Skip to content
2000
Volume 18, Issue 3
  • ISSN: 2212-7976
  • E-ISSN: 1874-477X

Abstract

Background

Artificial intelligence techniques are able to predict the erosion in various coatings. In recent times, the erosion of the coating was successfully predicted using artificial neural networks (ANN).

Aim

This patent aims to present the critical findings in the area of spray coatings used for the protection of hydroturbines. This critical review explores the surface erosion of numerous hydroturbine materials and coatings. Moreover, it covers the evolution of coating techniques used in different industries such as hydropower plants and materials handling industry.

Objective

The objective of this patent is to present the critical finding in the field of erosion wear in coatings utilizing an artificial neural networks (ANN) technique.

Methods

The effect of influencing factors on silt erosion was assessed. However, the evolution of various coating processes was explored comprehensively. Furthermore, the properties of various coatings, namely WC, CrC, and Ni/Co coatings, were reported. A number of comparative analyses were carried out that can help in the selection of coatings on the basis of their mechanical as well as chemical properties. The applications of ANN in the spray industry were explained extensively.

Results

The results show that the HVOF coating is the most widely used deposition method. HVOF is an appropriate technique for both ceramics and pure metals. Ceramics, as well as cermet, are deposited to enhance the wear and tear resistance of hydroturbine materials. As a result, the HVOF, laser cladding, D-Gun, and plasma spray technique are optimal in these circumstances. Coatings based on WC have been employed by several researchers to increase stainless steels' resistance to erosion and wear.

Conclusion

With the application of appropriate models and ML methods, it is expected that coatings with specific desired properties can be manufactured with fewer experiments. There is no surprise that WC-10Co-4Cr finds widespread usage in a variety of industrial contexts. Ni- and Co-based coatings show promise for use in tribological settings. Stellite is suggested by several researchers for high-erosion duty conditions in hydroturbines. Co-based coatings are more erosion resistant as compared to No-based coatings. Coatings formulated with chromium (Cr) are resistant to erosion and wear in harsh mining environments.

© 2025 Bentham Science Publishers
Loading

Article metrics loading...

/content/journals/meng/10.2174/0122127976316837240607054956
2025-06-01
2025-10-05

  • From This Site

    /content/journals/meng/10.2174/0122127976316837240607054956
    dcterms_title,dcterms_subject,pub_keyword
    -contentType:Contributor -contentType:Concept -contentType:Institution
    10
    5
Loading full text...

Full text loading...

