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Models for compressive strength estimation through non-destructive testing of highly self-compacting concrete containing recycled concrete aggregate and slag-based binder

机译:通过含有再生混凝土骨料和基于矿渣的粘合剂的高度自体压实混凝土的非破坏性测试抗压强度估算模型

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Indirect estimation of compressive strength through non-destructive testing is key to monitoring the strength of structural concretes used in construction and rehabilitation works. However, no models are available to perform this estimation in highly Self-Compacting Concrete (SCC) with Recycled Concrete Aggregate (RCA). To fill this gap, two indirect measures were tested in this paper, the hammer rebound index and Ultrasonic Pulse Velocity (UPV), to predict the compressive strength of highly SCC. To do so, 24 SCC mixes were developed with different aggregate powders, binders, such as Ground Granulated Blast Furnace Slag (GGBFS), and contents of fine RCA. Compressive strength, and both indirect measures of all mixtures were determined at 1, 7, 28, and 90 days. The development of specific models for highly SCC responded to the inappropriateness of conventional models that are not adapted to its high fines content. Modelling as a function of either UPV or the hammer rebound index yielded accurate predictions, although the UPV model proved more sensitive to compositional changes and presented higher uncertainty. The best predictions were modelled by combining both indirect measures. The models provided safe and accurate indirect estimations of the compressive strength of high flowability SCC in real structures. (C) 2021 Elsevier Ltd. All rights reserved.
机译:通过非破坏性测试间接估计抗压强度是监测建筑和康复工作中使用的结构混凝土强度的关键。但是,没有型号可以在高度自压缩混凝土(SCC)中进行这种估计,具有再循环的混凝土聚集体(RCA)。为了填补这种差距,本文测试了两个间接措施,锤击反弹指数和超声波脉冲速度(UPV),以预测高度SCC的抗压强度。为此,使用不同的聚集粉末,粘合剂等24个SCC混合物,如地面粒状高炉渣(GGBF)和细rca的含量。抗压强度,以及所有混合物的间接测量都在1,7,28和90天内测定。高度SCC的特定模型的开发应对不适应其高罚款含量的常规模型的不恰当性。由于UPV或锤子反弹指数的函数建模产生了准确的预测,尽管UPV模型证明对组成变化更敏感并提高了更高的不确定性。通过组合间接措施来建模最佳预测。该模型提供了对实际结构中高流动性SCC的抗压强度的安全和准确的间接估计。 (c)2021 elestvier有限公司保留所有权利。

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