Volume 62, Number 22 PHYSICAL REVIEW LETTERS Properties of ... · Volume 62, Number 22 PHYSICAL...

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Volume 62, Number 22 PHYSICAL REVIEW LETTERS 29 May 1989 Properties of Earthquakes Generated by Fault Dynamics J. M. Carlson and J. S. Langer Institute for Theoretical Physics, University of California, Santa Barbara. California 93106 (Received 6 March 1989) We present a model for fault dynamics consisting of a uniform chain of blocks and springs pulled slowly across a rough surface. The only nonlinear element of our model is a slip-stick friction force be tween the blocks and the surface. We find that this model gives rise to events of all sizes. Our numerical evaluation of the distribution of earthquake magnitudes results in a power-law spectrum similar to what is observed in nature. Like certain other dissipative dynamical systems, the observed large fluctuations in earthquake magnitude persist because the system is in a state of marginal stability. PACS numbers: 9l.30.Px, 05.40.+J, 05.45.-rb Systems which have no intrinsic time scales or length scales have been the subject of much investigation in re cent years. While extensive work has been done to characterize certain features of these kinds of systems, until recently there has been little success at providing detailed mechanisms for their evolution. In a series of papers Bak, Tang, and Wiesenfeld1 and, later, Kadanoff, Nagel, Wu, and Zhou2 studied various cellular automa ta, loosely referred to as "sandpiles." In these models, sand is dropped slowly, one grain at a time, onto random positions on a lattice. Numerically they found that, for many different rules of evolution of the pile, the distribu tion of avalanche sizes displays a power-law spectrum and that, at any given time, the configuration of sand on the pile has a fractal geometry. Bak, Tang, and Wiesen feld concluded that the observed large fluctuations in avalanche size and the spatial self-similarity result from the fact that the attractor of the dynamics is marginally stable; in essence the system is perpetually in a critical state. They introduced the term self-organized criticali ty to describe this behavior. To the best of our knowledge, the model for earth quakes that we shall describe here is the first demon strated example of self-organized criticality in a deter ministic continuum dynamical system. This model has two main advantages compared to the cellular automata. First, because we are working with a system of differential equations, certain analytic results can be ob tained. Second, there is no explicit randomness in the model; instead, the system evolves deterministically from irregular initial conditions. The system is illustrated schematically in Fig. 1(a). Several variations of this model were studied previously both numerically and experimentally by Burridge and Knopoff." The model consists of N blocks of equal mass m located at positions Xjit) along the x axis, which we imagine to be the axis of a lateral fault. Each block is connected to its two neighbors by harmonic springs of strength kc and, when there are no additional forces on the system, the equilibrium spacing between blocks is a. The blocks are pulled individually forward through elas tic couplings (leaf springs or torsion elements) of strength kp, which move at constant loading velocity i\ This loading mechanism corresponds to slow steady de formation far away from the point of. contact of two tec tonic plates whose linear elastic properties are described by the spring constants kc and kp. Finally, each block is subject to a friction force F(X) which depends only on the velocity of the block. The important nonlinearities in the problem are contained in the function F(X) illustrat ed in Fig. 1 (b). The equations of motion for this system are mXj = kc (Xj +, - 2Xj + Xj-1) -k,,(Xj-vt)-F(Xj). (1) The rest of this Letter will be devoted to describing some solutions of these equations. Note that, unlike many traditional earthquake models, Eq. (l) contains no ex plicit spatial inhomogeneity4-5 or memory effects.6-9 In stead we will show how the dynamics alone is sufficient to generate a wide spectrum of events. A trivial solution to Eq. (1) is given by uniform (b) FIG. I. (a) Block and spring system and (b) friction force F(X). For the numerical results given in Figs. 3 and 4 the pa rameters take the values w = l, Af=2500, ftp"40, a = \. and r=0.01. For the friction force we use F(X) =F0/(\ +X) for X>0 with Fo-50. 2632 1989 The American Physical Society

Transcript of Volume 62, Number 22 PHYSICAL REVIEW LETTERS Properties of ... · Volume 62, Number 22 PHYSICAL...

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Volume 62, Number 22 P H Y S I C A L R E V I E W L E T T E R S 29 May 1989

Properties of Earthquakes Generated by Fault Dynamics

J. M. Carlson and J. S. LangerInstitute for Theoretical Physics, University of California, Santa Barbara. California 93106

(Received 6 March 1989)

We present a model for fault dynamics consisting of a uniform chain of blocks and springs pulledslowly across a rough surface. The only nonlinear element of our model is a slip-stick friction force between the blocks and the surface. We find that this model gives rise to events of all sizes. Our numericalevaluation of the distribution of earthquake magnitudes results in a power-law spectrum similar to whatis observed in nature. Like certain other dissipative dynamical systems, the observed large fluctuationsin earthquake magnitude persist because the system is in a state of marginal stability.

