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首页> 外文期刊>ceramics >EMPIRICAL MODELLING OF THE COMPRESSIVE STRENGTH OF AN ALKALINE ACTIVATED NATURAL POZZOLAN AND LIMESTONE POWDER MORTAR
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EMPIRICAL MODELLING OF THE COMPRESSIVE STRENGTH OF AN ALKALINE ACTIVATED NATURAL POZZOLAN AND LIMESTONE POWDER MORTAR

机译:碱活性天然波佐和石灰石粉砂浆抗压强度的实证模型

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摘要

An experimental investigation was conducted to synthesise an alkali-activated binder using natural pozzolan and limestone powder. The effect of the mix parameters such as the binder ratio, NaOH molarity (4 -14 M), curing temperature (25 - 90 degrees C), sodium silicate to sodium hydroxide ratio (0.5 - 1.5), fine aggregate to binder ratio (1.4 - 2.2), alkaline activator to binder ratio (0.45 - 0.55) and curing days (1, 3, 7, 14, 28) were determined on the compressive strength of the mortar. A stepwise regression algorithm was developed to estimate the compressive strength of the mortar. Five different models (I-V) were developed using 130 experimental data sets with seven descriptors. Bayesian information criterion (BIC), Akaike's information criterion (AIC) and the sum of square error (SSE) criteria were used to fit the developed model in order to select the best model. The cubic with interactions model (V) is characterised with a high correlation coefficient (97.2 %), the lowest root means square error (1.672), and the lowest mean absolute error (1.313) in comparison with the other four models (I-IV). The outcomes of this work could provide an effective and efficient way of modelling the compressive strength of environmentally friendly binders with minimal experimental stress, limit the uncertainties and errors inherent in a laboratory.
机译:进行了一种实验研究,用天然波佐仑和石灰石粉合成碱活化粘合剂。混合参数如粘合剂比,NaOH摩尔性(4-14米),固化温度(25-90℃),硅酸钠对氢氧化钠比(0.5-1.5),细聚集成粘合剂比例(1.4 - 2.2),对粘合剂比(0.45-0.55)和固化天(1,3,7,14,28)的碱性活化剂造成砂浆的抗压强度。开发了一种逐步回归算法以估计砂浆的抗压强度。使用具有七个描述符的130个实验数据集开发了五种不同的模型(I-V)。贝叶斯信息标准(BIC),Akaike的信息标准(AIC)和方误差(SSE)标准的总和用于符合开发的模型,以选择最佳模型。与相互作用模型(V)的立方体具有高相关系数(97.2%),最低根部误差(1.672),与其他四个模型相比,最低的平均绝对误差(1.313)(I-IV )。这项工作的结果可以提供一种以最小的实验压力建模对环境友好粘合剂的抗压强度的有效和有效的方法,限制了实验室中固有的不确定性和误差。

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