T o l l F r e e 8 0 0 - 4 P T W I S E w w w . p o i n t w i s e . c o m

Volume 14 Issue 1 Spring 2010

Ship Appendage Drag Prediction Using Hybrid Grids 1

Simulation of Gust Noises in a Low Pressure Axial Fan 1

Partner Highlight: Go Virtual 4 Product News: T-Rex in Pointwise & Gridgen 5

Aerodynamic Shape Optimization of a Vertical Axis Wind Turbine 6

INSIDE THIS ISSUE

Ship Appendage Drag PredictionUsing Hybrid Grids

Simulation of Gust Noises in a Low Pressure Axial Fan

(Continues on page 2)

(Continues on page 3)

Prof. Chisachi Kato, University of Tokyo (Japan)Prof. Thomas Carolus, University of Siegen (Germany)Dr. Hauke Reese, University of Siegen (Germany)

Axial fans often operate in less than optimum conditions caused by imperfect intake geometry, time-varying ingested vortices, and turbulence that results in unsteady forces on the blade and undesirable tonal and broadband noise generation. Predicting this noise requires precise knowledge of the unsteady fl owfi eld. In this study, a high-resolution large eddy simulation (LES) is used to predict the unsteady forces on a single stage fan subject to turbulence generated by an upstream array of struts.

The overset numerical grid for this study was created with Gridgen. The fl ow domain was divided into four overlapping sections: inlet, struts, fan, and outlet. The overall grid system is shown in Figure 1 (on page 3). Each fan blade is modeled using a fi ve-block topology with an O-grid around the blade and four H-topology blocks around that, as shown in Figure 2. The entire grid contains approximately 5 million cells.

The fl ow solution was computed with Frontfl ow Blue, a fi nite element-based, LES code developed by C. Kato. It solves a spatially-fi ltered continuity equation and the Navier-Stokes

Existing empirical methods for predicting ship appendage drag are known to suffer diffi culty related to accounting for over-lapped areas and interference among pieces, using the actual velocity as opposed to just ship speed, scale effects, and the best drag coeffi cient selection. Commercial computational fl uid dynamics (CFD) software has advanced to the point to which it can be used to predict appendage drag accurately. In this study, Pointwise, Inc.’s Gridgen and Metacomp Technologies’ CFD++ with their hybrid grid capability are used to predict appendage drag on several Joint High Speed Sealift (JHSS) confi gurations.

Flow around four hull-appendage confi gurations was computed with variations in the number of appendages included in the analysis: fully appended, fully appended plus propeller hub and fairwater, full appended minus rudder, and bare hull. In addi-tion, the fl ow around each confi guration was computed with two different turbulence models: a realizable k-ε model, and Goldberg’s k-ε-Rt model that solves an additional equation for undamped eddy viscosity independently from k and ε.

Gridgen was used to create triangular surface grids on the hull, appendages and all other fl ow boundaries as shown in Figure 1. In order to accurately simulate the fl ow, grid points were clustered in areas where high velocity gradients are expected, which are around the bow dome and stern appendages. The surface grid was extruded outward from the wall boundaries to form the prism layers needed to capture details of the boundary layer fl ow near the walls. In the fi nal grid, 29 prism layers are used in the near wall regions. After the prism layers were formed, the rest of the domain was fi lled with tetrahedral cells. Since the focus of this study is appendage drag, free surface calculations were not included. Instead, the double hull method, in which a horizontal symmetry plane replaces the water surface, was used.

Figure 1: Grid distribution on the hull and appendages.

Dr. Minyee JiangNaval Surface Warfare Center, Carderock Division

Also, the ship is symmetric between the port and starboard sides, so only the port side of the ship was included, with a symmetry boundary condition between the two sides.

In order to maintain grid consistency between the various confi gurations, the fully appended confi guration was gridded

2Pointwise® FocalPoint Spring 2010

Ship Appendage Drag Prediction Using Hybrid Grids

(Continued from page 1)

Figure 3: Comparison of pressure contours on the appendages with propeller extension hub fairwater (above) and without propeller extension hub fairwater (below).

fi rst and the remaining grids were constructed by removing the appropriate appendages. For example, when the rudders were removed the grid was modifi ed only locally without altering the global domain. Grid sizes ranged from 9.3 million cells for the most complex confi guration (fully-appended plus hub and fairwater) to 2.3 million cells for the bare hull.

The confi guration with propeller hub and fairwater was added to study the fairwater’s effect on drag. The propeller hub was added to the last shaft barrel and a fairwater was added to the barrel to form smoother contours at the shaft end as seen in Figure 2. This small geometry extension signifi cantly reduces fl ow separation at the end of the shaft barrel, which should be carefully counted in the measurement for resistance prediction.

