Data-Driven Insights into Controlling the Reactivity of Supplementary Cementitious Materials in Hydrated Cement

IF 3.6 3区 工程技术 Q1 CONSTRUCTION & BUILDING TECHNOLOGY International Journal of Concrete Structures and Materials Pub Date : 2024-06-28 DOI:10.1186/s40069-024-00677-w
Aron Berhanu Degefa, Geonyeol Jeon, Sooyung Choi, JinYeong Bak, Seunghee Park, Hyungchul Yoon, Solmoi Park
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Abstract

Supplementary cementitious materials (SCMs) play an essential role in sustainable construction due to their potential to reduce carbon emissions, promote circular economy principles, and enhance the properties of concrete. However, the inherent diversity of SCMs makes it challenging to predict their degree of reaction (DOR). This study applies machine learning techniques to predict DOR while exploring key parameters affecting it. Five machine learning models are utilized: linear regression, Gaussian process regression (GPR), decision tree regression, support vector machine and extreme gradient boosting, with GPR providing the most accurate and adaptable prediction. The study delves into the impact of various parameters on DOR, revealing their significance. Silica content emerges as the most critical, followed by particle size distribution, specific gravity, and water-to-cement (W/C) ratio. Optimizing DOR requires extending curing time, reducing particle size distribution, and considering optimal silica content and W/C ratio. This research emphasizes the importance of understanding the relationships between parameters and the DOR of SCMs, providing insights to enhance the efficiency of SCMs in cementitious systems through machine learning and data-driven analysis.

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数据驱动的水化水泥中补充胶凝材料反应性控制见解
由于具有减少碳排放、促进循环经济原则和提高混凝土性能的潜力,补充胶凝材料(SCMs)在可持续建筑中发挥着至关重要的作用。然而,由于 SCM 固有的多样性,预测其反应度 (DOR) 具有挑战性。本研究应用机器学习技术预测 DOR,同时探索影响 DOR 的关键参数。研究采用了五种机器学习模型:线性回归、高斯过程回归 (GPR)、决策树回归、支持向量机和极端梯度提升,其中 GPR 预测最为准确,适应性最强。研究深入探讨了各种参数对 DOR 的影响,揭示了它们的重要性。硅含量是最关键的参数,其次是粒度分布、比重和水灰比(W/C)。要优化 DOR,就必须延长固化时间,减少粒度分布,并考虑最佳二氧化硅含量和水灰比。这项研究强调了了解单体材料参数与 DOR 之间关系的重要性,为通过机器学习和数据驱动分析提高水泥基系统中单体材料的效率提供了见解。
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来源期刊
International Journal of Concrete Structures and Materials
International Journal of Concrete Structures and Materials CONSTRUCTION & BUILDING TECHNOLOGY-ENGINEERING, CIVIL
CiteScore
6.30
自引率
5.90%
发文量
61
审稿时长
13 weeks
期刊介绍: The International Journal of Concrete Structures and Materials (IJCSM) provides a forum targeted for engineers and scientists around the globe to present and discuss various topics related to concrete, concrete structures and other applied materials incorporating cement cementitious binder, and polymer or fiber in conjunction with concrete. These forums give participants an opportunity to contribute their knowledge for the advancement of society. Topics include, but are not limited to, research results on Properties and performance of concrete and concrete structures Advanced and improved experimental techniques Latest modelling methods Possible improvement and enhancement of concrete properties Structural and microstructural characterization Concrete applications Fiber reinforced concrete technology Concrete waste management.
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