“The European automotive industry invests more than €50 billion in R&D annually, a large percentage of which goes towards fuel-efficiency technologies, to meet EU CO2 emission reduction targets thereby complying with NOx and soot standards. However, very few are likely to be able to change the makeup of their fleets fast enough to meet the immediate challenge of the 2021 EU CO₂ emission reduction targets and avoid the significant fines for missing them.” Source: The CO₂ emissions challenge: some carmakers are running late in the race to 2021 - PA Consulting reportCO₂ emission reduction over time against 2017 actual data and 2021 targets
Consequently, to achieve future regulations OEMs and suppliers must innovate in their conventional powertrain design and at the same time come up with competitive alternative propulsion systems as soon as possible. Nevertheless, innovation in conventional powertrains in many instances implies an increase of technology complexity while alternative technologies imply an immediate need of removing uncertainty through rapid system development. Either way, ideally, what OEMs and suppliers would need is to equip themselves with the best engineering tools to accelerate the transformation. That’s a challenge we at Siemens PLM Software accept: we provide a set of simulation solutions to make virtual design and evaluation of new innovative real.
One of the specific innovation areas where OEMs and suppliers can focus on is the thermal management of the internal engine combustion system. Optimizing thermal management of an aftertreatment systems is really a challenge. Indeed, for maximum efficiency (and so satisfying emission rate) aftertreatment systems such as catalysts require specific temperatures to operate efficiently. Using CFD simulation is a way to do a detailed thermal analysis and assess the best powertrain architecture.Engine thermal management analysis using Simcenter Star-CCM+
In the on-demand webinar “Optimizing thermal management in modern powertrains using CFD simulation”, Carlo Locci – simulation powertrain application specialist – showcases how using our CFD simulation tool Simcenter STAR-CCM+ can support the thermal management modeling of your engine, and introduces:
An innovative technique to predict the thermal interaction between the fluid film and the wall in an SCR. This technique was developed to allow for long transient runs in a Selective Catalytic Reduction (SCR),
The most recent developments in this field of Conjugate Heat Transfer (CHT) related to Powertrain problems,
Perspectives on heat production modeling for fuel cells.
If you are eager to know more about our whole Simcenter portfolio for powertrain applications, Warren Seeley Simcenter Director of Powertrain gives an overview in the introduction of this online presence.
Just one numerical simulation contains a wealth of information – we can gain a lot of insight on how a device performs, and from that, we can infer how to make that device better. To confidently recommend one design over another, though, we’ll need to run more than one simulation. As our device knowledge is informed through simulation, we can expect to make numerous geometry/part modifications to the original design. How quickly we can turn these changes around will determine how many simulations we can run within our time budget. Without a highly efficient and flexible workflow, we might find ourselves in the position of being less certain of our final product recommendation. Risky. Now, you’ll be hearing a lot soon about Design Manager, a native capability within STAR-CCM+ v12.04® to do design exploration – that’s not this story. Instead, I want to share how just two mouse clicks can now get you quickly from that first simulation to the next one, and to the one after that and the one after that...
First, some history. In STAR-CCM+ v9.04, we introduced logic based “Filters”. For example, you could create a Filter to return all the geometry parts that contain the name “chip”. Using your Filter to make your part selection in an Operation saves you the trouble of having to find and select all of these objects in the simulation tree manually. Faster. Less error-prone. Repeatable. Good.
But, if you were to then add another “chip” geometry part, you had to go back to your Operation, re-apply your Filter and update your selection. In other words, the part selection wasn’t dynamic. To address this, we delivered "Query-Based Selection" in STAR-CCM+ v10.06. Automatable. Better. But still limited in coverage to just Operations, Displayers and Derived parts. Why is this limiting? Because Regions were statically linked to parts, so if you added, modified or removed parts, you would need to update your part selection for your region manually.
This is now a thing of the past. In STAR-CCM+ v12.04 , we’ve extended Query-Based Selection to apply to Regions, Boundaries, Sub-Groups, Interfaces and Reports. Faster. Less error-prone. Repeatable. Automatable. Better still.
To show how this can help you, let’s consider the simulation of a packed bed reactor for dry reformation of methane to produce hydrogen gas. These reactors contain randomly packed solid catalyst particles which can be various shapes and sizes:
Examples of catalyst particles used in packed bed reactors.
Our operating conditions may be fixed to a narrow range, so if we want to improve our reactor performance, the choice of particle size, shape and number is going to be critical. Let’s consider our workflow starting point to be a simulation (with the solution cleared) in which the physics continua (fluid and solid), regions, boundaries, interfaces, reports, scenes and displayers have already been set up. Lets say we want to replace an existing packed bed containing cylindrical shaped particles with seven wedge shaped holes in each (above at far left), with a new packed bed containing smaller tri-lobe shaped particles (above at far right). We’ve got four Query-Based Selections in play that we will use to assign…
…any geometry part with a name containing “__particle” to a Unite operation (this was possible in previous versions).
…the Geometry Part generated by the Unite Operation to the solid particle Region.
…all Part Surfaces containing the name “__particle” to a Region Boundary defined in the fluid region and another defined in the solid Region (the same dynamic query is used for both regions).
… all Part Surface Contacts (created when the Volume Extract Operation is run) to Interfaces.
Use four Query-Based Selections to automate your two mouse click workflow.
Now, with your .sim file set up this way, when you hit the Generate Volume Mesh button on the toolbar, our first of our two mouse clicks, the Mesh Operations pipeline is executed. What you end up with is a .sim file, meshed and ready to go – all Parts to Region assignments are automatically done. The second of our two mouse clicks, hitting the Run button, is almost anticlimactic in comparison. Your simulation starts running and any derived parts, reports and scene displayers that also use Query-Based Selection get automatically updated.
