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Graphics Processing Units (GPUs) consist of thousands of identical cores, each designed to operate independently on massively parallel tasks, which can be subdivided so that each core works independently. This design differs from that of the traditional Central Processing Unit (CPU), which is composed of a smaller number of highly complex cores, with sophisticated control logic, large amounts of hierarchical cache memory, and advanced mechanisms such as out-of-order execution, branch prediction, and deep pipelines. This architecture is optimized to minimize latency in the execution of sequential tasks and to handle diverse and dependent instruction streams. GPUs, on the other hand, are designed to keep data and processing as local as possible within their multiprocessors, reducing data movement, increasing throughput, and maximizing performance in highly parallelizable workloads. Computational Fluid Dynamics (CFD) is ideal for GPU architecture because everything is done locally in the computational cell, eliminating the need for communication with distant cells. Reducing the distance between electrons brings three main benefits: simulations can be run faster; power consumption per simulation is much lower; and the hardware footprint is much smaller. The ability to run Simcenter STAR-CCM+ simulations on GPUs is not new, but Simcenter STAR-CCM+ 2602 took a major step forward by adding Volume of Fluid (VOF) and Multiphase Mixing (MMP) to the list of native GPU solvers. The multiphase capability supported on GPU in this version is impressive, including phase change models such as evaporation, boiling, and cavitation, acceleration techniques such as implicit multi-steps, and support for multiple regimes with MMP-LSI. Here are some examples of the benefits that GPU execution can bring to a variety of applications. Run faster tank sloshing simulations Solver: VOF; Mesh: Uniform static mesh of 5.6 million pixels (AMR not yet compatible with GPU); Time step: 5e-4s with dynamic substeps (target CFL 0.5); Motion: Sinusoidal lateral motion; CPUs used: 192 CPU cores (AMD EPYC 7532); GPU used: 1 NVIDIA RTX 6000 Ada The first example is a case of liquid oscillation in an automotive fuel tank. As engineers, we want to know how the center of gravity shifts as the tank oscillates, due to the loads it transfers to the vehicle, and the effect this will have on the vehicle's stability and dynamics. Liquid oscillation is also a concern in cryogenic applications, where boiling occurs frequently, which is also addressed in this version. In Simcenter STAR-CCM+ , the same solver was used for both CPU and GPU versions, meaning that if the cases converge well, identical results can be expected. In the tank oscillation example, this is exactly what is observed, with the free surface motion over time being almost identical (as in real experiments, VOF transient cases are stochastic in nature and therefore no run will be completely identical to the point where every drop coincides). The center of gravity motion shows good agreement with the experiment, both in CPU and GPU runs. CPU GPU The advantage of running the program on the GPU becomes more evident when execution times are compared. A single GPU was significantly faster than 192 CPU cores. In fact, it would take 251 CPU cores to match the GPU's speed (a metric known as CPU core equivalence). When comparing power consumption, the benefits of the GPU are clear, as it uses only 19% of the CPU equivalent, reducing operating costs and carbon footprint. Speed up propeller cavitation simulations Solver: VOF plus Schnerr-Sauer cavitation model; Mesh: 4.4 million clipping static mesh (focused on the region near the propeller); Time step: 5e-6s with 3 volume fraction substeps; Motion: MRF; CPUs used: 160 CPU cores (Intel Xeon Gold 6248); GPU used: 1 NVIDIA Tesla V100 The next example is a marine propeller operating in a condition where cavitation is expected. This gives us the opportunity to test some of the advanced physics features included in the GPU VOF in this version. In this case, the Schnerr-Sauer cavitation model was used. The model predicts the growth and collapse of vapor bubbles due to low pressure on the propeller surface. These bubbles coalesce to form larger vapor pockets that fill the tip vortex and move downstream, forming a classic helical pattern. The results of this simulation on CPUs and GPUs are shown below. They are identical, as expected. CPU GPU The single GPU completed the execution in about 70% of the time it would take for the 160 CPU cores, which is equivalent to 231 CPU cores. As in the previous example, the energy consumed to complete the execution is also much lower, with the GPU consuming only 35% of the energy used by the CPUs. Accelerate marine resistance predictions: Kriso Container Ship (KCS) Solver: VOF plus VOF waves Mesh: 28M clipped static mesh Time step: 0.02s Movement: None CPUs used: 512 CPU cores (AMD EPYC 7532) GPUs used: 2 NVIDIA RTX 6000 Ada Still on the topic of maritime applications, the next simulation is a drag calculation for the Kriso container ship (KCS) test case. Accurate drag prediction in these examples requires precise capture of free surface waves both around the vessel and downstream. This simulation is possible on GPUs thanks to VOF wave support in this version. CPU GPU Once again, the CPU and GPU results are indistinguishable. Comparing execution time, both GPUs were slightly slower than 512 CPU cores, resulting in an equivalent of 214 CPU cores. The GPU's power consumption was only 30% of the CPU cluster's consumption. Run E-Motor cooling studies