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IEEE Day 2017: Smart Antennas for IoT and 5G

IEEE Day celebrates the first time in history when engineers worldwide and IEEE members gathered to share their technical ideas in 1884. Events were held around the world by 846 IEEE Chapters this year. So, to celebrate, I attended a joint chapter meeting in at The Museum of Flight in Seattle with technical presentations focused on “Smart Antennas for IoT and 5G”. There were approximately 60 in attendance, so assuming this was the average attendance globally results in over 50,000 engineers celebrating IEEE Day worldwide!

The Seattle seminar featured three speakers that spanned theory, design, test, integration, and application of smart antennas. There was much discussion about the complexity and challenges of meeting the ambitious goals of 5G, which extend beyond mobile broadband data access. Some key objectives of 5G are to increase capacity, increase data rates, reduce latency, increase availability, and improve spectral and energy efficiency by 2020. A critical technology behind achieving these goals is beamforming antenna arrays, which were at the forefront of each presentation.

Anil Kumar from Boeing focused on the application of mmWave technology on aircraft. Test data was used to analyze EM radiation leakage through coated and uncoated aircraft windows. However, since existing regulations don’t consider the increased path loss associated with such high frequencies, the integration of 5G wireless applications may be restricted or delayed. Beyond this regulatory challenge, Anil discussed how multipath reflectors and absorbers will present significant challenges to successful integration inside the cabin. Although testing is always required for validation, designing the layout of the onboard transceivers may be impractical to optimize without an asymptotic EM simulation tool that can account for creeping waves, diffraction, and multi-bounce.

Considering the test and measurement perspective, Jari Vikstedt from ETS-Lindgren focused on the challenges of testing smart antenna systems. Smart or adaptive antenna systems will not likely perform the same in an anechoic chamber test as they would in real systems. Of particular difficulty, radiation null placement is just as critical as beam placement. This poses a difficult challenge to the number and location of probes in a test environment. Not only would a large number of probes become impractical, there is significant shadowing at mmWave frequencies which can negatively impact the measurement. Furthermore, compact ranges can significantly impact testing and line of sight measurements become particularly challenging. While not a purely test-oriented observation, this lead to considering the challenge of tower hand off. If a handset and tower use beamforming to maintain a link, if is difficult for an approaching tower to even sense the handset to negotiate the hand-off.

In contrast, if the handset was continuously scanning, the approaching tower could be sensed to negotiate the hand-off before the link is jeopardized.

The keynote speaker, who also traveled from Phoenix to Seattle, was ASU Professor Dr. Constantine Balanis. Dr. Balanis opened his presentation by making a distinction between conventional “dumb antennas” and “smart antennas”. In reality, there are no smart antennas, but instead smart antenna systems. This is a critical point from an engineering perspective since it highlights the complexity and challenge of designing modern communication systems. The focus of his presentation was using an adaptive system to steer null points in addition to the beam in an antenna array using a least mean square (LMS) algorithm. He began with a simple linear patch array with fixed uniform amplitude weights, since an analytic solution was practical and could be used to validate a simulation setup. However, once the simulation results were verified for confidence, designing a more complex array with weighted amplitudes accompanying the element phase shift was only practical through simulation. While beam steering will create a device centric system by targeting individual users on massive multiple input multiple output (MIMO) networks, null steering can improve efficiency by minimizing interference to other devices.

Whether spatial processing is truly the “last frontier in the battle for cellular system capacity”, 5G technology will most certainly usher in a new era of high capacity, high speed, efficient, and ubiquitous means of communication. If you would like to learn more about how PADT approaches antenna simulation, you can read about it here and contact us directly at

Parameterizing Solid Models for ANSYS HFSS

ANSYS HFSS features an integrated “history-based modeler”. This means that an object’s final shape is dependent on each and every operation performed on that object. History-based modelers are a perfect choice for analysis since they naturally support parameterization for design exploration and optimization. However, editing imported solid 3D Mechanical CAD (or MCAD) models can sometimes be challenging with a history-based modeler since there are no imported parameters, the order of operation is important, and operational dependencies can sometimes lead to logic errors. Conversely, direct modelers are not bound by previous operations which can offer more freedom to edit geometry in any order without historic logic errors. This makes direct modelers a popular choice for CAD software but, since dependencies are not maintained, they are not typically the natural choice for parametric analysis. If only there was a way to leverage the best of both worlds… Well, with ANSYS, there is a way.

