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

机译:模拟处理后的细沉积物的机械强度发展:一种统计方法

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摘要

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:由于不同的约束和实际困难,沉积物的增值(回收)已显示出局限性。当涉及不同的回收方法时,仍然需要确定评估各种类型沉积物的可能性。使用统计方法,本研究旨在定量评估稳定沉积物的机械阻力。从文献中选择并收集了一个包含22个细小沉积物的数据库。这些沉积物用不同类型和数量的添加剂(填料和/或粘合剂)处理。本研究包括两个部分。一方面,使用XLstat软件的多元线性回归工具,获得了一个分析模型,该模型突出了28天后影响处理后沉积物机械阻力的各种参数的影响。该模型表明,有机质含量和可塑性指数是沉积物特性的最重要因素,而水泥是最好的机械强度增强剂。另一方面,使用最小二乘回归法通过指数关系来模拟处理后的沉积物机械阻力随时间的变化。与一组选定的实验值相比,两种模型均显示出可接受的精度。

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