Superior usability and functionality of the Femap pre- and post-processor contributed to the improvement of computer-aided engineering competence. The company substantially increased the number of new analysis methods in its development projects and increased analysis skills in the entire group while reducing costs. Femap. Real [...]
The material handling machine manufacturer cut design time seven times with Solid Edge. Designers learned to use Solid Edge four times faster than their previous system and enabled engineers to solve design problems on site for customers. "Using Solid Edge is fun. It’s like a [...]
The next generation space telescope requires every part and assembly of every system be thoroughly tested. Visualization pinpoints potential flaws in components. Finding and fixing potential problems long before the telescope is launched is how NASA uses Femap. Real FEA made easy from Siemens PLM [...]
The social enterprise provides innovative, low-cost, low-maintenance solutions for people in the developing world. A low-cost pump, designed with Solid Edge, can cut irrigation time by 80 percent. The easy and intuitive to operate pump enables farmers in the developing world to exchange five hours [...]
The company develops diagnostic equipment such as clinical, chemical and hematology analyzers used in medical clinics, hospitals and veterinary facilities in more than 110 countries. Synchronous technology in Solid Edge is the cure for previous slow design process. The company reported 40 percent faster design [...]
Using sophisticated structural analysis, Cometal optimized weights and materials of its aluminum foundry machinery and minimized or eliminated the need for physical tests. The company also reduced costs and provided immediate feedback to designers and customers. Cometa accelerated its product development cycle with a single [...]
The fireplace manufacturer cut design time 85 percent and expanded product lines with Solid Edge. During the design phase, the fact that the fireplace is an important part of a living space must be taken into consideration, and it has to harmonize with the surrounding [...]
The food processing machine maker modifies product designs two times faster with synchronous technology compared with the traditional history-tree approach which requires editing a large complex set of features. The new approach also provides the ability to re-use existing design solutions and speeds production process. [...]
Radio telescope and astronomic instruments maker uses CAD-neutral finite element analysis to cut processing time 30 percent. ADS International significantly accelerated translation of 3D CAD models and reduced program costs while increasing benefits with Femap. Real FEA made easy from Siemens PLM Software. (Read on [...]
Alpha Omega designs better with Solid Edge. The advanced neurosurgery equipment maker uses Solid Edge to improve patients’s lives, including treatment for movement disorders such as Parkinson’s Disease. Innovations on a next-generation micro-electrode recording system helped shrink the instrument’s size and weight, making it easier [...]
This industrial oven manufacture creates new designs 7 times faster and handles design revisions 15- to 20-times faster with synchronous technology in Solid Edge. With Solid Edge;s synchronous technology, moving from 2D to 3D design became easier. “CAD based solely on history-based design confuses 2D [...]
Collaborating with architectural partners, Octatube simulates stresses and loads and meets build specification and compliance codes. It also helped employ unconventional building materials to obtain cost and aesthetic advantage using finite element analysis software Femap. Real FEA made easy from Siemens PLM Software. (Read on [...]
The bulk material handling machine manufacturer’s innovative ideas for handling dry bulk solids required a transition from 2D to 3D design software. . Today, the company uses almost every aspect of Solid Edge. For example, Hecht designers use the product’s synchronous technology for importing customer [...]
Precision surface machine manufacturer moved from 2D to 3D design and adopted synchronous technology, allowing it to respond more agilely to market requests. The move in 2001 from 2D to 3D was considered a major reason for the company’s success. The company’s adoption of synchronous [...]
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Our ADAS systems are here to assist us. But how do we test the systems that are supposed to help us not crashing into people? We crash into dummies!
Vehicle safety has become more important than ever; it’s crowded on the road and there’s too much place for human errors.
There are more than 1 billionautomotive vehicles operating worldwide
3,287 people are killed by crashes daily
More than 90% of all accidents is caused by driver error
Therefore, decreasing the human influence on driving can significantly reduce the number of casualties. Implementing advanced driver assistance systems (ADAS) is the first step towards achieving full autonomy (level 5), a situation in which the driver is no longer needed to operate the vehicle. Siemens is fully equipped to perform all sorts of ADAS tests.
Our dedicated ADAS team performs consumer tests for passenger vehicles (Euro NCAP testing for example) and for heavy vehicles such as trucks and buses (UNECE testing for example). Among other things, to make sure our vehicle does not crash into people.
What we do crash into
We are fully equipped with the latest test targets for AEB (autonomous emergency braking) tests. Autonomous emergency braking systems help us from not crashing into objects in two ways: they help avoid such situations by warning the driver and when there’s no response, they’ll break for you.
Our global vehicle target (GVT) is a controllable soft vehicle target that looks exactly like a passenger vehicle, but its body is built from lightweight foam so it is easy to reassemble in between test runs. It is controllable thanks to the GPS platform (accurate to 1 cm!), it can go up to 100 km/h and contains the same radar, lidar and visual attributes as a passenger vehicle. Therefore, it will be seen as such by the vehicle under test (vehicle under test is the naming for the vehicle that is being tested).
We use adult and child dummies, as well as adult bicyclist dummies for the vulnerable road users assessment. These dummies are also made from lightweight foam parts, so it’s easy to re-attach a leg in case of an unfortunate system failure. They’re designed with humanlike radar cross section, infrared and visual properties.