A cylinder derived part (intersecting the packed bed near the reactor wall) is unrolled to compare hydrogen gas production rates between the two packed bed designs.
Data Focus highlights areas of higher (in color) compared to lower (grey) catalyst site blockage.
To get the workflow down to two clicks did take some preparation and the methodology does rely on a part naming convention. When does it make sense to go through the extra steps? If we want to examine just 3 different particle sizes for each particle shape pictured above, that’s 21 different random packed bed geometries; 21 .sim files that can be consistently set up and run; 21 sets of reports and plots and scenes that can be consistently compared in an automated fashion. And, if that isn’t enough of a reason, there are two great new features in STAR-CCM+ v12.04, Replace Assemblies and 3D-CAD Part Synchronization, that also leverage the benefits of Query-Based Selection. The bottom line is this: Some initial preparation to set up your simulation template is the logic based choice.
Throughout the computer-aided engineering (CAE) design process, engineers must balance a variety of critical performance aspects to validate whether the product under development will work as intended. This complex task cannot be based on a test-and-repair approach. Such an approach would lead to expensive iterations on physical hardware. Other unique projects require that the first prototype is the final product. Testing these kinds of products under extreme boundary conditions can have dramatic consequences.
As a result, Siemens PLM Software solutions provides engineers with the necessary tools to conduct upfront analysis for a variety of applications during the design process. To be successful, machine manufacturers must use models to reproduce the complex behavior within the operational environment. Engineers require pinpoint accuracy to understand how structures work and expedite the analysis of new designs for potential modifications that optimize performance.
The right solution for any nonlinear application
Computation of accurate dynamic loads in structural analysis often requires the consideration of nonlinear behaviors. Simcenter Samcef nonlinear motion analysis fully exploits the augmented Lagrangian method and the large-displacement-large-rotation approach to deliver this capability. The software features an extended library of flexible kinematic joints that can be included in FEA. By coupling these joints to super elements and beams, the complete kinematics and dynamics of the system can be simulated.
When combined with Simcenter Samcef nonlinear structural analysis, nonlinear and fully meshed components can be included to capture material and geometrical nonlinear structural behavior. Furthermore, Simcenter Samcef can be used to integrate sensors, actuators, and controllers in the simulation. These can be imported from Matlab®/ Simulink® and Simcenter Amesim™ software or preprogrammed in Simcenter Samcef. In that case, the control parameters can be optimized. Simcenter Samcef can also be coupled to Matlab and Simcenter Amesim for co-simulation. This co-simulation capability is done through a dedicated module that enables coupling between different transient solvers. This mechanism is used to connect Simcenter Samcef to the AMRC tool (a research center linked to the University of Sheffield) that provides the cutting forces of the machines.
Twin-Control is a European project (H2020, grant agreement nº 680725) aimed to develop new concepts for machine tools and machining process performance simulation. It is coordinated by IK4-TEKNIKER in Spain, with additional partners Renault, COMAU, MASA, Gepro Systems, ModuleWorks, Artis, Predict, TU Darmstadt, University of Sheffield and Samtech, a Siemens Company, in Liège, Belgium.
In the Twin-Control project, Siemens focuses on the dynamic modeling of machine tools, including its Computer Numeric Control (CNC), and its interaction with the machining process. To properly simulate modern high-speed tools, which show close interactions between the dynamic behavior of the mechanical structure, drives, and the CNC, it is crucial to build models that represent the flexibility of all components and interactions.
Simcenter Samcef Mecano enables accurate modeling of machines by considering FEA modeled components connected by a set of flexible kinematic joints. Models are implemented to deal with drive-trains and motor dynamics. To fully capture the dynamic behavior of the machine tool, force interactions between the cutting tool and the workpiece are also considered in the models. These forces consider the dynamics of the tooltip, combined with the tool work-piece engagement determined by Module Works CAD/CAM for toolpath generation and simulation.
As seen in figure 1, a model of the CNC is connected to the machine model by specialized elements that compute motor forces from controller inputs, calling a dynamic library embedding the Matlab Simulink model of this controller.
Figure 1: Coupling scheme
To properly model the machine tools when operating, the following objectives are followed:
Properly account for flexibility of all structural components, connections and feed drive to obtain a model that can represent interior vibrations. The guiding system is modeled by flexible slider elements, which constrain a node to move along a deformable trajectory represented by beam elements.
Limit the number of degrees of freedom (DOF) as much as possible to use the model in the time domain (small time step imposed by the machining simulation module and the controller model). This is done by using a super-element technique. The model contains super-element techniques and can represent the desired levels of vibrations.
The proposed technology is applied to build a flexible multibody mechatronic model of a box-in-box fast machine of project partner COMAU, as seen in Figure 2. This approach provides comprehensive simulation capabilities for virtual machine prototyping in working conditions.
Figure 2: A Multibody model of the COMAU machine tool. Courtesy of Comau.
Another example that illustrates this technology is the 5 axes machine from project partner Gepro Systems (shown in Figure 3).
Figure 3: A Multibody model of a five axes machine tool with multiple spindles. Courtesy Gepro Systems
An industrial CNC controls the motors of the axes to follow the desired trajectories with minimal error. In the model, all frames are fully flexible, as the rails and screw drivetrains, which are represented by a set of slider elements. The control loops are modeled in MATLAB/Simulink, translated into a dynamic library associated with specific control elements to manage the coupling between 1D models and flexible 3D models.
The resulting Twin-Control simulation package is dedicated to both machine tool builders for design activities and machine tool users looking to improve their processes. In both cases, this virtual model will avoid performing costly physical. Simcenter Samcef, coupled with the different modules from our partners, allows building this virtual model in the form of a fully flexible and nonlinear finite element based digital twin.
