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Tesseroids: forward modeling gravitational fields in spherical coordinates

Uieda, L.
•
Barbosa, V. C. F.
•
BRAITENBERG, CARLA
2016
  • journal article

Periodico
GEOPHYSICS
Abstract
We have developed the open-source software Tesseroids, a set of command-line programs to perform forward modeling of gravitational fields in spherical coordinates. The software is implemented in the C programming language and uses tesseroids (spherical prisms) for the discretization of the subsurface mass distribution. The gravitational fields of tesseroids are calculated numerically using the Gauss-Legendre quadrature (GLQ). We have improved upon an adaptive discretization algorithm to guarantee the accuracy of the GLQ integration. Our implementation of adaptive discretization uses a “stack-based” algorithm instead of recursion to achieve more control over execution errors and corner cases. The algorithm is controlled by a scalar value called the distance-size ratio (D) that determines the accuracy of the integration as well as the computation time. We have determined optimal values of D for the gravitational potential, gravitational acceleration, and gravity gradient tensor by comparing the computed tesseroids effects with those of a homogenous spherical shell. The values required for a maximum relative error of 0.1% of the shell effects are D = 1 for the gravitational potential, D = 1.5 for the gravitational acceleration, and D = 8 for the gravity gradients. Contrary to previous assumptions, our results show that the potential and its first and second derivatives require different values of D to achieve the same accuracy. These values were incorporated as defaults in the software.
DOI
10.1190/GEO2015-0204.1
WOS
WOS:000392752200035
Archivio
http://hdl.handle.net/11368/2877741
info:eu-repo/semantics/altIdentifier/scopus/2-s2.0-84979610094
http://library.seg.org/doi/abs/10.1190/geo2015-0204.1
Diritti
open access
license:digital rights management non definito
license:digital rights management non definito
FVG url
https://arts.units.it/request-item?handle=11368/2877741
Soggetti
  • algorithm, gravity, m...

Scopus© citazioni
98
Data di acquisizione
Jun 14, 2022
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Web of Science© citazioni
130
Data di acquisizione
Mar 22, 2024
Visualizzazioni
3
Data di acquisizione
Apr 19, 2024
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