As discussed in a previous blog post, since the release of ANSYS 18.1, ANSYS SpaceClaim Direct Modeler (SCDM) and the MCAD translator used to import geometry from third-party CAD tools are now packaged together. The post also covered a few simple procedures to import and prepare a solid model for electromagnetic analysis. However, this blog post will demonstrate how to define parameters in SCDM, directly link the model in SCDM to HFSS, and drive a parametric sweep from HFSS. This link unites the geometric flexibility of a direct modeler to the parametric flexibility of a history-based modeler.

You can download a copy of this model here to follow along. If you need access to SCDM, you can contact us at It’s also worth noting that the processes discussed throughout this article work the same for HFSS-IE, Q3D, and Maxwell designs as well.

[1] To begin, open ANSYS SpaceClaim and select File > Open to import the step file.

[2] Split the patch antenna and reference plane from the dielectric. Click here for steps to splitting geometry. Notice the objects can be renamed and colors can be changed under the Display tab.

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[1] Click and hold the center mouse button to rotate the model, zoom into the microstrip feed using the mouse scroll, then select the side of the trace.

[2] Rotate to the other side of the microstrip feed, hold the Ctrl key, and select the other side of the trace. Note the distance between the faces is shown as 3mm in the Status Bar at the bottom of the screen, which is the initial trace width.

[3] Select Design > Edit > Pull and select No merge under Options – Pull.

[4] Click the yellow arrow in the model, and drag the side of the trace. Notice how both faces move in or out to change the trace width. After releasing the mouse, a P will appear next to the measurement box. Click this P to create a parameter.

[5] Select the Groups panel under the Structure tree. Change “Group1” to “traceWidth” and reset the Ruler dimension to 0mm. Then, save the project as UWB_Patch_Antenna_PCB.scdoc and leave SCDM open.

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[1] Open ANSYS Electronics Desktop (AEDT), insert a new HFSS Design, and select the menu item Modeler > SpaceClaim Link > Connect to Active Session… Notice that there is an option to browse and open any SCDM project if the session is not currently active (or open).

[2] Select the active UWB_Patch_Antenna_PCB session and click Connect.

[3] The geometry from SCDM is automatically imported into HFSS.

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[1] Double-click the SpaceClaim1 model in the HFSS modeler tree and select the Parameters tab in the pop-up dialogue box. Notice the SCDM parameter can now be controlled within HFSS. Change the Value of traceWidth to SCDM_traceWidth to create a local variable and set SCDM_traceWidth equal to -1mm. Then click OK. Notice a lightning bolt over the SpaceClaim1 model to indicate changes have been made.

[2] Right-click SpaceClaim1 in the modeler tree and select Send Parameters and Generate.

[3] Notice how the HFSS geometry reflects the changes.

[4] Notice how the SCDM also reflects the changes. In practice, it is generally recommended to browse to unopen SCDM projects (rather than connecting to an active session) to avoid accidentally editing the same geometry in two places.

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At this point, not only can the geometry in SCDM be controlled by variables in HFSS, but a parametric analysis can now be performed on geometry within a direct modeler. The best of both worlds!

Use the typical steps within HFSS to setup a parametric sweep or optimization. When performing a parametric analysis, the geometry will automatically update the link between HFSS and SCDM, so step [2] above does not need to be performed manually. Be sure to follow the typical HFSS setup procedures such as assigning materials, defining ports and boundaries, and creating a solution setup before solving.

Here are some additional pro-tips:

  1. Create local variables in HFSS that can be used for both local and linked geometry. For example, create a variable in HFSS for traceWidth = 3mm (which was the previously noted width). Define SCDM_traceWidth = (traceWidth-3mm)/2. Now the port width can scale with the trace width.

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  1. Link to multiple SCDM projects. Either move and rotate parts as needed or create a separate coordinate system for each component. For example, link an SMA end connector to the same HFSS project to analyze both components. Notice that each component has variables and the substrate thickness changes both SCDM projects.

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  1. Design other objects in the native HFSS history-based modeler that are dependent on the SCDM design variables. For example, the void in an enclosure could be a function of SCDM_dielectricHeight. Notice that the enclosure void is dependent on the SCDM dielectric height.

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Getting to Know PADT: Simulation Services

This is the fourth installment in our review of all the different products and services PADT offers our customers. As we add more, they will be available here.  As always, if you have any questions don’t hesitate to reach out to or give us a call at 1-800-293-PADT.

