Forum for Science, Industry and Business

Sponsored by:     3M 
Search our Site:

 

Machine-learning earthquake prediction in lab shows promise

31.08.2017

Listening to faultline's grumbling gives countdown to future quakes

By listening to the acoustic signal emitted by a laboratory-created earthquake, a computer science approach using machine learning can predict the time remaining before the fault fails.


Researchers at Los Alamos National Laboratory have developed a two-dimensional tabletop simulator that models the buildup and release of stress along an artificial fault. In this image, the simulator is viewed through a polarized camera lens, photo-elastic plates reveal discrete points of stress buildup along both sides of the modeled fault as the far (upper) plate is moved laterally along the fault.

Credit: Los Alamos National Laboratory

"At any given instant, the noise coming from the lab fault zone provides quantitative information on when the fault will slip," said Paul Johnson, a Los Alamos National Laboratory fellow and lead investigator on the research, which was published today in Geophysical Research Letters.

"The novelty of our work is the use of machine learning to discover and understand new physics of failure, through examination of the recorded auditory signal from the experimental setup. I think the future of earthquake physics will rely heavily on machine learning to process massive amounts of raw seismic data. Our work represents an important step in this direction," he said.

Not only does the work have potential significance to earthquake forecasting, Johnson said, but the approach is far-reaching, applicable to potentially all failure scenarios including nondestructive testing of industrial materials brittle failure of all kinds, avalanches and other events.

Machine learning is an artificial intelligence approach to allowing the computer to learn from new data, updating its own results to reflect the implications of new information.

The machine learning technique used in this project also identifies new signals, previously thought to be low-amplitude noise, that provide forecasting information throughout the earthquake cycle. "These signals resemble Earth tremor that occurs in association with slow earthquakes on tectonic faults in the lower crust," Johnson said. "There is reason to expect such signals from Earth faults in the seismogenic zone for slowly slipping faults."

Machine learning algorithms can predict failure times of laboratory quakes with remarkable accuracy. The acoustic emission (AE) signal, which characterizes the instantaneous physical state of the system, reliably predicts failure far into the future. This is a surprise, Johnson pointed out, as all prior work had assumed that only the catalog of large events is relevant, and that small fluctuations in the AE signal could be neglected.

To study the phenomena, the team analyzed data from a laboratory fault system that contains fault gouge, the ground-up material created by the stone blocks sliding past one another. An accelerometer recorded the acoustic emission emanating from the shearing layers.

Following a frictional failure in the labquake, the shearing block moves or displaces, while the gouge material simultaneously dilates and strengthens, as shown by measurably increasing shear stress and friction. "As the material approaches failure, it begins to show the characteristics of a critical stress regime, including many small shear failures that emit impulsive acoustic emissions," Johnson described.

"This unstable state concludes with an actual labquake, in which the shearing block rapidly displaces, the friction and shear stress decrease precipitously, and the gouge layers simultaneously compact," he said. Under a broad range of conditions, the apparatus slide-slips fairly regularly for hundreds of stress cycles during a single experiment. And importantly, the signal (due to the gouge grinding and creaking that ultimately leads to the impulsive precursors) allows prediction in the laboratory, and we hope will lead to advances in prediction in Earth, Johnson said.

###

The paper: "Machine learning predicts laboratory earthquakes" Geophysical Research Letters, http://onlinelibrary.wiley.com/wol1/doi/10.1002/2017GL074677/abstract

The funding: Los Alamos National Laboratory Directed Research and Development (LDRD).

About Los Alamos National Laboratory

Los Alamos National Laboratory, a multidisciplinary research institution engaged in strategic science on behalf of national security, is operated by Los Alamos National Security, LLC, a team composed of Bechtel National, the University of California, BWX Technologies, Inc. and URS Corporation for the Department of Energy's National Nuclear Security Administration. Los Alamos enhances national security by ensuring the safety and reliability of the U.S. nuclear stockpile, developing technologies to reduce threats from weapons of mass destruction, and solving problems related to energy, environment, infrastructure, health and global security concerns.

Media Contact

Nancy Ambrosiano
nwa@lanl.gov
505-667-0471

 @LosAlamosNatLab

http://www.lanl.gov 

Nancy Ambrosiano | EurekAlert!

More articles from Earth Sciences:

nachricht World’s oldest known oxygen oasis discovered
18.01.2018 | Eberhard Karls Universität Tübingen

nachricht A close-up look at an uncommon underwater eruption
11.01.2018 | Woods Hole Oceanographic Institution

All articles from Earth Sciences >>>

The most recent press releases about innovation >>>

Die letzten 5 Focus-News des innovations-reports im Überblick:

Im Focus: Artificial agent designs quantum experiments

On the way to an intelligent laboratory, physicists from Innsbruck and Vienna present an artificial agent that autonomously designs quantum experiments. In initial experiments, the system has independently (re)discovered experimental techniques that are nowadays standard in modern quantum optical laboratories. This shows how machines could play a more creative role in research in the future.

We carry smartphones in our pockets, the streets are dotted with semi-autonomous cars, but in the research laboratory experiments are still being designed by...

Im Focus: Scientists decipher key principle behind reaction of metalloenzymes

So-called pre-distorted states accelerate photochemical reactions too

What enables electrons to be transferred swiftly, for example during photosynthesis? An interdisciplinary team of researchers has worked out the details of how...

Im Focus: The first precise measurement of a single molecule's effective charge

For the first time, scientists have precisely measured the effective electrical charge of a single molecule in solution. This fundamental insight of an SNSF Professor could also pave the way for future medical diagnostics.

Electrical charge is one of the key properties that allows molecules to interact. Life itself depends on this phenomenon: many biological processes involve...

Im Focus: Paradigm shift in Paris: Encouraging an holistic view of laser machining

At the JEC World Composite Show in Paris in March 2018, the Fraunhofer Institute for Laser Technology ILT will be focusing on the latest trends and innovations in laser machining of composites. Among other things, researchers at the booth shared with the Aachen Center for Integrative Lightweight Production (AZL) will demonstrate how lasers can be used for joining, structuring, cutting and drilling composite materials.

No other industry has attracted as much public attention to composite materials as the automotive industry, which along with the aerospace industry is a driver...

Im Focus: Room-temperature multiferroic thin films and their properties

Scientists at Tokyo Institute of Technology (Tokyo Tech) and Tohoku University have developed high-quality GFO epitaxial films and systematically investigated their ferroelectric and ferromagnetic properties. They also demonstrated the room-temperature magnetocapacitance effects of these GFO thin films.

Multiferroic materials show magnetically driven ferroelectricity. They are attracting increasing attention because of their fascinating properties such as...

All Focus news of the innovation-report >>>

Anzeige

Anzeige

Event News

10th International Symposium: “Advanced Battery Power – Kraftwerk Batterie” Münster, 10-11 April 2018

08.01.2018 | Event News

See, understand and experience the work of the future

11.12.2017 | Event News

Innovative strategies to tackle parasitic worms

08.12.2017 | Event News

 
Latest News

Let the good tubes roll

19.01.2018 | Materials Sciences

How cancer metastasis happens: Researchers reveal a key mechanism

19.01.2018 | Health and Medicine

Meteoritic stardust unlocks timing of supernova dust formation

19.01.2018 | Physics and Astronomy

VideoLinks
B2B-VideoLinks
More VideoLinks >>>