Multi-scale particles optimization for some rheological properties of Eco-SCC: Modelling and experimental study

被引：0

作者：

Zhang, Junyi ^{[1
]}

Xu, Pengju ^{[1
]}

Gao, Xiaojian ^{[1
,2
]}

机构：

[1] School of Civil Engineering, Harbin Institute of Technology, Harbin,150090, China

[2] School of Materials Science and Engineering, Zhengzhou University, Zhengzhou,450001, China

来源：

Construction and Building Materials | 2021年 / 308卷

基金：

中国国家自然科学基金;

关键词：

Discrete element method modeling - Discrete elements method - Ecologically-friendly self-compacting concrete - Layer thickness - Lubrication layer - Lubrication layer thickness - Method model - Multi-scales - Particle optimization - Rheological property;

D O I：

暂无

中图分类号：

学科分类号：

摘要：

The development of mix design method for low-binder ecologically-friendly self-compacting concrete (Eco-SCC) has attracted interest in recent years. Most studies investigated this topic by evaluating mixtures with various ingredient proportions experimentally and then establish empirical correlations. This research attempts to take the first step towards a novel numerical discrete element method (DEM) simulation to optimize multi-scale particles size distribution of Eco-SCC at a constant mixing proportion. The two-phase DEM model was generated as an assembly of hard core with soft shell based on the thickness of mortar layer covering gravels and rheological behavior of suspending mortar, to characterize fresh properties of Eco-SCC. The rolling resistance standard contact model was adopted for simulating fresh mortar matrix lacking in excess paste. It was found that the blended cementitious powders closer to Fuller ideal curve and the aggregates gradation with higher fractal dimension were beneficial to the flowability of mixture. However, potential negative impacts on stability or passing ability of Eco-SCC might also be induced by an overmuch incorporation of slag or a higher portion of large-size gravel. The numerical results not only showed good agreements with experimental verifications (deviations lower than 7% for flow spread prediction), but also provided insights into the interactions among particles along with their continuous motion traces. Thereby, DEM modelling can be used as an efficient tool to reveal the influential mechanism of aggregates on fresh Eco-SCC and attain a general improvement in rheological performance via multi-scale particles optimization, with the measured slump flow increasing from 510 mm to 730 mm (by 43.1% at most) in this study. The eventually optimized Eco-SCC mix can be obtained with slump flow at 670 mm, V-funnel time at 4.1 s, J-ring spread at 635 mm, VSI = 0, and the cost intensity of 7.09 CNY·m−3·MPa. © 2021 Elsevier Ltd

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