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Modelling the mechanical strength development of treated fine sediments: a statistical approach

机译:造型治疗细沉积物的机械强度发展:一种统计方法

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Sediments valorization (recycling) has revealed limitations due to different restrains and practical difficulties. When it comes to different recovery methods, the possibility of valuing diverse types of sediments still needs to be defined. Using a statistical approach, the present study aims to quantitatively estimate the mechanical resistance of stabilized sediments. A database that included 22 fine sediments is selected and assembled from the literature. These sediments were treated with distinct types and quantities of additives (fillers and/or binders). The present study includes two parts. On one hand, using multivariate linear regression tool of XLstat software, an analytical model that highlights the effects of various parameters influencing the mechanical resistance of treated sediments after 28 days is obtained. This model showed that organic matter content and plasticity index are the most significant factors of sediments characteristics, while cement is the best mechanical strength booster. On the other hand, the evolution of treated sediments mechanical resistance over time is modelled by an exponential relationship using a least square regression method. Both models showed acceptable accuracies compared to a panel of selected experimental values.
机译:沉积物估值(回收)由于不同的抑制和实际困难而揭示了局限性。当涉及不同的恢复方法时,需要定义重视各种沉积物的可能性。使用统计方法,本研究旨在定量估计稳定沉积物的机械抗性。包括22个细沉积物的数据库,并从文献中组装。用不同类型和数量的添加剂(填料和/或粘合剂)处理这些沉积物。本研究包括两部分。一方面,使用XLSTAT软件的多变量线性回归工具,获得了一种分析模型,突出了影响28天后经处理沉积物的机械电阻的各种参数的效果。该模型表明,有机质含量和可塑性指数是沉积物特征最重要的因素,而水泥是最佳的机械强度助推器。另一方面,通过使用最小二乘回归方法的指数关系模拟了处理沉积物的变化因指数关系而建模。与选定的实验值面板相比,这两种模型都显示出可接受的精度。

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