James, G., Witten, D., Hastie, T., Tibshirani, R., 2021. An introduction to statistical learning. Springer US, New York, NY.
  • 41. Müller, A.C., Guido, S., 2016. Introduction to machine learning with python: a guide for data scientists. O’Reilly Media.
  • 42. Géron, A., 2019. Hands-on machine learning with scikit-learn. Keras, and TensorFlow: Concepts, Tools, and Techniques to Build Intelligent Systems, O’Reilly Media.
  • 43. Breiman, L., 2001. Random forests. Mach Learn, 45(1), 5-32.
  • 44. Chen, T., Guestrin, C., 2016. XGBoost: a scalable tree boosting system. Proceedings of the 22nd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, ACM, New York, NY, USA, 785-794.
  • 45. Friedman, J.H., 2001. Greedy function approximation: a gradient boosting machine. The Annals of Statistics, 29(5), 1189-1232.
  • 46. Demirelli, E., Solak, H.İ., Tiryakioğlu, İ., 2023. Makine öğrenmesi algoritmaları ile deprem katalogları kullanılarak deprem tahmini. Gümüşhane Üniversitesi Fen Bilimleri Enstitüsü Dergisi, 13(4), 979-989.
  • 47. Kelle, A.C., Yüce, H., 2022. MQTT trafiğinde DoS saldırılarının makine öğrenmesi ile sınıflandırılması ve modelin SHAP ile yorumlanması. Journal of Materials and Mechatronics: A, 3(1), 50-62.
  • 48. Sharma, M., Ortlepp, I., Bleck, W., 2019. Boron in heat‐treatable steels: a review. Steel Res Int, 90(11), 1900133.
  • 49. Luitjohan, K.E., Krane, M.J.M., Ortalan, V., Johnson, D.R., 2018. Investigation of the metatectic reaction in iron-boron binary alloys. J Alloys Compd, 732, 498-505.
  • 50. Lucci, A., Venturello, G., 1971. Comments on the condition of boron in α-iron. Scripta Metallurgica, 5(1), 17-24.
  • 51. Hallemans, B., Wollants, P., Roos, J.R., 1994. Thermodynamic reassessment and calculation of the Fe-B phase diagram. International Journal of Materials Research, 85(10), 676-682.
  • 52. Busby, P.E., Warga, M.E., Wells, C., 1953. Diffusion and solubility of boron in iron and steel. JOM, 5(11), 1463-1468.
  • 53. Goldhoff, R.M., Spretnak, J.W., 1957. Distribution of boron in gamma iron grains. JOM, 9(10), 1278-1283.
  • 54. Nicholson, M.E., 1954. Constitution of iron-boron alloys in the low boron range. JOM, 6(2), 185-190.
  • 55. Strocchi, P.M., Melandri, B.A., Tamba, A., 1967. On the nature of boron solid solution in α-iron. Il Nuovo Cimento B Series 10, 51(1), 1-11.
  • 56. Lucci, A., Della Gatta, G., Venturello, G., 1969. On the solubility of boron in high-purity alpha-iron. Metal Science Journal, 3(1), 14-17.
  • 57. Başman, G., Arıkan, M.M., Arısoy, C., Şeşen, K., 2023. A kinetic study of thermochemically borided AISI 316l stainless steel. Journal of Scientific Reports-A, (052), 279-296.
  • 58. Gunes, I., Kanat, S., 2015. Diffusion kinetics and characterization of borided AISI D6 steel. Protection of Metals and Physical Chemistry of Surfaces, 51(5), 842-846.
  • 59. Turgut, S., Günen, A., 2020, Mechanical properties and corrosion resistance of borosintered distaloy steels. J Mater Eng Perform, 29(11), 6997-7010.
  • 60. Şahin, S., 2009. Effects of boronizing process on the surface roughness and dimensions of AISI 1020, AISI 1040 and AISI 2714. J Mater Process Technol, 209(4), 1736-1741.
  • 61. Li, C., Shen, B., Li, G., Yang, C., 2008. Effect of boronizing temperature and time on microstructure and abrasion wear resistance of Cr12Mn2V2 high chromium cast iron, Surf Coat Technol, 202(24), 5882-5886.
  • 62. Mathew, M., Rajendrakumar, P.K., 2014. Effect of precarburization on growth kinetics and mechanical properties of borided low-carbon steel. Materials and Manufacturing Processes, 29(9), 1073-1084.
  • 63. Bourithis, L., Papaefthymiou, S., Papadimitriou, G.D., 2002. Plasma transferred arc boriding of a low carbon steel: microstructure and wear properties. Appl Surf Sci, 200(1-4), 203-218.
  • 64. Kaouka, A., Alaoui, O., 2019. Characterization and corrosion resistance of boride layers on carbon steel. IOP Conf Ser Mater Sci Eng, 477, 012029.
  • 65. Kayalı, Y., Kul, M., Talaş, Ş., Yalçın, M.C., 2022. Investigation of corrosion and adhesion behaviors of boronized asp ® 2012 Steel. Surface Review and Letters, 29(12), 2250155.
  • 66. Alkan, S., Günen, A., Gülen, M., Gök, M.S., 2024. Effect of boriding on tribocorrosion behaviour of HSLA offshore mooring chain steel. Surf Coat Technol, 476, 130276.
  • 67. Campos, I., Palomar, M., Amador, A., Ganem, R., Martinez, J., 2006. Evaluation of the corrosion resistance of iron boride coatings obtained by paste boriding process. Surf Coat Technol, 201(6), 2438-2442.

