利用响应面法预测改性自密实混凝土的强度

Q3 Engineering
B. Udayasree, Avuthu Narender Reddy, Yadav Suvidha, Prathik Kulkarni, C. A. Kumar, Bodevenkata Kavyatheja
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引用次数: 0

摘要

本研究强调了响应面法在预测含有废铸造砂和人造砂的硬化混凝土性能方面的有效性。在当前的研究中,使用废铸造砂和人造砂作为细骨料的部分替代品,配制了不同的混合比例。对所有混凝土混合料进行了工作性、强度和耐久性研究。试验结果证实,掺入 20% 的废铸造砂最有利于提高强度和耐久性。此外,在人造砂混凝土中加入 20% 的废铸造砂也能达到最佳强度和耐久性效果。此外,还采用了响应面法来建立抗压强度预测模型。抗压强度模型的 R 方和残余误差平方和分别为 0.9863 和 2.345,证实了拟合的良好性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Strength prediction of modified self-compacting concrete using response surface method
This study highlights the effectiveness of the response surface method in predicting the properties of hardened concrete containing spent foundry sand and manufactured-sand. In current research, different mix proportions are prepared with spent foundry sand and manufactured-sand as partial replacements for fine aggregate. The workability, strength, and durability studies are conducted on all concrete mixes. The test results confirm that the inclusion of 20% of spent foundry sand is optimum for enhancing the strength and durability. Also, the inclusion of 20% of spent foundry sand in manufactured-sand concrete also possesses optimum results in strength and durability. Further, the response surface method has been employed to develop a model for compressive strength prediction. The R-squared and residual sum of squares of error for the compressive strength model were 0.9863 and 2.345, which confirms the goodness of the fit.
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来源期刊
Pollack Periodica
Pollack Periodica Engineering-Civil and Structural Engineering
CiteScore
1.50
自引率
0.00%
发文量
82
期刊介绍: Pollack Periodica is an interdisciplinary, peer-reviewed journal that provides an international forum for the presentation, discussion and dissemination of the latest advances and developments in engineering and informatics. Pollack Periodica invites papers reporting new research and applications from a wide range of discipline, including civil, mechanical, electrical, environmental, earthquake, material and information engineering. The journal aims at reaching a wider audience, not only researchers, but also those likely to be most affected by research results, for example designers, fabricators, specialists, developers, computer scientists managers in academic, governmental and industrial communities.
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