We can all be blinded by the obvious. The number ofDilbert cartoonson the topic is great evidence for how often it happens to all of us.
This has been on my mind lately because of a recent experience. About a year ago, my family finally had our kitchen renovated. When we first saw the house before buying it many years ago, I distinctly remember walking in and saying “well, we will need to renovate the kitchen.” But then time slips by and priorities shift. Soon the kitchen that so clearly needed renovating just became our kitchen. Our brains so quickly and easily plaster over the imperfections around us that those imperfections disappear from our perception.
On the last day in our old kitchen before renovations started, we took a picture of everyone crammed into the one corner that always seemed to be where everything in the kitchen was located. I found that picture the other day and was struck by what I saw. Was it really that small, that dingy? I found myself slightly embarrassed that we had happily hosted guests for so many years with a kitchen that looked like that!
This ability to tune things out that continually bombard us is often rather useful. Just think, that ability allowed me to happily live with a kitchen that desperately needed an update for many years. Imagine how draining it would be to wake up every day and have all the imperfections be as obvious as the day we first toured the home. However, there is also danger in not stopping to reevaluate. It’s possible to go on so long without reevaluation that our perception becomes entirely detached from reality.
As simulation engineers, we are especially at risk in this regard. One of the most important aspects of what we do is to determine what is important,what should be included into a model being developed and what can be neglected. Even worse, we must balance the amount of personal and computational effort required to capture a certain piece of physics. We may deem it important, but not so important that we are willing to invest in modeling the phenomenon.
One perfect example is the process that goes into designing and modeling a gas turbine such as those used for powering aircraft or generating electricity. These are massive machines that start with tens-of-rows of compressor blades working to create massive amounts of high-pressure air. That air is then mixed with fuel and ignited, producing gasses at even higher pressures and temperatures. All that work is done so that the high-pressure and temperature gasses can rotate turbine blades to extract mechanical energy. The gasses driving those turbine blades are so hot that cold air is pumped through complex internal passageways of the blades and out over their surface just to keep them from being damaged.
To simulate a system this complex, the level of physics appropriate for a model depends on how far along the design process we are. For example, when coming up with the right shape for those turbine blades so that they extract the most energy possible, those complex internal passages are usually not included. Conversely, when determining how to most efficiently cool those blades, it is necessary to include that complex internal detail. However, it’s not always so easy to decide what can safely be neglected.
Simcenter STAR-CCM+ is particularly strong for modeling complex cases. Modeling conjugate heat transfer, complex geometry, combustion chemistry and unsteady blade-passing effects are some of the common types of analysis done by our gas turbine simulation users. Astreamlined workflow gives unmatched ability to accurately mesh the most complex geometry features while enabling the simulation of complex physics such as combustion, conjugate heat transfer and unsteady flows.
Multi-timescale simulation capabilities are now available in Simcenter STAR-CCM+, making it a good time to stop and re-evaluate the tradeoffs being made in our gas turbine simulations. Mixing plane interfaces allow us to model just a single blade passage in each row, which keeps the computational cost down. However, these heavily cooled blades produce distinct cold wakes that wash over the next row of blades downstream.
Ignoring the impact of these localized, unsteady wakes on blade temperature prediction is common. Until now, many have decided that capturing that effect would require too high a computational cost and so mixing planes have become the standard. At one point, the decision was made to ignore blade-passing effects and deal with the decreased accuracy of the simulation. Now it is an assumption made so often that most are blind to it, not recognizing that there are other options available.
Simcenter STAR-CCM+ has been a pioneer in developing harmonic balance simulation capabilities for gas turbine engine simulation for many years. The harmonic balance method allows the unsteady blade-passing effects in the fluid to be modeled at a much lower computational cost than traditional time-domain unsteady simulation. The method takes advantage of the periodic nature of the unsteadiness in the fluid to formulate a much more efficient simulation method.
With Simcenter STAR-CCM+ 2019.1, it is now possible to use the harmonic balance solver on the fluid side to capture the unsteady blade-passing effects and the steady solver on the solid side, all within the same simulation. This decoupling of the fluid and solid timescales makes efficient use of computational resources while more accurately representing the physical system. With this time-scale decoupling, it is no longer necessary to assume that the flow-field is steady andto neglect the impact of localized wakes when performing conjugate heat transfer simulations.
Simcenter STAR-CCM+ will continue to push the boundaries of what is possible with simulation, tackling the most complex cases, and timescale decoupling is evidence of that progress.
In addition to taking on the most complex gas turbine simulation needs, a new initiative has begun for gas turbine simulation with Simcenter STAR-CCM+ that is focused on improving gas turbine simulation for all levels of complexity. Each phase of the design and simulation process have unique challenges. Early in the cycle, flow and thermal predictions must be extremely fast and reliable and provide automatic reporting on the performance of a candidate blade. Later additional geometric and physics complexities are added, and more blade-rows of the machine are simulated simultaneously. Late in the cycle, very large simulations are performed once the design is nearing maturity. Many new capabilities are being brought into Simcenter STAR-CCM+ to help address the unique challenges of gas turbine simulation at each of these design phases. Interaction with design tools, specialized meshing and gas turbine specific post-processing are all on the way. Additionally, with unrivaled abilities to simulate the complex, it will become much easier to mature a given model with additional details as a design progresses.
It’s an exciting time for gas turbine simulation. With so many new capabilities, it may be time to reevaluate assumptions and look for blind spots.
“Through model-based development with OEM, we [at Denso] contribute to more advanced powertrain development” Masashi Hayashi - Digital engineering expert for powertrain components design and simulation at Denso Corporation.
Developing advanced and innovative powertrain is a complex challenge to meet increasing fuel economy and emission standards. Suppliers and OEM need to work together to accelerate the development of their new vehicle. Interaction and the use of a common methodology such as model-based development adopting a common system simulation platform can be a way to achieve in short lead-time development and innovation targets.
