​Phoenix Business Journal: The Arizona startup market needs bridge funding for growth

Just-Published-PBJ-1The state of Arizona has made some great strides in creating a vibrant and growing startup community. Only a few things are missing and the big one right now is that “The Arizona startup market needs bridge funding for growth” Check out the article to get my feelings on the topic, what our problems are and how we can fix them.

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Phoenix Business Journal: Publishing your own book, technology makes it easy

Just-Published-PBJ-1A few years back PADT turned one of our training courses into a book, and even though it is about an obscure programming language for a software product that is only known to our industry, it has done well. In “Publishing your own book, technology makes it easy” I review how truly easy and affordable on-demand self publishing can be. You can see the book here “Introduction to the ANSYS Parametric Design Language – Second Edition

Introduction_to_APDL_V2-1_Cover

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The next webinar of the ANSYS Breakthrough Energy Innovation Campaign is now available!

Turbocharge Rotating Machinery Efficiency with Simulation
 
Rotating machinery users demand increased efficiency, reliability and durability while expecting compliance with regulatory mandates to reduce emissions and noise. Simulation pinpoints solutions and guides trade-offs early in the design process before significant investments have been made. By reducing the need for expensive prototypes and test rigs, simulation delivers better performance at lower cost.
By watching this webinar you will:

● Understand the concept of a virtual prototype and how it reduces development costs while optimizing product performance.

● Identify seven essential features that must be included in a simulation in order to maximize the performance and efficiency.

● Learn how ZECO Hydropower used ANSYS simulation tools coupled with high performance computing to develop a new and optimal intake for a Kaplan turbine in half of the usual time. They were able to reduce civil engineering infrastructure costs to ensure they would be competitive in emerging markets.

● Walk through ZECO’s simulation process and results including CFD turbomachinery simulation, parallel computing, parametric modeling, and optimization tools.

Register here to watch – or Click Here for more information on Machine & Fuel Efficiency
This webinar is presented by Brad Hutchinson and Alessandro Arcidiacono.
Keep checking back to the Energy Innovation Homepage for more updates on upcoming segments, webinars, and other additional content.
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ANSYS 17.2 FLUENT External Flow Over a Truck Body Polyhedral Mesh

Part 3: The ANSYS FLUENT Performance Comparison Series – CUBE Numerical Simulation Appliances by PADT, Inc.

November 22, 2016

External Flow Over a Truck Body with a Polyhedral Mesh (truck_poly_14m)

  • External flow over a truck body using a polyhedral mesh
  • This test case has around 14 million polyhedral cells
  • Uses the Detached Eddy Simulation (DES) model with the segregated implicit solver

ANSYS Benchmark Test Case Information

  • ANSYS HPC Licensing Packs required for this benchmark
    • I used three (3) HPC Packs to unlock all of the cores used during the ANSYS Fluent Test Cases of the CUBE appliances shown on the Figure 1 chart.
    • I did use four (4) HPC Packs for the two 256 core benchmarks shown on the data but only wanted the data for testing.
  • The best average seconds per iteration goes to the 2015 CUBE Intel® Xeon® e5-2667 V3 with a 0.625 time using 128 compute cores.
    • The 2015 CUBE Intel® Xeon® e5-2667 V3 outperformed the 256 core AMD Opteron™ series ANSYS Fluent 17.2 benchmarks.
    • Please note that different numbers of CUBE Compute Nodes were used in this test. However straight across CPU times are also shown for single nodes at 64 cores.
  • To illustrate this ANSYS Fluent test case as it relates to the real world. A completely new ANSYS HPC customer is likely to have up two (2) of the entry level INTEL CUBE Compute Nodes versus eight (8) CUBE compute nodes configuration.
  • Please contact your local ANSYS Software Sales Representative for more information on purchasing ANSYS HPC Packs. You too may be able to speed up your solve times by unlocking additional compute power!
  • What is a CUBE? For more information regarding our Numerical Simulation workstations and clusters please contact our CUBE Hardware Sales Representative at SALES@PADTINC.COM Designed, tested and configured within your budget. We are happy to help and to listen to your specific needs.

Figure 1 – ANSYS 17.2 FLUENT Test Case Graph

truck_poly_14m

ANSYS FLUENT 17.2 External Flow Over a Truck Body – Graph

ANSYS FLUENT External Flow Over a Truck Body with a Polyhedral Mesh (truck_poly_14m) Test Case
Number of cells 14,000,000
Cell type polyhedral
Models DES turbulence
Solver segregated implicit

The CPU Information

The AMD Opteron™ 6000 Series Platform:

Yes, I am still impressed with the performance day after day, 24×7 of these AMD Opeteron CPU’s!  After years of operation the AMD Opteron™ series of processors are still relevant and powerful numerical simulation processors. heavy sigh…For example, after reviewing the ANSYS Fluent Test Case data you can see for yourselves below. The 2012 AMD Opteron™ and 2013 AMD Opteron™ CPU’s can still hang in there with the INTEL XEON CPU’s. However one INTEL CPU node vs. four AMD CPU nodes?

I thought a more realistic test case scenario would be to drop the number of AMD Compute Nodes down to four. Indeed, I could have thrown more of the CUBE Compute Nodes with the AMD Opteron™ series CPU’s inside of them. That is why you can see one 256 core benchmark score where I put all 64 cores on each node to the test. As one would hopefully see in their hardware performance unleashing ANSYS Fluent with 256 core did drop the iteration solve time for the test case with the CUBE Compute Appliances.

Realistically a brand new ANSYS HPC customer is not likely to have:

a) Vast qualities of cores (AMD or INTEL) & compute nodes for optimal distributive numerical solving

b) ANSYS HPC licensing for 512 cores

c) The available circuit breakers to provide power

The Intel® Xeon® CPU’s used for this ANSYS Fluent Test Case

  1. Intel® Xeon® Processor E5-2690 v4  (35M Cache, 2.60 GHz)
  2. Intel® Xeon® Processor E5-2667 v4  (25M Cache, 3.20 GHz)
  3. Intel® Xeon® Processor E5-2667 v3  (20M Cache, 3.20 GHz)
  4. Intel® Xeon® Processor E5-2667 v2  (25M Cache, 3.30 GHz)

The Estimated Wattage?

