With this version, we accelerate the software delivery model to provide access to new enhancements every 6 months, while maintaining focus on the technical excellence.
The latest release helps you build digital twins faster and earlier in the design cycle by democratizing access to system simulation. By further extending Modelica® support and integration with other Simcenter solutions, version 2019.1 enables you to set up a unique toolchain throughout various development phases and teams.
Among many other enhancements, new capabilities in Simcenter Amesim 2019.1 focus on the 4 main areas:
aircraft systems performance engineering,
system simulation efficiency and ease of use.
Find out top 10 functionalities in 3 minutes:
Let us walk you through the major new capabilities in these 4 areas.
#1 Vehicle electrification
Simcenter Motorsolve model import
Simcenter Battery Design Studio import for equivalent circuit battery models
Ready-to-use air cooled battery pack demonstrators
Many industries, such as automotive, aerospace, off-highway and marine, are making the shift toward e-mobility. After introducing the capability to import from Simcenter SPEED in the previous release, the latest Simcenter Amesim version reinforces its integration with other Simcenter solutions that support electrification challenges.
Using the same app for linear and nonlinear variants, you can import permanent magnet synchronous motor (PMSM) parameters from Simcenter Motorsolve to test your machine in the vehicle context earlier in the design cycle.
Moreover, battery equivalent circuit models from Simcenter Battery Design Studio can be imported into Simcenter Amesim 2019.1 to obtain a shared battery model. You can visualize parameters of the imported model before using them in Simcenter Amesim. For more details, read this article.
New demonstrators allow you to easily re-use the complete battery pack model based on geometry, identify critical temperatures for controls design, apply a documented methodology for model reduction as well as integrate the reduced battery model into your vehicle energy management analysis.
#2 Aircraft systems performance engineering
Upgraded CAD import capabilities for fuel systems
Enhanced postprocessing apps and scaling tool for aircraft engine and gas turbine
New rotorcraft engine demonstrators with the recuperated cycle and series hybrid variant
To support the aerospace industry, the latest release of Simcenter Amesim comes with upgradedCAD importcapabilities that enable users to easily create rib submodels and generate all the required tank and rib data files. Therefore, you can drastically reduce the time required for creating data files and organizing your output files. Moreover, the new rib submodel allows users to account for flowing areas, speeding up parameterization while improving accuracy.
By using the enhanced postprocessing apps and scalingtool when exploring new gas turbine configurations, users can easily derive scaled performance maps starting from reference maps and looking at the surge margin.
Users can benefit from two rotorcraft engine demonstrators that are derived from a validated engine model. The first derivative is a recuperated engine cycle and the second is a series hybrid variant assessed during an oil and gas mission.
#3 Controls engineering
Extracting a nested signal bus
New tool for proportional–integral–derivative (PID) controller calibration
New real-time components for thermal and valvetrain systems
With the industry shift towards connected, software-intensive, complex products, Simcenter Amesim 2019.1 offers a large set of new or enhanced capabilities for controls design and validation to enable you to simultaneously optimize the mechanics, electronics and software as an integrated system.
You can now use signal buses to manage data transfers between physical subsystems. This redesigned capability facilitates visualization of all data flowing through any given bus component and simplifies information propagation across nested buses.
In addition, the latest release comes with a new tool for PID controller calibration, which is associated with two demos for speed and position control. Hence, you can visualize closed-loop step response and check the robustness with stability margins.
Whether you are a system designer who just wants to quickly make the PID controller work, or a control expert interested in stability margins, find out the step-by-step process in this article.
Additionally, new real-time components of thermal and valvetrain systems will allow you to greatly reduce CPU time and run hardware-in-the-loop (HiL) simulations.
#4 System simulation efficiency and ease of use
New Modelica compiler and full Modelica Standard Library (MSL) v3.2.2 support
Model conversion from hydraulic to thermal-hydraulic domain
Two-phase flow thermodynamic cycle analysis app
To boost the efficiency of your system simulation activities, Simcenter Amesim now offers you full MSL 3.2.2 support and greater openness thanks to Modelon’s compiler, which is integrated into this Simcenter Amesim version. You can easily couple Modelica and native Simcenter Amesim library components: Using Modelica Editor enables you to automatically import Modelica models into Simcenter Amesim and get the best of both.
