<?xml version="1.0" encoding="utf-8" standalone="yes"?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>Project-Archives |</title><link>https://eqsci.mit.edu/camcat/project-archive/</link><atom:link href="https://eqsci.mit.edu/camcat/project-archive/index.xml" rel="self" type="application/rss+xml"/><description>Project-Archives</description><generator>HugoBlox Kit (https://hugoblox.com)</generator><language>en-us</language><lastBuildDate>Wed, 27 Apr 2016 00:00:00 +0000</lastBuildDate><image><url>https://eqsci.mit.edu/camcat/media/icon_hu_eee4a95885829ab2.png</url><title>Project-Archives</title><link>https://eqsci.mit.edu/camcat/project-archive/</link></image><item><title>Seismicity on rough faults</title><link>https://eqsci.mit.edu/camcat/project-archive/roughness/</link><pubDate>Wed, 27 Apr 2016 00:00:00 +0000</pubDate><guid>https://eqsci.mit.edu/camcat/project-archive/roughness/</guid><description>&lt;p&gt;Faults are not planar features, but instead exhibit geometrical roughness at all scales. This affects the slip behavior of individual ruptures, as well as the seismicity patterns. Our goal is to understand how fault roughness affects seismic sequences.&lt;/p&gt;
&lt;p&gt;We have been exploring this question with quasi-dynamic rate-state simulations. The effect of roughness is easily understood in terms of normal stress variations, as follows. Slip on a rough fault generates regions of compressive stresses, which are stronger and tend to act as seismic asperities: they are locked between earthquakes, and once they accelerate they break in fast (seismic) events. Other regions experience tensile stress perturbations due to slip, and these weaker regions tend to slip in a stable matter (creep). Foreshock sequences are controlled by the stress transfer between these two regions, and several observed features (such as the temporal evolution of foreshocks and their tendency to migrate) arise naturally from these interactions.&lt;/p&gt;
&lt;p&gt;In future work we will explore how a rough fault responds to external stress perturbations such as those from regional and remote earthquakes or anthropogenic activites (e.g. fluid injection). We will also extend our simulations to 3-D and include inelastic effects.&lt;/p&gt;</description></item><item><title>Fault mechanics and earthquake cycles</title><link>https://eqsci.mit.edu/camcat/project-archive/eq-cycles/</link><pubDate>Wed, 27 Apr 2016 00:00:00 +0000</pubDate><guid>https://eqsci.mit.edu/camcat/project-archive/eq-cycles/</guid><description>&lt;p&gt;While some seismic sources rupture in characteristic, quasi-periodic earthquakes, most faults produce a more irregular pattern, with temporal clustering and a power-law distribution of rupture lengths. Why do we see such different behaviors?&lt;/p&gt;
&lt;p&gt;We&amp;rsquo;ve been addressing this question from the prospective of fracture mechanics, connecting fault physics at a microscopic scale with the timing and extent of earthquake ruptures. Energy balance criteria predict that the timing and size of seismic events is controlled by the dimension of a fault relative to a characteristic length arising from frictional and elastic properties; for sufficiently large faults, this leads to power-law distributions commonly observed in earthquake catalogs. On the other hand, small faults can rupture in simple, quasi-periodic sequences of identical events. We have depeloped theoretical arguments predicting the recurrence intervals and its scaling with magnitude, in agreement with observations of small repeating earthquakes worldwide.&lt;/p&gt;
&lt;p&gt;Until now, we have considered a rather idealized fault geometry and spatial distribution of frictional properties. Current and future work explores more complex and realistic cases, with applications to subduction zone cyles.&lt;/p&gt;</description></item><item><title>The physics of small earthquakes</title><link>https://eqsci.mit.edu/camcat/project-archive/small-eqk/</link><pubDate>Wed, 27 Apr 2016 00:00:00 +0000</pubDate><guid>https://eqsci.mit.edu/camcat/project-archive/small-eqk/</guid><description>&lt;p&gt;Small repeating earthquakes are events characterized by very similar waveforms, and overlapping rupture areas. Unlike most other earthquakes, they are very periodic; they are commonly interpreted as rupturing an isolated asperity embedded in a velocity-strengthening (creeping) fault. Since they are driven by aseismic slip, they are an invaluable tool to probe creeping sections of a fault, and detect spatio-temporal variations in slip rate.
