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The Effects of Reactive MgO on the Mechanical Properties of Rock Flour Mortar

  • Ali HeidariEmail author
  • Masoumeh Hashempour
  • Hamed Javdanian
  • Mohammad Reza Nilforoushan
Research paper
  • 18 Downloads

Abstract

In this study, mechanical properties of rock flour mortar were investigated through experimental studies. The tests results were employed to assess compressive strength, water absorption and specific gravity of rock flour mortar in the presence of reactive MgO. The results showed that the use of rock flour-to-cement ratio of 1.5 with 2.5% magnesium oxide had the maximum compressive strength and adding more MgO to mortar could not play an effective role in strength property. Water absorption also increased with increasing amounts of magnesium oxide for almost all of the samples. In this study, the lowest water absorption was 11.16% for the sample containing 2% magnesium oxide and rock flour-to-cement ratio of 2.5. The specific gravity of the samples also increased with an increase in the amount of magnesium oxide which varied between 16.2 and 2.4 g/cm3. The field emission scanning electron microscope and energy-dispersive X-ray spectroscopy tests were also used to verify the results. In addition, backpropagation neural network was used for better parameter estimation. This network showed better precision for predicting the 28th day compressive strength with 0.936 regression.

Keywords

Mechanical properties Mortars Magnesia Rock flour 

References

  1. Aliabdo AA, Abd Elmoaty AEM, Auda EM (2014) Re-use of waste marble dust in the production of cement and concrete. Constr Build Mater 50:28–41CrossRefGoogle Scholar
  2. Aruntaş HY, Gürü M, Dayı M, Tekin İ (2010) Utilization of waste marble dust as an additive in cement production. Mater Des 31(8):4039–4042CrossRefGoogle Scholar
  3. Asghshahr MS, Rahai A, Ashrafi H (2016) Prediction of chloride content in concrete using ANN and CART. Mag Concr Res 68(21):1085–1098CrossRefGoogle Scholar
  4. Chen X, Hq Yang, Li W (2016) Factors analysis on autogenous volume deformation of MgO concrete and early thermal cracking evaluation. Constr Build Mater 118:276–285CrossRefGoogle Scholar
  5. Corinaldesi V, Moriconi G, Naik TR (2010) Characterization of marble powder for its use in mortar and concrete. Constr Build Mater 24(1):113–117CrossRefGoogle Scholar
  6. Dogan E (2008) Reference evapotranspiration estimation using adaptive neuro-fuzzy inference system. J Irrig Drain 58(5):617–628CrossRefGoogle Scholar
  7. Du C (2006) A review of magnesium oxide in concrete. Cem Concr World 59:53–63Google Scholar
  8. Dung NT, Unluer C (2016) Improving the performance of reactive MgO cement-based concrete mixes. Constr Build Mater 126:747–758CrossRefGoogle Scholar
  9. Ergün A (2011) Effects of the usage of diatomite and waste marble powder as partial replacement of cement on the mechanical properties of concrete. Constr Build Mater 25(2):806–812CrossRefGoogle Scholar
  10. Freeman J (1994) Simulating neural networks. Addison-Wesley Publishing Company, New YorkGoogle Scholar
  11. Harrison A (2003) New cements based on the addition of reactive magnesia to Portland cement with or without added pozzolan. In: Proc., CIA conference: concrete in the Third Millenium, CIA: Brisbane, AustraliaGoogle Scholar
  12. Heidari A, Hashempour M (2018) Investigation of mechanical properties of self compacting polymeric concrete with backpropagation network. Int J Eng 31(6):903–909Google Scholar
  13. Heidari A, Tavakoli D (2013) A study of the mechanical properties of ground ceramic powder concrete incorporating nano-SiO2 particles. Constr Build Mater 38:255–264CrossRefGoogle Scholar
  14. Heidari A, Hashempour M, Javdanian H, Shahi M (2017a) The investigation of reactive MgO on waste concrete properties. In: The nineth national ICI conference, Tehran, Iran (Farsi)Google Scholar
  15. Heidari A, Hashempour M, Tavakoli D (2017b) Using of backpropagation neural network in estimating of compressive strength of waste concrete. Soft Comput Civ Eng 1(1):54–64Google Scholar
  16. Heidari A, Hashempour M, Javdanian H, Karimian M (2018a) Investigation of mechanical properties of mortar with mixed recycled aggregates. Asian J Civ Eng 19(5):583–593CrossRefGoogle Scholar