Borlanmış AISI H11 Takım Çeliğinin Kaplama Özellikleri ve Korozyon Oranının Makine Öğrenmesi Temelli Modellenmesi

Yıl 2024, Cilt: 39 Sayı: 3, 625 - 638, 03.10.2024
https://doi.org/10.21605/cukurovaumfd.1560038

Öz

Yüksek sertlik, aşınma ve korozyon direncinde önemli ölçüde artışlar sağlaması nedeniyle borlama işlemi kullanılan en yaygın termokimyasal kaplama işlemlerinden birisidir. Bu çalışmada sıcak iş takım çeliklerinden AISI H11 malzemenin kutu borlama tekniğiyle borlanmasında işlem sıcaklığı ve süresinin kaplama kalınlığı, yüzey pürüzlülüğü, sertliği ve korozyon oranına etkisi makine öğrenmesi yöntemleriyle modellenmiş ve incelenmiştir. Çalışma kapsamında çoklu doğrusal, K en yakın komşu, destek vektör makinesi, karar ağacı, rastgele orman ve ekstrem eğim arttırma regresyon algoritmaları ile modeller oluşturulmuş ve bu modellerin performansları R2, ortalama mutlak hata ve ortalama kare hatası kriterleri kullanılarak kıyaslanmıştır. Kaplama tabakası kalınlık ve sertlikleri işlem sıcaklığı ve süresi ile artmaktadır. Diğer yandan bu özellikleri üzerinde borlama sıcaklığı süreye göre daha etkilidir. Regresyon modeli sonuçları incelendiğinde kaplama parametrelerinin kaplama kalınlığına ve pürüzlülüğe olan etkilerinin birleşerek korozyon oranı üzerinde kümülatif bir etkiye dönüştüğü görülmüştür. Çalışma sonucunda AISI H11 çeliğinin borlanmasında korozyon direnci için optimum parametre değerlerinin 1000 °C ve 2,2 saat olduğu sonucuna varılmıştır.