Moreover, existing hydraulic models can be converted into thermal-hydraulic models with one click while maintaining model structure and parameters.
With a new app for two-phase flow thermodynamic cycle predesign, within just a few seconds you can assess steadystate cycle performance by adapting your design points from predefined cycles. Watch how this app works in the demo here.
Finally, the latest improvements in valve builder functionality allow users to create pilot-operated directional valves and connect them to the hydraulic or pneumatic pilot stage, as well as integrate nonreturn valves into the design of your directional valve to avoid unnecessary volumes and dynamics.
Humans have used fire for thousands of years. From cooking meat to make it easier to eat and digest, to firing pottery to make watertight containers, to managing grass or moorlands through controlled burning, fire has been a vital tool for many aspects of human existence. These days, combustion is used in many industrial processes. These may be less visible to the general public, but are essential to produce materials and products used by everyone on a daily basis. Coal burners, dryers and kilns, and steel furnaces are just some of the areas where high temperature processes and combustion are used.
Today, process engineers must ensure these high temperature processes are as efficient as possible: inefficient processes lead to costly and excessive energy consumption, with the potential of excess emissions and non-optimal product yields. The use of Computational Fluid Dynamics (CFD) to virtually investigate high temperature processes is now an established design tool in many industries, including the process industry, but are you using it to its full potential?
This on-demand webinar takes a look at recent advances in simulation capabilities in Simcenter STAR-CCM+, which make simulation and optimization of combustion processes even easier. Our technical experts will cover:
Recent advances in CAD maneuverability for geometry setup
Different reaction modeling approaches available in Simcenter STAR-CCM+
Combining CFD and design space optimization for intelligent geometry optimization
Successful use of simulation is enabling process engineers to reduce design costs and create innovative, efficient designs. Join us to learn more, and discover how CFD can help to optimize your high temperature processes.
There’s no doubt about it: simulation is delivering value in product development.
Some are avoiding multiple rounds of prototypes. Some are reducing the cost of goods in products. Some are making designs both lighter and stronger simultaneously. Some are coming up with more innovative designs that work functionally. Overall, many companies are reaping the benefits of applying simulation early and throughout the design cycle. And if there are any issues with simulation, it’s that managers seem to want more.
So how can an engineering team get more productivity out of their analysis tools? One clear answer is automation. It removes repetitive tasks from users hands, allowing them to concentrate on the value-added aspect of simulation. It also promotes standard best practices across a company. Here are some capabilities that do just that.
One of the most simple, yet valuable, ways to automate a simulation process is to leverage macros.
The idea is straightforward. A user can record a sequence of user interface interactions, such as selecting menu options or entering values. This sequence of actions is then mapped to a trigger, often a specific combination of keyboard keys or mouse buttons. Then, whenever the users want to initiate that sequence of actions, they simply hit the trigger.
This approach provides the most value when applying repeated actions within the same model. It reduces repetitive work for the user. However, it also eliminates any potential human error likely to occur in a heavily repeated action. Furthermore, executing macros happens very quickly, far faster than the sequence of actions could be executed by hand. Lastly, macros are an opportunity to apply analysis standards across a company.
In all, macros allow users to avoid repetitive work, reduce human error, accelerate their simulation processes, and distribute analysis standards.
Where macros automate repetitive tasks within a simulation model, analysis templates automate entire sets of tasks by offering an accelerated starting point.
Analysis model templates include standards that should be included in all simulations of that type. For some cases, a template might include a parametric model of a pump that has already been meshed to the correct level of detail. For other cases, a template might include standard loading cases based on data collected from physical tests. For yet others, a template might encompass all of the standard materials and their properties that are officially approved by a company.
Templates, however, do not just apply to entire models. Loads and boundary conditions can be applied as templates. Solver selections, method selections, and their corresponding parameters might be included in a template.
The value in templates is also straightforward. Templates simply allow users to avoid creating everything from scratch. They start their process several steps farther than a clean sheet. But just as importantly, templates are another way to distribute best and standard practices within a company.
