Mathematical Model finds Acoustic Signal that May Predict Earthquakes

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Discussion Overview

The discussion centers around a mathematical model that identifies acoustic signals potentially predictive of earthquakes. Participants explore the implications of these signals, their origins, and related phenomena, including the acoustic properties of sand dunes. The scope includes theoretical insights, exploratory reasoning, and technical discussions regarding the mechanics of sound production in geological contexts.

Discussion Character

  • Exploratory
  • Technical explanation
  • Conceptual clarification
  • Debate/contested
  • Mathematical reasoning

Main Points Raised

  • Some participants reference a study indicating that acoustic signals from earthquake faults may predict future seismic events, suggesting a connection between stress chain collapse and sound emission.
  • Others express optimism about the potential for these acoustic signals to provide advance warning of earthquakes, although some caution that short-term predictions remain challenging.
  • A participant proposes the idea of listening to the acoustic signals, suggesting that audio playback could enhance understanding of the phenomenon.
  • Discussion includes a comparison to unexplained underwater sounds and the acoustic characteristics of sand dunes, with references to external articles for context.
  • One participant questions the relationship between sand grain size and sound frequency, proposing dimensional analysis to explore this connection further.
  • Another participant elaborates on the mechanics of sound production in sand dunes, suggesting that the sound may arise from internal movements rather than surface interactions, and discusses the propagation of movements within the dune structure.
  • Mathematical models are proposed to estimate the relationship between grain size and sound frequency, with calculations presented to explore potential acoustic resonances.

Areas of Agreement / Disagreement

Participants express a range of views regarding the implications of the acoustic signals for earthquake prediction, with some expressing optimism and others highlighting the difficulties involved. There is no consensus on the exact mechanisms of sound production in sand dunes or the applicability of dimensional analysis to connect grain size and frequency.

Contextual Notes

Participants note uncertainties regarding the mechanisms behind sound production in both earthquake faults and sand dunes, as well as the limitations of current models and assumptions about grain interactions.

Who May Find This Useful

This discussion may be of interest to those studying geophysics, acoustics, and the mechanics of granular materials, as well as individuals curious about the predictive capabilities of acoustic signals in geological contexts.

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https://www.upi.com/Science_News/20...signal-preceding-seismic-shake/4431564489814/
"Previous machine-learning studies found that the acoustic signals detected from an earthquake fault can be used to predict when the next earthquake will occur," Ke Gao, a computational geophysicist at Los Alamos National Laboratory, ... "This new modeling work shows us that the collapse of stress chains inside the earthquake gouge emits that signal in the lab, pointing to mechanisms that may also be important in Earth."
 
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Sounds promising, thanks for posting it. From the summary article:
Thanks to the simulations, scientists are beginning to understand how acoustic signals can reveal the evolution of stress within a fault structure. Eventually, these acoustic signals could be used to predict earthquakes many hours, perhaps days, in advance.
Paging @davenn
 
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Thanks for the link, @jedishrfu , an interesting read

Thanks @berkeman for the heads up :smile:

Looks to be a promising area of research. I'm not one to say that short term quake prediction will
never happen, just that it's going to be very difficult
 
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The high-tech version of an ominous creak in the timberwork.

It might be interesting to listen to an audio version of the signal, with the playback speed suitably adjusted for human hearing.

They may have provided the raw data under "supplemental material"
https://journals.aps.org/prl/abstract/10.1103/PhysRevLett.123.048003(I don't have access.)

Random thought: can pigeons be trained for this task?
 
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Re. the singing sand dunes (previous post)...
Some key inputs from the article:
It's not necessarily the motion of the sandy ocean that determines the pitch of the note—it's the size of the grains, though why the size matters is still unknown. ... The one-note Moroccan sand grains are almost entirely the same size—160 millionths of a meter, or microns across—but the noisy Omani sands run the gamut, from 150 to 300 microns.

But when the messy sands were sieved down to just the 200-to-250 micron particles, the tone cleared into a single tone. "The size of the grain controls the actual sound," Dagois-Bohy concluded.
Why exactly this happens, and how the sound itself is created, is still uncertain.

Can we apply dimensional analysis to connect the ~ 300 micron sand size to the ~100 Hz frequency, and thus get some clue about the kinds of things that may be going on? How can we get the latter order of magnitude from the former?
 
Swamp Thing said:
Can we apply dimensional analysis to connect the ~ 300 micron sand size to the ~100 Hz frequency, and thus get some clue about the kinds of things that may be going on? How can we get the latter order of magnitude from the former?

The speed of sound in grains that size puts their acoustic resonant frequency in the megahertz range. So that's one possibility eliminated.

Let's try the time between impacts between the grains, and assume the average spacing is one grain.
  • grain size 3E-4 meter; 100Hz = 10mS between impacts
  • in 1 sec. a grain would move 3E-2 meter, or 1.2in.
  • in 1 min. it would move 1.8 meter, or just under 6ft.
Does this seem a ballpark estimate for the speed of sand movement?

If not, how about if a grain impacts another grain at two to three times the grain spacing? That would double or triple the travel speed. My wild guess is they would hit at the most every other grain, traveling at least 3.6M/min, 11.5ft/min.

Hmm... still seems slow. Hope it helps someone else come up with a conjecture.

Cheers,
Tom
 
I expect the sound is produced from movement within the dune, not from the exposed surface. The fact that it has a clear tone suggests it is composed of many small identical movements that are coupled in some way.

If you take a bag of glass marbles and wring it between your hands it will produce a distinctive growl as the marbles slip and stick against each other.

Consider three interlocked gear wheels, they cannot roll. To roll they must be separated far enough for one gear pair to disengage. Likewise, close-packed spheres cannot roll against each other because every group of three in contact is locked by friction. Each grain contacts up to 12 others which effectively locks a dune in place.

In order that a shear zone form within a dune, a slip of a plane must take place. That is unlikely as adjacent planes are well interlocked. So, imagine one grain somewhere separates from one third of it's neighbours, immediately that would unlock a group and a rotation could take place that might then propagate as a wave along a shear zone through the body of the dune. Each rotation frees the way for the next, and so on.

The question then becomes, what is the minimum movement that will self propagate and how much time does it take each movement to propagate? The reciprocal of that is the audible frequency.

Maybe it can be modeled as a propagation of holes into each of which a grain falls to create another hole, to be modeled as a gravity wave. So how long does it take a grain to free-fall its own radius?
r = ½ ⋅ g ⋅ t2;
t = √( 2 ⋅ r / g )
For 0.2 mm diameter grain, r = 1e-4 metre; g = 9.8;
T = 4.5 millisec; f = 220 Hz.
 
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Swamp Thing said:
to connect the ~ 300 micron sand size to the ~100 Hz frequency
F = 100 Hz; T = 10 millisec;
h = ½ ⋅ g ⋅ t2
h = 0.49 mm which represents a fall of 1.63 diameters.
 
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