  17. Heidari A, Hashempour M, Delshad Chermahini M (2018b) Influence of reactive MgO hydration and cement content on C&DW aggregate concrete characteristics. Int J Civ Eng.  https://doi.org/10.1007/s40999-018-0361-5 CrossRefGoogle Scholar
  18. Javdanian H, Jafarian Y, Haddad A (2015) Predicting damping ratio of fine-grained soils using soft computing methodology. Arab J Geosci 8(6):3959–3969CrossRefGoogle Scholar
  19. Li FX, Chen YZ, Long SZ, Wang B, Li GG (2010) Research on the preparation and properties of MgO expansive agent. Adv Cem Res 22(1):37–44CrossRefGoogle Scholar
  20. Mo L, Zhang F, Deng M, Panesar DK (2016) Effectiveness of using CO2 pressure to enhance the carbonation of Portland cement-fly ash-MgO mortars. Cem Concr Compos 70:78–85CrossRefGoogle Scholar
  21. Pu L, Unluer C (2016) Investigation of carbonation depth and its influence on the performance and microstructure of MgO cement and PC mixes. Constr Build Mater 120:349–363CrossRefGoogle Scholar
  22. Rodrigues R, de Brito J, Sardinha M (2015) Mechanical properties of structural concrete containing very fine aggregates from marble cutting sludge. Constr Build Mater 77:349–356CrossRefGoogle Scholar
  23. Ruan S, Unluer C (2017) Influence of mix design on the carbonation, mechanical properties and microstructure of reactive MgO cement-based concrete. Cement Concr Compos 80:104–114CrossRefGoogle Scholar
  24. Salajegheh E, Heidari A (2004a) Optimum design of structures against earthquake by adaptive genetic algorithm using wavelet networks. Struct Multidiscip Optim 28(4):277–285CrossRefGoogle Scholar
  25. Salajegheh E, Heidari A (2004) Optimum design of structures against earthquake by discrete wavelet neural network. Paper presented at the 7th International Conference on Computational Structures Technology, Lisbon, PortugalGoogle Scholar
  26. Salajegheh E, Heidari A (2005) Optimum design of structures against earthquake by wavelet neural network and filter banks. Earthq Eng Struct Dyn 34(1):67–82CrossRefGoogle Scholar
  27. Shand MA (2006) The chemistry and technology of magnesia. Wiley, HobokenCrossRefGoogle Scholar
  28. Tavakoli D, Hashempour M, Heidari A (2018) Use of waste materials in concrete: a review. Pertanika J Sci Technol 26(2):499–522Google Scholar
  29. Taylor JG, Mannion CLT (1992) Theory and application of neural networks. Springer, BerlinCrossRefGoogle Scholar
  30. Ukrainczyk N, Ukrainczyk V (2008) A neural network method for analysing concrete durability. Mag Concr Res 60(7):475–486CrossRefGoogle Scholar
  31. Unluer C, Al-Tabbaa A (2013) Impact of hydrated magnesium carbonate additives on the carbonation of reactive MgO cements. Cem Concr Res 54:87–97CrossRefGoogle Scholar
  32. Unluer C, Al-Tabbaa A (2014a) Enhancing the carbonation of MgO cement porous blocks through improved curing conditions. Cem Concr Res 59:55–65CrossRefGoogle Scholar
  33. Unluer C, Al-Tabbaa A (2014b) Characterization of light and heavy hydrated magnesium carbonates using thermal analysis. J Therm Anal Calorim 115(1):595–607CrossRefGoogle Scholar
  34. Vandeperre LJ, Al-Tabbaa A (2007) Accelerated carbonation of reactive MgO cements. Adv Cem Res 19(2):67–79CrossRefGoogle Scholar
  35. Vandeperre LJ, Liska M, Al-Tabbaa A (2008) Hydration and mechanical properties of magnesia, pulverized fuel ash, and portland cement blends. J Mater Civ Eng 20(5):375–383CrossRefGoogle Scholar
  36. Vardhan K, Goyal S, Siddique R, Singh M (2015) Mechanical properties and microstructural analysis of cement mortar incorporating marble powder as partial replacement of cement. Constr Build Mater 96:615–621CrossRefGoogle Scholar
  37. Yi Y, Liska M, Al-Tabbaa A (2014) Properties and microstructure of GGBS—magnesia pastes. Adv Cem Res 26(2):114–122CrossRefGoogle Scholar

Copyright information

© Shiraz University 2018

Authors and Affiliations

  • Ali Heidari
    • 1
    Email author
  • Masoumeh Hashempour
    • 1
  • Hamed Javdanian
    • 1
  • Mohammad Reza Nilforoushan
    • 2
  1. 1.Department of Civil EngineeringShahrekord UniversityShahrekordIran
  2. 2.Department of Materials EngineeringShahrekord UniversityShahrekordIran

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