PACS numbers: 9l.30.Px, 05.40.+J, 05.45.-rb

Systems which have no intrinsic time scales or lengthscales have been the subject of much investigation in recent years. While extensive work has been done tocharacterize certain features of these kinds of systems,until recently there has been little success at providingdetailed mechanisms for their evolution. In a series ofpapers Bak, Tang, and Wiesenfeld1 and, later, Kadanoff,Nagel, Wu, and Zhou2 studied various cellular automata, loosely referred to as "sandpiles." In these models,sand is dropped slowly, one grain at a time, onto randompositions on a lattice. Numerically they found that, formany different rules of evolution of the pile, the distribution of avalanche sizes displays a power-law spectrumand that, at any given time, the configuration of sand onthe pile has a fractal geometry. Bak, Tang, and Wiesenfeld concluded that the observed large fluctuations inavalanche size and the spatial self-similarity result fromthe fact that the attractor of the dynamics is marginallystable; in essence the system is perpetually in a criticalstate. They introduced the term self-organized criticality to describe this behavior.

To the best of our knowledge, the model for earthquakes that we shall describe here is the first demonstrated example of self-organized criticality in a deterministic continuum dynamical system. This model hastwo main advantages compared to the cellular automata.First, because we are working with a system ofdifferential equations, certain analytic results can be obtained. Second, there is no explicit randomness in themodel; instead, the system evolves deterministically fromirregular initial conditions.

The system is illustrated schematically in Fig. 1(a).Several variations of this model were studied previouslyboth numerically and experimentally by Burridge andKnopoff." The model consists of N blocks of equal massm located at positions Xjit) along the x axis, which weimagine to be the axis of a lateral fault. Each block isconnected to its two neighbors by harmonic springs ofstrength kc and, when there are no additional forces onthe system, the equilibrium spacing between blocks is a.The blocks are pulled individually forward through elas

tic couplings (leaf springs or torsion elements) ofstrength kp, which move at constant loading velocity i\This loading mechanism corresponds to slow steady deformation far away from the point of. contact of two tectonic plates whose linear elastic properties are describedby the spring constants kc and kp. Finally, each block issubject to a friction force F(X) which depends only onthe velocity of the block. The important nonlinearities inthe problem are contained in the function F(X) illustrated in Fig. 1 (b).

The equations of motion for this system are

mXj = kc (Xj +, - 2Xj + Xj-1)

- k , , ( X j - v t ) - F ( X j ) . ( 1 )The rest of this Letter will be devoted to describing somesolutions of these equations. Note that, unlike manytraditional earthquake models, Eq. (l) contains no explicit spatial inhomogeneity4-5 or memory effects.6-9 Instead we will show how the dynamics alone is sufficientto generate a wide spectrum of events.

A trivial solution to Eq. (1) is given by uniform

(b)

FIG. I. (a) Block and spring system and (b) friction forceF(X). For the numerical results given in Figs. 3 and 4 the parameters take the values w = l, Af=2500, ftp"40, a = \. andr=0.01. For the friction force we use F(X) =F0/(\ +X) forX>0 with Fo-50.

2632 1989 The American Physical Society

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Volume 62, Number 22 P H Y S I C A L R E V I E W L E T T E R S 29 May 1989

(a)

0.03

•x 0.02

0.01

TIME t

(b)

TIME t

FIG. 3. Complex solutions: velocity X, vs position j andtime t. The smallest features in (a) are periodic creep eventswhich involve only one block. The larger features are catastrophic events which involve a larger number of blocks. Thegreat event illustrated in (b) involves all of the blocks andessentially resets the system.

The equation of motion for the slipping blocks is givenby

nmX=-2kcX-nkp(X-vt)-nF(X) , (3)

where X describes the coherent motion of the n blocks,and we have absorbed an unimportant constant on theright-hand side (which is determined by the positions ofthe two blocks which remain fixed) into our definition ofX. Observe that all forces, except those due to the twosprings which connect the slipping blocks to the rest ofthe system, act equally on all the slipping blocks and arethus preceded by a factor of n. In the limit of large n,(3) reduces to the equation for periodic events involvingthe whole system discussed previously. The importantfeature of the model which has been left out of Eq. (3) isthe amplification of spatial irregularities while blocksslip. Our assumption in (3) is that the system is locally

sufficiently smooth for an event of size n to occur. Equation (3) allows us to determine analytically the approximate amplitude and shape of an event of size n. However, in the original system [Eq. (1)], the blocks are left ina scrambled state after a slipping event, and smaller orlarger events will follow.

During the small creep events, the slipping blocks attain only very small velocities, and thus to a good approximation we can linearize F(X): FCY)«F0— F'(0)X. In this approximation (3) becomes the equation of motion for an antidamped harmonic oscillatorwith a slowly increasing bias force. Letting X(t)-~ea',we find that the solution oscillates (a is complex) when

Am kp-r2kc >[F'(0)]2 (4)

This condition can be satisfied, for example, when kc islarge and n is sufficiently small. In the limit thatF'(0)=0 and kp<Kkc,u the velocity X simply oscillatessinusoidally between zero and nkpv/kc. WhenF'(0) < 0, the antidamping results in a residual force onthe blocks when they restick. Because the maximum velocity of these small-amplitude events is less than theloading speed v, these events never release much of thestrain accumulated in the pulling spring.

