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Application of response surface methodology to optimize alkali‐activated slag mortar with limestone powder and glass powder
Structural Concrete ( IF 3.0 ) Pub Date : 2020-09-09 , DOI: 10.1002/suco.202000018
Lanfang Zhang 1 , Jianjin Zhai 2
Affiliation  

An experimental and statistical investigation is carried out to analyze the influences of three variables (limestone powder, glass powder, and alkali content) on performance of alkali activated slag mortar. Response surface methodology (RSM) was used to model all measured responses like 28‐day flexural and compressive strength, water absorption, and dry shrinkage. Analysis of variance showed that all developed models were statistically significant. The interaction between the corresponding variables was analyzed using three‐dimensional response surface plots that were drawn using developed regression models. Optimization was performed using desirability approach of the RSM with an objective to maximize 28‐day flexural and compressive strength while minimizing water absorption and drying shrinkage. The optimum values of limestone powder, glass powder, and alkali content with highest desirability of 0.706 are 15.80, 17.02, and 6.71%, respectively. The predicted combination was validated by confirmatory tests and the error in prediction was found to be within 3.5%.

中文翻译:

应用响应面法优化石灰石粉和玻璃粉对碱活化矿渣砂浆的影响

进行了实验和统计研究,以分析三个变量(石灰石粉,玻璃粉和碱含量)对碱活化矿渣砂浆性能的影响。响应面方法(RSM)用于对所有测得的响应进行建模,例如28天抗弯强度和抗压强度,吸水率和干缩率。方差分析表明,所有已开发的模型均具有统计学意义。使用发达的回归模型绘制的三维响应表面图分析了相应变量之间的相互作用。使用RSM的理想方法进行了优化,目的是最大化28天的抗弯强度和抗压强度,同时最大程度地减少吸水率和干燥收缩率。石灰石粉的最佳值 玻璃粉和最高期望值为0.706的碱含量分别为15.80%,17.02和6.71%。通过验证性测试验证了预测的组合,发现预测误差在3.5%以内。
更新日期:2020-09-09
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