Rock Burst Hazard Assessment Through Physics-Data Integration
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Solution Overview
Problem
Current rock burst hazard assessment methods lack integration of multi-physical field monitoring parameters and data-driven approaches, failing to provide intelligent and quantitative characterization of the rock burst process, particularly in complex environments.
Innovation Solution
A physics-based and data-driven integrated method for rock burst hazard assessment, utilizing grid discretization, physics-based models, and data-driven models to correct stress concentration coefficients using seismic wave CT detection and microseismic data, enabling nearly real-time inversion of mining-induced stress concentration coefficients.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If physics-based models are used for stress concentration assessment, then theoretical foundation is improved, but accuracy in complex geological environments deteriorates
Solution Approach 1:
The patent combines physics-based models (elastodynamic, damage mechanics) with data-driven models (seismic wave CT, microseismic monitoring) into an integrated assessment system. The physics-based models provide theoretical framework for stress concentration coefficient calculation, while data-driven models correct and refine these calculations using actual monitoring data, thereby maintaining theoretical rigor while improving accuracy in complex geological conditions.
2Area of stationary object
If multi-parameter comprehensive monitoring is implemented, then monitoring coverage is improved, but system complexity deteriorates
Solution Approach 1:
The patent creates a unified rock burst hazard assessment system that integrates multiple monitoring functions (seismic wave CT detection, microseismic monitoring, stress measurement) into a single platform. This system uses a common theoretical framework (stress concentration coefficient) to coordinate different monitoring parameters, enabling multi-functional operation while reducing overall system complexity through standardized processing and analysis procedures.
3Reliability
If real-time monitoring is achieved, then early warning capability is improved, but data processing time deteriorates
Solution Approach 1:
The patent pre-establishes the theoretical framework and calculation models (stress concentration coefficient formulas, damage mechanics models) before actual monitoring begins. By having the assessment system ready with pre-configured physics-based models and data processing algorithms, the system can immediately process incoming monitoring data in real-time without requiring complex on-the-fly model development, thus maintaining early warning capability while minimizing data processing delays.
Data Source
AI summary
The present disclosure provides a physics-based and data-driven integrated method for rock burst hazard assessment, including the following steps: determining an initial stress concentration coefficient by conducting grid discretization on an assessment region, and assigning a value to each of grid nodes using a Weibull distribution function; obtaining a stress concentration coefficient value of each grid node under physics-based models; introducing seismic wave CT detection data to obtain stress concentration coefficient distribution in the assessment region under the integration of a seismic wave CT detection and its derived characterization stress model; introducing microseismic data to obtain stress concentration coefficient distribution in the assessment region under the integration of a microseismic damage reconstruction stress model; and assessing the degree of rock burst hazard according to the size of the stress concentration coefficient value.