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OPTIMIZATION of ATMOSPHERIC PLASMA SPRAY PROCESS PARAMETERS for DEPOSITION of THERMAL BARRIER COATINGS

Year 2022, Issue: 049, 184 - 197, 30.06.2022

Abstract

In the production of thermal barrier coating (TBC) with the atmospheric plasma spray coating system, the process parameters directly affect the production cost and performance of the coatings. In this study, a comprehensive modeling-design-optimization study was conducted to improve the analytical performance of TBC. For this purpose, the data were taken from a literature study that included an extensive experimental design application. The modeling study prepared first, second, and third-order polynomial, trigonometric, and logarithmic-based models for each process output. Model selections were made with neuro-regression and a statistical method. The selected models were run on four different stochastic optimization algorithms for the coatings' deposition efficiency, bond strength, porosity, and hardness value outputs. Thirty-six neuro-regression models prepared in the modeling study have high R2training values. The second-order logarithmic nonlinear (SOLN) models were successful in the coatings' deposition efficiency and bond strength, and the polynomial nonlinear models were successful for the four process outputs. Therefore, they were chosen as the objective functions of the optimization algorithms. In addition, the selected models were run at the parameters determined by numerical optimization in the reference publication, and the prediction abilities of the models in the two studies were compared. SOLN models for deposition efficiency and bond strength values, second-order nonlinear model for hardness value, and reference study’ model predicted more closely to the validation test result for porosity values of coating. In the optimization studies, three or more algorithms suggested the same results with the same parameter sets for the deposition efficiency and hardness values. The optimization results show that these points can be a global optimum point for optimizing these two coating properties.

Thanks

The author thanks reviewers for constructive comments and suggestions that helped to improve the quality of the article.