What we don’t crash into
Besides testing vulnerable road users and autonomous emergency braking systems, we are also fully equipped to test lane support systems (LSS) at the test facility in Aldenhoven, Germany. Here, we can perform LSS tests on real road edges.
As a valued Mechanical Analysis user, we would like to welcome you to the Simcenter Communities page!
This is an essential source of information where you can get the latest news directly from the horses’ mouth! Visit this page to find out any new information coming from our Simcenter products, you can also interact with us here directly as we are always keen to hear from our users about your experience with our software.
There are three vital areas that you cannot miss:
BLOG: This is where our product specialists will share new/exciting information that they think would interest you. Use the commenting area to give feedback on our blogs and start a conversation with us.
KNOWLEDGE BASE: Here you will find technical articles about our products so check here for any articles hot off the press!
FORUM: Use this area to post any ideas, questions or comments on any Simcenter products.
Have a browse around and join in our Community. We hope to hear from you, but we also hope this area provides you plenty of practical and constructive information. If you have any questions or suggestions for content on this site, please contact @JessicaFertier, @Venkata.
We are pleased to invite you to our unique webinar, in which we will present and illustrate our new state-of-the-art method.
Developing and validating autonomous vehicles is an unprecedented challenge that will turn simulation from a mean to optimize projects resources to a mandatory enabler.
An autonomous system reliability validation will often require at the least millions of test cases to be assessed, with numerous domains to be considered: sensors behavior, sensors fusion strategy, decisional artificial intelligence, lower level controls, drivers’ behavior, vehicle multi-physics, all this embedded in realistic environments and scenarios. The coming AD validation will require the combination of efficient ego vehicle sensors, controllers, AI and vehicle dynamics models with a tremendous amount of scenarios, while enabling CAE engineers understanding of the millions results generated, without analyzing them all. This also needs to be driven by requirements and linked to collaborative development assets repositories.
This year, Siemens PLM will launch its first generation ADAS and automated driving simulation framework. With this launch, Siemens PLM aims to provide a virtual validation and verification simulation framework gathering the needed domains while enabling scenarios, designs and massive results spaces exploration to pin down system failures root causes and validate autonomous systems.
The webinar will be presented by our Product Line Manager for ADAS and autonomous vehicles Enguerrand Prioux. During this webinar, we will provide more information about our new ADAS and automated driving validation and verification framework and demonstrate it.
Analysis is no longer the purview of highly trained experts. For more than a decade, engineers have been able to run simulations of the models they’ve designed. Now, their simulation systems include more capabilities and tools than ever. Engineers can mesh a model. They can apply boundary conditions and loads. They can solve for several physical forces acting on their model at the same time. They can take multiple types of physics into account.
While this new age of simulation has delivered numerous benefits to engineering teams, what if they could do more faster? What if engineers don’t need to start from scratch, building every model anew. What if they don’t need to “take it from the top,” as it were, each time they run a simulation? Perhaps they don’t need to start from a clean slate sheet every time when it comes to model creation and simulation.
A Treasure Trove of Past Analyses
Engineers at most manufacturers have already created models and simulations for many of the company’s parts and products. Those models are digitally stored--digitally warehoused by some means--within the manufacturer.
That’s particularly true for companies that work in highly regulated industries--like those in the pharmaceutical, medical device, and food packaging industries—and those must document due diligence with their designs. In many cases, these companies are required to save the models and simulations that demonstrate their products have met regulatory specifications. If in a worst case scenario, someone brings a lawsuit against the company, the models and simulations come immediately into play. They stand as proof that the product was safely designed.
Beyond proof of due diligence, these simulation models and results represent more. They embody a significant of work and, in some cases, best practices that have been carefully developed over years. Additionally, these completed simulations represent work that can be built upon. The results have been accepted and are shown to be superior to any other, earlier results. They’re the final product. They already exist.
Accelerating Simulation Processes
In all of these cases, there is little need to start every simulation from scratch. Rerunning an existing simulation is a valid case. Engineers can use these simulations to build new products. Existing simulations offer a shorter path to delivering results, representing a more efficient way to work than beginning with a clean slate. Why recreate the wheel when a simulation of the wheel, representing best practices, already exists? Grab that simulation and make it your own. Many times, you only need to make a slight change to the pre-existing simulation. Then it will be perfectly suited to your needs. You may need to tweak the geometry. You may need to apply and solve for a new load case, apply a boundary condition. You may need to tweak the finite element mesh.
Opening Legacy Simulation Models
Before a completed analysis can be reused, however, it must be accessed. In many cases, accessing a simulation is more complicated than simply opening a file. Older simulation models and results might be in old, proprietary, or depreciated formats. Too often, companies may no longer even own the simulation application that was used to build the analysis model.
In the aerospace industry, for example, certain parts continue to be manufactured for years. But their designs are slightly changed as time and needs change. These design can be updated with only a few changes to the existing model. But simulation application needs access to that original model no matter its format.
Companies may keep their models and simulations in the digital archives, but they’ve certainly updated their design and simulation technologies over the years. They’ve may have moved to an entirely different CAD system or updated their system numerous times throughout the years. They may have models stored that came from any number of suppliers provided in any number of formats. The simulation application must be able to open all of them.