I used simple crack models to derive analytical expressions for the recurrence interval as a function of asperity dimension and seismic moment. These expressions are in excellent agreement with the scaling between recurrence interval and seismic moment observed in the simulations: $T_r \sim M_0^{1/ 6}$ (see figure), consistent with observations.&lt;/p&gt;
&lt;p&gt;While these results are based on a relatively simple model (circular, uniform asperities), they provide a useful framework to interpret the seismic behavior of small asperities. They make specific predictions, such as a dependence of stress drop on magnitude and a transition between central ruptures for small asperities to lateral ruptures for large asperities (where small and large is a well defined ratio between the asperitity radius and the nucleation radius); similarly, the occurrence of partial ruptures is expected for asperities exceeding a particular dimension.&lt;/p&gt;
&lt;p&gt;Cattania, C. and P. Segall (2018), &lt;em&gt;Crack models of repeating earthquakes predict observed moment-recurrence scaling&lt;/em&gt;, J. Geophys. Res. Solid Earth (
;
)&lt;/p&gt;
&lt;hr&gt;
&lt;p&gt;&lt;strong&gt;Current and future efforts:&lt;/strong&gt; The results above imply a break of self-similarity near the nucleation dimension. Could this be seen in the data? To answer this question, we first need a theoretical source model for small earthquakes, which does not assume constant rupture velocity but instead considers the initial acceleration. I will present some preliminary results on this topic at the 2020 AGU Fall Meeting.&lt;/p&gt;</description></item><item><title>Static stress triggering in operational earthquake forecasting</title><link>https://eqsci.mit.edu/camcat/project-archive/eof/</link><pubDate>Wed, 27 Apr 2016 00:00:00 +0000</pubDate><guid>https://eqsci.mit.edu/camcat/project-archive/eof/</guid><description>&lt;p&gt;&lt;em&gt;with Sebastian Hainzl and the Collaboratory for the Study of Earthquake Predictability (CSEP)&lt;/em&gt;&lt;/p&gt;
&lt;p&gt;Aftershock sequences take place after all moderate and large earthquakes, and are a significant source of hazard. A primary mechanism for aftershocks is the static deformation and stresses in vicinity of a mainshock. Physics-based models for Operational Earthquake Forecasting bring our physical knowledge of elasticity and friction into time-dependent, probabilistic earthquake forecasts.&lt;/p&gt;
&lt;p&gt;Our approach has been guided by an attempt to construct physically consistent and realistic models of the processes involved, by including time-dependent (aseismic) fault slip and a realistic fault geometry. We found that deep afterslip following large subduction earthquakes significantly contributes to triggering seismicity on shallow crustal faults (
). Another outcome of this work is that stress heterogeneity due to the geometrical complexity of a fault system has a first-order impact in model behavior (
), and it significantly improves performance.
This improvement was confirmed by a collaborative experiment carried out within CSEP for the aftershock sequence of the 2010 Canterbury (New Zealand) earthquake (
). In a collaboration with Simone Mancini (British Geological Survey/University of Bristol), Margarita Segou (BGS) and Max Werner (Univeristy of Bristol) we have further improved and tested these models, in the context of
.&lt;/p&gt;
&lt;p&gt;External links:
on phys.org&lt;/p&gt;</description></item><item><title>Seismic swarms and aseismic slip driven by dikes</title><link>https://eqsci.mit.edu/camcat/project-archive/miyakejima/</link><pubDate>Wed, 27 Apr 2016 00:00:00 +0000</pubDate><guid>https://eqsci.mit.edu/camcat/project-archive/miyakejima/</guid><description>&lt;p&gt;In addition to static stress changes from earthquakes on nearby faults, seismic sequences can be triggered by stress perturbations due to a number of processes, including magma migration and seismic waves from remote earthquakes.&lt;/p&gt;
&lt;p&gt;With Eleonora Rivalta, Luigi Passarelli and Yosuke Aoki, we analyzed a seismic swarm during the 2000 Miyakejima dike intrusion and found evidence of aseismic slip on a complex fault system.&lt;/p&gt;
&lt;p&gt;With Jeff McGuire and John Collins, we used a seismic catalog from ocean bottom seismometers in the East Pacific Rise, and detected instances of dynamic earthquake triggering from remote mainshocks.&lt;/p&gt;</description></item><item><title>Dynamic triggering on transform faults</title><link>https://eqsci.mit.edu/camcat/project-archive/dyntrig/</link><pubDate>Wed, 27 Apr 2016 00:00:00 +0000</pubDate><guid>https://eqsci.mit.edu/camcat/project-archive/dyntrig/</guid><description>&lt;p&gt;We used stastical tools to analyze data from ocean bottom seismometers in the East Pacific Rise, and detect instances of dynamic earthquake triggering from remote mainshocks.&lt;/p&gt;</description></item></channel></rss>