References

  1. PrasharG. VasudevH. ThakurL. Performance of different coating materials against slurry erosion failure in hydrodynamic turbines: A review.Eng. Fail. Anal.202011510462210.1016/j.engfailanal.2020.104622
     [Google Scholar]
  2. SinghJ. A review on mechanisms and testing of wear in slurry pumps, pipeline circuits and hydraulic turbines.J. Tribol.2021143909080110.1115/1.4050977
     [Google Scholar]
  3. SinghJ. Application of Thermal spray coatings for protection against erosion, abrasion, and corrosion in hydropower plants and offshore industry. Therm Spray Coatings.1st edBoca RatonCRC Press202124328310.1201/9781003213185‑10
     [Google Scholar]
  4. AwalR. SapkotaP. ChitrakarS. ThapaB.S. NeopaneH.P. ThapaB. A general review on methods of sediment sampling and mineral content analysis.J. Phys. Conf. Ser.20191266101200510.1088/1742‑6596/1266/1/012005
     [Google Scholar]
  5. PadhyM.K. SainiR.P. Effect of size and concentration of silt particles on erosion of Pelton turbine buckets.Energy200934101477148310.1016/j.energy.2009.06.015
     [Google Scholar]
  6. ChitrakarS. DahlhaugO.G. NeopaneH.P. Numerical investigation of the effect of leakage flow through erosion-induced clearance gaps of guide vanes on the performance of Francis turbines.Eng. Appl. Comput. Fluid Mech.201812166267810.1080/19942060.2018.1509806
     [Google Scholar]
  7. KapaliA. ChitrakarS. ShresthaO. NeopaneH.P. ThapaB.S. A review on experimental study of sediment erosion in hydraulic turbines at laboratory conditions.J. Phys. Conf. Ser.20191266101201610.1088/1742‑6596/1266/1/012016
     [Google Scholar]
  8. SangroulaD.P. Hydropower development and its sustainability with respect to sedimentation in Nepal.J Ins Eng197071566410.3126/jie.v7i1.2063
     [Google Scholar]
  9. SwarnakarN.K. RaoV.S. TripathiS. Innovative use of technology to curb the menace of silt erosion in hydro turbines.Water Energy Abstr2008182728
     [Google Scholar]
  10. GandhiB.K. SinghS.N. SeshadriV. Study of the parametric dependence of erosion wear for the parallel flow of solid–liquid mixtures.Tribol. Int.199932527528210.1016/S0301‑679X(99)00047‑X
     [Google Scholar]
  11. GrewalH.S. AroraH.S. AgrawalA. SinghH. MukherjeeS. Slurry erosion of thermal spray coatings: Effect of sand concentration.Procedia Eng.20136848449010.1016/j.proeng.2013.12.210
     [Google Scholar]
  12. VinodK. PorwalR.K. Effect of coating on erosion wear: An experimental investigation.IOP Conf Ser: Mater Sci Eng201840201211710.1088/1757‑899X/402/1/012117
     [Google Scholar]
  13. DasguptaR. PrasadB.K. JhaA.K. ModiO.P. DasS. YegneswaranA.H. Effects of sand concentration on slurry erosion of steels.Mater. Trans.199839121185119010.2320/matertrans1989.39.1185
     [Google Scholar]
  14. O’FlynnD.J. BingleyM.S. BradleyM.S.A. BurnettA.J. A model to predict the solid particle erosion rate of metals and its assessment using heat-treated steels.Wear20012481-216217710.1016/S0043‑1648(00)00554‑8
     [Google Scholar]
  15. TurenneS. ChâtignyY. SimardD. CaronS. MasounaveJ. The effect of abrasive particle size on the slurry erosion resistance of particulate-reinforced aluminium alloy.Wear1990141114715810.1016/0043‑1648(90)90199‑K
     [Google Scholar]
  16. SinghJ SinghS Neural network supported study on erosive wear performance analysis of Y2O3/WC-10Co4Cr HVOF coating. J King Saud Univ -Eng Sci 2022; 2022141: 12.005.10.1016/j.jksues.2021.12.005
  17. SinghJ. Wear performance analysis and characterization of HVOF deposited Ni–20Cr2O3, Ni–30Al2O3, and Al2O3–13TiO2 coatings.Appl Surf Sci Adv2021610016110.1016/j.apsadv.2021.100161
     [Google Scholar]
  18. BursteinG.T. SasakiK. Effect of impact angle on the slurry erosion–corrosion of 304L stainless steel.Wear20002401-2809410.1016/S0043‑1648(00)00344‑6
     [Google Scholar]
  19. DengT. BingleyM.S. BradleyM.S.A. Influence of particle dynamics on erosion test conditions within the centrifugal accelerator type erosion tester.Wear2001249121059106910.1016/S0043‑1648(01)00831‑6
     [Google Scholar]
  20. DivakarM. AgarwalV.K. SinghS.N. Effect of the material surface hardness on the erosion of AISI316.Wear20052591-611011710.1016/j.wear.2005.02.004
     [Google Scholar]
  21. Al-BukhaitiM.A. AhmedS.M. BadranF.M.F. EmaraK.M. Effect of impingement angle on slurry erosion behaviour and mechanisms of 1017 steel and high-chromium white cast iron.Wear20072629-101187119810.1016/j.wear.2006.11.018