faster Solver: MMP-LSI; Mesh: Static polyhedral mesh of 4.16 million iterations; Time step: Adaptive time step with a maximum CFL target of 2 and 10 substeps; Motion: Rigid body motion (with intersection based on metrics and distance from the PDE wall); CPUs used: 160 CPU cores (Intel Xeon Gold 6248); GPU used: 1 NVIDIA Tesla V100 The last example is an electric motor similar to those found in electric vehicles. These motors require cooling with a dielectric fluid (oil) which, in this motor, is injected through fixed inlets on the top of the machine over the copper windings. Optimizing cooling in an electric motor is fundamental to maximizing performance and efficiency. This simulation uses Multiphase Mixture Modeling (MPM) with Large Scale Interface (LSI) to allow the coexistence of resolved jets and dispersed mixtures of sub-grid droplets. The simulation also includes relative motion (Rigid Body Motion with sliding interfaces). CPU GPU The results again show excellent agreement between CPU and GPU execution. In this example, the single GPU was slightly slower than the 160 CPU cores, resulting in an equivalent of 124 CPU cores and power consumption equivalent to 65% of that of the CPUs. This is not as good as in the other examples due to the need to re-intersect the sliding mesh at each time step (this is a non-local operation and therefore less suitable for GPUs). Even so, it still represents a very significant speed gain. Take your multiphase simulations to a new level of speed and efficiency with the power of GPUs in Simcenter STAR-CCM+ . CAEXPERTS can help you implement, optimize, and extract maximum performance from this technology in your projects. Schedule a meeting with our experts and discover how to accelerate your results, reduce computational costs, and innovate with greater confidence. WhatsApp: +55 (48) 98814-4798 E-mail: contato@caexperts.com.br

A strong rise of the interest in green hydrogen production The demand for today and the future is for true zero-emission power. Alternatives must be found to replace fossil fuels. Currently, batteries are a solution for automotive. Unfortunately, they are not suitable for many applications due to limitations with storage capacity, lifetime, charge constraints and environmental concerns. Therefore, green hydrogen production (produced for instance by electrolysis, using renewable electricity) is identified as a promising solution for long-term zero-emission renewable energy storage. In 2019, the power generated thanks to hydrogen had the order of magnitude of the power delivered by a modern nuclear plant. And for a few years, hydrogen consumption rose rapidly. This trend will continue to grow significantly as many countries have recently committed large investments to increase hydrogen production and usage for transportation, energy or the industry. Fig. 1: Evolution of hydrogen consumption Most hydrogen is still produced from fossil fuels, which means that new infrastructures must be developed with the following challenges: Green hydrogen production, without any CO₂ emissions. Water electrolysis is one solution, using clean electricity generated for instance from wind turbines, solar panels, wave converters or a combination of these. The improvement of the system performances, reliability and efficiency in order to reach an acceptable price for the produced hydrogen The storage of the hydrogen. As this gas has a poor mass energy density in ambient conditions, it is usually compressed or liquefied for storage. Fig. 2: Hydrogen production plant So, how do we address these challenges, capture the behavior of a hydrogen production plant and each of its subsystem? A model combining all subsystems to evaluate global performances Green hydrogen production simulation within Simcenter Amesim is the solution. It makes it possible to capture the complete process of green hydrogen production, predict interactions between subsystems and the global performances. Fig. 3: Hydrogen production plant model in Simcenter Amesim Let's now move on to analyzing the example of electricity generated from 3 different green sources: Wind turbines Solar panels Wave converters The electric power is used to power an electrolyzer generating hydrogen. The hydrogen is finally compressed in order to store it in high pressure tanks, ready to be used, refuel vehicles or to be transported. Wind Turbines The wind turbine model takes into account the number of wind turbines we wish to use, the definition of the turbine geometry (especially the propeller diameter, the angle of inclination…), the generator performance, the losses of the subcomponents and the control of the propeller pitch. Fig. 4: Wind turbine model This model makes it possible to predict, for instance, the electric power and the mechanical power of the turbine depending on the wind transient speed. Fig. 5: Wind turbine model results Solar panels The solar panel model is taking into account the number and geometries of cells and panels, the transient operating conditions: considering the evolution of the sun position and the impact of clouds and the definition of the solar array performances. Fig. 6: Solar panels model It makes it possible, for instance to predict the electric power delivered by the solar panel, depending on the transient irradiation power on the cells. Fig. 7: Solar panels model results Wave Generator To predict the performance of a wave generator, a highly detailed multiphysics model was initially built. This model reproduces the detailed architecture of the system, considering the sizing and behavior of the subsystems: the piston, valves, hydraulic motor and generator, an