Towards the understanding of creep-feed deep grinding of DD6 nickel-based single-crystal superalloy View Full Text


Ontology type: schema:ScholarlyArticle     


Article Info

DATE

2019-01

AUTHORS

Yulong Gu, Haonan Li, Baicun Du, Wenfeng Ding

ABSTRACT

DD6 nickel-based single-crystal superalloy has been treated as an ideal material for the high-valued and high-performed aero-engine components; however, it was found difficult to remove material from the DD6 nickel-based single-crystal superalloy in cutting and grinding. Although creep-feed deep grinding (CFDG) has been widely employed for various nickel-based superalloys (i.e., Inconel 718, DZ4, IN738LC), very few efforts however have been focused on the nickel-based single-crystal superalloy. With this, this paper focuses on CFDG of DD6 nickel-based single-crystal superalloy to gain the more in-depth understandings, targeting grinding force, specific grinding energy, grinding temperature, surface integrity, and wheel wear condition. Scheduled experimental observation proved that (i) microcrystalline alumina abrasive wheel generally shows more superior grinding performances in aspect to grinding force, force ratio, and specific grinding energy than that of brown alumina abrasive wheel; (ii) grinding temperature is decreased by 35% by using the microcrystalline alumina abrasive wheel compared to brown alumina abrasive wheel, and therefore the microcrystalline alumina abrasive wheels have the potential to be applied in the high-efficiency grinding; (iii) the surface ground by the microcrystalline alumina abrasive wheel is found smooth without any grinding-induced damage; and (iv) microcrystalline alumina abrasive wheels easily lead to micro-fractures and therefore result in better self-sharpness ability and longer service life in CFDG of DD6 nickel-based single-crystal superalloy. More... »

PAGES

445-455

Identifiers

URI

http://scigraph.springernature.com/pub.10.1007/s00170-018-2686-2

DOI

http://dx.doi.org/10.1007/s00170-018-2686-2

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1107229126


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