No the lights did not dim…but here is a quick comparison with energy use by estimated maximum Watt’s used metric shows up in volumes (decibels) and dollars ($$$) saved or spent.

Less & More!

Overall CUBE Compute Node drops in average watts estimated consumption, indeed has moved forward in progress over the past four years!

  • 2012 CUBE AMD Numerical Simulation Appliance with the Opteron™ 6278 – Four (4) Compute Nodes
    • Estimated CUBE Configuration @ Full Power: ~8000 Watts
  • 2013 CUBE AMD Numerical Simulation Appliance with the Opteron™ 6380
    • Estimated CUBE Configuration @ Full Power: ~7000 Watts
  • 2015 CUBE Numerical Simulation Appliance with the  Intel® Xeon® e5-2667 V3 – Eight (8) Compute Nodes
    • Estimated CUBE Configuration @ Full Power: ~4000 Watts
  • 2016 CUBE Numerical Simulation Appliance with the Intel® Xeon® e5-2667 V4 – One (1) Compute Node.
    • Estimated CUBE Configuration @ Full Power:  ~900 Watts
  • 2016 CUBE Numerical Simulation Appliance with the Intel® Xeon® e5-2690 V4 – Two (2) Compute Nodes
    • Estimated CUBE Configuration @ Full Power:  ~1200 Watts

Figure 2 – Estimated CUBE compute node power consumption as configured for this ANSYS FLUENT Test Case.

Power consumption means money

CUBE HPC Compute Node Power Consumption as configured

The CUBE phenomenon

2012 AMD Opteron™ 6278 2015 CUBE Intel® Xeon® e5-2667 V3
4 x Compute Node CUBE HPC Appliance 8 x Compute Node CUBE HPC Appliance
4 x 16c @2.4GHz/ea 2 x 8c @3.2GHz/ea  – Intel® Xeon® e5-2667 V3
Quad Socket motherboard Dual Socket motherboard
DDR3-1866 MHz ECC REG DDR4-2133 MHz ECC REG
5 x 600GB SAS2 15k RPM 4 x 600GB SAS3 15k RPM
40Gbps Infiniband QDR High Speed Interconnect 2016 CUBE Intel® Xeon® e5-2667 V4
2013 CUBE AMD Opteron™ 6380 1 x CUBE HPC Workstation
4 x Compute Node CUBE HPC Appliance 2 x 8c @3.2GHz/ea  – Intel® Xeon® e5-2667 V4
4 x 16c @2.5GHz/ea Dual Socket motherboard
Quad Socket  motherboard DDR4-2400 MHz LRDIMM
DDR3-1866 MHz ECC REG 6 x 600GB SAS3 15k RPM
3 x 600GB SAS2 15k RPM 2016 CUBE Intel® Xeon® e5-2690 V4
40Gbps Infiniband QDRT High Speed Interconnect 1 x 1U CUBE APPLIANCE – 2 Compute Nodes
2014 CUBE Intel® Xeon® e5-2667 V2 2 x 14c @2.6GHz/ea – Intel® Xeon® e5-2690 V4
1 x CUBE HPC Workstation Dual Socket motherboard
2 x 8c @3.3GHz/ea –  Intel® Xeon® e5-2667 V2 DR4-2400 MHz LRDIMM
Dual Socket motherboard 4 x 600GB SAS3 15k RPM – RAID 10
DDR3-1866 MHz ECC REG 56Gbps Infiniband FDR CPU High Speed Interconnect
3 x 600GB SAS2 15k RPM 10Gbps Ethernet Low Latency

Operating Systems Used

  1. Linux 64-bit
  2. Windows 7 Professional 64-Bit
  3. Windows 10 Professional 64-Bit
  4. Windows Server 2012 R2 Standard Edition w/HPC

It Is All About The Data

Test Metric – Average Seconds Per Iteration

  • Fastest Time: 0.625 seconds per iteration – 2015 CUBE Intel® Xeon® e5-2667 V3
  • ANSYS FLUENT 17.2
Cores 2014 CUBE Intel® Xeon® e5-2667 V2

(1 x Node)

2015 CUBE Intel® Xeon® e5-2667 V3

(8 x Nodes)

2016 CUBE Intel® Xeon® e5-2667 V4

(1 x Node)

2016 CUBE Intel® Xeon® e5-2690 V4

(2 x Nodes)

2012 AMD Opteron™ 6278

(4 x Nodes)

2013 CUBE AMD Opteron™ 6380

(4 x Nodes)

1 100.6 65.8 32.154 40.44 120.035 90.567
2 40.337 32.024 17.149 35.355 63.813 46.385
4 20.171 16.975 11.915 19.735 32.544 23.956
6 13.904 12.363 9.311 13.76 21.805 17.147
8 10.605 9.4 7.696 11.121 16.783 13.158
12 7.569 6.913 6.764 8.424 11.59 10.2
16 6.187 4.286 6.388 7.363 8.96 7.94
32 2.539 4.082 6.033 4.75
48 2.778 4.126 3.835
52 2.609 3.161 4.784
55 2.531 3.003 4.462
56 2.681 3.025 4.368
*64 3.871 5.004
64 2.688 2.746
96 2.433 2.202
128 0.625 2.112 2.367
256 1.461 3.531

* One (1) CUBE Compute Node with  4 x AMD Opteron™ Series CPU’s for a total of 64 cores was used to derive these two ANSYS Fluent Benchmark data points (Baseline).

