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The beauty of gas turbines Some say that beauty is in the eye of the beholder, but others believe that beauty can be universal. It sounds crazy to some, but often the intricate and complex machinery of a gas turbine, along with the resulting simulation, is considered incredibly beautiful. There is something mesmerizing about all the blades, valves, rotors, as well as the fuel lines and wiring. The shape and structure of the blades, vanes, channels and cavities exhibit an intuitive beauty, which design experts say is essential to the success of a part and assembly. Otherwise, there is a high risk of failure. The theory is that the physics of fluids and structures should align and appear natural, almost as if it came from nature, even if it is counterintuitive to the complexity of the parts, components, wiring, alloys and compounds — the pinnacle of human engineering. Like gas turbines, computational fluid dynamics (CFD) simulations are also known for their ability to mesmerize people with their colorful results. And with more computing power, increasingly unstable simulations with higher fidelity and more complex physics are being made. And even further and faster with GPUs. And with advances in machine learning, one can go even further and faster. Advances in gas turbine simulations and machine learning Siemens Energy has implemented an industry-leading multidisciplinary analysis and optimization (MDAO) workflow supported by Simcenter simulation technologies. This environment incorporates advanced capabilities such as expanded enterprise knowledge capture, artificial intelligence (AI)-powered design wizards, and reduced-order modeling that can operate in near real time. These advancements, including data science methods such as machine learning, have significantly improved the quality and efficiency of the design process. Benefits of gas turbine simulations A look at the current state of the art for gas turbine design workflow The “classical” approach of a CAD image from a jet engine assembly using NX . Designing a gas turbine in the past would take several years and would not always be a success. Thanks to digital tools, we can improve on today’s design quite easily with a multidisciplinary approach of design an optimization. Jet engine assembly (Generated with NX). Even though it is very advanced physics and complex geometries, one can today combine several of these steps in an automated way. Keeping the CAD alive, boundary conditions and various versions stay totally in your control. The design process of a component is shown in the schematic below. This is done by joining the CAD from NX to various CAE simulation tools like Simcenter STAR-CCM+ and Simcenter 3D . The automation and optimization are handled by HEEDS and all data is managed by Teamcenter. It really does not matter if it is higher efficiency through aerodynamics, improved mechanical integrity and durability, reducing cooling air usage or new combustion fuels; they all affect each other and there is no way to be competitive and innovative unless correctly using modern multidisciplinary design space exploration methods. Current state-of-the-art design process for a turbomachinery component. In order to effectively do product development, we want to evaluate as many designs as early on in the process as possible. Taking the next steps into the future means combining this with machine learning, since the design space can become large quickly and with many disciplines involved. What if we could have a machine learning algorithm train itself in real time on the design space that is currently being evaluated with computational fluid dynamics (CFD) or finite element method (FEM)? An improvement on multidisciplinary design optimization for future product engineering For that, we have two proofs of concept that are related to turbomachinery. One is to optimize a water pump efficiency at a flow rate of 110 kg/s and 1200 rpm. We worked on a parametrized model with 12 geometric variables and the number of blades. HEEDS , a comprehensive multi-disciplinary design analysis and optimization (MDAO) software, uses its default search method, SHERPA, to conduct multiple search strategies simultaneously, and it dynamically adapts to the problem as it learns about the design space. With SHERPA, HEEDS can discover 300 design variations in 40 hours. With the introduction of HEEDS AI Simulation Predictor, an add-on extension in HEEDS , SHERPA’s search technology is significantly enhanced. Some CFD simulations are replaced by AI evaluations conducted through an automatically trained AI model, leveraging insights gained from early simulations – revolutionizing this process. In this case, it counted 151 CFD runs while 149 were done with AI evaluation (for a total of 300). This took roughly 20 hours reaching the same results and saving 49% in time. The pump’s efficiency increased by 3% and head by 10%. Water pump – design space exploration with HEEDS AI Simulation Predictor – CAD and CFD results Water pump efficiency for various designs – design space exploration with HEEDS AI Simulation Predictor. The second case is a gas turbine blade for cooling optimization. Here, the objective is to minimize blade temperature and minimize cooling air mass flow. A parametrized CAD from NX is used to simulate in Simcenter STAR-CCM+ . The CAD has 34 parametrized characteristics on the serpentine channel with changes of cooling ribs and shower head holes. The 500 design evaluations done for this case experienced an approximate 38% time save, skipping CFD simulations with AI and still reaching the same best solution. This might mean 20 days of time saved if 160 cores are used for each simulation. This way, you could easily save weeks and months on projects and get a better product faster to market. External and internal temperature for conjugate heat transfer turbine blade design space exploration with HEEDS AI Simulation Predictor, NX and Simcenter STAR-CCM+. Pareto front of design space exploration for minimizing blade temperature and reducing cooling inlet mass flow results using HEEDS AI Simulation Predictor. From these first examples of adding AI and machine learning to an already impressive CAD-CAE workflow, one can already see the potential and how easy it is to get started without being a machine learning or optimization expert. How big the revolution of AI and ML will be and the impact it will have on the fate of the mechanical industry is too early to say. But we already know that it will be the key to staying in front of the competition. Digital twin technology for turbomachinery Schedule a meeting with CAEXPERTS  and discover how the latest advances in gas turbine simulations and machine learning can transform your projects. Take advantage of this opportunity to explore innovative solutions that drive accuracy, efficiency and technical excellence in your industry. WhatsApp: +55 (48) 988144798 E-mail: contato@caexperts.com.br

We are surrounded by rotating machinery. Pumps, fans, compressors or turbines can literally be found everywhere: In cars – air conditioning fans, turbochargers, pumps for fuel or water, coolant pumps for engine and battery cooling. In our buildings and offices – from heat pumps to refrigerator compressors, hairdryers or electronic cooling fans in computers. And of course the industry and energy sector would never work without massive employment of turbomachinery. Large pump (impeller and volute) assembled by an engineer The dimensions of impellers and housings range from the size of a industry hall – like for gas turbines – to only a few millimeters – for example for incorporate blood pumps. A vast variety of different fluids and gases that can have rather challenging properties need to be transported, like chemicals or other aggressive media, hot gases or particle loaded fluids. Sometimes phenomena like phase change or multi-phase flow or the interaction of the fluid with the solid parts need to be taken into account. Medical applications like blood pumps (see more details in the example pointed out below) or respiratory equipment need to be compliant with strict medical technology regulations. Also food & beverage applications require high hygienic standards, and there are of course always safety requirements that must be fulfilled. Traditional Design versus Computational Methods There are several approaches to design a pump, fan, compressor or turbine. The first step is to decide about the basic concept, and to determine the impeller type: Will it rather be an axial, a radial or a mixed flow impeller? With or without stators, guide vanes, diffusors, volutes or housings? Will it be a single- or rather a multi-stage machine? The “traditional” way then is to use analytical equations to define the main dimensions as well as the flow angles and thus the shape of the blades. The calculations are based on the required duty data – volume flow, pressure rise or pump head for the design operating point, the rotational velocity and fluid properties. Available installation space, the type of electrical drive as well as the materials of the impellers and housings can also be relevant. The blade and housing design can be performed by using either commercially available or custom software tools, spreadsheets or even paper-and-pen based approaches. In reality, industrially relevant flow processes are turbulent and three dimensional – this is even more relevant for flow through rotating machinery. Such “real world effects”, as well as blade thickness, blade number, or the influence of tip clearings or secondary flow paths are neglected or only taken into account via empirical information by the usually applied design tools. The gap between the idealized and the real system can be closed with the help of Simcenter simulation approaches, modeling also the most complex physical behavior and geometry details with high accuracy. Visualization of 3D flow results Design from Scratch or Incremental Development? It is common practice for many manufacturers to incrementally modify already existing designs instead of creating a completely new machine from scratch. After the changes are implemented, prototypes need to be build and tested experimentally. The procedure is typically repeated several times to find a design fulfilling the respective requirements, which can be costly and very time consuming. Furthermore, with such an approach developers and engineers sometimes tend to rather stay in their comfort zone, thus missing potential for more efficiency and innovation. This can be avoided by applying 3D CFD computations or even systematic optimization methods, comprehensively involving the complete available design space. Design Space Optimization for Rotating Machinery Design improvements typically require numerous iterations through trial and error. By leveraging automatic optimization techniques , machines can be designed significantly faster.  Simcenter allows to systematically optimize a design. Different blade parameters can be made accessible as variables during the design exploration, thus representing the blade-shape, the main dimensions and number of blades.  