2024
DOI: 10.3389/fmats.2023.1293254
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Novel study on investigating the mechanical, microstructure morphological, and dry sliding wear characteristics of grey cast iron GG25 with copper additions for valve guides in internal combustion engine

Baljeet Singh,
Jasmaninder Singh Grewal,
Rajeev Kumar
et al.

Abstract: Introduction: The performance functionality efficacy of the engine’s valve train assembly is considerably affected by the valve guide. Material selection is impacted by the prolonged operational lifespan of engines, which favours casting and machining materials such as cast iron. The intent of this study is to examine the dry sliding characteristics of GG25 cast iron with copper additives. Discovering the ways in which variations in load and sliding velocity impact wear characteristics is of paramount signific… Show more

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Cited by 2 publications
(1 citation statement)
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“…Figure 4B shows a perturbation graph for the surface roughness, which will assist in comparing the influence of various variables at a suitable point location in the design area. The output is characterized by varying each factor within its given range during possession, keeping all variables constant (Singh et al, 2023a;Dikshit et al, 2023;Singh et al, 2024). A steeply inclined slope or curvature in the characteristic curve shows the input parameter factor as the response is sensitive to the output parameter surface roughness.…”
Section: Mathematical Modelling and Regression Analysismentioning
confidence: 99%
“…Figure 4B shows a perturbation graph for the surface roughness, which will assist in comparing the influence of various variables at a suitable point location in the design area. The output is characterized by varying each factor within its given range during possession, keeping all variables constant (Singh et al, 2023a;Dikshit et al, 2023;Singh et al, 2024). A steeply inclined slope or curvature in the characteristic curve shows the input parameter factor as the response is sensitive to the output parameter surface roughness.…”
Section: Mathematical Modelling and Regression Analysismentioning
confidence: 99%