When the condition given in Eq. (4) is violated, thesolution of (3) in the linearized regime grows exponentially with time (a is real). Eventually the group ofblocks attains a velocity for which F(X) is small. Thelarge catastrophic events exhibit this type of behavior.We can obtain an approximate solution for X(t) duringa large event by letting F(X) ~ 0 while the blocks areslipping. In this approximation and in the limit of slowpulling velocities, while the blocks slip (3) has a solutionof the form

X(t) = - Focos(cot), (5)

to mwhere co-=kp/m + 2kc/nm, and the coefficient Fo/co2mis determined by the initial conditions X(0) =0 and— oj~X(0)=Fo/m, which specifies that the spring forcesbalance the threshold static friction. A more carefulanalysis including the linear approximation to F(X) forsmall velocities produces similar results. In either case,unlike the small-amplitude creep events, during a largeevent the blocks always attain a velocity greater than theloading speed. When the blocks eventually stop slippingthere is a residual force which compresses the pullingsprings, resulting in a relatively long delay before theseblocks are involved in another slip event.

Finally, from our numerical results we have calculatedthe distribution of earthquake magnitudes. The magnitude M is defined to be the natural logarithm of theearthquake moment Mo, which for our model can be taken to be

i * /cv t X jd t , (6)

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Volume 62, Number 22 P H Y S I C A L R E V I E W L E T T E R S 29 May 1989

'

0 5 1 0 1 5 2 0MAGNITUDE yft

FIG. 4. Distribution of earthquake magnitudes N(M). Forthis result the number of blocks is ^ = 200 and the constant Cin Eq. (6) is IO6*.

where C is a constant. The distribution N(M) producedby our numerical results is illustrated in Fig. 4, and is instrikingly good agreement with what has been observedfor real earthquakes:12 \nN(M) ~A —BM, where A is aconstant and _?«!. Even the obvious discrepancy— the frequency of great events is too large—may beconsistent with observations. We tentatively attributethe latter phenomenon to the fact that both our computer model and real earthquake faults necessarily havefinite lengths.

The observed large fluctuations in the magnitudes ofearthquakes in nature suggest that certain dynamicalmodels of faults may be ideal candidates for the study ofgeneral features of self-organized criticality. Many faultmodels incorporate an intrinsic spatial variation which isimportant for certain features of earthquakes. For example, Burridge and Knopoff3 showed that local high-

viscosity regions incorporated into this model can generate sequences of aftershocks in qualitatively goodagreement with what is observed. In this paper we haveshown that the dynamics alone is sufficient to generate awide range of events. Somewhat alarmingly, our resultssuggest that small events lead to smoothing on a largerscale, resulting in larger events later on. Currently weare analyzing our results in more detail to determine thecorrelations between large events.

We have benefitted from many useful discussions withJ. R. Rice, Chao Tang, Franco Nori, Hiizu Nakanishi,and Glen Swindle. This research was supported by U.S.Department of Energy Grant No. DE-FG03-84ER45108and also in part by the National Science Foundation under Grant No. PHY82-17853, supplemented by fundsfrom the National Aeronautics and Space Administration, at the University of California at Santa Barbara.

'P. Bak. C. Tang, and K. Wiesenfeld, Phys. Rev. Lett. 59,381 (1987); Phys. Rev. A 38, 36 (1988); C. Tang and P. Bak,Phys. Rev. Lett. 60, 2347 (1988); J. Stat. Phys. 51, 7977(1988).

2L. Kadanoff, S. Nagel, L. Wu, and S. Zhou, Phys. Rev. A(to be published).

3R. Burridge and L. Knopoff, Bull. Seismol. Soc. Amer. 57,341 (1967).

4S. T. Tse and J. R. Rice, J. Geophys. Res. 91, 9452 (1986).5For related work on the theory of random pinning forces in

charge-density waves, see S. N. Coppersmith and P. B. Little-wood. Phys. Rev. B 36, 31 I (1987).

6A. L. Ruina, J. Geophys. Res. 88, 359 (1983).7J. R. Rice, Pure Appl. Geophys. 121, 443 (1983).8F. Horowitz, Ph.D. thesis, Cornell University, Ithaca, 1989

(unpublished).9J. H. Dieterich, Pure Appl. Geophys. 116, 790 (1978).'"Periodic boundary conditions, however, always seem to lead

to smooth propagating modes."If the system is to have sensible elastic properties in the

continuum limit, a—0, then ma, kca, and kp/a must remainfinite. Thus we choose kc^kp.

12B. Gutenberg and C. F. Richter, Ann. Geofis. 9, 1 (1956).

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