Optimized pump impeller geometry In that way, also contradicting simulation objectives – for example increasing pressure rise or pump head while at the same time reduce power – can be tackled. The chart shown here illustrates the tradeoff between the two objectives. Every dot in the diagram stands for one impeller design point. The blue line represents a so-called pareto front, where one objective cannot be improved without changing the other one for the worse. In doing so, hundreds of pump impeller designs can be compared. Design space analysis with pareto front (blue line) Solving Operational Challenges with Advanced Flow Behavior Modeling A very typical and frequent challenge is cavitation in a pump, occurring when the static pressure in a flow drops beneath the vapor pressure of the fluid, forming gas-filled bubbles. These are carried away downstream with the flow, and decay again when reaching areas of higher pressure. This can lead to unwanted or even dangerous effects like noise, damage of structures or vibration. An example for dealing with cavitation with the help of Simcenter STAR-CCM+ simulations is demonstrated by MORFO (Morfo Design Srl), a startup and spin-off from the University of Florence, specialized in the aerodynamic development of turbomachinery, who has pioneered the integration of parametric and optimization tools with Simcenter STAR-CCM+ . The pump inducer shown here increases the pressure of the cryogenic fluid while minimizing cavitation issues, which arise due to the thermodynamic conditions at the inlet (low pressure relative to temperature). It is thus significantly improving the overall quality of the pump. MORFO has parametrized the inducer with “Papillon”, their own graphical interface. Simcenter STAR-CCM+ was then used to perform a CFD study and optimization, using various modelling capabilities to represent complex phenomena like phase change and gas bubble formulation and transport as well as the interaction of the bubbles with the fluid flow. To be able to evaluate the inducer’s efficiency and it’s robustness against caviation, it is crucial both to represent cavitation mechanisms accurately and to examine also off-design by varying the flow rate. The development goal here was to maintain a constant flow rate and determine the lowest possible total inlet pressure without the inducer significantly losing performance in terms of compression ratio. Pump inducer: discretized geometry Visualization of cavitation areas Modeling Flow Behavior of Specialized Fluids: Medical Blood Pumps Another realm where complex flow behavior must be taken into account are medical devices. Pumps are used for several medical applications, for example for live-support machines, where they are used to maintain blood circulation in emergencies or during surgeries, for ECMO (extra-corporate membrane oxygenation), or as dialysis or infusion pumps.  For blood pumps, it is crucial to operate in a blood-friendly manner and reduce hemolysis – destruction of blood cells – as well as thrombogenicity – clotting of the blood. This can be achieved with the help of 3D CFD by limiting the shear stress in the fluid, keeping the blood temperature below body temperature, and also by trying to avoid stagnating or recirculating flow areas. Blood pump with shear stress at the walls Computational Fluid Dynamics is able to provide detailed insights into the non-newtonian blood fluid flow and allows to optimize the pump accordingly. Good pump efficiency means low power consumption and is an important goal as well. Terumo Corporation is developing next-generation technology, including diagnostic devices, therapeutic devices, myocardial regenerative therapy, and devices for emerging markets and is usingCFD to develop blood pumps for cardiovascular surgical devices. Introducing a CFD-based design exploration tool allowed to increase the efficiency of blood pump development, deal with variations of the blood properties and eventually bring a better design to market faster. The exploration team is not a specialized CAE department, but is using CFD together with optimization techniques in order to both increase the efficiency of the product development process and bring a better design to market faster. Visualized cfd results: pump impeller and volute Benefits for SME: Generate Efficient Rotating Machines, Faster! Many SMEs are often bringing specialized solutions to the market. Design tools for impellers and housings have been used for decades and are based on simplified assumptions and empirical information, but to allow for real-world physical behavior, often costly trial-and error test procedures need to be performed yet. 3D CFD can be a good alternative to extensive physical testing, allowing insights which are not possible experimentally. By systematically exploring the design space, higher quality can be reached in less time. Sophisticated, automated workflows enable engineers and developers to focus more on engineering challenges rather than spending excessive time on modeling tasks and allow to leverage simulation technology also for non-experts.Of course also other disciplines beyond CFD, like structure mechanics, can be tackled with Siemens software products. As a result, engineers and developers can allocate more time and effort towards dealing with complex engineering challenges, analyzing simulation results, and implementing innovative design improvements. The use of Simcenter simulation, available via scalable licensing and pricing, thus empowers them to make informed decisions, enhance performance, and optimize the overall design process, resulting in faster time to market and higher quality. Schedule a meeting with CAEXPERTS and discover how we can improve the performance of your rotating machines. Our experts use advanced technologies, such as Simcenter STAR-CCM+ , to develop more efficient and innovative solutions, reducing costs and production time. Let's together improve the quality of your project and increase the efficiency of your processes. Get in touch and take your design to the next level! WhatsApp: +55 (48) 988144798 E-mail: contato@caexperts.com.br

The Simcenter STAR-CCM+ 2410 release brings major enhancements to accelerate and improve your simulation workflows. It introduces powerful tools for modeling complex physics, such as the new Sub-grid Particle Aging model for accurate battery degradation prediction and advanced SPH surface tension modeling for rapid, accurate lubrication simulations. The release boosts productivity with multi-body instancing, providing faster geometry setup, and speeds up Volume of Fluid (VOF) simulations with a new Dynamic Implicit Multi-Step feature. For automotive aerodynamics and fluid further applications, GPU-accelerated sliding mesh and SPH solvers deliver significant performance gains, now with Windows support for GPUs, making high-speed simulations accessible across platforms. Integration enhancements like Teamcenter Active Workspace support and automatic material assignment streamline workflows, ensuring consistency across simulation projects. With these updates, Simcenter STAR-CCM+ 2410 empowers you to model complexity, explore engineering possibilities, and innovate faster than ever before. Improved fidelity for Battery Cell Degradation Prediction Battery degradation due to mechanical stresses is a significant challenge, as it can lead to reduced capacity and increased internal resistance over time. In Simcenter STAR-CCM+ 2410 , the introduction of two Sub-grid Particle Aging models addresses this issue by simulating local degradation effects, including cracking during lithium cycling. You can now use the “Loss of Active Material” and “Surface Crack Growth” options to understand the specific impacts of mechanical stress on cell performance. This enables you to identify the regions most affected by aging, improving predictions of battery life and reliability. Ultimately, this allows for a more accurate prediction of cell capacity and impedance evolution. Higher fidelity for Powertrain Lubrication simulations Modeling the interaction of liquids with solids presents a key challenge in powertrain lubrication applications. The latest release of Simcenter STAR-CCM+ 2410 addresses this by introducing a surface tension model for Smoothed-Particle Hydrodynamics (SPH), allowing for accurate yet rapid simulation of hydrophilic and hydrophobic fluid-solid interactions. You can now apply the same surface tension workflows used in finite volume methods, enhancing the accuracy of simulations in lubrication scenarios and other applications. This upgrade ensures more precise modeling of liquid-wall interactions, leading to better product performance prediction through higher fidelity in powertrain lubrication simulations with SPH. Leaner modeling of complex CHT problems with Motion Setting up complex Conjugate Heat Transfer (CHT) problems with moving meshes often requires manual mapping of data, which can be time-consuming and error-prone. With Simcenter STAR-CCM+ 2410 , explicit mapped contact interfaces are now compatible with motion, eliminating the need for manual data mappers and Java macros. You can set up advanced CHT simulations, such as turbine blade cooling or E-Machine thermal management, more efficiently with automatic mapping of heat transfer coefficients and reference temperatures. This enhancement allows for leaner and more straightforward modeling of complex CHT problems with motion, saving time and reducing setup complexity. Maximum modeling flexibility for Turbulence Transition Turbulence transition modeling is a research topic in continuous evolution, with numerous variations presented in the literature. Each model offers specific advantages for different industrial applications. Hence, to achieve optimal results for a given use case, customization is often required to enhance prediction accuracy. Simcenter STAR-CCM+ 2410 introduces user-defined source terms for Gamma and Gamma-ReTheta models, providing you with the flexibility to adjust transition behavior for specific industrial applications. This approach enables you to fine-tune simulations for scenarios like turbine blade flows, ensuring more accurate thermal and fluid dynamics predictions. The added flexibility allows you to achieve maximum modeling customization to match your specific needs. Accurate and realistic Colliding Spray shapes for any mesh Accurate spray modeling can be limited by the influence of mesh size and grid topology on collision outcomes, sometimes leading to unrealistic spray shapes. Simcenter STAR-CCM+ 2410 addresses this with a new superior collision detection method that uses cell clusters to identify collision pairs and eliminate mesh-related artifacts. By dynamically re-clustering cells, this solution reduces unrealistic spray patterns caused by mesh dependencies, such as “clover-leaf” artifacts. As a result, you can achieve more reliable predictions of droplet sizes and spray shapes, ensuring accurate and realistic spray shapes even for trimmed meshes. Increased realism for Pharmaceutical and Chemical processing applications Simulating wetting phenomena in pharmaceutical and chemical applications can be challenging due to the need for an accurate representation of liquid-solid interactions. In Simcenter STAR-CCM+ 2410 , a new absorption model for Lagrangian-DEM interactions enables you to model mass transfer from liquid droplets to solid particles. This feature allows for the realistic simulation of processes like tablet coating, where droplet deposition on the surface of solid particles must be resolved. By modeling wetting behavior accurately, you can achieve increased realism in simulations related to pharmaceutical and chemical processing. Quickly and easily model multi-stage solid stress and fluid-structure interaction In complex solid mechanics simulations, dealing with multiple stages of stress and deformation can be challenging, especially when different load conditions and boundary parameters need to be considered. In the latest release of Simcenter STAR-CCM+ 2410 , you can now utilize staged physics and simulation operations to automate multi-stage solid stress and fluid-structure