PADT offers a line of high performance computing (HPC) systems specifically designed for CFD and FEA number crunching aimed at a balance between cost and performance. We call this concept High Value Performance Computing, or HVPC. These systems have allowed PADT and our customers to carry out larger simulations, with greater accuracy, in less time, at a lower cost than name-brand solutions. This leaves you more cash to buy more hardware or software.

http://www.cube-hvpc.com/

Related Blog Posts

ANSYS FLUENT Performance Comparison: AMD Opteron vs. Intel XEON

Part 2: ANSYS FLUENT Performance Comparison: AMD Opteron vs. Intel XEON

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SFF Symposium 2016 Paper: Predicting the Mechanical Behavior of ULTEM-9085 Honeycomb Structures

Our work on  3D printed honeycomb modeling that started as a Capstone project with students from ASU in September 2015 (described in a previous blog post), was published in a peer-reviewed paper released last week in the proceedings of the SFF Symposium 2016. The full title of the paper is “A Validated Methodology for Predicting the Mechanical Behavior of ULTEM-9085 Honeycomb Structures Manufactured by Fused Deposition Modeling“. This was the precursor work that led to a us winning an 18-month award to pursue this work further with America Makes.

Download the whole paper at the link below:
http://sffsymposium.engr.utexas.edu/sites/default/files/2016/168-Bhate.pdf

Abstract
ULTEM-9085 has established itself as the Additive Manufacturing (AM) polymer of choice for end-use applications such as ducts, housings, brackets and shrouds. The design freedom enabled by AM processes has allowed us to build structures with complex internal lattice structures to enhance part performance. While solutions exist for designing and manufacturing cellular structures, there are no reliable ways to predict their behavior that account for both the geometric and process complexity of these structures. In this work, we first show how the use of published values of elastic modulus for ULTEM-9085 honeycomb structures in FE simulation results in 40- 60% error in the predicted elastic response. We then develop a methodology that combines experimental, analytical and numerical techniques to predict elastic response within a 5% error. We believe our methodology is extendable to other processes, materials and geometries and discuss future work in this regard.

Figure

Fig 1. Honeycomb tensile test behavior varying as a function of manufacturing parameters

The ASU Capstone team (left to right): Drew Gibson, Jacob Gerbasi, John Reeher, Matthew Finfrock, Deep Patel and Joseph Van Soest.

Fig 2. The ASU Capstone team (left to right): Drew Gibson, Jacob Gerbasi, John Reeher, Matthew Finfrock, Deep Patel and Joseph Van Soest.

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ANSYS 17.2 CFX Benchmark External Flow Over a LeMans Car

Wow? yet another ANSYS Bench marking blog post? I know, but I have had four blog posts in limbo for months. There is no better time than now and since it is Friday. Time to knock out another one of these fine looking ANSYS 17.2 bench marking results of my list!

The ANSYS 17.2 CFX External Flow Over a LeMans Car Test Case

…dun dun dah!

On The Fast Track! ANSYS 17.2

On The Fast Track! ANSYS 17.2

The ANSYS CFX test case has approximately 1.8 million nodes

  • 10 million elements, all tetrahedral
  • Solves compressible fluid flow with heat transfer using the k-epsilon turbulence model.

ANSYS Benchmark Test Case Information

  • ANSYS HPC Licensing Packs required for this benchmark
    • I used (3) HPC Packs to unlock all 56 cores of the CUBE a56i.
    • The fastest solve time goes to the CUBE a56i – Boom!
      • From start to finish a total of forty-six (46) ticks on the clock on the wall occurred.
      • A total of fifty-five (55) cores in use between two twenty-eight (28) core nodes.
      • Windows 2012 R2 Standard Edition w/HPC update 3
      • MS-MPI v7.1
      • ANSYS CFX 17.2
  • Please contact your local ANSYS Software Sales Representative for more information on purchasing ANSYS HPC Packs. You too may be able to speed up your solve times by unlocking additional compute power!
  • What is a CUBE? For more information regarding our Numerical Simulation workstations and clusters please contact our CUBE Hardware Sales Representative at SALES@PADTINC.COM Designed, tested and configured within your budget. We are happy to help and to listen to your specific needs.

Figure 1 – ANSYS CFX benchmark data for the tetrahedral, 10 million elements External Flow Over a LeMans Car Test Case

ANSYS CFX Benchmark Data

ANSYS CFX Benchmark Data

ANSYS CFX Test Case Details – Click Here for more information on this benchmark

External Flow Over a LeMans Car
Number of nodes 1,864,025
Element type Tetrahedral
Models k-epsilon Turbulence, Heat Transfer
Solver Coupled Implicit

The CPU Information

The benchmark data is derived off of the running through the ANSYS CFX External Flow Over a LeMans Car test case. Take a minute or three to look at how these CPU’s perform with one of the very latest ANSYS releases, ANSYS Release 17.1 & ANSYS Release 17.2.

Wall Clock Time!

I have focused and tuned the numerical simulation machines with a focus on wall clock time for years now. What is funny if you ask Eric Miller we were talking about wall clock times this morning.

What is wall clock time? Simply put –> How does the solve time FEEL to the engineer…..yes, i just equated a feeling to a non-human event. Ah yes, to feel…oh and  I was reminded of old Van Halen song where David Lee Roth says.

Oh man, I think the clock is slow.

  I don’t feel tardy.

Class Dismissed!”

The CUBE phenomenon

CUBE a56i Appliance – Windows 2012 R2 Standard w/HPC
1U CUBE APPLIANCE (2 x 28)
4 x 14c @2.6GHz/ea – Intel® Xeon® e5-2690 V4
Dual Socket motherboard
256GB DDR4-2400 MHz LRDIMM
4 x 600GB SAS3 15k RPM
56Gbps Infiniband FDR CPU High Speed Interconnect
10Gbps Ethernet Low Latency
CUBE w32i Workstation – Windows 10 Professional
1 x 4U CUBE APPLIANCE
2 x 16c @2.6GHz/ea – Intel® Xeon® e5-2697a V4
Dual Socket motherboard
256GB DDR4-2400 MHz LRDIMM
2 x 600GB SAS3 15k RPM
NVIDIA QUADRO M4000

It Is All About The Data

 11/17/2016

PADT, Inc. – Tempe, AZ

ANSYS CFX 17.1 ANSYS CFX 17.1 ANSYS CFX 17.2
Total wall clock time Cores CUBE w32i CUBE a56i CUBE a56i
2 555 636 609
4 304 332 332
8 153 191 191
16 105 120 120
24 78 84 84
32 73 68 68
38 0 61 59
42 0 55 55
48 0 51 51
52 0 52 48
55 0 47 46
56 0 52 51

Picture Sharing Time!

