• T. Chinnababu
• D. Prudhvi Raju
• G.L.V. Krishnam Raju
• T. Vamsi Nagarju

In this paper, we propose novel nature inspired meta herustic optimization i.e., particle swarm optimization (PSO) to predict the 28-day compressive strength of geopolymer mortars. To construct and validate these models, 81 different mixes with 243 specimens were casted and tested. Seven input parameters were used to predict the tested compressive strength of geopolymer mortars, i.e., the sodium solution (NaOH) concentration (varied as 8M, 11M and 14 M), the mass ratio of alkaline activation solution to precursor content, variation of precursors and their contents, Na/Al ratio and Si/Al ratio . The compressive strength of the fabricated geopolymer mortars was used as output parameter for the prediction models. Validation of the models was done using several criteria’s such as variation of inertia weight and incorporating damping coefficient. The results show that the PSO models have strong potential for predicting the 28-day compressive strength of geopolymer mortars. This study will help in reducing the time and cost for the implementation of laboratory experiments in designing the optimum proportions of geopolymer specimens.

Alkali-activation, PSO, Optimization, compressive strength

"Estimation of Compressive Strength of Geopolymer Mortars using Nature Inspired Algorithm", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.6, Issue 6, page no.574-577, June 2019, Available :http://www.jetir.org/papers/JETIR1906T69.pdf

"Estimation of Compressive Strength of Geopolymer Mortars using Nature Inspired Algorithm", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.6, Issue 6, page no. pp574-577, June 2019, Available at : http://www.jetir.org/papers/JETIR1906T69.pdf