interaction (FSI) cases. This allows you to bundle specific sets of loads and boundary conditions into distinct stages, streamlining the setup process. As a result, you can efficiently model sequential applications such as the deformation of an O-Ring under various conditions, from being stretched onto a piston to achieving full sealing capacity when squeezed between components. By automating these simulation sequences, you save significant time and effort while maintaining the accuracy of complex physical behaviors. Gain deeper insights into your study results Design exploration often generates large datasets that can be difficult to analyze effectively. With Simcenter STAR-CCM+ 2410 , you can perform operations on columns within the Output Table, using expressions to calculate metrics such as averages, sums, or standard deviations. This spreadsheet-like functionality lets you derive reports from any combination of study metrics, giving you a deeper understanding of your results. By enabling the creation of user-defined reports, you can gain insights more quickly and make informed decisions on design optimizations, allowing you to gain deeper insights into study results. Quick and dynamic Qualitative Field Analysis Volumetric CFD data analysis can be complicated by obscuring surfaces that hide important result details. Simcenter STAR-CCM+ 2410 introduces dynamic slicing and clipping for resampled volumes, allowing you to visualize the complete dataset while hiding unnecessary elements. This feature makes it easier to identify areas of interest and understand flow behavior. The ability to slice through the data dynamically enhances your exploration capabilities and supports a deeper understanding of complex phenomena, facilitating quick and dynamic qualitative field analysis. Faster interactive CAD handling with user-defined hotkeys Navigating through the 3D-CAD interface for geometry preprocessing tasks can be time-consuming, impacting productivity. With the new release of Simcenter STAR-CCM+ 2410 , you now have the ability to define custom hotkeys for any 3D-CAD action, providing faster access to frequently used operations. This update not only enhances your workflow but also supports collaboration by allowing the export and import of defined hotkey sets among users. The hotkey table also includes filtering and clash detection features, ensuring seamless navigation and optimal use of your shortcuts. This improved usability in 3D-CAD translates to faster simulation setup, enabling you to explore more design iterations in less time. Increased productivity and reduced memory footprint Managing complex CAD assemblies is time-consuming, particularly when explicitly dealing with multiple instances of the same part. Simcenter STAR-CCM+ 2410 addresses this by introducing multi-body instancing, enabling you to create instances of bodies using pattern or rotation features. Allowing modifications on one instance to be propagated across all instances with ease, this approach reduces geometry preparation time and memory usage. As a result, you can handle large assemblies more efficiently, increasing productivity and reducing memory footprint. Accessible Order of Magnitude speed-up for VOF Simulations Volume of Fluid (VOF) simulations often require long run times, limiting their usefulness for time-sensitive applications. The previously introduced Implicit Time Stepping approach, while offering speed-ups led to variable time steps, which many users try to avoid. With the new Dynamic Implicit Multi-Step feature in Simcenter STAR-CCM+ 2410 , you can now achieve speed-ups of almost two orders of magnitude by using large and constant timesteps without sacrificing accuracy. This improvement is made possible by dynamic sub-stepping, which maintains stability during the simulation. The result is significantly faster simulations, allowing you to achieve accurate results more quickly and making accessible order of magnitude speed-up for VOF simulations. GPU-accelerated sliding mesh for automotive applications To meet CO2 emissions standards while coping with a multitude of vehicle variants, faster simulation tools are needed for external vehicle aerodynamics. Simcenter STAR-CCM+ 2410 introduces GPU-accelerated sliding mesh simulations to cope with rotating wheels on GPUs, providing over 30% faster performance compared to CPU-based methods. This acceleration is crucial for validating CO2 emissions and aerodynamic performance in compliance testing. The improved speed enables you to complete more design iterations in less time. Rapid SPH simulations on single GPUs Smoothed-Particle Hydrodynamics (SPH) simulations in Simcenter STAR-CCM+ were limited to CPU-based calculations. In Simcenter STAR-CCM+ 2410 , we introduce a GPU-native SPH solver which significantly reduces simulation compared to CPU solutions. This allows you to run complex SPH simulations, such as multiphase flow analysis, much faster while maintaining accuracy. The seamless transition and a shared code base between CPU and GPU ensure consistent results, enabling rapid SPH simulations on single GPUs and enhancing your productivity in fluid dynamics simulations. Achieve faster simulations with GPU acceleration on Windows To date the use of GPUs for accelerated simulation runs with Simcenter STAR-CCM+ have been limited to Linux systems. With Simcenter STAR-CCM+ 2410 , GPU-native physics solvers are now available on Windows, bringing significant performance improvements to your workflow. You can now leverage GPU acceleration on your Windows workstation, achieving reductions in simulation time by up to 24 times compared to CPU-only runs. This capability extends support to various physics scenarios while delivering consistent results across both Windows and Linux systems. The ability to unlock such speed enhancements on Windows greatly broadens accessibility, allowing you to solve large-scale problems on more commonly used platforms. Benefit from faster-coupled flow and energy simulations with improved GPU linear solver Even with the adoption of GPUs, the need for faster solver technologies remains critical for complex simulations. The new Simcenter STAR-CCM+ 2410 addresses this by incorporating algorithmic improvements in the GPU linear solver, significantly boosting the performance of coupled flow and energy simulations. You will experience the largest speedups in cases where most of the computational effort is focused on solving linear systems, such as turbomachinery aerodynamics and thermal management of automotive components. This update allows you to complete demanding simulations more efficiently, freeing up valuable resources for additional analyses or higher-fidelity studies. Increased confidence in simulations being Correct and Relevant Adding new parts to complex simulations as a corrective retrofit can disrupt workflows if done in a non-orchestrated manual ad-hoc way. Simcenter STAR-CCM+ 2410 integrates Teamcenter Active Workspace directly, enabling you to add parts and automatically update traceability information within the simulation environment. This integration ensures that you are always using the correct data, fostering collaboration across teams and improving data accuracy in large assemblies. As a result, you can achieve increased confidence in simulations being correct and relevant. Seamless Material Properties assignment from CAD to CFD Manually assigning material properties in large-scale simulations of complex assemblies is tedious and error-prone. The automatic material assignment feature in Simcenter STAR-CCM+ 2410 reads metadata from CAD models, matches it to user-defined material databases, and propagates the material assignments to the physics regions and boundaries set up, streamlining the setup process. This automation reduces errors and ensures consistent material properties across all components, enhancing the reliability of your simulations by allowing seamless material properties assignment from CAD to CFD. Schedule a meeting with CAEXPERTS and discover how the improvements in the new Simcenter STAR-CCM+ 2410 version can transform your simulation processes, increasing your productivity and accuracy. Don't miss the opportunity to explore innovations that will accelerate your analysis and help you tackle complex engineering challenges with faster, more realistic results. WhatsApp: +55 (48) 988144798 E-mail: contato@caexperts.com.br

Discover the power of Solid Edge X — the same Solid Edge you know and love in a secure SaaS environment. You can easily and instantly access your projects either online or offline. With automatic software updates and simplified IT management, Solid Edge X offers a seamless user experience. Simplified IT management is done through centralized cloud license management, aiding in a lower cost of ownership. Solid Edge X is also connected to Solid Edge and other Siemens Xcelerator products by utilizing the same Solid Edge architecture.   Feel secure with Solid Edge X data management and collaboration  The security of your work is never compromised with Solid Edge X . Every seat of Solid Edge X includes built-in, cloud-data management. Having a secure data management system enables you to assign and complete tasks, create and manage revisions and much more during collaborative processes. Improved collaboration among team members improves workflows, working to make collaboration a hassle-free and seamless process by utilizing Teamcenter Share.   Flexible user experience With more and more people working remotely all over the world, the workplace requires more accessible software solutions. Companies now need to provide their employees with a flexible software solution that meets their needs. Solid Edge X enables workers to download and install the software which they will have access to anywhere at any time. This provides a flexible user experience by making the software easily accessible. Solid Edge X works online and offline, ensuring productivity, regardless of internet access. Value-based licensing Value-based licensing allows users to utilize and explore a multitude of Solid Edge portfolio products at a low cost. Solid Edge X works hand in hand with value-based licensing to provide users with the most flexible and seamless software experience. Instead of buying each individual product, you can mix and match as you need. Value-based licensing includes Generative Design Pro, Point Cloud Visualization, Solid Edge Simulation Advanced and many others. Seamlessly work across disciplines Solid Edge X is integrated with a plethora of products in the Siemens Xcelerator Portfolio. Since Solid Edge X is built on the same infrastructure as Solid Edge , the software effortlessly works with NX CAM and Simcenter 3D . AI productivity assistance Solid Edge X has new Artificial Intelligence powered features that offer real-time assistance. The real time assistance provided by AI works to minimize disruptions to your workflows. You can quickly and easily get your questions answers without leaving the Solid Edge X environment thanks to the AI chat copilot. Schedule a meeting with CAEXPERTS  to explore all the new features of Solid Edge X ! Discover how this secure and flexible SaaS environment can transform your productivity and simplify IT management, with advanced AI and cloud collaboration capabilities. Don't miss the opportunity to see up close the possibilities that Solid Edge X offers your company! WhatsApp: +55 (48) 988144798 E-mail: contato@caexperts.com.br

