A FEniCS-based programming framework for modeling turbulent flow by the Reynolds-averaged Navier-Stokes equations

Finding an appropriate turbulence model for a given flow case usually calls for extensive experimentation with both models and numerical solution methods. This work presents the design and implementation of a flexible, programmable software framework for assisting with numerical experiments in computational turbulence. The framework targets Reynolds-averaged Navier-Stokes models, discretized by finite element methods. The novel implementation makes use of Python and the FEniCS package, the combination of which leads to compact and reusable code, where model- and solver-specific code resemble closely the mathematical formulation of equations and algorithms. The presented ideas and programming techniques are also applicable to other fields that involve systems of nonlinear partial differential equations. We demonstrate the framework in two applications and investigate the impact of various linearizations on the convergence properties of nonlinear solvers for a Reynolds-averaged Navier-Stokes model. © 2011 Elsevier Ltd.

Investigations on wooden floating materials: the loss of buoyancy under continuous immersion in water and the rate of its redemption by drying

A wooden fishing float under immersion in water for long periods is liable to absorb water, the quantity of water absorbed possibly being dependent upon the physical factors like the specific gravity and the inherent property of the material, the time of soaking and the pressure acting on it. Consequently a wooden float is likely to become heavy and loss its original buoyancy. However, when the float is removed from water and dried, the lost buoyancy is regained on complete drying. The present paper is an attempt to elucidate these two important characteristics of some of the chief wooden floating materials used on the West Coast of India.