Check out the pictures below of the Microsoft Server 2012 R2  HPC Cluster Manager.

I used the Windows Server 2012 R2  on both of the two compute nodes that make up the CUBE a56i.

Microsoft 2012 R2 w/HPC – is very quick, and oh so very powerful!

winhpc-cfx-56c-cpu

Windows 2012 HPC

Microsoft Windows 2012 R2 HPC. It is time…

INTEL XEON e5-2690 v4

The INTEL XEON e5-2690 v4 loves the turbo mode vrrooom It is time…

Please be safe out there in the wilds, you are all dismissed for the weekend!

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Press Release: New 3D Printing Support Cleaning Apparatus Features Large Capacity for Stratasys FDM Systems

PADT-Press-Release-IconBuilding on the worldwide success of previous products in the family, PADT has just released the new SCA 3600, a large capacity cleaning system for removing the support material from Stratasys FDM parts.  This new system adds capacity and capability over the existing benchtop SCA-1200HT System.

A copy of the press release is below.
At the same time, we are also launching a new website for support removal: www.padtinc.com/supportremoval.

The SCA 3600 can dissolve support from all the SST-compatible materials you use – ABS, PC, and nylon. A “no heat” option provides agitation at room temperature for the removal of Polyjet SUP706 material as well. The SCA 3600’s versatility and efficient cleaning performance are built on the success of earlier models with all the features you have come to expect, in a larger and more capable model.sca_3600-3pics

Since the launch of the original SCA-1200 in 2008, PADT has successfully manufactured and supported the SCA family of products for users worldwide. Common requests from desktop SCA users were for a larger system for bigger parts, the ability to clean many parts at the same time, and the option to remove supports from PolyJet parts. The SCA 3600 is the answer: Faster, larger, and more capable.

sca-logo3-web7SCA 3600 Key Features are:

  • Removes soluble support from ABS, PC, and nylon 3D printed FDM parts
  • Removes soluble support from PolyJet 3D Printed parts
  • User-selectable temperature presets at 50, 60, 70, and 85°C and “No Heat” for PolyJet
  • User-controlled timer
  • Uses cleaning solutions from Stratasys
  • Unique spray nozzle optimizes flow coverage
  • 230 VAC +/- 10%, 15A
  • Whisper-quiet operation
  • Includes rolling cart for easy movement, filling, and draining.
  • Capacity: 27 gal / 102 L
  • Size: 42.8″ x 22.8″ x 36.5″/ 1,086 x 578 x 927 mm
  • 16” x 16” x 14” / 406 x 406 x 356 mm removable large parts basket
  • Integral hinged lid and small part basket
  • Stainless steel tub and basket
  • Over temperature and water level alarms
  • Automatic halt of operation with alarms
  • Field replaceable sub-assemblies
  • Regulatory Compliance: CE/cTUVus/RoHS/WEEE

You can download our new brochure for both systems:

SCA 3600 Spec Sheet

SCA-1200HT Spec Sheet

If you are interested in learning more or adding an SCA 3600 to your additive manufacturing lab, contact your Stratasys reseller.

Official copies of the press release can be found in HTML and PDF.

Press Release:

New 3D Printing Support Cleaning Apparatus Features Large Capacity for Stratasys FDM Systems

Offered Worldwide, the SCA 3600 is Big Enough to Handle Large 3D Printed Parts, Effortlessly Dissolving Support Material

TEMPE, Ariz., November 17, 2016 – Phoenix Analysis & Design Technologies, Inc. (PADT), the Southwest’s largest provider of simulation, product development, and rapid prototyping services and products, today introduced its new SCA3600 3D Printing Support  Cleaning Apparatus (SCA). The systems are sold exclusively by Stratasys, Ltd. (SSYS) for use with its FORTUS line of 3D Printers. The hands-free support removal technology is a huge advantage to people who use Fused Deposition Modeling (FDM) systems for their 3D Printing.

“With more than 10,000 of our benchtop SCA units in the field, we gathered a wealth of knowledge on performance and reliability,” said Rey Chu, Co-owner and Principal of PADT. “We used that information to design and manufacture a system that cleans larger parts, or multiple small parts, while keeping the speed, easy maintenance and great user experience of the benchtop system.”

A powerful upgrade over PADT’s successful SCA-1200HT and SCA-1200 support removal products that have been in use around the world since 2008, the SCA 3600 features a simpler, more user-friendly design. The new versatile SCA offers temperature choices of 50, 60, 70 and 80 degrees Celsius, as well as no-heat, that readily cleans supports from all SST compatible materials – ABS, PC and Nylon. The SCA 3600 also features a large 16” x 16” x 14” parts basket, 3400 watts of heating for faster warm-up and a wheeled cart design for mobility.

The advantages of the system were highlighted by Sanja Wallace, Sr. Director of Product Marketing and Management at Stratasys, Ltd. when she commented, “the addition of the SCA 3600 as an accessory to our very successful FORTUS systems simplifies the support removal process with increased speed and capacity for multiple large parts.”

Once parts are printed, users simply remove them from their Stratasys FDM system, place them in the SCA 3600, set a cleaning cycle time and temperature, and then walk away.  The device gently agitates the 3D printed parts in the heated cleaning solution, effortlessly dissolving away all of the support material. This process is more efficient and user friendly than those of other additive manufacturing systems using messy powders or support material that must be manually removed.

