Pyroxene-pyrolite and plagioclase-pyrolite in inclusions,with Norites,in an Alkali Basalt (Causses,France)

In three representative nodules contained in an alkali-olivine basalt, a succession of cumulate cycles has been noted: $$\begin{gathered} 1) olivine - orthopyroxene + \varepsilon (Cpx + Sp.); \hfill \\ 2) ortho - clinopyroxene + \varepsilon (Ol. + Sp. + Plag); \hfill \\ 3) ortho - clinopyroxene + Plag + \varepsilon (Ol. + Sp.). \hfill \\ \end{gathered} $$ The element distribution in the minerals enables us to say that these mafic and ultramafic nodules formed near the stability line of plagioclase at about 10 kb. These cumulates, which belong to a comagmatic series, from picrites to basalts, were formed in the upper mantle. They are associated with norites — Plag. + Opr. + Cpx. +≡ (Il. + Bi) — belonging to the same series, but crystallized in the deep part of the crust. On the other hand, these norites could be xenoliths taken away from an infragranitic basement of granulite facies.     

The boundary value problem of Poisson’s equation with Stokes’ boundary condition

The following Poisson’s equation with the Stokes’ boundary condition is dealt with $$\left\{ \begin{gathered} \nabla ^2 T = - 4\pi Gp outside S, \hfill \\ \left. {\frac{{\partial T}}{{\partial h}} = \frac{1}{\gamma }\frac{{\partial y}}{{\partial h}}T} \right|_s = - \Delta g, \hfill \\ T = O\left( {r^{ - 3} } \right) at infinity, \hfill \\ \end{gathered} \right.$$ whereS is reference ellipsord. Under spherical approximation transformation, the ellipsoidal correction terms about the boundary condition, the equation and the density in the above BVP are respectively given. Therefore, the disturbing potentialT can he obtained if the magnitudes aboveO(ε⁴) are neglected.     

Estimation du débit de SO2, HCl et HF émis par le volcan Vulcano (Italie)

The flow rate of SO₂, HCl and HF was calculated from a transfer coefficient obtained by measuring the concentration of a tracer gas (SF₆) emitted at the plume and analysed down wind with a field gas chromatograph. The results obtained are: $$\begin{gathered} SO_2 = 2.3 \pm 0.4 t/day \hfill \\ HCl = 6.4 \pm 0.4 t/day \hfill \\ HF = 0.11 \pm 0.3 t/day \hfill \\ \end{gathered} $$      

Lyapunov exponent and dimension of the strange attractor of elastic frictional system

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Long-term earthquake prediction in the Aegean area based on a time and magnitude predictable model

The Aegean and surrounding area (34°N–43°N, 18°E–30°E) is separated into 76 shallow and intermediate depth seismogenic sources. For 74 of these sources intervent times for strong mainshocks have been determined by the use of instrumental and historical data. These times have been used to determine the following empirical relations: $$\begin{gathered} \log T_t = 0.24M_{\min } + 0.25M_p - 0.36\log \dot M_0 + 7.36 \hfill \\ M_f = 1.04M_{\min } - 0.31M_p + 0.28\log \dot M_0 - 4.85 \hfill \\ \end{gathered} $$ whereT ₁ is the interevent time, measured in years,M _min the surface wave magnitude of the smallest mainshock considered,M _p the magnitude of the preceding mainshock,M _f the magnitude of the following mainshock, \(\dot M_0 \) the moment rate in each source per year. A multiple correlation coefficient equal to 0.74 and a standard deviation equal to 0.18 for the first of these relations were calculated. The corresponding quantities for the second of these relations are 0.91 and 0.22. On the basis of the first of these relations and taking into consideration the time of occurence and the magnitude of the last mainshock, the probabilities for the occurrence of mainshocks in each seismogenic source of this region during the decade 1993–2002 are determined. The second of these relations has been used to estimate the magnitude of the expected mainshock.     

