Fracture Process in Conceptual Numerical Geological Rock Mass System Model and Its Implications for Landslide Monitoring and Early Warning

Liming Tang, Xu Chen (), Chao Huang and Chunan Tang
Additional contact information
Liming Tang: School of Environment and Civil Engineering, Chengdu University of Technology, Chengdu 610059, China
Xu Chen: School of Environment and Civil Engineering, Chengdu University of Technology, Chengdu 610059, China
Chao Huang: School of Environment and Civil Engineering, Chengdu University of Technology, Chengdu 610059, China
Chunan Tang: State Key Laboratory of Geohazard Prevention and Geoenvironment Protection, Chengdu University of Technology, Chengdu 610059, China

Sustainability, 2025, vol. 17, issue 18, 1-20

Abstract: To determine whether rock landslides can be predicted early and accurately forecasted, a numerical simulation method is used. The geological rock mass system is simplified into 16 heterogeneous geological rock mass units. By subjecting this two-dimensional planar model to uniaxial compression loading, qualitative insights into the evolution of displacement, stress, and acoustic emission signals throughout the fracture process of the heterogeneous geological rock mass were obtained, leading to the following insights: (1) Before the fracture of the heterogeneous geological rock mass system model, a “differentiation” phenomenon occurred, characterized by varying magnitudes and directions of both displacement and stress increments, coupled with a sudden surge in the number of acoustic emission events and their clustering near macroscopic cracks. Such a phenomenon could serve as an early warning indicator for predicting rock landslides. (2) Although the phenomenon of “differentiation” has been observed, the lack of uniformity and regularity in these phenomena across different elements indicates that integrated monitoring methods such as displacement, stress, and acoustic monitoring are insufficient for the precise prediction of rock landslides. (3) Increasing the number and range of monitoring points, as well as diversifying and integrating monitoring methods, can significantly enhance the precision of rockslide early warning systems. The outcomes of this research provide a scientific tool and metric for quantifying precursory signals of slope instability, thereby contributing to the development of sustainable environmental monitoring frameworks and informed policymaking for disaster-resilient infrastructure in vulnerable regions.

Keywords: conceptual numerical model; geological rock mass system; landslide; monitoring and early warning; evolution characteristics (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2025
References: Add references at CitEc
Citations:

Downloads: (external link)
https://www.mdpi.com/2071-1050/17/18/8408/pdf (application/pdf)
https://www.mdpi.com/2071-1050/17/18/8408/ (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:gam:jsusta:v:17:y:2025:i:18:p:8408-:d:1753269

Access Statistics for this article

Sustainability is currently edited by Ms. Alexandra Wu

More articles in Sustainability from MDPI
Bibliographic data for series maintained by MDPI Indexing Manager ().