Mechanistic Sieve-Size Classification of Aggregate Gradation by Characterizing Load-Carrying Capacity of Inner Structures

AbstractTo choose the maximum dividing sieve sizes for multiscale analysis, a mechanistic classification principle of sieve sizes is developed to characterize the size ranges of four inner structures in an aggregate’s gradation. A theoretical model of interlock check and stress evaluation is also es...

Ausführliche Beschreibung

Gespeichert in:
Bibliographische Detailangaben
Veröffentlicht in:Journal of engineering mechanics 2019-09, Vol.145 (9)
Hauptverfasser: Zhang, Yao, Ma, Tao, Ling, Meng, Huang, Xiaoming
Format: Artikel
Sprache:eng
Schlagworte:
Online-Zugang:Volltext
Tags: Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
Beschreibung
Zusammenfassung:AbstractTo choose the maximum dividing sieve sizes for multiscale analysis, a mechanistic classification principle of sieve sizes is developed to characterize the size ranges of four inner structures in an aggregate’s gradation. A theoretical model of interlock check and stress evaluation is also established to evaluate the contact and interactive-filling status between the identified structures. Then, a discrete element (DE) simulation of triaxial compression tests of graded aggregates is built to validate the mechanistic classification principle. The contact force is extracted to calculate the contribution of each sieve size to bear the load and stabilize the structure. The size ranges of inner structures can be determined by the combined analysis of force occupation curves and mechanistic classification principle. The results show that the dividing sieve sizes for four gradations in the main classification system are different, but they are the same in the subclassification system. The sieve-size classification principle along with DE simulation can provide a basis of choosing appropriate sieve sizes to conduct multiscale analysis of asphalt mixtures and asphalt pavements.
ISSN:0733-9399
1943-7889
DOI:10.1061/(ASCE)EM.1943-7889.0001640