In order to accelerate the simulation process through reuse, engineers need simulation tools that can open analysis models in a wide range of native or neutral formats.
Changing Legacy Simulation Models
Of course, your simulation application also has to let you make changes to an existing model. That may seem straightforward, but there are many functions it needs to allow for. It’s important you be able to modify the geometry of the existing model. You have to be able to change its mesh geometry or even to change the mesh itself. You need to be able to create and modify loads and boundary conditions as well.
Remember, no need to recreate the wheel. The wheel you’re looking for probably already exists. But it also probably won’t be exactly suited to your present-day needs. Some simulation applications let you find the wheel, modify it, and run the needed simulations. Ultimately, to get the most from reusing existing simulations, engineers need simulation tools that can not only open legacy analysis models but modify them as well.
Compared to starting from a clean slate, existing simulation models may offer a shorter path to delivering results. There are many scenarios in which a slight change to a pre-existing model is the only thing needed.
Simulation applications need to provide access to existing models and must allow engineers to make changes to them, like tweaking geometry or applying boundary conditions.
That is my take folks. Do you have experience in leveraging legacy simulation models? Sound off in the comments and share what you’ve found.
Siemens PLM provides a range of capabilities that directly address legacy simulation workflows. For more details on how FEMAP addresses these needs, download our complimentary eBook.
The development of the Samcef solver started in the 1960s at the University of Liege in Belgium and a spin-off company (called Samtech) was created to market Samcef. More than 50 years later, this finite element code is still using cutting-edge technology and can rival the biggest competitors on the market. Moreover, 100% of the development is still done in Liege. Now, with its integration in Nastran, as the nonlinear solution 402, and in Simcenter 3D, the future of our code is very promising.
The vast amount of functionality in Samcef is impressive, ranging from simple linear analysis to modal, nonlinear, rotor dynamic, response, spectral, fracture mechanics, advanced material models, parallel computation… I’ve had the opportunity to work in many areas and meet many experts, both colleagues and customers. This such a rich environment to work in.
This affected me greatly. I became a team leader and my role completely changed. I also started working on Nastran and interacted with our American and Chinese colleagues on a very regular basis. This is truly an international organization. Finally, Siemens brought a lot of perspective for the future.
Siemens is a leader in the field of computation software. Being part of the Siemens brand is highly appreciated by our (future) customers. This was a necessary step to ensure the future of Samcef.
Learning new technical skills from experienced colleagues, who were (and still are) passionate about their work.
Computer simulations are replacing a lot of physical tests and helping bring products to market much faster. With the advancement of computation power, the size and accuracy of the models is always increasing. This means that simulations deemed impossible few years ago have now become possible.
Learn to balance my roles of team leader and software developer.
I would like Samcef or Nastran SOL402 be a major player on the nonlinear market.
Automotive Testing Expo organization has started the final countdown to open the gates of the 2019 edition. Starting May 21, thousands and thousands of professionals will arrive to Stuttgart Messe to explore the latest innovations in the automotive testing field. So, what can you expect from this edition?
SimRod: The journey to the Digital Twin
Last year, we introduced you SimRod, the sporty electrical vehicle that was just about to start its journey to get a test-calibrated digital twin. (You can read the complete story of SimRod here.) Throughout past year, SimRod became a point of attention for many various teams across Simcenter. We spent hours and hours to do an extensive number of physical tests and simulations to achieve the complete digital twin of an existing product using one single platform. After one year, we’re so excited to bring SimRod to our booth again. But this time with a lot of new information. And more importantly, with a great experience of completing the digital twin experience.
SimRod Motion Model in Simcenter Testlab
The SimRod you will see at our booth will be shipped directly from our R&D department. Wondering what does it mean? To demonstrate the digital twin concept step-by-step, we’ll leave all the testing instrumentation on the SimRod, just the way we use it. Don’t expect a shiny sporty car with no scratched and no testing past. So come to the Siemens booth and explore the test setup detailly.
You will learn about the current innovations in data acquisition and post-processing for durability, NVH, ride and handling testing. Next to that, you can also get a good explanation of new emerging concepts like (component) TPA and Model-based system testing and how you can adopt these technologies into your framework. Also, as mentioned, SimRod is an electrical vehicle. It is a great illustration of the new acoustic approach for developing electrical vehicles. If you are interested in learning more about sound quality for electrical vehicles, then you should pass by the Siemens booth, or attend the seminar Latest innovations for electrical vehicle NVH testing.
Simcenter SimRod instrumentation
I agree, this is a lot of information and we’d like to tell you all this in person. Check out the time slots and add to your agenda when you can join a ‘Guided tour’ in different languages.
Siemens booth – Hall 8, booth 8224
Join us for two seminars:
Tuesday May 21 at 14:20 - Free-to-Attend Technology Demonstration Area
Parallel to the Automotive Testing Expo, the Autonomous Vehicle Technology Expo takes place just next doors. Also here, Siemens Simcenter will be present, showing solutions for design exploration, validation, verification and certification of autonomous vehicles. Through Digital Twin technology, from Chip to City, Siemens drives continuity throughout the supply chain of the automotive industry. Starting with a Mentor simulation and emulation offering for AV specific chip design, through Simcenter simulation and test solutions for embedded software and hardware, sensors and vehicles, up to infrastructure solutions for Vehicle-to-Infrastructure communication and fleet management solutions.
