1

© Dell

ANSYS® Application Benchmarking on Dell PowerEdge VRTX

Authors: Wayne Glanfield, Garima Kochhar

2

© Dell

Table of Contents

1. IntroductIon . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .3

2. dell Poweredge VrtX . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .3

3. AnSYS SoftwAre & BenchmArkS . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .4

3.1. mechAnIcAl & BenchmArkS . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .4

3.2. fluent & BenchmArkS . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .4

3.3. cfX & BenchmArkS . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .5

3.4. AnSYS rSm. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .5

4. cluSter SoftwAre . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .5

4.1. mIcroSoft wIndowS for hPc . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .5

5. AnSYS BenchmArkIng. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .5

5.1. BenchmArk PlAtformS And confIgurAtIon . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .6

5.2. PerformAnce reSultS And AnAlYSIS . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .6

5.2.1. AnSYS mechAnIcAl . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .6

5.2.2. AnSYS fluent . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .10

5.2.3. AnSYS cfX . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .14

6. concluSIon . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .16

7. for more InformAtIon . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 17

A. APPendIX: AnSYS mechAnIcAl BenchmArk cASeS . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .18

B. APPendIX: AnSYS fluent BenchmArk cASeS . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .21

c. APPendIX: AnSYS cfX BenchmArk cASeS . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .23

3

© Dell

1. IntroductionA large number of departmental workgroups run engineering simulation software on desk-side workstations. Popular software for such simulations include the mechanical suite of applications and computational fluid dynamics codes fluent and cfX from AnSYS which benefit from parallel processing. Although workstations are powerful machines that provide some parallel processing capability and large memory footprint they are ultimately limited in the number of processor cores, memory and Io performance providing an upper boundry to the capacity and capability of the simulation platform available to the engineers. Additionally, a workstation running engineering simulations will consume all available cPu and memory resources and therefore cannot be used for any other day-to-day tasks until the simulation has completed.

engineers often have a requirement to turnaround simulations in faster times to meet design cycles and reviews and to perform a greater number of design optimisations than is possible on a single workstation. Several of these high-end workstations can be networked together as a small high Performance cluster (hPc) to increase the available processing capacity and capability, however It departments may not have the internal expertise, experience or resource to build and support such a cluster of networked workstations. Although this “build-your-own” hPc cluster approach is acceptable in some environments where this expertise is available, others may prefer a pre-configured, pre-tested and supported hPc cluster that has the additional benefit of freeing up the workstation resource for design, development, collaboration, visualisation, etc.

the white paper describes a pre-packaged and fully supported hPc cluster solution based on the Poweredge VrtX platform. Performance results on AnSYS mechanical, fluent and cfX benchmarks are provided to demonstrate the feasibility and scalability of the VrtX simulation and manufacturing solution.

the following sections of this paper describe the platform used for the hPc cluster, the software available, performance results and analysis on the hPc platform. the appendices contain further details on the application benchmark test cases.

2. Dell PowerEdge VRTXthe dell Poweredge VrtX platform is designed to be an easy-to manage solutions platform, optimised specifically for office environments. It allows engineers to extend their current windows workstation based environment to a more powerful hPc cluster. the VrtX platform provides servers, storage and networking in a single chassis. this platform configured as an hPc manufacturing and simulation cluster can be shared amongst different engineers and engineering teams. demanding engineering jobs can easily be run on the VrtX while the user can still run smaller jobs on her/his workstations and visualise results.

the VrtX supports up to four dual-socket servers or two quad-socket servers. this study compares the performance and scalability of a VrtX hPc cluster across two generations of servers – the Poweredge m620 and the Poweredge m630. the m630 is the latest generation blade server that supports the Intel Xeon e5-2600 v3 processor family (code named haswell), the m620 is the previous generation blade server that supports the Xeon e5-2600 processor family (code named SandyBridge). each of these dual-socket servers has 24 dImm slots and can support up to 768 gB total memory capacity. the servers also have a choice of two 2.5” or four 1.8” local disk drives including options of SAtA, SAS or PcIe SSds. for networking, each server has an on-board network daughter card supporting two 10gbe or four 1gbe ports.