     [Google Scholar]
  22. KrishnamurthyN. MuraliM.S. VenkataramanB. MukundaP.G. Characterization and solid particle erosion behavior of plasma sprayed alumina and calcia-stabilized zirconia coatings on Al-6061 substrate.Wear2012274-275152710.1016/j.wear.2011.08.003
     [Google Scholar]
  23. SinghJ. SinghS. Neural network prediction of slurry erosion of heavy-duty pump impeller/casing materials 18Cr-8Ni, 16Cr-10Ni-2Mo, super duplex 24Cr-6Ni-3Mo-N, and grey cast iron.Wear202147620374110.1016/j.wear.2021.203741
     [Google Scholar]
  24. DesaleG.R. GandhiB.K. JainS.C. Improvement in the design of a pot tester to simulate erosion wear due to solid–liquid mixture.Wear20052591-619620210.1016/j.wear.2005.02.068
     [Google Scholar]
  25. OkaY. MatsumuraM. OhsakoY. YamawakiM. Particle impact conditions in vibratory sand-erosion facilities.Boshoku Gijutsu198433527828310.3323/jcorr1974.33.5_278
     [Google Scholar]
  26. MakwanaM. SutariaB.M. Slurry erosion behaviour of Ni-Hard under various impact angle and speed.IOP Conf Ser: Mater Sci Eng1984100401202310.1088/1757‑899X/1004/1/012023
     [Google Scholar]
  27. DesaleG.R. GandhiB.K. JainS.C. Slurry erosion of ductile materials under normal impact condition.Wear20082643-432233010.1016/j.wear.2007.03.022
     [Google Scholar]
  28. CaiF. HuangX. YangQ. Mechanical properties, sliding wear and solid particle erosion behaviors of plasma enhanced magnetron sputtering CrSiCN coating systems.Wear2015324-325273510.1016/j.wear.2014.11.008
     [Google Scholar]
  29. XuY. LiuL. ZhouQ. WangX. HuangY. Understanding the influences of pre-corrosion on the erosion-corrosion performance of pipeline steel.Wear2020442-44320315110.1016/j.wear.2019.203151
     [Google Scholar]
  30. SinghJ. MohapatraS.K. KumarS. Performance analysis of pump materials employed in bottom ash slurry erosion conditions.J. Tribol.2021307389
     [Google Scholar]
  31. SinghJ. KumarS. MohapatraS.K. Study on solid particle erosion of pump materials by Fly Ash Slurry using Taguchi’s Orthogonal Array. Tribologia - Finnish.J. Tribol.2021383-4313810.30678/fjt.97530
     [Google Scholar]
  32. SinghJ. Tribo-performance analysis of HVOF sprayed 86WC-10Co4Cr & Ni-Cr2O3 on AISI 316L steel using DOE-ANN methodology.Ind. Lubr. Tribol.202173572773510.1108/ILT‑04‑2020‑0147
     [Google Scholar]
  33. SinghJ. SinghJ.P. Performance analysis of erosion resistant Mo2C reinforced WC-CoCr coating for pump impeller with Taguchi’s method.Ind. Lubr. Tribol.202274443144110.1108/ILT‑05‑2020‑0155
     [Google Scholar]
  34. HawthorneH.M. XieY. YickS.K. A study of single particle–target surface interactions along a specimen in the Coriolis slurry erosion tester.Wear20022533-440341010.1016/S0043‑1648(02)00151‑5
     [Google Scholar]
  35. HawthorneH.M. Some Coriolis slurry erosion test developments.Tribol. Int.2002351062563010.1016/S0301‑679X(02)00053‑1
     [Google Scholar]
  36. SinghJ. Slurry erosion performance analysis and characterization of high-velocity oxy-fuel sprayed Ni and Co hardsurfacing alloy coatings.J. King Saud Univ. Eng. Sci.202135641542910.1016/j.jksues.2021.06.009
     [Google Scholar]
  37. RajahramS.S. HarveyT.J. WoodR.J.K. Electrochemical investigation of erosion–corrosion using a slurry pot erosion tester.Tribol. Int.201144323224010.1016/j.triboint.2010.10.008
     [Google Scholar]
  38. RajahramS.S. HarveyT.J. WoodR.J.K. Erosion–corrosion resistance of engineering materials in various test conditions.Wear20092671-424425410.1016/j.wear.2009.01.052
     [Google Scholar]
  39. IslamM.A. AlamT. FarhatZ.N. MohamedA. AlfantaziA. Effect of microstructure on the erosion behavior of carbon steel.Wear2015332-3331080108910.1016/j.wear.2014.12.004
     [Google Scholar]
  40. DengT. LiJ. ChaudhryA.R. PatelM. HutchingsI. BradleyM.S.A. Comparison between weight loss of bends in a pneumatic conveyor and erosion rate obtained in a centrifugal erosion tester for the same materials.Wear20052581-440241110.1016/j.wear.2004.02.012
     [Google Scholar]
  41. SchoopM.U. An improved process of applying deposits of metal or metallic compounds to surfaces. UK Patent AD21066, 1911.
  42. SchoopM.U. Improvements in or connected with the coating of surfaces with metal, applicable also for soldering or uniting metals and other materials. UK Patent AD5712, 1910
