Vinod K. Lakshminarayan
Embedded boundary methods provide the advantage of easily handling arbitrariy large deformation of the body. However, for turbulent fluid-structure interaction problems with large deformations, embedded mesh sizes can become prohibitively large for accurate resolution of the boundary layer.
My research involves development of an ALE embedded boundary method, in which the boundary layers during large displacements, rotations, and/or deformations of the structure are resolved by formulating the governing flow equations in a rigid instance of the Arbitrary Lagrangian Eulerian (ALE) framework, and by using corotational method to update the rigid body motion of the CFD mesh. This non deformable mesh motion enables the original non body-fitted CFD mesh to follow the boundary layers, and therefore minimize the need for complex adaptive mesh refinement. To achieve nonlinear stability, temporal discretization is performed using an extension of the second-order three point backward difference implicit scheme that satisfies its discrete geometric conservation law.
Wind energy is a promising alternative to traditional fossil fuels in terms of carbon footprint and sustainability. However, a wider adaptation of wind energy is dependent on reducing the cost per unit of energy extracted, which currently is higher than that of fossil fuels if environmental impact is not accounted for. In the recent past, a considerable number of studies have been done to improve the productivity of the wind turbines/farms and a significant portion of these research efforts rely upon simulations and modeling. A principal difficulty in the accurate simulation of wind turbine aerodynamics comes from the prediction of transition from laminar to turbulent flow.
My current research involves assessing the applicability of Reynolds Averaged Navier Stokes (RANS) based CFD methodology using a transition model in predicting the wind turbine flow field. Further, keeping the limitations of these methodologies in mind, I am also performing high-fidelity calculations of diffuser augmented wind turbine (DAWT). By placing the conventional horizontal axis wind turbines inside a shroud, the efficiency of the turbines can be improved above the well-known Betz limit.
For any CFD simulations to be meaningful, it is critical to ensure that numerical error does not overwhelm either the accuracy of the calculation. Further, wind turbine simulations are subject to a range of uncertainties, arising either from natural variabilities present in the system such as the physical variation in wind speed and free stream turbulence, or from an improper knowledge of the system and the boundary conditions. Therefore, the estimation and control of numerical errors in propagating the effect of these uncertainties becomes very important.
My research attempts to carefully estimate error in spatial, temporal and stochastic space using adjoint based methods for wind turbine applications. Such estimates can help budget the computational resources towards improving accuracy in regions of high errors and also provide a basis for adaptive sampling in stochastic space.
Over the past decade, micro air vehicles (MAVs) have received an increasing amount of attention in military and civilian markets. Common MAV missions involve surveillance into complex and possibly dangerous situations without much risk. However, most of the current day MAVs lack the capabilities demanded by such missions. One of the main problems associated with MAVs is their relatively poor aerodynamic characteristics. MAVs operate at a low Reynolds number, where viscous effects in the flow are dominant over the inertial ones, boundary layers are thick and undergo several complex phenomena, thereby causing strong adverse effect on the lifting surface characteristics. Apart from improvements in blade/airfoil design for MAVs, various conceptual designs of rotary MAVs have evolved over the period of time to meet the target set by DARPA.
My research involves developing computational methodologies that can be used to simulate the aerodynamics of different MAV configurations including unconventional rotary wing concepts like ducted and cycloidal rotors as well as studying avian-based flapping wing MAVs. With my research, I would like to gain fundamental understanding of the flow physics at the micro-scale, which can aid in improving the existing MAV designs.
The brownout problem consists of the creation of a dense dust cloud that envelops the rotorcraft during in-ground effect operation. Apart from the obvious problem of rendering the pilot visually disoriented, these clouds can also be responsible for blade erosion and mechanical wear. Current day workarounds to the brownout problem include the use of sensors and avionic displays for improving the situational awareness or the employment of piloting strategies to avoid the brownout cloud. Although these solutions can contribute in limiting the number of brownout related mishaps, these strategies only provide a temporary solution and a more permanent solution is desired for this problem. Since the interaction of the rotor wake with the dust particles on the ground is the driving force of the brownout phenomenon, it is believed that a good understanding of the underlying flow physics can provide insight to develop effective means of preventing and/or mitigating the adverse effects of rotorcraft brownout.
In my research, I use Reynolds Averaged Navier Stokes (RANS) based CFD solver to understand the flow physics of rotors operating close to the ground. The simulations involved are very expensive and requires massive parallelization as well as intelligent clustering of mesh points. Overset meshes are used for clustering points in the region of interest.
A common difficulty in simulating complex geometries is that a single, contiguous grid will not be sufficient to represent the flow features well enough. For hovering rotors, it is very difficult to obtain a single structured mesh which can represent the blade surfaces and also preserve important off-surface flow features, like tip vortices. In such cases, the common approaches used are unstructured meshes, multiblock structured meshes or overlapping chimera structured meshes. Unstructured meshes are generally considered to be easily adaptable to complex configurations, but they require more memory and are less efficient compared to structured meshes. Using block structured grids, the grid interfaces have to be matched and this makes the grid generation process very complicated. Overset structured grids have the advantage in that different grids can be generated independent of each other and can be placed in the region of interest without any distortion.
The use of overset meshes requires exchanging information between different meshes based on some connectivity information. The algorithms required to determine the connectivity information are still heavily under development. I am working on an algorithm called Implicit Hole Cutting (IHC). My focus is on improving robustness and efficiency of this methodology.