Siemens PLM with Simcenter Amesim enables the collaboration between suppliers and OEM, with IP protection and encryption. The advantage on both sides from model sharing is the reciprocal understanding of challenges and benefits. By joining the on-demand webinar “Optimizing the design of engine actuation systems using system simulation” learn how the supplier Denso and the expert Masashi Hayashi analyze an ICE actuation system performances based on OEM requirements using Simcenter Amesim, and assess the benefits from each side.
How Denso optimize hydraulic Variable Camshaft Timing (VCT) design based on performance specification from OEM?
Masashi Hayashi focuses on the development of hydraulic Variable Camshaft Timing (VCT) using system simulation. The challenge in optimizing hydraulic VCT systems design is to improve engine performance, reduce emissions and increase fuel efficiency compared to engine with fixed camshaft.
There are 2 characteristics to be fulfilled and optimized: the VCT speed and stability, in various working conditions (low/high power generation) – based on OEMs requests. Using Simcenter Amesim, the Simcenter system simulation solution, allows validating the correct VCT architecture to satisfy both phase speed and stability.
The additional target for Denso as an engine actuator supplier is to use existing legacy/core design data in the simulation model for more design reliability. By watching the webinar discover how Denso simulation reaches the results accuracy allowing to confirm their VCT model design, based on OEM requirements.
By watching the webinar discover how Denso simulation reach the results accuracy allowing to confirm their VCT model design, based on OEM requirements.
You are eager to know more about other combustion engine actuation systems that you could optimize using Simcenter Amesim? Francesca Furno, our hydraulics expert shows how system simulation easily helps you to tune and improve fuel systems, valvetrains, engine mechanical systems and airpath and exhaust systems and finally the overall vehicle performance. Go deeper into details by watching the live demonstration about Variable Compression Ratio System optimization with Simcenter Amesim at the end of that webinar.
Simcenter Amesim for engine acutation systems optimization
Multidisciplinary design space exploration relies on a robust and automatable framework, capable of seamlessly orchestrating parametric changes, swapping old geometry with new assemblies, and executing the whole CFD pipeline through meshing, solving, and all the way to outputting data. No manual user intervention required!
One of the strongest differentiators of Simcenter STAR-CCM+ is that it truly enables complex CFD process automation. Rewinding time, I recall the joys, the wows even, of new Simcenter STAR-CCM+ adopters when they were learning how to swap a design (at the time manually and of a discrete surface) in our famous ‘lock valve’ example, in doing so turning it 30 degrees. That was in our basic training course, and the rest magically unfolded. That was over 10 years ago.
Since then, Simcenter STAR-CCM+ has matured tremendously in its native automation capabilities, in most recent years illustrated by the release of automation enablers such as Tags, Filters and Query-Based Selection, as well as Global Parameters. (Building a Better Sim File Part 1, and Part 2.)
Simcenter STAR-CCM+ 2019.1 continues to focus on automation with the release of two significant enhancements. If you’re Java shy, you should pay attention because we will be saving you from writing a lot of code going forward. Ultimately, what it means is that you will be freed time to do what you do best: analysing simulation results, deepening your product understanding, and devising creative solutions to improve your design's performance.
So, with Awards Season in full swing, Ladies and Gentlemen (queue music!), it’s now time to recognize the best in automation for Simcenter STAR-CCM+ 2019.1. I give to you, the ‘Automation Awards’!
And the winners for ‘Best New (Automation) Actor and Actress’ are:
Parametric Expressions in Coordinates for her marvellous performance in ‘Repeat Me If You Can’
Let me introduce you first to the new Parameter on the block: File Parameter. He has big shoes to fill, with the seasoned ‘Scalar Parameter’ and ‘Vector Parameter’ winning ‘Best (Automation) Actors’ each year since they came on the scene. But there is a new man in town! File Parameter has just proven himself in this release by being a key instrument to completely automate the process to replace a part in a simulation (inside the Replace Part Geometry Operation), which has earned him the attention of quite a crowd, especially Design Manager. Here is a peek on set:
File Parameter in use in the Replace Part Geometry Operation
Indeed, he has single-handedly allowed Design Manager to automatically sweep through a list of discrete geometry files during an optimization study. Critics will say that it was previously possible to do this with Java scripting, but File Parameter is delivering a process that is faster, much more robust and is able to handle the most sophisticated geometries.
For your viewing pleasure, here is File Parameter in action in his reinterpretation of 'Out with the Old, In with the New' in Design Manager:
File Parameter is automation savvy, ambitious, and a team player who nicely compliments “Scalar” and “Vector”. You will see much more of him in future productions, as we expect more operations in Simcenter STAR-CCM+ to want to hire him. We’re all looking forward to seeing what he will do next.
Now, let’s move on to the stellar performance of Parametric Expressions in Coordinates in ‘Repeat Me If You Can’. She instantly broadens the parameter space available for design exploration studies, with the ability to define Coordinate input fields using Scalar or Vector Global Parameter expressions. This lets users create powerful, parametrically-driven solutions that are easy to automate and template, without the need for writing macros.
Here is a film still of her in action inside the DFBI 6-DOF initial Center of Mass, where the Position Coordinate is defined from parametric values with the Expression Editor.
Entering a parametric expression for the Center of Mass Position Coordinate field, in the Expression Editor
Other examples of Coordinate fields are those for Transforms, be they graphical, 3D-CAD or Geometry Operations, the Derived Part Plane Section Normal, and the Coordinate System Origin, to name a few. These fields, because they can now be defined from Global Parameters, have become instantly available for optimization studies in Design Manager.