accumulator, piping, etc. The model takes into account transient operating conditions with variable wave frequency and amplitude. This model is accurate and useful for the detailed design and optimization of the wave generator. However, for long-duration simulations, it remains slow. Then, in a second stage, starting from the accurate model, a reduced model was built using the Simcenter Amesim Neural Network Builder tool. The Neural Network Builder allows training a reduced model easily and quickly, generating the corresponding Amesim model that will run very quickly. In a validation simulation, the reduced wave generator model managed to reproduce the results of the initial model with a 94% confidence level, with a significantly shorter simulation time. It's truly amazing! Fig. 8: Wave generator model reduction This reduced-scale model can then be used to predict the electrical energy generated by the wave generator, depending on the frequency and amplitude of the wave, with the performances we need in our green hydrogen production system model. Fig. 9: Wave generator model results Electrolyzer The electric power generated by solar panels, wind turbines and wave generators is combined and used by the electrolyzer. This will convert water into O₂ and H₂. In this model, performance and reaction rates are predicted thanks to the polarization curve provided as a parameter, the number of cells, and the active area of ​​the cells. Fig. 10: Electrolyzer model This makes it possible to predict the electric power used by the electrolyzer, the hydrogen instantaneous flow it will produce and the corresponding average mass you can produce per day. In this example, you can produce approximately 9 kg of hydrogen per day. You can also see that, with the sizing of the subsystems, the wave converter produces 88% of the electrical energy, the solar panels 4%, and the wind turbine 7%. Fig. 11: Electrolyzer model results Hydrogen storage Finally, the hydrogen is compressed in the hydrogen storage model. This model is based on pipes, a compressor with its control, controlled valves and several tanks. The valves control allows the 1st tank to fill until the pressure reaches 750 bars. The 2nd tank is filled next and finally the 3rd. Thermal exchanges occurring between hydrogen, the pipes and the tanks are taken into account. The simulation stopped when the pressure had reached 750 bars in each of the 3 tanks. Figure 12: Hydrogen storage system model Thanks to the model and simulation, it is possible to predict that, under the defined operating conditions, the 3 tanks can be filled in 42 days. It is also possible to clearly understand how quickly the pressure and mass of hydrogen increase, as well as the evolution of the gas temperature inside the 3 tanks. The compression of hydrogen to 750 consumes part of the energy generated by the solar panels, wind turbines, and wave generators. This, ultimately, reduces hydrogen production. Thanks to the simulation, it can be estimated that the compressor consumes about 6% of the electrical energy. Fig. 13: Hydrogen storage system model results Conclusions In conclusion, green hydrogen production simulation within Simcenter Amesim can definitively help address the challenges of green hydrogen production. The extensive multi-physics simulation platform makes it possible to model complete systems Sizing the different subsystems, considering various operating conditions is beneficial It makes it possible to better integrate subsystems and improve the overall performances and ROI Provides you with a better understanding of the system global behavior With system simulation, you can better design your system but also evaluate virtually and improve your control strategies You can finally select the right design at the 1st attempt, reducing risks of errors and accelerating your projects Finally, Simcenter Amesim , thanks to generic models and libraries makes it possible to address clean hydrogen production but also many other applications. We can mention briefly for instance the following ones: Design of hydrogen tanks integrated in a vehicle or an aircraft, considering high pressure or cryogenic tanks, simulation of scenarios as refueling or hydrogen extraction. Evaluation of the performances of aero-engine and gas turbines, analyze the bleed impact on multi-stage compressors, focus on engineering questions analyzing model for off-design and transient assessment. Design of hydrogen combustion engines, adapt the injection systems and controls, charging systems, combustion controls and after treatment systems. Fuel cells design and integration with the air and hydrogen supply, the power electronics, the thermal management and controls. Fig. 14: Examples of Simcenter Amesim capabilities for other applications about hydrogen About the author: Patrice Montaland is a Business Developer for Simcenter Amesim . He first gained experience about simulation, fuel cells and hybrid vehicles as an engineer working in the automotive and the hydrogen industries. Patrice joined Siemens 14 years ago, he is now working very closely with the Simcenter Amesim development team, with a real motivation for better addressing the industry new challenges. Patrice strongly believes in the benefits of system simulation for designing green hydrogen production systems and improving the usage of the hydrogen in systems as for instance fuel cells thanks to a fast and comprehensive multi-physics modeling approach. Ready to advance your green hydrogen production more efficiently and safely? Schedule a meeting with CAEXPERTS and discover how simulation solutions, such as Simcenter Amesim , can help your company optimize systems, reduce risks, and accelerate results in clean energy projects. WhatsApp: +55 (48) 98814-4798 E-mail: contato@caexperts.com.br

