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703, 2019

Why focusing on ICE thermal management to reach emission regulation targets?

“The European automotive industry invests more than €50 billion in R&D annually, a large percentage of which goes towards fuel-efficiency technologies, to meet EU CO2 emission reduction targets thereby complying with NOx and soot standards. However, very few are likely to be able to change the makeup of their fleets fast enough to meet the immediate challenge of the 2021 EU CO₂ emission reduction targets and avoid the significant fines for missing them.” Source: The CO₂ emissions challenge: some carmakers are running late in the race to 2021 -  PA Consulting reportCO2_emissions_reduction_status_vs_targets.jpgCO₂ emission reduction over time against 2017 actual data and 2021 targets

Consequently, to achieve future regulations OEMs and suppliers must innovate in their conventional powertrain design and at the same time come up with competitive alternative propulsion systems as soon as possible. Nevertheless, innovation in conventional powertrains in many instances implies an increase of technology complexity while alternative technologies imply an immediate need of removing uncertainty through rapid system development. Either way, ideally, what OEMs and suppliers would need is to equip themselves with the best engineering tools to accelerate the transformation.  That’s a challenge we at Siemens PLM Software accept: we provide a set of simulation solutions to make virtual design and evaluation of new innovative real.


One of the specific innovation areas where OEMs and suppliers can focus on is the thermal management of the internal engine combustion system. Optimizing thermal management of an aftertreatment systems is really a challenge. Indeed, for maximum efficiency (and so satisfying emission rate) aftertreatment systems such as catalysts require specific temperatures to operate efficiently. Using CFD simulation is a way to do a detailed thermal analysis and assess the best powertrain architecture.Engine thermal management analysis using Simcenter Star-CCM+.pngEngine thermal management analysis using Simcenter Star-CCM+

In the on-demand webinar “Optimizing thermal management in modern powertrains using CFD simulation”, Carlo Locci – simulation powertrain application specialist – showcases how using our CFD simulation tool Simcenter STAR-CCM+ can support the thermal management modeling of your engine, and introduces:

  • An innovative technique to predict the thermal interaction between the fluid film and the wall in an SCR. This technique was developed to allow for long transient runs in a Selective Catalytic Reduction (SCR),
  • The most recent developments in this field of Conjugate Heat Transfer (CHT) related to Powertrain problems,
  • Perspectives on heat production modeling for fuel cells.

If you are eager to know more about our whole Simcenter portfolio for powertrain applications, Warren Seeley Simcenter Director of Powertrain gives an overview in the introduction of this online presence.

Register here to access the online webinar: Optimizing thermal management in modern powertrains using CFD simulation 


More information on our website:

Engineer innovation with CFD- focused Multiphysics simulation webpage

703, 2019

STAR-CCM+ v12.04: Two mouse clicks? Hold that thought!

Please note: Original publication date 06-29-2017 


Just one numerical simulation contains a wealth of information – we can gain a lot of insight on how a device performs, and from that, we can infer how to make that device better. To confidently recommend one design over another, though, we’ll need to run more than one simulation. As our device knowledge is informed through simulation, we can expect to make numerous geometry/part modifications to the original design. How quickly we can turn these changes around will determine how many simulations we can run within our time budget. Without a highly efficient and flexible workflow, we might find ourselves in the position of being less certain of our final product recommendation. Risky. Now, you’ll be hearing a lot soon about Design Manager, a native capability within STAR-CCM+ v12.04® to do design exploration – that’s not this story. Instead, I want to share how just two mouse clicks can now get you quickly from that first simulation to the next one, and to the one after that and the one after that...


First, some history. In STAR-CCM+ v9.04, we introduced logic based “Filters”. For example, you could create a Filter to return all the geometry parts that contain the name “chip”. Using your Filter to make your part selection in an Operation saves you the trouble of having to find and select all of these objects in the simulation tree manually. Faster. Less error-prone. Repeatable. Good.


But, if you were to then add another “chip” geometry part, you had to go back to your Operation, re-apply your Filter and update your selection. In other words, the part selection wasn’t dynamic. To address this, we delivered "Query-Based Selection" in STAR-CCM+ v10.06. Automatable. Better. But still limited in coverage to just Operations, Displayers and Derived parts. Why is this limiting? Because Regions were statically linked to parts, so if you added, modified or removed parts, you would need to update your part selection for your region manually.


