Geopolymer concrete (GPC) holds promise as a substitute for traditional concrete, primarily due to its environmental benefits; however, because of the intricate physical and chemical interactions that are a part of the geopolymerization process, developing a reliable forecasting model for compressive strength becomes challenging. Therefore, this study presents a comparative analysis of the neural network model (Artificial Neural Networks, ANN)) and tree-based model (Decision Tree, DT) to forecast the compressive strength properties of ground granulated blast furnace slag (GGBS) based GPC. This study utilized 558 datasets on GGBS-based GPC extracted from various literature sources, incorporating eleven input variables. The predictive performance of all the studied models was validated by analyzing performance metrics such as MSE, MAPE, RMSE, MAE and R2 values. The findings showed that, with a R2 value of 0.943, the ANN model performed better than the DT model in forecasting the compressive strength parameters of GPC made with GGBS. The lower error values (MAE, MSE, MAPE, and RMSE) and higher R2 values strongly indicated the ANN model’s enhanced performance. The results of the input parameter sensitivity carried on the ANN model showed that the specimen’s age, sodium hydroxide molarity, and curing temperature substantially impacted the compressive strength.
Geopolymer binders such as ground granulated blast furnace slag (GGBS) and fly ash (FA) have been promisingly surfaced as probable alternatives to ordinary portland cement (OPC) in concrete preparation over the last few decades. The production of geopolymer concrete (GPC) generates approximately 30 - 50 % less carbon-dioxide (CO2) gas emissions than OPC concrete. GPC not only reduces 2 emissions, but it also uses industrial solid wastes. To achieve optimum mechanical strength, three parameters which play crucial roles have been considered: Molarity of sodium hydroxide (NH) concentration, solution to binder ratio (S/B) and sodium silicate-sodium hydroxide (NS/ NH) proportion. So, in present paper, the mechanical and microstructural characteristics of GPC cured at ambient curing condition using several mixes prepared with varying NaOH concentrations (10 M - 16 M), solution to binder ratios (total alkali activator/total binder content) (0.45 - 0.55) and sodium silicate (NS) to (NH) ratios (1.5 - 2.5) has been investigated. In addition to this, for a conceptualization of environmental impact of GPC, life-cycle assessment (LCA) has been performed.
Concrete is the most fundamental material used in the construction work. It requires a huge quantity of water to cure. An effective remedy for this issue is self-curing, which uses chemicals rather than water to cure it. This study looks into the efficacy of self-curing technology and how it impacts concrete's strength. The curing agent used in the current investigation is polyethylene glycol (PEG-400) is added in concrete through casting. The study concludes that self-curing is an effective curing method, outperforming traditionally cured concrete. The split tensile strength of the M20 and M25 self-curing concrete improves by a margin of 36.25 and 18.81 %, respectively.
Developing countries like India need to address the utilization of agroindustrial waste such as sugarcane bagasse ash (SCBA) to tackle environmental concerns and reduce the consumption of expensive raw materials such as cement for making selfcompacting concrete (SCC). An attempt has been made to partially replace ordinary Portland cement by employing raw SCBA as one of the constituent materials in the SCC. The raw SCBA in SCC mixtures was varied in between 7.5 to 25 % and the hardened concrete was subjected to mechanical and physical tests. The compressive strength of SCC was found to increase with the curing period and the highest values were recorded after 28 days. Further, the ultrasonic pulse velocity test revealed excellent quality and high structural integrity for concrete having 25 % SCBA and cured at 56 days due to high density and strong intergranular bonding. The rapid chloride ion penetration test showed better resistance to chloride ion penetration. Overall the study suggests the employability of agricultural waste such as raw SCBA as potential cement replacement material in making SCC in the construction industry.
December 2024
Volume - 98
Number : 12
November 2024
Volume - 98
Number : 11
October 2024
Volume - 98
Number : 10
September 2024
Volume - 98
Number : 09
August 2024
Volume - 98
Number : 08
July 2024
Volume - 98
Number : 07
June 2024
Volume - 98
Number : 06
May 2024
Volume - 98
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April 2024
Volume - 98
Number : 04
March 2024
Volume - 98
Number : 03
February 2024
Volume - 98
Number : 02