  43. SchoopM.U. The autogenous soldering of metals.Sci. Am.190796918919010.1038/scientificamerican03021907‑189
     [Google Scholar]
  44. AvcuY.Y. GüneyM. AvcuE. High-velocity air fuel coatings for steel for erosion-resistant applications.J Electrochem Sci Eng20221340742010.5599/jese.1369
     [Google Scholar]
  45. MahmoudZ.H. MahmoodJ.M. Al-ObaidiN.S. RahimaA.M. Gama-Fe2O3 silica-coated 2-(2-benzothiazolyl azo)-4-methoxyaniline for supercapacitive performance.J Electrochem Sci Eng20231352153610.5599/jese.1657
     [Google Scholar]
  46. AbdulaahH.A. Al-GhabanA.M. AnaeeR.A. KhadomA.A. KadhimM.M. Cerium-tricalcium phosphate coating for 316L stainless steel in simulated human fluid: Experimental, biological, theoretical, and electrochemical investigations.J Electrochem Sci Eng20221311512610.5599/jese.1257
     [Google Scholar]
  47. KumarD. YadavR. SinghJ. Evolution and adoption of microwave claddings in modern engineering applications.Advances in Microwave Processing for Engineering Materials.Boca RatonCRC Press202213415310.1201/9781003248743‑8
     [Google Scholar]
  48. VasudevH. ThakurL. SinghH. BansalA. Effect of addition of Al2O3 on the high-temperature solid particle erosion behaviour of HVOF sprayed Inconel-718 coatings.Mater. Today Commun.20223010301710.1016/j.mtcomm.2021.103017
     [Google Scholar]
  49. PrasharG. VasudevH. Structure-property correlation and high-temperature erosion performance of Inconel625-Al2O3 plasma-sprayed bimodal composite coatings.Surf. Coat. Tech.202243912845010.1016/j.surfcoat.2022.128450
     [Google Scholar]
  50. VasudevH. ThakurL. SinghH. BansalA. Mechanical and microstructural behaviour of wear resistant coatings on cast iron lathe machine beds and slides.Met. Mater.2018561556310.4149/km_2018_1_55
     [Google Scholar]
  51. PrasharG. VasudevH. High temperature erosion behavior of plasma sprayed Al 2 O 3 coating on AISI-304 stainless steel.World J. Eng.202118576076610.1108/WJE‑10‑2020‑0476
     [Google Scholar]
  52. SinghJ. VasudevH. SinghS. Performance of different coating materials against high temperature oxidation in boiler tubes – A review.Mater. Today Proc.20202697297810.1016/j.matpr.2020.01.156
     [Google Scholar]
  53. SinghG. VasudevH. BansalA. VardhanS. SharmaS. Microwave cladding of Inconel-625 on mild steel substrate for corrosion protection.Mater. Res. Express20207202651210.1088/2053‑1591/ab6fa3
     [Google Scholar]
  54. AroraH. KumarV. PrakashC. Analysis of sensitization in austenitic stainless steel-welded joint.Rai J Technol Res Innov2017513810.1007/978‑981‑15‑5151‑2_2
     [Google Scholar]
  55. GoyalK. BhatiaR. Effect of nano yttria stabilized zirconia on corrosion behaviour of chromium oxide coatings on boiler steel.J Electrochem Sci Eng2023136995100410.5599/jese.2147
     [Google Scholar]
  56. MiryalaV.V.S. VasudevH. Mechanical and microstructural charaterization of YSZ/Al2O3/CeO2 plasma Sprayed coatings.J Electrochem Sci Eng20221316317210.5599/jese.1431
     [Google Scholar]
  57. MehtaA. SinghG. Consequences of hydroxyapatite doping using plasma spray to implant biomaterials.J Electrochem Sci Eng202313152310.5599/jese.1614
     [Google Scholar]
  58. SinghJ. SinghJ.P. KumarS. GillH.S. Short review on hydroxyapatite powder coating for SS 316L.J Electrochem Sci Eng2023131253910.5599/jese.1611
     [Google Scholar]
  59. FouladvariN. FirtinG. KahyaogluB. NobiliL. BernasconiR. Electrodeposition of zinc-nickel alloys from ethylene glycol-based electrolytes in presence of additives for corrosion protection.J Electrochem Sci Eng20231398199310.5599/jese.1895
     [Google Scholar]
  60. BuytozS. UlutanM. IslakS. KurtB. Nuri ÇelikO. Microstructural and wear characteristics of High Velocity Oxygen Fuel (HVOF) sprayed NiCrBSi–SiC composite coating on SAE 1030 steel.Arab. J. Sci. Eng.20133861481149110.1007/s13369‑013‑0536‑y
     [Google Scholar]
  61. SinghJ. KumarS. MohapatraS.K. Tribological performance of Yttrium (III) and Zirconium (IV) ceramics reinforced WC–10Co4Cr cermet powder HVOF thermally sprayed on X2CrNiMo-17-12-2 steel.Ceram. Int.20194517231262314210.1016/j.ceramint.2019.08.007
     [Google Scholar]
  62. MehtaA. VasudevH. SinghS. Recent developments in the designing of deposition of thermal barrier coatings – A review.Mater. Today Proc.2020261336134210.1016/j.matpr.2020.02.271