This is now a thing of the past. In STAR-CCM+ v12.04 , we’ve extended Query-Based Selection to apply to Regions, Boundaries, Sub-Groups, Interfaces and Reports. Faster. Less error-prone. Repeatable. Automatable. Better still.


To show how this can help you, let’s consider the simulation of a packed bed reactor for dry reformation of methane to produce hydrogen gas. These reactors contain randomly packed solid catalyst particles which can be various shapes and sizes:


catalyst_particle_shapes_updated.pngExamples of catalyst particles used in packed bed reactors.

Our operating conditions may be fixed to a narrow range, so if we want to improve our reactor performance, the choice of particle size, shape and number is going to be critical. Let’s consider our workflow starting point to be a simulation (with the solution cleared) in which the physics continua (fluid and solid), regions, boundaries, interfaces, reports, scenes and displayers have already been set up. Lets say we want to replace an existing packed bed containing cylindrical shaped particles with seven wedge shaped holes in each (above at far left), with a new packed bed containing smaller tri-lobe shaped particles (above at far right). We’ve got four Query-Based Selections in play that we will use to assign…


  1. …any geometry part with a name containing “__particle” to a Unite operation (this was possible in previous versions).
  2. …the Geometry Part generated by the Unite Operation to the solid particle Region.
  3. …all Part Surfaces containing the name “__particle” to a Region Boundary defined in the fluid region and another defined in the solid Region (the same dynamic query is used for both regions).
  4. … all Part Surface Contacts (created when the Volume Extract Operation is run) to Interfaces.

two_click_workflow.pngUse four Query-Based Selections to automate your two mouse click workflow.

Now, with your .sim file set up this way, when you hit the Generate Volume Mesh button on the toolbar, our first of our two mouse clicks, the Mesh Operations pipeline is executed. What you end up with is a .sim file, meshed and ready to go – all Parts to Region assignments are automatically done. The second of our two mouse clicks, hitting the Run button, is almost anticlimactic in comparison. Your simulation starts running and any derived parts, reports and scene displayers that also use Query-Based Selection get automatically updated.


unrolled_view_mole_fraction_H2.pngA cylinder derived part (intersecting the packed bed near the reactor wall) is unrolled to compare hydrogen gas production rates between the two packed bed designs.

data_focus_filter_for_site_blockage.pngData Focus highlights areas of higher (in color) compared to lower (grey) catalyst site blockage.

To get the workflow down to two clicks did take some preparation and the methodology does rely on a part naming convention. When does it make sense to go through the extra steps?  If we want to examine just 3 different particle sizes for each particle shape pictured above, that’s 21 different random packed bed geometries; 21 .sim files that can be consistently set up and run; 21 sets of reports and plots and scenes that can be consistently compared in an automated fashion. And, if that isn’t enough of a reason, there are two great new features in STAR-CCM+ v12.04, Replace Assemblies and 3D-CAD Part Synchronization, that also leverage the benefits of Query-Based Selection. The bottom line is this: Some initial preparation to set up your simulation template is the logic based choice. 

703, 2019

The Digitalization of Industrial Machinery



Providing realistic virtual simulation 

Throughout the computer-aided engineering (CAE) design process, engineers must balance a variety of critical performance aspects to validate whether the product under development will work as intended. This complex task cannot be based on a test-and-repair approach. Such an approach would lead to expensive iterations on physical hardware. Other unique projects require that the first prototype is the final product. Testing these kinds of products under extreme boundary conditions can have dramatic consequences. 


As a result, Siemens PLM Software solutions provides engineers with the necessary tools to conduct upfront analysis for a variety of applications during the design process. To be successful, machine manufacturers must use models to reproduce the complex behavior within the operational environment. Engineers require pinpoint accuracy to understand how structures work and expedite the analysis of new designs for potential modifications that optimize performance.


The right solution for any nonlinear application 

Computation of accurate dynamic loads in structural analysis often requires the consideration of nonlinear behaviors. Simcenter Samcef nonlinear motion analysis fully exploits the augmented Lagrangian method and the large-displacement-large-rotation approach to deliver this capability. The software features an extended library of flexible kinematic joints that can be included in FEA. By coupling these joints to super elements and beams, the complete kinematics and dynamics of the system can be simulated.