Solve the impossible. The hard ones are already solved
“This is impossible!”
said an inner voice to me, “it harms Navier-Stokes, it harms continuity, it harms third law of thermodynamics and god knows what else it harms! You cannot do this. It’s a trick! " It was the rational, all-negative-grumble in me that talked!
“Well, we’ll see, my friend!” the rebel-part in me responded and neglecting good old crabber for a moment I went upstairs to my office where the old books catch the dust.
Among those was an 800-paged brick of paper that was scary even if you just looked at it. It was still there from University times when it was a common practice among my mates and me to show-off talking about super-philosophic books we actually never read.
"You talked about books you never read? What a super-embarrassing and ridiculous nerd you were!”.
“Well, maybe”, I said to the crabber in me and took the book out of the shelf remembering it might help to
do “the weird thing”.
The beast was called
Gödel, Escher, Bach*
and the cool thing about the book I never read was that - though it - as far as I had heard - was a truly tough read, it had pictures in it. So, I started a deep dive image subtitle study and stumbled across some interesting hints:
The first guy mentioned in the book’s title – Gödel, an Austrian mathematician and philosopher - proved the following: Imagine a mathematical system with first principles aka axioms and the derivation of true sentences based on clearly defined mathematical rules: Now, luckily the author of the book makes it understandable for a poor-men’s mathematician like me: those axioms are the trunk of a tree and each derived sentence yields a branch, based on which further branches can be derived which then have further branches etc. pp. The genius proof of Gödel was that regardless how fine your re-branching becomes you will never be able to fill the complete space the tree is embedded into (in math words you end up with some fractal structure). Gödel was able to proof that those gaps between the branches leave the mathematical space for things that might be part of a holistic truth but are neither to be proven nor to be falsified from within the initial system of axioms.
“Hope Hofstaedter* or any other mathematician does not read this” the crabber went “he will probablythrow his hands up in horror reading that summary.”
“Why don’t you go downstairs and get me a coffee, I am explaining something here.”
So, another consequence of Goedel’s finding seems that if you start from the axioms and follow the rules of your system you might end up at the start of your journey.
“You mean like you in the old times doing those mathematical derivations and ending up back at 0 = 0 after pages of manipulations, instead of getting your homework done?”
“I said, go and get me a coffee!”
Now, comes the cool thing and this is what I was after: In Goedel, Escher, Bach there is a chapter about
one of the masterpieces of Escher, a dutch artist famous for his mathematically inspired woodcuts. This artworks visualizes the Goedel principle in a way that had always fascinated me: The water runs in circles and no matter how hard you try you don’t get it – Why the heck is that thing flowing “downwards” all the time? What’s wrong with the laws of gravity in that picture, where does Escher harm the Navier-Stokes Equation?
Well, you stare at it for a minute
“you are staring at this for an hour now!”
“What if I just ignore you for a bit…and by the way where's my coffee?”
and you start to understand Escher plays some tricks on you with the perspective. The arrangement of the columns somehow doesn’t make sense. The channels the water runs on somehow point downwards but effectively lead upwards. The fascinating thing is:
If you don’t change your view on the problem
and in this particular example it’s literally the viewing angle, you can spend ages
“see, like I said ages, not minutes…”
you can spend ages, staring at it and you somehow don’t get it ultimately.
you will be caught in a trap.
“you for sure”
You will be lost in a system of seemingly true axioms and sentences, but you will miss the ultimate truth outside that system. You will feel that everything runs smoothly following that water-stream step-by-step while you fail to realize that things run up the hill during some period.
Now you might wonder, why do I tell you all this philosophic crap in a Simulation blog
“I guess they all do! Get to the point… I told you it’s useless. It’s impossible!”
We are all facing the “Waterfall-trap”
It’s there all the time in our business models, in our private lives and…in our simulation workflows:
“Uuh, there comes the little philosophic, again”
Take Diesel gate.
For a long time the business model of selling Diesel powered cars as the clean holy-CO2-grail and trying to “somehow” get around the emissions topic worked out, everything was running well from a business perspective… it looks like nobody creating that model dared to look at it from another angle. Until, yeah, until somebody else rotated that scene from the outside.
Take our simulation workflows.
Anytime we build a model we make early decisions on the level of abstraction/simplification. Then we run our models and everything that comes out of those simulation is - convergence premissed - true within the system of initial axioms. It is a 100% consistent solution. But there is NO single guarantee, that it is the truth. “Take what’s fastest, it’s all wrong anyways, a colleague of mine once said.” Well, maybe that’s not 100 % true, but we should be clear: we interpret the results within the system of axioms we defined a priori. Needless to say, it is essential to challenge those early axioms by looking at our models from another – critical - angle. That’s when you go ask a colleague, that’s when you question your first results, and that’s when you ask the guy that delivers the ultimate truth...reality aka. Nature aka. measurement. We typically call this Validation! The successful (simulation) engineer always questions what he is doing. He always rotates the scene, he always validates, in particular when things seem to run too well.
And by the way, so should the experimentalist do. Just because an experiment always gives “the right” answer, it only gives the answer to the question that you defined a priori - by your experimental setup and care. The biggest waterfall trap in experiments is if you asked a different question than you believed you were asking. That’s the classical moment when the simulation engineer gets a different result than you as the experimentalist, because your geometry or operating condition or measurement location was not the one you thought it was when you handed over the results data. Which by the way was undoubtable the right answer from nature but, to another question than you thought.
