Estimating the optimal mix design of silica fume concrete using biogeography-based programming

Estimating the optimal mix design of silica fume concrete using biogeography-based programming
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DOI:
10.1016/j.cemconcomp.2018.11.005
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发表时间:
2019-02-01
影响因子:
10.5
通讯作者:
Behnood, Ali
Behnood, Ali
中科院分区:
工程技术1区
文献类型:
--
作者:
Golafshani, Emadaldin Mohammadi;Behnood, Ali

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在混凝土工业中,特别是为了获得高强度混凝土,硅粉在混凝土混合物中的使用已急剧增加。准确的硅粉混凝土抗压强度估算模型和优化配合比设计可以节省时间和成本。在这项研究中,基于图形的规划(BBP)作为一种符号回归方法来预测硅粉混凝土的抗压强度,而约束基于图形的优化(CBBO)被用来估计其最佳配合比设计。为此目的,从各种出版的文件中收集了一个综合数据库。从收集的数据中,约75%的数据用于训练模型,而其余的用于验证开发的模型。模型的有效输入变量为水泥用量、水用量、硅灰用量、粗骨料用量、细骨料用量、高效减水剂用量以及骨料最大粒径和混凝土龄期。以硅灰混凝土的抗压强度为唯一输出变量。结果表明,BBP模型可以成功地用于预测硅灰混凝土的抗压强度,具有可接受的精度。此外,设计了一个图形用户界面,允许用户估计硅粉混凝土的最佳配合比设计。
The use of silica fume in concrete mixtures has been dramatically increased in concrete industry, especially for achieving high strength concrete. An accurate model of estimating the compressive strength and optimal mix design of silica fume concrete can save in time and cost. In this study, the biogeography-based programming (BBP) was used as a symbolic regression method to predict the compressive strength of silica fume concrete, while the constrained biogeography-based optimization (CBBO) was used to estimate its optimal mix design. For this purpose, a comprehensive database was gathered from various published documents. From the collected data, about 75% of all data was employed to train the model, while the rest was used to verify the developed model. The amounts of cement, water, silica fume, coarse aggregate, fine aggregate, superplasticizer, as well as the maximum size of aggregate and concrete age were selected as the effective input variables of the model. The compressive strength of silica fume concrete was considered as the only output variable. The results show that the BBP model can be successfully used for the prediction of the compressive strength of silica fume concrete with acceptable accuracy. In addition, a graphical user interface was designed which allows the users to estimate the optimal mix design of silica fume concrete.