A Scheffe’s Predictive Model for Modulus of Elasticity of Sawdust Ash - Sand Concrete

  • Kenneth Miebaka Oba Lecturer, Department of Civil Engineering, Faculty of Engineering, Rivers State University, P.M.B 5080, Port Harcourt, NIGERIA
  • Onuegbu Okoronkwo Ugwu Professor, Department of Civil Engineering, Faculty of Engineering and Technology, Alex Ekwueme Federal University, P.M.B 1010, Ndufu-Alike, Abakaliki, NIGERIA
Keywords: Saw Dust Ash, Scheffe’s Simplex Lattice, Sustainability, Modulus of Elasticity of Concrete

Abstract

The industrial waste, Saw Dust Ash (SDA) has been explored by several concrete related researches to achieve environmental and economic sustainability. In this study, 5% of sand was replaced with SDA to produce concrete with five different mix ratios. Scheffe’s simplex theory was used for five mix ratios in a {5,2} experimental design which resulted in additional ten mix ratios. For purposes of verification and testing, additional fifteen mix ratios were generated from the initial fifteen. Concrete cubes of 150mmX150mmX150mm were formed using the thirty concrete mix ratios generated, and cured in water for 28days. The compressive strengths of cubes from each mix ratio were determined. The static moduli of elasticity were also determined with a mathematical relationship. The results of the first fifteen static moduli of elasticity values were used for the calibration of the model constant coefficients, while those from the second fifteen were used for the model verification and testing using Scheffe’s simplex lattice design. A mathematical regression model was formulated from the results, with which the static moduli of elasticity were predicted. The model was then subjected to a two-tailed t-test with 5% significance, which confirms the model adequate and fit with an R2 of 0.8536. The study also revealed that SDA can be used to replace 5% of sand and promote environmental sustainability without significantly decreasing the static modulus of elasticity.

Downloads

Download data is not yet available.

References

A. M. Neville & J. J. Brooks. (1987). Concrete technology. (2nd ed.). New Delhi: Pearson Education.

M. S. Mamlouk & J. P. Zaniewski. (2011). Materials for Civil and Construction Engineers. (3rd ed.) New Jersey: Pearson Prentice Hall.

T. G. C. Awodiji, J. O. Dimo, C. Nwurumibe, O. O. Awodiji, & I. J. Arimanwa. (2019). Reactions of hydrated lime-saw dust ash blend on the strength properties of cement concrete. Glob. J. Res. Eng., 19(3), 28–39.

H. Gil, A. Ortega, & J. Pérez. (2017). Mechanical behavior of mortar reinforced with sawdust waste. In: 3rd International Conference on Natural Fibers: Advanced Materials for a Greener World, ICNF, 200, pp. 325–332.

C. Marthong. (2012). Sawdust Ash (SDA) as partial replacement of cement. Int. J. Eng. Res. Appl., 2(4), 1980–1985.

S. Chowdhury, M. Mishra, & O. Suganya. (2015). The incorporation of wood waste ash as a partial cement replacement material for making structural grade concrete : An overview. Ain Shams Eng. J., 6, 429–437.

M. Mageswari & B. Vidivelli. (2009). The use of sawdust ash as fine aggregate replacement in concrete. J. Environ. Res. Dev., 3(3), 720–726.

S. T. Tyagher, J. T. Utsev, & T. Adagba. (2011). Suitability of saw dust ash-lime mixture for production of sandcrete hollow blocks. Niger. J. Technol., 30(1), 1–6.

ASTM.C618. (2000). Standard specification for coal fly ash and raw or calcined natural pozzolan for use as a mineral admixture in concrete. West Conshohocken: American Society for Testing and Materials.

M. E. Onyia. (2017). Optimisation of the cost of lateritic soil stabilized with quarry dust. Int. J. Sci. Eng. Res., 8(9), 1400–1413.

C. U. Anya. (2015). Models for predicting the structural characteristics of sand-quarry dust blocks. Ph.D Thesis, Department of Civil Engineering, University of Nigeria, Nsukka.

O. M. I., bearugbulem, L. O. Ettu, J. C. Ezeh, & U. C. Anya. (2013). A new regression model for optimizing concrete mixes. Int. J. Eng. Sci. Res. Technol., 2(7), 1735–1742.

Y. M. Gamil & I. H. Bakar. (2015). The development of mathematical prediction model to predict resilient modulus for natural soil stabilised by POFA-OPC additive for the use in unpaved road design. In: Soft Soil Engineering International Conference, pp. 1–11.

P. N. Onuamah. (2015). Development-and-optimization-of-mechanical-strength-model-of-cement-laterite-sand-hollow-sandcrete-blocks.docx. Int. J. Sci. Eng. Res., 6(5), 645–655.

P. N. Onuamah. (2015). Prediction-of-the-compressive-strength-of-concrete-with-palm-kernel-aggregate-using-the-artificial-neutral-networks-approach.docx. Int. J. Sci. Eng. Res., 6(6), 962–969.

N. N. Osadebe, C. C. Mbajiorgu, & T. U. Nwakonobi. (2007). An optimization model development for laterized- Concrete mix proportioning in building constructions. Niger. J. Technol., 26(1), 37–46.

K. M. Oba, O. O. Ugwu, & F. O. Okafor. (2019). Development of a model to predict the flexural strength of concrete using SDA as partial replacement for fine aggregate. Int. J. Sci. Eng. Res., 10(5), 1216–1224.

K. M. Oba, O. O. Ugwu, and F. O. Okafor. (2019). Development of scheffe’s model to predict the compressive strength of concrete using SDA as partial replacement for fine aggregate. Int. J. Innov. Technol. Explor. Eng., 8(8), 2512–2521.

K. M. Oba. (2019). A mathematical model to predict the tensile strength of asphalt concrete using quarry dust filler. Int. J. Sci. Eng. Res., 10(2), 1491–1498.

C. E. Okere, D. O. Onwuka, S. U. Onwuka, & J. I. Arimanwa. (2013). Simplex-based concrete mix design. IOSR J. Mech. Civ. Eng., 5(2), 46–55.

E. M. Mbadike & N. N. Osadebe. (2014). Five component concrete mix optimization of aluminum waste using Scheffe’s theory. Int. J. Comput. Eng. Res., 4(4), 23–31.

E. M. Mbadike & N. N. Osadebe. (2013). Application of Scheffe’s model in optimization of compressive strength of lateritic concrete. J. Civ. Eng. Constr. Technol., 4(9), 265–274.

L. Brown, A. N. Donev, & A. T. Biessett. (2015). General blending models for data from mixture experiments. Technometrics, 57(4), 449–456.

H. Scheffe. (1958). Experiments with mixtures. J. R. Stat. Ser. B, 25(2), 235–263.

K. M. Oba & I. G. Amadi. (2020). A predictive mathematical model for water absorption of sawdust ash - Sand concrete. Int. J. Eng. Manag. Res., 10(01), 33–41.

Published
2021-02-05
How to Cite
Kenneth Miebaka Oba, & Onuegbu Okoronkwo Ugwu. (2021). A Scheffe’s Predictive Model for Modulus of Elasticity of Sawdust Ash - Sand Concrete. International Journal of Engineering and Management Research, 11(1), 9-17. https://doi.org/10.31033/ijemr.11.1.2