the 5u VrtX chassis includes shared storage. options include 25 2.5” drives or 12 3.5” drives providing a maximum capacity of 48tB. these shared disk drives include choices of SAS, nl-SAS or SSd. the chassis has an option for a 1 gbe or a 10gbe switch module that can provide connectivity to all servers as well as external access outside the chassis. Additionally the VrtX has eight PcI-e slots, a chassis management controller, shared fans and redundant power supplies for a complete solution.

4

© Dell

the Intel Xeon processor support and large memory capacity make this platform well suited for cfd type applications like AnSYS fluent. the large memory and multiple storage options benefit structural mechanics applications employing implicit solvers which require large amounts of memory or local storage for certain phases of the solution that generate lots of temporary data.

the VrtX cluster can be configured as a microsoft windows system or a linux system. In either case, multiple easy-to-use and intuitive tools that enable users to submit jobs to the cluster from their workstation are available from AnSYS. these tools include AnSYS remote Solve manager (rSm) that is pre-packaged with Ansys products, and the AnSYS fluent/cfX/mechanical launcher guI itself.

for more information, visit dell Poweredge VrtX and dell Poweredge VrtX technical guide.

3. ANSYS Software & Benchmarks3.1. Mechanical & Benchmarks

AnSYS mechanical software is a comprehensive feA analysis (finite element) tool for structural analysis, including linear, nonlinear and dynamic studies. the engineering simulation product provides a complete set of elements behavior, material models and equation solvers for a wide range of mechanical design problems. In addition, AnSYS mechanical offers thermal analysis and coupled-physics capabilities involving acoustic, piezoelectric, thermal–structural and thermo-electric analysis.

the AnSYS mechanical benchmark cases range in size from 650,000 degrees of freedom to over 14 million degrees of freedom. the suite contains both Pcg and Sparse equation solver benchmark cases as well as covering a wide variety of analysis types including static, transient, modal, cyclic symmetry modal and harmonic. Additionally, both thermal and structural physics are covered.

3.2. Fluent & Benchmarks

AnSYS fluent software contains the broad physical modeling capabilities needed to model flow, turbulence, heat transfer, and reactions for industrial applications ranging from air flow over an aircraft wing to combustion in a furnace, from bubble columns to oil platforms, from blood flow to semiconductor manufacturing, and from clean room design to wastewater treatment plants. Special models that give the software the ability to model in-cylinder combustion, aero acoustics, turbo machinery, and multiphase systems have served to broaden its reach.

the AnSYS fluent benchmark cases range in size from a few hundred thousand cells to more than 100 million cells. the suite contains both pressure-based (segregated and coupled) and density-based implicit solver cases using a variety of cell types and a range of physics.

3.3. CFX & Benchmarks

AnSYS cfX software is a high-performance, general purpose fluid dynamics program that has been applied to solve wide-ranging fluid flow problems for over 20 years. At the heart of AnSYS cfX is its advanced solver technology, the key to achieving reliable and accurate solutions quickly and robustly. the modern, highly parallelised solver is the foundation for an abundant choice of physical models to capture virtually any type of phenomena related to fluid flow. the solver and its many physical models are wrapped in a modern, intuitive, and flexible guI and user environment, with extensive capabilities for customisation and automation using session files, scripting and a powerful expression language.

the AnSYS cfX benchmark cases cover mesh sizes ranging from approx. half a million to over 100 million nodes, and include a variety of element types and physics models.

to learn more, visit AnSYS, AnSYS Benchmarks overview.

