Abstract

The desire to make the concrete industry more environmentally friendly has existed for a long time. Geopolymer concrete, which uses industrial or agricultural by-product ashes as the primary source of binder materials instead of Portland cement, has emerged as a viable building material due to the environmental concerns associated with cement production. One of the most important mechanical parameters for all types of concrete composites, including geopolymer concrete, is compressive strength. This parameter is influenced by a variety of factors, including the alkaline solution to binder ratio, the type and amount of binder, the chemical composition of the binder materials, the amount of aggregate present, the type and amount of alkaline solutions, the ratio of alkaline liquid to binder materials, the curing regime, and the age of the specimens. In this context, a detailed systematic assessment was conducted to demonstrate the effect of these various parameters on the compressive strength of fly ash-based geopolymer concrete (FA-GPC). In addition, multi-scale models such as artificial neural networks, M5P-tree, linear regression, and multi-logistic regression models were developed to predict the compressive strength of FA-GPC composites. Results show that the curing temperature (between 60 °C to 90 °C), sodium silicate to sodium hydroxide ratio (between 1.5 to 2.5), and the alkaline solution to the binder ratio (between 0.35 to 0.5) are those parameters that govern the compressive strength of the FA-GPC. Furthermore, based on the statistical assessment tools, the ANN model has better performance for predicting the compressive strength of FA-GPC than the other developed models as it has the highest value of the coefficient of determination (0.96), lower values of the root mean squared error (3.33), mean absolute error (2.58), objective function value (2.91), and scatter index (0.109).

摘要

让混凝土行业更加环保的愿望由来已久。地质聚合物混凝土使用工业或农业副产品灰烬作为粘合剂材料的主要来源，而不是硅酸盐水泥，由于与水泥生产相关的环境问题，它已成为一种可行的建筑材料。对于包括地质聚合物混凝土在内的所有类型的混凝土复合材料，最重要的机械参数之一是抗压强度。该参数受多种因素影响，包括碱性溶液与粘合剂的比例、粘合剂的类型和数量、粘合剂材料的化学成分、存在的骨料数量、碱性溶液的类型和数量、碱性液体到粘合剂材料、固化方式和样品的使用年限。在这种情况下，进行了详细的系统评估，以证明这些不同参数对粉煤灰基地质聚合物混凝土 (FA-GPC) 抗压强度的影响。此外，开发了人工神经网络、M5P 树、线性回归和多逻辑回归模型等多尺度模型来预测 FA-GPC 复合材料的抗压强度。结果表明，固化温度（60 °C 至 90 °C）、硅酸钠与氢氧化钠的比例（1.5 至 2.5 之间）以及碱性溶液与粘合剂的比例（0.35 至 0.5 之间）是控制固化的参数FA-GPC 的抗压强度。此外，基于统计评估工具，