Kaynakça

  • 1. Ma, L., Luo, Y., Wang, Y., Du, W., Song, Z., Zhang, J., 2018. Fatigue and ratcheting assessment of AISI H11 at 500°C using constitutive theory coupled with damage rule. Fatigue Fract Eng Mater Struct, 41(3), 642-652.
  • 2. Tillmann, W., Grisales, D., Stangier, D., Butzke, T., 2019. Tribomechanical behaviour of TiAlN and CrAlN coatings deposited onto AISI H11 with different pre-treatments. Coatings, 9(8), 519.
  • 3. Gök, M.S., Küçük, Y., Erdoğan, A., Öge, M., Kanca, E., Günen, A., 2017. Dry sliding wear behavior of borided hot-work tool steel at elevated temperatures. Surf Coat Technol, 328, 54-62.
  • 4. Podgornik, B., Puš, G., Žužek, B., Leskovšek, V., Godec, M., 2018. Heat treatment optimization and properties correlation for H11-type hot-work tool steel. Metallurgical and Materials Transactions A, 49(2), 455-462.
  • 5. Šebek, M., Falat, L., Kováč, F., Petryshynets, I., Horňak, P., Girman, V., 2017. The effects of laser surface hardening on microstructural characteristics and wear resistance of AISI H11 hot work tool steel. Archives of Metallurgy and Materials, 62(3), 1721-1726.
  • 6. Davis, J.R., 2001. Surface engineering for corrosion and wear resistance, ASM International.
  • 7. Günen, A., Kanca, Y., Karahan, İ.H., Karakaş, M.S., Gök, M.S., Kanca, E., Çürük, A., 2018. A comparative study on the effects of different thermochemical coating techniques on corrosion resistance of STKM-13A steel. Metallurgical and Materials Transactions A, 49(11), 5833-5847.
  • 8. Deng, J., Wu, F., Lian, Y., Xing, Y., Li, S., 2012. Erosion wear of CrN, TiN, CrAlN, and TiAlN PVD nitride coatings. Int J Refract Metals Hard Mater, 35, 10-16.
  • 9. Salem, M., Le Roux, S., Dour, G., Lamesle, P., Choquet, K., Rézaï-Aria, F., 2019. Effect of aluminizing and oxidation on the thermal fatigue damage of hot work tool steels for high pressure die casting applications. Int J Fatigue, 119, 126-138.
  • 10. Peng, D.Q., Bai, X.D., Sun, H., Chen, B.S., 2007. Effect of copper ions implantation on corrosion behavior of zirconium in 1M H2SO4. Int J Refract Metals Hard Mater, 25(1), 32-38.
  • 11. Picas, J.A., Forn, A., Baile, M.T., Martı́n, E., 2005. Substrate effect on the mechanical and tribological properties of arc plasma physical vapour deposition coatings. Int J Refract Metals Hard Mater, 23(4-6), 330-334.
  • 12. Azadi, M., Rouhaghdam, A.S., Ahangarani, S., Mofidi, H.H., 2014. Mechanical behavior of TiN/TiC multilayer coatings fabricated by plasma assisted chemical vapor deposition on AISI H13 hot work tool steel. Surf Coat Technol, 245, 156-166.
  • 13. Qiu, L., Du, Y., Wang, S., Li, K., Yin, L., Wu, L., Zhong, Z., Albir, L., 2019. Mechanical properties and oxidation resistance of chemically vapor deposited TiSiN nanocomposite coating with thermodynamically designed compositions. Int J Refract Metals Hard Mater, 80, 30-39.
  • 14. Çiçek, A., Kara, F., Kivak, T., Ekici, E., 2013. Evaluation of machinability of hardened and cryo-treated AISI H13 hot work tool steel with ceramic inserts. Int J Refract Metals Hard Mater, 41, 461-469.
  • 15. Altinsoy, I., Efe, F.G.C., Ipek, M., Ozbek, I., Zeytin, S., Bindal, C., 2013. An investigation on borided AISI 1020 steel. AIP Conf Proc, 1569(1), 43-46.