The A in PADT actually stands for Analysis.  Back in 1994 when the company was started, computer modeling for mechanical engineering was called Analysis. It was such an important part of what we wanted to achieve that we put it in the name.  Unfortunately, Analysis was a bit to generic so the industry switched to Numerical Simulation, or simply simulation. In the 23 years since we started, analysis… sorry, simulation, has been not just a foundation for what PADT does for our customers, it has become a defacto tool in product development.  Through it all there has been a dedicated group here that is focused on providing the best simulation as a service to customers around the world.

Driving Designs with Simulation

Many companies know about PADT with regards to simulation because we are an ANSYS Elite Channel Partner – selling and supporting the entire suite of ANSYS simulation tools in the Southwestern US. The success of simulation in the design and development of physical products is a direct result of the fact that these fantastic tools from ANSYS can be used to drive the design of products.  This can be done in-house by companies designing the products, or outsourced to experts. And that is where PADT has come in for hundreds of customers around the world.  The expertise we use to support and train on ANSYS products derives directly from our real world experience providing CFD, structural, thermal, electromagnetic, and multiphysics simulations to help those customers drive their product development.

For those not familiar with simulation, or who only use the basic tools embedded in CAD software as a quick check, understanding why it is so important hinges on understand what it really is. Numerical Simulation is a methodology where a physical product is converted into a computer model that represents its physical behavior.  This behavior can be many different physics: stresses, vibration, fluid flow, temperature flow, high frequency electromagnetic radiation, sloshing of liquids, deformation during impact, piezoelectric response, heating from static electromagnetic waves, cooling from air flow. The list goes on and on. Pretty much anything you studied in physics can be modeled using a numerical simulation.

The process of doing the simulation consists of taking the physical object and breaking it into discrete chunks, often very small relative to the size of the object, so that equations can easily be written for each chunk that describes the physical behavior of that chunk relative to the chunks around it.  Imagine writing equations for the fluid flow in a complicated valve housing, very hard to do. But if you break it up into about one million small polyhedrons, you can write an equation for flow in and out of each polyhedron. These equations are then assembled into a giant matrix and solved using linear algebra.  That is why we need such large computers.  We mostly use the world’s leading software for this, from ANSYS, Inc.

More than Building and Running Models

Knowing how to build and run finite element and CFD models is key to providing simulation as a service. PADT’s team averages over 18 years of experience and few people come close to their knowledge on geometry preparation, meshing, setting up loads and boundary conditions, leveraging the advantages of each solver, and post processing. That is a good starting point. But what really sets PADT apart is the understanding of how the simulation fits into product development, and how the information gathered from simulation can and should be used.  Instead of providing a number or a plot, PADT’s experienced engineers deliver insight into the behavior of the products being simulated.

How each project is conducted is also something that customers keep coming back for.  Nothing is ever “thrown over the wall” our passed through a “black box.” From quote through delivery of final report, PADT’s engineers work closely with the customer’s engineers to understand requirements, get to the heart of what the customer is looking for, and deliver useful and actionable information.  And if you have your own in-house simulation team, we will work closely with them to help them understand what we did so they can add it to their capabilities. In fact, one of the most popular simulation services offered by PADT is automation of the simulation process with software tools written on top of ANSYS products.  This is a fantastic way to leverage PADT’s experience and knowledge to make your engineers more efficient and capable.

Unparalleled Breadth and Depth

Based on feedback from our customers, the other area where PADT really stands out is in the incredible breadth and depth of capability offered.  Whereas most service providers specialize in one type of simulation or a single industry, more than twenty years of delivering high-end simulation to evaluate hundreds of products has given PADT’s team a unique and special level of understanding and expertise. From fluid flow in aerospace cooling systems to electromagnetics for an antenna in a smart toy, a strong theoretical understanding is combined with knowledge about the software tools to apply the right approach to each unique problem.

No where is this breadth and depth exemplified than with PADT’s relationship with ANSYS, Inc. Since the company was founded, PADT engineers have worked closely with ANSYS development and product management to understand these powerful tools better and to offer their advice on how to make them better.  And each time ANSYS, Inc. develops or acquires a new capability, that same team steps up and digs deep into the functionality that has been added. And when necessary, adding new engineers to the team to offer our customers the same expert access to these new tools.


The best way to understand why hundreds of companies, many of them large corporations that are leaders in their industry, come to PADT from around the world for their simulation services needs is to talk to us about your simulation services needs. Regardless of the industry or the physics, our team is ready to help you drive your product development with simulation. Contact us now to start the discussion.