More information on the systems available at www.padtinc.com/supportremoval. Those interested in acquiring an SCA 3600 should contact their local Stratasys reseller.

About Phoenix Analysis and Design Technologies

Phoenix Analysis and Design Technologies, Inc. (PADT) is an engineering product and services company that focuses on helping customers who develop physical products by providing Numerical Simulation, Product Development, and Rapid Prototyping solutions. PADT’s worldwide reputation for technical excellence and experienced staff is based on its proven record of building long term win-win partnerships with vendors and customers. Since its establishment in 1994, companies have relied on PADT because “We Make Innovation Work.” With over 80 employees, PADT services customers from its headquarters at the Arizona State University Research Park in Tempe, Arizona, and from offices in Torrance, California, Littleton, Colorado, Albuquerque, New Mexico, and Murray, Utah, as well as through staff members located around the country. More information on PADT can be found at http://www.PADTINC.com.

###

Media Contact
Alec Robertson
TechTHiNQ on behalf of PADT
585-281-6399
alec.robertson@techthinq.com
PADT Contact
Eric Miller
PADT, Inc.
Principal & Co-Owner
480.813.4884
eric.miller@padtinc.com

 

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ANSYS R17 Topological Optimization Application Example – Saxophone Brace

topo-opt-sax-a2What is Topological Optimization? If you’re not familiar with the concept, in finite element terms it means performing a shape optimization utilizing mesh information to achieve a goal such as minimizing volume subject to certain loads and constraints. Unlike parameter optimization such as with ANSYS DesignXplorer, we are not varying geometry parameters. Rather, we’re letting the program decide on an optimal shape based on the removal of material, accomplished by deactivating mesh elements. If the mesh is fine enough, we are left with an ‘organic’ sculpted shape elements. Ideally we can then create CAD geometry from this organic looking mesh shape. ANSYS SpaceClaim has tools available to facilitate doing this.

topo-opt-sax-a1Topological optimization has seen a return to prominence in the last couple of years due to advances in additive manufacturing. With additive manufacturing, it has become much easier to make parts with the organic shapes resulting from topological optimization. ANSYS has had topological optimization capability both in Mechanical APDL and Workbench in the past, but the capabilities as well as the applications at the time were limited, so those tools eventually died off. New to the fold are ANSYS ACT Extensions for Topological Optimization in ANSYS Mechanical for versions 17.0, 17.1, and 17.2. These are free to customers with current maintenance and are available on the ANSYS Customer Portal.

In deciding to write this piece, I decided an interesting example would be the brace that is part of all curved saxophones. This brace connects the bell to the rest of the saxophone body, and provides stiffness and strength to the instrument. Various designs of this brace have been used by different manufacturers over the years. Since saxophone manufacturers like those in other industries are often looking for product differentiation, the use of an optimized organic shape in this structural component could be a nice marketing advantage.

This article is not intended to be a technical discourse on the principles behind topological optimization, nor is it intended to show expertise in saxophone design. Rather, the intent is to show an example of the kind of work that can be done using topological optimization and will hopefully get the creative juices flowing for lots of ANSYS users who now have access to this capability.

That being said, here are some images of example bell to body braces in vintage and modern saxophones. Like anything collectible, saxophones have fans of various manufacturers over the years, and horns going back to production as early as the 1920’s are still being used by some players. The older designs tend to have a simple thin brace connecting two pads soldered to the bell and body on each end. Newer designs can include rings with pivot connections between the brace and soldered pads.

topo-opt-sax-01

Half Ring Brace

 

Solid connection to bell, screw joint to body

Solid connection to bell, screw joint to body

Older thin but solid brace rigidly connected to soldered pads

Older thin but solid brace rigidly connected to soldered pads

topo-opt-sax-04

Modern ring design

Modern Dual Degree of Freedom with Revolute Joint Type Connections

Modern Dual Degree of Freedom with Revolute Joint Type Connections

Hopefully those examples show there can be variation in the design of this brace, while not largely tampering with the musical performance of the saxophone in general. The intent was to pick a saxophone part that could undergo topological optimization which would not significantly alter the musical characteristics of the instrument.

The first step was to obtain a CAD model of a saxophone body. Since I was not able to easily find one freely available on the internet that looked accurate enough to be useful, I created my own in ANSYS SpaceClaim using some basic measurements of an example instrument. I then modeled a ‘blob’ of material at the brace location. The idea is that the topological optimization process will remove non-needed material from this blob, leaving an optimized shape after a certain level of volume reduction.

Representative Solid Model Geometry Created in ANSYS SpaceClaim. Note ‘Blob’ of Material at Brace Location.

Representative Solid Model Geometry Created in ANSYS SpaceClaim. Note ‘Blob’ of Material at Brace Location.

In ANSYS Mechanical, the applied boundary conditions consisted of frictionless support constraints at the thumb rest locations and a vertical displacement constraint at the attachment point for the neck strap. Acceleration due to gravity was applied as well. Other loads, such as sideways inertial acceleration, could have been considered as well but were ignored for the sake of simplicity for this article. The material property used was brass, with values taken from Shigley and Mitchell’s Mechanical Engineering Design text, 1983 edition.

topo-opt-sax-07

Applied Boundary Conditions Were Various Constraints at A, B, and C, as well as Acceleration Due to Gravity.

This plot shows the resulting displacement distribution due to the gravity load:

topo-opt-sax-08

Now that things are looking as I expect, the next step is performing the topological optimization.

Once the topological optimization ACT Extension has been downloaded from the ANSYS Customer Portal and installed, ANSYS Mechanical will automatically include a Topological Optimization menu:

topo-opt-sax-09

I set the Design Region to be the blog of material that I want to end up as the optimized brace. I did a few trials with varying mesh refinement. Obviously, the finer the mesh, the smoother the surface of the optimized shape as elements that are determined to be unnecessary are removed from consideration. The optimization Objective was set to minimize compliance (maximize stiffness). The optimization Constraint was set to volume at 30%, meaning reduce the volume to 30% of the current value of the ‘blob’.
After running the solution and plotting Averaged Node Values, we can see the ANSYS-determined optimized shape:

topo-opt-sax-10

Two views of the optimized shape.