Estimates of fracture parameters of earthquakes

A new estimate of the fracture parameters of earthquakes is provided in this paper. By theMuskhelishvili method (1953) a number of basic relations among fracture-mechanics parameters are derived. A scheme is proposed to evaluate the slip weakening parameters in terms of fault dimension, average slip, and rise time, and the new results are applied to 49 events compiled in the earthquake catalogue ofPurcaru andBerckhemer (1982). The following empirical relations are found in the paper: $$\begin{gathered} \frac{{\tau _B - \tau _f }}{{\tau _\infty - \tau _f }} = 2.339 \hfill \\ {{\omega _c } \mathord{\left/ {\vphantom {{\omega _c } {W = 0.113}}} \right. \kern-\nulldelimiterspace} {W = 0.113}} \hfill \\ \log G_c \left( {{{dyne} \mathord{\left/ {\vphantom {{dyne} {cm}}} \right. \kern-\nulldelimiterspace} {cm}}} \right) = 2 \log L (km) + 6.167 \hfill \\ \log \delta _c (cm) = 2 \log L (km) - 1.652 \hfill \\ \end{gathered} $$ whereG _c is the specific fracture energy,ω _c the size of the slip weakening zone,δ _c the slip weakening displacement,τ _B ?τ _f the drop in strength in the slip weakening zone,τ _∞?τ _f the stress drop,L the fault length, andW the fault width. The investigation of 49 shocks shows that the range of strength dropτ _B ?τ _f is from several doze to several hundred bars at depthh<400 km, but it can be more than 10³ bars ath>500 km; besides, the range of the sizeω _c of the strength degradation zone is from a few tenths of a kilometer to several dozen kilometers, and the range of the slip weakening displacementδ _c is from several to several hundred centimeters. The specific fracture energyG _c is of the order of 10⁸ to 10¹¹ erg cm^?2 when the momentM ₀ is of the order of 10²³ to 10²⁹ dyne cm.     

Long-term earthquake prediction in the circum-pacific convergent belt

Investigation of the time-dependent seismicity in 274 seismogenic regions of the entire continental fracture system indicates that strong shallow earthquakes in each region exhibit short as well as intermediate term time clustering (duration extending to several years) which follow a power-law time distribution. Mainshocks, however (interevent times of the order of decades), show a quasiperiodic behaviour and follow the ‘regional time and magnitude predictable seismicity model’. This model is expressed by the following formulas $$\begin{gathered} \log T_t = 0.19 M_{\min } + 0.33 M_p - 0.39 \log m_0 + q \hfill \\ M_f = 0.73 M_{\min } - 0.28 M_p + 0.40 \log m_0 + m \hfill \\ \end{gathered} $$ which relate the interevent time,T _t (in years), and the surface wave magnitude,M _f , of the following mainshock: with the magnitude,M _min, of the smallest mainshock considered, the magnitude,M _p , of the preceded mainshock and the moment rate,m ₀ (in dyn.cm.yr^?1), in a seismogenic region. The values of the parametersq andm vary from area to area. The basic properties of this model are described and problems related to its physical significance are discussed. The first of these relations, in combination with the hypothesis that the ratioT/T _t , whereT is the observed interevent time, follows a lognormal distribution, has been used to calculate the probability for the occurrence of the next very large mainshock (M _s ≥7.0) during the decade 1993–2002 in each of the 141 seismogenic regions in which the circum-Pacific convergent belt has been separated. The second of these relations has been used to estimate the magnitude of the expected mainshock in each of the regions.     

Ground-motion Attenuation Relation from Strong-motion Records of the 2001 Mw 7.7 Bhuj Earthquake Sequence (2001–2006), Gujarat, India

Predictive relations are developed for peak ground acceleration (PGA) from the engineering seismoscope (SRR) records of the 2001 M_w 7.7 Bhuj earthquake and 239 strong-motion records of 32 significant aftershocks of 3.1 ≤ M_w ≤ 5.6 at epicentral distances of 1 ≤ R ≤ 288 km. We have taken advantage of the recent increase in strong-motion data at close distances to derive new attenuation relation for peak horizontal acceleration in the Kachchh seismic zone, Gujarat. This new analysis uses the Joyner-Boore’s method for a magnitude-independent shape, based on geometrical spreading and anelastic attenuation, for the attenuation curve. The resulting attenuation equation is,