Video Tips – Two-way connection between Solidworks and ANSYS HFSS

This video will show you how you can set up a two-way connection between Solidworks and ANSYS HFSS so you can modify dimensions as you are iterating through designs from within HFSS itself. This prevents the need for creating several different CAD model iterations within Solidworks and allows a more seamless workflow.  Note that this process also works for the other ANSYS Electromagnetic tools such as ANSYS Maxwell.

Importing and Splitting Solid Models for ANSYS HFSS 18.0

Importing solid 3D Mechanical CAD (or MCAD) models into ANSYS HFSS has always been and remains to be a fairly simple process. After opening ANSYS Electronics Desktop and creating an HFSS design, from the menu bar, select Modeler > Import. A dialog box will open to navigate to and directly open the model.

The CAD will automatically be translated and loaded into the HFSS 3D Modeler. If the geometry is correct and does not require any editing, the import process is complete and analysis can begin! However, if there are any errors with the geometry, there is excessive or invalid detail, or if it’s not organized into separate bodies conducive for electromagnetic analysis, you may soon realize that the editing capability is limited to scaling, reorienting, or Boolean operations. This approach can be particularly troublesome when portions of the model (or all of the model) which consist of different materials are not split into different objects. For example, notice the outer conductor, inner conductor, and dielectric of the imported SMA below are all one solid object.

Unless you’re lucky enough to work with the creator of the CAD, you will need to find a way to split this model into the inner and outer conductors, and the dielectric. However, since the release of ANSYS R18.1, the power of SpaceClaim Direct Modeler (SCDM) and the MCAD translator will be packaged together. The good news is, the process described above will continue to work. The better news is, SCDM offers new capabilities to directly edit or clean imported geometry. So, here are a few simple steps to quickly split this SMA connector using SCDM. You can download a copy of this model here to follow along. If you need access to SCDM, you can contact us at It’s worth noting, at this point, that the processes discussed throughout this article work the same for HFSS-IE, Q3D, and Maxwell designs as well.

[1] First, after opening ANSYS SpaceClaim, the step file can be imported through the menu File > Open or by simply dragging and dropping the file into the SCDM window. [2] To separate the dielectric from the outer conductor, select Design > Intersect > Split Body. [3] Click and hold the center mouse button to rotate the model so the boundary between the dielectric and outer conductor is visible. Hold the Ctrl key and click the center mouse button to pan, and use the center mouse scroll to zoom in and out. Finally, press ‘z’ on the keyboard to fit the view window. [4] When positioned, click on the object to split (in this case it is the entire model). [5] Then, click on the face which defines the boundary between the dielectric and outer conductor. [6] Finally, press the Esc key. The first split is done!

Repeat the Split Body process to separate the center conductor from the dielectric. Notice under the structure tree that there are now three separate objects.

The split body function is also useful to simplify a structure for analysis. For example, the female side of the SMA could be simplified as a solid center conductor. [1] Reposition the connector to view the female side. [2]-[3] Control the visibility of each body with the object’s checkbox in the structure tree. [4] Measure the length of the female side by pressing the letter ‘e’ on the keyboard and selecting the top edge (note the line length of 2.95mm for later). [5] Then, repeat the Split Body process to split the center conductor at the boundary between the male and female sides. [6]-[7] However, rather than pressing the Esc key, click on the female receiver to automatically remove the body.

[1] To extend the center pin to its original length, select Design > Edit > Pull. [2] Click on the face where the female side was originally attached and select the Up To option. [3] Type in the previously measured length of 2.95mm. [4] Finally, press Enter (press Esc 3x to exit the Pull command).

Repeat the Split Body and Pull processes until the model has been divided into different bodies for each material type and is sufficiently simplified.

Once the model is ready, select File > Save As to save the geometry as the preferred format. Perhaps the most familiar approach to HFSS users would be to save the new model as a STEP file, then to import the model into HFSS as described in the first paragraph.

DesignCon 2017 Trends in Chip, Board, and System Design

Considered the “largest gathering of chip, board, and systems designers in the country,” with over 5,000 attendees this year and over 150 technical presentations and workshops, DesignCon exhibits state of the art trends in high-speed communications and semiconductor communities.

Here are the top 5 trends I noticed while attending DesignCon 2017:

1. Higher data rates and power efficiency.

This is of course a continuing trend and the most obvious. Still, I like to see this trend alive and well because I think this gets a bit trickier every year. Aiming towards 400 Gbps solutions, many vendors and papers were demonstrating 56 Gbps and 112 Gbps channels, with no less than 19 sessions with 56 Gbps or more in the title. While IC manufacturers continue to develop low-power chips, connector manufacturers are offering more vented housings as well as integrated sinks to address thermal challenges.