     [Google Scholar]
  63. VasudevH. PrasharG. ThakurL. BansalA. Microstructural characterization and electrochemical corrosion behaviour of HVOF sprayed Alloy718-nanoAl2O3 composite coatings.Surf. Topogr.20219303500310.1088/2051‑672X/ac1044
     [Google Scholar]
  64. PrasharG. VasudevH. ThakurL. Influence of heat treatment on surface properties of HVOF deposited WC and Ni-based powder coatings: A review.Surf. Topogr.20219404300210.1088/2051‑672X/ac3a52
     [Google Scholar]
  65. VasudevH. PrasharG. ThakurL. BansalA. Electrochemical corrosion behavior and microstructural characterization of HVOF sprayed Inconel718-Al2O3 composite coatings.Surf. Rev. Lett.2022292225001710.1142/S0218625X22500172
     [Google Scholar]
  66. BansalA. VasudevH. SharmaA.K. KumarP. Investigation on the effect of post weld heat treatment on microwave joining of the Alloy-718 weldment.Mater. Res. Express20196808655410.1088/2053‑1591/ab1d9a
     [Google Scholar]
  67. ThakurL. AroraN. JayaganthanR. SoodR. An investigation on erosion behavior of HVOF sprayed WC–CoCr coatings.Appl. Surf. Sci.201125831225123410.1016/j.apsusc.2011.09.079
     [Google Scholar]
  68. StackM.M. JanaB.D. AbdelrahmanS.M. Models and mechanisms of erosion–corrosion in metals.Tribocorrosion of Passive Metals and Coatings.United KingdomWoodhead Publishing Series201110.1533/9780857093738.1.153
     [Google Scholar]
  69. StackM.M. Abd El-BadiaT.M. Some comments on mapping the combined effects of slurry concentration, impact velocity and electrochemical potential on the erosion–corrosion of WC/Co–Cr coatings.Wear20082649-1082683710.1016/j.wear.2007.02.025
     [Google Scholar]
  70. WheelerD.W. WoodR.J.K. Erosion of hard surface coatings for use in offshore gate valves.Wear20052581-452653610.1016/j.wear.2004.03.035
     [Google Scholar]
  71. MaitiA.K. MukhopadhyayN. RamanR. Effect of adding WC powder to the feedstock of WC–Co–Cr based HVOF coating and its impact on erosion and abrasion resistance.Surf. Coat. Tech.2007201187781778810.1016/j.surfcoat.2007.03.014
     [Google Scholar]
  72. ChoT.Y. YoonJ.H. KimK.S. A study on HVOF coatings of micron and nano WC–Co powders.Surf. Coat. Tech.200820222-235556555910.1016/j.surfcoat.2008.06.106
     [Google Scholar]
  73. LeeC.W. HanJ.H. YoonJ. ShinM.C. KwunS.I. A study on powder mixing for high fracture toughness and wear resistance of WC–Co–Cr coatings sprayed by HVOF.Surf. Coat. Tech.2010204142223222910.1016/j.surfcoat.2009.12.014
     [Google Scholar]
  74. Vite-TorresM. Laguna-CamachoJ.R. Baldenebro-CastilloR.E. Gallardo-HernándezE.A. Vera-CárdenasE.E. Vite-TorresJ. Study of solid particle erosion on AISI 420 stainless steel using angular silicon carbide and steel round grit particles.Wear20133011-238338910.1016/j.wear.2013.01.071
     [Google Scholar]
  75. MuruganK. RagupathyA. BalasubramanianV. SridharK. Optimizing HVOF spray process parameters to attain minimum porosity and maximum hardness in WC–10Co–4Cr coatings.Surf. Coat. Tech.20142479010210.1016/j.surfcoat.2014.03.022
     [Google Scholar]
  76. KumarA. SharmaA. GoelS.K. Effect of heat treatment on microstructure, mechanical properties and erosion resistance of cast 23-8-N nitronic steel.Mater. Sci. Eng. A2015637566210.1016/j.msea.2015.04.031
     [Google Scholar]
  77. SinghJ. KumarS. MohapatraS.K. An erosion and corrosion study on thermally sprayed WC-Co-Cr powder synergized with Mo2C/Y2O3/ZrO2 feedstock powders.Wear2019438-43910275110.1016/j.wear.2019.01.082
     [Google Scholar]
  78. SinghJ. SinghS. VasudevH. SinghJ. KumarS. Neural computing and Taguchi’s methodbased study on erosion of advanced Mo2C–WC10Co4Cr coating for the centrifugal pump.Adv Mater Proc Technol20232023222188410.1080/2374068X.2023.2221884
     [Google Scholar]
  79. ThakurL. AroraN. A study of processing and slurry erosion behaviour of multi-walled carbon nanotubes modified HVOF sprayed nano-WC-10Co-4Cr coating.Surf. Coat. Tech.201730986087110.1016/j.surfcoat.2016.10.073
     [Google Scholar]
  80. SafonovV. ZykovaA. StellerJ. SeremakT. DonkovN. Comparative analysis of cavitation erosion of Cr-C carbide coatings depending on the carbon content.J. Phys. Conf. Ser.20222240101201210.1088/1742‑6596/2240/1/012012
     [Google Scholar]
  81. HongS. WuY. WangB. ZhengY. GaoW. LiG. High-velocity oxygen-fuel spray parameter optimization of nanostructured WC–10Co–4Cr coatings and sliding wear behavior of the optimized coating.Mater. Des.20145528629110.1016/j.matdes.2013.10.002