“When I was young, there were no signs of an electric drive or electrified vehicles. Car adverts were about speed and horsepower. Now, they are all about range and zero emissions,” comments Steven Dom, Director, Automotive Industry Solutions at Siemens Digital Industries Software. No, this is not an invitation for speeding. These advertisements from 1985 illustrate how customer requirements have shifted over the years. As electric vehicles (EVs) have changed advertising, they have also changed engineering. “A team of engineers tasked with developing a combustion engine might choose to buy or design a gearbox,” continues Steven. “As long as they meet the vehicle specification, the decision is theirs. That type of solo decision-making is not possible in EVs, where the trend is clearly to go to integrated electric drive units or e-drives in which the power electronics, motor, and transmission system that make up the drive are packaged as one entity. From a manufacturing perspective, it is easier to build one integrated box but to get that package right, there must be an ongoing conversation between each distinct engineering discipline. For some individuals and organizations, this will be an enormous challenge.” Although electric drives are simpler, lighter, and more efficient than traditional engines, their development is technologically challenging. Our integrated approach to electric drive engineering allows for rapid redesign and workflow reuse as requirements change while staying connected to a PLM platform. Managing the challenges of electric drive systems engineering Siemens experts Steven Dom and Benoit Magneville, Electrification Product Manager, addressed all aspects of electric-drive systems development and how organizations can support engineering teams and embrace closer collaboration. As Benoit explains: “The overall aim is to design an electric drive that is highly efficient in a wide range of operating conditions, yet there are many potentially conflicting requirements. Reducing the distance between the inverter and the motor, for example, presents benefits in terms of overall package size, cable weight, and harnessing; however, it creates new thermal and mechanical challenges as the inverter is evolving more restrained way.” Other challenges related to thermal cooling include a critical requirement within a package of heat-producing items. Considering separate cooling systems for each component in an e-drive is not the most efficient approach. Integrating the cooling system for all components will simplify construction, doing away with an array of pipes, pumps, and heat exchangers. Still, it also makes for a more complex engineering task. On top of this, the battery and the passengers compete for effective thermal management, and appropriate cooling will need to be provided. In addition, there is a complex dynamic between meeting operational targets for the e-drive and predicting how noise and vibration are perceived by people sitting in the cabin. From a commercial perspective, passenger comfort is essential to manufacturers, particularly for high-value brands. Addressing Power Electronics design, system integration, and reliability Topology design is one of the early stages of developing an electric drive’s electronics. Key metrics, such as efficiency, cost, tolerance, and EMI suppression, must be understood to define the best topology. Much engineering time can be spent assessing how topology impacts the vehicle and then optimizing based on those results. However, the effort can be wasted if thermal implications are only discovered at the end of that process. Ideally, thermal design and simulation are entirely in sync with topology design and evaluation. The choice of semi-conductor technology is also important. Still, the best decisions cannot be made if you do not know how to identify a semiconductor’s characteristics and compare available options. “The ability to understand junction temperature is key because that defines reliability,” says Benoit. “You cannot just rely on performance ratings from a supplier or on one set of test results.” Evaluating different wide-bandgap (WBG) semiconductors and inverter thermal management systems enables accelerated decisions of inverter technology and thermal design innovation. A thorough and accurate electronics design exploration encompassing PCB (Printed Circuit Board) and Busbar design requires integration with mechanical CAD and electromagnetic, thermal, and structural analysis. The solution is for development to take place within a single environment in which all engineers have easy access to other disciplinary areas, and specialists can interact with each other. From early electric motor sizing up to performance validation One fundamental requirement is that a motor’s lifetime is reliably higher than the vehicle warranty and the vehicle’s lifetime. Thermal design is one of the main ways to improve lifetime and performance. “As usual, success begins with the design phase,” notes Benoit. “Electric motor requirements are cascaded down from EV performance targets. The best way to obtain fast and accurate motor sizing and configuration is to quickly evaluate multiple design types and topologies against electro-magnetic efficiency, thermal and thermal and vibro-acoustics performance while still in the architectural phase.” The video below demonstrates an axial fluw machine workflow, performed in Simcenter E-Machine Design . Axial flux machine workflow The Simcenter portfolio connects all these areas, enabling an assessment of how motor sizing and design impact the entire vehicle. In the initial stages, when the design only exists as a set of operational requirements, Simcenter offers an extensive library of motor templates and more than 200 materials. This opens the possibility of identifying a completely new motor architecture that will fulfill targets and generate the best thermal cooling system. Any virtual model can be tested and validated simply by exporting it into Simcenter Amesim . Maximizing the efficiency of the electric drive transmission From an operational point of view, the challenge is to maximize transmission system efficiency while minimizing weight and combining it with the rest of the drive within packaging limits. It is essential to assess gear contact stresses, bearing forces, and shaft flexibility so that noise and vibration from the rotating gear in the gearbox can be accurately predicted. Again, this means designing against multiple attributes, including durability and oil supply for lubrication. Manufacturers want to create lighter vehicles and may consider using new materials, yet these bring specific challenges because they are not always fully proven. Another factor is budget. The cost of prototyping a single gear can be up to $200,000 US. Hence, performance needs to be thoroughly evaluated, and any failure or weakness promptly addressed before a capital investment is made. Want to streamline the development of electric drive systems and maximize the efficiency of your projects? Schedule a meeting with CAEXPERTS to discuss how our integrated approach can transform your engineering. Our experts are ready to help your team tackle the challenges of automotive electrification, from systems integration to thermal and vibro-acoustic design. Contact us today! WhatsApp: +55 (48) 988144798 E-mail: contato@caexperts.com.br

Simcenter E-Machine Design and Simcenter Amesim working together for better electric motor design The typical electric motor design sequence involves many iterations, especially during the early design stages. Identifying the most important load points for a given design problem is necessary but complex. Our release of the Simcenter Motorsolve software in 2020 added a new set of experiments which leveraged user-defined duty-cycles. This capability has been enhanced in Simcenter Motorsolve’s replacement, the Simcenter E-Machine Design software. With an exchange of the machine performance requirements from Simcenter Amesim , Simcenter E-Machine Design can use realistic vehicle behavior to advance the design process. The losses and top five most important load points are calculated and transferred between the software. Load point workflow between Simcenter Amesim and Simcenter E-Machine Design This technology includes several standard Electric Vehicle drive-cycles for the automotive sector. To activate this feature, the user simply defines the desired vehicle torque and rotor speed details. Pulse Width Modulation analysis with arbitrary voltages Calculating machine performance based on measured or arbitrary voltages using traditional finite element analysis (FEA) can be time-consuming and impractical due to the signal’s switching frequency. In Simcenter E-Machine Design , the Pulse Width Modulation (PWM) analysis experiments utilize analytical analysis coupled with FEA to determine accurate performance in a timely fashion. An additional option of assigning user-defined arbitrary voltages to the Phase Windings is now part of the PWM analysis capability. Therefore, digital twins or model calibrations can be based on measurements imported directly from dynamometers or other sources. User-specific arbitrary voltage profile Halbach Array electric motor design in Simcenter E-Machine Design Halbach array template in Simcenter E-Machine Design Rotor templates support the creation of Halbach array patterns with even and odd numbered magnet segments per pole. It also includes the ability to apply unevenly distributed segments with user-defined magnetization directions. As a Halbach array generates the poles in a desired volume (the air-gap), there is a secondary benefit to the Rotor design. There is flux cancellation in the volume where the core would be, and so no back iron or steel is required; a nonmagnetic lightweight core can be used instead, significantly reducing the mass of the Rotor. “…electric motors based on the Halbach array offer measurable benefits over conventional designs, including high power density and high efficiency. One of the enablers of these benefits is that a Halbach array motor does not require Rotor laminations or back iron, so the motor is essentially ironless. This significantly reduces eddy current losses and hysteresis losses… “ Excerpt from “What is a Halbach array and how is it used in electric motors?” by Danielle Collins highlights the benefits of Halbach array electric motor designs. Maximum torque and flux weakening control Motor performance is highly dependent on the control strategy. This link between the motor and the electronics impacts performance parameters like efficiency, loss and the machine’s output power. Simcenter E-Machine Design continues to support these two key control strategies. Maximum torque per amps Flux weakening based on optimal load points You can have confidence that your experimental data more accurately replicates the physical conditions using these control strategies. Efficiency map based on MTPA and Flux weakening The figure above showcases the Efficiency map experiment for an electric machine where the newly added MTPA drive cycle and the Flux weakening control strategy are combined. Simcenter E-Machine Design impacts the electric machine design process. Significantly improve your efforts by including realistic vehicle behavior and control strategies in your experimental outcomes. To learn more about Simcenter E-Machine Design please consider the following: Want to learn how Simcenter E-Machine Design and Simcenter Amesim can transform your electric motor design? Schedule a meeting with CAEXPERTS and discover how our integrated solutions can streamline your analysis, save time, and improve your design efficiency. Don’t miss this opportunity to take your electric motor development to the next level! Cel.: +55 (48) 98814-4798 E-mail: contato@caexperts.com.br

