Degradation of granulite and charnockite aggregates under simulated train loading: Morphological and mechanical insights for railway ballast
Year: 2025
Type: article
Abstract: The performance of railway ballast strongly depends on the mineralogical and morphological characteristics of the aggregates. However, little is known about the behavior of regional rocks in Rio de Janeiro, Brazil, under manipulation caused by railway traffic. This study investigates the manipulation of granulite and charnockite particles from the EF-118 railway line using Micro-Deval tests and the Aggregate Image Measurement System (AIMS II). Petrography, mercury intrusion porosimetry, and point load tests were also extended to correlate mineralogy, porosity, and mechanical strength with ballast performance. The results indicate that the Itaperuna granulite, with a higher biotite content and the presence of microcracks, showed greater mass loss (16.0 %) and lower uniaxial tensile strength (97 MPa). The Outeiro charnockite showed a significant reduction in angularity (≈36 %), affecting the interlocking of particles. In contrast, the Italva granulite showed better performance, with lower porosity (0.75 %), lower abrasion loss (14.9 %), and higher strength (110 MPa). Loss of angularity and texture alteration were identified as the main manipulation mechanisms, controlled by mineralogy and microstructural defects. The Weibull parameter (m) revealed greater homogeneity in Italva and greater variability in Itaperuna. Another important aspect is that a strong correlation was observed between the variation in angularity and porosity (R 2 = 1.00). This indicates that aggregates with higher porosity consistently undergo greater manipulation of angularity. The study provides new information on the suitability of local rocks for use as railway ballast, highlighting the Italva granulite as the most promising for long-term stability.
Language: English
Subfield: Mechanical Engineering
Field: Engineering
Domain: Physical Sciences
Open Access status: gold
Estimated APC paid: $1,640
Award: G8567506201
OpenAlex ID: W4417073114
