Michael P. Ebert

Numerical Simulation of Two- and Three-Dimensional Circulation Control Problems

The flows about 2-D and 3-D bluff trailing edge circulation control (CC) airfoils are computed using steady Reynolds Averaged Navier-Stokes (RANS) methods. The 2-D foil is the NCCR 1510-7067 elliptical CC airfoil with circular and logarithmic spiral trailing edge geometries. The free stream Reynolds number, based on chord, is 5.45 × 10 5 , with a free stream Mach number of 0.12. For the circular trailing edge the slot height, blowing rate and angle of attack are varied, while for the logarithmic spiral only the blowing rate is varied. The 3-D foil is a semi-span wing with an elliptical cross section. It is run with a chord-based Reynolds number of 2 × 10 6 and two blowing rates. The 2-D flows are computed using the compressible, segregated solver, Fluent. 2-D results show that the full-Reynolds stress turbulence model (FRSM) predicts the correct jet detachment behavior for the circular trailing edge although the integrated lift forces are consistently underpredicted. The coanda jet detachment point for the logarithmic spiral trailing edge is predicted correctly for a lower blowing rate, but as blowing rate increases, the jet does not detach until it has wrapped around to the pressure side. We show additional 2-D results using mesh refinement via grid adaption and isotropic eddy viscosity turbulence models. The 3-D simulations use the incompressible segregated Fluent solver applying the k −ω SST turbulence model. Results show a slight attachment of the the coanda jet on the pressure side, but the results are generally encouraging.

Simulation of Shear Driven Cavity Flows Using Unstructured Hybrid RANS/LES

** �� *** Two separate, unstructured hybrid RANS/LES methods are used to simulate both resonant, and non -resonant, shear driven cavity flows. The first method uses an upwind -biased discretization for the inviscid flux calculations in the governing equations, along with a non -linear k-� turbulence closure for RANS regions, and the Smagorinsky sub -grid scale closure for LES regions. The second method uses an upwind -biased discre tization for the inviscid flux terms which can be modified to reduce the inherently high dissipation in the associated Riemann solver when applied to cell faces not orthogonal to the flow direction. The second method uses a k-� closure for RANS regions. In LES regions, the second method solves a transport equation for sub -grid turbulent kinetic energy, relating this energy to a spectrum for the energy -inertial -dissipation range, which allows calculation of a less dissipative eddy viscosity. Both methods are applied to a three -dimensional, deep cavity problem, at resonant and non -resonant flow conditions. Resulting pressure time series are compared to experimental measurements.

Shape Optimization of a Multi-Element Foil Using an Evolutionary Algorithm

A movable flap with a NACA foil cross section serves as a common control surface for underwater marine vehicles. To augment the functionality of the control surface, a tab assisted control (TAC) surface was experimentally tested to improve its performance especially at large angles of operation. The advantage of the TAC foil could be further enhanced with shape memory alloy (SMA) actuators to control the rear portion of the control surface to form a flexible tab (or FlexTAC) surface. Hybrid unstructured Reynolds averaged Navier–Stokes (RANS) based computational fluid dynamics (CFD) calculations were used to understand the flow physics associated with the multi-element FlexTAC foil with a stabilizer, a flap, and a flexible tab. The prediction results were also compared with the measured data obtained from both the TAC and the FlexTAC experiments. The simulations help explain subtle differences in performance of the multi-element airfoil concepts. The RANS solutions also predict the forces and moments on the surface of the hydrofoil with reasonable accuracy and the RANS procedure is found to be critical for use in a design optimization framework because of the importance of flow separation/turbulent effects in the gap region between the stabilizer and the flap. A systematic optimization study was also carried out with a genetic algorithm (GA) based design optimization procedure. This procedure searches the complex design landscape in an efficient and parallel manner. The fitness evaluations in the optimization procedure were performed with the RANS based CFD simulations. The mesh regeneration was carried out in an automated manner through a scripting process within the grid generator. The optimization calculation is performed simultaneously on both the stabilizer and the nonflexible portion of the flap. Shape changes to the trailing edge of the stabilizer strongly influence the secondary flow patterns that set up in the gap region between the stabilizer and the flap. They were found to have a profound influence on force and moment characteristics of the multi-element airfoil. A new control surface (OptimTAC) was constructed as a result of the design optimization calculation and was shown to have improved lift, drag, and torque characteristics over the original FlexTAC airfoil at high flap angles.

