Metal fatigue : effects of small defects and nonmetallic inclusions

By 村上敬宜. 2002

841 citations recorded by the source corpus.

View Paper: https://www.semanticscholar.org/paper/76554acd1a62d9c4c854ed47178cfd317abb72a9

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

Citations in the corpus

Structure–property linkages using a data science approach: Application to a non-metallic inclusion/steel composite system (2015, background): “Murakami [25] treated inclusion as mechanically equivalent to small cracks and small defects, and has suggested a power-law relationship between fatigue strength and inclusion size.”
Modelling the influence of machined surface roughness on the fatigue life of aluminium alloy (2008, background): “Murakami [10] considered surface roughness as surface defect and defined a parameter related to the area of the periodic defects.”
The Effect of Manufacturing Defects on the Fatigue Behaviour of Ti-6Al-4V Specimens Fabricated Using Selective Laser Melting (2014, methodology): “However, the effect from the LOF defect was difficult to analyse because the defect had a very complex morphology, which cannot easily be quantified using so-called geometrical parameters as suggested by Murakami [7].”
Hydrogen Effect against Hydrogen Embrittlement (2010, methodology): “The replica method([42]) was used for the measurements of crack length and for the observation of crack growth behavior.”
Effects of Defects in Laser Additive Manufactured Ti-6Al-4V on Fatigue Properties (2014, methodology): “The calculation of the representative crack length for bonding defects is calculated by the “penny shaped” approach after MURAKAMI [Mur02]:”
Fatigue Strength Prediction for Titanium Alloy TiAl6V4 Manufactured by Selective Laser Melting (2015, methodology): “For detailed information regarding the determination of the area parameter, the reader is referred to Murakami.([22]) In order to obtain representative hardness values necessary for each fatigue strength prediction, five Vickers hardness measurements in the Fig.”
A comparison of fatigue strength sensitivity to defects for materials manufactured by AM or traditional processes (2017, background): “[102] Murakami Y. Inclusion rating by statistics of extreme values and its application to fatigue strength prediction and quality control of materials.”