The surface roughness and planetary boundary layer

Applications of the entrainment process to layers at the boundary, which meet the self similarity requirements of the logarithmic profile, have been studied. By accepting that turbulence has dominating scales related in scale length to the height above the surface, a layer structure is postulated wherein exchange is rapid enough to keep the layers internally uniform. The diffusion rate is then controlled by entrainment between layers. It has been shown that theoretical relationships derived on the basis of using a single layer of this type give quantitatively correct factors relating the turbulence, wind and shear stress for very rough surface conditions. For less rough surfaces, the surface boundary layer can be divided into several layers interacting by entrainment across each interface. This analysis leads to the following quantitatively correct formula compared to published measurements. 1 $$\begin{gathered} \frac{{\sigma _w }}{{u^* }} = \left( {\frac{2}{{9Aa}}} \right)^{{1 \mathord{\left/ {\vphantom {1 4}} \right. \kern-\nulldelimiterspace} 4}} \left( {1 - 3^{{1 \mathord{\left/ {\vphantom {1 2}} \right. \kern-\nulldelimiterspace} 2}} \frac{a}{k}\frac{{d_n }}{z}\frac{{\sigma _w }}{{u^* }}\frac{z}{L}} \right)^{{1 \mathord{\left/ {\vphantom {1 4}} \right. \kern-\nulldelimiterspace} 4}} \hfill \\ = 1.28(1 - 0.945({{\sigma _w } \mathord{\left/ {\vphantom {{\sigma _w } {u^* }}} \right. \kern-\nulldelimiterspace} {u^* }})({z \mathord{\left/ {\vphantom {z L}} \right. \kern-\nulldelimiterspace} L})^{{1 \mathord{\left/ {\vphantom {1 4}} \right. \kern-\nulldelimiterspace} 4}} \hfill \\ \end{gathered} $$ where \(u^* = \left( {{\tau \mathord{\left/ {\vphantom {\tau \rho }} \right. \kern-0em} \rho }} \right)^{{1 \mathord{\left/ {\vphantom {1 2}} \right. \kern-0em} 2}} \) , σ _w is the standard deviation of the vertical velocity,z is the height andL is the Obukhov scale lenght. The constantsa, A, k andd _n are the entrainment constant, the turbulence decay constant, Von Karman's constant, and the layer depth derived from the theory. Of these,a andA, are universal constants and not empirically determined for the boundary layer. Thus the turbulence needed for the plume model of convection, which resides above these layers and reaches to the inversion, is determined by the shear stress and the heat flux in the surface layers. This model applies to convection in cool air over a warm sea. The whole field is now determined except for the temperature of the air relative to the water, and the wind, which need a further parameter describing sea surface roughness. As a first stop to describing a surface where roughness elements of widely varying sizes are combined this paper shows how the surface roughness parameter,z ₀, can be calculated for an ideal case of a random distribution of vertical cylinders of the same height. To treat a water surface, with various sized waves, such an approach modified to treat the surface by the superposition of various sized roughness elements, is likely to be helpful. Such a theory is particularly desirable when such a surface is changing, as the ocean does when the wind varies. The formula, 2 $$\frac{{0.118}}{{a_s C_D }}< z_0< \frac{{0.463}}{{a_s C_D (u^* )}}$$ is the result derived here. It applies to cylinders of radius,r, and number,m, per unit boundary area, wherea _s =2rm, is the area of the roughness elements, per unit area perpendicular to the wind, per unit distance downwind. The drag coefficient of the cylinders isC _D . The smaller value ofz _o is for large Reynolds numbers where the larger scale turbulence at the surface dominates, and the drag coefficient is about constant. Here the flow between the cylinders is intermittent. When the Reynolds number is small enough then the intermittent nature of the turbulence is reduced and this results in the average velocity at each level determining the drag. In this second case the larger limit forz ₀ is more appropriate.     

Empirical ground-motion relations using moderate earthquakes recorded by Medellín–Aburrá Valley (Colombia) strong-motion networks