For any vehicle, poorly handled water can be a problem, one that is very well known to today’s automotive engineers. Whether a light drizzle or a deep flood, water impacts almost all aspects of a car design, from driver visibility and component longevity to vehicle safety and overall performance. For years, tackling these issues meant costly, time-consuming physical tests. Today, however, car designers are equipped with an ever-growing suite of tools to simulate and mitigate excess water flow and ingress concerns. This growing tool set, coupled with the continuous advancement of high performance computing (HPC), has solidified simulation as the “must have” option for the modern engineer, boosting cost and time savings early in the design cycle. You’ve Got Options To help navigate the simulation waters, Simcenter software and services offers both RANS and SPH method-based analysis tools providing efficient combinations of fast, high fidelity solutions. Let’s take a deeper look at what each option can provide. RANS (Reynolds-Averaged Navier-Stokes) RANS methods are continuum-based, grid-dependent Computational Fluid Dynamics (CFD) methods that solve time-averaged equations for fluid flow, meaning they model the effects of turbulence rather than resolving every turbulent eddy directly. A RANS solver treats fluid as a continuous medium and solves for averaged quantities like velocity, pressure, and temperature on a fixed mesh. RANS methods have several strengths: Computational efficiency for steady-state flows: Generally more efficient for steady-state or quasi-steady flows, making them suitable for larger domains and longer simulation times. Bulk Fluid/Air Flow Prediction: Excellent for predicting overall water behavior with aerodynamic interaction of the vehicle (multiphase). Pressure Prediction: Provide stable, accurate pressure fields used in coupled deflection and stress predictions, ie – FSI (Fluid/Solid Interaction) or FEA/CFD coupling. SPH (Smoothed Particle Hydrodynamics) SPH methods are mesh-free, Lagrangian particle-based methods. Instead of solving on a grid, the fluid is represented by particles that move with the flow, carrying properties such as mass, velocity, and pressure. These particles interact with their neighbors within a defined smoothing length, and fluid properties are reconstructed using kernel-based interpolation from these particle interactions. SPH methods also have several strengths: Computational efficiency for transient flows: Naturally excel at simulating highly transient, violent, free-surface deformation, splashing, sloshing, and complex free-surface dynamics without numerical diffusion. No meshing: Eliminate the need for complex meshing and remeshing, simplifying setup for intricate geometries, moving components, and scenarios involving breakup or water fragmentation. Localized water ingress and component-level interaction: Well-suited for detailed analysis of water ingress through vents, drains, seals, and small openings, as well as direct water interaction with sensors, cameras, and air-intake pathways. Let’s explore some common water management issues comprehensively tackled using Simcenter Fluids and Thermal Software and Simcenter Engineering and Consulting Services solutions. Ensuring Clear Vision and Driver Safety Everyone knows good visibility while driving is paramount. Even a mild compromise to a driver’s point of view can be aggravating or at its worst downright dangerous. Luckily there are a number of ways simulation can help your car maintain a clear view on a rainy day. Windshield & Wiper Optimization Using multiphase CFD modeling, engineers can precisely predict how wiper blades remove water under various rain and wind conditions. This allows for the optimization of blade design, speed, and sweep angle, and helps mitigate issues like water flow and streaking from A-pillars. More advanced coupled simulations (air and water) even analyze aerodynamic effects to ensure wipers remain effective at high speeds, reducing noise and vibration issues from wiper chatter. Side Mirrors & Windows Side view mirrors are an essential component of safe driving, one whose design must comply with varying government guidelines (minimum sizes and angles) as well as aerodynamic engineering constraints (minimal drag). For these reasons, a side mirror’s surface area tends to be relatively small and can easily become compromised by water. Fortunately, advanced CFD modeling techniques exist to mitigate these problems before they occur on the road. Detailed side mirror simulations often require a hybrid approach using different multi-phase models to approximate different solution domains; air flow, bulk water, water droplets & water film. Transition between domains is dictated by a user defined criteria (ie – droplet impingement, film thickness or blob diameter). Hydroplaning & Tire Analysis A properly performed tire analysis can enhance vehicle safety through optimized tire tread designs and significantly reduce physical prototyping time. These complex simulations use advanced methods to model the interactions between tires, water, and air in order to predict when and how a tire loses traction. They can be highly challenging simulations due to the moving and deforming tire geometry, transient flow behavior and the level of detail required to achieve acceptable accuracy. These challenges can be overcome with Simcenter STAR-CCM+ using a combination of Volume of Fluid (VOF), dynamic or overset meshing and coupled FSI