Stochastic differential equations (3rd ed.): an introduction with applications
Stochastic differential equations (3rd ed.): an introduction with applications
A level set approach to Eulerian-Lagrangian coupling
Journal of Computational Physics
A comprehensive three-dimensional model of the cochlea
Journal of Computational Physics
Finite Differences And Partial Differential Equations
Finite Differences And Partial Differential Equations
Introduction to Computational Micromechanics (Lecture Notes in Applied and Computational Mechanics)
Introduction to Computational Micromechanics (Lecture Notes in Applied and Computational Mechanics)
Fluid-Structure Interaction by the Spectral Element Method
Journal of Scientific Computing
A stochastic immersed boundary method for fluid-structure dynamics at microscopic length scales
Journal of Computational Physics
MATH'07 Proceedings of the 12th WSEAS International Conference on Applied Mathematics
Dynamics of a Closed Rod with Twist and Bend in Fluid
SIAM Journal on Scientific Computing
On computational issues of immersed finite element methods
Journal of Computational Physics
Efficient solutions to robust, semi-implicit discretizations of the immersed boundary method
Journal of Computational Physics
Journal of Computational Physics
Hi-index | 31.45 |
We present approaches for the study of fluid-structure interactions subject to thermal fluctuations. A mixed mechanical description is utilized combining Eulerian and Lagrangian reference frames. We establish general conditions for operators coupling these descriptions. Stochastic driving fields for the formalism are derived using principles from statistical mechanics. The stochastic differential equations of the formalism are found to exhibit significant stiffness in some physical regimes. To cope with this issue, we derive reduced stochastic differential equations for several physical regimes. We also present stochastic numerical methods for each regime to approximate the fluid-structure dynamics and to generate efficiently the required stochastic driving fields. To validate the methodology in each regime, we perform analysis of the invariant probability distribution of the stochastic dynamics of the fluid-structure formalism. We compare this analysis with results from statistical mechanics. To further demonstrate the applicability of the methodology, we perform computational studies for spherical particles having translational and rotational degrees of freedom. We compare these studies with results from fluid mechanics. The presented approach provides for fluid-structure systems a set of rather general computational methods for treating consistently structure mechanics, hydrodynamic coupling, and thermal fluctuations.