  • 16. Arslan, D., Uzun, R.O., 2021. Microwave boriding to improve the corrosion resistance of AISI 304L austenitic stainless steel. Iğdır Üniversitesi Fen Bilimleri Enstitüsü Dergisi, 11(1), 490-499.
  • 17. Gómez-Vargas, O.A., Solis-Romero, J., Figueroa-López, U., Ortiz-Domínguez, M., Oseguera-Peña, J., Neville, A., 2016. Boro-nitriding coating on pure iron by powder-pack boriding and nitriding processes. Mater Lett, 176, 261-264.
  • 18. Su, Z.G., Tian, X., An, J., Lu, Y., Yang, Y.L., Sun, S.J., 2009. Investigation on boronizing of N80 tube steel. ISIJ International, 49(11), 1776-1783.
  • 19. Gunes, I., Yıldız, I., 2016. Investigation of adhesion and tribological behavior of borided AISI 310 stainless steel. Matéria (Rio de Janeiro), 21(1), 61-71.
  • 20. Hernández-Sánchez, E., Velázquez, J.C., Castrejón-Flores, José. L., Chino-Ulloa, A., Avila, I.P.T., Carrera-Espinoza, R., Yescas-Hernández, J.A., Orozco-Alvarez, C., 2019. Tribological behavior of borided AISI 316L steel with reduced friction coefficient and enhanced wear resistance. Mater Trans, 60(1), 156-164.
  • 21. Kara, G., Purcek, G., Yanar, H., 2017. Improvement of wear behaviour of titanium by boriding. Industrial Lubrication and Tribology, 69(1), 65-70.
  • 22. Zuno-Silva, J., Ortiz-Domínguez, M., Simón-Marmolejo, I., Martínez-Martínez, L.E., Flores-Rentería, M.A., Arenas-Flores, A., Cruz-Avilés, A., 2018. The powder-pack boriding process: a microstructure comparison of boride layers formed on AISI 4150 and M2 steels. Microscopy and Microanalysis, 24(S1), 1064-1065.
  • 23. Bayça, S.U., Bican, O., 2022. Increasing corrosion resistance of AISI 1010 steel by boride coatings. Materials and Corrosion, 73(12), 2032-2040.
  • 24. Flores-Renteria, M.A., Ortiz-Dominguez, M., Simon-Marmolejo, I., Martinez-Martinez, L.E., Zuno-Silva, J., 2018. Microstructural characterization of nitro-boriding coating on ARMCO® pure iron. Microscopy and Microanalysis, 24(S1), 2240-2241.
  • 25. Medvedovski, E., Leal Mendoza, G., Vargas, G., 2021. Influence of boronizing on steel performance under erosion-abrasion-corrosion conditions simulating downhole oil production. Corrosion and Materials Degradation, 2(2), 293-324.
  • 26. Medvedovski, E., Leal Mendoza, G., Vargas, G., 2021. Influence of boronizing on steel performance under erosion-abrasion-corrosion conditions simulating downhole oil production. Corrosion and Materials Degradation, 2(2), 293-324.
  • 27. Gurgenc, T., Altay, O., Ulas, M., Ozel, C., 2020. Extreme learning machine and support vector regression wear loss predictions for magnesium alloys coated using various spray coating methods. J Appl Phys, 127(18).
  • 28. Pashkov, D.M., Belyak, O.A., Guda, A.A., Kolesnikov, V.I., 2022. Reverse engineering of mechanical and tribological properties of coatings: results of machine learning algorithms. Physical Mesomechanics, 25(4), 296-305.
  • 29. Paturi, U.M.R., Reddy, N.S., Cheruku, S., Narala, S.K.R., Cho, K.K., Reddy, M.M., 2021. Estimation of coating thickness in electrostatic spray deposition by machine learning and response surface methodology. Surf Coat Technol, 422, 127559.
  • 30. Kamnis, S., Sfikas, A.K., Gonzalez, S., 2022. Design of high entropy alloys for thermal spray processes using machine learning, ITSC 2022, 522-533.
  • 31. Jokar, M., Guo, X., Frankel, G.S., 2022. Machine learning approaches to model galvanic corrosion of coated al alloy systems. Corrosion, 78(12), 1176-1189.