When combined with Simcenter Samcef nonlinear structural analysis, nonlinear and fully meshed components can be included to capture material and geometrical nonlinear structural behavior. Furthermore, Simcenter Samcef can be used to integrate sensors, actuators, and controllers in the simulation. These can be imported from Matlab®/ Simulink® and Simcenter Amesim™ software or preprogrammed in Simcenter Samcef. In that case, the control parameters can be optimized. Simcenter Samcef can also be coupled to Matlab and Simcenter Amesim for co-simulation. This co-simulation capability is done through a dedicated module that enables coupling between different transient solvers. This mechanism is used to connect Simcenter Samcef to the AMRC tool (a research center linked to the University of Sheffield) that provides the cutting forces of the machines.


Twin-Control Project 

Twin-Control is a European project (H2020, grant agreement nº 680725) aimed to develop new concepts for machine tools and machining process performance simulation. It is coordinated by IK4-TEKNIKER in Spain, with additional partners Renault, COMAU, MASA, Gepro Systems, ModuleWorks, Artis, Predict, TU Darmstadt, University of Sheffield and Samtech, a Siemens Company, in Liège, Belgium.  


In the Twin-Control project, Siemens focuses on the dynamic modeling of machine tools, including its Computer Numeric Control (CNC), and its interaction with the machining process. To properly simulate modern high-speed tools, which show close interactions between the dynamic behavior of the mechanical structure, drives, and the CNC, it is crucial to build models that represent the flexibility of all components and interactions. 


Simcenter Samcef Mecano enables accurate modeling of machines by considering FEA modeled components connected by a set of flexible kinematic joints. Models are implemented to deal with drive-trains and motor dynamics. To fully capture the dynamic behavior of the machine tool, force interactions between the cutting tool and the workpiece are also considered in the models. These forces consider the dynamics of the tooltip, combined with the tool work-piece engagement determined by Module Works CAD/CAM for toolpath generation and simulation.


As seen in figure 1, a model of the CNC is connected to the machine model by specialized elements that compute motor forces from controller inputs, calling a dynamic library embedding the Matlab Simulink model of this controller. 


Figure.pngFigure 1: Coupling scheme

To properly model the machine tools when operating, the following objectives are followed: 

  • Properly account for flexibility of all structural components, connections and feed drive to obtain a model that can represent interior vibrations. The guiding system is modeled by flexible slider elements, which constrain a node to move along a deformable trajectory represented by beam elements. 
  • Limit the number of degrees of freedom (DOF) as much as possible to use the model in the time domain (small time step imposed by the machining simulation module and the controller model). This is done by using a super-element technique. The model contains super-element techniques and can represent the desired levels of vibrations.

The proposed technology is applied to build a flexible multibody mechatronic model of a box-in-box fast machine of project partner COMAU, as seen in Figure 2. This approach provides comprehensive simulation capabilities for virtual machine prototyping in working conditions. 


Photo 2.pngFigure 2: A Multibody model of the COMAU machine tool. Courtesy of Comau.

Another example that illustrates this technology is the 5 axes machine from project partner Gepro Systems (shown in Figure 3).

Photo 3.pngFigure 3: A Multibody model of a five axes machine tool with multiple spindles. Courtesy Gepro Systems

An industrial CNC controls the motors of the axes to follow the desired trajectories with minimal error. In the model, all frames are fully flexible, as the rails and screw drivetrains, which are represented by a set of slider elements. The control loops are modeled in MATLAB/Simulink, translated into a dynamic library associated with specific control elements to manage the coupling between 1D models and flexible 3D models.


The resulting Twin-Control simulation package is dedicated to both machine tool builders for design activities and machine tool users looking to improve their processes. In both cases, this virtual model will avoid performing costly physical. Simcenter Samcef, coupled with the different modules from our partners, allows building this virtual model in the form of a fully flexible and nonlinear finite element based digital twin.

703, 2019

Blinded by the Obvious

We can all be blinded by the obvious. The number of Dilbert cartoons on the topic is great evidence for how often it happens to all of us.




This has been on my mind lately because of a recent experience. About a year ago, my family finally had our kitchen renovated. When we first saw the house before buying it many years ago, I distinctly remember walking in and saying “well, we will need to renovate the kitchen.” But then time slips by and priorities shift. Soon the kitchen that so clearly needed renovating just became our kitchen. Our brains so quickly and easily plaster over the imperfections around us that those imperfections disappear from our perception.