2. More conductor-based signaling.

PAM4 was everywhere on the exhibition floor and there were 11 sessions with PAM4 in the title. Shielded twinaxial cables was the predominant conductor-based technology such as Samtec’s Twinax Flyover and Molex’s BiPass.

A touted feature of twinax is the ability to route over components and free up PCB real estate (but there is still concern for enclosing the cabling). My DesignCon 2017 session, titled Replacing High-Speed Bottlenecks with PCB Superhighways, would also fall into this category. Instead of using twinax, I explored the idea of using rectangular waveguides (along with coax feeds), which you can read more about here. I also offered a modular concept that reflects similar routing and real estate advantages.

3. Less optical-based signaling.

Don’t get me wrong, optical-based signaling is still a strong solution for high-speed channels. Many of the twinax solutions are being designed to be compatible with fiber connections and, as Teledyne put it in their QPHY-56G-PAM4 option release at DesignCon, Optical Internetworking Forum (OIF) and IEEE are both rapidly standardizing PAM4-based interfaces. Still, the focus from the vendors was on lower cost conductor-based solutions. So, I think the question of when a full optical transition will be necessary still stands.
With that in mind, this trend is relative to what I saw only a couple years back. At DesignCon 2015, it looked as if the path forward was going to be fully embracing optical-based signaling. This year, I saw only one session on fiber and, as far as I could tell, none on photonic devices. That’s compared to DesignCon 2015 with at least 5 sessions on fiber and photonics, as well as a keynote session on silicon photonics from Intel Fellow Dr. Mario Paniccia.

4. More Physics-based Simulations.

As margins continue to shrink, the demand for accurate simulation grows. Dr. Zoltan Cendes, founder of Ansoft, shared the difficulties of electromagnetic simulation over the past 40+ years and how Ansoft (now ANSYS) has improved accuracy, simplified the simulation process, and significantly reduced simulation time. To my personal delight, he also had a rectangular waveguide in his presentation (and I think we were the only two). Dr. Cendes sees high-speed electrical design at a transition point, where engineers have been or will ultimately need to place physics-based simulations at the forefront of the design process, or as he put it, “turning signal integrity simulation inside out.” A closer look at Dr. Cendes’ keynote presentation can be found in DesignNews.

5. More Detailed IC Models.

This may or may not be a trend yet, but improving IC models (including improved data sheet details) was a popular topic among presenters and attendees alike; so if nothing else it was a trend of comradery. There were 12 sessions with IBIS-AMI in the title. In truth, I don’t typically attend these sessions, but since behavioral models (such as IBIS-AMI) impact everyone at DesignCon, this topic came up in several sessions that I did attend even though they weren’t focused on this topic. Perhaps with continued development of simulation solutions like ANSYS’ Chip-Package-System, Dr. Cende’s prediction will one day make a comprehensive physics-based design (to include IC models) a practical reality. Until then, I would like to share an interesting quote from George E. P. Box that was restated in one of the sessions: “Essentially all models are wrong, but some are useful.” I think this is good advice that I use for clarity in the moment and excitement for the future.

By the way, the visual notes shown above were created by Kelly Kingman from on the spot during presentations. As an engineer, I was blown away by this. I have a tendency to obsess over details but she somehow captured all of the critical points on the fly with great graphics that clearly relay the message. Amazing!

Exploring High-Frequency Electromagnetic Theory with ANSYS HFSS

I recently had the opportunity to present an interesting experimental research paper at DesignCon 2017, titled Replacing High-Speed Bottlenecks with PCB Superhighways. The motivation behind the research was to develop a new high-speed signaling system using rectangular waveguides, but the most exciting aspect for me personally was salvaging a (perhaps contentious) 70 year old first-principles electromagnetic model. While it took some time to really understand how to apply the mathematics to design, their application led to an exciting convergence of theory, simulation, and measurement.

One of the most critical aspects of the design was exciting the waveguide with a monopole probe antenna. Many different techniques have been developed to match the antenna impedance to the waveguide impedance at the desired frequency, as well as increase the bandwidth. Yet, all of them rely on assumptions and empirical measurement studies. Optimizing a design to nanometer precision empirically would be difficult at best and even if the answer was found it wouldn’t inherently reveal the physics. To solve this problem, we needed a first-principles model, a simulation tool that could quickly iterate designs accurately, and some measurements to validate the simulation methodology.