  • 32. Kolesnikov, V.I., Pashkov, D.M., Belyak, O.A., Guda, A.A., Danilchenko, S.A., Manturov, D.S., Novikov, E.S., Kudryakov, O.V., Guda, S.A., Soldatov, A.V., Kolesnikov, I.V., 2023. Design of double layer protective coatings: finite element modeling and machine learning approximations. Acta Astronaut, 204, 869-877.
  • 33. Kariofillis, G.K., Kiourtsidis, G.E., Tsipas, D.N., 2006. Corrosion behavior of borided AISI H13 hot work steel. Surf Coat Technol, 201(1-2), 19-24.
  • 34. Kulka, M., 2019. Trends in thermochemical techniques of boriding. In Current Trends in Boriding, 17-98.
  • 35. Günen, A., 2020. Properties and high temperature dry sliding wear behavior of boronized inconel 718. Metallurgical and Materials Transactions A, 51(2), 927-939.
  • 36. Jiang, J., Wang, Y., Zhong, Q., Zhou, Q., Zhang, L., 2011. Preparation of Fe2B boride coating on low-carbon steel surfaces and its evaluation of hardness and corrosion resistance. Surf Coat Technol, 206(2-3), 473-478.
  • 37. Tavakoli, H., Mousavi Khoie, S.M., 2010. An electrochemical study of the corrosion resistance of boride coating obtained by thermo-reactive diffusion. Mater Chem Phys, 124(2-3), 1134-1138.
  • 38. Wang, H., Zhao, Y., Yuan, X., Chen, K., Xu, R., 2013. Effects of boronizing treatment on corrosion resistance of 65Mn steel in two acid mediums. Phys Procedia, 50, 124-130.
  • 39. Günen, A., 2020. Properties and corrosion resistance of borided AISI H11 tool steel. J Eng Mater Technol, 142(1), 011010.
  • 40. James, G., Witten, D., Hastie, T., Tibshirani, R., 2021. An introduction to statistical learning. Springer US, New York, NY.
  • 41. Müller, A.C., Guido, S., 2016. Introduction to machine learning with python: a guide for data scientists. O’Reilly Media.
  • 42. Géron, A., 2019. Hands-on machine learning with scikit-learn. Keras, and TensorFlow: Concepts, Tools, and Techniques to Build Intelligent Systems, O’Reilly Media.
  • 43. Breiman, L., 2001. Random forests. Mach Learn, 45(1), 5-32.
  • 44. Chen, T., Guestrin, C., 2016. XGBoost: a scalable tree boosting system. Proceedings of the 22nd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, ACM, New York, NY, USA, 785-794.
  • 45. Friedman, J.H., 2001. Greedy function approximation: a gradient boosting machine. The Annals of Statistics, 29(5), 1189-1232.
  • 46. Demirelli, E., Solak, H.İ., Tiryakioğlu, İ., 2023. Makine öğrenmesi algoritmaları ile deprem katalogları kullanılarak deprem tahmini. Gümüşhane Üniversitesi Fen Bilimleri Enstitüsü Dergisi, 13(4), 979-989.
  • 47. Kelle, A.C., Yüce, H., 2022. MQTT trafiğinde DoS saldırılarının makine öğrenmesi ile sınıflandırılması ve modelin SHAP ile yorumlanması. Journal of Materials and Mechatronics: A, 3(1), 50-62.
  • 48. Sharma, M., Ortlepp, I., Bleck, W., 2019. Boron in heat‐treatable steels: a review. Steel Res Int, 90(11), 1900133.
  • 49. Luitjohan, K.E., Krane, M.J.M., Ortalan, V., Johnson, D.R., 2018. Investigation of the metatectic reaction in iron-boron binary alloys. J Alloys Compd, 732, 498-505.
  • 50. Lucci, A., Venturello, G., 1971. Comments on the condition of boron in α-iron. Scripta Metallurgica, 5(1), 17-24.
  • 51. Hallemans, B., Wollants, P., Roos, J.R., 1994. Thermodynamic reassessment and calculation of the Fe-B phase diagram. International Journal of Materials Research, 85(10), 676-682.