We tested attenuation relations obtained for different regions of the world to verify their suitability to predict strong-motion data recorded by Medellín and Aburrá Valley Accelerographic Networks. We used as comparison criteria, the average of the difference between the observed and the predicted data as a function of epicenter distance and its standard deviation. We also used the approach developed by Sherbaum et al. (Bull Seism Soc Am 94:2164–2185, 2004) that provides a method to evaluate the overall goodness-of-fit of ground-motion prediction equations. The predictive models selected use a generic focal depth. We found that this parameter has an important influence in the ground-motion predictions and must be taken into account as an independent variable. We also found important to characterize the local soil amplification to improve the attenuation relations. We found empirical relations for peak horizontal acceleration PGA and velocity PGV based on the Kamiyama and Yanagisawa (Soils Found 26:16–32, 1986) approach. $$\begin{aligned} \log _{10} (PGA)=0.5886M_L -1.0902\log _{10}(R)-0.0035H+C_{st}\pm 0.\text{29} \end{aligned}$$ $$\begin{aligned} \log _{10} (PGV)=0.7255M_L -1.8812\log _{10}(R)-0.0016H+C_{st}\pm 0.36 \end{aligned}$$ where PGA is measured in cm/s $^{2}$ and PGV in cm/s, $M_{L}$ is local magnitude in the range 2.8–6.5, $R$ is epicentral distance up to 290 km, $H$ is focal depth in km and $C_{st}$ is a coefficient that accounts for the site response due to soil conditions of each recording station. The introduction of focal depth and local site conditions as independent variables, minimize the residuals and the dispersion of the predicted data. We conclude that $H$ and $C_{st}$ are sensitive parameters, having a strong influence on the strong-motion predictions. Using the same functional form, we also propose an empirical relation for the root mean square acceleration a $_\mathrm{rms}$ : $$\begin{aligned} \log _{10} \left( {a_{rms} } \right)=0.4797M_L -1.1665\log _{10} (R)-0.00201H+C_{st}\pm 0.40 \end{aligned}$$ where a $_\mathrm{rms}$ is measured in cm/s $^{2}$ , from the S-wave arrival and using a window length equal to the rupture duration. The other variables are the same as those for PGA and PGV. The site correction coefficients $C_{st}$ found for PGA, PGV and a $_\mathrm{rms}$ show a similar trend indicating a good correlation with the soil conditions of the recording sites.     

Strong motion recorded during the Emilia 2012 thrust earthquakes (Northern Italy): a comprehensive analysis

A complex seismic sequence characterised by two thrust earthquakes of magnitudes M \(_\mathrm{L}\) 5.9 and M \(_\mathrm{L}\) 5.8 occurred on May 20 and 29, 2012, respectively, and activated the central portion of the Ferrara Arc structure beneath the Po Plain in northern Italy. The sequence, referred to as Emilia 2012, was recorded by the Italian Strong Motion Network, the Irpinia Network, the Friuli Venezia Giulia Network and 15 temporary stations installed by the Civil Protection Department. In this study, we compile and analyse a large dataset that contains 3,273 waveforms from 37 \(M_\mathrm{L} \ge 4.0\) seismic events. The main aim of this paper is to characterise the ground motion induced by the Emilia 2012 seismic sequence and compare it with other data in the Italian strong motion database and to the recent Ground Motion Prediction Equations (GMPEs) developed for northern Italy, all of Italy and Europe. This is achieved by (1) the computation and analysis of the strong motion parameters of the entire Emilia Strong Motion Dataset (ESMD) and (2) a comprehensive investigation of the May 29 event recordings in terms of time–frequency analysis, the ground motion parameters and the response spectra. This detailed analysis was made possible by the temporary Civil Protection Department stations that were installed soon after the May 20 event at several municipalities in the epicentral area. Most of the recordings are characterised by low-frequency content and long durations, which is a result of the thick sedimentary cover that is typical of the Po Plain. The distributions of the observed horizontal peak ground accelerations and velocities (PGAs and PGVs) with distance are generally consistent with the GMPEs. This is particularly true for the data from M \(_\mathrm{L} \ge \) 5.0 (M \(_\mathrm{W}\ge \) 5.0) events, though the data are scattered at distances beyond approximately 60–70 km and show faster attenuation than the European GMPEs. The horizontal components for the May 29 event at two near-fault stations (Mirandola and San Felice sul Panaro) are overestimated by all of the analysed GMPEs. In contrast, the vertical components, which played an important role in the shaking near the source, are underestimated. The May 29 event produced intense velocity pulses on the horizontal components and the highest peak ground acceleration ever recorded in Italy on the vertical component of the Mirandola near-fault station. The ground motion recordings contained in the ESMD significantly enrich the Italian strong motion database. They contribute new information about (1) the possibility of exceeding the largest recorded PGA in Italy, (2) the development of a spectral design that takes into account the role of the vertical component and the extreme variability of the near-fault ground shaking, and (3) the characterisation of the ground motions in deep sedimentary basins.     