What is apparent when looking at these shapes is that the ‘solder patch’ where the brace attaches to the bell on one end and the body on the other end was allowed to be reduced. For example, in the left image we can see that a hole has been ‘drilled’ through the patch that would connect the brace to the body. On the other end, the patch has been split through the middle, making it look something like an alligator clip.

 

Another optimization run was performed in which the solder pads were held as surfaces that were not to be changed by the optimization. The resulting optimized shape is shown here:

topo-opt-sax-11

Noticing that my optimized shape seemed on the thick side when compared to production braces, I then changed the ‘blob’ in ANSYS SpaceClaim so that it was thinner to start with. With ANSYS it’s very easy to propagate geometry changes as all of the simulation and topological optimizations settings stay tied to the geometry as long as the topology of those items stays the same.

Here is the thinner chunk after making a simple change in ANSYS SpacClaim:

topo-opt-sax-12

And here is the result of the topological optimization using the thinner blob as the starting point:

topo-opt-sax-13

Using the ANSYS SpaceClaim Direct Modeler, the faceted STL file that results from the ANSYS topological optimization can be converted into a geometry file. This can be done in a variety of ways, including a ‘shrink wrap’ onto the faceted geometry as well as surfaces fit onto the facets. Another option is to fit geometry in a more general way in an around the faceted result. These methods can also be combined. SpaceClaim is really a great tool for this. Using SpaceClaim and the topological optimization (faceted) result, I came up with three different ‘looks’ of the optimized part.

Using ANSYS Workbench, it’s very easy to plug the new geometry component into the simulation model that I already had setup and run in ANSYS Mechanical using the ‘blob’ as the brace in the original model. I then checked the displacement and stress results to see how they compared.

First, we have an organic looking shape that is mostly faithful to the results from the topological optimization run. This image is from ANSYS SpaceClaim, after a few minutes of ‘digital filing and sanding’ work on the STL faceted geometry output from ANSYS Mechanical.

topo-opt-sax-14

This shows the resulting deflection from this first, ‘organic’ candidate:

topo-opt-sax-15

The next candidate is one where more traditional looking solid geometry was created in SpaceClaim, using the topological optimization result as a guide. This is what it looks like:

topo-opt-sax-16

This is the same configuration, but showing it in place within the saxophone bell and body model in ANSYS SpaceClaim:

topo-opt-sax-17

Next, here is the deformation result for our simple loading condition using this second geometry configuration:

topo-opt-sax-18

The third and final design candidate uses the second set of geometry as a starting point, and then adds a bit of style while still maintaining the topological optimization shape as an overall guide. Here is this third candidate in ANSYS SpaceClaim:

topo-opt-sax-19

Here are is the resulting displacement distribution using this design:

topo-opt-sax-20

This shows the maximum principal stress distribution within the brace for this candidate:

topo-opt-sax-21

Again, I want to emphasize that this was a simple example and there are other considerations that could have been included, such as loading conditions other than acceleration due to gravity. Also, while it’s simple to include modal analysis results, in the interest of brevity I have not included them here. The main point is that topological optimization is a tool available within ANSYS Mechanical using the ACT extension that’s available for download on the customer portal. This is yet another tool available to us within our ANSYS simulation suite. It is my hope that you will also explore what can be done with this tool.

Regarding this effort, clearly a next step would be to 3D print one or more of these designs and test it out for real. Time permitting, we’ll give that a try at some point in the future.

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ANSYS 17.1 FEA Benchmarks using v17-sp5

The CUBE machines that I used in this ANSYS Test Case represent a fine balance based on price, performance and ANSYS HPC licenses used.

Click Here for more information on the engineering simulation workstations and clusters designed in-house at PADT, Inc.. PADT, Inc. is happy to be a premier re-seller and dealer of Supermicro hardware.

  • ANSYS Benchmark Test Case Information.
  • ANSYS HPC Licensing Packs required for this benchmark
    • I used (2) HPC Packs to unlock all 32 cores.
  • Please contact your local ANSYS Software Sales Representative for more information on purchasing ANSYS HPC Packs. You too may be able to speed up your solve times by unlocking additional compute power!
  • What is a CUBE? For more information regarding our Numerical Simulation workstations and clusters please contact our CUBE Hardware Sales Representative at SALES@PADTINC.COM Designed, tested and configured within your budget. We are happy to help and to  listen to your specific needs.

Figure 1 – ANSYS benchmark data from three excellent machines.

CUBE

CUBE by PADT, Inc. ANSYS Release 17.1 FEA Benchmark

BGA (V17sp-5)

BGA (V17sp-5)
Analysis Type Static Nonlinear Structural
Number of Degrees of Freedom 6,000,000
Equation Solver Sparse
Matrix Symmetric

Click Here for more information on the ANSYS Mechanical test cases. The ANSYS website has great information pertaining to the benchmarks that I am looking into today.

Pro Tip –> Lastly, please check out this article by Greg Corke one of my friends at ANSYS, Inc. I am using the ANSYS benchmark data fromthe Lenovo Thinkstation P910 as a baseline for my benchmark data.  Enjoy Greg’s article here!

  • The CPU Information

The benchmark data is derived off of the running through the BGA (sp-5) ANSYS test case. CPU’s and how they perform with one of the very latest ANSYS releases, ANSYS Release 17.1.