5

© Dell

4. Cluster Software4.1. Microsoft Windows for HPC

windows hPc is a high performance computing (hPc) solution built on windows Server technology and microsoft hPc Pack. the windows hPc solution combines a comprehensive set of deployment, administration, job scheduling, and monitoring tools for your windows hPc cluster environment, and a flexible platform for developing and running hPc applications.

the latest version of the hPc Pack is microsoft hPc Pack 2012 r2 update 1. hPc Pack allows you to create, manage, and run hPc.to learn more, visit microsoft hPc.

5. ANSYS BenchmarkingApplication performance benchmarking of real world or commercial applications is an increasingly important aspect of the procurement process of new hPc systems. It is also important for optimising performance of simulations on existing hardware and bleeding edge technology.

Although synthetic benchmarks including hPl and StreAm etc. are useful in understanding how various discreet aspects of hPc systems perform, new processor technology including advanced vector extensions (AVX, AVX2) and accelerators do not necessarily translate to the same level of performance for end user applications. development of these applications may lag behind hardware technology and it may be a number of years before these technologies are utilized, if at all. certain applications cannot make efficient use of these technologies.

Although synthetic benchmarks including hPl and StreAm are useful in understanding how various discreet aspects of hPc systems perform, new processor technology including advanced vector extensions (AVX, AVX2) and accelerators do not necessarily translate to the same level of performance for end user applications. Application updates and enhancements tend to lag behind hardware technology and it may be a number of years before these technologies are effectively utilised, if at all. thus application benchmarking is very useful to fully understand how real-world applications perform on different technologies and to set realistic performance expectations.

the results presented in this study compare two generations of Poweredge VrtX servers and show functionality and scalability of the VrtX hPc platform.

5.1. Benchmark Platforms & Configuration

this section provides details on the two test bed platforms used for this study. one VrtX cluster was built with four Poweredge m620 servers and the second test bed with Poweredge m630 servers. each test environment was configured with the best available components for that generation of product.

the VrtX m620 cluster was configured as with windows, and the VrtX m630 cluster configured with linux. Both environments are supported options in this architecture and subsequent sections will show performance results and scalability for both cases, demonstrating the versatility of this solution.

the VrtX m630 cluster has a total of 80 cores with 20 cores each on four servers. Since the Ansys hPc license pack is in units of 32, the results in this study uses 16 cores per m630 server allowing a direct comparison with the 16 core m620. the performance results therefore compare cluster architecture over generations keeping software licensing costs identical across the configuration. for environments where core licensing is not a concern, the VrtX m630 solution offers 25% more cores than the previous generation m620 solution in the same form factor and chassis space.

6

© Dell

Dell PowerEdge VRTX/M620 Dell PowerEdge YRTX/M630

Servers 4 x Poweredge m620 4 x Poweredge m630

Processor

Intel® Xeon® e5-2680

2.7 ghz, 8 cores, 130w

3.1 ghz max all core turbo

Intel® Xeon® e5-2660 v3 2.6 ghz, 10 cores, 105 w 2.9 ghz max all core turbo

memory320 gB

20x16 gB ddr3 1333mt/s256gB 16x16gB ddr4 2133mt/s

network card Intel® ethernet 10g 2P X540-t Broadcom Bcm57810

network switch dell force10 3S4820t 10g 10gbe Iom in VrtX chassis

operating Systemmicrosoft windows Server 2012

Standardred hat enterprise linux 6.5

to learn more, visit dell Poweredge VrtX, dell Poweredge m620, dell Poweredge m630.

5.2. Performance Results and Analysisthis section presents benchmark results with AnSYS mechanical, fluent and cfX on the two test platforms – Poweredge VrtX with m620 servers, and Poweredge VrtX with m630 servers.

5.2.1. ANSYS Mechanicalresults on the ten Ansys mechanical benchmarks are presented in this section. All results are relative to the first test case of m620 using 16 cores.

7

© Dell

© Dell

8

the graphs in this section show many interesting results for AnSYS mechanical. As mentioned previously, the VrtX m630 cluster provides a total of 80 cores, but this study uses 16 cores per system for a total of only 64 cores. this method was used to keep the cores in test similar to the VrtX m620 cluster, removing core-based license costs as a factor and to provide a more direct comparison across the two generations.

