International Journal of Applied Science and Engineering
Published by Chaoyang University of Technology

Rachna Aggarwala*, Maneek Kumarb, R.K. Sharmac, and M.K. Sharmac

aDepartment of Mathematics, M.L.N. College, Yamuna nagar, Haryana, India
bDepartment of Civil Engineering, Thapar University, Patiala, India
cSchool of Mathematics and Computer Application, Thapar University, Patiala, India


 

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ABSTRACT


This paper deals with development of regression models for prediction of compressive strength of concrete. The compressive strength of concrete is predicted using four variables, namely, water-binder ratio, fine aggregate-binder ratio, coarse aggregate-binder ratio and binder content. Linear regression models have been developed for variations in fly ash replacements (0 and 15 percent), Zones of aggregates (A, B and C) and curing ages (28, 56 and 91 days). An effort has also been made to modify the linear models using a two step approach. First step is to develop quadratic models (termed as full models) by identifying the suitable combinations of the four variables described above. The second step is to select the best minimal subset of the predictors in full models using Mallow’s Cp statistic. The proposed quadratic regression models yielded coefficient of determination R2 ≥ 0.99 in almost every case except for concrete with Zones A and B of aggregates without fly ash for 91 days curing period and for concrete with Zone C of aggregates without fly ash for 56 days curing period.


Keywords: Concrete; compressive strength; regression models


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REFERENCES


 

  1. [1] Nipatsat, N. and Tangtermsirikul, S. 2000. Compressive strength prediction model for fly ash Thammasat International Journal of Science and Technology, 5: 1-7.

  2. [2] Kazberuk, M.K. and Lelusz, M. 2006. Strength development of concrete with fly ash addition. Journal of Civil Engineering and Management, 13: 115-122.

  3. [3] Namyong, J., Sangchun, Y., and Hongbum, C. 2006. Prediction of compressive strength of in-situ concrete based on mixture proportions. Journal of Asian Architecture and Building Engineering, 3: 9-16.

  4. [4] Pande, A.M. and Gupta, L.M. 2007. Proportions of concrete ingredients and their significance in compressive strength development. The Indian Concrete Journal, 81: 15-36.

  5. [5] Chakraverty, S., Saini Himani and Panigrahi, S.K. 2008. Prediction of compressive strength using simplex lattice design for mixture proportions in ternary systems of fly ash-cement-sand particles. The Indian Concrete Journal, 82: 27-34.

  6. [6] Abd, S.M., Zain, M.F.M., and Hamid, R.A. 2008. Modeling the prediction of compressive strength of cement and foam concrete, Proceedings of International Conference on Construction and Building Technology, Kuala Lumpur, Malaysia, 16-20 June.

  7. [7] Abd, S.M. and Zain, M.F.M. 2009. Multiple regression model for compressive strength prediction of high performance concrete. Journal of Applied Sciences, 9: 155-160.

  8. [8] Abdullahi, M., Al-Mattarneh, H.M.A., and Mohammed, B.S. 2009. Statistical Modeling of lightweight concrete mixtures. European Journal of Scientific Research, 31: 124-131.

  9. [9] Al Qadi, A.N.S., Mustapha, K.N.B., Al-Mattarneh, H. and Al-Kadi, Q.N.S. 2009. Statistical models for hardened properties of self-compacting concrete. American Journal of Engineering and Applied Sciences, 2: 764-790.

  10. [10] Chen Li 2010. A multiple linear regression prediction of concrete compressive strength based on physical properties of electric arc furnace oxidizing slag. International Journal of Applied Science and Engineering, 7: 153-158.

  11. [11] Ramugade, P.D. 2010. Estimating compressive strength. The Indian Concrete Journal, 84: 35-44.

  12. [12] Wu, S.S., Li, B.Z., Yang, J.G., and Shukla, S.K. 2010. Predictive modeling of high-performance concrete with regression analysis, Proceedings of IEEE International Conference on Industrial Engineering and Engineering Management, Macao, December.

  13. [13] Kumar Maneek 2003. “Reliability based design of structural elements”. PhD thesis, Thapar University, Patiala, India.

  14. [14] Mallows, C.L. 1973. Some comments on Cp. Technometrics, 15: 661-675.


ARTICLE INFORMATION


Received: 2014-05-01
Revised: 2015-03-23
Accepted: 2015-04-29
Available Online: 2015-06-01


Cite this article:

Aggarwal, R., Kumar, M., Sharma, R.K., Sharma, M.K. 2015. Predicting compressive strength of concrete. International Journal of Applied Science and Engineering, 13, 171–185. https://doi.org/10.6703/IJASE.2015.13(2).171


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