A systematic review of Coda Wave Interferometry technique for evaluating rock behavior properties: From single to multiple perturbations
Bibliographic record
Abstract
Understanding rock behavior is crucial in mine geotechnical engineering to ensure construction efficiency, mitigate rock-related hazards, and promote environmental sustainability. Coda Wave Interferometry (CWI), a non-destructive ultrasonic testing method, has been widely employed to assess micro-damage evolution in rocks induced by perturbations in scatterer position, velocity, or source location due to its exceptional sensitivity. However, challenges persist in evaluating cross-scale rock behavior influenced by nonlinear deformation and multi-field interactions under multiple coupled perturbations. A comprehensive review of the perturbation factors affecting rock damage evolution and potential failure mechanisms is essential for presenting available knowledge in a more systematic and structured manner. This review provides an in-depth analysis of the CWI technique, encompassing its origins, theoretical framework, and classical data processing methodologies. Additionally, it explores the diverse applications of CWI in assessing rock behavior under various perturbation factors, including temperature variations, fluid infiltration, and stress conditions, with a particular emphasis on nonlinear deformation and multi-field coupling effects. Furthermore, a novel method for calculating relative velocity changes in coda waves is introduced, enabling a more precise characterization of the entire rock failure process. The study also proposes a cutting-edge concept of ultra-early and refined monitoring and warning technology for mine rock disasters, leveraging the advancements in CWI. Finally, the review highlights the potential future developments of CWI in high-level intelligent mining scenarios, particularly its integration with ambient noise interferometry and microseismic coda wave analysis. This work serves as a valuable reference, contributing to the refinement of CWI applications for assessing complex rock behavior and enhancing the accuracy of rock disaster prediction and early warning systems. • This review systematically examines the Coda Wave Interferometry (CWI) technique, covering its origin, theoretical foundation, classical data processing methods, and its applications in evaluating rock behavior under single and multiple perturbations. • A novel method for calculating relative velocity changes in coda waves is proposed, enabling comprehensive tracking of the entire rock failure process across scales. • A new concept of ultra-early, refined monitoring and warning technology for mine rock disasters based on the CWI technique is introduced. • The improvement of the CWI technique in high-level intelligent mining is discussed, with a focus on integrating ambient noise interferometry and microseismic coda wave technology with traditional CWI methods.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".