Enhanced slurry and cavitation erosion resistance of deep cryogenically treated thermal spray coatings for hydroturbine applications

Abstract Thermal spray coatings are widely used for erosion resistance, but the relationship between the microstructure of the coatings and their erosion resistance is not well understood. In this paper the performance of several commonly used coatings at ambient and elevated temperatures is reviewed in light of the coatings' structure and compared with a new coating. Two high temperature industrial applications, solid particle erosion in steam turbines and alumina-based erosion have been chosen to illustrate the significance of a coating's structure on its performance.

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Neural Modelling of APS Thermal Spray Process Parameters for Optimizing the Hardness, Porosity and Cavitation Erosion Resistance of Al2O3-13 wt% TiO2 Coatings

Processes ◽

10.3390/pr8121544 ◽

2020 ◽

Vol 8 (12) ◽

pp. 1544

Author(s):

Mirosław Szala ◽

Leszek Łatka ◽

Michał Awtoniuk ◽

Marcin Winnicki ◽

Monika Michalak

Keyword(s):

Thermal Spray ◽

Process Parameters ◽

Cavitation Erosion ◽

Erosion Resistance ◽

Ceramic Coatings ◽

Thermal Spray Process ◽

Spray Process ◽

Tio2 Coatings ◽

Cavitation Erosion Resistance ◽

Selection Of

The study aims to elaborate a neural model and algorithm for optimizing hardness and porosity of coatings and thus ensure that they have superior cavitation erosion resistance. Al2O3-13 wt% TiO2 ceramic coatings were deposited onto 316L stainless steel by atmospheric plasma spray (ASP). The coatings were prepared with different values of two spray process parameters: the stand-off distance and torch velocity. Microstructure, porosity and microhardness of the coatings were examined. Cavitation erosion tests were conducted in compliance with the ASTM G32 standard. Artificial neural networks (ANN) were employed to elaborate the model, and the multi-objectives genetic algorithm (MOGA) was used to optimize both properties and cavitation erosion resistance of the coatings. Results were analyzed with MATLAB software by Neural Network Toolbox and Global Optimization Toolbox. The fusion of artificial intelligence methods (ANN + MOGA) is essential for future selection of thermal spray process parameters, especially for the design of ceramic coatings with specified functional properties. Selection of these parameters is a multicriteria decision problem. The proposed method made it possible to find a Pareto front, i.e., trade-offs between several conflicting objectives—maximizing the hardness and cavitation erosion resistance of Al2O3-13 wt% TiO2 coatings and, at the same time, minimizing their porosity.

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Neural Modelling of APS Thermal Spray Process Parameters for Optimising the Hardness, Porosity and Cavitation Erosion Resistance of Al2O3 -13% TiO2 Coatings

10.20944/preprints202011.0200.v1 ◽

2020 ◽

Author(s):

Mirosław Szala ◽

Leszek Łatka ◽

Michał Awtoniuk ◽

Marcin Winnicki ◽

Monika Michalak

Keyword(s):

Thermal Spray ◽

Process Parameters ◽

Cavitation Erosion ◽

Erosion Resistance ◽

Ceramic Coatings ◽

Thermal Spray Process ◽

Spray Process ◽

Conflicting Objectives ◽

Cavitation Erosion Resistance ◽

Selection Of

The study aims to elaborate a neural model and algorithm for optimising hardness and porosity of coatings and thus ensure that they have superior cavitation erosion resistance. Al2O3-13wt.%TiO2 ceramic coatings were deposited onto 316L stainless steel by atmospheric plasma spray (ASP). The coatings were prepared with different values of two spray process parameters: the stand-off distance and torch velocity. Microstructure, porosity and microhardness of the coatings were examined. Cavitation erosion tests were conducted in compliance with the ASTM G32 standard. Artificial neural networks (ANN) were employed to elaborate the model, and the multi-objectives genetic algorithm (MOGA) was used to optimise both properties and cavitation erosion resistance of the coatings. Results were analysed with Matlab software by Neural Network Toolbox and Global Optimization Toolbox. The fusion of artificial intelligence methods (ANN+MOGA) is essential for future selection of thermal spray process parameters, especially for the design of ceramic coatings with specified functional properties. Selection of these parameters is a multicriteria decision problem. The proposed method made it possible to find a Pareto front, i.e. trade-offs between several conflicting objectives – maximising the hardness and cavitation erosion resistance of Al2O3-13%TiO2 coatings and, at the same time, minimizing their porosity.