Team competed in the electric battery prototype category E3 UFSC   (UFSC Energy Efficiency Team) set a new Latin American record at the Shell Eco-marathon Brazil 2024 , reaching 381 km/kWh  with its electric battery prototype. This result was achieved in collaboration with CAEXPERTS  and Siemens Digital Industries Software ,  which plays a key role in the success of teams like E3 UFSC , offering a full range of software focused on design, simulation, and analysis. CAEXPERTS  provided support and training, and together with Siemens   enabled the E3 UFSC  team to access tools such as NX , Simcenter STAR-CCM+ , Simcenter 3D , and Solid Edge , which are essential to optimize the performance of the ultra-efficient prototype developed by the team.               E3 UFSC  was founded in 2009  with the mission of developing prototypes of ultra-efficient vehicles, focused on sustainable solutions. The team is composed of 28 members from various courses at the Federal University of Santa Catarina , covering areas such as mechanical engineering, electrical engineering, control and automation engineering, as well as disciplines such as pharmacy and geography, reflecting the interdisciplinary and collaborative nature of the group. In addition, the team has achieved notable results in previous competitions, such as 1st place  in the Shell Eco-marathon Brasil 2017  (petrol category), with a record of 525.7 km/L  and 1st place  in the Decarbonasing the Home challenge in 2021 .   Actively participating in the Shell Eco-marathon , the team is dedicated to building vehicles designed to maximize energy efficiency, setting new standards in the competition. The main objective of the E3 UFSC  prototypes is to minimize energy consumption, demonstrating that it is possible to combine performance and sustainability in innovative solutions. Source: https://www.instagram.com/reel/C_lq0fCpfVz/?igsh=MWhycTlsNXYyN3A3OQ==   With an eye on the future, the team plans to participate in the Shell Eco-marathon Americas  and develop new projects, with a focus on building an ultra-efficient urban vehicle. Innovation in energy efficiency and sustainability continues to be the main focus of E3 UFSC , which seeks to push its own limits with each new competition. The SIEMENS, CAEXPERTS and E3 UFSC Partnership CAEXPERTS not only provided the software, but also provided in-depth technical training and ongoing support. This included assistance with complex simulations and providing strategic knowledge to optimize results. With CAEXPERTS ' expertise , E3 UFSC was able to seamlessly integrate simulations into its design process, creating predictive models   to understand how parts would behave under competition conditions. The team is in a constant state of evolution and improvement, always seeking to innovate in different areas of the project. Simulations are a crucial part of this journey, allowing E3 UFSC  to optimize its designs based on accurate data and predict vehicle performance in different situations, which directly contributed to the record achievement.   Emerald Prototype Thanks to this collaboration between CAEXPERTS  and Siemens , E3 UFSC  is not only able to carry out faster and more accurate simulations and tests, but also continually improve its designs, ensuring that the prototype is always optimized for the extreme conditions of the competition.   ​ Source: https://www.youtube.com/live/PXA5gRzkdhQ?t=2007s The Shell Eco-marathon Competition   The Shell Eco-marathon  is a global competition that challenges university students to design, build and operate vehicles that are as energy efficient as possible. The goal is simple but challenging: to create a car that travels the longest distance possible using the least amount of energy. This includes using conventional fuels such as gasoline, but also alternative sources such as electric batteries and hydrogen.   The competition originated in 1939 in Shell's laboratories in the United States, starting as a bet between scientists on who could achieve the greatest fuel efficiency in their experiments. However, the modern form of the competition was officially created in 1985 in France, and has since expanded to various regions of the world, including Europe, the Americas and Asia.   There are two main categories:   Prototype : Ultralight vehicles, with a design focused exclusively on maximizing energy efficiency, reducing friction and weight to the extreme. Urban Concept : Cars designed to look more like street vehicles, but with sustainable technologies and a focus on efficiency.   The competition takes place annually and involves rigorous technical inspection phases, where the cars are evaluated in terms of safety, design and compliance with the rules. Only after they have been approved can the vehicles be tested on the track. The competition is not based on speed, but on energy efficiency, with teams aiming to cover the maximum distance with the least amount of fuel or energy. Currently, E3 UFSC  competes only in the Battery Electric Prototype category, where it has already achieved remarkable results. However, the team has plans to expand into the Urban Concept  category  in the future, developing an ultra-efficient vehicle for this class.   E3 UFSC wins Shell Eco-marathon 2024   E3 UFSC   achieved an impressive milestone at the Shell Eco-marathon Brasil 2024 , setting a new South American record  for energy efficiency. Competing in the Electric Battery Prototype category , the team achieved the 381 km/kWh  mark, which represents a remarkable feat in terms of efficiency. To give you an idea, this distance is equivalent to traveling more than 3,000 km with just one liter of gasoline , consolidating the team's excellent technical performance.   This achievement was the result of hard and innovative work by the team, which modified around 80% of the vehicle   compared to previous versions. The main changes include:   The implementation of a new transmission system , allowing greater energy conservation during vehicle operation. The development of carbon fiber wheels , designed and manufactured by the team members themselves, which drastically reduced the weight of the vehicle and improved its aerodynamics. A new drive and controller system , which was essential to optimize the use of electrical energy during the route. Changes to the monocoque  improving aerodynamics and reducing weight , optimized in CFD. These innovations were tested and optimized using Siemens  simulation tools , which allowed the team to perform detailed analyses of different scenarios and refine the prototype design to maximize its efficiency. NX  is widely used for CAD modeling, allowing the team to explore different geometries and adjust the vehicle design to maximize aerodynamic and structural efficiency. Simcenter STAR-CCM+  enables computational fluid dynamics (CFD)  simulations, which are essential for developing the vehicle’s aerodynamics and thermal control.   These tools not only accelerate the development cycle, but also enable high-fidelity analysis that would be impossible without the use of predictive simulations. The Future   The partnership between E3 UFSC  and CAEXPERTS  is increasingly promising, with the prospect of continued growth and development of new projects. With the constant support of CAEXPERTS , the E3  team is in a state of continuous improvement, always looking for ways to innovate in the design and efficiency of its prototypes. In addition, E3  plans to expand its operations, especially with the development of a vehicle for the Urban category   of the Shell Eco-marathon.   Sapphire Urban Prototype The partnership with E3 UFSC  reflects this dedication to continuous innovation   and the development of young engineers . By supporting the team with the most advanced simulation and design tools, Siemens  and CAEXPERTS  are empowering future professionals to solve engineering challenges with agility and precision. This commitment is not limited to technical support, but also extends to knowledge transfer and preparing students for the job market, as already seen in other successful partnerships with Formula Student  teams and other academic competitions.   WhatsApp: +55 (48) 988144798 E-mail: contato@caexperts.com.br

Characterization and Optimization of Flows in Bioreactors The design of bioreactors presents challenges that go far beyond those of conventional reactors due to the use of living cells and microorganisms. The characterization and optimization of currents and flows in these equipment, as well as the adequate control of flow speed, concentrations and temperature, for example, are essential points that require a lot of attention from bioreactor engineers and operators. Microorganisms (animal cells, plant cells, bacteria, fungi and viruses), often used for the production of modern pharmaceutical and cosmetic compounds, are particularly sensitive to chemical and physical stresses. The homogeneity of the mixture, adjusted by the rotation of the impeller, is important to avoid chemical stress, while physical stress can be controlled by balancing the agitation and avoiding shear stresses that harm the organisms. Therefore, bioreactors and fluid flows within the tank must be well characterized. If key engineering parameters such as energy consumption, mixing time, and mass transfer coefficient (oxygen) are well known, it is possible to optimize the growth and productivity of organisms while maintaining high product quality. In addition, trial and error experiments, which are time-consuming and cost-intensive, can be reduced, which is especially important if the availability of biological material is limited, as is the case with primary tissues or stem cells. Challenges on an Industrial Scale Understanding and correctly modeling the complex interactions between biological and hydrodynamic phenomena is essential in bioprocesses. When scaling up a bioreactor from laboratory to industrial scale, it is common to observe a decrease in productivity. This is usually due to the decrease in mixing efficiency as the reactor size increases. With increasing volume, steep gradients of substrate, dissolved oxygen and pH arise, which can alter biological responses, both in terms of physiology and metabolism, compared to small-scale cultures. Another important challenge is the shear forces in stirred tank bioreactors – larger volumes imply higher stirring speeds to ensure the mixture is homogeneous – which can impair the attachment of cells to microcarriers, causing collisions and cell damage. Therefore, it is necessary to predict the hydrodynamic behavior in bioreactors of different sizes and their interaction with biological reactions to ensure scale-up success and mixing efficiency. The use of Computational Fluid Dynamics (CFD) allows us to understand and adjust these phenomena, making scale-up more efficient and minimizing problems, optimizing the performance of industrial bioreactors. Use of Computational Fluid Dynamics (CFD) in Bioreactor Design Computational Fluid Dynamics (CFD) can provide detailed modeling of hydrodynamics and mixing to properly size both the process and the equipment. In this scenario, Simcenter STAR-CCM+ offers complete solutions, allowing simulation of not only fluid dynamics, but also chemical reactions and heat transfer, using multiphysics coupling. This makes it possible to more accurately model the physical and chemical dynamics of bioreactors, addressing mixing and performance challenges in an optimized way. In the following topics, we will explore case studies that apply CFD to bioreactors using STAR-CCM+ ,  demonstrating how this technology can predict and optimize key variables such as mixing efficiency and liquid accumulation. Mass Transfer in Gas-Liquid Flows Mass transfer in gas-liquid flows is a common phenomenon in the chemical and bioprocess industries. In this case, air is considered to be dispersed in water, through which oxygen dissolves in the water. This is a very important process for bioreactor  applications , playing a role in maintaining optimal conditions for biological processes. To model this process, the Eulerian multiphase approach was used, together with a population balance model to capture the bubble size distribution. The liquid and gas phases were treated as multicomponents to account for oxygen dissolution, with turbulence modeled by the KE model and the dispersed phase flow by the Issa model. Interphase interactions were described by drag and turbulent dispersion models, while Henry's Law was used to calculate mass transfer. The results showed that gas hold-up, i.e., the ratio between gas volume and tank volume, is a key metric for phase interaction. A higher hold-up increases the interfacial area and mass transport. The dissolved oxygen fraction converged to the saturation value (~8.24 mg/L at 25°C), and the simulation showed a higher gas concentration around the impeller axis due to centrifugal action, with less gas in the peripheral areas. These results highlight the efficiency of the modeling and its importance in gas-liquid interaction to optimize industrial mass transfer processes.   