By Pradeep L. Menezes, Michael Nosonovsky, Sudeep P. Ingole, Satish V. Kailas, Michael R. Lovell
This e-book describes to be had tribology applied sciences and introdces a finished assessment of tribology. normal, up to date wisdom on how tribology is approached in a number of similar parts of study, either experimental and computational is provided.
Read Online or Download Tribology for Scientists and Engineers: From Basics to Advanced Concepts PDF
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Extra resources for Tribology for Scientists and Engineers: From Basics to Advanced Concepts
Example text
2. Explain various methods of characterizing surface layers. 3. Classify surface roughness parameters. Define any one surface roughness parameter under each classification using necessary diagrams and equations. 4. What is fractal dimension? List various methods to calculate fractal dimension. 5. Explain the terms skewness and kurtosis. 6. Explain autocorrelation and autocovariance functions. 7. Write a note on amplitude parameters. 8. Define the terms roughness and mean line. 9. Explain the differences between roughness and surface texture.
Mater Sci Eng, A 429(1–2):149–160 5. Whitehouse DJ (1994) Handbook of surface metrology. L. Menezes et al. 6. Feder J (1988) Fractals. Plenum, New York 7. Menezes PL, Kishore, Kailas SV (2006) Influence of surface texture on coefficient of friction and transfer layer formation during sliding of pure magnesium pin on 080 M40 (EN8) steel plate. Wear 261(5–6):578–591 8. Menezes PL, Kishore, Kailas SV (2008) Influence of roughness parameters of harder surface on coefficient of friction and transfer layer formation.
16 Profile showing the method of calculating various roughness parameters such as Rp, Rv, and Rt [3] moment m3 in normalized form gives the skewness. The fourth moment m4 in normalized form gives the kurtosis. It is expressed as follows: • • • • First moment (m1) ¼ Ra Second moment (m2) ¼ Rq Third moment (m3) ¼ Rsk Fourth moment (m4) ¼ Rku Maximum height of peaks (Rp): Rp is used to measure the maximum height of the profile above the mean line. It is the height difference between the mean line and the highest point over the evaluation length (see Fig.
