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Computational Code for Detonation Spraying Process

Authors: T.P. Gavrilenko; Y.A. Nikolaev; V.Y. Ulianitsky; M.C. Kim; J.W. Hong;

Computational Code for Detonation Spraying Process

Abstract

Abstract Interactive Computational Code is presented that provides a high-productivity analysis of the complex detonation spraying technology. It is based on exact gas dynamics theory taking into account chemical reactions for description of the gaseous detonation phenomena. It deals with specific features of the process like non-homogeneity of gaseous mixture compositions due to gas filling operation and powder injection into the barrel. Acceleration and heating of powder particles by the detonation product flow were simulated including particle melting, fragmentation and vaporization. Calculations for different fuels and powder materials were accomplished. Optimum conditions (gas mixture, barrel length, powder injection point, etc.) to provide highest velocity and appropriate temperature for typical metal and cermet powders are discussed. The conditions for coating formation by the detonation gun «Ob» were established and samples were produced. Experimental data on detonation coating properties are presented to prove the theoretical results.

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Powered by OpenAIRE graph
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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
17
Top 10%
Top 10%
Average
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