Montavon, G., Berndt, C., Trifa, F.I., and Guessasma, S. (2005) Correlating the spray pattern to the coating architecture: exploring the dominant mechanisms and process parameters. In: Proceedings of International Thermal Spray Conference & Exposition. From: International Thermal Spray Conference & Exposition, 2-4 May 2005, Basel, Switzerland.

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Abstract

The plasma spray process is unique because the coating properties depend indirectly on the processing parameters. Therefore, the in-service properties derive mostly from the coating architecture. The coating architecture is related to the intrinsic lamellae formation mechanism; which is related to the impinging particle characteristics that are linked to the power and feedstock injection. The coating architecture is also related to the extrinsic spray pattern formation mechanism; i.e., the kinematics and geometric spray parameters such as spray velocity, spray angle, and stand off distance. Understanding relationships between coating architecture and its properties requires consideration of the whole coating formation process. Ultimately, this permits selection of process parameters that demonstrate enhanced spray efficiencies and manufacturing capability. Included in this study are the pore network architecture and residual stress level because they play important roles in coating cohesion from which derive most of the in-service properties. Coating manufacturing mechanisms, from the spray pattern to an actual coating formed by several successive patterns, are investigated in this paper. The case of atmospheric plasma sprayed Al2O3-TiO2 (13% by wt.) is considered. Data are statistically assessed by implementing Gaussian and Weibull analyses. The critical role of pores which develop within the spray pattern and between successive patterns is examined in detail. There is contamination between layers and the intrinsic roughness of the coating is altered during the spray process. In summary, within this work, it is intended to define the intrinsic and extrinsic operational variables that contribute to the coating architecture and, thereby, suggest technology that can be implemented to improve coating quality and deposition efficiency.

Item ID:	14827
Item Type:	Conference Item (Research - E1)
ISBN:	978-3-87155-793-4
Keywords:	control; mechanisms; neural networks; process parameters; thermal spray
Related URLs:	http://www.asminternational.org/content/...
Date Deposited:	26 Nov 2010 01:56
FoR Codes:	09 ENGINEERING > 0913 Mechanical Engineering > 091399 Mechanical Engineering not elsewhere classified @ 50% 09 ENGINEERING > 0901 Aerospace Engineering > 090103 Aerospace Structures @ 25% 09 ENGINEERING > 0912 Materials Engineering > 091202 Composite and Hybrid Materials @ 25%
SEO Codes:	87 CONSTRUCTION > 8703 Construction Materials Performance and Processes > 870302 Metals (e.g. Composites, Coatings, Bonding) @ 50% 86 MANUFACTURING > 8610 Ceramics, Glass and Industrial Mineral Products > 861002 Ceramics @ 25% 86 MANUFACTURING > 8615 Instrumentation > 861501 Industrial Instruments @ 25%
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