Work

Machine Learning-Based Classification of Dynamic Damage Modes in Rock–Concrete Composites Under Impact Loading

Year: 2026

Type: article

Abstract: In tunnel engineering, rock–concrete composite structures may be subjected to dynamic loading induced by earthquakes, blasting, and rockbursts. This study investigated the dynamic response and damage evolution of granite- and sandstone-based composites with ordinary or fiber-reinforced concrete using split Hopkinson pressure bar (SHPB) impact tests at different impact velocities. Acoustic emission (AE) monitoring was combined with a Gaussian mixture model–support vector machine (GMM–SVM) framework to classify damage modes based on the rise-time-to-peak-amplitude ratio (RA) and average frequency (AF). Across the four specimen types, dynamic compressive strength ranged from 37.35 to 57.65 MPa under low-impact conditions and from 102.73 to 120.75 MPa under ultra-high-impact conditions. The corresponding dissipated energy values ranged from 34.19 to 64.12 J and from 192.98 to 266.81 J, respectively. Granite-based specimens exhibited a more pronounced double-peak response, whereas sandstone-based specimens showed more continuous post-peak softening. Fiber reinforcement improved post-peak load-bearing stability, although its effect on energy dissipation varied with impact velocity. AE activity was concentrated mainly during the early impact stage. Under medium-impact-velocity conditions, where damage-mode classification was performed, shear damage dominated in granite-based specimens (56.0% for GC-1 and 53.4% for GCF-1), whereas tensile damage dominated in sandstone-based specimens (52.6% for SC-1 and 59.9% for SCF-1). Fiber reinforcement increased the tensile-damage ratio in granite-based specimens from 44.0% to 46.6%. These findings clarify how rock type and fiber reinforcement influence the dynamic response and damage evolution of rock–concrete composites.

Source: Materials

DOI: 10.3390/ma19214624

Authors: Zhixuan Gao, Quanmin Xie, Yuzhu Guo, Yuntian Wang, Jin Wu

Institutions: Jianghan University, Changsha University of Science and Technology, Chengdu Polytechnic, Zhejiang University

Language: English

Topic: Rock Mechanics and Modeling

Subfield: Mechanics of Materials

Field: Engineering

Domain: Physical Sciences

SDG: Industry, innovation and infrastructure

Open Access status: gold

Estimated APC paid: $3,137