But hobby-philosophy aside
“They’ll appreciate it!”
of course, there is a second more fun reason why I tell you all this in a simulation blog:
Escher’s Waterfall is made to be explored by CFD!
“Pahhh! I knew it, I knew that’s what you plan, you’re so naive”
So here I am standing now talking to my grumpy inner me as it’s the first time since university that I’ve taken Gödel, Escher, Bach out of the book shelf. I hold it in my hands and stare at the cover when I recall that another fascinating fact about the book I never read is that it has been composed such that the reader – as he starts from page one and works himself through the chapters- will seamlessly be brought back to the very beginning of the book as he finishes it. That moment I take the book and - not reading any further line - put it back into the shelf and with confidence I think to myself:
Many problems in engineering history have been said to be impossible to solve... until you just solve them.
All it takes is a bold plan, a change of perspective and the right toolset.
In Siemens we call this ingenuity for life, and here's a place where we live it with you
Join the Simcenter Conference 2019, Amsterdam, NL!
The geometry generator, WiseTex, produces so-called “idealized” unit cell structures (Figure 1 (left)). Such an approach accepts certain assumptions of, for example, a simplified shape of the yarn cross-section, its constant form along the yarn length or warp/weft yarns alignment [2, 3]. However, real-life structures are not perfect, which also applies to composites (Figure 1 (right)). Real composite materials are subjected to geometrical variability and possible defects introduced by the different phases of the manufacturing process .Figure 1: Examples of “idealized” (left) and real (right) composite geometries (a micro-CT image). The dashed rectangle indicates a defect in the composite specimen .
It is known that more reality (details) in the modeled geometry leads to a higher accuracy of the modelling prediction. Thus, the next R&D question is: how can the real geometry of composites be introduced in simulations? This blogpost will show a positive answer to this question: with the help of modern image processing techniques leading to the generation of materials models based on Micro-CT images. This is the topic of a VLAIO-funded postdoctoral research “Innovation Mandate” called “MicroCT-based Model Generation Engine for Virtual Material Characterization” between Siemens Industry Software NV and the Department of Materials Engineering (MTM), KU Leuven. The aim is to provide a new “VirtualCT” functionality to the VMC ToolKit that allows delivering more realistic composites models, by getting information (geometry, orientation) directly from pictures taken, and directly translating that information into models.
First, let’s take a look at the core imaging technique “Micro-CT” (or in full: “X-ray Micro-Computed Tomography”). What is this about? As shown in Figure 2 (left), the sample is placed on a rotation stage and radiated with X-rays. The rotation step θ is defined by the user. A detector acquires high-resolution “X-rays shadows of the sample” (called radiographs) at each rotation step. This process is similar to what radiologists perform on people in hospitals. Afterwards, a 3D volumetric image of the sample is created from the radiographs using a reconstruction software (Figure 2 (right)). Beyond medical applications, this technique is widely used in materials science. For composites, one should know that matrix and fibers usually absorb X-rays differently (except for carbon fiber-reinforced polymers; both matrix and fibers have a high carbon content), so there is the advantage that the general texture and layup of reinforced plastics can be observed in the micro-CT images (Figure 1 (right)).
Figure 2: Micro-CT (X-ray Micro-Computed Tomography): schematic view of the process  (left), 3D volumetric image of a PVC foam (courtesy of Department MTM, KU Leuven) (right).
The VirtualCT process of the Simcenter 3D VMC ToolKit illustrated in Figure 3 is applied on a woven composite material. First, the acquired micro-CT volumetric image of a composite sample is split into sub-volumes (voxels) and analyzed for material components (segmentation) and local fiber orientations using the micro-CT data analysis software “VoxTex” (courtesy of Department MTM, KU Leuven) . The obtained result is then imported into the Simcenter 3D simulation platform as a voxel rectilinear mesh with the evaluated material orientations using the VirtualCT tool. Afterwards, 2D or 3D periodic boundary conditions, tensile and shear loading cases are automatically created for the stiffness homogenization using the available functionalities of the Simcenter 3D VMC ToolKit. As a result, a material card with the elastic constants is automatically generated for the studied composite sample.Figure 3: Workflow “from micro-CT images to material properties” by example of a laminate manufactured from a 30˚-sheared woven organo sheet .
The potential of the Simcenter 3D VMC ToolKit for micro-CT-based stiffness homogenization for composite materials was illustrated in  by an example of thermoplastic woven organo sheets sheared to various angles: 15˚, 30˚, 45˚ and 60˚ (Figure 4, A). The goal of this study was to virtually assess the effect of shear on the composites performance (elastic constants). The sheared laminates were made of two consolidated plies of glass roving-PA6 (thermoplastic-based) organo sheets with a woven architecture (2×2 twill). The manufacturing process was defined and commissioned by inpro, Germany. One specimen for each laminate type was cut from the plates and scanned by XRE NV (now TESCAN XRE), Belgium using their UniTOM XL X-ray computed tomography system. Micro-CT images of the sheared laminates are presented in Figure 4, B. Afterwards, a set of high-fidelity micro-CT-based FE models was created using the VirtualCT tool in Simcenter 3D (Figure 4, C). The models captured the realistic variation of yarn orientation and the thickness of the produced laminates. The effective elastic properties were determined and compared with the existing results of tensile tests by inpro , which showed to be in a good agreement (Figure 4, D).Figure 4: X-ray computed tomography-based FE-homogenization of sheared organo sheets .