9

© Dell

1) the generation-over-generation technological advances translate into application performance as seen from the m620 vs. m630 performance for all test cases. the two test beds were configured with the best available components for that generation – hence the differences in cPu speed, number of available processor cores, memory technology (ddr3 1333 mt/s vs. ddr 2133 mt/s). Another difference is the windows environment on the m620 and the linux environment on the m630. the generational differences are much more significant in these results than any windows-to-linux delta.

2) test cases like cg-1 and sp-3 show scalability across 16, 32, 48 and 64 cores over the 10 gbe cluster interconnect.

3) test cases like ln-1, ln-2 and sp-4 show great improvements in performance on the newer generation m630 server, with m630 performing 1.5 to 2.5 times faster than the m620 (150 to 250%). these test cases do not scale well past 32 cores and are best run on up to 32 cores, with the option of running two simultaneous such simulations on the 64-core cluster. the scalability pattern on 16, 32 to 48, 64 cores is similar for the m620 and the m630.

4) test cases like cg-2 show an interesting pattern where the older generation m620 outperforms the new m630 for the 48 and 64 core cases. this is because the dramatic 1.5x to 2.0x improvement in compute performance with the m630 transfers the bottle-neck to the network earlier than with the m620 and the test does not scale very well past 32 cores. the option here is to run two simultaneous such simulations on the whole cluster.

5) the results show application performance scalability on 16 to 64 cores with both windows and linux clustering.

5.2.2. ANSYS Fluentresults on the seven AnSYS fluent benchmarks are presented in this section. All results are relative to the first test case with m620 using 16 cores. 48 core results were not available on the VrtX m620 system and are not plotted in the graphs below.

© Dell

10

11

© Dell

the following observations can be made from the performance results on AnSYS fluent. As mentioned previously, the VrtX m630 cluster provides a total of 80 cores, but this study uses 16 cores per system for a total of only 64 cores. this method was used to keep the cores in test similar to the VrtX m620 cluster, removing core-based license costs as a factor and to provide a more direct comparison across the two generations.

1) AnSYS fluent shows great performance improvements with the VrtX m630 compared to the previous generation m620. like the AnSYS mechanical case, the technological advances on the new m630 server do translate into application performance. the two test beds were configured with the best available components for that generation –the differences in cPu speed, number of available processor cores, memory technology (ddr3 1333 mt/s vs. ddr 2133 mt/s) all contribute to the improved performance. Another difference is the windows environment on the m620 and the linux environment on the m630 but the cluster architecture differences are much more significant in these results than any windows-to-linux delta.

2) eddy_417k, sedan_4m, truck_poly_14m and truck_111m test cases scale very well on this cluster architecture with the VrtX m630 demonstrating better scalability than the m620 solution. fluent is known to scale well to hundreds of cores and it is expected to see better scaling with fluent than AnSYS mechanical.

3) on cases like turbo_500k, aircraft_2m and truck_14m, the test scales to 48 cores on the m630, but there is a drop in performance for 64cores. this is because the faster compute capability on the m630 exposes the network as the bottleneck for larger cluster sizes. fluent is known to scale to tens of servers and hundreds of cores on hPc clusters with an InfiniBand network interconnect that has higher bandwidth and lower latency than ethernet. the m620 has lower compute capability than the m630 due to the slower memory and previous generation processor architecture, and here the slower compute balances the interconnect making the network less of a factor in performance.

4) the results show application performance scalability on 16 to 64 cores with both windows and linux clustering.

12

© Dell

5.2.3. ANSYS CFXresults on the five AnSYS cfX benchmarks are presented in this section. All results are relative to the first test case with m620 using 16 cores. VrtX m630 results were not available at the time of writing.