Flowfi elds for each confi guration were computed with CFD++ using both turbulence models and compared to experimental data. Figure 3 shows pressure contours on the hull and append-

ages from one of the computed solutions. On the top is the confi guration that includes all appendages and the fairwater. On the bottom is the fully appended confi guration without the fairwater. Higher pressure on the aft end of the fairwater contributes to lower propeller shaft drag for this confi guration, but the higher pressure also increases the drag on the rudder. However, the total resistance is lowered with the fairwater since the increased drag on the rudder is offset by drag decreases on other components. Interaction between the elements is also the likely cause of drag differences from the inboard and outboard fairwaters. Lower pressure on the outboard fairwater relative to the inboard may explain why drag is lower on the inboard. The k-ε Rt turbulence model predicts higher resistance than the realizable k-ε model, which provides predictions closer to the measured data. However, the free surface was not included

in the analysis, so it could be argued the low drag predictions from the realizable k-ε model are more reasonable. In general, CFD++ provides very reasonable predictions compared to the

Figure 2: Surface grid on the appendages with propeller extension hub fairwater.

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of one fan revolution required approximately 40 CPU-hours. Details of the unsteady fl ow are shown in Figures 3 and 4. The combination of Gridgen and Frontfl ow Blue enabled obtaining good agreement with experimental measurements of blade force fl uctuations and radiated sound power.

Simulation of Gust Noises in a Low Pressure Axial Fan

(Continued from page 1)

equations in Cartesian coordinates. The velocity fl uctuations are decomposed, with the grid scale velocities resolved by the LES and the sub-grid scale velocities modeled with a dynamic Smagorinsky model. The scheme is second order accurate in both space and time.

Computations were performed on a Hitachi SR 8000 computer with eight nodes and eight CPUs each node. The simulation

Figure 3: Iso-surfaces of the divergence of the pressure gradient.

Figure 4: Iso-surfaces of vorticity in fl ow direction. The color on the surfaces represents the surface pressure distribution.

Figure 2: Numerical grid in the fan blade region.

Figure 1: Numerical grid of the complete fl ow domain; every third grid point and mesh line are plotted for clarity.

4Pointwise® FocalPoint Spring 2010

P a r t n e r H i g h l i g h t

Training DatesPointwise Standard Course 13-15 July 2010 Fort Worth, TX

Gridgen Standard Course 14-16 September 2010 Fort Worth, TX

Pointwise Standard Course 12-14 October 2010 West Coast

Pointwise Standard Course 16-18 November 2010 Fort Worth, TX

For more information, contact our training department at training@pointwise.com.

P a r t n e r H i g h l i g h t

Go Virtual is the newest addition to the Pointwise family of distributors, supporting Pointwise products in Denmark, Norway and Sweden. The company was founded in 2002 with the mission of assisting companies to adopt more virtual product development. Go Virtual focuses on three major business areas: CFD Software, High Performance Computing (HPC) systems and Visualization systems.

Within CFD, Go Virtual represents a handful of truly inde-pendent software providers that are leaders in their respec-tive fi elds:

Meshing: Pointwise/Gridgen from Pointwise• Geometry preparation for scanned and faceted • data: 3-matic from Materialise CFD and Aero Acoustics solvers CFD++ and CAA++ • from Metacomp TechnologiesThermal solver: RadTherm from ThermoAnalytics• Post-processor: FieldView from Intelligent Light•

Go Virtual has four offi ces, with headquarters in Gothenburg, Sweden. The three sales offi ces are in Stockholm, Sweden, and Ratingen and Holzgerlingen, Germany. The customer

base is spread over 13 European countries and covers academia, government and many industry segments such as aerospace, automotive and wind energy.

Go Virtual strongly believes in maintaining an open CFD process in which products are sold individually or together to suit the customer’s way of working. All products have open interfaces so they can function together with any other CFD software customers might use in their processes.

For more information about Go Virtual, go to http://www.govirtual.se/ or contact Per Österdahl, Sales Manager, CFD Applications, at per.osterdahl@govirtual.se.

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It increases productivity by more than 20 percent, accord-•

ing to the white paper “The Economic Payback of 3D Mice,” available at www.pointwise.com/3Dmouse.

5Pointwise® FocalPoint Spring 2010

213 South Jennings Avenue Fort Worth, Texas 76104-1107 Toll-free 800-4PTWISETel (817) 377-2807 Fax (817) 377-2799 focalpoint@pointwise.com www.pointwise.com

FocalPoint is a publication of Pointwise, Inc. It is for Gridgen and Pointwise users and people interested in learning more about numerical grid gen-eration. It includes information about the software, latest releases, future development plans, and tips on how to get the most out of Gridgen and Pointwise while saving time in grid generation. Pointwise and Gridgen are registered trademarks and GridgenGlyph, PointwiseGlyph and T-Rex are trademarks of Pointwise, Inc. All other trademarks are property of their respective owner. Copyright © 2010 Pointwise, Inc. All rights reserved.