A rigorous first-principles model was developed by Robert Collin in 1960, but this solution has since been forgotten and replaced by simplified rules. Unfortunately, these simplified rules are unable to deliver an optimal design or offer any useful insight to the critical parameters. In fairness, Collin’s equations are difficult to implement in design and validating them with measurement would be tedious and expensive. Because of this, empirical measurements have been considered a faster and cheaper alternative. However, we wanted the best of both worlds… we wanted the best design, for the lowest cost, and we wanted the results quickly.

For this study, we used ANSYS HFSS to simulate our designs. Before exploring new designs, we first wanted to validate our simulation methodology by correlating results with available measurements. We were able to demonstrate a strong agreement between Collin’s theory, ANSYS HFSS simulation, and VNA measurement.

Red simulated S-parameters strongly correlated with blue measurements.

To perform a series of parametric studies, we swept thousands of antenna design iterations across a wide frequency range of 50 GHz for structures ranging from 50-100 guide wavelengths long. High-performance computing gave us the ability to solve return loss and insertion loss S-parameters within just a few minutes for each design iteration by distributing across 48 cores.

Sample Parametric Design Sweep

Finally, we used the lessons we learned from Collin’s equations and the parametric study to develop a new signaling system with probe antenna performance never before demonstrated. You can read the full DesignCon paper here. The outcome also pertains to RF applications in addition to potentially addressing Signal Integrity concerns for future high-speed communication channels.

Rules-of-thumb are important to fast and practical design, but their application can many times be limited. Competitive innovation demands we explore beyond these limitations but the only way to match the speed and accuracy of design rules is to use simulations capable of offering fast design exploration with the same reliability as measurement. ANSYS HFSS gave us the ability to, not only optimize our design, but also teach us about the physics that explain our design and allow us to accurately predict the behavior of new innovative designs.

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 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:


Autodyn Standalone:


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

Fluent Standalone (Fluent Launcher):


Icepak Standalone:


Polyflow Standalone:

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







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




Five Ways CoresOnDemand is Different than the Cloud

CoresOnDemand-Logo-120hIn a recent press release, PADT Inc. announced the launch of CoresOnDemand offers CUBE simulation clusters for customers’ ANSYS numerical simulation needs. The clusters are designed from the ground up for running ANSYS numerical simulation codes and are tested and proven to deliver performance results.



The current clusters available as part of the CoresOnDemand offering are:
1- CoresOnDemand – Paris:

80-Core Intel based cluster. Based on the Intel Xeon E5-2667 v.2 3.30GHz CPU’s, the cluster utilizes a 56Gbps InfiniBand Interconnect and is running a modified version of CentOS 6.6.


2- CoresOnDemand – Athena:

544-Core AMD based cluster. Based on the AMD Opteron 6380 2.50GHz CPU’s the cluster utilizes a 40Gbps InfiniBand Interconnect and is running a modified version of CentOS 6.6.


Five Key Differentiators

The things that make CoresOnDemand different than most other cloud computing providers are:

  1. CoresOnDemand is a non-traditional cloud. It is not an instance based cluster. There is no hypervisor or any virtualization layer. Users know what resources are assigned exclusively to them every time. No layers, no emulation, no delay and no surprises.
  2. CoresOnDemand utilizes all of the standard software designed to maximize the full use of hardware features and interconnect. There are no layers between the hardware and operating system.
  3. CoresOnDemand utilizes hardware that is purpose built and benchmarked to maximize performance of simulation tools instead of a general purpose server on caffeine.
  4. CoresOnDemand provides the ability to complete high performance runs on the compute specialized nodes and later performing post processing on a post-processing appropriate node.
  5. CoresOnDemand is a way to lease compute nodes completely and exclusively for the specified duration including software licenses, compute power and hardware interconnect.

CoresOnDemand is backed up by over 20 years of PADT Inc. experience and engineering know-how. Looking at the differentiating features of CoresOnDemand, it becomes apparent that the performance and flexibility of this solution are great advantages for addressing numerical simulation requirements of any type.

To learn more visit or fill out our request form.

Or contact our experts at or 480.813.4884 to schedule a demo or to discuss your requirements.


Three Jobs Open at PADT

3-Guys-PADTPADT currently has three job openings, two sales and one engineering.  If you are interested, or know of someone that is, please use the links below to learn more.

If you are smart, proactive, love technology, and believe in win-win interactions with customers, then PADT might be the place for you.

Electrical Engineer, High-Frequency Simulation: RF/Antenna
Account Manager: ANSYS Simulation Software
Account Manager, Flownex Sales