13

© Dell

these results show good scalability with AnSYS cfX test cases on the VrtX 620 solution. It is expected that the VrtX m630 system will show better performance and scalability as seen with the AnSYS mechanical and fluent cases.

6. Conclusionthe dell Poweredge VrtX is an ideal cAe platform for small workgroup, departmental or roBo (remote office Branch office) deployments. the memory capacity (up to 768gB) of each the VrtX servers and local storage (up to 48tB) is particularly suited to structural mechanics applications employing implicit solvers which require large amounts of memory or local storage for certain phases of the solution. the computational power across four dual socket enterprise class servers and the 10 gigabit ethernet interconnect have been shown to support computational fluid dynamics applications. the VrtX platform provides significant capability when running large memory both in-core and out-of-core solutions. the large shared storage capacity also reduces the need for high performance shared storage when running these jobs. the performance benchmarking results presented in this study provide additional validation for such use cases, across multiple applications and multiple test case sizes.

the architecture of the VrtX makes it an ideal entry level or small cluster platform when moving from serial or local parallel simulations to distributed parallel simulations. the platform would also be ideal as a development platform where such a dedicated resource is required.

despite its small form factor, the VrtX packs lots of computer power and storage capacity. one clear advantage the VrtX has however, is the ability to choose between a windows or linux environment. while that may seem trivial to many large users of AnSYS solutions that potentially scale their environment to thousands of cores on linux, this study demonstrates that a windows-based VrtX cluster scales as well as linux-based. this can be a factor in organizations that run some or most of their cAe simulations on windows workstations and do not want to learn a new skill set to manage and run their simulations of a small cluster. this frees up valuable workstation capacity that can be leveraged to further optimise the cAe workflow.

7. For more Informationlearn more about AnSYS: www.ansys.comlearn more about dell: www.dell.com and www.dell.co.uk/hpc

©2015 Dell Inc. All rights reserved. Dell, the DELL logo, the DELL badge and PowerEdge are trademarks of Dell Inc. Other trademarks and trade names may be used in this document to refer to either the entities claiming the marks and names or their products. Dell disclaims proprietary interest in the marks and names of others.

14

© Dell

A. Appendix: ANSYS Mechanical Benchmark Cases

Test Case: cg-1 - Power Supply Module

Description: Steady state thermal analysis of a power supply module Jcg solver, symmetric matrix, 5300k dofS, static, linear, thermal analysis. medium sized job for iterative solvers, good test of memory bandwidth.

Test Case: cg-2 - Tractor Rear Axle

Description: Static structural analysis of a farm tractor rear axle assemble Pcg solver, symmetric matrix, 12300k dofs, static, linear, structural analysis. large sized job for iterative solvers, good test of memory bandwidth.

Test case: cg-3 - Engine Block

Description: Static structural analysis of an engine block without the internal components Pcg solver, symmetric matrix, 14200k dofs, static, linear, structural analysis. large sized job for iterative solvers, good test of processor flop speed and memory bandwidth.

Test case: ln-1 – Gear Box

Description: description: Static structural analysis of an engine block without the internal components Pcg solver, symmetric matrix, 14200k dofs, static, linear, structural analysis. large sized job for iterative solvers, good test of processor flop speed and memory bandwidth.

15

© Dell

Test case: ln-2 – Radial Impeller

Description: cyclic symmetric modal analysis of a single blade of an impeller Subspace eigensolver, symmetric matrix, 2000k dofs, modal, cyclic symmetry, linear, structural analysis requesting 50 modes. medium sized job for direct solvers, should run incore on machines with 64 gB or more of memory, good test of processor flop speed and memory bandwidth.

