Advertisement

New Prediction Models for Compressive Strength of GGBS-Based Geopolymer Clays Using Swarm Assisted Optimization

  • T. Vamsi NagarajuEmail author
  • Ch. Durga Prasad
Conference paper
Part of the Lecture Notes in Civil Engineering book series (LNCE, volume 55)

Abstract

This paper discusses experimental data on unconfined compressive strength (UCS) of an expansive soil chemically altered with GGBS-based geopolymer with varying amounts of GGBS content. Ground granulated blast furnace slag (GGBS) was added to the expansive soil up to 25% in increments of 5%. Scanning Electron Microscopy (SEM) analysis was undertaken to know the microstructural development in the GGBS-based geopolymer clay blends. The unconfined compressive strength (UCS) of the GGBS-based geopolymer clay blends increased with increasing additive content. This paper also presents the viability of particle swarm optimization (PSO) technique in predicting 28 days UCS of alkali-activated blended expansive clays. With availability of limited experimental data accurate estimation is possible with PSO. In multilinear model UCS equation, the coefficients are adjusted by PSO has been developed for the prediction of UCS for geotechnical designs is the key factor presented in this paper.

Keywords

Alkali-activation Expansive clay GGBS PSO Unconfined compressive strength 

References

  1. 1.
    AlRashidi MR, El-Hawary ME (2006) A survey of particle swarm optimization applications in electric power systems. IEEE Trans Evol Comput.  https://doi.org/10.1109/TEVC.2006.880326CrossRefGoogle Scholar
  2. 2.
    Botao L, Cerato Amy B (2012) Prediction of expansive soil swelling based on four micro-scale properties. Bull Eng Geol Environ 71:71–78CrossRefGoogle Scholar
  3. 3.
    Chen FH (1988) Foundations on expansive soils. Elsevier Scientific Publishing Co., AmsterdamGoogle Scholar
  4. 4.
    Gourley CS, Newill D, Schreiner HD (1993) Expansive soils: TRL’s research strategy. In: Proceedings, 1st international symposium on engineering characteristics of arid soils, LondonGoogle Scholar
  5. 5.
    Hajihassani M, Armaghani DJ, Kalatehjari R (2017) Applications of particle swarm optimization in geotechnical engineering: a comprehensive review. Geotech Geol Eng.  https://doi.org/10.1007/s10706-017-0356-zCrossRefGoogle Scholar
  6. 6.
    Itthikorn P, Suksun H, Tanakorn P, Arul A, Shui-Long S (2016) Marginal lateritic soil stabilized with calcium carbide residue and fly ash geopolymers as a sustainable pavement base material. J Mater Civ Eng ASCE 29(2):04016195Google Scholar
  7. 7.
    Kennedy J, Eberhart R (1995) Particle Swarm Optimization. In: IEEE, 0-7803-2768-3/95, pp 1942–1948Google Scholar
  8. 8.
    Phanikumar BR, Nagaraju TV (2018) Engineering behaviour of expansive clays blended with cement and GGBS. Ground Improv.  https://doi.org/10.1680/jgrim.17.00054CrossRefGoogle Scholar
  9. 9.
    Phanikumar BR, Nagaraju TV (2018) Swell compressibility characteristics of expansive clay lumps and powders blended with GGBS—a comparison. Indian Geotech J, ISSN 2277–3347:1–9Google Scholar
  10. 10.
    Ruhul Amin Mozumder and Aminul Islam Laskar (2015) Prediction of unconfined compressive strength of geopolymer stabilized clayey soil using artificial neural network. Comput Geotech 69:291–300CrossRefGoogle Scholar
  11. 11.
    Ramesh HNG, Sivapullaiah PV (2010) Role of moulding water content in lime stabilization of soil. Ground Improv 64(1):15–19CrossRefGoogle Scholar
  12. 12.
    Ranganatham BV, Sathyanarayana B (1965) A rational method of predicting swelling potential for compacted expansive clays, In: Proceedings of the 6th international conference on S.M. and F.E., Canada, vol 1, pp 92–96Google Scholar
  13. 13.
    Sarat KD, Pijush S, Akshaya Kumar S, Sitharam TG (2010) Prediction of swelling pressure of soil using artificial intelligence techniques. Environ Earth Sci 16:393–403Google Scholar
  14. 14.
    Shaymaa A, Nima F, Afshin A, Bujang KM (2017) Collapsibility potential of gypseous soil stabilized with fly ash geopolymer; characterization and assessment. Constr Build Mater 137:390–409CrossRefGoogle Scholar

Copyright information

© Springer Nature Singapore Pte Ltd. 2020

Authors and Affiliations

  1. 1.Department of Civil EngineeringS. R. K. R Engineering CollegeBhimavaramIndia
  2. 2.Department of Electrical EngineeringS. R. K. R. Engineering CollegeBhimavaramIndia

Personalised recommendations