Abstract

Geopolymer Concrete (GPC) is a new class of concrete that presents a vital improvement in sustainability and the environment, particularly in recycling and alternative construction methods. Geopolymers offer a sustainable, low energy consumption, low carbon footprint, and a 100% substitute for the Portland cement binder for civil infrastructure applications. Furthermore, many aluminosilicate materials can be obtained as by-products of other processes, such as coal combustion or the thermal pulping of wood. In addition, slag and fly ash are necessary to source materials for geopolymer. Therefore, geopolymer is considered a solution for waste management that can minimize greenhouse gas emissions. In this statistical study, the present experimental work and found experimental data were collected from local and international literature and were used to build and validate the statistical models to predict the strength development of Geopolymer concrete with binary and ternary systems of source materials. The main independent variable was R, representing the ratio of SiO2/Al2O3by weight in the source material. The investigated range of R was 1.42–3.6. Nine concrete geopolymer mixes with R in the above range represent the experimental part carried out. The targeted properties were compressive, splitting, and flexural strengths. The experimental results showed that the R ratio significantly influences the mechanical performance of the final product. The compressive strength improved by 82, 86, 93, and 95%, when metakaolin content was partially replaced by fly ash and GGBS by percentages of 30, 70, 72, 90, and 95% for mixes 2, 3, 5, 7, and 8 respectively. Also, when GGBS partially replaced fly ash content by 36% and 100% for mixes 6 and 9, compressive strength improved by 10.6% and 41.8%, respectively, compared to mix4. Furthermore, the statistical study revealed that the R ratio might be utilized to determine geopolymer strength with reasonable accuracy. The built models were developed by linear and non-linear regression analysis using SPSS software, version 25. Doi: 10.28991/CEJ-2022-08-03-04 Full Text: PDF

Highlights

  • Geopolymer Concrete (GPC) is a form of inorganic polymer composite that has recently emerged as a promising binding medium based on new engineering material usage

  • When metakaolin content was partially replaced by fly ash and ground granulated blast furnace slag (GGBS) in mixes 2, 3, 5, 7, and 8, compressive strength improved by 82%, 86%, 93%, and 95%, respectively to mix1

  • When fly ash content was fully or partially replaced by GGBS in mixes 6 and 9, compressive strength improved by 10.6% and 41.8%, respectively, when compared to mix 4

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Summary

Introduction

Geopolymer Concrete (GPC) is a form of inorganic polymer composite that has recently emerged as a promising binding medium based on new engineering material usage. Chen-Tan et al [17] demonstrated that not all amorphous SiO2 and Al2O3 in fly ash-based Geopolymer systems were involved in the process They showed that, complete dissolution of all amorphous SiO2 and Al2O3 phases is not needed, the quality of the end product may be improved if the aluminosilicate source material has a significant percentage of amorphous silica and alumina phases. The motive is often economical to save money, time, or another essential resource [21] This part of the work aims to build a specified statistical model for predicting compressive strength for Geopolymer concrete that is produced in Iraq, By elucidating the unique chemistry involved in the formation of SiO2/Al2O3 GPC, commonly referred to as poly(sialate) Geopolymers, as well as to investigate the effect of R ratio (1.42-3.6) on strength development when ternary and binary binder materials are used to meet the requirements for fresh and hardening properties of GPC, as these parameters are known to have a significant effect. Statistical models were built to predict the strength development of Geopolymer concrete

A Statistical Model to Predict Strength Development
Used Materials
Geopolymer Concrete Mixes
Compressive Strength
Splitting Tensile Strength
Flexural strength
Data Collection for Building and Validating the Model
Compressive Strength Model
Validation of Compressive Strength Model
Relationship Model between Different Types of Strength
Conclusions
Author Contributions
Full Text
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