A different kind of automation builds on top of templates. Simulation workflows apply the concept of workflows to simulation.
The idea here is that each analysis template requires several inputs to be run. Once those are provided, the simulation can be solved, producing a number of outputs. With simulation workflows, the outputs from one analysis is fed as inputs to another analysis. This chain of simulations can be used to connect disparate types of engineering physics that are interrelated. For example, a fluids dynamics analysis of a wing would yield loads that are then passed on to a structural analysis of the internal stringers. In another example, a complex combustion analysis of a turbine engine would pass temperature fields to a structural analysis of a turbine blade.
Such simulation workflows can be used to automate very complicated analyses, but they can also provide guidance to novice users as well. They simply ask for standard inputs and produce standard outputs that can be interpreted.
The value here is more advanced than in other cases. Expert users can automate an entire complex simulation process. Novice users get guidance on how to complete a range of analyses, ranging from the simplest to incredibly complex. Both use cases deliver value.
The last, but not least important, means of automating simulation is through application extensions.
Here, a company will build out new functionality by coding software extensions to an analysis application. This is done using an Application Programming Interface (API) toolkit, which often is an externally available version of the code used to build the analysis application by the software provider.
This toolkit can be used to build brand new functionality on top of the solution. This functionality can dramatically automate simulation processes and procedures. It can add completely new interfaces such as dialog boxes and menus. It can tweak or modify how the application prepares models and passes them to solvers.
The toolkit can also be used to integrate with specialized homegrown simulation tools. Doing so allows data and other information to be passed back and forth between the applications. This is applicable when the company is dealing with custom calculations, ranging in complexity from programmed spreadsheets to their own internal software.
The value here is strong. Companies that seeking new ways to automate the simulation process has an opportunity to build it the way they want with the API. Companies with custom applications for specialize calculations can wrap their work into the simulation software.
Companies that are looking to get more value out of simulation can look to automation, which comes in a variety of flavors.
Macros allow users to record and then execute a sequence of actions through a trigger. This is of value to users repeatedly applying the same actions within an analysis model.
Templates allow users to accelerate their simulation process, applying and reusing prior analysis work.
Simulation workflows stitch the output of one analysis to the input of another, enabling the automation of several interconnected simulations.
Application extensions add new capabilities to existing tools by coding with the software’s API toolkit. This is an opportunity for automation or integration with a company’s custom analysis application.
Automation can provide a lot of additional value to companies already leveraging analysis. What has your experience been with simulation automation? Let me know your thoughts in the comments.
Siemens PLM provides a range of capabilities that directly address automation of modern simulation processes. For more details on how FEMAP addresses these needs, download our complimentary eBook.
The question of the day is – would you buy an electric vehicle (EV) today?
Maybe. Although, during the upcoming years, you are more likely to answer: “Yes!”. Let’s face it. Avere, the European association for electromobility, estimates that there are already 1 265 441 passenger electricity powered cars driving around the Europe, using 161 426 public charging points. And both numbers will increase in near future. Countries world-wide are introducing the mobility visions promoting and supporting electric cars (e.g. Electromobility in Germany: Vision 2020 and Beyond,etc.). According to Bloomberg New Energy Finance, 55% of all new car sales and 33% of the global fleet will be electric by 2040.
Electric car development hits bumps in the road
However, there are also some important bottlenecks that cause reluctance to switch to electric cars. One of the most important is the driving range of the electric vehicles. The EV development teams strive to reduce the vehicle weight to increase the driving range. But reducing weight of the vehicle chassis and body is not given! Finding the optimal balance between vehicle weight and performance attributes, such as durability, NVH, ride and handling, becomes more important than ever. Yes, you need to increase the driving range, but on the cost of reduced durability performance that could lead to earlier vehicle damage. Also, reducing vehicle weight can deteriorate handling performance. It means your vehicle may lose stability when performing certain driving maneuvers.