In summary, the Simcenter 3D VMC ToolKit does not only allow the creation of idealized models of composites, but it has been extended with a new functionality to build the realistic models of composites on modern image processing techniques. The new VirtualCT tool adopts the voxel-based approach by interfacing with the VoxTex software. The status of the work demonstrates the potential of the Simcenter 3D VMC ToolKit for stiffness homogenization for real composite materials starting from their micro-CT images. The presented modeling framework is applicable in a broader multi-physics context by combining the voxel models with FE-simulations of different disciplines for strength, damage, permeability, thermal etc. homogenizations.
The work on Virtual Material Characterization (VMC) leading to this publication has been funded by the twin projects SBO & IBO “M3Strength”, which fit in the MacroModelMat (M3) research program, coordinated by Siemens (Siemens PLM software, Belgium) and funded by SIM (Strategic Initiative Materials in Flanders) and VLAIO (Flemish government agency Flanders Innovation & Entrepreneurship). O. Shishkina thanks VLAIO for financing her work in the framework of the Innovation Mandate Project “MicroCT-based Model Generation Engine for Virtual Material Characterisation” (Grant no. HBC.2017.0189). The authors also thank inpro for providing the reference test data for the tensile properties of the organo sheets.
 L. Farkas, K. Vanclooster, H. Erdelyi, R.D.B. Sevenois, S.V. Lomov, T. Naito, Y. Urushiyama, W. Van Paepegem, Virtual material characterization process for composite materials: an industrial solution, in Proceedings of the 17th European Conference on Composite Materials (ECCM-17), Munich, Germany, 2016.
N. Isart, B. El Said, D.S. Ivanov, S.R. Hallett, J.A. Mayugo, N. Blanco, Internal geometric modelling of 3D woven composites: A comparison between different approaches, Compos. Struct. 132 (2015) 1219-1230.
S.V. Lomov, Modelling the geometry of textile reinforcements for composites: WiseTex, in: P. Boisse (Ed.), Composite Reinforcements for Optimum Performance, Elsevier, 2011, pp. 200-238.
A. Vanaerschot, F. Panerai, A. Cassell, S.V. Lomov, D. Vandepitte, N.N. Mansour, Stochastic characterisation methodology for 3-D textiles based on micro-tomography, Compos. Struct. 173 (2017) 44-52.
O. Shishkina, A. Matveeva, S. Wiedemann, K. Hoehne, M. Wevers, S. V. Lomov, L. Farkas. X-Ray computed tomography-based FE-homogenization of sheared organo sheets, Proceedings of the 18th European Conference on Composite Materials ECCM-18, Athens, 24-28 June 2018.
O. Shishkina. Experimental and modelling investigations of structure-property relationships in nano-reinforced cellular materials, PhD thesis, Department of Materials Engineering (MTM), KU Leuven, Leuven, Belgium, 2014.
I. Straumit, S.V. Lomov, M. Wevers. Quantification of the internal structure and automatic generation of voxel models of textile composites from X-ray computed tomography data. Compos. Part A Appl. Sci. Manuf. 54 (2015) 150-158.
Realize LIVE is less than a month away and we have an exciting agenda planned for the Simcenter track.
Here are some of the customer keynotes you can look forward to:
Tom Ramsay, Principal Engineer at Honda R&D Americas and Department Manager for the Vehicle Performance will talk about Realizing the Benefits of Aerodynamic Simulation in Automotive Development. He will share a number of examples of how simulation is applied and the lessons learned in the process.
Luis Velasco works for NASA’s Jet Propulsion Laboratory in Pasadena, CA and leads the Mechanical Design team for Cruise, Entry, Descent and Landing subsystems for the Mars 2020 mission. He will speak about the use of motion simulation along with Monte Carlo analysis to understand the conditions for ensuring rover landing safety.
Dan Mekker is Engineering Advisory Lead at Siemens Gas & Power. His session will cover a multi-year journey to migrate from various internal and external tools to the Siemens Simcenter suite including business challenges, the migration approach, joint work on strategic improvements to the CAE tools for turbomachinery.
Eric Keipper is Director for Vehicle Integration at Karma Automotive. His talk will focus on the Karma Revero GT and the partnership with Siemens for noise, vibration and harshness performance engineering to deliver a vehicle worthy of the tagline “Art that Moves You”.
These are just a handful of the many presentations that will be delivered at Realize LIVE. You can follow this link to see the full agenda and register for the conference.
Realize LIVE takes place Jun 10-13, 2019 at the Cobo Center in Detroit. We look forward to seeing you there!
Kettering University reduces undesired EV motor noise
In today's automotive industry, it is apparent that electric vehicles (EVs) are the future of mobility. Internal combustion is out. As a result, manufacturers are looking for better ways to develop and design electric engines. One might assume those conducting research on EVs to be looking for ways to enhance long distance performance; however, in this instance, the issue is less about optimizing travel and more about and enhancing comfort. In electric vehicles, high frequency noises from tires or electrical accessories become more prominent. As a result, Kettering Universities engineering students have been studying the causes of high-frequency vibrations within e-motors.