“Pandora box” — Matrix in the calculus of observations

Summary If the condition R(A)=k(n), whereA is the design matrix of the type n × k and k the number of parameters to be determined, is not satisfied, or if the covariance matrixH is singular, it is possible to determine the adjusted value of the unbiased estimable function of the parameters f(), its dispersion D( (x)) and ² as the unbiased estimate of the value of ² by means of an arbitrary g-inversion of the matrix . The matrix , because of its remarkable properties, is called the Pandora Box matrix. The paper gives the proofs of these properties and the manner in which they can be employed in the calculus of observations.     

Stochastic finite-fault simulation of ground motion from the August 11, 2012, <Emphasis Type="Italic">M</Emphasis><Subscript><Emphasis Type="Italic">w</Emphasis></Subscript> 6.4 Ahar earthquake,northwestern Iran

In this study, the 11 August 2012 M _w 6.4 Ahar earthquake is investigated using the ground motion simulation based on the stochastic finite-fault model. The earthquake occurred in northwestern Iran and causing extensive damage in the city of Ahar and surrounding areas. A network consisting of 58 acceleration stations recorded the earthquake within 8–217 km of the epicenter. Strong ground motion records from six significant well-recorded stations close to the epicenter have been simulated. These stations are installed in areas which experienced significant structural damage and humanity loss during the earthquake. The simulation is carried out using the dynamic corner frequency model of rupture propagation by extended fault simulation program (EXSIM). For this purpose, the propagation features of shear-wave including \( {Q}_s \) value, kappa value \( {k}_0 \), and soil amplification coefficients at each site are required. The kappa values are obtained from the slope of smoothed amplitude of Fourier spectra of acceleration at higher frequencies. The determined kappa values for vertical and horizontal components are 0.02 and 0.05 s, respectively. Furthermore, an anelastic attenuation parameter is derived from energy decay of a seismic wave by using continuous wavelet transform (CWT) for each station. The average frequency-dependent relation estimated for the region is \( Q=\left(122\pm 38\right){f}^{\left(1.40\pm 0.16\right)}. \) Moreover, the horizontal to vertical spectral ratio \( H/V \) is applied to estimate the site effects at stations. Spectral analysis of the data indicates that the best match between the observed and simulated spectra occurs for an average stress drop of 70 bars. Finally, the simulated and observed results are compared with pseudo acceleration spectra and peak ground motions. The comparison of time series spectra shows good agreement between the observed and the simulated waveforms at frequencies of engineering interest.     

Design energy input spectra for high seismicity regions based on Turkish registers

This work proposes design energy spectra in terms of an equivalent velocity, intended for regions with design peak acceleration 0.3 g or higher. These spectra were derived through linear and nonlinear dynamic analyses on a number of selected Turkish strong ground motion records. In the long and mid period ranges the analyses are linear, given the relative insensitivity of the spectra to structural parameters other than the fundamental period; conversely, in the short period range, the spectra are more sensitive to the structural parameters and, hence, nonlinear analyses are required. The selected records are classified in eight groups with respect to soil type (stiff or soft soil), the severity of the earthquake in terms of surface magnitude $M _\mathrm{s} (M_\mathrm{s} \le $ 5.5 and $M _\mathrm{s} >$ 5.5) and the relevance of the near-source effects (impulsive or vibratory). For each of these groups, median and characteristic spectra are proposed; such levels would respectively correspond to 50 and 95 % percentiles. These spectra have an initial linear growing branch in the short period range, a horizontal branch in the mid period range and a descending branch in the long period range. Empirical criteria for estimating the hysteretic energy from the input energy are suggested. The proposed design spectra are compared with those obtained from other studies.     

