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Resilient moduli of demolition wastes in geothermal pavements: Experimental testing and ANFIS modelling
Transportation Geotechnics ( IF 4.9 ) Pub Date : 2021-06-03 , DOI: 10.1016/j.trgeo.2021.100592
Behnam Ghorbani , Arul Arulrajah , Guillermo Narsilio , Suksun Horpibulsuk , Melvyn Leong

Construction and demolition (C&D) waste materials have been used in a wide range of civil engineering applications, particularly as unbound pavement materials. A comprehensive understanding of the deformation and thermal properties of C&D materials is necessary for their usage in novel applications related to heat transfer in pavement unbound layers, such as geothermal pavements. This research study focused on developing a correlation between the resilient modulus (MR) and thermal conductivity of C&D materials for geothermal pavement applications. The thermal conductivity of C&D materials, namely recycled concrete aggregate (RCA), crushed brick (CB), reclaimed asphalt pavement (RAP), and waste rock (WR), was evaluated at different moisture contents and dry densities. The MR and permanent deformation responses of C&D materials were characterized at the optimum moisture content (OMC), 85%OMC, and 70%OMC, using the repeated load triaxial (RLT) test. An intelligent model was developed for predicting the MR of C&D materials incorporating thermal conductivity, physical properties, confining stress, and deviator stress as input parameters using adaptive neuro-fuzzy inference system (ANFIS) approach. The developed ANFIS model had excellent performance in predicting the MR of C&D materials, with R2 = 0.99 for both training and testing datasets. The ANFIS model was converted into a mathematical relationship, which can be used by researchers and practitioners for estimating the MR of C&D materials.



中文翻译:

地热路面拆除废料的弹性模量:实验测试和 ANFIS 建模

建筑和拆除 (C&D) 废料已用于广泛的土木工程应用,特别是作为未结合的路面材料。全面了解 C&D 材料的变形和热性能对于将其用于与路面未结合层(例如地热路面)中的传热相关的新应用是必要的。此研究集中在开发弹性模量(M之间的相关性[R )和C&d材料地热路面应用中的热导率。C&D 材料,即再生混凝土骨料 (RCA)、碎砖 (CB)、再生沥青路面 (RAP) 和废石 (WR) 的导热系数在不同的水分含量和干密度下进行了评估。所述M ř使用重复载荷三轴 (RLT) 测试在最佳含水量 (OMC)、85%OMC 和 70%OMC 下表征 C&D 材料的永久变形响应。开发了一种智能模型,用于使用自适应神经模糊推理系统 (ANFIS) 方法预测C&D 材料的 M R,其中包括热导率、物理特性、围压和偏应力作为输入参数。开发的 ANFIS 模型在预测C&D 材料的 M R方面具有出色的性能, 训练和测试数据集的R 2 = 0.99。ANFIS 模型被转换为数学关系,可供研究人员和从业人员用于估计C&D 材料的 M R。

更新日期:2021-06-13
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