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高温作用下废陶瓷混凝土的力学性能、裂缝宽度及扩展:一项综合研究

Mechanical Properties, Crack Width, and Propagation of Waste Ceramic Concrete Subjected to Elevated Temperatures: A Comprehensive Study.

作者信息

Najm Hadee Mohammed, Nanayakkara Ominda, Ahmad Mahmood, Sabri Sabri Mohanad Muayad

机构信息

Department of Civil Engineering, Zakir Husain Engineering College, Aligarh Muslim University, Aligarh 202002, India.

Department of Civil Engineering, Xi'an Jiaotong-Liverpool University, Suzhou 215000, China.

出版信息

Materials (Basel). 2022 Mar 23;15(7):2371. doi: 10.3390/ma15072371.

Abstract

Waste ceramic concrete (WOC) made from waste ceramic floor tiles has several economic and environmental benefits. Fire is one of the most common disasters in buildings, and WOC is a brittle construction material; therefore, the mechanical properties of WOC structures under high temperatures should be considered. According to previous studies, hybrid fiber can further reduce damage to concrete under high temperatures. Meanwhile, crack width and propagation are among the key characteristics of concrete materials that need to be considered, but few studies have focused on their behavior when subjected to elevated temperatures. The new concrete materials proposed by the authors are WOC and WOC-Hybrid. WOC was prepared with Natural Coarse Aggregates (NCA), Natural Fine Aggregate (NFA), Ordinary Portland Cement (OPC 43 grade), and ceramic waste tiles with 20% replacements for coarse aggregates, 10% replacements for fine aggregates, and 10% replacement for cement. In contrast, WOC-Hybrid was prepared with the addition of hybrid fiber (1% crimped steel fiber and 1% polyvinyl alcohol fiber) in WOC. The specimens were exposed to temperatures of 100-300 °C, and then the specimens were tested for tensile and compressive strength. The present study aims to find a new method to improve concrete resistance to elevated temperatures at the lowest costs by experimental and computational analysis via machine learning models. The application of machine learning models such as artificial neural networks (ANN) and multiple linear regression (MLR) was employed in this study to predict the compressive and tensile strength of concrete. The linear coefficient correlation (R) and mean square error (MSE) were evaluated to investigate the performance of the models. Based on the experimental analysis, the results show that the effect of hybrid fiber on the crack width and propagation is greater than that on the crack width and propagation of WOC and PC after exposure to high temperatures. However, the enhanced effect of hybrid fiber on the mechanical properties, rack width, and propagation decreases after subjecting it to a high-temperature treatment, owing to the melting and ignition of hybrid fibers at high temperatures. Regarding the computational analysis, it was found that the developed MLR model shows higher efficiency than ANN in predicting the compressive and tensile strength of PC, WOC, and WOC-Hybrid concrete.

摘要

由废弃陶瓷地砖制成的废弃陶瓷混凝土(WOC)具有若干经济和环境效益。火灾是建筑物中最常见的灾害之一,而WOC是一种脆性建筑材料;因此,应考虑WOC结构在高温下的力学性能。根据以往的研究,混杂纤维可以进一步减少混凝土在高温下的损伤。同时,裂缝宽度和扩展是混凝土材料需要考虑的关键特性之一,但很少有研究关注它们在高温下的行为。作者提出的新型混凝土材料是WOC和WOC-混杂纤维混凝土。WOC由天然粗骨料(NCA)、天然细骨料(NFA)、43级普通硅酸盐水泥(OPC)和陶瓷废料制成,其中粗骨料替代率为20%,细骨料替代率为10%,水泥替代率为10%。相比之下,WOC-混杂纤维混凝土是在WOC中添加了混杂纤维(1%的卷曲钢纤维和1%的聚乙烯醇纤维)制备而成。将试件暴露在100-300℃的温度下,然后对试件进行抗拉和抗压强度测试。本研究旨在通过机器学习模型进行实验和计算分析,找到一种以最低成本提高混凝土耐高温性能的新方法。本研究应用了人工神经网络(ANN)和多元线性回归(MLR)等机器学习模型来预测混凝土的抗压和抗拉强度。评估了线性系数相关性(R)和均方误差(MSE)以研究模型的性能。基于实验分析,结果表明,混杂纤维对高温后WOC和PC裂缝宽度和扩展的影响大于对其的影响。然而,由于混杂纤维在高温下熔化和着火,高温处理后混杂纤维对力学性能、裂缝宽度和扩展的增强作用降低。关于计算分析,发现所开发的MLR模型在预测PC、WOC和WOC-混杂纤维混凝土的抗压和抗拉强度方面比ANN具有更高的效率。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/95a4/8999623/c9cf8ca84ae8/materials-15-02371-g001.jpg

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