Shape Optimization for Drag Minimization Using the Navier-Stokes Equation

Fluid drag is a force that opposes relative motion between fluid layers or between solids and surrounding fluids. For a stationary solid in a moving fluid, it is the amount of force necessary to keep the object stationary in the moving fluid. In addition to fluid and flow conditions, pressure drag on a solid object is dependent on the size and shape of the object. The aim of this project is to compute the shape of a stationary 2D object of size 3.5 m2 that minimizes drag for different Reynolds numbers. We solve the problem in the context of shape optimization, making use of shape sensitivity analysis. The state variables are fluid pressure and velocity modeled by the Navier-Stokes equation with cost function given by the fluid drag which depends on the state variables. The geometric constraint is removed by constructing a Lagrangian function. Subsequent application of shape sensitivity analysis on the Lagrangian generates the shape derivative and gradient. Our optimization routine uses a variational form of the sequential quadratic programming (SQP) method with the Hessian replaced by a variational form for the shape gradient. The numerical implementation is done in Python while the open source finite element package, FEniCS, is used to solve all the partial differential equations. Remeshing of the computational domain to improve mesh quality is carried out with the open source 2D mesh generator, Triangle. Final shapes for low Reynolds numbers resemble an american football while shapes for moderate to high Reynolds numbers are more streamlined in the tail end of the object than at the front

Pore-scale lattice Boltzmann simulations of inertial flows in realistic porous media: a first principle analysis of the Forchheimer relationship

With recent advances in the capabilities of high performance computing (HPC) platforms and the relatively simple representation of complex geometries of porous media, lattice Boltzmann method (LBM) has gained popularity as a means of solving fluid flow and transport problems. In this work, LBM was used to obtain flow parameters of porous media, study the behavior of these parameters at varying flow conditions and quantify the effect of roughness on the parameters by relating the volume averaged flow simulation results to Darcy and Forchheimer equations respectively. To validate the method, flow was simulated on regular and random sphere arrays in cubic domains, for which a number of analytical solutions are available. Permeability and non-Darcy coefficients obtained from the simulation compared well with Kozeny and Ergun estimates while deviation from the observed constant permeability and tortuosity values occurred aroundRe≈1-10. By defining roughness as hemispherical protrusions on the smooth spheres in the regular array, it was observed from flow streamlines obtained at different roughness heights that the average length of the flow paths increased with increasing roughness height. As such, the medium tortuosity and non-Darcy coefficient increased while the permeability decreased as height of the roughness increased. Applying the method to a 3D computed tomography image of Castlegate sandstone, the calculated macroscopic permeability and beta factor components were in good agreement with reported experimental values. In addition, LBM beta factors were compared with a number of empirical models for non-Darcy coefficient estimation and were found to be of the same order of magnitude as most of the correlations, although estimates of the models showed wide variation in values. Resolution of the original sample was increased by infilling with more voxels and simulation in the new domain showed better flow field resolution and higher simulated flow regimes compared to those of the original sample, without significant change in the flow parameters obtained. Using the Reynolds number based on the Forchheimer coefficient, the range of transition from Darcy to non-Darcy regime was within the values reported by Ruth and Ma (1993) and Zeng and Grigg (2006).