Spectral-element analysis in seismology

Chaljub, Emmanuel; Komatitsch, Dimitri; Vilotte, J. P.; Capdeville, Yann; Valette, Bernard; Festa, Gaetano

doi:10.1016/s0065-2687(06)48007-9

Cited by 176 publications

(141 citation statements)

References 97 publications

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“…In addition, the highdegree Lagrange polynomials assure exponential spatial accuracy. Thorough reviews of the SEM in seismology can be found, e.g., in Komatitsch et al (2005), Chaljub et al (2007), Tromp et al (2008), andFichtner (2010).…”

Section: Methodsmentioning

confidence: 99%

“…In particular, areas characterized by low wavespeed sedimentary basins may show a very different ground response compared to hardrock sites, with strong amplifications, multiple reverberations, and prolonged shaking (e.g., Rovelli et al, 2001;Olsen et al, 2006;Chaljub et al, 2007;Lee et al, 2008). Moreover, these effects can be intensified and complicated by topographic ridges, which can cause amplifications, reflections, and multipathing (e.g., Lee et al, 2008;).…”

Section: Simulations With a 3d Model: Effects Of Geological Structuresmentioning

confidence: 99%

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Spectral-Element Simulations of Seismic Waves Generated by the 2009 L'Aquila Earthquake

Magnoni¹,

Casarotti²,

Michelini³

et al. 2013

Bulletin of the Seismological Society of America

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We adopt a spectral-element method (SEM) to perform numerical simulations of the complex wavefield generated by the 6 April 2009 M w 6.3 L'Aquila earthquake in central Italy. The mainshock is represented by a finite-fault solution obtained by inverting strong-motion and Global Positioning System data, testing both 1D and 3D wavespeed models for central Italy. Surface topography, attenuation, and the Moho discontinuity are also accommodated. Including these complexities is essential to accurately simulate seismic-wave propagation. Three-component synthetic waveforms are compared to corresponding velocimeter and strong-motion recordings. The results show a favorable match between data and synthetics up to ∼0:5 Hz in a 200 km × 200 km × 60 km model volume, capturing features mainly related to topography or low-wavespeed basins. We construct synthetic peak ground velocity maps that, for the 3D model, are in good agreement with observations, thus providing valuable information for seismic-hazard assessment. Exploiting the SEM in combination with an adjoint method, we calculate finite-frequency kernels for specific seismic arrivals. These kernels capture the volumetric sensitivity associated with the selected waveform and highlight prominent effects of topography on seismic-wave propagation in central Italy.

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Section: Methodsmentioning

confidence: 99%

Section: Simulations With a 3d Model: Effects Of Geological Structuresmentioning

confidence: 99%

Spectral-Element Simulations of Seismic Waves Generated by the 2009 L'Aquila Earthquake

Magnoni¹,

Casarotti²,

Michelini³

et al. 2013

Bulletin of the Seismological Society of America

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show abstract

“…Another class of FEMs that relies on the Gauss-Lobatto-Legendre quadrature points has removed these limitations, and allows for spectral convergence with high approximation orders. This high-order FEM, called the spectral element method (SEM) (Komatitsch & Vilotte, 1998;Seriani & Priolo, 1994) has been applied to large-scale geological models up to the global scale (Chaljub et al, 2007;Komatitsch et al, 2008). The major limitation of SEM is the exclusive use of hexahedral meshes, which makes the design of an optimal mesh cumbersome in contrast to the flexibility offered by tetrahedral meshes.…”

Section: Finite-elements Discontinuous Galerkin Methods: a Weak Formumentioning

confidence: 99%

Seismic Waves - Research and Analysis

Kanao¹

2012

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“…Several authors compared the various methods (Fornberg, 1987;Moczo et al, 2011;Chaljub et al, 2007;Wang et al, 2010;Pasquetti and Rapetti, 2004;De Basabe and Sen, 2007, e.g.). Zhebel et al (2012a) considered the continuous mass-lumped and the discontinuous Galerkin finite elements in terms of accuracy, stability and computational cost.…”

Section: Introductionmentioning

confidence: 99%

Performance and scalability of finite-difference and finite-element wave-propagation modeling on Intel's Xeon Phi

Zhebel

Minisini

Kononov

et al. 2013

SEG Technical Program Expanded Abstracts 2013

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SUMMARYWith the rapid developments in parallel compute architectures, algorithms for seismic modeling and imaging need to be reconsidered in terms of parallelization. The aim of this paper is to compare scalability of seismic modeling algorithms: finite differences, continuous mass-lumped finite elements and discontinuous Galerkin finite elements. The performance for these methods is considered for a given accuracy. The experiments were performed on an Intel Sandy Bridge dual 8-core machine and on Intel's 61-core Xeon Phi, which is based on the Many Integrated Core architecture. The codes ran without any modifications. On the Sandy Bridge, the scalability is similar for all methods. On the Xeon Phi, the finite elements outperform finite differences on larger number of cores in terms of scalability.

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Spectral-element analysis in seismology

Cited by 176 publications

References 97 publications

Spectral-Element Simulations of Seismic Waves Generated by the 2009 L'Aquila Earthquake

Spectral-Element Simulations of Seismic Waves Generated by the 2009 L'Aquila Earthquake

Seismic Waves - Research and Analysis

Performance and scalability of finite-difference and finite-element wave-propagation modeling on Intel's Xeon Phi

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