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Viscoplastic Responses With Stochastic Q-Damping Or Soil

  • G. Dasgupta
Conference paper
Part of the Solid Mechanics and its Applications book series (SMIA, volume 47)

Abstract

Viscoelastic responses in mechanical systems are significantly influenced by material damping losses. In time dependent steady harmonic vibration problems, energy loss per cycle generally varies with the frequency of excitation. In a large number of geophysical computations, however, frequency independent Q-models — a higher value of Q indicating less damping — are routinely chosen for convenient representation of soil damping characteristics in the visco-plastic regime dominated by nonlinear effects.

The distribution of the viscous loss index — Q-factor — can be realistically depicted by a spatially correlated random field with bounded variation as per in situ experiments. Consequently, the numerical estimation of dynamic viscoplastic response statistics of a soil-structure system demands extensive and time consuming computation invoking methods of nonlinear stochastic mechanics. In this paper on frequency independent viscoplastic Q-factors, a systematic nonlinear formulation is presented in order to reduce computational costs without compromising the accuracy demanded by hazard mitigation problems arising out of seismic, wind and wave activities.

Symbolic computation is carried out to implement the analytical steps of continuum mechanics in order to construct quality nonlinear finite elements for the interior and boundary elements for the outer semi-infinite region. The numerical computation for production runs is anticipated to be carried out by C++ object-oriented program modules. It is noteworthy to observe that the computer algebra code segments provided an efficient framework for C++ development.

Keywords

Boundary Element Boundary Element Method Monte Carlo Sample Constitutive Property Pade Approximant 
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

© Kluwer Academic publishers 1996

Authors and Affiliations

  • G. Dasgupta
    • 1
  1. 1.Civil Engineering & Engineering MechanicsColumbia UniversityNew YorkUSA

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