solvers. Navigating the Deep: Water Wading and Component Protection Large accumulations of water are common after heavy rainfall, particularly in low-elevation areas, coastal communities and poorly draining roadways. Manufacturers know these events will occur over a vehicle’s lifetime and as a result, controlled water wading tests have become a standard requirement of most vehicle validation programs, particularly for electric vehicles where e-component protection is critical. Water wading places simultaneous demands on splash management, sealing integrity, and dynamic water channeling around the vehicle. The unique architectures of both combustion-engine and battery-electric platforms create very different exposure paths for water, from air-intake and vent systems to underbody components, high-voltage enclosures, and thermal management hardware. Understanding how water moves, accumulates, and interacts with these systems during a wading event is essential early in the design process, long before physical testing begins. Underpanel Deflections and Stress Whether from reckless driving or simply not paying attention, there is a good chance you will impact a large, heavy mass of water at high speeds with your car. You may not realize it at the time but this unfortunate event not only produces excessive water splashing but it can also lead to significant structural damage around the underbody of your car. Large panel deflections can produce unwanted stress or contact between components. So, although counterintuitive, a vehicle’s underbody must be designed for impact. Engineers start the analysis by calculating high speed wading impact loads. These loads are then used as input conditions to predict underpanel deflections. The deflections correspond to mount point stresses which can lead to material fatigue and failure. The entire workflow is a coupled analysis called Fluid-Structure Interaction (FSI), and is essentially a two-part process with two separate simulation disciplines: CFD – A transient, multiphase (air/water) simulation calculates hydrodynamic pressure loads on the vehicle’s underbody as it wades (can include aerodynamic effects). FEA – Pressure loads are mapped onto a structural model and a Finite Element Analysis Solver is used to compute deflection, stress and strain of the underpanels and connecting components. Taming the Spray: Fortifying Durability and Component Protection We all remember childhood bike rides, drifting mindlessly between the road, sidewalk and puddles of rain. And it’s not until you are home when you realize that your back is completely soaking wet from the tire spray (more poor vehicle water management). Water spray from a BMX bike could be seen as an acceptable nuisance (or even kind of fun), however, water spray from a motorcycle or car must be taken more seriously. It can be corrosive, destructive or even dangerous. Fortunately, there are several ways simulation can help mitigate the impact of tire spray early in the design cycle before the vehicle hits the road. Driver Visibility & Safety Spray simulations help engineers design components like wheel arches, underbody panels, and mudguards to minimize spray, improving driver visibility and addressing aero-acoustic and aesthetic issues. Component Contamination A spray analysis can predict areas of high soiling on components like headlights, taillights, and radiators, allowing for optimized placement and the development of anti-adhesion coatings. Corrosion and Component Failure Dynamically simulating spray can also help engineers understand how corrosive substances like road salt affect vulnerable parts of a car or motorcycle over time, allowing for protective design measures. Camera and Sensor Degradation For Advanced Driver Assistance Systems (ADAS) and autonomous vehicles, a high-fidelity simulation can be critical for eliminating poor designs. Water droplet and film predictions help determine the optimal placement of cameras and sensors to minimize exposure to rain, mud, and dirt, and can aid in the design of effective cleaning systems. Ingress Protection of Electronics Ingress Protection (IP) Testing has become a critical part of modern vehicle validation as more electronics are packaged in exposed or splash-prone locations. Standards such as IEC 60529 and ISO 20653 define liquid ingress requirements for enclosures and road-vehicle electrical equipment (e.g. inverters, ECUs, sensors, battery pack housings, and connectors). It covers water-exposure scenarios that range from basic drip and spray protection (IPX1) to high-pressure, high-temperature washdown conditions (IPX9), representing progressively more demanding ingress protection requirements for automotive components. Simulation is particularly effective for studying these behaviors because ingress failures are often driven by highly transient, localized water motion rather than steady flow. Short-duration events such as splash impingement, and impact-driven exposure can be analyzed to understand water pathways and accumulation. Simulation can also reveal how water enters components like latch mechanisms, while assessing the impact of vent and drain placement and identifying where water accumulates and repeatedly wets critical regions. Optimizing Performance and System Functionality Bulk water simulations also fine-tune how water interacts with complex vehicle systems. Cowl Assembly Drainage and HVAC Ingress Control The cowl assembly plays a critical role in vehicle water management, acting as a primary collection and redistribution zone for rainwater, spray, and runoff from the windshield and hood. At the same time, it often houses or feeds