Design Optimization at the Innovation Process Center In the case study conducted by the Innovation Process Center , a design exploration approach was adopted to identify solutions that would deliver significant performance improvements before building physical prototypes. This method allowed for a more accurate and efficient analysis of design options, saving resources and time. Among the improvements achieved, a 40% increase  in mixing performance within the system stands out , which resulted in a significant reduction in costs and time required for development. In addition, the oxygen supply in the process was optimized, achieving an overall increase of up to 17%,   which contributed to improving the reactor's efficiency. The optimization process involved evaluating a complex range of parameters to maximize reactor performance. This was done by constructing a physics pipeline that analyzed velocity, mass transfer, and species present in the system for a variety of parameters. This significantly narrowed down the testing options, focusing on those alternatives with the highest chance of success. The criterion with the greatest impact identified was oxygen transfer rate, which is essential for optimal system performance. As engineer Alex Smith pointed out, “Instead of testing 25 options, we can focus on the ones that have the highest chance of success, saving time and cost.” This approach has resulted in a faster, more efficient design process. Improving Bioreactor Efficiency at the University of Los Andes The University of Los Andes conducted a case study with the aim of improving the efficiency of bioreactors in its wastewater treatment plant. To achieve this goal, the CFD simulation method was used in the design of bioreactor mixing vessels, seeking to optimize process performance. The analysis focused on improving mixing efficiency in the reactor and reducing energy consumption. The challenge was to perform CFD analysis based on injection points, designing different configurations and adding baffles to improve mixture homogeneity. The simulation results revealed unnecessary energy consumption in the current reactor, highlighting the need for system adjustments. Various jet agitation configurations and the inclusion of baffles were tested to explore the design space and identify the most efficient solution. The final design was able to balance sufficient mixing, adequate residence time, and reduction of process short circuits. Furthermore, the best solution was identified using the virtual model, allowing for a significant reduction in operating costs. The impact of the project was remarkable. According to Jorge Lopez of the University of Los Andes, “it is possible to obtain a homogeneous mixture in an anaerobic MBR system without the need to include a mechanical agitator.” The study demonstrated a 50% reduction in energy consumption  , reinforcing the effectiveness of using CFD simulation to optimize industrial processes and reduce energy costs. In conclusion, the use of advanced CFD techniques and software with STAR-CCM+  has proven to be essential for the characterization and optimization of bioreactor flows. Through detailed modeling, it is possible to improve mixing efficiency, minimize stresses on organisms, optimize mass transfer and reduce energy consumption. Case studies demonstrate that CFD simulation allows identifying effective solutions to design and scale-up challenges, resulting in more efficient and productive processes, saving time and resources. Interested in improving the performance of your bioreactors and optimizing industrial processes? Schedule a meeting with CAEXPERTS  and find out how our advanced Computational Fluid Dynamics (CFD) solutions using Simcenter STAR-CCM+  can help you characterize and optimize flows, saving time and resources in the development of your project.   WhatsApp: +55 (48) 988144798 E-mail: contato@caexperts.com.br References DELAFOSSE, Angélique et al. CFD-based compartment model for description of mixing in bioreactors.  Chemical Engineering Science , v. 106, p. 76-85, 2014. WERNER, Sören et al. Computational fluid dynamics as a modern tool for engineering characterization of bioreactors.  Pharmaceutical Bioprocessing , v. 2, n. 1, p. 85-99, 2014.

Ignoring the profound impact of strong two-way coupling in the Fluid-Structure Interaction (FSI) between prosthetic heart valves and blood during the design process will result in suboptimal valve designs and could, ultimately, lead to heart failure. Fortunately, Simcenter STAR-CCM+ gives you all the tools you need to design for maximum longevity and safety of any type of valve. 35 million beats per year Your heart tirelessly beats approximately 100,000 times a day, totaling a staggering 35 million beats in a year. With each beat, your heart valves diligently open and close, facilitating the vital task of pumping blood through your arteries. Serving as one-way inlets or outlets from the heart muscle to the ventricle, these valves prevent the backward flow of blood. But what if one day there is a flaw in that clockwork? Unfortunately, sometimes even irrespective of how much one takes care, reality for some is that their heart may at one day simply not be functioning anymore as it should: the aortic valve has two basic failure modes called Stenosis and Insufficiency. Stenosis describes the narrowing of the valve orifice due to reduced leaflet excursion and opening of the valve, restricting the flow of blood in flow direction. Insufficiency describes the inability of the valve to close quickly enough, creating leakage of blood against the flow direction. Both failure modes will largely increase the workload on the heart and ultimately lead to heart failure. The trileaflet heart valve And so, unfortunately, some people face issues with their natural valves, leading to the necessity of replacing them with prosthetics. Considering the heart’s extraordinary workload of over 35 million cycles annually, the careful and precise design of these prosthetic trileaflet heart valves is not just important but critical. That is why today, I will demonstrate how Fluid-Structure-Interaction (FSI) simulations can aid engineers in the design of safer, longer-lasting prosthetic heart valves (PHV) and guide you through the effects that a Multiphysics approach will have on enhancing the precision and reliability of heart valve simulations and compare it to a single physics approach. To model strong two-way coupled Fluid-Structure Interaction (FSI) applications, where a dense fluid interacts with a flexible structure and vice versa, is one of the most intricate challenges in the realm of multiphysics. To predict the dynamic interaction between fluid and structure, engineers need dedicated sophisticated simulation capabilities. And while modeling the FSI in a heart valve is a highly complex engineering challenge it has the potential to transform the everyday of many, for the better. Why FSI? Despite the highly nonlinear nature of opening and closing of a PHV, where the thin leaflet membrane experiences a snap-through instability transitioning between open and closed positions with virtually zero stress, it successfully captured these motions. In his set-up, the opening and closing of the valve was driven by a pressure boundary condition on the leaflet surface, mimicking the blood pressure. The time-dependent pressure curve was derived from experimental data on the differential pressure between the inlet and outlet of the valve. While this is a remarkable dynamic simulation, it is not really new and could have been done with other simulation tools as well. And, more importantly, a significant effect was ignored here – the valve leaflets don’t operate in isolation; every minuscule movement of a leaflet affects the surrounding blood, creating fluctuations in pressure, modifying flow patterns, or even inducing turbulence. Simultaneously, the fluid’s motion and the pressure exerted on the leaflet surface induce or dampen deformations and accelerations of the leaflet. Because of the blood’s high density, the ratio between the mass of the leaflet and fluid mass displaced by the leaflet is nearly one. Together with the very low stiffness of the leaflet, this indicates a strong two-way coupling between fluid and solid. Disregarding these strong Fluid-Structure Interactions will lead to inaccurate predictions of the valve dynamics. The video below provides a visual comparison of the leaflet dynamics with and without considering FSI effects, e.g. the dampening effect of the blood on the leaflet and the acceleration of blood through the leaflet displacement. As you can see, disregarding the two-way FSI leads to an overprediction of the opening and closing speed of the valve, which in return may lead to a leaflet design that does not open and close quickly enough when interacting with the surrounding blood. As mentioned earlier, this will cause Stenosis and Insufficiency and increase the workload on the heart with heart failure as a potential outcome. The next animation shows the difference in the shape and size of the orifice during valve opening between a simulation without FSI and with FSI effects included. It is evident that the coupling between blood and leaflet structure has not only an effect on the speed at which the valve opens but also on the shape of the orifice once the valve is opened. This shows that only a correct simulation of all the two-way coupled FSI effects will allow to design an optimal leaflet shape and thickness with maximum efficiency and longevity and therefore safety for the patient. The challenge of modeling strong two-way coupling in FSI Modeling strong two-way coupled Fluid-Structure Interaction (FSI) presents inherent challenges owing to the distinct physics and dynamics of fluids and solids, each governed by different equations and continuum discretization methods. In the context of a prosthetic heart valve (PHV), where the fluid adheres to Incompressible Navier-Stokes equations and the solid follows a hyper-elastic material law, coupling these equations becomes a complex endeavor, particularly at the fluid-structure interface. Two fundamental physical conditions must be satisfied at this interface. The kinematic condition dictates identical velocities for fluid and solid, essentially