We need to note that Parametric Expressions in Coordinates was also critically acclaimed in Simcenter STAR-CCM+ IdeaStorm with a whopping 7 nominations (ideas), so it should be no surprise that she receives the ‘Best (Automation) Actress’ award for Simcenter STAR-CCM+ 2019.1!
This year, we also hand out 'Lifetime (Automation) Achievement Awards' to:
Filters and Query-Based Selections, last seen in 'Two mouse clicks? Hold that thought!', for their ruthless commitment to sorting and filtering through your inputs to your simulation set-up process, saving you from having to write Java code to set up your simulations in an automated way. Grouping a series of parts to feed into a boundary following a naming convention or any other logical combination need only be done once, you can then reuse this Filter elsewhere in your Simulation Template for example inside a Scene or as input to a Report. Read more in Building a better sim file - part 2 of 2. Here is the genius mastermind icon to watch out for in your input fields:
Global Parameters for their role in the blockbuster 'Define Once, Apply Everywhere, Optimize!', now episode 5! With a well built Simulation Template, running simulation variants has never been so easy: change a few parameters, including now the actual CAD file with the help of the new File Parameter, and 'mesh and run' again. With a direct exposure in Design Manager, running an optimization study from these simulation parameters is seamless. Read more in Building a better sim file - part 1 of 2.
Tags for their flexibility in grouping objects that may not be logically connected. Tags can even be the only manual step you may need, before executing a well build Simulation Template. Apply a predefined Tag to Parts that need to get assigned the same mesh custom control for instance, and with the Tag already defined as the Filter input to the mesh custom size: you're done. Read more in Building a better sim file - part 1 of 2.
If you're not using these features today in your Simcenter STAR-CCM+ automation strategy, you are missing out.
As the adage goes, automation and the ‘end of work’ myth don’t go together. You’ve just been freed for more creative ways to explore your design space (or watch Award Shows!). Automation just happens. It’s in Simcenter STAR-CCM+’s DNA.
Bei der Entwicklung industrieller Maschinen für das Verpacken, Abfüllen oder Pressen muss der beste Kompromiss zwischen verschiedenen Eigenschaften gefunden werden:
Produktivität zur Senkung der Produktionskosten
Genauigkeit zur Begrenzung der Ausschussrate
Zuverlässigkeit zur Maximierung der Standzeiten
Effizienz zur Reduzierung der Energiekosten
Um den optimalen Kompromiss dieser Eigenschaften zu ermitteln, kann eine Systemsimulation eines digitalen Zwillings helfen. Durch diese multiphysikalischen Simulationsmodelle können Untersuchungen zur Steigerung der Produktionsgeschwindigkeit ohne Abstriche bei der Produktivität, der Genauigkeit und der Zuverlässigkeit durchgeführt werden.
Digitaler Zwilling: Simulation zur Analyse der Energiebilanz und virtuellen Inbetriebnahme von Anlagen und Maschinen
In unserem kostenlosen Online-Seminar über den digitalen Zwilling lernen Sie anhand von Praxisbeispielen, wie Sie Untersuchungen zur Reduzierung der Energiebilanz Ihrer Produktionsanlagen und Validierungen von SPS-Programmen vornehmen können.
Mit der Simulation eines digitalen Zwillings sind Sie zukünftig in der Lage, Ihre Entwicklungskosten und -zeiten zu reduzieren und insbesondere Inbetriebnahmezeiten zu verkürzen.
Inhalte des Online-Seminars:
Industrie 4.0: Wettbewerbsvorteile durch frühzeitigen Entwicklungswandel sichern
Systemsimulation digitaler Zwillinge für die multidisziplinäre Auslegung und Optimierung komplexer Anlagen und Maschinen
Multiphysikalische Systemmodelle des digitalen Zwillings in Simcenter Amesim, um
mit einen besseren Systemverständnis den Durchsatz von Maschinen zu steigern
mit neuen innovativen Konzepten den Energieverbrauch von Maschinen zu reduzieren
mit virtueller Inbetriebnahme die SPS-Steuerung von Maschinen in der frühen Entwicklungsphase durchzuführen zu können.
During our GVT Master Class, held in September, we had the pleasure to host Elena Garcia Sanchez, Structures Expert at the European Aviation Safety Agency (EASA). She gave a presentation on how to comply with aeroelastic stability requirements.
Can you briefly explain the responsibilities of EASA?
EASA is the single regulatory authority for civil aviation safety in Europe, consisting of thirty-two member states. It was established in 2002 as an agency of the European Union (EU) responsible for civil aviation safety. The organization assists the European Commission in the drafting of aviation safety regulations. It also certifies and approves aeroplanes, propellers, engines, and organizations with exclusive competence. The regulations are derived from ICAO (International Civil Aviation Organization), a worldwide authority.
What is your role within EASA?
I am a Structures Expert within the Large Aeroplane Department of the Certification Directorate, and my work involves fixed wing product certification and continued airworthiness. Together with the Product Certification Manager and several experts of other disciplines, I help review and approve the requests of companies that seek to certify a new aeroplane design or a modification according to regulations, such as airworthiness and environmental certification (part-21) or large aeroplanes (CS-25). We also address in-service events that could potentially affect safety.
When a company wishes to certify a new aeroplane design, it must comply with a set of rules. The certification team Elena Garcia Sanchez, Structures Expertinvestigates the design and verifies whether it complies with regulations. The certification process usually starts with a familiarization meeting with the applicants, where they introduce the design of the new aeroplane and its characteristics, as well as the proposed means for regulation compliance. We then engage in further discussion to understand and agree upon critical aspects of compliance. I may ask questions such as “how do you define the load cases applied in the aeroplane static test?” or “how will you analyze the gust response of the aeroplane?” Actually, the more novel and complex the design or the means of compliance, the more time we need to spend on investigating if nothing will go wrong. This is part of the “Level of Involvement” principle, which also takes the design organization performance into account.