sensitive systems such as HVAC air intakes, cabin air filters, wiper mechanisms, and electronic components. During heavy rain or car wash events, the cowl experiences highly transient inflow, localized pooling, and rapid drainage demands. Poorly managed water behavior in this area can lead to ingestion into air-handling systems, water accumulation near electrical components, noise issues, or long-term durability concerns. Simulation enables engineers to study these complex, time-dependent behaviors early in the design process. Transient water accumulation, overflow, splash-back, and interaction with grilles, screens, and drain paths can be visualized and quantified under repeatable conditions. This allows teams to evaluate cowl geometry, drain sizing and placement, and baffle effectiveness before physical prototypes are built. By understanding how water moves through the cowl under realistic loading scenarios, designers can reduce ingress risk, improve robustness, and avoid costly late-stage design changes. Hood and Tailgate Water Run-off Run-off from the hood, decklid, and tailgate is a key aspect of vehicle water management, as water naturally follows surface geometry and will migrate toward gaps, edges, and interfaces if not intentionally guided. During rain and car-wash conditions, water films and rivulets form on exterior panels and detach at edges, hinges, lamps, and latch regions. Simulation allows engineers to visualize these run-off paths under controlled conditions and evaluate features such as gutters, lips, channels, and drip rails that direct water away from openings and user touchpoints. This helps reduce water dumping during tailgate opening, limits repeated wetting of critical interfaces, and improves overall robustness before physical prototypes are built. Tank Sloshing Tank sloshing is a challenge in vehicle design, particularly in applications involving partially filled tanks such as fuel, coolant, or washer-fluid reservoirs. During braking, acceleration, cornering, or operation on uneven roads, liquid motion inside these tanks can become highly dynamic and chaotic. Uncontrolled sloshing can influence vehicle dynamics, introduce transient loads on tank walls and mounts, contribute to load shifting and slosh-induced roll moments, and generate noise. These effects are especially important in larger vehicles and systems where fluid volumes are significant and operating conditions vary widely. Simulation provides a practical way to study and manage sloshing behavior early in the design process. Engineers can evaluate the influence of tank geometry, fill level, and internal features such as baffles under repeatable driving scenarios. This enables rapid optimization of baffle layouts to improve vehicle stability, reduce transient structural loading, limit fluid-induced center-of-mass movement, and mitigate slosh-related roll moments before physical testing begins. Digital Drops, Real Impact Vehicle water management is an intricate challenge, extending far beyond the backyards and driveways of our daily lives, and practical solutions may not always be obvious. Water mitigation requires insight, creativity and innovation – all of which the Simcenter portfolio of software and services can help provide. With effective simulation, the unpredictable becomes calculable, transforming engineering from a reactive, trial-and-error process into a proactive, predictive science. Today’s engineers can innovate faster, build safer, and deliver more reliable products, ensuring a safer, drier, and more comfortable experience for everyone, regardless of the weather. Discover how simulation can transform the challenges of water management in vehicles into opportunities for innovation and performance. CAEXPERTS  can help your team apply advanced solutions with tools like Simcenter STAR-CCM+ to improve designs, reduce prototyping costs, and accelerate development. Schedule a meeting with our experts and see how to implement efficient simulations in your engineering process. WhatsApp: +55 (48) 98814-4798 E-mail: contato@caexperts.com.br

SIEMENS NX delivers the next generation of design, simulation and manufacturing solutions that enable companies to realize the value of the digital twin. NX for Design; Automate electrode design; Additive Manufacturing; Tool Design; Mold; Headquarters; Stamping; Generative Engineering; Direct and Synchronous Modeling NX NX is a flexible and powerful integrated solution that helps you deliver better products faster and more efficiently. It offers the next generation of design , simulation and manufacturing solutions that enable companies to realize the value of the digital twin. Supporting all aspects of product development, from conceptual design to engineering and manufacturing, NX offers an integrated toolset that coordinates disciplines, preserves data integrity, design intent, and streamlines the entire process. Contact an Expert NX for Design NX for manufacturing Automate electrode design Additive Manufacturing Tools and accessories design Mold design Progressive matrix design Stamping die design Generative Engineering The industry's most powerful, flexible and innovative product development solution, NX has the performance and features to help you get your product to market faster than ever before. Drive efficient end-to-end part manufacturing operations and deliver high-precision parts through digitalization. Program CNC machine tools, control robotic cells, 3D printers and monitor quality using one software system. Digitally transform your parts manufacturing business to gain productivity and increase profitability. The electrode design software