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Mechanical Properties Test and Strength Prediction on Basalt Fiber Reinforced Recycled Concrete

机译:玄武岩纤维增强再生混凝土机械性能试验与强度预测

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In order to study the mechanical properties of basalt fiber reinforced recycled concrete (BFRRC), nine groups of tests are designed with three different replacement rates of recycled aggregates (40%, 70%, and 100%) and volume fraction of basalt fibers (0.1%, 0.2%, and 0.3%). Another group of tests on ordinary concrete without fiber and recycled aggregate is used as comparison. The workability, cubic compressive strength, splitting tensile strength, and flexural strength of BFRRC are tested and analyzed. The effects of fiber content and recycled aggregate replacement ratio on the mechanical properties of concrete are studied. The strength development of fiber reinforced recycled concrete is predicted by using convolution neural network theory. The test results show that the fluidity of concrete mixtures decreases, while the cohesion and water retention are better than ordinary concrete with the increase of replacement ratio of recycled coarse aggregate and basalt fiber content. The compressive and flexural strength of recycled concrete first decrease and then increase slightly, while the splitting tensile strength of recycled concrete continue to decrease with the increase of replacement ratio of recycled aggregate. The flexural strength and splitting tensile strength of recycled concrete are obviously improved after adding basalt fiber, while the compressive strength increases first and then decreases with the increase of fiber content. A convolution neural network model for predicting the strength of basalt fiber reinforced recycled concrete is established. The predicted results are very close to the measured values and can be used as reference for the mix ratio of basalt fiber reinforced recycled concrete.
机译:为了研究玄武岩纤维增强的再生混凝土(BFRRC)的机械性能,设计了九组试验,具有三种不同的再循环聚集液(40%,70%和100%)和玄武岩纤维的体积分数(0.1 %,0.2%和0.3%)。使用没有纤维和再循环骨料的普通混凝土的另一组测试用作比较。测试和分析了BFRRC的可加工性,立方抗压强度,分裂拉伸强度和抗弯强度。研究了纤维含量和再循环聚集置换比对混凝土机械性能的影响。利用卷积神经网络理论预测了纤维增强再生混凝土的强度发展。测试结果表明,混凝土混合物的流动性降低,而粘性和水保留比普通混凝土较好,随着再生粗骨料和玄武岩纤维含量的替代比的增加。再循环混凝土的压缩和弯曲强度首先降低,然后略微增加,而再循环混凝土的分裂拉伸强度随着再循环骨料的替代比的增加而继续降低。在添加玄武岩纤维后,再循环混凝土的抗弯强度和分裂拉伸强度明显改善,而抗压强度首先增加,然后随着纤维含量的增加而降低。建立了一种卷积神经网络模型,用于预测玄武岩纤维增强混凝土的强度。预测结果非常靠近测量值,可用作玄武岩纤维增强再生混凝土的混合比的参考。

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