How would qualify the designs that you received for certification? Do you see more novel designs? Are more newcomers entering the market?
There are several new and very innovative ventures in the general aviation world, and indeed also some new developments in the field of large aeroplanes. For large aeroplanes, however, the novelties tend to be more an evolution than a revolution. Most applications come from established players in the aviation industry, where designs are in continuation with their predecessors. They rely on their past experiences to propose designs that integrate innovation while still linking to previous designs. There are also examples of manufacturers entering the market of large aeroplanes. This typically requires quite a significant launching effort. For instance, think about the expense of testing a brand-new large aircraft design at all levels—from thousands of coupon tests, to full aeroplane specimens. Depending on previous experience, it may be necessary to recruit experts, develop certification expertise and establish new organization procedures in order to be aligned with certification demands.
What is the most challenging part of certification procedures?
Some structural disciplines are relatively more challenging than others in terms of complexity, test difficulties and reliability of analysis prediction. Static strength evaluations need to be comprehensive and either rational or conservative. However, it can be considered as relatively straightforward. Fatigue strength evaluations are less intuitive, but still part of the regular activity of small organizations obtaining Supplemental Type Certificates (STCs, third party changes). I’d say that the next step in complexity is predicting sudden decompression, flutter behavior, and in general, complex evaluations with several highly non-linear aspects—such as ditching or crashworthiness assessments. A refined rational analysis is always trickier than a simple conservative approach.
A typical test called GVT to predict the flutter behavior of an aircraft
Which role does simulation play in the certification process?
Today, it is not possible to certify a new aircraft based on simulated data only. Applicants rely more on simulation than before, as they benefit from the increased computational power of modern PCs and have a better understanding of typical phenomena. However, they always need to validate their finite element models through physical tests.We insist on the fact that a physical test reference is still needed, as it is easy to lose track of reality. We have seen problems occur due to errors in the model or oversimplified analysis. I remember a situation where a failure mode had been forgotten in an aeroplane simulation model. The wing of that aeroplane failed in a static test. Luckily, the static test was performed and the issue was discovered in a laboratory and could be managed and corrected efficiently. For that reason, a test reference of sufficient similarity and representativeness is always a must in the certification process. A good guide for structure and similarity proof can be found in the AMC to CS-25.307.
Maximum wing bending test of an A350 XWB, Airbus
How do you see regulations evolve?
The trend is towards performance-based regulations, which are less prescriptive but maintain the level of safety. We wish to be able to respond with agility to changes in the world of aviation and to the novel designs that are brought to us. The intent is to achieve a balance between flexibility and a firm reference to ensure a level playing field, and mitigate possible risks and uncertainty.
How do you feel about working at EASA?
Before joining EASA, I worked as a stress engineer in private companies, contributing to the analysis and test of space and aeroplane structures. I familiarized myself with certification processes; at that time, from the applicant side.
At EASA, I have had a chance to work with different colleagues who had an industry background like me, deep academic knowledge or regulatory expertise. As an EU agency, we strive to follow a harmonized multidisciplinary approach, and to benefit from the varied certification experiences. I like to engage in advanced technical discussions with my applicant counterparts, who bring their knowledge and different perspectives on practical engineering challenges.
If you want to know more about the certification process for flutter and how to use physical testing for verification, follow our on-demand webinar.
My name is John, and I'm in charge of the simulation department in this company. This sunny Monday could have been the worst ever in my career.
I remember very well this morning: everything was perfect from the moment I woke up until my morning coffee. Sun was shining, no traffic jam on my way to the office, I could even park my car near the entrance and had time to enjoy the sunny Monday. The temperature of my coffee was just fine; maybe if I had listened to the news I would have perceived the subtle stress in my colleagues' attitude. I had not: had I switched on the radio news while driving, I can tell you, the temperature of my coffee would have been the tiniest of my concerns.
I happen to work for this company who designs, manufactures and sells cars worldwide. You may have heard about this situation where an incident with a car somewhere in the world catches media attention. In such a situation, one has to decide whether the company will have to recall or not its X million vehicles. This has a massive cost but imagine the cost of our customer security. To better understand the root causes of such an incident, thousands of situations have to be explored, analyzed and this has to be done very quickly; user safety is not an option for us.
We don't know. You are the expert. Explore all the options
My cup of coffee had barely reached my lips when I heard this ringing phone; it was one of these situations where we had to determine whether the chassis design was the root cause for unbalancing the vehicle leading to poor vehicle dynamics behavior under lateral wind ... or maybe it was something else. "We are not sure, hence we need your team to explore all the options", - in a nutshell, this was the emergency of the day.
I did call upon my most experienced guys for us to plan how we would address this emergency. Exploring multiple variants, understanding which element of the design has failed, reassure our customers of our deep expertise, - or recommend to recall vehicles: we needed to act fast, and we don’t have the time to figure this out with physical testing, only simulation could help us here.
Our attack plan was obvious:
Retrieve the models we had built using Simcenter solutions to support vehicle design
Thanks to the company experience, identify the key parameters in the chassis, the controller, the structure as well in the overall system which may have led to this incident
For each variant of the vehicle range, run the simulation reproducing the scenario and vary the parameters
From thousands of simulations, extract the key outcome and draw the conclusion.
Nothing critical for us: one may even say "a walk in the park"... let's be fair, this would be "a walk in the park on a stormy day".
We cannot run our simulation
"A walk in the park"... Yes, assuming we had access to the company HPC. It was about noon, I had already received dozens of calls from many stakeholders watching the news. I had reassured all of them: "The situation is under control, we will get simulation results for you by the end of the day". It was about noon when Bob opened the door: "We have a situation, he told me, we cannot run our simulation, the HPC is fully busy for the next week, no way to divert any resources from it".
