Engineering topics
Publications and source records attributed to Holst, Terry L..
The effect of turbulence models in the off-body grids on the accuracy of solutions for rotor flows in hover has been investigated. Results from the Reynolds-Averaged Navier-Stokes and Laminar Off-Body models are compared. Advection of turbulent eddy viscosity has been studied to find the mechanism leading to inaccurate solutions. A coaxial rotor result is also included.
This paper presents an automated approach for effective extraction, visualization, and quantification of vortex core radii from the Navier-Stokes simulations of a UH-60A rotor in forward flight. We adopt a scaled Q-criterion to determine vortex regions and then perform vortex core profiling in these regions to calculate vortex core radii. This method provides an efficient way of visualizing and quantifying the blade tip vortices. Moreover, the vortices radii are displayed graphically in a plane.
Helicopter aeromechanics encompasses a highly vortical flow field. The vortices generated at each blade tip contain unsteady, complex, three-dimensional structures, which interact with each other, other blades, the fuselage and various components of the helicopter. It is crucial to understand vortex kinematics and their subsequent dynamic evolution. Much research has been devoted to the understanding of helicopter vortex dynamics, including a number of experimental studies.1-6 In May 2010 Particle Image Velocimetry (PIV) measurements of a full-scale UH-60A rotor were acquired in the National Full-Scale Aerodynamics Complex (NFAC) 40- by 80-Foot Wind Tunnel.1 These measurements were taken at a plane just downstream of the advancing blade in the vicinity of the blade tip—the so-called PIV plane. The resulting PIV data were then processed using an ensemble-average approach to create graphical representations of the vortical wake velocity and vorticity fields, which, in turn, have enhanced the understanding of rotorcraft vortical wake flow field physics and have provided a more detailed validation of vortical wake computer simulations.7 A common approach used to analyze flow field features is to compute and plot color contour maps of various scalar quantities such as pressure, velocity magnitude and vorticity magnitude. For example, the color map of the vorticity magnitude is typically used to determine vortical flow structure. With this approach the vortex core may appear larger or smaller, depending on the contour levels that are selected. Thus, the resulting visualization is sensitive to user-specified contour levels. For vortex core radius measurements, it is more accurate to calculate the vortex core radius using the cross-flow velocity profile across the vortex core. The task of extracting the cross-flow velocity profile can be time consuming with existing tools since the user needs to manually select the core center then specify sampling points along the profile axis. The task becomes even more challenging when the associated grid system uses AMR (Adaptive Mesh Refinement) where the profile axis could span multiple grid blocks. There are a number of existing techniques for profiling of vortex core attributes;8-9 however, these techniques are not fully automatic in that the user still needs to select the vortex core center to compute the cross-flow velocity profile. The present study introduces a new color map scheme that is based on the vortex core radius, which is fully automatic and does not require user intervention. Analysis and visualization of blade tip vortices on the PIV plane using the proposed new color map scheme are described in Section II. The new approach is evaluated using two case studies, which are described in Section III. The paper ends with a summary in Section IV.
No abstract available
A genetic algorithm approach suitable for solving multi-objective problems is described and evaluated using a series of aerodynamic shape optimization problems. Several new features including two variations of a binning selection algorithm and a gene-space transformation procedure are included. The genetic algorithm is suitable for finding Pareto optimal solutions in search spaces that are defined by any number of genes and that contain any number of local extrema. A new masking array capability is included allowing any gene or gene subset to be eliminated as decision variables from the design space. This allows determination of the effect of a single gene or gene subset on the Pareto optimal solution. Results indicate that the genetic algorithm optimization approach is flexible in application and reliable. The binning selection algorithms generally provide Pareto front quality enhancements and moderate convergence efficiency improvements for most of the problems solved.
A genetic algorithm approach suitable for solving multi-objective optimization problems is described and evaluated using a series of aerodynamic shape optimization problems. Several new features including two variations of a binning selection algorithm and a gene-space transformation procedure are included. The genetic algorithm is suitable for finding pareto optimal solutions in search spaces that are defined by any number of genes and that contain any number of local extrema. A new masking array capability is included allowing any gene or gene subset to be eliminated as decision variables from the design space. This allows determination of the effect of a single gene or gene subset on the pareto optimal solution. Results indicate that the genetic algorithm optimization approach is flexible in application and reliable. The binning selection algorithms generally provide pareto front quality enhancements and moderate convergence efficiency improvements for most of the problems solved.
A genetic algorithm approach suitable for solving multi-objective optimization problems is described and evaluated using a series of simple model problems. Several new features including a binning selection algorithm and a gene-space transformation procedure are included. The genetic algorithm is suitable for finding pareto optimal solutions in search spaces that are defined by any number of genes and that contain any number of local extrema. Results indicate that the genetic algorithm optimization approach is flexible in application and extremely reliable, providing optimal results for all optimization problems attempted. The binning algorithm generally provides pareto front quality enhancements and moderate convergence efficiency improvements for most of the model problems. The gene-space transformation procedure provides a large convergence efficiency enhancement for problems with non-convoluted pareto fronts and a degradation in efficiency for problems with convoluted pareto fronts. The most difficult problems --multi-mode search spaces with a large number of genes and convoluted pareto fronts-- require a large number of function evaluations for GA convergence, but always converge.
A genetic-algorithm-based optimization approach is described and evaluated using a simple hill-climbing model problem. The model problem utilized herein allows for the broad specification of a large number of search spaces including spaces with an arbitrary number of genes or decision variables and an arbitrary number hills or modes. In the present study, only single objective problems are considered. Results indicate that the genetic algorithm optimization approach is flexible in application and extremely reliable, providing optimal results for all problems attempted. The most difficult problems - those with large hyper-volumes and multi-mode search spaces containing a large number of genes - require a large number of function evaluations for GA convergence, but they always converge.