Let the Battle Begin — Pointwise Takes on T-RexWith the Pointwise UGM 2010 and the release of Pointwise Version 16.03 now successfully in our rear-view mirror, it’s time to look ahead to new meshing capabilities coming this year. The most promising news is that very few Gridgen features remain to be ported to Pointwise, some small and some large. We’re tackling the large ones fi rst.

Migration of T-Rex (anisotropic tetrahedral extrusion), the highly automated hybrid boundary layer meshing technique, has already begun. We plan for the initial T-Rex implemen-tation to be similar to what’s in Gridgen, with the usual workload reductions achieved through use of Pointwise’s modern GUI. Addition of NCRs (native CAD readers) to Pointwise has been under way for several months with very promising success rates for CAD fi le import including ACIS, CATIA V4, CATIA V5, Pro/E, NX, Parasolid, SolidWorks and STEP. The NCRs in Pointwise will differ from those in Gridgen because we’re using a new suite of libraries at the core of the NCRs.

Overset and T-Rex EnhancementsIn GridgenThe research results from Pointwise’s recently completed Phase 1 SBIR contract* on overset grid assembly have been migrated into Gridgen’s production source code and will be available in a production release this summer. As history has shown, sometimes the smallest features have the most impact so we anticipate everyone will enjoy the expanded PLOT3D support including IBLANK, single block, 2D, and big/little endian. Those of you actively generating overset grids will be able interactively to setup input fi les for PEGASUS5 and SUGGAR and launch those overset assembly codes directly from Gridgen. You’ll then be able to import the resulting overset data and view fringe, hole, and orphan points and visualize IBLANK data in the Examine command. Adjusting the grid will be easier with all the overset data available to guide you.

Gridgen Version 15.16 also includes a major improvement to T-Rex and its ability to reduce your cell count by combin-ing near-wall anisotropic tetrahedra into prisms. In the past, use of the multiple normals fl ag that added points near convex corners (like wing trailing edges) was incompatible

with prism recombination. That restriction has been lifted yielding a 28 percent cell count reduction for the horizontal axis wind turbine shown below.

*Sponsored by Arnold Engineering Development Center, Air Force Materiel Command, and the U.S. Air Force.

T-Rex will be migrated to Pointwise this year, including several workfl ow improvements. At the same time, im-provements to T-Rex in Gridgen will cut the cell count for this wind turbine by 28 percent.

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Volume 14 Issue 1 Spring 2010

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Travis J. Carrigan and Prof. Brian H. Dennis,

The University of Texas at Arlington

With the push for a greener planet, vertical axis wind turbines (VAWT) have become increasingly popular. VAWTs have made their way into urban environments for residential applications because they are not restricted to large, open spaces and because of their ability to operate in fl uctuating and turbulent wind condi-tions. Further research and development is required for this new market in wind energy technology, specifi cally in fi nding ways to increase VAWT effi ciency. Current research at The University of Texas at Arlington is addressing the need for higher effi ciency through aerodynamic shape optimization.

The purpose of this study is to introduce and demonstrate a fully automated process for optimizing the airfoil cross-section. The objective is to maximize the torque while enforcing several typical wind turbine design constraints (tip speed ratio, solidity, and blade profi le). These constraints represent the foundation of wind turbine design, and any combination of these can result in maximum torque.

The design system required to maximize torque incorporates automated hybrid mesh generation tools together with viscous, unsteady computational fl uid dynamics (CFD) simulation soft-ware. Pointwise was used to generate a series of structured and hybrid grids for the two-dimensional, three bladed wind turbine.

Aerodynamic Shape Optimization of a Vertical Axis Wind Turbine

The time-averaged torque for the different mesh topologies was calculated using the FLUENT solver. Grid independent solutions were found using a hybrid mesh topology with approximately 55,000 cells as opposed to the structured mesh containing over 100,000 cells. The fl exibility and automation in Pointwise, as well as the decision to use a hybrid grid, allowed for the mesh genera-tion of many airfoil geometries to be seamlessly integrated into the fi nal automated optimization process. In the end, a parallel differential evolution algorithm was used to obtain an optimum design that maximized the effi ciency of the wind turbine.

The next step of this study involves demonstrating the robust-ness of the optimization process for a wide range of design constraints.

Hybrid mesh and velocity contours for a two-dimensional section cut of a three bladed VAWT.