Determination of the Stacking Velocity Field via Optimization Methods

Oliveira, Danian Steinkirch de; Porsani, Milton J.; Cunha, Paulo Eduardo Miranda

doi:10.22564/rbgf.v33i3.750

Cited by 1 publication

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“…where a n ≈ü(t n ) and v n ≈u(t n ). The Newmark scheme naturally provides approximations for not only displacement, but also velocity and acceleration, which are useful to the inversion of three-component data [66]. The leapfrog method corresponds to β = 0 and γ = 1/2.…”

Section: Newmark Methodsmentioning

confidence: 99%

Numerical modeling of mechanical wave propagation

Seriani

Oliveira

2020

Riv. Nuovo Cim.

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The numerical modeling of mechanical waves is currently a fundamental tool for the study and investigation of their propagation in media with heterogeneous physical properties and/or complex geometry, as, in these cases, analytical methods are usually not applicable. These techniques are used in geophysics (geophysical interpretation, subsoil imaging, development of new methods of exploration), seismology (study of earthquakes, regional and global seismology, accurate calculation of synthetic seismograms), in the development of new methods for ultrasonic diagnostics in materials science (non-destructive methods) and medicine (acoustic tomography). In this paper we present a review of numerical methods that have been developed and are currently used. In particular we review the key concepts and pioneering ideas behind finite-difference methods, pseudospectral methods, finite-volume methods, Galerkin continuous and discontinuous finite-element methods (classical or based on spectral interpolation), and still others such as physics-compatible, and multiscale methods. We focus on their formulations in time domain along with the main temporal discretization schemes. We present the theory and implementation for some of these methods. Moreover, their computational characteristics are evaluated in order to aid the choice of the method for each practical situation.

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Section: Newmark Methodsmentioning

confidence: 99%