Prediction of Catastrophes: an experimental model

TL;DR

This paper presents a laboratory model demonstrating that critical slowing down in noisy signals can serve as a precursor to catastrophic events, with potential applications in predicting earthquakes and other large-scale failures.

Contribution

It introduces an experimental setup that detects early warning signals of catastrophes through critical slowing down in both abstract and physical models.

Findings

Critical slowing down signals precede catastrophes in models

Laboratory data supports theoretical prediction methods

Potential for early catastrophe warning in various systems

Abstract

Catastrophes of all kinds can be roughly defined as short duration-large amplitude events following and followed by long periods of "ripening". Major earthquakes surely belong to the class of 'catastrophic' events. Because of the space-time scales involved, an experimental approach is often difficult, not to say impossible, however desirable it could be. Described in this article is a "laboratory" setup that yields data of a type that is amenable to theoretical methods of prediction. Observations are made of a critical slowing down in the noisy signal of a solder wire creeping under constant stress. This effect is shown to be a fair signal of the forthcoming catastrophe in both of two dynamical models. The first is an "abstract" model in which a time dependent quantity drifts slowly but makes quick jumps from time to time. The second is a realistic physical model for the collective motion of dislocations (the Ananthakrishna set of equations for creep). Hope thus exists that similar changes in the response to noise could forewarn catastrophes in other situations, where such precursor effects should manifest early enough.