Here is another engineering dilemma - how do you balance the vehicle body stiffness while keeping up with the right NVH characteristics? At Siemens Simcenter, we recognize these challenges and we aim to provide our customers with solutions for different vehicle development teams to tackle all these problems and help to find optimal lightweight vehicle conditions without loss in performance. What are the other electrical cars development shifts?
Electric vehicle noise in the spotlight
The trend towards electrical vehicles poses both challenges as well as opportunities for car developers. The absence of the internal combustion engine (ICE) changes the signature of the interior cabin noise dramatically. The most obvious game changer is the fact, that the withdrawal of the traditional powertrain unveils the other noise contributors or make them more audible and prominent. In 2011, G. Goetchius (Leading the Charge – The Future of Electric Vehicle Noise Control, Sound & Vibration) estimated the noise contributors in ICE vehicles and predicted the noise morphology in the electrical ones. According this publication back then, in the traditional ICE vehicles, the biggest noise contributor is the powertrain followed by the road, wind and ancillary system noise. While in electrical vehicles, the road noise and wind are the most dominant noises. And what’s more, the new structure reveals noises that were originally masked by the combustion engine (such as ancillary system - whine gears, steering rack, air conditioning system, wipers, ABS module, pumps etc.).
EV vs ICE vehicles NVH challenges
Without any surprises, the structural changes in electric vehicle noise will need new engineering approaches to optimize the NVH performance with appealing sound quality. Here are three strategies you should focus on to make the ride in your electrical vehicle to sound as a symphony.
Act on the present noise source
Firstly, you may need to find the noise root cause and act on it. Depending of the origin of the noise source, different NVH analysis techniques are required. Reducing wind noise, for instance, happens most effectively in wind tunnels. These allow to effectively isolate the wind noise from other noise sources and find the most effective measures to reduce this annoying source. However, as these tests are extremely costly, it is crucial to test with extremely efficient measurement techniques. The use of industrialized testing processes based on large beamforming arrays that allow identification of the exterior noise sources, and use this data to decide what to test next, becomes more and more a reference.
Road noise needs to be handled with effective and reliable techniques, such as transfer path analysis (TPA). This technique allows to pinpoint the noise critical paths on the chassis and car body contributing to the interior noise. To be able to handle the complexity and closely spaces loads of suspension systems, more advanced techniques such as strain-based TPA becomes another necessary building block.
For other auxiliaries, the key information can be provided by wide toolset of NVH tests and analysis techniques. And again, for many of these subsystems the traditional transfer path analysis (TPA) can help to identify the component or structure causing the noise issue. Acting on the noise source, however, does not always provide solutions early enough. In case it is not too late in the vehicle development cycle, the responsible team can proceed with component design adaptations and improvements. But in real life, there are situations, when design adaptations are impossible or cause conflict with other attributes (such as weight, durability, etc.). Or often, the results of the TPA leads to pragmatic and expensive additions of damping and trimming to the vehicle. The disadvantage is that damping material increases the vehicle weight - which will directly reduce the vehicle range, add extra cost and prolong the vehicle assembly. What’s more, this strategy is limited and doesn’t offer an optimal solution in all the cases.
Master the electric vehicle sound quality including active sounds
There is good news. The shifted noise structure of the electric vehicle brings an option to add new noises. This opens an opportunity to create new and pleasant driving experience for your customers. From this perspective, sound quality engineering is the key tool to develop high-performing sounds within the vehicle. This technology is currently gaining ground in the automotive industry. It all starts with the acquisition of realistic sound data, including for instance binaural recording. Secondly, to be able to analyze the acquired sounds, you can proceed with audio replay, using different filtering and analysis through different sound quality metrics. And finally, you shall organize a Jury testing, which is based on subjective audio perception. Sound quality engineering combines objective analysis metrics with subjective analysis. This strategy will provide you with detailed insights to find answers to questions like – what do the customers like to hear? What sounds do they prefer in different corners of the world?