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Processing and Thermal Cycling Effects on the Erosion Behavior of Thermal Barrier Coatings

Thermal Spray 1997: Proceedings from the United Thermal Spray Conference ◽

10.31399/asm.cp.itsc1997p0285 ◽

1997 ◽

Author(s):

J. Gutleber ◽

S. Sampath ◽

S. Usmani

Keyword(s):

Thermal Spray ◽

Thermal Barrier Coatings ◽

Room Temperature ◽

Erosion Resistance ◽

Thermal Spray Coatings ◽

Thermal Barrier ◽

Powder Particle Size ◽

Barrier Coatings ◽

Erosion Behavior ◽

Spray Coatings

Abstract The erosion behavior of yttria stabilized zirconia thermal barrier coatings is investigated with respect to powder particle size. Solid particle erosion experiments were conducted at room temperature to determine the mechanism of erosion for ceramic thermal spray coatings. Testing was carried out on as-sprayed as well as thermally cycled specimens. Porosity and bend testing measurements indicate that a decrease in porosity and an increase in inter-lamellar strength leads to an increase in the erosion resistance of ceramic thermal spray coatings.

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Combined Slurry and Cavitation Erosion Resistance of Hvof Thermal Spray Coated Stainless Steel

Materials Today Proceedings ◽

10.1016/j.matpr.2017.01.046 ◽

2017 ◽

Vol 4 (2) ◽

pp. 465-470 ◽

Cited By ~ 5

Author(s):

H.J. Amarendra ◽

M.S. Prathap ◽

S. Karthik ◽

B.M. Darshan ◽

Devaraj ◽

...

Keyword(s):

Stainless Steel ◽

Thermal Spray ◽

Cavitation Erosion ◽

Erosion Resistance ◽

Hvof Thermal Spray ◽

Cavitation Erosion Resistance

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Elevated Temperature Erosion Resistance of Several Experimental Amorphous Thermal Spray Coatings

Thermal Spray 1998: Proceedings from the International Thermal Spray Conference ◽

10.31399/asm.cp.itsc1998p0151 ◽

1998 ◽

Author(s):

B. Wang

Keyword(s):

Elevated Temperature ◽

Thermal Spray ◽

Erosion Resistance ◽

Thermal Spray Coatings ◽

Test Results ◽

Hvof Coating ◽

Spray Coatings ◽

Erosion Test ◽

Sprayed Coatings ◽

Better Than

Abstract The elevated temperature erosion resistance of experimental amorphous thermal spray coatings was determined in a laboratory elevated temperature erosion tester. Test conditions attempted to simulate the erosion conditions found at the combustor waterwall tubes in fossil fuel fired boilers. Erosion tests were conducted on four experimental amorphous thermal spray coatings, using the bed ash retrieved from an operating coal fired boiler. An experimental arcspray process was used to spray coatings. These results were compared with erosion test results of two common structural materials, two commercially available arc-sprayed coatings, and a proprietary HVOF coating. Test results indicated that the Duocor coating had the highest erosion resistance among the four experimental coatings, it showed equal resistance to the HVOF coating (DS-200). Compared to AISI 1018 steel, both Duocor and DS-200 coatings reduced material wastage by 26-fold. Other test results indicated that the XJ-16, 60T and Armacor M coatings had equal erosion resistance reducing material wastage approximately 7-fold, while Arrnacor CW reduced by IO-fold. Only slightly better than the unprotected 1018 steel, the X-20 coating performed poorly on erosion tests. The high erosion resistance of Duocor and DS-200 coatings was attributed to their high densities and fine splat structures.

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