     [Google Scholar]
  82. ShresthaS. HodgkiessT. NevilleA. Erosion–corrosion behaviour of high-velocity oxy-fuel Ni–Cr–Mo–Si–B coatings under high-velocity seawater jet impingement.Wear20052591-620821810.1016/j.wear.2005.01.038
     [Google Scholar]
  83. TamK.F. ChengF.T. ManH.C. Cavitation erosion behavior of laser-clad Ni–Cr–Fe–WC on brass.Mater. Res. Bull.20023771341135110.1016/S0025‑5408(02)00766‑3
     [Google Scholar]
  84. ArjiR. DwivediD.K. GuptaS.R. Some studies on slurry erosion of flame sprayed Ni‐Cr‐Si‐B coating.Ind. Lubr. Tribol.200961141010.1108/00368790910929476
     [Google Scholar]
  85. YaoSH Tribological behaviour of NiCrBSi–WC(Co) coatings. Mater Res Innov 2014; 18(sup2): S2-332-, S2-33710.1179/1432891714Z.000000000436
  86. KarimiM.R. SalimijaziH.R. GolozarM.A. Effects of remelting processes on porosity of NiCrBSi flame sprayed coatings.Surf. Eng.201632323824310.1179/1743294415Y.0000000107
     [Google Scholar]
  87. LiG. YangX. GuoJ. WuY. WangX. ZhangJ. Study on Corrosion resistance and mechanism of NiCrBSiFeCoC coating in 3.5 wt% NaCl solution.Trans. Indian Inst. Met.20177082213221910.1007/s12666‑017‑1052‑7
     [Google Scholar]
  88. ChattopadhyayR. High silt wear of hydroturbine runners.Wear1993162-1641040104410.1016/0043‑1648(93)90119‑7
     [Google Scholar]
  89. ArjiR. DwivediD.K. GuptaS.R. Sand slurry erosive wear of thermal sprayed coating of stellite.Surf. Eng.200723539139710.1179/174329407X247145
     [Google Scholar]
  90. SidhuH.S. SidhuB.S. PrakashS. Solid particle erosion of HVOF sprayed NiCr and Stellite-6 coatings.Surf. Coat. Tech.2007202223223810.1016/j.surfcoat.2007.05.035
     [Google Scholar]
  91. YarrapareddyE. ZekovicS. HamidS. KovacevicR. The development of nickel-tungsten carbide functionally graded materials by a laser-based direct metal deposition process for industrial slurry erosion applications.Proc. Inst. Mech. Eng., B J. Eng. Manuf.2006220121923193610.1243/09544054JEM578
     [Google Scholar]
  92. ShivamurthyR.C. KamarajM. NagarajanR. ShariffS.M. PadmanabhamG. Influence of microstructure on slurry erosive wear characteristics of laser surface alloyed 13Cr–4Ni steel.Wear20092671-420421210.1016/j.wear.2008.12.027
     [Google Scholar]
  93. GnanasekaranS. PadmanabanG. BalasubramanianV. Effect of laser power on metallurgical, mechanical and tribological characteristics of hardfaced surfaces of nickel-based alloy.Lasers Manufac Mater Proc20174417819210.1007/s40516‑017‑0045‑z
     [Google Scholar]
  94. MachioC.N. AkdoganG. WitcombM.J. LuyckxS. Performance of WC–VC–Co thermal spray coatings in abrasion and slurry erosion tests.Wear20052581-443444210.1016/j.wear.2004.09.033
     [Google Scholar]
  95. LiuS.L. ZhengX.P. GengG.Q. Influence of nano-WC–12Co powder addition in WC–10Co–4Cr AC-HVAF sprayed coatings on wear and erosion behaviour.Wear20102695-636236710.1016/j.wear.2010.04.019
     [Google Scholar]
  96. GoyalD.K. SinghH. KumarH. SahniV. Slurry erosive wear evaluation of HVOF-spray Cr2O3 coating on some turbine steels.J Thermal Spray Technol201221583885110.1007/s11666‑012‑9795‑5
     [Google Scholar]
  97. GrewalH.S. AgrawalA. SinghH. ShollockB.A. Slurry erosion performance of Ni-Al2O3 based thermal-sprayed coatings: Effect of angle of impingement.J Thermal Spray Technol201423338940110.1007/s11666‑013‑0013‑x
     [Google Scholar]
  98. Raj SharmaA. GoyalR. Immersion studies of Al2O3 – 13% TiO2 and Cr2O3 coatings on ship hull plate in simulated seawater environment in laboratory.Mater. Today Proc.20224894695110.1016/j.matpr.2021.05.677
     [Google Scholar]
  99. RoopraiR.S. SinghH. SinghT. SinglaY.K. Analysis of the wear properties of through hardened AISI-4140 alloy steel using Taguchi technique.Mater. Today Proc.20225066166410.1016/j.matpr.2021.04.196
     [Google Scholar]
  100. GoyalK. GoyalR. Improving hot corrosion resistance of Cr3C2 –20NiCr coatings with CNT reinforcements.Surf. Eng.202036111200120910.1080/02670844.2019.1662645
     [Google Scholar]
  101. SinghJ. VasudevH. ChohanJ.S. Neural computing of slurry erosion of Al2O3-13TiO2 thermal spray HVOF coating for mining pump.Int J Interac Des Manuf202320230140010.1007/s12008‑023‑01400‑x
     [Google Scholar]
