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Solar System Research

, Volume 36, Issue 5, pp 374–402 | Cite as

Tectonic Structure, Classification, and Evolution of Arachnoids on Venus: Preliminary Results

  • A. S. Krassilnikov
Article

Abstract

An analysis has been done of the topography and geologic structure of arachnoids—specific radial/concentric volcannic-tectonic structures on the surface of Venus. A representative sample (53 arachnoids) from 265 structures of this type, which are listed in the catalog of volcanic structures of the surface of Venus (Crumpler and Aubele, 2000), has been studied. The overwhelming majority of arachnoids are shown to be depressions that are commonly outlined by concentric extensional structures. Following Head et al. (1992) and Aittola and Kostama (2001), the assumption is confirmed and substantiated that arachnoids are formed by gravitational relaxation of small magmatic diapirs. Several types of arachnoids are identified on the basis of an analysis of structural patterns characteristic of such structures. It is also shown that the formation of different types of arachnoids depends on the depth of the magmatic diapir under the surface, on the thickness and reologic properties of the structures superposed on the evolving magmatic diapir, and on the character of regional stress fields that arise in the process of formation of such structures. The conclusion is drawn that most of the arachnoids were formed due to the gravitational relaxation of magmatic diapirs within the brittle part of the lithosphere, and some of them appeared as a result of the gravitational relaxation of radially fractured centers—novae. It is also shown that arachnoids are long-lived and multistep structures. At least some of them began to evolve before the formation of regional plains with wrinkle ridges, and their development ended after this event.

Keywords

Depression Brittle Representative Sample Lithosphere Stress Field 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© MAIK “Nauka/Interperiodica” 2002

Authors and Affiliations

  • A. S. Krassilnikov
    • 1
  1. 1.Vernadsky Institute of Geochemistry and Analytical Chemistry

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