Assessment of the Deterioration of used Engine Oil Soaked Fly ash Concrete and its Analysis using Automated SEM Analysis

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Nandini M. Naik 1,* Girish.S.Kulkarni 2 K. B. Prakash 3

1. Chemical Engineering Department K.L.E DR M.S.Sheshagiri College of Engineering & Technology,Udyambag,Belgaum-590008.Karnataka

2. Environmental Science and Technology and Director Shivaji University Kolhapur, Maharashtra

3. Civil Engineering Department and Principal of Govt. Engineering College Haveri. Karnataka.

* Corresponding author.


Received: 29 Jan. 2016 / Revised: 2 Mar. 2016 / Accepted: 31 Mar. 2016 / Published: 8 May 2016

Index Terms

Flyash, Concrete, Used engine oil, SEM, Correlation Coefficient, SVM


The determination of strength properties i.e compressive strength, flexural strength and splitting tensile strength is essential to estimate the load at which the concrete members may crack especially in aggressive environment. The paper reports an experimental investigation on deterioration of used engine oil (UEO) soaked flyash concrete with respect to its strength properties and effective automation of classification of data sets returned by the SEM test on the same set of samples. In the former part, concrete cube ,beam and cylinder specimens with fly ash admixture as partial replacement of cement by 0%, 5%, 10%, 15%, 20%, 25%, 30%, 35% and 40% were subjected to water curing and then to UEO soaking. Gradual decrease in the strength properties of concrete specimens with respect to time was observed. An attempt has been made to study the permeation properties like soroptivity with the addition of fly ash in concrete. The SEM analysis of test results was in good agreement to this. An attempt was made to automate this analysis phase using correlation coefficient and Support Vector Machines (SVM). It was found that the latter achieved better results in terms of performance.

Cite This Paper

Nandini M.Naik, Girish S.Kulkarni, K.B.Prakash,"Assessment of the Deterioration of used Engine Oil Soaked Fly ash Concrete and its Analysis using Automated SEM Analysis", International Journal of Engineering and Manufacturing(IJEM), Vol.6, No.3, pp.1-11, 2016. DOI: 10.5815/ijem.2016.03.01


[1]Nuruddin M.F.,et al(2008). Effect of Used Engine Oil on MIHRA Concrete, A New Material In The Construction Industry. United Kingdom Malaysia Engineering Conference, vol. 28, No. 3, pp. 398-11.

[2]Wasiu O. Ajagbe, Olusola S. Omokehinde, Gabriel A. Alade, Oluwole A. Agbede, (2012). Effect of Crude Oil Impacted Sand on compressive strength of concrete. Construction and Building Materials 26 (2012) 9–12, Elsevier. doi: 10.1016/j.conbuildmat.2011.06.028.

[3]M.A. Matti, (1983). Effect of oil soaking on the dynamic modulus of concrete. International Journal of Cement Composites and Lightweight Concrete, Volume 5, Issue 4, Pages 277–282, Elsevier. doi: 10.1016/0262-5075(83)90069-6.

[4]T.Z. Blaszczynski, 'Concrete in contact with crude oil', STATYBA-CIVIL ENGINEERING, No. 2(6), 1996, pp.13-17. 

[5]J.L.Rodgers, W.A. Nicewander, "Thirteen Ways to Look at the Correlation Coefficient", The American Statistician, February 1988, Vol. 42, No. 1, pp.59-66 

[6]Eugene K. Jen, Roger G.Johnston, "The Ineffectiveness of Correlation Coefficient for Image Comparisons", Research Paper prepared by Vulnerability Assessment Team, Los Alamos National Laboratory, New Mexico.

[7]Vapnik, Vladimir Naumovich, and Vlamimir Vapnik. Statistical learning theory. Vol. 2. New York: Wiley, 1998.

[8]Joachims, Thorsten. Learning to classify text using support vector machines: Methods, theory and algorithms. Kluwer Academic Publishers, 2002.

[9]Lin, Yuan-Pin, Chi-Hong Wang, Tien-Lin Wu, Shyh-Kang Jeng, and Jyh-Horng Chen. "Support vector machine for EEG signal classification during listening to emotional music." In Multimedia Signal Processing, 2008 IEEE 10th Workshop on, pp. 127-130. IEEE, 2008. Doi: 10.1109/MMSP.2008.4665061.

[10]Panda, R., P. S. Khobragade, P. D. Jambhule, S. N. Jengthe, P. R. Pal, and T. K. Gandhi. "Classification of EEG signal using wavelet transform and support vector machine for epileptic seizure diction." In Systems in Medicine and Biology (ICSMB), 2010 International Conference on, pp. 405-408. IEEE, 2010. Doi: 10.1109/ICSMB.2010.5735413.

[11]Guo, Guodong, Stan Z. Li, and Kap Luk Chan. "Support vector machines for face recognition." Image and Vision computing 19, no. 9 (2001): 631-638, Elsevier. DOI: 10.1016/S0262-8856(01)00046-4.

[12]Navalyal, Geeta U., and Rahul D. Gavas. "A dynamic attention assessment and enhancement tool using computer graphics." Human-centric Computing and Information Sciences 4.1 (2014): 1-7, Springer. doi:10.1186/s13673-014-0011-0.

[13]Shankar, Sheela. "Assessment of the effect of variations in Eye Blinks on a face recognition algorithm." Advance Computing Conference (IACC), 2015 IEEE International. IEEE, 2015.

[14]Sheela Shankar and V.R Udupi, "Achieving Robustness in Face Recognition by Effective Feature Acquisition", IJIGSP, Vol. 7, No. 9, MECS Publisher.

[15]Navalyal, Geeta U., and Rahul D. Gavas, "Enhanced learning with abacus and its analysis using BCI technology", International Journal of Modern Education and Computer Science 6.9 (2014): 22.