The "walk in the park" all of a sudden turned out to be a "base jump without a suit". Well, Bob is one of these guys who rarely comes with a problem without any solution to propose. It happened the week before he received the visit from the Siemens PLM Software team; they mentioned to him that they now have this agreement with Rescale to make their Simcenter Nastran, Simcenter 3D, Simcenter Amesim and Simcenter STAR-CCM+ software available on the on-demand HPC platform.
Let's use our own license on the Cloud platform
This Cloud platform allowed us to run many simulations of our Simcenter models with immediate availability of computation resources. Do you know what is great about this Cloud thing? You have access to a virtually infinite and on-demand computation power.
Siemens PLM Software, not only do they deliver good software but they are also very well aware of our difficulties; the partnership they have built with Rescale did allow us to "use our own license" so that we could build an immediate return on investment for these licenses. On the other hand, working with Rescale has gone very smooth: on-demand access to their infrastructure happens to be an operational expenditure. And guess what: in such emergency situation, these costs are easily accepted by management.
In less than an hour, we had access to an online powerful HPC. It was easy and secure to upload them to this platform. Using our own licenses on the platform has been very fast.
Addressing the crisis
It was 12 pm when I almost had a heart attack... it was 5 pm when the simulation department thanks to its thorough analysis of many variants based on the Simcenter simulation software was able to deliver a conclusion to the management.
Our vehicle design was nowhere to be incriminated: most likely there was an unfortunate reaction from the driver which luckily had no dramatic effect.
Even nicer, thanks to Simcenter on the Rescale platform, we were able to explore additional variants and secure our future answer to such cases. It was Monday evening, the sun was still shinning, our design was proven to be robust. Using Simcenter on the cloud-based Rescale platform saved my day.
STAR-CCM+ v2019.1 includes a host of new features that increase both the realism of your simulations and your ability to automate them.
Simcenter STAR-CCM+ has a hard-won reputation for being the leading CFD platform for both realistic multiphysics simulation, capturing the complete geometry of your product, and all of the physics that are likely to influence its real-world performance, and also for the ease with which it allows you to extract maximum value from those simulations through automation and design exploration.
With the release of Simcenter STAR-CCM+ 2019.1, we continue to build on our reputation through a host of new features that increase both the realism of your simulations and your ability to automate them.
Please note that 2019.1 is the first release to adopt the Simcenter release numbering convention (superseding the October 2018 release of v13.06 ) and is the first in our three release a year schedule for 2019. Simcenter STAR-CCM+ 2019.1 includes a wide range of enhancements, only some of which are highlighted below.
Simcenter STAR-CCM+ 2019.1 benefits and features at a glance:
Industry demands that engineering simulation provides a constant stream of engineering data that guide the product development process through every design decision. In this context, success depends entirely on your ability to turn your single point simulations (no matter how complicated) into automated processes which allow you to explore hundreds of design configurations and operating scenarios with little or no extra manual effort.
Replace Parts File Parameters: One of the most powerful features in Simcenter STAR-CCM+ is Replace Part, which allows you to substitute design variations of any component in your simulation, without having to redefine simulation or meshing parameters. In v2019.1 we introduce a new Automate Replace Part feature through the provision of a new File Parameter that allows you to sweep through a list of discrete geometry files in a Design Manager optimization study. Although users had previously managed to do this using Java scripting, this new approach is faster and more robust and is able to handle the most sophisticated geometries allowing you to create even more powerful parametrically-driven simulation studies.
Each release of Simcenter STAR-CCM+ provides enhanced physics modeling capabilities that expand your application scope and improve the realism of your simulations. In Simcenter STAR-CCM+ 2019.1 we introduce plasma chemistry (useful to simulate the manufacture of electronic devices) and enhancements to the harmonic balance capability (applicable for rotating machinery applications such as gas turbines).
Multiscale Harmonic Balance: The harmonic balance method offers the best compromise between accuracy and efficiency for periodic flows, such as those that occur in rotating machinery. 2019.1 includes an enhancement that significantly improves CHT turbomachinery workflows allowing the use of harmonic balance on the fluid side of the fluid-to-solid mapping interface. This enables a single simulation multi-timescale approach while at the same time efficiently taking account of transient flow and thermal effects.
Of course, realistic simulation demands much more than just modeling physics: engineers also need to capture the full geometric detail of the product that they are simulating. This often involves working with CAD assemblies that are built of hundreds, or even thousands, of individual parts. Simcenter STAR-CCM+ 2019.1 increases your productivity by introducing new features that allow you to more easily navigate the simulation tree and to quickly understand imported CAD models.
Search the Simulation Tree: When constructing a large or complex simulation, navigating the simulation tree manually can sometimes be time-consuming and mouse click intensive. In 2019.1 you can now search the simulation using “Ctrl+f” resulting in much less time wasted in traversing the tree when searching for an object.
3D CAD Colors: Simcenter STAR-CCM+ 2019.1 allows direct import of colors assigned in any CAD package into its 3D-CAD modeler. After import, you can also assign or edit colors within 3D-CAD. This enhancement is applicable to both neutral and native CAD format and particularly benefits users were the CAD provided for simulation already has real-world colors assigned, delivering greater understanding of the model and enabling collaboration.
Das autonome Fahren gewinnt zunehmend an Bedeutung und stellt dennoch eine große Herausforderung für viele Entwicklungsteams bei Automobil- und Landmaschinenherstellern dar. Schließlich sind viele Fragen der Entwicklung über autonomes Fahren im Hinblick auf Methoden, Werkzeuge, Prozesse und Abnahmeverfahren offen.