The study was divided into three parts: electromagnetic analysis, structural analysis, and acoustic analysis. Kettering's goal was to develop a cost-effective method for reducing noise caused by these vibrations. The engineers began by analyzing the sound generated by an electromagnetic model of a three-phase induction motor via simulation. To validate these simulation results, the engineers had to conduct an acoustic test on a small-scale general-purpose motor.
A Kettering University engineering student conducting a sound measurement on a general purpose motor.
Kettering's engineers utilized Simcenter Testlab during both the structural and acoustic analysis on the motor. The acoustic analysis assisted engineers in identifying frequencies at which sound pressure peaked and offered insight as to how these could be isolated. The test involved the creation of a spherical mesh with microphones around the motor. These microphones were placed approximately one meter from the motor (as seen in pink below).
Field Point Mesh (Microphones in Pink)
Eventually, an operational modal analysis visualized specific motor vibrations at certain points within the motor. It was found that frequencies were generating from within the motor's housing and its end brackets. The engineers found that by using modified end brackets, they could simplify the process of isolating frequencies that amplify perceived sound.
Operating Deflection Shapes of End Bracket
If successful, Kettering's study could provide electric motor manufacturers' a new way of reducing undesired motor noise without adding additional weight. For more information regarding how Kettering students and researchers are using Simcenter, click here.
Simcenter Prescan announces the release of version 2019.1. This release proudly announces the introduction of two new major Physics Based Sensors:
The Physics Based Camera based on the Unreal Gaming Engine
The Physics Based Radar model
In addition, a new ground truth sensor for real-time applications has been introduced and is called the Object List Provider. Improvements to Prescan’s world generation capabilities, new EuroNCAP 2020 scenarios and the Data Model API round up the list of exciting features for this new release.
Physics Based Camera (based on Unreal render engine)
A new Physics Based Camera based on the Unreal Engine is now available. This new Physics Based Camera sensor provides the following functionality:
Complete sensor & optics pipeline simulation
Fisheye camera simulation
Support for rain simulation
Improved performance (compared to original Physics Based Camera)
Additionally, the use of the Unreal gaming Engine provides the following advantages:
Improved motion blur
Improved grass models
A viewer based on the Unreal Engine is also now available as part of this release.
Physics Based Radar model
A new Physics Based Radar model is now officially released. This new Physics Based Radar model allows users to generate raw data output (e.g. ADC data) to help with the testing and development of signal processing algorithms, and new automotive radar systems. Validation of this new radar model has been performed with Tier 2 and Tier 1 manufacturers, ensuring that the simulation output matches very closely to measurements gathered in real life with radar sensors.
Object List Provider
The Object List Provider is a new ground truth sensor that provides complete information about all objects in an experiment. This sensor is ideal for experiments that require access to ground truth information and need to run in real-time or faster than real-time.
The information provided by the sensor includes the unique id, numerical id, object type id, origin, orientation, centre of gravity, centre of bounding box, bounding box size, and corners of the bounding box. The new sensor can be enabled in general settings and adds a new block to the compilation sheet with a single output port which outputs an array of buses (one bus for each detected object).
World modelling improvements
Simcenter Prescan continues to extend the OpenDRIVE support. In the current 2019.1 release the following OpenDRIVE 1.4H features are added to the supported items:
Constant Road shape
Additionally, the following sensors now work in conjunction with OpenDRIVE roads:
Lane line labels are visible with the Advances Lane Marker Sensor
Lane marker is now visible in the ISS in yellow
Data Model API
Simcenter Prescan announces the release of the MATLAB Data Model API 0.9. The Data Model API is a powerful scripting tool that allows for fast and reliable Test Automation as well as GUI-less operation of Prescan.
The MATLAB Data Model API 0.9 release showcases the capabilities of the Data Model API, that will be progressively improved in the subsequent releases, allowing full control of the experiment design, creation and execution via scripting.
Meshing has always been an important area for our customers. The pre- and post-processing application Samcef Field provided an extensive suite of tools to help users generate practically any required mesh for their simulations. Since Samcef Field was an integrated application, the meshing capabilities were seamlessly integrated into the model data and designed to support all types of particular meshing needs. Today, you find this in Simcenter 3D.
By combining 3D geometrical models and model data like boundary conditions, kinematic joints, drivers and controllers, Samcef Field automatically produced mesh models by combining various types of elements and integrating them into one mesh model that could cover all aspects of the simulation.
Siemens offers developers the chance to work on a very large and international team. There is almost an infinite amount of talent, so much experience and cultural diversity. You can learn a lot.
Siemens also offers a lot of diversity in regards to work and career opportunities, which gives everyone a chance to find a place to fulfill their career interests.
Something we quickly figured out at Siemens is that our work can have a significant impact on the industry.
Contributing to designing and creating a new product for simulating the 3D printing of components is an exciting challenge. I am having a lot of fun, while I leveraging and increasing my knowledge in the meshing field. 3D printing is a new and exciting domain.
As 3D printing ramps up in the industry, there is a higher and higher interest from our customers for reliable and automated simulation capabilities to predict the 3D printing behavior, reduce print failures, and assess the resulting quality.