Characteristics of rain electricity in Nigeria II — Experimental and theoretical relations

Analysis of data, covering four rainy seasons, of rain current, point-discharge current and potential gradient reveal novel relations in the form (i) $$Q_{r + } /Q_{r - } = k_1 (T_{r + } /T_{r - } )^{1.1} $$ for rain charge and duration ratios; and (ii) $$Q_{p - } /Q_{p + } = k_2 (T_{p - } /T_{p + } )^{1.1} $$ for point charge and duration ratios, where thek's are constants; and (iii) $$i_r = - \alpha (i_p - c)$$ for rain and point-discharge current densities, where α has the same value for all types of rain andc is a constant controlled by the rainfall intensityR. For rain not associated with point discharge the relation takes the familiar form $$i_r = - AR(E - \bar E)$$ Theoretical values are obtained for \ga andA on the basis of the Wilson ion-capture theory as worked out in detail by Whipple and Chalmers.     

Towards fully data driven ground-motion prediction models for Europe

We have used the Artificial Neural Network method (ANN) for the derivation of physically sound, easy-to-handle, predictive ground-motion models from a subset of the Reference database for Seismic ground-motion prediction in Europe (RESORCE). Only shallow earthquakes (depth smaller than 25 km) and recordings corresponding to stations with measured $V_{s30}$ properties have been selected. Five input parameters were selected: the moment magnitude $M_{W}$ , the Joyner–Boore distance $R_{JB}$ , the focal mechanism, the hypocentral depth, and the site proxy $V_{S30}$ . A feed-forward ANN type is used, with one 5-neuron hidden layer, and an output layer grouping all the considered ground motion parameters, i.e., peak ground acceleration (PGA), peak ground velocity (PGV) and 5 %-damped pseudo-spectral acceleration (PSA) at 62 periods from 0.01 to 4 s. A procedure similar to the random-effects approach was developed to provide between and within event standard deviations. The total standard deviation ( $\sigma $ ) varies between 0.298 and 0.378 (log $_{10}$ unit) depending on the period, with between-event and within-event variabilities in the range 0.149–0.190 and 0.258–0.327, respectively. Those values prove comparable to those of conventional GMPEs. Despite the absence of any a priori assumption on the functional dependence, our results exhibit a number of physically sound features: magnitude scaling of the distance dependency, near-fault saturation distance increasing with magnitude, amplification on soft soils and even indications for nonlinear effects in softer soils.     

A SIMPLIFIED METHOD FOR PREDICTION OF KINEMATIC SOIL–FOUNDATION INTERACTION EFFECTS ON PEAK HORIZONTAL ACCELERATION OF A RIGID FOUNDATION

The kinematic soil–foundation interaction changes the free field ground motion to a different motion at the foundation of a structure. This interaction effect may be expressed by the ratio of the peak horizontal acceleration of a rigid and relatively lightweight foundation to the peak horizontal acceleration at the ground surface in the free field. It is found that the interaction effect can be defined by a simple function of the ratio of the peak horizontal ground velocity and ground acceleration in the free field, the length of the foundation and the shear wave velocity in the soil. Predictive equations for the kinematic soil foundation effect are derived using 350 strong motion records generated by 114 earthquakes world-wide. At the same time, an attenuation relationship is derived for the ratio of the peak horizontal ground velocity and acceleration from the same set of data. Ten case histories are studied; the interaction effects are calculated by using the predictive equations and then compared with measured field values. The results of the comparison illustrate the degree of predictive capability of the method when the foundation mass and the inertial soil–foundation interaction are not considered.     

Attenuation of P,S, and coda waves in Koyna region,India

The attenuation properties of the crust in the Koyna region of the Indian shield have been investigated using 164 seismograms from 37 local earthquakes that occurred in the region. The extended coda normalization method has been used to estimate the quality factors for P waves and S waves , and the single back-scattering model has been used to determine the quality factor for coda waves (Q _c). The earthquakes used in the present study have the focal depth in the range of 1–9 km, and the epicentral distance vary from 11 to 55 km. The values of and Q _c show a dependence on frequency in the Koyna region. The average frequency dependent relationships (Q = Q ₀ f ⁿ) estimated for the region are , and . The ratio is found to be greater than one for the frequency range considered here (1.5–18 Hz). This ratio, along with the frequency dependence of quality factors, indicates that scattering is an important factor contributing to the attenuation of body waves in the region. A comparison of Q _c and in the present study shows that for frequencies below 4 Hz and for the frequencies greater than 4 Hz. This may be due to the multiple scattering effect of the medium. The outcome of this study is expected to be useful for the estimation of source parameters and near-source simulation of earthquake ground motion, which in turn are required in the seismic hazard assessment of a region.