References

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  • [2] Darolia, R., (2013), Thermal barrier coatings technology: critical review, progress update, remaining challenges and prospects, International Materials Reviews, 58(6), 315-348.
  • [3] Mutasim, Z. and Brentnall, W, (1997), Thermal barrier coatings for industrial gas turbine applications: An industrial note, Journal of Thermal Spray Technology, 6(1), 105-108.
  • [4] Lin, C.M., Yen, S.H. and Su, C.Y., (2016), Measurement and optimization of atmospheric plasma sprayed CoMoCrSi coatings parameters on Ti-6Al-4V substrates affecting microstructural and properties using hybrid abductor induction mechanism, Measurement, 94, 157-167.
  • [5] Guo, H., Gong, S., Khor, K.A. and Xu, H., (2003), Effect of thermal exposure on the microstructure and properties of EB-PVD gradient thermal barrier coatings, Surface and Coatings Technology, 168(1), 23-29.
  • [6] Liu, Q., Huang, S. and He, A., (2019), Composite ceramics thermal barrier coatings of yttria stabilized zirconia for aero-engines, Journal of Materials Science And Technology, 35(12), 2814-2823.
  • [7] Matejka, D. and Benko, B., (1989), Plasma spraying of metallic and ceramic materials, John Wiley and Sons.
  • [8] Chen, H., Hao, Y., Wang, H. and Tang, W., (2010), Analysis of the microstructure and thermal shock resistance of laser glazed nanostructured zirconia TBCs, Journal of Thermal Spray Technology, 19(3), 558-565.
  • [9] Bertrand, G., Bertrand, P., Roy, P., Rio, C. and Mevrel, R., (2008), Low conductivity plasma sprayed thermal barrier coating using hollow psz spheres: Correlation between thermophysical properties and microstructure, Surface and Coatings Technology, 202(10), 1994-2001.
  • [10] Ning, L., Cai, Z., Zhao, X., Liu, Y. and Wang, W., (2021), Fast stress evaluation of the top coat of thermal barrier coatings under CaO–MgO–Al2O3–SiO2 penetration based on image recognition and an artificial neural network, Ceramics International, 47(13), 18252-18261.
  • [11] Ramachandran, C., Balasubramanian, V. and Ananthapadmanabhan, P., (2011), Multiobjective optimization of atmospheric plasma spray process parameters to deposit yttria-stabilized zirconia coatings using response surface methodology, Journal of Thermal Spray Technology, 20(3), 590-607.
  • [12] Kim, K., Kim, D., Park, K., Yun, J., Jun, N. and Seok, C.S., (2021), A cumulative oxide growth model considering the deterioration history of thermal barrier coatings, Corrosion Science, 182, 1-8.
  • [13] Karthikeyan, S., Balasubramanian, V. and Rajendran, R., (2014), Developing empirical relationships to estimate porosity and microhardness of plasma-sprayed YSZ coatings, Ceramics International, 40(2), 3171-3183.
  • [14] Rajesh, T.S. and Rao, R.V., (2016), Parameter Optimization of Amalgamated Al2O3-40%TiO2 Atmospheric Plasma Spray Coating on SS304 Substrate Using TLBO Algorithm, Journal of Surface Engineered Materials and Advanced Technology, 6(03), 89-105.
  • [15] Shi, H., Zhao, C. and Wang, B., (2016), Modeling the thermal radiation properties of thermal barrier coatings based on a random generation algorithm, Ceramics International, 42(8), 9752-9761.
  • [16] Sankar, V., Thampi, B.G. and Panicker, M.R., (2020), Optimization of thermal barrier coatings in a single cylinder diesel engine using thermal analysis and genetic algorithm, Journal of Physics: Conference Series, IOP Publishing.
  • [17] Tonkonogyi, V., Dasic, P., Rybak, O. and Lysenko, T., (2019), Application of the modified genetic algorithm for optimization of plasma coatings grinding process, International Conference New Technologies, Development and Applications, Springer.
  • [18] Ye, D., Wang, W., Xu, Z., Yin, C., Zhou, H. and Li, Y., (2020), Prediction of thermal barrier coatings microstructural features based on support vector machine optimized by cuckoo search algorithm, Coatings, 10(7), 1-13.
  • [19] Aydin, L., Artem H.S. and Oterkus, S., (2020), Designing engineering structures using stochastic optimization methods, CRC Press, Taylor & Francis Group.
  • [20] Ozturk, S., Aydin, L. and Celik, E., (2018), A comprehensive study on slicing processes optimization of silicon ingot for photovoltaic applications, Solar Energy, 161, 109-124.
  • [21] Ozturk, S., Aydin, L., Kucukdogan, N., and Celik, E, (2018), Optimization of lapping processes of silicon wafer for photovoltaic applications, Solar Energy, 164, 1-11.
Year 2022, Issue: 049, 184 - 197, 30.06.2022

Abstract

References

  • [1] Boyce, M.P., (2011), Gas turbine engineering handbook, Elsevier.
  • [2] Darolia, R., (2013), Thermal barrier coatings technology: critical review, progress update, remaining challenges and prospects, International Materials Reviews, 58(6), 315-348.
  • [3] Mutasim, Z. and Brentnall, W, (1997), Thermal barrier coatings for industrial gas turbine applications: An industrial note, Journal of Thermal Spray Technology, 6(1), 105-108.
  • [4] Lin, C.M., Yen, S.H. and Su, C.Y., (2016), Measurement and optimization of atmospheric plasma sprayed CoMoCrSi coatings parameters on Ti-6Al-4V substrates affecting microstructural and properties using hybrid abductor induction mechanism, Measurement, 94, 157-167.
  • [5] Guo, H., Gong, S., Khor, K.A. and Xu, H., (2003), Effect of thermal exposure on the microstructure and properties of EB-PVD gradient thermal barrier coatings, Surface and Coatings Technology, 168(1), 23-29.
  • [6] Liu, Q., Huang, S. and He, A., (2019), Composite ceramics thermal barrier coatings of yttria stabilized zirconia for aero-engines, Journal of Materials Science And Technology, 35(12), 2814-2823.
  • [7] Matejka, D. and Benko, B., (1989), Plasma spraying of metallic and ceramic materials, John Wiley and Sons.
  • [8] Chen, H., Hao, Y., Wang, H. and Tang, W., (2010), Analysis of the microstructure and thermal shock resistance of laser glazed nanostructured zirconia TBCs, Journal of Thermal Spray Technology, 19(3), 558-565.
  • [9] Bertrand, G., Bertrand, P., Roy, P., Rio, C. and Mevrel, R., (2008), Low conductivity plasma sprayed thermal barrier coating using hollow psz spheres: Correlation between thermophysical properties and microstructure, Surface and Coatings Technology, 202(10), 1994-2001.
  • [10] Ning, L., Cai, Z., Zhao, X., Liu, Y. and Wang, W., (2021), Fast stress evaluation of the top coat of thermal barrier coatings under CaO–MgO–Al2O3–SiO2 penetration based on image recognition and an artificial neural network, Ceramics International, 47(13), 18252-18261.
  • [11] Ramachandran, C., Balasubramanian, V. and Ananthapadmanabhan, P., (2011), Multiobjective optimization of atmospheric plasma spray process parameters to deposit yttria-stabilized zirconia coatings using response surface methodology, Journal of Thermal Spray Technology, 20(3), 590-607.
  • [12] Kim, K., Kim, D., Park, K., Yun, J., Jun, N. and Seok, C.S., (2021), A cumulative oxide growth model considering the deterioration history of thermal barrier coatings, Corrosion Science, 182, 1-8.
  • [13] Karthikeyan, S., Balasubramanian, V. and Rajendran, R., (2014), Developing empirical relationships to estimate porosity and microhardness of plasma-sprayed YSZ coatings, Ceramics International, 40(2), 3171-3183.
  • [14] Rajesh, T.S. and Rao, R.V., (2016), Parameter Optimization of Amalgamated Al2O3-40%TiO2 Atmospheric Plasma Spray Coating on SS304 Substrate Using TLBO Algorithm, Journal of Surface Engineered Materials and Advanced Technology, 6(03), 89-105.
  • [15] Shi, H., Zhao, C. and Wang, B., (2016), Modeling the thermal radiation properties of thermal barrier coatings based on a random generation algorithm, Ceramics International, 42(8), 9752-9761.
  • [16] Sankar, V., Thampi, B.G. and Panicker, M.R., (2020), Optimization of thermal barrier coatings in a single cylinder diesel engine using thermal analysis and genetic algorithm, Journal of Physics: Conference Series, IOP Publishing.
  • [17] Tonkonogyi, V., Dasic, P., Rybak, O. and Lysenko, T., (2019), Application of the modified genetic algorithm for optimization of plasma coatings grinding process, International Conference New Technologies, Development and Applications, Springer.
  • [18] Ye, D., Wang, W., Xu, Z., Yin, C., Zhou, H. and Li, Y., (2020), Prediction of thermal barrier coatings microstructural features based on support vector machine optimized by cuckoo search algorithm, Coatings, 10(7), 1-13.
  • [19] Aydin, L., Artem H.S. and Oterkus, S., (2020), Designing engineering structures using stochastic optimization methods, CRC Press, Taylor & Francis Group.
  • [20] Ozturk, S., Aydin, L. and Celik, E., (2018), A comprehensive study on slicing processes optimization of silicon ingot for photovoltaic applications, Solar Energy, 161, 109-124.
  • [21] Ozturk, S., Aydin, L., Kucukdogan, N., and Celik, E, (2018), Optimization of lapping processes of silicon wafer for photovoltaic applications, Solar Energy, 164, 1-11.
There are 21 citations in total.

Details

Primary Language English
Subjects Engineering
Journal Section Research Articles
Authors

Savaş Öztürk 0000-0003-2661-4556

Publication Date June 30, 2022
Submission Date March 9, 2022
Published in Issue Year 2022 Issue: 049

Cite

IEEE S. Öztürk, “OPTIMIZATION of ATMOSPHERIC PLASMA SPRAY PROCESS PARAMETERS for DEPOSITION of THERMAL BARRIER COATINGS”, JSR-A, no. 049, pp. 184–197, June 2022.