Intelligent numerical computation method and quantitative study on morphological characteristics of multi-scale aggregate

Abstract

Use Image-Pro Plus software, high-precision inductive sensor TR200, electro n microscope and ENVI image processing system to quantitatively study aggregate mo rphology from three scales: macro, meso, and micro, and obtain P, As, R, Ry, Rsm, et c. 17 quantitative indicators of morphological characteristics, compared with the occup ancy rate of the aggregate broken surface and the roughness of the aggregate surface. T he results show that the 17 morphological characteristics indexes are feasible for multi -scale quantification of aggregate morphology. Macro-morphological characteristics di rectly indicate the angularity and needle-like shape of materials, micro-morphological characteristics directly indicate the roughness of materials surface, and micro-morphol ogical characteristics directly indicate the micro-morphological characteristics of mate rials. The quantitative indexes of aggregate morphology at micro-scale and micro-scal e are improved, and the results are helpful to reveal the morphological characteristics o f aggregate comprehensively.