  102. SinghJ. VasudevH. SzalaM. GillH.S. Neural computing for erosion assessment in Al-20TiO2 HVOF thermal spray coating.Int J Interact Des Manuf202320230137210.1007/s12008‑023‑01372‑y
     [Google Scholar]
  103. SinghJ. VasudevH. KumarR. UbaidullahM. Study on wear analysis of Ni-20Al2O3 HVOF micron layers using artificial neural network technique.Int J Interact Des Manuf2023202301433210.1007/s12008‑023‑01433‑2
     [Google Scholar]
  104. KumarP. SinghJ. SinghS. Neural network supported flow characteristics analysis of heavy sour crude oil emulsified by ecofriendly bio-surfactant utilized as a replacement of sweet crude oil.Chem. Eng. J. Adv.20221110034210.1016/j.ceja.2022.100342
     [Google Scholar]
  105. SinghJ. SinghS. Support vector machine learning on slurry erosion characteristics analysis of Ni- and Co-alloy coatings.Surf. Rev. Lett.2023234000610.1142/S0218625X23400061
     [Google Scholar]
  106. BulgarevichD.S. TsukamotoS. KasuyaT. DemuraM. WatanabeM. Pattern recognition with machine learning on optical microscopy images of typical metallurgical microstructures.Sci. Rep.201881207810.1038/s41598‑018‑20438‑6 29391483
     [Google Scholar]
  107. ShobhaG. RangaswamyS. Machine Learning.1st edAmsterdamElsevier201810.1016/bs.host.2018.07.004
     [Google Scholar]
  108. PraveenA.S. SaranganJ. SureshS. ChannabasappaB.H. Optimization and erosion wear response of NiCrSiB/WC–Co HVOF coating using Taguchi method.Ceram. Int.20164211094110410.1016/j.ceramint.2015.09.036
     [Google Scholar]
  109. QiaoL. WuY. HongS. ZhangJ. ShiW. ZhengY. Relationships between spray parameters, microstructures and ultrasonic cavitation erosion behavior of HVOF sprayed Fe-based amorphous/nanocrystalline coatings.Ultrason. Sonochem.201739394610.1016/j.ultsonch.2017.04.011 28732960
     [Google Scholar]
  110. SinghJ. KumarS. SinghG. Taguchi’s approach for optimization of tribo-resistance parameters forss304.Mater. Today Proc.2018525031503810.1016/j.matpr.2017.12.081
     [Google Scholar]
  111. TabbaraH. GuS. McCartneyD.G. Computational modelling of titanium particles in warm spray.Comput. Fluids201144135836810.1016/j.compfluid.2011.01.034
     [Google Scholar]
  112. LiM. ChristofidesP.D. Modeling and control of high-velocity oxygen-fuel (HVOF) thermal spray: A tutorial review.J Therm Spray Technol2009185-675376810.1007/s11666‑009‑9309‑2
     [Google Scholar]
  113. DongmoE. WenzelburgerM. GadowR. Analysis and optimization of the HVOF process by combined experimental and numerical approaches.Surf. Coat. Tech.2008202184470447810.1016/j.surfcoat.2008.04.029
     [Google Scholar]
  114. GuessasmaS. SalhiZ. MontavonG. GougeonP. CoddetC. Artificial intelligence implementation in the APS process diagnostic.Mater. Sci. Eng. B2004110328529510.1016/j.mseb.2004.03.017
     [Google Scholar]
  115. GuessasmaS. MontavonG. CoddetC. Modeling of the APS plasma spray process using artificial neural networks: Basis, requirements and an example.Comput. Mater. Sci.200429331533310.1016/j.commatsci.2003.10.007
     [Google Scholar]
  116. GuessasmaS. MontavonG. CoddetC. Neural computation to predict in-flight particle characteristic dependences from processing parameters in the APS process.J Thermal Spray Technol200413457058510.1361/10599630419391
     [Google Scholar]
  117. SahraouiT. GuessasmaS. FeninecheN.E. MontavonG. CoddetC. Friction and wear behaviour prediction of HVOF coatings and electroplated hard chromium using neural computation.Mater. Lett.200458565466010.1016/j.matlet.2003.06.010
     [Google Scholar]
  118. ChoudhuryT.A. HosseinzadehN. BerndtC.C. Artificial Neural Network application for predicting in-flight particle characteristics of an atmospheric plasma spray process.Surf. Coat. Tech.201120521-224886489510.1016/j.surfcoat.2011.04.099
     [Google Scholar]
  119. ChoudhuryT.A. HosseinzadehN. BerndtC.C. Improving the generalization ability of an artificial neural network in predicting in-flight particle characteristics of an atmospheric plasma spray process.J Therm Spray Technol201221593594910.1007/s11666‑012‑9775‑9
     [Google Scholar]
  120. KantaA.F. MontavonG. PlancheM.P. CoddetC. Artificial neural networks implementation in plasma spray process: Prediction of power parameters and in-flight particle characteristics vs. desired coating structural attributes.Surf. Coat. Tech.2009203223361336910.1016/j.surfcoat.2009.04.023
     [Google Scholar]