application in NX simplifies electrode modeling and design for any tool design that requires electrical discharge machining (EDM). NX electrode design software offers a time - saving, step-by-step solution that automates the entire EDM process, from design to production. It even helps manage even the most complex and challenging electrodes. Industrialize additive manufacturing and create revolutionary products using our integrated software . Design, simulate, prepare, print and validate prototypes or production parts on a wide range of 3D printing equipment. Automate the design of associative molds, fixtures, and stamping and progressive dies using process-based design applications. Accelerate the entire mold development process, including part design, tooling design, and motion validation. Ensure rapid response to design changes and high quality molds. Improve productivity by automating the most tedious tasks and streamlining complex progressive die design processes. Use a comprehensive solution for free-form and straight-break sheet metal parts. Use advanced features to design automotive stamping dies, including formability analysis, die planning, die face design, detailed die structure design, and die validation. A generative design process is one that engineers can adopt to rapidly develop new products based on meeting design constraints. It is an iterative process that produces quick results that the engineer can refine through constraint variation to find the best design to meet the requirements. As companies face increasing pressure to get products to market faster, designgenerative is now a necessity in product development. Engineers, constrained by time constraints, often choose the first viable design over the ideal one. It is imperative that companies adopt tools that empower engineers to find the best design to meet requirements earlier in the development process in order to stay competitive. ⇐ Back to Tools

CAEXPERTS brings together an experienced and multidisciplinary team of CAE experts, prepared to deliver advanced engineering and computational simulation at different scales and levels of maturity. We use high-performance hardware and software resources that are scalable in the cloud. SIMULATION SPECIALISTS We are a team prepared to deliver results , innovation and competitiveness . Resquest for Quotation Areas of expertise Advanced Engineering Digital Twins Knowledge Transfer Assertive Solutions Cost Reduction R&D and Innovation Digitization of Engineering With the advancement of globalization and technological competitiveness, products and their manufacturing processes are increasingly complex , with more restricted life cycles . In response to this, vanguard companies use computer simulation to virtually test their projects, concepts, inventions, products, equipment and processes, in the most critical scenarios, seeking to always be ahead and go even further. SIEMENS Digital Industries takes this seriously and brings the broadest range of software tools for digitization and computer-aided engineering to the market . Know the Tools Discover the Disciplines Why CAEXPERTS CAE implementation As official resellers of SIEMENS Digital Industries software, we help your company build a high-performance CAE team for your engineering, combined with the ideal simulation tools in conjunction with our technical team, so that your production generates assertive results in an intelligent and fast way. We are simulation experts and know how industries can obtain a high return on their CAE investments. Engineering Services We help industries increase their competitiveness and raise their level of innovation. We work with projects and consultancy for the development of products and equipment, as well as conduct studies aimed at reducing Capital Costs and Operating Costs of industrial enterprises, owner engineering, R&D in industrial processes, integrity analyses and increased operational reliability of production assets. In addition, we are official resellers of Siemens software, which allows us to offer the best technological solutions to our customers. Conheça os nossos serviços Discover our Services Softwares ofertados Software Licensing 3D Multiphysics Simulation Simcenter 3D Star-CCM+ FloEFD Femap CAD Design Solid Edge NX 1D Systems Simulation Flomaster Amesim Electromagnetic Simulation and Design Magnet E-machine Design Speed HEEDS Optimization Learn more Why CAEXPERTS Professional Development: Program designed for engineers and professionals who want to master the use of computer simulation tools in real industry applications. Personalized: We work side by side, from the selection of relevant topics, the study of the state of the art, the scientific technical development stages, training until the completion of the project. Real Projects: The training is developed based on real industry challenges, providing applied and practical learning that prepares you for concrete challenges. Recognition: Master computer simulation in practice and become an expert valued by the industry. Discover our specialization program Areas of expertise ACOUSTICS ELECTROMAGNETIC COMPATIBILITY DESIGN OF ELECTRONICS CIRCUI S COMPUTATIONAL FLUID DYNAMICS THERMOFLUID DYNAMIC SYSTEMS WIRING AND WIRING HARNESS ELETRIC MACHINES STRUCTURAL ANALYSIS PROJECT OPTIMIZATION MATERIALS ENGINEERING ADDITIVE MANUFACTURING AUTOMATION Âncora 1 Know more Recent Posts 1 2 3 4 5 See it all Let's start Get in touch and find out why CAEXPERTS and the best solution for your company's engineering to go even further. Name Last name Email enter a message I agree to receive information and news by email To send Thank you!