Autonomes Fahren: Methoden, Prozesse und Werkzeuge für die FahrzeugentwicklungIn unserem kostenlosen Online-Seminar möchten wir einige dieser Fragen beantworten und Ihnen zeigen, welche Methoden, Prozesse und Werkzeuge Sie in der Fahrzeugentwicklung für autonomes Fahren einsetzen können.
Erfahren Sie, welche Lösungen und Werkzeugen von Siemens Ihr Unternehmen bei der Entwicklung autonomer Fahrzeuge von der Konzeptionierung über die Komponentenentwicklung bis hin zur Systemintegration einsetzen kann.
Inhalte des Online-Seminars:
Integrierte Umwelt-, Sensor-, Fahrzeug- und Insassensimulation
As systems become more electrified, designers are required to ensure compliance of electric drive systems in terms of electromagnetic, thermal, noise, vibration, and structural analysis. Simcenter integrated motor design and system analysis solutions are well positioned to meet these needs. An integrated workflow allows designers to be more decisive from the start, compressing the overall design cycle.
1D electric machine models are indispensable in electric-drive system analysis and emulators. They are used to validate real-time controllers (SIL, HIL, and PHIL), without the need of a physical machine, or when it is under prototype. This is a flexible and cost-effective way of testing electric-drives without investing in rotating machines and dynamometers.
The model fidelity is design-stage dependent. For instance, in the initial sizing of the system, the goal is to ensure that the components meet the global steady-state performance and energy requirements. Hence, fast simpler models are used. Reliability virtual testing such as fault analysis and controller design necessitates more accurate models.
Figure 1: The four types of Simcenter Amesim exports supported in Simcenter Motorsolve V6.3
Functional model (Static): A simple quasi-static model that is well suited for power budget or energy management in pre-sizing or validation.
Equivalent Electric Circuit (Quasi-static): A simple linear model that is typically used in controls development.
Equivalent Electric Circuit (Dynamic): A non-linear model that gives more insight into the motor behavior under high currents or fault conditions.
Equivalent Electric Circuit (Dynamic-Spatial): A non-linear model that includes spatial effects such as slots and rotor. It allows torsional vibration analysis and winding current distortions. It is also invaluable in controller validation.
The following video demos this integrated workflow between motor design and system-level mechatronics analysis, that is, Simcenter Motorsolve V6.3 and Simcenter Amesim. Hence, designers can evaluate whether the electric machine meets the system’s design requirements, within the specified operating conditions.
These automated export options ease the workflow for Simcenter Amesim users, by getting rid of the burden required to design, analyze and export electric machine 1D models.
Do you, as an NVH test engineer, regularly face the situations when you need to redo some measurements? For example, due to erroneous instrumentation that was not identified during testing? Or do you notice a large overlap between different test setups used within your company, so some tests are repeated twice? Do you spend a lot of time cleaning up and processing data? These are just a few examples of very common process inefficiencies within the vehicle development cycle.
The efficiency of the nvh testing equipment, software and procedures is a big topic for the testing departments in automotive industry. Especially these days, when car produces bring a wide range of model variants to the market speedily. Their goal is to satisfy customers seeking for personalized vehicles. The increased number of product variants means that the NVH testing teams must pursue more tests on less prototypes and sharper deadlines. So, how do you do that?
Three ideas how to improve your NVH testing methods
Bart Verrecas, a Business developer at Siemens Simcenter, shares his experience and inspirational ideas on how to increase the efficiency of NVH testing. Being 14 years in the automotive NVH testing business, Bart Verrecas has had the opportunity to visit and work with many different NVH testing departments around the globe. “To keep up with the with the continuous competitive push to develop cars faster, you need to open doors to innovation on all levels and departments. Sometimes, you need to take a step back from what you do today. Reinvent the current vehicle noise and vibration tests and the related procedures,” says Bart Verrecas.
His extensive experience in the field helped him to express his advice in three keywords: Flexibility – Confidence – Efficiency.
NVH testing equipment
Firstly, to accelerate the vehicle NVH testing procedures you should create a flexible working environment. Use NVH testing equipment that can easily adapt to your current need. Some of the changes could be pragmatic: offer an option to acquire data when needed. A personal hardware device for fast troubleshooting, whenever required, is one example. Or use a data acquisition system that is scaleable. It will allow you to collect data from small to high number of signals and wide range of sensors.
Secondly, you need to focus on the quality of the collected data. The data validation needs to happen as quickly as possible. The worst thing to happen is when you need to reacquire data because of late identification of the problem.
And finally, innovation in the NVH testing also means unification and automation. “We’re not far away from times, when some tests can be fully automated. Vice versa, some of our clients are already able to automate some tests.” This approach will help you to get rid of inefficiencies and similar redundant instrumentation multiple times. “Aim to combine different tasks and strive for intelligent test execution.”
Die Optimierung des Designs von Produkten gestaltet sich durch zeitintensive, manuelle Iterationen meist sehr mühevoll. Simcenter 3D Design Exploration kann Ihnen in kürzester Zeit helfen, Ihre Produkte zu verbessern und das Potenzial Ihrer Simulationsprozesse durch Automatisierung besser zu nutzen.
Simcenter 3D Design Exploration - Ein innovativer Weg für die OptimierungErfahren Sie in unserem kostenlosen Online-Seminar, wie durch die mathematisch optimierten Kombinationen von relevanten Parametern in Simcenter 3D Design Exploration effizientere Lösungen entstehen. Dabei lernen Sie die Optimierungspotenziale des hybriden Algorithmus kennen und sehen praxisnahe Optimierungen anhand von Beispielen. Zur Bewertung wird Ihnen das Ergebnis der Design Exploration anwenderfreundlich präsentiert.
Inhalte des Online-Seminars:
Optimierungspotenziale des adaptiven Algorithmus von Simcenter 3D Design Exploration
Beispiele für Design Exploration-Studien mit Simcenter 3D Design Exploration