  121. KantaA.F. MontavonG. BerndtC.C. PlancheM.P. CoddetC. Intelligent system for prediction and control: Application in plasma spray process.Expert Syst. Appl.201138126027110.1016/j.eswa.2010.06.056
     [Google Scholar]
  122. KantaA.F. MontavonG. PlancheM.P. CoddetC. Artificial intelligence computation to establish relationships between APS process parameters and alumina–titania coating properties.Plasma Chem. Plasma Process.200828224926210.1007/s11090‑007‑9116‑9
     [Google Scholar]
  123. ZhangC. KantaA.F. LiC.X. Effect of in-flight particle characteristics on the coating properties of atmospheric plasma-sprayed 8mol% Y2O3–ZrO2 electrolyte coating studying by artificial neural networks.Surf. Coat. Tech.2009204446346910.1016/j.surfcoat.2009.08.009
     [Google Scholar]
  124. LiuT. DengS. PlancheM.P. MontavonG. Estimating the behavior of particles sprayed by a single-cathode plasma torch based on a nonlinear autoregressive exogenous model.Surf. Coat. Tech.201526828429210.1016/j.surfcoat.2014.10.040
     [Google Scholar]
  125. GuessasmaS. MontavonG. GougeonP. CoddetC. Designing expert system using neural computation in view of the control of plasma spray processes.Mater. Des.200324749750210.1016/S0261‑3069(03)00109‑2
     [Google Scholar]
  126. KantaA.F. PlancheM.P. MontavonG. CoddetC. In-flight and upon impact particle characteristics modelling in plasma spray process.Surf. Coat. Tech.20102049-101542154810.1016/j.surfcoat.2009.09.076
     [Google Scholar]
  127. CheriguiM. GuessasmaS. FeninecheN. CoddetC. Neural computation to correlate HVOF thermal spraying parameters with the magnetic properties of FeNb alloy deposits.Mater. Chem. Phys.200593118118610.1016/j.matchemphys.2005.03.042
     [Google Scholar]
  128. ZhangG. KantaA.F. LiW.Y. LiaoH. CoddetC. Characterizations of AMT-200 HVOF NiCrAlY coatings.Mater. Des.200930362262710.1016/j.matdes.2008.05.059
     [Google Scholar]
  129. KamnisS. MalamousiK. MarrsA. AllcockB. DelibasisK. Aeroacoustics and artificial neural network modeling of airborne acoustic emissions during high kinetic energy thermal spraying.J Therm Spray Technol201928594696210.1007/s11666‑019‑00874‑0
     [Google Scholar]
  130. MojenaM.A.R. RocaA.S. ZamoraR.S. OrozcoM.S. FalsH.C. LimaC.R.C. Neural network analysis for erosive wear of hard coatings deposited by thermal spray: Influence of microstructure and mechanical properties.Wear2017376-37755756510.1016/j.wear.2016.12.035
     [Google Scholar]
  131. LiuM. YuZ. ZhangY. WuH. LiaoH. DengS. Prediction and analysis of high velocity oxy fuel (HVOF) sprayed coating using artificial neural network.Surf. Coat. Tech.201937812498810.1016/j.surfcoat.2019.124988
     [Google Scholar]
  132. LiuM. YuZ. WuH. LiaoH. ZhuQ. DengS. Implementation of artificial neural networks for forecasting the HVOF spray process and HVOF sprayed coatings.J Therm Spray Technol20213051329134310.1007/s11666‑021‑01213‑y
     [Google Scholar]
  133. LiuM. WuH. YuZ. LiaoH. DengS. Description and prediction of multi-layer profile in cold spray using artificial neural networks.J Therm Spray Technol20213061453146310.1007/s11666‑021‑01212‑z
     [Google Scholar]
  134. WangZ. CaiS. ChenW. AliR.A. JinK. Analysis of critical velocity of cold spray based on machine learning method with feature selection.J Therm Spray Technol20213051213122510.1007/s11666‑021‑01198‑8
     [Google Scholar]
  135. SzalaM. HejwowskiT.J. LenartI. Cavitation erosion resistance of Ni-Co based coatings.Adv Sci Technol Res J201483642
     [Google Scholar]
/content/journals/meng/10.2174/0122127976316837240607054956
Loading
Artificial Neural Networks in Spray Coatings for Protection of Hydroturbines in Silt Conditions
Recent Patents on Mechanical Engineering 18, 268 (2025); https://doi.org/10.2174/0122127976316837240607054956
/content/journals/meng/10.2174/0122127976316837240607054956
/content/journals/meng/10.2174/0122127976316837240607054956
Loading

Data & Media loading...


  • Article Type:     Review Article
Keyword(s): artificial neural networks; coatings; hydroturbines; machine learning; Silt erosion; tribology

Most Cited Most Cited RSS feed

This is a required field
Please enter a valid email address
Approval was a Success
Invalid data
An Error Occurred
Approval was partially successful, following selected items could not be processed due to error
Please enter a valid_number test