Co-detection of acoustic emissions during failure of heterogeneous media: new perspectives for natural hazard early warning

TL;DR

This paper introduces a novel early warning method for natural hazard failure based on co-detection of acoustic emissions, accounting for media heterogeneity and wave attenuation, validated through numerical modeling.

Contribution

It presents a new approach combining co-detection of acoustic emissions with heterogeneity considerations for improved early failure detection.

Findings

Co-detection signals correlate with imminent catastrophic failure.

Sensor array configurations can detect failure precursors despite attenuation.

Numerical models demonstrate the method's potential for early warning systems.

Abstract

A promising method for real time early warning of gravity driven rupture that considers both the heterogeneity of natural media and characteristics of acoustic emissions attenuation is proposed. The method capitalizes on co-detection of elastic waves emanating from micro-cracks by multiple and spatially separated sensors. Event co-detection is considered as surrogate for large event size with more frequent co-detected events marking imminence of catastrophic failure. Using a spatially explicit fiber bundle numerical model with spatially correlated mechanical strength and two load redistribution rules, we constructed a range of mechanical failure scenarios and associated failure events (mapped into AE) in space and time. Analysis considering hypothetical arrays of sensors and consideration of signal attenuation demonstrate the potential of the co-detection principles even for insensitive sensors to provide early warning for imminent global failure.