On the last day in our old kitchen before renovations started, we took a picture of everyone crammed into the one corner that always seemed to be where everything in the kitchen was located. I found that picture the other day and was struck by what I saw. Was it really that small, that dingy? I found myself slightly embarrassed that we had happily hosted guests for so many years with a kitchen that looked like that!


This ability to tune things out that continually bombard us is often rather useful. Just think, that ability allowed me to happily live with a kitchen that desperately needed an update for many years. Imagine how draining it would be to wake up every day and have all the imperfections be as obvious as the day we first toured the home. However, there is also danger in not stopping to reevaluate. It’s possible to go on so long without reevaluation that our perception becomes entirely detached from reality.


As simulation engineers, we are especially at risk in this regard. One of the most important aspects of what we do is to determine what is important, what should be included into a model being developed and what can be neglected. Even worse, we must balance the amount of personal and computational effort required to capture a certain piece of physics. We may deem it important, but not so important that we are willing to invest in modeling the phenomenon.


One perfect example is the process that goes into designing and modeling a gas turbine such as those used for powering aircraft or generating electricity. These are massive machines that start with tens-of-rows of compressor blades working to create massive amounts of high-pressure air. That air is then mixed with fuel and ignited, producing gasses at even higher pressures and temperatures. All that work is done so that the high-pressure and temperature gasses can rotate turbine blades to extract mechanical energy. The gasses driving those turbine blades are so hot that cold air is pumped through complex internal passageways of the blades and out over their surface just to keep them from being damaged.


To simulate a system this complex, the level of physics appropriate for a model depends on how far along the design process we are. For example, when coming up with the right shape for those turbine blades so that they extract the most energy possible, those complex internal passages are usually not included. Conversely, when determining how to most efficiently cool those blades, it is necessary to include that complex internal detail. However, it’s not always so easy to decide what can safely be neglected.


Simcenter STAR-CCM+ is particularly strong for modeling complex cases. Modeling conjugate heat transfer, complex geometry, combustion chemistry and unsteady blade-passing effects are some of the common types of analysis done by our gas turbine simulation users.  A streamlined workflow gives unmatched ability to accurately mesh the most complex geometry features while enabling the simulation of complex physics such as combustion, conjugate heat transfer and unsteady flows.


Multi-timescale simulation capabilities are now available in Simcenter STAR-CCM+, making it a good time to stop and re-evaluate the tradeoffs being made in our gas turbine simulations. Mixing plane interfaces allow us to model just a single blade passage in each row, which keeps the computational cost down. However, these heavily cooled blades produce distinct cold wakes that wash over the next row of blades downstream.



Ignoring the impact of these localized, unsteady wakes on blade temperature prediction is common. Until now, many have decided that capturing that effect would require too high a computational cost and so mixing planes have become the standard. At one point, the decision was made to ignore blade-passing effects and deal with the decreased accuracy of the simulation. Now it is an assumption made so often that most are blind to it, not recognizing that there are other options available.


Simcenter STAR-CCM+ has been a pioneer in developing harmonic balance simulation capabilities for gas turbine engine simulation for many years. The harmonic balance method allows the unsteady blade-passing effects in the fluid to be modeled at a much lower computational cost than traditional time-domain unsteady simulation. The method takes advantage of the periodic nature of the unsteadiness in the fluid to formulate a much more efficient simulation method.


With Simcenter STAR-CCM+ 2019.1, it is now possible to use the harmonic balance solver on the fluid side to capture the unsteady blade-passing effects and the steady solver on the solid side, all within the same simulation. This decoupling of the fluid and solid timescales makes efficient use of computational resources while more accurately representing the physical system. With this time-scale decoupling, it is no longer necessary to assume that the flow-field is steady and to neglect the impact of localized wakes when performing conjugate heat transfer simulations.


Simcenter STAR-CCM+ will continue to push the boundaries of what is possible with simulation, tackling the most complex cases, and timescale decoupling is evidence of that progress.