A method for aerodynamic shape optimization based on an evolutionary algorithm approach is presented and demonstrated. Results are presented for a number of model problems to access the effect of algorithm parameters on convergence efficiency and reliability. A transonic viscous airfoil optimization problem, both single and two-objective variations, is used as the basis for a preliminary comparison with an adjoint-gradient optimizer. The evolutionary algorithm is coupled with a transonic full potential flow solver and is used to optimize the inviscid flow about transonic wings including multi-objective and multi-discipline solutions that lead to the generation of pareto fronts. The results indicate that the evolutionary algorithm approach is easy to implement, flexible in application and extremely reliable.
A method for aerodynamic shape optimization based on a genetic algorithm approach is demonstrated. The algorithm is coupled with a transonic full potential flow solver and is used to optimize the flow about transonic wings including multi-objective solutions that lead to the generation of pareto fronts. The results indicate that the genetic algorithm is easy to implement, flexible in application and extremely reliable.
The wing-body aerodynamics data base consists of a series of CFD (Computational Fluid Dynamics) simulations about a generic wing body configuration consisting of a ogive-circular-cylinder fuselage and a simple symmetric wing mid-mounted on the fuselage. Solutions have been obtained for Nonlinear Potential (P), Euler (E) and Navier-Stokes (N) solvers over a range of subsonic and transonic Mach numbers and angles of attack. In addition, each solution has been computed on a series of grids, coarse, medium and fine to permit an assessment of grid refinement errors.
A new method for aerodynamic shape optimization using a genetic algorithm with real number encoding is presented. The algorithm is used to optimize three different problems, a simple hill climbing problem, a quasi-one-dimensional nozzle problem using an Euler equation solver and a three-dimensional transonic wing problem using a nonlinear potential solver. Results indicate that the genetic algorithm is easy to implement and extremely reliable, being relatively insensitive to design space noise.
The aerothermodynamic database consists of Navier-Stokes solutions in PLOT3D format for the spherical-like nose cap of the X-38. These solutions are chosen to follow a reentry trajectory. The Mach number varies from 7.89 to 1.72 while the angle of attack varies from 38.73 degrees to 17.08 degrees. The Reynolds number varies from 4.139E6 to 2.766E7. Coarse, Medium and Fine grid solutions are supplied for each point in the data base. In addition to the flow solutions, a table of force and moment coefficients as well as the maximum heat transfer coefficient is also stored in the database.
This presentation describes the state of transonic flow simulation using nonlinear potential methods for external aerodynamic applications. The presentation begins with a review of the various potential equation forms (with emphasis on the full potential equation) and includes a discussion of pertinent mathematical characteristics and all derivation assumptions. Impact of the derivation assumptions on simulation accuracy, especially with respect to shock wave capture, is discussed. Key characteristics of all numerical algorithm types used for solving nonlinear potential equations, including steady, unsteady, space marching, and design methods, are described. Both spatial discretization and iteration scheme characteristics are examined. Numerical results for various aerodynamic applications are included throughout the presentation to highlight key discussion points. The presentation ends with concluding remarks and recommendations for future work. Overall. nonlinear potential solvers are efficient, highly developed and routinely used in the aerodynamic design environment for cruise conditions. Published by Elsevier Science Ltd. All rights reserved.
The objectives of this study were to develop chimera-based full potential methodology which is compatible with overflow (Euler/Navier-Stokes) chimera flow solver and to develop a fast donor cell search algorithm that is compatible with the chimera full potential approach. Results of this work included presenting a new donor cell search algorithm suitable for use with a chimera-based full potential solver. This algorithm was found to be extremely fast and simple producing donor cells as fast as 60,000 per second.
An approximate factorization scheme based on the AF2 algorithm is presented for solving the three-dimensional full potential equation for the transonic flow about isolated wings. Two spatial discretization variations are presented, one using a hybrid first-order/second-order-accurate scheme and the second using a fully second-order-accurate scheme. The present algorithm utilizes a C-H grid topology to map the flow field about the wing. One version of the AF2 iteration scheme is used on the upper wing surface and another slightly modified version is used on the lower surface. These two algorithm variations are then connected at the wing leading edge using a local iteration technique. The resulting scheme has improved linear stability characteristics and improved time-like damping characteristics relative to previous implementations of the AF2 algorithm. The presentation is highlighted with a grid refinement study and a number of numerical results.
A numerical scheme utilizing a chimera zonal grid approach for solving the three dimensional full potential equation is described. Special emphasis is placed on describing the spatial differencing algorithm around the chimera interface. Results from two spatial discretization variations are presented; one using a hybrid first-order/second-order-accurate scheme and the second using a fully second-order-accurate scheme. The presentation is highlighted with a number of transonic wing flow field computations.
A numerical scheme utilizing a chimera zonal grid approach for solving the full potential equation in two spatial dimensions is described. Within each grid zone a fully-implicit approximate factorization scheme is used to advance the solution one interaction. This is followed by the explicit advance of all common zonal grid boundaries using a bilinear interpolation of the velocity potential. The presentation is highlighted with numerical results simulating the flow about a two-dimensional, nonlifting, circular cylinder. For this problem, the flow domain is divided into two parts: an inner portion covered by a polar grid and an outer portion covered by a Cartesian grid. Both incompressible and compressible (transonic) flow solutions are included. Comparisons made with an analytic solution as well as single grid results indicate that the chimera zonal grid approach is a viable technique for solving the full potential equation.