Simcenter Testlab Jury testing for EV NVH development
Another application, where sound quality is currently gaining importance, is the exterior artificial sounds generated by the acoustic vehicle alerting system (AVAS). This system warns pedestrians of an approaching vehicle. Developing new exterior warning sounds is something of a novelty. Different countries around the globe currently impose new certification requirements for electrical cars. Car producers need to design and certify warning sounds that the electrical cars must exceed traveling at low speeds. Anc at the same time, automotive OEMs are highly concerned about the perception of the new vehicle sounds. Designing new artificial sounds that reflect the brand DNA requires the right toolset for sound quality engineering.
Speed up vehicle development time by blending simulation and testing together
To keep up with the market, automotive OEMs need to react fast and develop advanced vehicle models rapidly. This creates the need to take control of the vehicle NVH performance as quickly as possible, earlier in the development cycle ever. This translates into the demand to be able to predict the component or subsystems behavior before integrating them into the vehicle. In practice, this also leads to introduction of new technology that merges the simulation and physical testing together throughout the vehicle development cycle. While in the past simulation and testing where two separate worlds, the future evolves more into hybrid approaches. This concept can drastically impact and improve the development time. Component-based TPA is one example (here you can find a related white paper). The compelling combination of test and simulation enables the NVH engineers to predict the final vehicle NVH performance before assembling the first full prototype. In a nutshell, this technology enables you to predict a component or subsystems behavior prior to integration. Consequently, it enables the dream to create a virtual vehicle prototype by assembling different components (e.g. electrical engine, suspension system, body, etc.). Component-based TPA is very powerful concept not only because you may get an accurate prediction of the vehicle NVH behaviour in development stage, when implementing design improvements is still easier. But also, the component-based TPA enables you to work with a standardized platform to virtually assembly countless vehicle variations with much lower time investments.
Another example is the trend to combine 1D simulation and test in a more hybrid approach, so called Model-based system testing (MBST). With MBST technology, the use of physical component in combinations with 1D models becomes more and more the industry standard.
These are the key trends in NVH testing that will drive electrical vehicles development in near future. Besides, it is important to realize, that is not only the product changing. It is also the OEM’s frame-work that will change soon too. There will be new requirements and expectations that team members will have to fulfil and skills the engineers will need to learn. Are you interested to understand the EV development trend in more detail? Check out this website to find more details.
One of my favorite games at the arcade growing up was a full motion boat racing simulator. Every time I took a seat in the game, I was fascinated by the motion it provided and wondered what it would be like to design that system. In today’s ever advancing world, complex motion simulators are used to assist with learning and perfecting many specialized tasks. These systems generally have long lead times, undergo many revisions and take quite some time to deliver the finished product.
Now there is a new company, E2M Technologies, that is changing the industry with their quick to market, customizable motion systems for simulators. From conceptual phase to feasible end product in a very short frame of time, their durable, smooth electronic actuation products are used in product testing, flight simulation, medical training and the entertainment industry to name a few.
The company utilizes a variety of Simcenter software to design, test and stay organized when creating new products for customers. Watch this video to see how E2M Technologies employs these Simcenter products to ensure that they are developing and manufacturing top quality mechatronics products:
SimRod is obviously not a digital twin. It’s our Simcenter lab-on- wheels or in engineering speak: a demonstrator. Demonstrators are important because we can investigate those tricky engineering enigmas, but more importantly for the Simcenter story, we can check out the accuracy of the performance predictions created by our Simcenter and NX digital twins. This ability to double check the digitalized world in reality is a key success factor to creating a more truthful digital twin – rather than a less accurate, incomplete or “dirty digital twin”.
So what exactly is SimRod?
In essence, SimRod illustrates the process of improving the accuracy of Simcenter performance predictions. You might think of it like crosschecking a trusted hiking map (rather than the latest navi app) before a wrong turn gets you really lost in the digital twin wilderness.
More specifically, SimRod is based on eRod , an existing vehicle made by the Swiss company, KYBURZ. It is a 2-seater with a 120 km/h top speed and a 180 km range using a 45 kW/140 Nm electric motor. We packed the car with test equipment. Using this vehicle, we will demonstrate how to develop a test-calibrated digital twin. In other words, SimRod is really sustainable, way fun to drive, and equally fun to twin!