In addition to taking on the most complex gas turbine simulation needs, a new initiative has begun for gas turbine simulation with Simcenter STAR-CCM+ that is focused on improving gas turbine simulation for all levels of complexity. Each phase of the design and simulation process have unique challenges. Early in the cycle, flow and thermal predictions must be extremely fast and reliable and provide automatic reporting on the performance of a candidate blade. Later additional geometric and physics complexities are added, and more blade-rows of the machine are simulated simultaneously. Late in the cycle, very large simulations are performed once the design is nearing maturity. Many new capabilities are being brought into Simcenter STAR-CCM+ to help address the unique challenges of gas turbine simulation at each of these design phases. Interaction with design tools, specialized meshing and gas turbine specific post-processing are all on the way. Additionally, with unrivaled abilities to simulate the complex, it will become much easier to mature a given model with additional details as a design progresses.


It’s an exciting time for gas turbine simulation. With so many new capabilities, it may be time to reevaluate assumptions and look for blind spots.




703, 2019

Optimizing the design of engine actuation systems using system simulation

“Through model-based development with OEM, we [at Denso] contribute to more advanced powertrain development” Masashi Hayashi - Digital engineering expert for powertrain components design and simulation at Denso Corporation.


Developing advanced and innovative powertrain is a complex challenge to meet increasing fuel economy and emission standards. Suppliers and OEM need to work together to accelerate the development of their new vehicle. Interaction and the use of a common methodology such as model-based development adopting a common system simulation platform can be a way to achieve in short lead-time development and innovation targets.


Siemens PLM with Simcenter Amesim enables the collaboration between suppliers and OEM, with IP protection and encryption. The advantage on both sides from model sharing is the reciprocal understanding of challenges and benefits. By joining the on-demand webinar “Optimizing the design of engine actuation systems using system simulation” learn how the supplier Denso and the expert Masashi Hayashi analyze an ICE actuation system performances based on OEM requirements using Simcenter Amesim, and assess the benefits from each side.


Application case:

How Denso optimize hydraulic Variable Camshaft Timing (VCT) design based on performance specification from OEM?

Masashi Hayashi focuses on the development of hydraulic Variable Camshaft Timing (VCT) using system simulation. The challenge in optimizing hydraulic VCT systems design is to improve engine performance, reduce emissions and increase fuel efficiency compared to engine with fixed camshaft.


There are 2 characteristics to be fulfilled and optimized: the VCT speed and stability, in various working conditions (low/high power generation) – based on OEMs requests. Using Simcenter Amesim, the Simcenter system simulation solution, allows validating the correct VCT architecture to satisfy both phase speed and stability.


The additional target for Denso as an engine actuator supplier is to use existing legacy/core design data in the simulation model for more design reliability. By watching the webinar discover how Denso simulation reaches the results accuracy allowing to confirm their VCT model design, based on OEM requirements.


By watching the webinar discover how Denso simulation reach the results accuracy allowing to confirm their VCT model design, based on OEM requirements.


You are eager to know more about other combustion engine actuation systems that you could optimize using Simcenter Amesim? Francesca Furno, our hydraulics expert shows how system simulation easily helps you to tune and improve fuel systems, valvetrains, engine mechanical systems and airpath and exhaust systems and finally the overall vehicle performance. Go deeper into details by watching the live demonstration about Variable Compression Ratio System optimization with Simcenter Amesim at the end of that webinar.

Actuations_system_optimization_webinar.pngSimcenter Amesim for engine acutation systems optimization

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603, 2019

The Trends Driving Modular Plant Design

puzzle piee.jpgLet’s face it: designing and building a processing plant is an old school industry.

It has one foot firmly in the construction industry. It involves building a large scale structure. It traditionally involves a site where the structure is built up for months. It is a lot like building a commercial building. It has the other foot, however, firmly in manufacturing. Processing plants must support operations that often require high precision production. Ultimately, it falls into neither category — it kind of falls into both.

In recent years, there’s been a new trend with processing plants: modular design. What’s going on? Why is this trend gaining traction? What do companies hope to get out of it? We’ll touch on all those questions here. However, note that I’ll be speaking on a webinar on this exact topic in a couple of weeks. If this is a relevant topic, you might want to join us.

With all that context, let’s dive in.

Offsite Construction, Increased Precision, Standard Interfaces

There are numerous reasons why companies are increasingly adopting a modular plant design. One of those reasons deals with the plant construction process.  A construction site presents many variables that are difficult to predict when designing a processing plant. That results in many change orders that slow down the construction process. Those are delays that many can ill afford.

Instead, some companies are building sections of a plant, sets of equipment, and other machinery offsite. This work takes place in a manufacturing environment where the environment varies less than a construction site. As a result, there are fewer change orders. Construction and assembly of these systems happen far faster. The contractor transports those items to the construction site and incorporates them into the site.