With our new software solution, we provide the digital tools to accurately predict part distortion and printing failures, and we contribute to the development and adoption of 3D printing in various industries.
Working in a large organization like Siemens lets me learn new things every day. The in-house expertise is very high in many domains at Siemens. This allows me to learn about everything I need to know in my field and beyond – not to mention the many external training programs. I constantly learn from the expertise of my teammates, and in particular within my fields, meshing and additive manufacturing.
When we started working as part of a much bigger company, we had to find our way through a development organization that is designed to make hundreds of developers contribute to the same software suite. That was a long process, but it taught me a lot and was an exciting and rewarding journey.
We released the first version of the additive manufacturing simulation recently, and this field evolves rapidly. We will use the next years to improve our solution and offer a best-in-class product for the different aspects of 3D printing simulation, while continuing to strengthen the integration within the rest of our product portfolio. The meshing aspects will be critical and this will be my focus.
Do you want to include more physics and chemistry into your combustion system design process? The latest release of STAR-CD/es-ice/DARS, version 2019.1, is now available for download from our customer portal. Download them now and get access to a host of new features and enhancements including:
Use chemical mechanisms with thousands of species and get results overnight with the new optimizations and speed-ups in our detailed chemistry solver
Improve the prediction of evaporation and mixture formation in GDI engine simulations with our new flash boiling model
Get a better flow prediction in refined areas and in near-wall regions through the new Low Reynolds RNG K-Epsilon model with hybrid wall functions
Create laminar flame speed and flamelet libraries with mechanisms of any size quickly and efficiently using DARS
Please contact your in-cylinder Dedicated Support Engineer (DSE) for a full new features presentation covering all new features and improvements in STAR-CD/es-ice/DARS 2019.1, and stay tuned for more exciting in-cylinder capabilities coming in Simcenter STAR-CCM+ 2019.2 in June.
This year’s Simcenter Conference will focus on the “future of engineering,” and how engineers need to move beyond traditional simulation and embrace a future where multi-disciplinary engineering helps to create precise digital twins, that will help to drive the next generation of product innovation.
I attended both last year’s Simcenter Conferences (and before that annual STAR Conferences stretching back 25 years or more). Attending these conferences is always a “reality check” moment for me, and I am always staggered by how the use of simulation tools evolves from conference to conference. However, although technology evolves rapidly, ambition stays the same.
I always make a point of asking Simcenter customers about their "grand challenges," trying to understand what it is that keeps them up at night thinking: "if I could just _________, that would be a real game changer for my business!"
Regardless of which industry they come from, their answers are often quite similar: mostly they want bigger, more comprehensive simulations that account for more of the product they are trying to simulate.
You see, an uncomfortable truth about modern engineering is that there really are no easy problems left to solve. To meet the demands of industry, it's no longer good enough to do "a bit of CFD" or "some stress analysis." Complex industrial problems require solutions that span a multitude of physical phenomena, which often can only be solved using simulation techniques that cross several engineering disciplines. Simulations also need to be and validated using experiments test
What our customers are asking for is the ability to "see the big picture." Simulating whole systems rather than just individual components, taking account of all the factors that are likely to influence the performance of their product in its operational life. In short, to simulate the performance of their design in the context that it will be used. My point here is that our simulation tools, and the infrastructure that surrounds them, are now mature enough that we can begin to see the bigger picture and include more of the physical factors that will influence the real-world performance of a design.
Of course, I do not deny that our modeling ambitions are often constrained by a range of practical considerations. Although the principal concern is one of accuracy, modeling choices are often dictated as much by economic constraints as those of veracity of the prediction alone. Most modern engineers are acutely aware that, to influence the design process, simulation results need to be delivered on time, every-time. With access to limited simulation and computing resources, simulation engineers are often forced to ask, "How much of the problem can I afford to simulate?".
There are other constraints. Historically engineers have tended to align themselves strictly along disciplinary lines: the fluids guys do CFD, the stress guys do FEA, the chemical guys do all sorts of other stuff that no-one else understands. Getting individual engineers to talk to each other is as often as much of a challenge as interfacing the individual software tools.
It should also go without saying that including complexity for the sake of it is not "good engineering" either. Part of the art of engineering is in deciding exactly how much complexity can be excluded through modeling assumption, without reducing the overall quality of the prediction. In fact, at its purest, engineering might be described as the "art of simplification through modeling approximation," rendering intractable physics problems into neatly packaged engineering solutions. By making the correct modeling assumptions, you can accurately predict how an abstract design will perform under a range of real-world operating conditions. Make the wrong assumptions and your simulation results will either be a poor representation of the real-life performance of your design, or your model will be so complicated that you won't get any results at all.
At the Simcenter Conference, we will, with the aid of real-world examples, explore how Simcenter can help you to "see the big picture" by simulating entire systems rather than the individual components. We'll be talking about co-simulation and the many ways in which you can couple our software with other simulation tools and addressing the question of "modeling fidelity" by demonstrating how certain parts of the problem can be modeled at lower resolutions (in either space or time), without influencing the accuracy of the overall prediction. We'll also be discussing the economics of simulating large and complex systems and exploring how our licensing models allow you to exploit all your available computing resources in the most cost-effective manner.
For more information on how to register or present at the Simcenter Conference 2019, please visit: