Section 5: Model-based hazard assessment and forecasting

The insights from empirical statistical models (Section 2) and micromechanical models (Sections 3 and 4) can be used to provide a comprehensive measurement of long- and short-term hazards and a reliable forecasting of extreme events in mechanical processes.

This section invites the presentation of data-based and/or model-inspired hazard models for seismic and microseismic events; non-intrusive techniques for structural health monitoring based on micromechanics or spontaneous acoustic emission; Bayesian inference of parameters in the point process representation of avalanche processes; proportional hazard models; hidden Markov and semi-Markov models; epidemic and branching aftershock models; real time parameter estimation; and any kind of data-based techniques, including machine learning, applied to failure forecasting, hazard assessment and damage diagnosis.