For engineering, this implies some changes to the design process.  Engineers must clearly understand which aspects of the processing plant the construction plan. Changes to the design process include planning what is assembled off-site and what is constructed on site. Changes also must include detailing the interface of the modular system and the plant.

Notably, the need for greater precision with modules also speaks to a critical technological need. Such modules need high precision definitions. Mechanical CAD is the best fit for this work as opposed to Building Information Management (BIM) solutions. The latter lacks the fidelity to model these modules accurately.

Modularity: More Options, Fewer Systems

A different, but just as important, trend driving the adoption of modular plant design lies in customer demands in product complexity. Every plant is unique. However, designing every single aspect of a plant from scratch every single time is a failing strategy. There is too much work to do in too little time. Instead, many companies designing processing plants aim to reuse prior work. Tweaking and modifying prior work, however, is extremely challenging.

Instead of merely trying to tweak prior design work, some companies are transitioning to a modular platform. In this effort, engineers develop modules that fulfill particular functions. Engineers then mix and match those modules to plan unique combinations, fulfilling the unique needs of a specific processing plant. The result is a platform composed of all those modules. Such a platform won't cover the need of every single plant. However, if it reduces unique engineering work from 70% to 20%, that is a significant improvement for the company.

There are unexpected benefits to a modular strategy. For one, it is far faster to configure the design of a plant from a platform. This configuration path to plant design means costing, pricing, and quoting teams can respond faster to bid requests. Furthermore, configuring the design of a plant translates to less engineering work per project, translating to the need for less expertise. That makes the whole company easier to staff and fewer overworked engineers.

This type of effort, however, doesn't happen with a snap of the fingers. It takes some meticulous planning to identify where variability is needed and where standard functionality is needed. The process to define the modules, the functionality each provides and building out the entire platform can take a little bit of time. Some key technologies can help, however. Requirements management as well as the ability to allocate requirements to designs, such as modules, goes a long way towards automating the management of functions within the platform.


The plant design and construction industry is an old school one. However, many companies are injecting a bit of innovation into the processes by adopting modular approaches. Some do it as a way to enable prefabrication work off-site. Others do it to increase variability for their customers while increasing reuse.  In both cases, new technological capabilities are needed to enable change.

Sound like a topic that's relevant for you and your company? Well, there's a lot more to cover on this topic, ranging from more details on off-site construction to processes to define modular platforms to what enabling technologies are most crucial. I'll be talking to these issues, and more, during a webinar on  March 20th. Join us for a good discussion.

2702, 2019

Reverse Engineering Tutorial in Solid Edge Part 2 – Deep Dive

...continued from part 1


Step 6 - Extracting Treatment Feature Data


The intention of the reverse engineering process is to extract a high-level overall form of the object and it is not recommended to extract treatment features like holes, rounds, chamfers, etc.


The following video shows various techniques to extract measurements or sizes of the treatment features present in the mesh model for use in Solid Edge:



Step 7 – Reverse Engineering Best Practices


The video below shows with examples a couple of best practices to be followed in the reverse engineering process in Solid Edge:



Step 8 – Mesh Repair and Direct Mesh Modeling


Finally, the following video shows how you can perform modeling operations directly on a mesh model without having to extract surfaces or create a design body first.


Also, the video shows how to delete a portion of the imported mesh body and heal mesh regions manually by filling in holes and gaps.



Tushar Suradkar



2402, 2019

From the TODAY show: A high schooler (and Solid Edge) help an injured veteran get moving again

How did a high school student, an engineering class and Solid Edge change the life of a Marine veteran? Check out the story of Ashley Kimbel, featured on the TODAY show (a major US morning news and talk show) this morning. Ashley is a 17-year-old high school senior from Alabama with an interest in biomedical engineering, who put her skills to good use when she met Kendall Bane, a Marine and leg amputee.


Ashley, who had been introduced to Solid Edge through the Greenpower program, used the software to design and build a lightweight prosthetic foot to help Kendall again enjoy his favorite outdoor activities.


Check out the replay of Ashley and Kendall on the Today Show here.



What a great example of how software can enable users like Ashley to push the boundaries of what is humanly possible—and change lives.


Watch the full video of Ashley’s story here!

2402, 2019

Join Solid Edge at Realize LIVE in Detroit

As many of you have heard by now, PLM Connection will be a bit different this year. Far from just a rebranding, however, the Realize LIVE event offers more value for users. Join us for the Solid Edge Connection featuring four full days of more than 30 sessions that span best practices and helpful tips to the future of Solid Edge and what’s to come. Be the first to learn about Solid Edge 2020 during the event, which takes place June 10-13 at the Cobo Center in Detroit, Michigan, home to the International Auto Show.  Realize LIVE Detroit is our flagship user event and will be followed by dozens of one-day Solid Edge University events globally. Stay tuned for more details.




Don’t miss the early-bird pricing available until March 17. For Solid Edge customers, we have an extra special deal…

Solid Edge customers can receive additional special savings with a limited time offer. Use the following promo codes for two ways to save:

  • EDGE342 - 3 admission tickets for the price of 2
  • EDGE300 - a single registration discount of $300

These are in very limited supply and will be honored on a first come, first served basis. They are flat discounts, so you save the most if you register during the early-bird pricing. The discounts will remain good until they run out, however.


The event kicks off Monday, June 10 with an exciting announcement from VP of Development for Mainstream Engineering, Dan Staples. He’ll be sharing Solid Edge 2020 and its many benefits with you for the first time! You won’t want to miss this chance to be among the first to see and experience the latest technology he will unveil.


One of the best benefits of these types of events is the opportunity they offer for you to connect with other expert users, including many of the members of the Solid Edge team, and to learn. An exhibition space with Siemens and our partners gives you a chance to talk one-on-one and learn more about the solutions offered. Throughout the event, you’ll hear from a number of users in a variety of industries on how they use Solid Edge to solve their difficult design challenges and achieve maximum efficiency from the software. Melissa Schultz  will host a session on “Learn Synchronous and Optimize the Use of Existing Features.” As she is an expert synchronous user, you could not be in better hands to learn more on that topic.  Scott Wertel  will present “Prioritizing Your Product Requirements with Solid Edge,” a very important topic for any designer to know. Scott is well-experienced in design and has great insights to offer.


The best way of learning, of course, is through hands-on experience. You’ll have the opportunity to attend eight hands-on sessions during the course of the four-day event. Tushar Suradkar   will host a hands-on session on reverse engineering, a topic of growing important in today’s design world. He will also share a joint session with our own Mark Thompson   on Mechanical Design Tips & Tricks. He is renowned in the user community for his knowledge of Solid Edge techniques, so those sessions are sure to be helpful. Professional development and other workshops will be offered at the close of each day to help you build your skillset further. Among the topics that will be covered are manufacturing, large assembly modeling, wiring and harness design and more.


As a native Detroiter, I feel I must also speak to all of the fun activities outside the actual event that you will have the opportunity to enjoy. Detroit tends to get a bad rap as a city, but it has so much to offer. From the legendary architecture of the Guardian Building (a National Historic Landmark in the US) to the delicious cuisine and brews at any number of restaurants you’ll find throughout, to the birthplace of the Ford Model T at the Piquette Plant and so much more, there is something for everyone. Your days will be long and filled with learning and networking, but I highly encourage you to explore the area in your free time! Take one of your newly made (or longtime) Solid Edge friends along with you 😊 and if you need a recommendation of where to go, I’m sure myself, John Gaioni  , or any other locals would be happy to help, so don’t be shy.  


Register for the Solid Edge Connection at Realize LIVE by March 17 to receive early-bird pricing. Solid Edge customers can receive additional special savings with a limited time offer. Use the following promo codes for two ways to save:

  • EDGE342 - 3 admission tickets for the price of 2
  • EDGE300 - a single registration discount of $300

These are in very limited supply and will be honored on a first come, first served basis. They are flat discounts, so you get the biggest bang for your buck with savings if you register during the early-bird pricing. The discounts will remain good until they run out, however. Act fast and register today! We hope to see you there.

2002, 2019

Reverse Engineering Tutorial Part 1 – Get Your Feet Wet

A few weeks back an article on reverse engineering appeared in the community blog and got a great response, followed by another inquiry on the forum about a beginner tutorial on this topic.


This tutorial shows just one of the many ways in which scanned data in the form of a mesh can be converted into a Solid Edge model.


The reverse engineering process can typically be accomplished in the following 5 steps:

  1. Import and optimize the mesh.
  2. Identify regions based on various boundary representation type.
  3. Extract surfaces based on the identified regions.
  4. Post-process the surfaces to make them fit for body creation.
  5. Combine the surfaces to create the final Solid Edge model.


This process is illustrated in the following infographic with the Solid Edge commands involved at each step.




Ball01.png  Import and Optimize the Mesh


  1. Download the BearingBlock.STL file.
  2. In Solid Edge press Ctrl+O.
  3. In the File Open dialog, select STL documents from the drop-down list at the bottom.
  4. Select the downloaded STL file.
  5. Click the Options… button.
  6. Check ON the boxes for the base feature and heal mesh.




  1. Select the ISO metric part template.
  2. When the model loads, change the view style to wireframe.
  3. Note there are no regular faces.



Ball0P.png  A Quick Primer


A mesh body is made up of triangular polygons, called facets. Each facet has three vertices and three edges.



The facets of a mesh can be collected into faces. These faces are similar to the faces in Solid Edge BREP bodies, except that mesh faces do not have a geometric description.


For example, two or more facets of a mesh can make up a rectangle, but that face is defined simply as a collection of facets, not as a rectangle with a height and width.


  1. Back to the mesh model open in Solid Edge
  2. Note the blue i symbol in the Pathfinder and read its tooltip.



The Optimize command mentioned can be found on the ribbon bar - Reverse Engineering tab.


  1. Start the Optimize command, which selects the model automatically.
  2. Right-click to finish.
  3. Close the report dialog if it appears.


This finishes the first of five steps in the reverse engineering process in which you imported the mesh model by opting to create a base feature - a part copy and to heal any faults in the mesh. After this, you optimized the imported model, though I am not sure how relevant this command is for an imported mesh.


Later in this tutorial, you will see an example of using the Optimize command to simplify curves and surfaces.


Ball02.png  Identify Regions


This can be done either manually or automatically. The Manual command is shown in the video below which also illustrates some tips about rectifying mistakes while painting facets.



It is clear from the video that Solid Edge designated colors should be used for each type of face. Here’s the full list of the color codes:



These colors are in fact used by Solid Edge internally to identify regions in the Automatic command.

Open the BearingBlock.STL (if you have already downloaded) file one more time and try out the Automatic  REBLAT08.pngcommand which produces the results as seen below which are not quite as expected, perhaps because this is not really a scanned model, but in fact, I have saved out a Solid Edge regular model to an STL and shared for this beginner tutorial.



Close this file without saving and continue with the one that has regions identified manually as per the steps in the video.


This finishes the second step in the process of building a solid model from an imported mesh.


Ball03.png  Extract Surfaces


The steps involved are shown in this 45 seconds video:



TipIcon.png Note: Instead of the manual method using the Fit command, you can also use the Extract command which produces the same surfaces - automatically.


In both cases, lots of surfaces are generated and in some other cases additionally, spherical, conical and BSpline surfaces are generated too. If you want to toggle the display of these surfaces based on the type, here’s a free macro that does this in a jiffy:




dnicon.png  Download the macro from this page.


This finishes the third step of the reverse engineering workflow discussed in this beginner tutorial.


Ball04.png  Post-Processing


The extracted surfaces leave a large gap between them at several places as you would have noticed and these need to be closed by extending them.


Another important operation is adding tangent ‘face’ relationship at a couple of places where the top cylindrical face connects the planar faces, since they have all been created from different mesh facets, independent of each other, and may not be actually tangent.


The video below shows all the steps involved.



TipIcon.png Note: If you want to skip this laborious process, download this Solid Edge 2019 part file with the surfaces extended.


TipIcon.png Tip: You can still use the part to cross-check the edges which need to be extended by hovering the mouse cursor over each Extend feature in the Pathfinder.


This completes the fourth step in the process.


Ball05.png  Combine


The Intersect method is used to combine the surfaces to create several distinct bodies which can be further combined automatically by setting an option in the same command as seen in the short video below:


The ‘Create design bodies’ option is perhaps new to Solid Edge 2019, but I am not sure about this.



This finishes the core reverse engineering workflow.


The next part of this tutorial shows:

  • Several techniques to extract the holes and the rounds from the mesh model.
  • Best practices for reverse engineering with Solid Edge.
  • How to perform modeling operations directly on the mesh model.


Go to Part 2…


Tushar Suradkar





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