preventing the fluid from detaching from the solid or penetrating it and ensuring their cohesive motion. The dynamic condition balances pressures and forces at the fluid and solid sides of the interface and dictates a force equilibrium. In the case of a strong two-way coupled FSI application like the prosthetic trileaflet valve, the thin leaflets displace a substantial mass of blood and encounter large variations in pressure, leading to extensive deformations and accelerations, making it inherently challenging to satisfy the two physical conditions. Tackle the toughest FSI problems with Simcenter STAR-CCM+ Simcenter STAR-CCM+ addresses these challenges by introducing the new FSI Dynamic Stabilization Method and the 2nd Order Backward Differentiation integration scheme for solids. These enhancements significantly improve convergence and stability in simulations of such complex systems and ensure full kinematic consistency across the FSI interface for first and second-order time integration. In addition, satisfying geometric conservation is crucial, requiring the fluid and solid meshes to move synchronously at the interfaces. Simcenter STAR-CCM+ excels in this aspect through effective use of mesh morphing, overset meshes, and dynamic re-meshing, ensuring harmonized movement of meshes even in this case, where the large leaflet deformations lead to dramatic changes of the fluid domain. More accurate, stable, and reliable modeling of strong two-way coupled FSI In essence, these advancements in Simcenter STAR-CCM+ pave the way for more accurate, stable, and reliable modeling of strong two-way coupled FSI, particularly in intricate applications like prosthetic heart valves. There aren’t many instances where CFD can literally be called life-changing. This time I feel it is fair to say so. Disclaimer No hearts were broken during the making of this post. 😊 Want to learn more about Simcenter STAR-CCM+ and how it can transform your computer simulation? Schedule a meeting with CAEXPERTS to find out how our solutions can optimize your engineering projects! WhatsApp: +55 (48) 988144798 E-mail: contato@caexperts.com.br

Why Simcenter Nastran is used to model airframes Airframe structures must undergo a rigorous evaluation process to become flight certified. Finite element software is a critical tool used in the process as it enables simulation of the airframe to predict stress and deflections for many flight conditions. Linear finite element methods are most typically employed because of their efficiency of computation for a large number of load cases. Under linear behavior, structures have the same stiffness independent of how they are loaded. This is a generally valid assumption however, in airframes with thin skin, the linear behavior assumption may not be valid. When the load on the airframe changes The skin structure not only provides the lifting surface but also supplements the load-carrying capacity of the spars, ribs, and stringers. The skin carries mostly membrane and shear loads. When the skin is in a tension-loading condition, it can carry both membrane and shear loads. But if in compression, depending on the framing, it can locally buckle. In such cases, it can no longer carry membrane loads but can still carry shear loads. Existing modeling methods In the past, airframe analysts have modeled this behavior using manual techniques. They start with a base model that uses standard shell elements to model the skin. In Simcenter Nastran, shell elements are modeled with CQUAD4 elements with the PSHELL physical property. This element type has both membrane and shear stiffness. Then analysts perform a loads analysis to locate areas where the shell elements are in compression. In those areas where the compression level is significant enough, the analyst would create a new model by replacing the compressed shell elements with elements that only carry a shear load. In Simcenter Nastran, this is the CSHEAR element with the PSHEAR property. As can be imagined, this is a tedious effort and requires creating multiple models corresponding to various load conditions. In addition, it becomes difficult to manage the models which makes certification more challenging. The New modeling method A recent enhancement has been made to Simcenter Nastran Multistep Nonlinear (SOL 401) to simplify the workflow for this use case. A new element formulation has been added that changes the stiffness characteristics of the shell element based on whether it is in tension or compression. Thus, only one model is needed for all the various load conditions. In the new workflow, users again use a base model with shell elements. But the shell elements reference a new type of physical property called a shell/shear panel using the PSHLPNL physical property. The new property type has definitions for both membrane and shear stiffness properties. This new formulation is sometimes referred to as a tension-only quad element because it carries no compressive loads. How the new solution works The Simcenter Nastran Multistep Nonlinear (SOL 401), as the name implies, is a nonlinear solver and iterates on the stiffness until the residual forces are eliminated. Initially, the solution starts with the shell/shear panel elements with shell stiffness behavior. During the iteration process, the solver will check the internal loads in the shell/shear panel elements and the ones that have compression are converted to the pure shear formulation. Converged solutions are typically achieved within a few iterations, so solution times do not take much longer than a linear solution. Additionally, users can solve many load conditions in just one solution. The set-up Users have several settings to consider when defining the properties of the shell/shear panel element. The properties for the shell and shear behavior are the same as for standard shell and shear elements. While the new settings control conversion from shell to shear. There are two main settings in this regard: Stress direction for conversion Stress level for conversion For the shell/shear panel the user needs to define the stress direction that will be used to determine whether the element is in tension or compression. Options include the element X or Y direction, material X or Y direction, or the minimum principal stress direction. The software will compute the normal stress in this defined direction and is then compared to the user-defined conversion stress level. The default conversion level is 0.0, but it is often advised to use a small negative stress level instead. Figure 1: Example Wing Model Figure 1 shows an example wing structure that is using the new shell/shear panel elements shown as the darker blue elements. The skin thickness in these areas varies from 1.2 mm to 2.0 mm. The stress direction aligned with the stringer orientation is used for the stress component to determine the conversion behavior. A material coordinate was applied to these elements to define the desired direction. Figure 2: Material Co-ordinate system for stress evaluation, used in stiffness conversion Figure 2 shows the material coordinate system assigned to the shell/shear panel elements. The arrows are showing the X direction of the material coordinate system which is the direction chosen for the stress evaluation. The stress level for conversion was set to -6 MPa for the thinner skin section to -10 MPa for the thicker section. For the analysis, the wing is fixed where it would attach to the fuselage. A set of five force loadings were applied along the wingspan corresponding to various flight conditions. Results Figure 3 shows the deflection (in units of mm) from two of the load cases. Case 3, on the left, shows a downward deflection, and Case 4, on the right, shows an upward deflection. Figure 3: Deflection under load case 3 (left) and 4 (right) One of the new results with the shell/shear panel elements is a status value. A value of 0.0 indicates that the element has not converted to shear behavior and a value of 1.0 indicates it has been converted. It is noted that each load case is solved independently and starts from an unconverted condition. Figure 4: Tension Only Quad Status for load case 3 (left) and load case 4 (right), upwards loading in the top views and downward loading in the bottom views. In load Case 3, where the wing deflects downward, the skin elements on the bottom of the wing are in compression and hence can be seen to have been converted. In load Case 4, where the wing deflects upward, the opposite occurs and the skin elements on the top of the wing are in compression and are converted. Stress results on the shell/shear panel elements can also be displayed. Figure 5 shows the normal stress in the material X coordinate system. For elements that have converted, there is no longer any normal stress and subsequently, there are no results on these elements. For the unconverted elements, the normal stresses are seen in tension. Figure 5: Normal Stress XX for load cases 3 (left) and 4 (right) Figure 6 and 7 shows the shear stresses for the same load cases. The contours in Figure 6 show the shear stresses in the converted shell/shear panel elements. Again, for load case 3, the contours are only on the bottom side of the wing where conversion occurred, and for load case 4, the contours are on the top side of the wing. Figure 6: Shear stress XY for load case 3 (at left) and 4 (at right) on top of the converted shell/shear panels The contours in Figure 7 show the shear stresses on all unconverted elements and the standard shell elements. Figure 7: Shear stress XY for load case 3 (left) and case 4 (right) on the unconverted shell/shear panels and the standard shell elements Do you want to optimize your airframe modeling and ensure accurate analysis with Simcenter Nastran ? CAEXPERTS can help your team implement best practices and take full advantage of advanced finite element solutions. Schedule a meeting with us and find out how we can improve your simulation and certification processes in an efficient and innovative way! WhatsApp: +55 (48) 988144798 E-mail: contato@caexperts.com.br