Test case: sp-1 – Peltier Cooling Block

Description: Static nonlinear thermal-electric coupled field analysis of a Pelletier cooling block Sparse solver, non-symmetric matrix, 650k dofs, static, nonlinear, thermal-electric coupled field analysis. medium sized job for direct solvers, should run incore on machines with 32 gB or more of memory, good test of processor flop speed if running incore and I/o if running out-of-core

Test case: sp-2 – Semi-Submersible

Description: Static nonlinear thermal-electric coupled field analysis of a Pelletier cooling block Sparse solver, non-symmetric matrix, 650k dofs, static, nonlinear, thermal-electric coupled field analysis. medium sized job for direct solvers, should run incore on machines with 32 gB or more of memory, good test of processor flop speed if running incore and I/o if running out-of-core

Test case: sp-3 – Speaker

Description: Static nonlinear thermal-electric coupled field analysis of a Pelletier cooling block Sparse solver, non-symmetric matrix, 650k dofs, static, nonlinear, thermal-electric coupled field analysis. medium sized job for direct solvers, should run incore on machines with 32 gB or more of memory, good test of processor flop speed if running incore and I/o if running out-of-core

16

© Dell

B. Appendix: ANSYS Fluent Benchmark Cases

Test case: eddy_417k

Description: A reacting flow case with the eddy dissipation model. k-epsilon turbulence. 417k cells, reacting flow, segregated implicit solver

Test case: turbo_500k

Description: Single stage turbomachinery flow case using the Spallart-Allmaras turbulence model. 500k cells, turbulent flow, coupled implicit solver

Test case: ln-2 – Radial Impeller

Description: Static nonlinear structural analysis of a turbine blade as found in aircraft engines Sparse solver, symmetric matrix, 3200k dofs, static, nonlinear, structural analysis with 1 iteration. large sized job for direct solvers), should run incore on machines with 96 gB or more of memory, good test of processor flop speed if running incore and I/o if running out-of-core.

Test case: sp-5– BGA

Description: transient nonlinear structural analysis of a electronic ball grid array Sparse solver, symmetric matrix, 6000k dofs, transient, nonlinear, structural analysis with 1 iteration. large sized job for direct solvers, should run incore on machines with 128 gB or more of memory, good test of processor flop speed if running incore and I/o if running out-of-core

17

© Dell

Test case: sedan_4m

Description: external flow over a passenger sedan. 3.6m cells, turbulent flow, pressure-based coupled solver

Test case: aircraft_2m

Description: external flow over an aircraft wing. 1.8m cells, coupled implicit solver

Test case: truck_14m

Description: external flow case over a truck body. 14m cells, turbulent flow, segregated implicit solver

Test Case: truck_poly_14m

Description: external flow over a truck body using a polyhedral mesh. 14m cells, turbulent flow, segregated implicit solver

Test case: truck_111m

Description: external flow case over a truck body. 111m cells, turbulent flow, segregated implicit solver

18

© Dell

C. Appendix: ANSYS CFX Benchmark Cases

Test case: Pump

Description: Automotive pump with rotating and stationary components (2 domains), turbulent k-e, incompressible, isothermal, multiple frames of reference 1,305,718 nodes, 5,362,055 elements, 4,509,881 tetrahedral, 850,617 prisms, 1557 pyramids

Test case: LeMansCar

Description: low speed external aero around a lemans-style car, turbulent k-e, ideal gas, heat transfer 1,861,696 nodes, 10,285,401 elements (all tetrahedral)

Test Case: Airfoil_10M

Description: transonic flow around an airfoil. flow is 2d - the mesh is extruded to give a 3d meshes of various sizes, turbulent SSt, ideal gas, heat transfer 9,933,000 nodes, 9,434,520 elements (all hexahedra)

Test case: Airfoil_50M

Description: transonic flow around an airfoil. flow is 2d - the mesh is extruded to give a 3d meshes of various sizes, turbulent SSt, ideal gas, heat transfer 47,773,000 nodes, 47,172,600 elements (all hexahedra)

Test case: Airfoil_100M

Description: transonic flow around an airfoil. flow is 2d - the mesh is extruded to give a 3d meshes of various sizes, turbulent SSt, ideal gas, heat transfer 104,533,000 nodes, 103,779,720 elements (all hexahedra)