  1.  Intel® Xeon® e5-2680 V4
  2.  Intel® Xeon® e5-2667 V4
  3.  Intel® Xeon® e5-2697a V4
  • It Is All About The Data
    • Only one workstation was used for the data in this ANSYS Test Case
    • No GPU Accelerator cards are used for the data
    • Solution solve times are in seconds
ANSYS 17.1 Benchmark BGA v17sp-5
Lenovo ThinkStation P910 2680 V4 CUBE w16i 2667 V4 CUBE w32i 2697A V4
Cores Customer X  – 28 Core @2.4GHz/ea CUBE w16i CUBE w132i tS
2 1016 380.9 989.6 1.03
4 626 229.6 551.1 1.14
8 461 168.7 386.6 1.19
12 323 160.7 250.5 1.29
16 265 161.7 203.3 1.30
20 261 0 176.9 1.48
24 246 0 158.1 1.56
28 327 0 151.8 2.15
31 0 0 145.2 2.25
32 0 0 161.7 2.02
15-Nov-16 PADT, Inc. – Tempe, AZ –
  • Cube w16i Workstation – Windows 10 Professional
    1 x 4U CUBE APPLIANCE
    2 x 8c @3.2GHz/ea
    Dual Socket motherboard
    256GB DDR4-2400 MHz LRDIMM
    6 x 600GB SAS3 15k RPM
    NVIDIA QUADRO K6000
  • CUBE w32i Workstation – Windows 10 Professional
    1 x 4U CUBE APPLIANCE
    2 x 16c @2.6GHz/ea
    Dual Socket motherboard
    256GB DDR4-2400 MHz LRDIMM
    2 x 600GB SAS3 15k RPM
    NVIDIA QUADRO M4000
  • Lenovo Thinkstation P910 Workstation – Windows 10 Professional
    Lenovo P910 Workstation
    2 x 14c @2.4GHz/ea
    Dual Socket motherboard
    128GB DDR4-2400 MHz
    512GB NVMe SSD / 2 x 4TB SATA HDD / 512GB SATA SSD
    NVIDIA QUADRO M2000

As you will may have noticed above, the CUBE workstation with the Intel Xeon e5-2697A V4 had the fastest solution solve time for one workstation.

  • *** Using 31 cores the CUBE w32i finished the sp-5 test case in 145.2 seconds.

See 32 Cores of Power! CUBE by PADT, Inc.

cube-w32i-coresCUBE w32i

CUBE w32i

CUBE by PADT, Inc. of ANSYS 17.1 Benchmark Data for sp-5

CUBE by PADT, Inc. of ANSYS 17.1 Benchmark Data for sp-5

Thank you!

http://www.cube-hvpc.com/

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Phoenix Business Journal: The startup ecosystem cries of despair – ‘There’s no seed money’

Just-Published-PBJ-1If you spend time in the Southwest startup community you here a lot of complaining about not enough seed money.  In “The startup ecosystem cries of despair: ‘There’s no seed money‘” I share my perspective that tight markets make for smarter investments.

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ANSYS Startup Roadshow – November 18th, Phoenix AZ

Phoenix!

The Co-Owner of PADT, Inc. Eric Miller will be at The Gateway Center for Entrepreneurial Innovation (CEI) this Friday, November 18th, from 12-1pm to discuss how ANSYS software is helping new entrepreneurs drive success through simulation.

This is a free event, and while registration is not required it is preferred.

The presentation will include a discussion on:

  • What simulation is and how it can be applied to product development

  • How partnering with PADT and ANSYS can be crucial to the success of a startup
  • How using ANSYS software will help deliver ideas to market more rapidly and cost effectively. Thus saving money, time, and increasing the probability of success.

Click Here for directions and additional registration information.

Eric will also be presenting information on the ANSYS Startup Program, which provides entrepreneurs with access to various ANSYS multiphysics simulation products bundled and priced specifically for early stage startup companies.

Acceptance to this program is limited to companies who are not current ANSYS customers and meet a variety of qualifications.

Those who are eligible will also receive access to the ANSYS Customer Portal for marketing opportunities and customer support.

Visit Padtinc.com/ANSYS_Startup to see if you qualify for this program, or Click Here to register to attend the startup presentation on November 18th.

We look forward to seeing you there

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Phoenix Business Journal: What does living in a post-fact world imply for business?

Just-Published-PBJ-1One of the many realizations to come from this election cycle is that telling the truth really doesn’t matter anymore, we live in a post-fact world where you can say or post anything and ignore proof that it is wrong.  In this week’s post, I ask: “What does living in a post-fact world imply for business?

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ANSYS 17.2 Executable Paths on Linux


ansys-linux-penguin-1When running on a machine with a Linux operating system, it is not uncommon for users to want to run from the command line or with a shell script. To do this you need to know where the actual executable files are located. Based on a request from a customer, we have tried to coalesce the major ANSYS product executables that can be run via command line on Linux into a single list:

ANSYS Workbench (Includes ANSYS Mechanical, Fluent, CFX, Polyflow, Icepak, Autodyn, Composite PrepPost, DesignXplorer, DesignModeler, etc.):

/ansys_inc/v172/Framework/bin/Linux64/runwb2

ANSYS Mechanical APDL, a.k.a. ANSYS ‘classic’:

/ansys_inc/v172/ansys/bin/launcher172 (brings up the MAPDL launcher menu)
/ansys_inc/v172/ansys/bin/mapdl (launches ANSYS MAPDL)

CFX Standalone:

/ansys_inc/v172/CFX/bin/cfx5

Autodyn Standalone:

/ansys_inc/v172/autodyn/bin/autodyn172

Note: A required argument for Autodyn is –I {ident-name}

Fluent Standalone (Fluent Launcher):

/ansys_inc/v172/fluent/bin/fluent

Icepak Standalone:

/ansys_inc/v172/Icepak/bin/icepak

Polyflow Standalone:

/ansys_inc/v172/polyflow/bin/polyflow/polyflow < my.dat

Chemkin:

/ansys_inc/v172/reaction/chemkinpro.linuxx8664/bin/chemkinpro_setup.ksh

Forte:

/ansys_inc/v172/reaction/forte.linuxx8664/bin/forte.sh

TGRID:

/ansys_inc/v172/tgrid/bin/tgrid

ANSYS Electronics Desktop (for Ansoft tools, e.g. Maxwell, HFSS)

/ansys_inc/v172/AnsysEM/AnsysEM17.2/Linux64/ansysedt

SIWave:

/ansys_inc/v172/AnsysEM/AnsysEM17.2/Linux64/siwave

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The Chemistry Behind Soluble Support Removal in Fused Deposition Modeling

fdm-support-chemestry-1In the Fused Deposition Modeling (FDM) process, support structures are needed for features with overhang incline angle less than 45-degree from horizontal. Stratasys developed a series of support materials for different model materials: SR-30TM for ABS, SR-100TM for polycarbonate and SR-110TM for nylon. Also, they developed the Waterworks Soluble Concentrate, P400-SC, to be used to dissolve these support materials. In this blog post, I develop a theory for the chemical reaction how P400-SC Waterworks dissolves SR-30TM, SR-100TM and SR-110TM support materials. As part of this, I explain how PADT’s Support Cleaning Apparatus (SCA) tank, with its heating and unique circulation and agitation capabilities that are important for the support dissolving process.

Materials Introduction

We begin by looking at the composition of the different materials involved in the table below.

stratasys-support-removal-chemestry-table-01Adapted from Stratasys.com

How P400-SC Works for Support Materials Removal

Polymer can swell and then dissolve into water as a consequence of abundant hydrophilic groups, like carboxyl group (-COOH), ether group (-O-), hydroxyl group (-OH) and so on in its molecular structure. Theoretically, SR-30TM and SR-100TM /SR-110TM Soluble Support Materials including a carboxyl group (-COOH) in their repeat unit are likely to be water soluble. However, they also have a hydrophobic ester group (-COO-) in their repeat unit, which counteracts the efficacy of the hydrophilic group on the long carbon chain. Thus, the key to making SR-30TM and SR-100TM /SR-110TM soluble, is to somehow get rid of the ester group.

A great example of supports on an FDM part. The part on the right has had the supports dissolved away

A great example of supports on an FDM part. The white material on the part to the left is the soluble support material. The part on the right has had the supports dissolved away

Hydrolysis of ester in pure water is a slow process even the system is heated. Both acid and alkaline conditions can catalyze and speed up the process. Under the acid condition, the hydrolysis is a reversible process until it reaches an equilibrium state, whereas alkaline conditions promote a thorough hydrolysis with a stirring and heating system.

P400-SC Waterworks contains sodium carbonate, sodium hydroxide, sodium lauryl sulfate and sodium metasilicate. The last two constituents, with 1-5 wt% respectively, are auxiliaries in the P400-SC Waterworks. The remaining two react with carboxylic acid and ester group per the following chemical reaction:

  1. R-COOH + NaOH =  R-COONa+ + H2O (neutralization reaction)
  2. 2 R-COOH + Na2CO3 =  2 R-COONa+ + H2O + CO2
  3. R1–COO-R2 + NaOH ≜ R1-COONa+ + R2OH (ester hydrolysis under alkaline condition)

where R is the remaining carbon chain apart from carboxyl group and R1, R2 represent the two-side segments of ester group. Ester hydrolysis is the main reaction we need, which ionizes the ester group and makes it water soluble with an increased polarity. These reactions would happen when SR-30TM or SR-100TM /SR-110TM supports are dropped into a tank with P400-SC Waterworks cleaning solution inside.

From the table above, we can see that ABS-M30TM and PC-10TM don’t have hydrophilic groups, which restrains their solubility into water. Nylon is semi-crystalline polymer and difficult to dissolve into water and most organic solvent, despite the presence of the hydrophilic group acylamino (-CONH-), which still results in a nice water-absorbing ability. All these model materials are common-use engineering plastic with nice chemical resistance (depending on their functional groups), they can be safe in the cleaning solution.

SCA1200HT-side1PADT’s Support Cleaning Apparatus (SCA)

The SCA tank offers an optimized environment with agitation and heating for the ester hydrolysis reaction. The tank has four preset temperature options (50 ℃, 60℃, 70℃, 85℃) for ABS-M30TM, PC-10TM, and FDMTM Nylon 12 model materials, due to their different thermal resistance. The innovative custom designed pump is key to cause the solution to effectively and efficiently dissolve and remove the support materials.

For more information on PADT’s entire line of SCA, please see http://www.supportremoval.com/

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The first webinar of the ANSYS Breakthrough Energy Innovation Campaign is now available

download-6

Register here to watch

Simulation of Planar Magnetic Components – Possible or Impossible?

Planar magnetic components consisting of a ferrite magnetic core and numerous conductor/insulation layers have been in use for many years. Historically, determining temperature dependent winding and core losses has only been possible using iterative testing of physical models due to the difficulty in determining 3-D frequency and thermal dependency. The only way to accomplish this now is to use frequency and thermally dependent material properties in a 2-way spatially coupled simulation.

Additionally, you can only construct a frequency dependent system model that accurately represents the real device after the steady-state temperature condition has been reached throughout the device.

Recent breakthrough developments in simulation technology and high-performance computing from ANSYS make it possible to design, simulate and optimize planar magnetic components without building physical models or compromising simulation fidelity.

This webinar demonstrates how you can use ANSYS software tools, featuring a customized interface complete with manufacturer libraries, to automatically set up and then solve a frequency dependent, 2-way coupled magnetic-thermal model.

Register here to watch

This webinar is presented by Mark Christini, the lead ElectromagneticsMark Christini Application Engineer at ANSYS.

He has been working in design, development, application and manufacturing of electrical devices and systems for the past 30 years. Mark has a strong interest in transformers of all kinds ranging, from small electronic transformers to large oil-filled EHV power transformers.

Keep checking back to the Energy Innovation Homepage for more updates on upcoming segments, webinars, and other additional content.

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