CAD-embedded CFD simulation The new Simcenter FLOEFD 2406 software release enhances integration across Simcenter portfolio with import from Simcenter Flotherm XT software, introduces integration with Siemens NX PCB Exchange tool for greater workflow opportunities, adds Python scripting support for automation, speeds up handling of large CAD assemblies and much more. Read on to learn how new electronics cooling simulation oriented features and overall software enhancements that help you stay integrated, model the complexity, explore the possibilities and go faster in your simulation processes. Import Simcenter Flotherm XT models into Simcenter FLOEFD To enable easier model interchange and enhance communication between users and between organizations, you can now import a Simcenter Flotherm XT model into Simcenter FLOEFD and utilize the model set up from the original model. Export from Simcenter Flotherm XT and import into Simcenter FLOEFD This also helps users who are selecting to transition to using Simcenter FLOEFD to leverage a CAD-embedded analysis environment and take advantage of multi-physics oriented workflows including thermo-mechanical stress analysis capabilities within Simcenter FLOEFD . Below is a video showing the steps for importing exporting a thermal model from Simcenter Flotherm XT and then importing into the Simcenter FLOEFD . Leverage PCB Exchange with Simcenter FLOEFD PCB Exchange is an ECAD-MCAD bi-directional collaboration tool from Siemens Digital Industries Software allowing users to create and modify NX models leveraging EDA data. Capabilities have been added to PCB Exchange recently to create a simcenter FLOEFD project. The main capabilities are as follows: Create a Simcenter FLOEFD project directly from PCB Exchange EDA data is transferred as a Smart PCB, that users are familiar with PCB Exchange supports creation of wirebonds PCB Exchange is compatible with Simcenter FLOEFD for NX and Simcenter FLOEFD SC ( Simcenter FLOEFD for Simcenter 3D environment). Below is an extended demonstration video of a power electronics module thermal model analysis with the steps for importing PCB information shown using PCB exchange and the IDX file format and in particular components with wirebonds (via CCE file). Wire bonds are important to model in these types of applications. Model thermal vias quickly and easily in Simcenter FLOEFD 2406 New PCB thermal via modeling capabilities have been added to the Simcenter FLOEFD EDA Bridge so you can more easily explore thermal management options: Quickly add thermal vias by defining under a component Thermal vias are created as a cuboid representation of an array with orthotropic material properties when transferred to Simcenter FLOEFD How to add a thermal via representation under a component in EDA Bridge A thermal via region is created quickly by first selecting the relevant component and then adding the Thermal Via Region. How to edit PCB thermal via properties How do thermal vias appear in Simcenter FLOEFD 2406 Within Simcenter FLOEFD , a Thermal Via assembly is created within the parent component assembly. Geometry is created for each dielectric layer of the PCB. No geometry is created for the conducting layers since the additional conducting material from the via region is negligible. A material with an effective biaxial conductivity is automatically calculated from the thermal via properties and attached to each object in the thermal via assembly. Use a local system for point parameters You can now convert local coordinate systems to define point parameter locations. This means you can convert local system coordinates to a global one. For example if you select a local coordinate system, paste coordinates in from a table or import from a file, then you will be prompted if you want to convert them to global coordinates. Utilize simulation automation: PYTHON scripting support in EFDAPI Python is a widely used, popular scripting language for automation across engineering tools and functions. Simcenter FLOEFD 2406 introduces Python support for automation within the Simcenter FLOEFD API (the new EFDAPI was introduced in Simcenter FLOEFD 2312 ) . This opens up opportunities for pre-processing, simulation solve and post processing automation tasks. You can also pursue automating Simcenter FLOEFD operations within in multi-tool workflows for you analysis process. There are documentation and scripting examples available on Support Center to assist users. Below is a short simple demonstration video illustrating a Simcenter FLOEFD thermal analysis with all conditions, features and heat sources being created via Python script and how the simulation results are being post-processed and exported as an excel spreadsheet and graphic files. This is illustrated for an electronics cooling simulation model of a boost converter. Faster handling of large CAD assemblies It is now much faster to open, create and clone projects that contain thousands of component to 100K+ components. Of course any speed up is model dependent, 1.5 – 5 x faster for a model with 45K component to 100 to 150 x for a advanced package with 125K components (i.e lots of solder balls). Smart PCB thermal analysis memory consumption improvement The Smart PCB is one of several options for PCB thermal modeling and it is constantly being enhanced for speed, and memory use optimization. Smart PCB is a sophisticated approach to efficiently capture the detailed material distribution of a PCB without the added computational resource and time penalties typically required to model the PCB explicitly. It does this by using a network assembly approach , whereby a voxel-style grid based on the images of each PCB layer in imported EDA data is generated. In Simcenter FLOEFD 2406 , the solver has been optimized to further reduce memory required for thermal analysis. In comparison to the last 2306 release, memory use reduction is illustrated to be in the 18-20 % range. You can see this this illustrated for fine vs average approach for 3 types of board model in the figure below. Take advantage of the new features of Simcenter FLOEFD 2406 to optimize your simulation and electronic repair processes! Schedule a meeting with CAEXPERTS experts and discover how these innovations can improve your workflows, speed up training of large CAD assemblies, quickly and easily model thermal pathways, and more. Contact us and schedule right now! WhatsApp: +55 (48) 988144798 E-mail: contato@caexperts.com.br

The recent CAEXPERTS  webinar highlighted how simulation using Simcenter STAR-CCM+  is transforming the design and operation of agitated tanks. The integrated approach to engineering digitalization was a key focus, highlighting how to predict and optimize the behavior of complex processes, reduce costs and increase operational efficiency. 1. Why is Agitated Tank Simulation Necessary Today? With the growing demand for efficiency and innovation, agitated tank simulation is becoming a tool for industrial process design. Simcenter STAR-CCM+  allows you to explore multiple design variants and operating conditions, reducing the need for expensive experimental testing and increasing visualization of phenomena that only complex sensors can measure. In this way, companies can improve mixing quality, reduce energy consumption and increase productivity, creating more sustainable and competitive solutions. 2. Complex Geometry Manipulation and Multiphysics Modeling Simcenter STAR-CCM+  stands out for its ability to manipulate complex geometries, enabling the creation, modification and repair of CAD models directly in the software. With a flexible and robust mesh, the tool accurately captures geometric features, ensuring detailed and realistic results. Multiphysics modeling allows the simulation of complex interactions between different phases, such as gas-liquid or solid-liquid, and the prediction of the conversion and yield of chemical reactions. 3. Design Exploration and Workflow Automation with Admixtus Workflow automation with the Admixtus tool accelerates the configuration and simulation of mixing tanks. This approach facilitates the configuration of geometries, generation of meshes and definition of the physics involved in an automated manner based on best practices. The tool also facilitates the post-processing of results, generating reports and graphs in an integrated and customizable manner, ideal for exploring different design scenarios and operational conditions. 4. What Can Be Calculated Using Simulation? Simcenter STAR-CCM+  allows you to calculate a wide range of critical parameters for the optimization of agitated tanks, such as pumping and circulation rate, mixing time, flow field, shear rate, impeller torque, energy consumption, among others. These simulations are capable of predicting the performance of complex systems and adjusting design variables to achieve the best results. 5. Case Studies and Practical Impact Several case studies show the practical application of simulation. One of the highlights was the exploration of impeller positioning and rotation to minimize mixing time and reduce energy consumption in mixing tanks, resulting in significant process savings. Another study focused on the optimization of impellers and baffles, showing improvements in energy efficiency and mixing quality. 6. Challenges and Solutions for Agitated Tanks Key challenges addressed include energy efficiency, bubble and particle size distribution, and prediction of mixing quality in multiphase systems. Simulation helps minimize these challenges by enabling adjustments that improve process efficiency, reduce energy consumption, and increase design flexibility. The tool also facilitates the evaluation of new raw materials and process intensification, contributing to sustainability and cost management. 7. Solutions for Non-Newtonian Fluids During the webinar, we also addressed the challenges of mixing non-Newtonian fluids, such as polyacrylamide. Simulation with STAR-CCM+  allows for careful adjustment of the agitation speed and agitator design to avoid problems such as lump formation and inefficiency in the flocculation process. This type of analysis is essential to ensure the quality and homogeneity of the mixture, even under complex conditions. 8. Multiphase Models and Their Applications Simcenter STAR-CCM+  offers a comprehensive set of multiphase models, such as Discrete Element Method (DEM) and Volume of Fluid (VOF), which are used to capture the complexity of phase interactions. The Eulerian Multiphase (EMP) model is particularly useful for simulating the mixing of miscible fluids and predicting phenomena such as coalescence and break-up, essential for processes such as fermentation and polymerization. The ability to capture these complex effects is critical for simulating industrial processes involving multiple phases, such as gas-liquid or solid-liquid systems. 9. Heat and Mass Transfer, and Chemical Reactions The ability to simulate heat and mass transfer between different phases is essential for predicting the efficiency of chemical reactions in stirred tanks. STAR-CCM+  allows you to analyze everything from the dissolution of substances to heat transfer in complex systems, such as those involving heating or cooling coils. With dedicated models, it is possible to simulate reactions both within a phase and at the interface between phases. 10. Intelligent Design Optimization and Exploration The tool also stands out for its intelligent design exploration, combining multiple optimization strategies to find the best design configurations in fewer iterations. This includes performing Design of Experiments (DoE) and optimizing multiple objectives, such as minimizing mixing time and power requirements while maximizing yield and productivity. 11. Economic Impact and Return on Investment Finally, the economic impact of simulation is discussed, highlighting how reducing the number of experimental tests and optimizing the design can lead to significant savings. Simulation allows for accurate prediction of tank performance, reducing yield losses and scale -up  costs , as well as accelerating the development time of new products with greater reliability and much lower investments. 12. The Future of Simulation and the Redefining of Engineering The use of advanced tools such as STAR-CCM+  is redefining the way engineering is conducted. Digitizing processes allows for digital exploration and physical confirmation, minimizing the time and costs associated with physical testing. Using simulation, companies of all sizes can explore new designs and improve products more quickly and efficiently, while remaining competitive in an increasingly demanding market. The CAEXPERTS  webinar showed that agitated tank simulation with Simcenter STAR-CCM+  goes beyond simple analysis; it is an essential tool for innovation, efficiency, and competitiveness in today’s market. By adopting integrated digital simulation, companies can explore new design possibilities, reduce costs, and increase productivity in a sustainable way. Want to know how this technology can transform your processes? Schedule a meeting with us and find out how we can help your company optimize operations, reduce costs and increase competitiveness. WhatsApp: +55 (48) 988144798 E-mail: contato@caexperts.com.br