  • 52. Busby, P.E., Warga, M.E., Wells, C., 1953. Diffusion and solubility of boron in iron and steel. JOM, 5(11), 1463-1468.
  • 53. Goldhoff, R.M., Spretnak, J.W., 1957. Distribution of boron in gamma iron grains. JOM, 9(10), 1278-1283.
  • 54. Nicholson, M.E., 1954. Constitution of iron-boron alloys in the low boron range. JOM, 6(2), 185-190.
  • 55. Strocchi, P.M., Melandri, B.A., Tamba, A., 1967. On the nature of boron solid solution in α-iron. Il Nuovo Cimento B Series 10, 51(1), 1-11.
  • 56. Lucci, A., Della Gatta, G., Venturello, G., 1969. On the solubility of boron in high-purity alpha-iron. Metal Science Journal, 3(1), 14-17.
  • 57. Başman, G., Arıkan, M.M., Arısoy, C., Şeşen, K., 2023. A kinetic study of thermochemically borided AISI 316l stainless steel. Journal of Scientific Reports-A, (052), 279-296.
  • 58. Gunes, I., Kanat, S., 2015. Diffusion kinetics and characterization of borided AISI D6 steel. Protection of Metals and Physical Chemistry of Surfaces, 51(5), 842-846.
  • 59. Turgut, S., Günen, A., 2020, Mechanical properties and corrosion resistance of borosintered distaloy steels. J Mater Eng Perform, 29(11), 6997-7010.
  • 60. Şahin, S., 2009. Effects of boronizing process on the surface roughness and dimensions of AISI 1020, AISI 1040 and AISI 2714. J Mater Process Technol, 209(4), 1736-1741.
  • 61. Li, C., Shen, B., Li, G., Yang, C., 2008. Effect of boronizing temperature and time on microstructure and abrasion wear resistance of Cr12Mn2V2 high chromium cast iron, Surf Coat Technol, 202(24), 5882-5886.
  • 62. Mathew, M., Rajendrakumar, P.K., 2014. Effect of precarburization on growth kinetics and mechanical properties of borided low-carbon steel. Materials and Manufacturing Processes, 29(9), 1073-1084.
  • 63. Bourithis, L., Papaefthymiou, S., Papadimitriou, G.D., 2002. Plasma transferred arc boriding of a low carbon steel: microstructure and wear properties. Appl Surf Sci, 200(1-4), 203-218.
  • 64. Kaouka, A., Alaoui, O., 2019. Characterization and corrosion resistance of boride layers on carbon steel. IOP Conf Ser Mater Sci Eng, 477, 012029.
  • 65. Kayalı, Y., Kul, M., Talaş, Ş., Yalçın, M.C., 2022. Investigation of corrosion and adhesion behaviors of boronized asp ® 2012 Steel. Surface Review and Letters, 29(12), 2250155.
  • 66. Alkan, S., Günen, A., Gülen, M., Gök, M.S., 2024. Effect of boriding on tribocorrosion behaviour of HSLA offshore mooring chain steel. Surf Coat Technol, 476, 130276.
  • 67. Campos, I., Palomar, M., Amador, A., Ganem, R., Martinez, J., 2006. Evaluation of the corrosion resistance of iron boride coatings obtained by paste boriding process. Surf Coat Technol, 201(6), 2438-2442.
Toplam 67 adet kaynakça vardır.

Ayrıntılar

Birincil Dil Türkçe
Konular Makine Mühendisliği (Diğer)
Bölüm Makaleler
Yazarlar

Faruk Çavdar 0000-0002-4981-6428

Ali Günen 0000-0002-4101-9520

Mustafa Sert 0009-0003-6536-354X

Yayımlanma Tarihi 3 Ekim 2024
Gönderilme Tarihi 19 Ocak 2024
Kabul Tarihi 27 Eylül 2024
Yayımlandığı Sayı Yıl 2024 Cilt: 39 Sayı: 3

Kaynak Göster

APA Çavdar, F., Günen, A., & Sert, M. (2024). Borlanmış AISI H11 Takım Çeliğinin Kaplama Özellikleri ve Korozyon Oranının Makine Öğrenmesi Temelli Modellenmesi. Çukurova Üniversitesi Mühendislik Fakültesi Dergisi, 39(3), 625-638. https://doi.org/10.21605/cukurovaumfd.1560038