Abstract

The angularity of the coarse aggregate (CA) affects the performance of the concrete. A digital microscope is used to obtain three-dimensional contour data points on the surface of a CA and thus improve the effectiveness of the evaluation of the angularity of the CA. Three methods of characterizing the angularity of the CA, namely applying a fitted ellipsoid model (AIf), steradian model (AIc), or roughness model (SR), were studied. The effectiveness of different angularity characterization methods was compared with the Los Angeles abrasion (LAA) and void content (VC) experiments. Results show that the angularity index of the fitted ellipsoid model is the most effective model in characterizing aggregate angularity, and it can eliminate the influence of the particle sizes; the angularity index AIf changes most rapidly with an increase in the VC, indicating that AIf is the most effective in characterizing the VC of the CA; and the angularity index AIc has a strong negative correlation with sphericity, which indicates that AIc is the most effective index in characterizing the sphericity of the CA.

• Highlights

• A new algorithm (fitted ellipsoid model) for evaluating the 3D angularity of aggregates has significant advantages.

• The angularity index AIf is more suitable for characterizing the void content of the aggregate.

• The angularity index AIc is more suitable for characterizing the sphericity of the aggregate.

摘要

粗骨料 (CA) 的棱角会影响混凝土的性能。利用数码显微镜获取CA表面的三维轮廓数据点，从而提高CA棱角评价的有效性。表征 CA 棱角的三种方法，即应用拟合椭球模型 ( AIf )、球面度模型 ( AIc ) 或粗糙度模型 ( SR ))，进行了研究。将不同棱角表征方法的有效性与洛杉矶磨损 (LAA) 和空隙率 (VC) 实验进行了比较。结果表明，拟合椭球模型的棱角指数是表征骨料棱角最有效的模型，可以消除粒径的影响；棱角指数AIf随着VC的增加变化最快，表明AIf在表征CA的VC方面最有效；棱角指标AIc与球形度呈强负相关，说明AIc是表征CA球形度最有效的指标。

• 强调

• 一种用于评估骨料 3D 角度的新算法（拟合椭球模型）具有显着优势。

• 棱角指数AIf更适合表征骨料的空隙率。

• 棱角指数AIc更适合表征集料的球形度。