Fully instrumented Siemens SimRod vehicle
The basic idea behind the SimRod project is to go through the V cycle in reverse. Each step of the way, we will test the SimRod’s performance attributes, taking the typical sign-off criteria as a basic data set. In addition, we will enrich the instrumentation to allow model calibration. For each of the attributes, we will build a model and show in detail how testing can help drive model calibration towards absolute accuracy or in other words, a more truthful digital twin.
Siemens SimRod - instrumentation
Where needed, we build test-bench setups to validate component performance – again closing the loop by using testing to calibrate the simulated digital twin models.
100% accurate or a little white lie?
That isn’t saying that using a dirty or less accurate digital twin is a bad thing; sometimes, as an engineer, that is all you need. It depends on what stage in the process you are in.
As many of you know, the “design in V” approach offers a proven method, using simulation models as a solid base for making design decisions. At this point, the role of the simulation model is to deliver performance predictions to help guide program managers to the right design alterative. So in the design phase, simulation results that rank predicted performance are rather crucial to the decision process. But, at this point in the game, the absolute accuracy of the prediction is less important, as long as the ranking is correct.
But, when you are signing off the homologated vehicle or the production-ready transonic jet accuracy is vital and that final physical test is still mission critical. In most cases, it is a certification requirement, but often some part of the simulated digital twin lacked fidelity.
Unfortunately, all too often that final test is under budget and time pressure and happens quickly for product performance validation only. The newer idea of a final “loop-close test for the digital twin ” is skipped. This is a missed opportunity to upgrade a dirty digital twin to a truthful one. And a missed opportunity that we need to start addressing since many of the bits and pieces of a calibrated digital twin will be re-used in future products – not to mention soon-to-arrive active use scenarios for IoT and connected digital twins.
Simcenter SimRod Digital Twin
So, to make a long story shorter, this is why we created the SimRod. It gives us – the growing team of Simcenter developers and researchers – an excellent tool to prove our own ideas and solutions. We use SimRod to demonstrate the “loop-close test for the digital twin” process implemented in the Simcenter solutions. And we hope this will help our customers advance in this area.
So whether or not you are a digital native or skilled testing expert, the true power of the Simcenter platform lies in the combination of both testing and simulation. An excellent advanced engineering toolset, the Simcenter portfolio is designed for smooth data exchange between test and simulation development teams to help everyone efficiently build test-calibrated digital twins – digital twins that don’t lie.
Siemens SimRod: Acoustics
Over the next couple of months, we’ll be featuring some of the SimRod stories about our work in: durability, NVH, acoustics, structural testing, ride and handling, battery testing, brake testing and much more.
Also, if you want to see SimRod impersonating a dirty digital twin, make sure to visit us at Automotive Testing Expo 2019 (May 21-23 in Stuttgart, Germany)! You will get a chance to learn more about SimRod in different languages.
You’ll already get a good taste of what SimRod means for the future of the truthful digital twin.
ADAS is no longer for premium cars only but is being standardized in a broad range of vehicles. Step by step the level of automation in vehicles increases, and more control functions of the vehicle will be taken away from the driver until fully autonomous driving is a reality.
The road towards autonomous driving is marked by the need for the vehicle to recognize and react to more and more complex scenarios. In future protocols, large numbers of virtual tests will be required to complement the proving ground tests.
But testing thousands of scenarios is easier said than done. With the Siemens validation and verification framework for ADAS and autonomous driving, we can help our customers throughout the entire process.
Step 1: Fully virtual Most tests are first executed in a fully virtual MiL manner. This means the vehicle, environment, sensors and controller are put together as virtual representations, as close to the reality as required to generate trustworthy results.
Step 2: Digital testing twin However, virtual results can only be trustworthy if they are confirmed by physical testing. Simcenter Prescan enables you create a digital twin and run the exact same scenario in virtual conditions as on the actual proving ground. This way, test periods can be optimized and executed efficiently.
Step 3: On the actual proving ground The last stage of the verification and validation process will always take place outdoors on proving grounds with the pre-production vehicle. Both model validation tests and full performance verification tests can be executed. Our testing laboratory in Helmond, The Netherlands is Euro NCAP accredited and offers full-scale crash tests and active safety assessments for speed assist, lane support and emergency braking too.