Shape Optimization of a Multi-Element Airfoil Using CFD

Movable flap with a NACA airfoil serves as a common control surface for underwater marine vehicles. To augment the functionality of the control surface, a Tab-Assisted Control (TAC) surface was experimentally tested to address its benefits to various different requirements of the control surface. The advantage of the TAC surface could be further enhanced with Shape Memory Alloy (SMA) actuators to control the rear portion of the control surface to form a flexible tab (or FlexTAC) surface. Although the measured FlexTAC data demonstrated similar augmentation in enhancing airfoil’s functionality, they also show subtle differences in data obtained from the TAC and FlexTAC measurements. High fidelity hybrid unstructured RANS calculation results are used to define the flow fields associated with the multi-element FlexTAC airfoil with a stabilizer, a flap and a flexible tab. The prediction results are compared with the measured data obtained from both the TAC and the FlexTAC experiments. The comparison also leads to the resolution of the difference existed between the two data sets. In addition the RANS solutions are validated for predicting the forces and moments acting on the hydrofoil with adequate accuracy for use with an optimization scheme. For a horizontal control surface to effectively provide upward and downward motions, it is necessary to maintain a symmetric airfoil shape. In order to achieve maximum benefit out of a horizontal TAC/FlexTAC surface, a shape modification of the stabilizer (fixed portion of the hydrofoil) and the flap is desirable to account for the requirements at the most severe scenario. This paper focuses on the conditions when the movable flap surface becomes jammed. Since the present investigation deals with a FlexTAC configuration with a flexible tab, the shape modification focuses only on the stabilizer and the non-flexible portions of the flap. The shape optimization calculations coupling with the RANS predictions use an evolutionary algorithm, which consists of a genetic algorithm based design optimization procedure. This procedure searches the complex design landscape in an efficient and parallel manner. Furthermore, it can easily handle complexities in constraints and objectives and is disinclined to get trapped in local extreme regions. The utilization of the hybrid unstructured methodology provides flexibility in incorporating large changes in shape. The mesh regeneration is carried out in an automated manner through a scripting process within the grid generator. The optimization calculation is performed simultaneously on both the stabilizer and the flap. Shape changes to the trailing edge of the stabilizer strongly influence the secondary flow patterns that set up in the gap region between the stabilizer and the flap. These are found to have a profound influence on force and moment characteristics. Experimental and numerical evaluations of a shape obtained from a study of optimization results on the Pareto front for the current optimization landscape, further confirmed the optimization objectives.

The Increasing Use of Visualization in Ship Hydrodynamics

Flow field visualization is an important part of the study of fluid dynamics and ship hydrodynamics. The field of computational fluid dynamics has provided an unprecedented ability to explore the hydrodynamics of marine vehicles through visualization. Many examples of this exist in the literature for steady flow field situations. However, unsteady visualization provides both challenges and opportunities to extract meaningful physical insight and information from computational simulations. This paper discusses some of these issues along with approaches being pursued to obtain adequate flow field information using remote high performance computing resources as well as concurrent visualization using local resources. A number of examples of flow field computations being pursued are discussed including: cavity flow, ship roll motions, trailing edge vortex shedding, ballast water exchange and crashback

Performance of unstructured hybrid Reynolds averaged Navier‐Stokes/large‐eddy simulation methods in simulating shear‐driven cavity flows

Two separate, unstructured hybrid RANS/LES methods are used to simulate both resonant and nonresonant shear‐driven cavity flows. The first method uses an upwind‐biased discretization for the inviscid flux calculations in the governing equations, along with a nonlinear k−e turbulence closure for RANS regions, and the Smagorinsky subgrid‐scale closure for LES regions. The second method uses an upwind‐biased discretization for the inviscid flux terms which is modified to reduce the inherently high dissipation in the associated Riemann solver when applied to cell faces not orthogonal to the flow direction. The second method uses a k−e closure for RANS regions. In LES regions, the second method solves a transport equation for subgrid turbulent kinetic energy, relating this energy to a spectrum for the energy‐inertial‐dissipation range, which allows calculation of a less dissipative eddy viscosity. Both methods are applied to a three‐dimensional, deep cavity problem, at resonant and nonresonant flow conditions....