Simcenter STAR-CCM+ computational fluid dynamics (CFD) software capable of running complex multiphysics simulations of products operating under real operating conditions. DEM particle flux; Electrochemical Simulation; Moving objects; Multiphasic; Reactive; Rheology; Drums; Motor; solids; Simcenter STAR-CCM+ Simcenter STAR-CCM+ is a computational fluid dynamics (CFD) software capable of running complex multiphysics simulations of products operating under real operating conditions . Simcenter STAR-CCM+ also incorporates design exploration and optimization technology as the basis of the simulation toolkit available to the engineer. The unique integrated environment includes the entire workflow from CAD, automated meshing, multiphysics CFD, sophisticated post-processing and design exploration. This allows engineers to efficiently explore the entire design space to make better decisions faster. The additional insight gained from using Simcenter STAR-CCM+ to guide your design process leads to more innovative products that exceed customer expectations. Contact an Expert Computational fluid dynamics simulation (CFD) Particle flow Project Exploration Electrochemical Simulation Moving objects Multiphase Flow Simulation Reactive Flow Modeling and Rheology Thermal simulation Battery simulation Co-simulation Electric machines Engine simulation Mechanics of Solids Simc enter provides industry-leading Computational Fluid Dynamics (CFD) software for fast and accurate CFD simulation of engineering problems involving the flow of liquids, gases (or a combination of both), along with all the associated physics. The discrete element method can be used to simulate the motion of a large number of discrete objects (particles) that interact with each other, such as the granular flow of aggregates, food particles, metal powders, capsule tablets, and wheat or grass. Simcenter is the first commercial engineering simulation tool to include a DEM feature fully coupled with numerical flow simulation. Design exploration software takes simulation to the next level, allowing users to determine appropriate variable values, thereby generating product designs that result in exceptional performance Significantly improving a battery design throughout its operating range is a challenging task and involves the simultaneous optimization of several parameters. Simcenter provides a complete simulation environment for electrochemical system analysis and design and detailed geometry of individual battery cells. Within a single CFD software environment , Simcenter empowers users to simulate not only a wide range of physics, but also a wide range of body and mesh movements to accurately capture their physics. With our motion models for CFD simulations, you can simulate the real-world performance of moving and overlapping objects with an overset mesh , predict the dynamic motion of bodies with 6 degrees of freedom, understand multiphysics interactions to model performance in operation, easily drive geometric changes for design exploration, easily predict machine behavior in rotation/translation, and define sophisticated motions to accurately replicate machine operations. Accurately representing the physical behavior of different fluid and solid phases is critical to capturing the real performance of your product. Simcenter offers a variety of Eulerian and Lagrangian modeling capabilities to meet your multiphase flow simulation needs. Gain insight into the interactions between the turbulent flow field and the underlying chemistry of reaction flows. Simcenter helps you to improve the balance between your device's performance and emissions for different operating conditions. Computational rheology is used to model non-Newtonian or viscoelastic materials in industrial problems. The module for rheology accurately solves the flow of complex rheological material and helps to predict its behavior under real operating conditions. Star CCM+ includes first-class, comprehensive thermal simulation capabilities that can help you understand your product's thermal characteristics and subsequently tailor your thermal management solution for optimal performance. Digitally validate cell design , including cell performance and geometric specifications with battery CFD simulation. Extensive battery cell components are available, as well as a materials database to support the user in model development using CFD analysis. Pair with other simulation tools through dedicated interfaces or an intuitive API. This enables multiphysics simulations with different time scales ranging from microseconds to thousands of seconds, providing faster, more accurate analysis and shorter turnaround times for developing and evaluating complex designs. Complete analytical models cover all aspects of electrical machine design, including thermal, electromagnetic, and drive control. Particularly important in this regard is the efficient use and even disposal of magnets. Our simulation tools are structured to provide seamless design capability across the full range of permanent magnet and reciprocating machines, including hybrid combinations, and cover the full range of power, voltage and speed used in vehicular systems. Engine simulations involve moving components, multiphase flow, combustion and heat transfer. You no longer need to be an expert user to simulate internal combustion engines: using an application-specific workflow and a streamlined interface, you can quickly and easily set up engine simulations. Experienced users can use these simulations as a starting point to perform more complex multiphysics engine simulations, exploiting the full range of Simcenter STAR-CCM+ simulation capabilities. Almost all real-world engineering problems ultimately depend on the interaction between fluids and solid structures. Simcenter STAR-CCM+ offers finite volume (FV) based computational fluid dynamics and finite element (FE) based computational solid mechanics (CSM) in a single, easy-to-use, integrated user interface. Using this approach, you can solve static, quasi-static, and dynamic problems, including those with nonlinear geometry and multiple parts using sliding and glued contacts. ⇐ Back to Tools