Step 4: Data collection It doesn’t stop there. Data collected during the lifetime of the vehicle can be used to further improve the vehicle with over-the-air software updates. Having an established virtual and physical validation and verification framework enables this new way of working.
As global warming is becoming a reality and transportation emissions affect public health in a visible way, while conventional fossil-fueled vehicles face major difficulties in reducing their environmental impact, electric and electrified transportation appears as a sustainable alternative to preserve the environment and support mobility needs. The switch of a major part of the mobility from conventional transportation to electric is already a major challenge for the automotive industry.
In that context, European research projects are initiated to bring together research organisms and industrial players together to develop innovative engineering approaches to support those challenges. OBELICS (Optimization of scalaBle rEaltime modeLs and functIonal testing for e-drive ConceptS) is one of them, and gather Siemens PLM software with OEMs, suppliers, and academics actors in order to “develop a systematic and comprehensive framework for the design, development and testing of advanced e-powertrains and EVs line-ups, to reduce development efforts by 40% while improving efficiency of the e-drivetrain by 20% and increase safety by a factor of 10 using OBELICS advanced heterogeneous model-based testing methods and tools; as well as scalable and easy to parameterize real-time models.”
During the next edition of the 32nd International Electric Vehicle Symposium (Lyon, France) and the Society of Automotive Engineers of Japan annual congress (Yokohama, Japan) both held in May 2019, OBELICS representatives will unveil one important achievement of their research work : a methodology applied to couple system and CFD models on HPC in context of electric vehicle FIAT 500 thermal management design. (cf. attached abstract for the EVS32)
For that work, Nicola Tobia from the Fiat Research Center and Matthieu Ponchant from Siemens Industry Software, explains how resorting to virtual engineering - using Siemens PLM Software simulation solutions - makes it possible to understand the complete behavior of an electric vehicle early at the development cycle, over various drive cycle scenario, in order to focus and improve the thermal management design.
Simcenter Amesim Electric Vehicle modellingIn that study, Mr Tobia and Mr Ponchant use Simcenter Amesim to simulate systems and components of the electric vehicle, replicating how they work, and to mutually link them in order to simulate the behavior of the whole vehicle in real driving conditions. In parallel, they use Simcenter Star-CCM+ to calculate thermal response with high fidelity in specific conditions on remote HPC. A smart coupling simulation between both software is implemented to improve, from a thermal point of view, both system model in the loop (MiL) simulation and 3D CFD simulation; in fact, CFD receives from 1D MIL more accurate boundary conditions, and in turn gives back results to MiL that uses more accurate data to run, even if not running on same machine.
You’re eager to know more about that project?
Join the OBELICS project representative speakers during one of the two conferences in May 2019 or get directly in touch the technical paper authors:
A few months ago we released the first version of Simcenter Webapp Server, our zero-installation solution allowing you to give access to system simulation models to a new range of users (for example, technical salespeople).
With version 2019.1, we have further extended Simcenter Webapp Server capabilities.
What are the top 4 upgrades?
#1 Workflow simplification
Preparing and consuming models have become easier:
The model author can now embed the picture of the model directly within Simcenter Amesim using the model properties. The upload is then limited to the model (no need to upload the picture separately).
The creation of the project for the model consumer is one-click away on the model. Of course, you still have the possibility to change the properties of the project (title, description, picture) afterwards.
#2 User library support
It is now possible to reuse Simcenter Amesim user libraries created with Submodel Editor. So if your model includes non-standard libraries created by you or a third party, you simply need to upload them into Simcenter Webapp Server and then reuse them in your models.
#3 Reuse of post-processing variables
You can re-use post-processing variables of your model and therefore define meaningful variables for your model consumers.
This is the first step towards more customization for the view of results.
#4 CSV export
The model consumer can now export the results as an Excel file for further detailed post-processing.
These exciting new capabilities highlight our priorities for Simcenter Webapp Server: user-friendliness and greater customization.
Find out why you no longer have to wait to deploy system simulation with Simcenter Webapp Server:
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.
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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.