Analysis on suitability of HVOF sprayed Ni-20Al, Ni-20Cr and Al-20Ti coatings in coal-ash slurry conditions using artificial neural network model
Industrial Lubrication and Tribology
ISSN: 0036-8792
Article publication date: 8 July 2019
Issue publication date: 12 September 2019
Abstract
Purpose
The purpose of this study is to analyze the slurry erosion failure of Ni-20Cr (Ni-Cr2O3), Ni-20Al (Ni-Al2O3) and Al-20Ti (Al2O3-TiO2) coatings deposited on SS316L by the high-velocity oxy-fuel process.
Design/methodology/approach
Slurry erosion experiments were conducted using a pot type erosion tester at different velocities 1.81, 2.71, 3.61 and 4.59 m/s for the time duration of 90-180 minutes. Fly ash and bottom ash were used as erodent media; the concentration of mass flux was taken as 30-60 wt. per cent. Artificial neural network (ANN) method was used to simulate the slurry erosion for thermally sprayed coatings.
Findings
Slurry erosion of coatings increases non-linearly with an increase in experimental durations, mass flux and velocity. Slurry erosion of Ni-20Cr and Ni-20Al layers was found to be maximum at 60° impingement angle, whereas 30° for SS316L and 45° for Al-20Ti coating. Slurry erosion performance of SS316L was improved by 2.56-3.19 times by depositing Ni-20Cr and Ni-20Al layers, whereas it improved 1.15-1.75 times by Al-20Ti coating. The slurry erosion SS316L was found almost 1.35 ± 1.28 times greater than that of the Ni-20Al coating, whereas it was to be 1.12 ± 1.36 times greater than Al-20Ti. Ni-20Al-coated SS316L showed a lower value of slurry erosion than Al-20Ti-coated SS316L.
Practical implications
Stainless Steel SS316L is widely used in hydraulic machinery (such as turbines, pumps, valves, fittings, etc.) of hydraulic and thermal power plants, chemical industry and marine industry. Therefore, the deposition of ductile and brittle coatings is a better option for their durable performance.
Originality/value
Erosion wear of Ni-20Cr, Ni-20Al and Al-20Ti coatings was successfully simulated by using an artificial neural network model by supplying experimental data as a target.
Keywords
Acknowledgements
The author wants to acknowledge Dr Satish Kumar (Department of Mechanical Engineering, National Institute of Technology, Jamshedpur, India) and Professor S. K. Mohapatra (Mechanical Engineering Department, Thapar Institute of Engineering and Technology, Patiala, India) for the supervision during PhD thesis. The author would also like to confirm that this work is an extension of his PhD work. The ANN model was developed separately for the prediction of slurry erosion data.
Citation
Singh, J. (2019), "Analysis on suitability of HVOF sprayed Ni-20Al, Ni-20Cr and Al-20Ti coatings in coal-ash slurry conditions using artificial neural network model", Industrial Lubrication and Tribology, Vol. 71 No. 7, pp. 972-982. https://doi.org/10.1108/ILT-12-2018-0460
Publisher
:Emerald Publishing Limited
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