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Introduction Electrification is rapidly reshaping the commercial trucking industry, promising cleaner and more efficient transport solutions. Driven by new regulations [ 1 ], the electrification of heavy-duty vehicles (HDVs) and their trailers represents is essential to decarbonize freight logistics [ 2 ]. One emerging innovation is the electrified drive axle, or e-axle, integrated into heavy-duty vehicles (HDVs) and their trailers to provide regenerative braking and additional traction. But introducing this technology fundamentally alters the dynamic characteristics of the entire vehicle, bringing new challenges in vehicle stability, a critical safety aspect for heavy-duty trucks. Our recent simulation-based study dives deep into these challenges, analyzing how electrified trailers interact with existing vehicle control systems like ABS and ESP. The goal: to identify potential stability risks including jackknifing, shaking, and roll-over [ 3 ], and uncover how a smart supervisory control system could help ensure safe operation across all driving conditions. Methodology To investigate the complex dynamics of an e-trailer system, a detailed multi-body simulation model was developed using Simcenter Amesim . Simcenter Amesim is a powerful platform for multi-domain system simulation, enabling the modeling of mechanical, hydraulic, pneumatic, thermal, and electrical components within a single environment. 2.1 Vehicle Model Description The simulated vehicle configuration consists of a 3-axle articulated vehicle: a 2-axle tractor unit coupled with a 1-axle semi-trailer featuring an electrified drive axle. The multi-body template model VDCAR22DOF01 was employed, which is specifically designed to account for critical stability issues in articulated vehicles, including: Jackknife: The acute angle formed between the tractor and trailer. Shaking: High-frequency oscillations of the vehicle body. (Trailer swing) Roll-over: Lateral instability leading to vehicle overturning. Standard tractor and semi-trailer combination Tractor and semi-trailer combination with driven trailer electrical axles 2.2 Control Systems The model incorporates realistic chassis stability controllers for both the tractor and the trailer: Tractor Unit: Equipped with ABS (Anti-lock Braking System) and ESP (Electronic Stability Program) [ 4 ]. Trailer Unit: Equipped with ABS and TCU (Traction Control Unit). The e-axle’s regenerative braking and electrical traction capabilities are integrated with specific blending strategies. The interactions between these e-axle controls and the conventional chassis stability controllers are a central focus of the analysis. Simcenter Amesim model sketch Traction blending “parallel” strategy (e-trailer machine vs. truck engine) 2.3 Driver Model An advanced driver model, utilizing Model Predictive Control (MPC) techniques, was implemented. This robust control strategy ensures accurate path following and effective sway control of the trailer, providing a realistic representation of driver inputs during various maneuvers. 2.4 Test Track Definition The simulations were conducted on a virtual test track based on a real-world road section in Croix-Rousse, Lyon, France. This challenging route includes significant ascending and descending slopes, which are crucial for evaluating the e-axle’s performance during regenerative braking and traction phases. The varying gradients and curves allow for the assessment of vehicle stability under diverse load conditions and driving scenarios. Selection of the road path with the Route planning Tool, used in the Track Import Tool Visualization of the road track Results and Discussion The Simcenter Amesim simulations provided comprehensive data on electric machine performance, battery state of charge (SOC), and overall vehicle dynamics. Electric Machine Torque at trailer axle, and battery State Of Charge (SOC) 3.1 Electric Machine Performance and Battery SOC During the ascending sections of the test track (e.g., 0-150 seconds), the e-axle required significant traction torque to assist the tractor. Conversely, during important descending sections (e.g., 250-300 seconds), the e-axle effectively engaged in regenerative braking, leading to a notable increase in the battery’s SOC. This demonstrates the e-trailer’s potential for energy efficiency and reduced reliance on friction brakes. Rapid torque sign switches (from traction to regeneration) were observed before and after overcoming road cornering, indicating dynamic operation of the e-axle. 3.2 Vehicle Dynamics and Pathological Situations The simulations revealed several critical “pathological” situations that underscore the stability challenges introduced by e-axles. One such instance occurred during a combination of significant driver steering input and braking action, where a trailer wheel was observed to be on the verge of losing contact with the road. This scenario, if unmanaged, could lead to a roll-over event. A crucial observation pertained to the interaction between the electric machine controls and the chassis stability controllers. In certain cases, particularly during rapid torque switches or intense braking/traction demands, the individual actions of the ESP on the tractor unit, ABS on the trailer, and the e-axle’s torque control were not harmonized. The absence of a high-level supervisory control system to coordinate these conjoint actions was identified as a significant risk factor. Without such a supervisor, the study indicated that a complete instability of the truck + trailer vehicle could foreseeably occur at higher velocities, highlighting a critical safety concern. Trajectory, target velocity and steering angle 3.3 Implications for Control Strategy Development The findings emphasize that simply integrating an e-axle with independent control strategies for regenerative braking and traction is insufficient. Effective integration requires a sophisticated, higher-level supervisor that can intelligently blend the e-axle’s operations with the conventional chassis stability controllers. This supervisor would need to dynamically adjust torque distribution, braking effort, and traction forces across all axles to maintain overall vehicle stability under varying road conditions, driver inputs, and e-axle operational modes. Chassis controller status (ESP and ABS) Conclusion The findings from this study highlight a key takeaway: electrified trailers hold great promise, but they require sophisticated coordination between new and legacy control systems to keep trucks stable and safe. A high-level supervisory control system is essential to avoid dangerous scenarios such as wheel lift and rollover, especially at highway speeds. If you’re involved in vehicle design, control system development, or fleet safety management, this research offers valuable insights to guide your work. Staying ahead in the electrification journey means embracing integrated solutions that prioritize stability. Referências [1] United Nations Economic Commission for Europe (UNECE). Global Forum for Road Traffic Safety (WP.1). Available at: https://unece.org/transport/publications/consolidated-resolution-road-traffic-re1 [2] European Automobile Manufacturers’ Association (ACEA). Commercial Vehicles: Decarbonisation. Available at: https://www.acea.auto/fact/commercial-vehicles-and-co2/ [3] G. G. P. Van Der Heijden, H. B. Pacejka, and J. M. J. Van Der Knaap, “Dynamic behaviour of articulated vehicles,” Vehicle System Dynamics, vol. 20, no. sup1, pp. 294-307, 1991. (General reference for articulated vehicle dynamics, not specific to e-trailers, but foundational). [4] Bosch Global. ABS and ESP: The history of vehicle safety. Available at: https://www.bosch-mobility.com/en/mobility-topics/safety-for-all-road-users/driver-assistance-systems-for-commercial-vehicle/ Want to understand how simulation can support the safe development of electric trailers and advanced control strategies? Schedule a meeting with CAEXPERTS and talk to our experts about how to apply Simcenter Amesim to assess stability, integrate control systems and reduce risks from the early phases of the project. WhatsApp: +55 (48) 98814-4798 E-mail: contato@caexperts.com.br

The new Simcenter FLOEFD 2512 software release as of December 12, 2025 is now available in all its CAD-embedded CFD variants, and also the Simcenter 3D embedded variant. This release delivers focused improvements for fast sealing of geometry for internal flow analyses for all general purpose CFD applications through to multiple enhancements for electronics thermal analysis workflows. Please read on below to explore every new feature grouped under key Simcenter pillars, or scan the topic list on the left hand side to shortcut to the sections that interest you most. Auto-sealing of CAD geometry for internal flow CFD analysis There are many reasons for performing internal flow CFD simulations depending on modeling application or computational efficiency. For any internal flow scenario, you want to seal geometry as quickly and efficiently as possible For complex CAD assemblies with hundreds or thousands of parts, this can become a time consuming challenge to make the geometry watertight. You spend your time first, locating gaps and openings, and then sealing them manually with geometry. Such approaches also mean you are making modifications or additions to the CAD model that need to be tracked and removed before you hand back modified product geometry to design and manufacturing teams after you finish your analysis tasks. CFD tools typically have features or utilities to help you. Simcenter FLOEFD users will be familiar with Simcenter FLOEFD’s existing automatic fluid volume recognition strengths and tools such as “leak tracking” to identify paths between faces which is helpful in many instances. In Simcenter FLOEFD 2512 , a step change in auto-sealing for internal flow CFD tasks has been delivered to engineers in the form of enhancements to “Close Thin Slots” and “Fill Thin Slots”. This feature is accessible when you are utilizing Mesh Boolean approach to geometry handling and meshing, that is particularly suited to complex assemblies and varying quality found in CAD models. You can now retrieve the internal fluid region automatically for non-watertight models more easily, efficiently, and without altering CAD geometry. How do you control this new automatic mesh-enabled sealing ? Users configure “Fill Thin Slots” approach in 2 ways starting from the ribbon bar: Within the mesh group, select either global mesh or local mesh and then in mesh settings you activate close “Close Thin Slots”  then specify the “Maximum Heigh of Slots to Close” and other parameters.ers. Within the Insert group, select Source> Fill Thin Slots which opens a dialog. You then select in the graphic area faces on either side of the slot, or choose relevant bodies to consider their faces Set Solid material set the desired material (or allow the default setting). Set the parameter for “Maximum Heigh of Slots to Close” Choose between options: Fill Thin Slots only ( A conservative approach where solid material is applied within the slot) Fill within slots and openings (A default approach that is a more comprehensive sealing approach where solid material is applied in the slot and also extends into the fluid domain by one computational mesh cell to seal the opening fully) Additional notes: Simcenter FLOEFD chooses material properties from nearby to the gap to preserve close thermal model accuracy, or alternatively users can set a default value. There is an option in the mesh viewer to view where where cells are inserted by selecting a mesh plot of “closed thin cells”. How do you seal thin gaps in assemblies to prepare CAD geometry for CFD internal flow studies? Find out about the new approach in Simcenter FLOEFD 2512 by watching this short video on how seal an automotive lighting CFD model for thermal analysis where there are many gaps to seal in the CAD assembly for an internal flow case. The approach uses the method starting from the “Fill Thin Slots” dialog opened from the insert group Sources>Fill Thin Slots in the ribbon. It also shows how you can view where solid material cells are added using using the mesh viewer. Faster BCI-ROM extraction: Setting specific HTC ranges A new way to set specific heat transfer coefficient (HTC) ranges has significantly shortened the reduced order model extraction time for BCI-ROM models. Below are results comparisons for one example model where setting suitable ranges of HTC for each boundary condition is compared to setting a single common range value. In this case, extraction is 8 times faster and memory peak usage was more than halved. Shorter solve time for your models with thousands of two-resistor (2R) or Network Assembly components Thermal engineers frequently leverage components modeled as two-resistors (2R) or Network Assemblies in their models. Calculations for models with hundreds or even thousands of these is now much faster through software optimization implemented in Simcenter FLOEFD 2512 release. This enables the preparation stage of analysis to take significantly less time and use less memory. A Simcenter FLOEFD model containing DIMM memory card assemblies on a motherboard with components modeled as two-resistor (2R) type components. Download Simcenter FLOEFD 2512 and evaluate your own models with 2R and Network Assembly components to see what kind of speed you can get. For one example model, containing many 2R components, a comparison was carried out with the results shown below. A speed-up by a factor of 6 was realized for the solver time compared to the prior 2506 release and a significant reduction in peak memory usage achieved by a factor of more than 3 and a half. A useful update to scripting in EDA Bridge for PCB data processing To reduce time correcting script errors that are typically only discovered at runtime when transferring from EDA Bridge to Simcenter FLOEFD that force project restarts, scripts are now validated before running to catch errors and prevent disruption. Reduced order modeling: BCI-ROM support for 2R and Network Assembly components Boundary Condition Independent-Reduced Order Models are reduced order models that operate in any thermal environment and are extracted from a 3D conduction-only model in Simcenter FLOEFD . It is now possible to extract these from 3D electronics thermal analysis models that contain 2R and Network Assembly components. As a recap on BCI-ROM model formats that you can generate in Simcenter FLOEFD : – matrices (for standalone solution) – FMU format (for system simulation use in accordance with FMI standard) – VHDL-AMS format (for circuit simulation electro-thermal modeling use) Accurate radiation modeling: Henyey-Greenstein phase function Simcenter FLOEFD has a proven history of radiation modeling for lighting applications. In the Simcenter FLOEFD 2512 release, the Henyey-Greenstein phase function has been added that enhances accuracy for modeling scattering in certain semi-transparent materials. (This is accessible via the Simcenter FLOEFD Lighting module) You select this option and define scattering coefficients in the item properties menu. A simple comparison using basic model and source and then changing the scattering coefficient value of a plexiglass material illustrates scattering below. Easier sub model re-use: Rebuild of sub-projects “From component” Many Simcenter FLOEFD users work with sub models. The previous 2506 release delivered capabilities to define project parameters in sub projects so they propagate upward into your main CFD model. Building on that release and efforts to deliver more library driven re-use of components and sub projects, in the new 2512 release there is now a built-in function to select rebuild of all sub-projects at the same time when this is required. This eliminates time overhead of manual rebuild of each sub project. View tabular results: maximum temperature column in Component Explorer If you are working with a complex thermal model and want to more quickly retrieve maximum temperatures of all components you can now do so in Component Explorer (as a convenient alternative to assigning many Volume Goals) . A new column provides maximum temperatures of all solids with minimal effort and does not slow down the solver. You can also export value to Microsoft Excel. You can also export a useful matching table of component names, input data and resulting maximum temperatures automatically leveraging Batch Results Processing. As a reminder, Component Explorer received significant updates in the 2412 release (LED and 2R model creation, surface power listing/summation and more) and 2506 (status and temperature column) release, so please do go back and review prior release blogs and documentation. Updated FMU graphical editor makes connections clearer Users are starting to leverage multiple FMU based components in their Simcenter FLOEFD projects more and more since the introduction of “FMU as a feature“. To aid the understanding of the connections to the project and to connect multiple FMU’s to each other more easily, an FMU graphical editor has been introduced. You can more easily map goals to inputs and interpret connectivity between FMUs as complexity increases. Automation in Simcenter FLOEFD 2512: Added new capabilities in EFDAPI Automation of simulation tasks continues to be a popular topic with users. EFDAPI, the API introduced back in  Simcenter FLOEFD 2312 , continues to be developed based on consistently received user feedback. Key new EFDAPI capabilities added in Simcenter FLOEFD 2512 : Switch geometry recognition to Mesh Boolean Apply default radiation surface Switch between Global and Face coordinate systems For NX users performing PCB thermal analysis: PCB Exchange – EDA Bridge integration update For customers using Xpedition and NX CAD software, there are linkages for close MCAD-ECAD collaboration enabled by PCB Exchange.  As of this release, you can now author the set up of a PCB thermal simulation for Simcenter FLOEFD for NX , right from within the PCB Exchange workflow. This incorporates the ease of PCB data processing for thermal modeling purposes using EDA Bridge accessed through its integration into PCB Exchange. Components and libraries: XTXML export of features (for 2R and Network Assembly) XTXML export for component editing was introduced in the last 2506 release which allows users to import models from Simcenter FLOEFD Package Creator utility, make adjustments to the models and then save the models in XTXML format to libraries. Manually created detailed models can also be exported in XTXML format. The Simcenter FLOEFD 2512 enhancement now has the option to export models of 2R and Network Assembly components. This enables you to build up a component library quickly. A note for CATIA V5 users. You can now edit XTXML files exported from Package Creator or create new XTXML library items with Simcenter FLOEFD for CATIA V5, as was introduced in version 2506 for other variants. Avoid the risk of losing EDA files To reduce the risk of losing EDA files from EDA Bridge for your many projects, often stored in separate folders, an option has been introduced to store EDA files nested to the main assembly. So users can choose from 3 options in settings now: 1) Model folder – files are stored next to main assembly (default option) 2) Sub-folder – files are in a separate folder next to main assembly 3) Specify – choose permanent path to the folder Want to apply these new features of Simcenter FLOEFD to your own models and gain momentum in your next simulations? CAEXPERTS can show you, in practice, how to use the new automatic cooling features, thermal resource optimizations, and model hydration to reduce setup effort, solution time, and memory usage. Schedule a quick meeting with our team and see how to extract maximum performance from your CFD and thermal analyses. WhatsApp: +55 (48) 98814-4798 E-mail: contato@caexperts.com.br

Simcenter Systems Simulation 2511  has just been released, introducing new capabilities that accelerate innovation across industries such as automotive, aerospace, heavy equipment, and turbomachinery. This latest version empowers engineers with smarter modeling workflows, AI-based documentation assistance, and enhanced productivity in Simcenter Amesim , Simcenter Flomaster , and Simcenter System Analyst. Together, these updates help users work faster, manage greater complexity, and seamlessly integrate simulation throughout the product development lifecycle. Simcenter X This release reinforces Simcenter Systems as a key pillar of Siemens’ digital transformation strategy, with continued focus on cloud enablement, AI-driven assistance, and user productivity across system simulation workflows. Simcenter Amesim can now also be offered as part of Simcenter X , Siemens’ flexible Software-as-a-Service (SaaS) multi-domain simulation suite. Simcenter X Advanced combines the trusted capabilities of Simcenter Amesim with the power of cloud entitlement, empowering teams to simulate multi-physics systems with scalable performance and instant access through a cloud-managed desktop. Simcenter X Advanced – Cloud-managed desktop Simcenter X Advanced offers a secure, cloud-managed desktop that enables users to access Simcenter Amesim without the burden of license setup and management. This deployment option simplifies IT administration, accelerates onboarding, and scales efficiently across distributed engineering teams. Simcenter X AI Chat Assistant – Instant answers, built into the cloud environment For customers using Simcenter X Advanced , the integrated AI chat assistant delivers contextual answers with direct links to documentation. Supporting multiple languages helps teams find information faster, streamline troubleshooting, and remain productive across global simulation environments. Simcenter Systems 2511 The Simcenter Systems 2511 release strengthens the portfolio with key improvements in electrification, cloud accessibility, and user experience. Engineers benefit from enhanced modeling accuracy, faster setup, and improved visualization features that support system-level design across industries. From streamlined parameter management to more efficient simulation workflows, Simcenter Systems 2511 empowers users to innovate with greater speed and confidence. Electrification Electrification remains a driving force in the Simcenter Systems portfolio, and this release continues to expand capabilities for battery modeling, integration, and optimization. With Simcenter Amesim 2511 , engineers can now design and validate battery packs more efficiently, leveraging improved workflows for parameter import and thermal management. These innovations support electric vehicle (EV) and energy storage applications, helping teams accelerate the transition toward sustainable and high-performance electrified systems. Battery Battery pack assistant – Seamless electrical parameter integration Defining accurate battery cell parameters can often be tedious and prone to error. With Simcenter Amesim 2511 , part of the Simcenter Systems Simulation portfolio, battery designers and integration teams can now automatically import cell electrical parameters directly from a validated database or an existing model into the battery pack assistant. This new capability streamlines the setup process, ensuring that simulations start from trusted data while minimizing manual input errors. Engineers can reuse existing models, resize them efficiently to match target capacity, and evaluate pack architectures earlier in the design cycle, all within a unified battery design environment. Whether applied to EV battery modeling or stationary energy storage systems, this update accelerates pack design and improves accuracy. Battery pack assistant – Capture heat gradients where they matter most Controlling temperature gradients within a battery pack is crucial for ensuring safety, optimal performance, and extended durability. In Simcenter Amesim 2511 , the battery pack assistant introduces a new capability that allows users to thermally discretize pattern groupings in any direction (X, Y, or Z) to better capture critical heat variations across packs. This flexible approach enables engineers to model a wide range of cell technologies, from prismatic to blade cells, adapting the size and orientation of thermal discretization to each design’s unique behavior. With just one click, users can generate detailed thermal models that accurately reflect real-world gradients, ensuring accurate simulation results. For battery designers and integration teams working in the automotive, mechanical, or energy storage sectors, this enhancement provides the control needed to refine thermal management strategies and improve the accuracy of electrification simulation workflows. Chassis engineering Electric motorcycle demo model – Analyze ride and handling with ease Designing an electrified motorcycle chassis that strikes a balance between ride and handling performance can be a complex process. With Simcenter Amesim 2511 , engineers now have access to a new electric motorcycle demo model, built using the 3D mechanical library and integrated with vehicle dynamics driver models. This demo serves as a fully modular starting point for creating and analyzing electrified motorbike architecture. Users can quickly explore different layouts and optimize the position of heavy components, such as the battery pack and e-motors, to ensure stability and control across varying speeds and trajectories. The real-time capable model helps motorbike manufacturers and suppliers study ride and handling dynamics in curves, evaluate design trade-offs, and accelerate development from concept to validation. Ground designer – Create a batch from parameters Testing vehicle behavior across different roads and terrain conditions is crucial for accurate chassis engineering. In Simcenter Amesim 2511 , the new ground designer batch feature introduces the ability to generate virtual proving grounds with multiple obstacle heights, shapes, and spacing, all defined through customizable parameters. This update enables engineers to create batch runs directly from any parameter in the ground designer, allowing for quick exploration of numerous test scenarios and geometries. The result: faster analysis cycles and deeper insights into vehicle dynamics performance on parametric 3D proving grounds. With this capability, automotive, off-road, and heavy equipment engineers can easily optimize suspension, stability, and control systems under varied conditions, boosting the efficiency and realism of vehicle simulation workflows. E-motors Squirrel Cage Induction Machine (SCIM) – Enhanced electro-thermal modeling Designing high-power-density electric drivetrains requires a precise understanding of thermal behavior and magnetic effects. The enhanced squirrel cage induction machine (SCIM) model in Simcenter Amesim 2511 introduces detailed loss definitions and non-linear inductance support for accurate electro-thermal simulations. This update enables engineers to analyze temperature-dependent losses that directly impact e-powertrain performance, helping to refine thermal management strategies and enhance system reliability. Through comprehensive modeling of DC, AC, and iron losses, the new SCIM component supports more accurate sizing, efficiency predictions, and component optimization. Whether used in automotive, aerospace, or industrial applications, this upgrade empowers powertrain engineers to push performance limits with greater confidence and precision. Energy and thermal management Efficient thermal management is crucial for maintaining performance and safety in electrified systems. In Simcenter Amesim 2511 , new capabilities within the Heat Exchanger Assistant simplify model generation and provide early design insights to help engineers optimize HVAC and cooling systems faster. Heat exchanger assistant – Streamline your HVAC heat exchanger design Creating detailed heat exchanger models can be time-consuming and prone to errors. In Simcenter Amesim 2511 , the heat exchanger assistant receives a significant enhancement with new capabilities that expand the range of supported geometries, including fin-and-tube and multi-core micro-channel heat exchangers. Engineers can now generate complete parameterized models with integrated 2D/3D visualization more efficiently. The updated assistant also introduces automatic sketch generation for multi-core micro-channel designs, helping HVAC and thermal engineers iterate faster and maintain consistent model structures. By simplifying model creation and providing real-time geometric feedback, this enhancement accelerates early-phase heat exchanger design and improves modeling confidence. Heat exchanger assistant – Early heat exchanger size and mass assessment Late-stage adjustments to heat exchanger dimensions or weight can lead to costly redesigns and delays. With Simcenter Amesim 2511 , engineers can now evaluate the size and mass of heat exchangers directly in the geometry definition phase, using the heat exchanger assistant. This enhancement provides real-time insights into packaging feasibility and component weight before running simulations, allowing teams to validate designs against system requirements earlier in the process. By integrating mass and dimensional data at the geometry stage, thermal engineers can make data-driven decisions faster and ensure alignment with performance targets and packaging constraints. Hydrogen Hydrogen continues to play a pivotal role in enabling clean propulsion and sustainable energy systems. With Simcenter Amesim 2511 , engineers gain new modeling tools that simplify the design and integration of fuel cell and cryogenic storage systems, helping industries such as aerospace, marine, and automotive explore the future of zero-emission powertrains. Fuel-cell turboprop demonstrator – Integrated gas, liquid, and hydrogen modeling Designing and validating an aircraft fuel-cell system requires accurate modeling of gas, liquid, and cryogenic hydrogen interactions across multiple components. The updated fuel-cell turboprop demonstrator in Simcenter Amesim 2511 provides a ready-to-use model that shows how to configure the required fluid species and phases using the common framework shared by the gas and fluid storage libraries. This demonstration gives engineers practical insight into cryogenic tank behavior, Boil-off gas (BOG) management, and fuel-cell operation throughout an entire flight cycle. It highlights how individual subsystems such as the cryogenic storage system, the fuel cell stack, and associated balance-of-plant (BoP) components interact within a complete aircraft configuration. Simcenter Amesim 2511 also introduces an improved hydrogen aging model, enabling engineers to evaluate long-term performance decay and its impact on power output, efficiency, and mission range. Together, these enhancements accelerate system-level validation and reduce setup time for hydrogen-powered aircraft studies. Strengthening the core Beyond electrification and hydrogen innovation, Simcenter Systems Simulation 2511 also strengthens its foundation with improvements that enhance accuracy, interoperability, and productivity across the modeling environment. These updates help engineers build, manage, and analyze system models more efficiently, whether they’re optimizing pneumatic and gas systems, working with advanced libraries, or improving collaboration through tighter version control. With new capabilities across both Simcenter Amesim and Simcenter Flomaster , including enhanced simulation libraries, improvements to turbomachinery modeling, and strengthened Git integration, Simcenter Systems Simulation 2511 reinforces the robustness and scalability of the platform for all industries. Gas library – Build scalable and accurate gas systems Modern gas systems require precise control, reliable modeling, and strong scalability, especially in automotive, aerospace, and industrial applications. The new gas library in Simcenter Amesim 2511 introduces a unified, real-time-capable framework that replaces multiple legacy pneumatic and gas libraries, offering greater accuracy, consistency, and flexibility. This next-generation library integrates industry-standard modeling capabilities, including ISO-6358 compliant components and Redlich–Kwong–Soave (RKS) equations of state, enabling engineers to simulate compressible flows and advanced gas behavior with improved fidelity. The library is also fully compatible with real-time export, making it suitable for hardware-in-the-loop (HiL) applications and control system validation. By consolidating and modernizing the modeling workflow for gas systems, the new gas library helps teams build, maintain, and scale large multi-domain system models more efficiently and with higher reliability. New help system – Faster access to smarter documentation Accessing technical documentation efficiently is critical for simulation engineers. The new browser-based help system in Simcenter Amesim 2511 delivers a modernized and more intuitive documentation experience. With enhanced search capabilities, familiar navigation categories, and integrated web features such as zoom, bookmarks, translation, and history, users can now find information more quickly and easily. The new help platform also offers seamless integration with Simcenter Amesim , allowing engineers to directly access relevant documentation without interrupting their workflow. NX Diagramming XML import – Simplify system model creation For fluid system engineers working on complex piping networks, CAD tools are often used to define the initial layout of 2D diagrams. However, transferring these definitions manually into a system simulation environment can be time-consuming and error-prone. The new NX Diagramming XML import capability in Simcenter Amesim 2511 bridges this gap by allowing users to automatically generate system models directly from NX Diagramming files. This functionality enables engineers to rapidly create 2D piping network definitions inside Simcenter Amesim , ensuring seamless interoperability between CAD tools and system simulation. By eliminating repetitive manual work, it accelerates model setup and provides a smoother transition from early design to performance validation, benefiting industries such as energy, oil and gas, marine, aerospace, and process engineering. 3D Scenes – Enhanced visualization for model setup and analysis Understanding model behavior visually can dramatically improve accuracy and productivity. The new 3D Scenes tool in Simcenter Amesim 2511 introduces an advanced 3D visualization environment that enables engineers to interact directly with simulation models, whether it be during building or in the simulation phase. This enhancement enables users to set parameters effortlessly by interacting with 3D objects, gain a better understanding of the system before running simulations, and interpret physical quantities through clear visual cues. With two distinct 3D viewing modes available, engineers can visualize model states before and after simulation, enabling them to validate configurations and identify potential modeling issues early. By providing intuitive visualization and interactive parameter control, the new 3D Scenes feature empowers system simulation engineers across industries to make faster, more informed design decisions. Test Execution Manager – Compare reports side by side As simulation models evolve, engineers often need to validate changes, compare results across versions, or assess the impact of updates to libraries and model parameters. Manually comparing outputs from different runs can be tedious and error-prone, especially when handling large datasets or complex systems. The enhanced compare-report feature in the Test Execution Manager streamlines this process by displaying two reports side by side in a clear, structured table. Differences in parameter values, simulation outputs, and timeseries data are automatically highlighted, making it easier to pinpoint what changed between two executions. This capability improves productivity by reducing the manual effort required for regression testing and model validation. It also strengthens traceability and transparency across simulation runs, helping engineers understand the impact of updates more quickly and make better-informed decisions. Client for Git – Large File Storage (LFS) The Large File Storage capability in Simcenter Client for Git keeps repositories lightweight by storing large files in a dedicated area. This speeds up uploads, removes file-size limits, and enhances version control efficiency. Client for Git – Delete branches from server collections As simulation projects evolve, Git collections often accumulate numerous branches — many of which eventually become outdated or unused. These obsolete branches take up server space, clutter the project history, and make it harder for teams to navigate active development lines. With Simcenter Client for Git in the 2511 release, users can now delete branches directly from server collections. This capability makes it easier to remove unnecessary or obsolete branches at the source, helping teams keep their repositories lean and better organized. By decluttering the repository, server collections become smaller and more efficient, improving performance during repository operations. It also supports better project hygiene by maintaining a cleaner and more understandable version history. Overall, this enhancement enables engineering teams to manage their branches more effectively and maintain a streamlined, professional version-control workflow. Turbomachinery simulation improvements Meeting today’s efficiency and performance targets in turbomachinery requires highly detailed and integrated modeling capabilities. As systems grow more complex, traditional approaches often struggle to capture the full dynamics of rotating components, secondary air flows, and co-simulation behaviors across tools. Simcenter Flomaster 2511 introduces several targeted enhancements to address these challenges. Internal duct and forced vortex components have been upgraded to support turbine speed data directly, enabling more realistic and precise modeling of rotating secondary air systems. A new flow-tracking capability now enables engineers to visually trace which inlet sources contribute to the flow at any given outlet, providing deeper insight into system behavior and helping to accelerate diagnostics. Additionally, FMU export has been reinforced with support for implicit iterations and improved error handling, resulting in more robust co-simulation with Simcenter 3D Thermal . Together, these improvements deliver more accurate turbine speed modeling, clearer flow-origin identification, and smoother integration into whole-engine digital workflows, supporting faster decisions and more reliable development of high-efficiency turbomachinery systems. Want to understand how Simcenter Systems Simulation can accelerate innovation, reduce the complexity of your projects, and increase the productivity of your engineering? Schedule a meeting with CAEXPERTS and discover, in practice, how to apply these advanced simulation resources to your challenges in electrification, thermal systems, hydrogen, and much more. WhatsApp: +55 (48) 98814-4798 E-mail: contato@caexperts.com.br

Capture the real-world complexity with multi-domain simulation using Simcenter X Advanced Designing complex engineering systems, such as a gas turbine, are often long-time projects where many iterations and extensive collaboration across teams, departments or organizations are needed. The traditional approach is often characterized by siloed domain workflows which additionally cost time and effort. With Simcenter X Advanced , a flexible, Software as a Service (SaaS) multi-domain engineering simulation suite, we provide you with one-license access to a comprehensive and integrated multi-domain simulation solution portfolio to address multidisciplinary complexity in one environment. Simcenter X Advanced effectively breaks down engineering silos enabling robust, physics-based, AI-augmented decision-making across multiple domains to deliver innovative and dependable engineering solutions faster. A tribute to gas turbine technology The really great thing about gas turbines, besides their beauty, is the flexibility of applications the core technology can be applied to. Gas turbines can be found everywhere in our modern daily lives, as heart for sustainable and reliable power generation, as drives in various industrial, chemical or maritime applications or designed as aircraft engines in nearly every commercial or military aircraft. Although the technological idea of a gas turbine is not new and its first applications went back to early 1900, it is still an amazing technology which we can see every day and everywhere and it affects all our lives, even if we don’t know. And today, more than 120 years later, designing a gas turbine has not become a less complex engineering challenge, independently if designed for just a few kilowatts, for hundreds of megawatts as stationery or flying applications. Designing a gas turbine is an artful interplay of physics and covering multidisciplinary engineering challenges. Since 120 years, gas turbines have marked the spearhead of engineering innovation Gas turbine development and innovation are driven by ultimate targets to become cleaner, bigger, more silent and flexible. Reducing emissions and enhancing thermal cycle efficiencies have and will remain to be main drivers of new generations of gas turbines. Since decades aero engine and gas turbine manufactures are pushing the Bryton cycle towards higher efficiencies with improvements in materials, coatings, cooling technologies, combustion and more. Faster and closer cross-domain collaboration will be the next crucial factor enabling comprehensive cross-domain and cross-disciplinary design studies to uncover and unleash hidden potential. The only limit? Carnot! Simcenter X Advanced enables integrated multi-domain simulation engineering to design a micro gas turbine Power outages, while often brief, can severely impact critical infrastructure like hospitals and data centers. To ensure uninterrupted operation, robust emergency power units (EPUs) are essential and can ultimately even decide about life and death. To fulfill their purpose, these systems, often relying on fast-starting gas turbines, need to kick in within seconds. Hybrid EPUs, combining microturbines with battery storage, offers a powerful solution, with batteries bridging the startup time and providing immediate backup. When an emergency power unit needs to take over, there is usually no acceptance for failure. Imagine, in case of a hospital or intensive care unit power backup, it even becomes live critical. An emergency power unit (EPU) is a complex multidisciplinary engineering system. A system in which various elements need to interact to provide a reliable and functional system which can operate on point, as expected, when expected and in its best-balanced performance. Break down engineering silos and boost engineering productivity Emergency power units (EPU) have one ultimate goal, they must work reliable and provide power as expected in the case of cases without any option for failure. To design an EPU systems engineering is key to size the entire EPU modules and simulate the case scenarios. System modeling allows tailored engineering towards the application cases and provides the necessary physics-based parameters that are essentially needed for sizing the integrated modules or subsystems such as the gas turbine package. Within Simcenter X Advanced engineers have direct access to powerful Simcenter system solutions such as Simcenter Amesim , which allow a comprehensive system design. In This example, the EPU has an integrated 100kW micro gas turbine. By applying the gas turbine performance application within Simcenter Amesim , engineers can directly specify the architecture of the micro gas turbine and extract relevant pre sizing design parameters for the main gas turbine components. Multi-domain engineering solves multidisciplinary challenges best Designing the micro gas turbine requires a comprehensive interplay between different technical disciplines and various multi-domain simulation techniques. As an example, flow path components which have been perfectly designed towards aerodynamic performance need be checked against their to be manufacturability but also need to be checked if they are able to withstand the transient loading during operation. Thus, structural integrity investigation need to go hand in hand with aerodynamic design considerations to be most effective and to avoid unneeded iterations. But even if the single components fulfill all requirements towards aerodynamic and structural performance, the assembly may operate in safety risk condition, e.g. due to rotational resonance. Simcenter provides a comprehensive multi-domain simulation portfolio that ideally supports turbomachinery engineers to consider all those dependencies and multi domain challenges within one CAE environment. Simcenter X Advanced provides you multi-domain simulation access to Mechanical, Computational Fluid Dynamics (CFD), Systems simulation and Multidisciplinary Design Analysis and Optimization (MDAO) under a single license Design and validation of gas turbines, from early system level via component to entire whole engine modeling. With Simcenter X Advanced , engineers get now ultimate access to a comprehensive multiphysics CAE platform via one license. With integrated PLM connectivity and data management the digital thread is not a vision anymore, with Simcenter X Advanced it becomes real. When failure is not an option: Multi-disciplinary engineering excellence with Simcenter X Advanced In the demonstrative study “When failure is not an option: Designing a micro gas turbine in context of emergency power generation”, Simcenter X Advanced for multi-domain simulation put to the test. The result: A real world engineering example of an end-to-end design workflow established with Simcenter X Advanced . system and architecture design of EPU and gas turbine sub model aerodynamic design and validation of compressor and turbine AI accelerated optimization of rotor shaft design structural design and validation of compressor, turbine and rotor rotor dynamic and self-excitation investigation, automatic creation of Campbell diagram fluid-structure co-simulation for automated cold-to-hot transformation and operational gap clearance investigation Want to understand how Simcenter X Advanced  can accelerate the design and validation of complex systems like gas turbines and EPUs, unifying all disciplines in a single environment? Schedule a meeting with CAEXPERTS  and discover, in practice, how to take your multi-domain engineering to a new level of performance and reliability. WhatsApp: +55 (48) 98814-4798 E-mail: contato@caexperts.com.br

Cement production is one of the most energy-intensive and emission-intensive industrial activities, accounting for approximately 5% to 8% of global CO₂ emissions. In the modern dry manufacturing process, the pre-calciner plays a central and critical role, being the equipment where most of the limestone calcination occurs (decomposition of CaCO₃ into CaO and CO₂) and where between 55% and 65% of the system's total fuel is consumed. The efficiency of this equipment depends on a delicate thermodynamic balance between two main reactions: fuel combustion (exothermic process) and raw material decomposition (endothermic process). Due to the complexity of multiphase flow, where solid and gaseous phases interact at high speeds and temperatures, physical experimentation on an industrial scale is extremely costly and often impractical for detailed internal measurements. In this context, Computational Fluid Dynamics (CFD), with STAR-CCM+ , emerges as an essential tool for the optimization and design of these reactors. Through numerical modeling, it is possible to predict the hydrodynamics of the flow, heat transfer, chemical kinetics, and emissions, critical factors that act in the pre-calciner. Challenges and Solutions in Pre-calciner Simulation CFD simulation of pre-calciners presents challenges associated with the multiphase, thermal, and reactive complexity of the process. The cohesion and agglomeration of fine raw meal particles significantly alter the flow and calcination efficiency, requiring advanced particulate phase models. On a larger scale, the formation of gas-solid clusters introduces heterogeneities that render homogeneous drag models inadequate. Heat transfer constitutes another critical point, due to the very thin thermal boundary layers along the walls, whose correct mesh refinement is unfeasible in complete industrial geometries. As a solution, coupling CFD with simplified mechanistic models allows for realistic thermal estimates with reduced computational cost. Furthermore, the strong coupling between exothermic and endothermic reactions imposes high nonlinearity on the system. In the context of emissions reduction, oxy-fuel combustion presents additional challenges, such as ignition delay and high CO₂ concentrations, which can be mitigated by multi-stage combustion and pre-gasification strategies, ensuring operational stability and low NOx levels. CFD Simulation of the Pre-calciner This numerical simulation study, developed in STAR-CCM+ , focuses on the detailed analysis of combustion in a large-scale cement pre-calciner, emphasizing the evaluation of the characteristics of the oxy-fuel process and its impacts on the thermal efficiency and operational stability of the equipment. The modeling was conducted using a non-premixed combustion model, incorporating the chemical kinetics of coal, devolatilization phenomena, NOx formation, and thermal radiation effects. The kinetic mechanism employed is presented in Table 1. It should be noted that, in this study, the particulate model of calcium carbonate (CaCO₃) was not considered, focusing the analysis exclusively on the combustion of the solid fuel. Reaction Equation R1 2CO+O2->2CO2 R2 C + 1.5 O2 -> 0.5 CO +0.5 CO2 R3 C + CO2 -> 2CO R4 CaCO3 -> CaO + CO2 R5 Devolatilization Table 1. Chemical Reactions The numerical model adopted the following simulation assumptions: steady-state regime, ideal gases, Eddy Break-Up (EBU) combustion model, k-ε Realizable turbulence model, thermal NOx model, and coal particles modeled in a Lagrangian fashion, with an average diameter of 50 μm. The computational mesh was strategically refined in regions of higher thermal and chemical gradients, such as the primary and tertiary air intake zones and coal injection zones. Boundary conditions were defined to reproduce real operational scenarios, including prescribed air and fuel flow rates, ensuring greater physical representativeness of the model. Figure 1. Geometry and computational mesh Figure 2 shows the temperature field inside the pre-calciner. It can be observed that the regions near the central axis of the flow reach temperatures above 2100 K, evidencing intense combustion activity. In contrast, a low-temperature zone is identified near the inlet nozzles, associated with the high concentration of air in these regions, which promotes dilution of the fuel mixture and locally reduces thermal efficiency. The analysis of the thermal field allows us to assess whether the regions of interest operate within the appropriate temperature range for the process. Figure 2. Temperature profile Complementing this analysis, Figure 3 presents the axial temperature profile along the pre-calciner. A thermal peak is observed in the first 10 meters, resulting from the initial combustion reactions of the coal, followed by a gradual reduction in temperature along the flow, as the fuel is consumed and the gases are diluted. Figure 3. Temperature plot Figure 4 illustrates the concentration profiles of CO, CO₂, and O₂ along the height of the pre-calciner. The CO₂ concentration progressively decreases as the gases rise, reflecting chemical interactions and flow dilution. CO shows peaks near the burner region, associated with centralized coal injection and incomplete combustion. Due to the low local availability of oxygen, some of the CO is not oxidized to CO₂, resulting in a lower CO₂ concentration at the equipment outlet. Figure 4. Concentration profiles: (a) CO; (b) CO2; (c) O2 Figure 5 shows the evolution of the molar fraction of the main components along the vertical axis of the pre-calciner. A significant consumption of O₂ and CO₂ is observed, concomitant with the generation of species such as volatiles, CO and H₂O, characterizing the dominant stages of the coal combustion process. Figure 5. Molar fraction plot Finally, Figure 6 presents the velocity field and streamlines, highlighting the direct influence of the pre-calciner geometry on the flow. Recirculation zones near the tertiary air inlet are prominent, as are regions of low turbulence ("dead zones"), which represent potential areas for the accumulation of unreacted material. Although these regions are associated with flow separation, they also play a relevant role in the conduction and mixing of gases. These results indicate the need for geometric adjustments to optimize the flow, reduce energy losses, and improve the overall efficiency of the equipment. Figure 6. Velocity Profile Conclusion The results presented demonstrate that the use of STAR-CCM+ as a Computational Fluid Dynamics (CFD) platform for the integrated analysis of fluid dynamic, thermal, and reactive phenomena governing the performance of cement pre-calciners is effective. The robustness of the software allowed for consistent modeling of non-premix combustion, species transport, thermal radiation, and particulate behavior, enabling a faithful representation of industrial operating conditions. The adopted approach proved particularly relevant in the context of Oxy-Fuel combustion, where the coupling between chemical reactions, heat transfer, and particulate dynamics imposes additional challenges. The use of appropriate models makes it possible to evaluate operating and design strategies, such as the optimization of air and fuel injection, geometric adjustments, and burner configurations, aiming at reducing emissions, increasing energy efficiency, and greater operational robustness. In this way, CFD simulation is consolidating itself as a strategic tool for decision-making, retrofitting, and developing new technologies in cement plants, reducing dependence on empirical testing and accelerating the transition to more efficient and environmentally sustainable processes.   References ZHENG, Qiang et al. CFD simulation of a cement precalciner with agglomerate-based drag modeling. Powder Technology, v. 436, p. 119508, 2024. ZHANG, Leyu et al. Numerical simulation of oxy-fuel combustion with different O2/CO2 fractions in a large cement precalciner.  Energy & Fuels , v. 34, n. 4, p. 4949-4957, 2020. KANELLIS, Georgios et al. CFD modelling of an indirectly heated calciner reactor, utilized for CO2 capture, in an Eulerian framework.  Fuel , v. 346, p. 128251, 2023. HAIJIAN, Dou; ZUOBING, Chen; JIQUAN, Huang. Numerical Study of the Coupled Flow Field in a Double-spray Calciner. In:  2009 International Conference on Computer Modeling and Simulation . SHU, Yixiang et al. Numerical study on oxy-fuel combustion of coal pre-gasification products in cement calciner.  Applied Thermal Engineering , p. 126901, 2025. MIKULČIĆ, Hrvoje et al. Numerical analysis of cement calciner fuel efficiency and pollutant emissions.  Clean technologies and environmental policy , v. 15, n. 3, p. 489-499, 2013. If you are looking to increase the thermal efficiency of your pre-calciner, reduce emissions, and make more informed engineering decisions, CAEXPERTS can help with advanced CFD solutions using STAR-CCM+ . Schedule a meeting with us and discover how to apply numerical simulation to optimize your cement production process and accelerate results with lower costs and greater reliability. WhatsApp: +55 (48) 98814-4798 E-mail: contato@caexperts.com.br

By combining well-established Simcenter modelers and solvers under a unified SaaS entitlement including Teamcenter X data management with embedded AI assistance, Siemens is expanding access to multidisciplinary simulation while enhancing its digital-thread and SaaS leadership across engineering fields. CIMdata, Industry consulting and analyst firm Introducing Simcenter X Advanced The need for efficient engineering simulation software utilization Engineering simulation offers an efficient way to streamline product development and bring product to markets faster and more cost efficient. However, numerous challenges may prevent you to make the most out of your simulation software investments: Underutilization of licenses The underutilization or wasted IT spending for desktop software is a significant cost factor. This means you need deployment methods that ensure always-on accessibility and licensing models for flexible usage. Source: Flexera, 2023 Simulation business case shift Today, faster-time-to market is the key value driver of simulation. This means you need to maximize the simulation throughput by speeding up every element of the simulation process chain. Source: McKinsey, 2023 Explosion of complexity You therefore must maximize the effectiveness of how you deploy and use your engineering simulation tools. To stay competitive, you specifically must address the following challenges: How do you reduce the complexity of deployment, license, and user management? How do you ensure optimal use of engineering simulation software? How do you equip your engineers with simulation tools to maximize productivity? How do you break down engineering silos to address complex products and unlock the power of digital threads? Simcenter X – your flexible Software as a Service (SaaS) multi-domain engineering simulation Simcenter X Advanced has been released – a flexible, Software as a Service (SaaS) multi-domain engineering simulation suite. This cloud-powered solution will address all the beforementioned challenges and enable you to unlock the power of performance engineering. With Simcenter X Advanced… …as an IT representative you will reduce your IT cost of ownership and make the most of your software licenses with a simple, flexible and easily manageable licensing model you will quickly and easily onboard simulation software users through a unified cloud entitlement, leveraging a centralized administration console that will streamline and simplify the deployment of our software …as simulation engineers and CAE team leaders you will boost productivity with AI technology and cross-domain collaboration and built-in data management you will have access to on-demand capabilities across all major engineering simulations domains (i.e. Computational Fluid Dynamics, Mechanical, Systems simulation and Multidisciplinary Design Analysis and Optimization), simple, anytime, anywhere. Accelerate digital transformation with secure, scalable solutions Simcenter X – integral part of Siemens Xcelerator and a holistic digital thread vision Simcenter X does not come in isolation. Embedded into a large ecosystem of industry software, it is an inherent part of Siemens Xcelerator, Siemens’s open digital business platform that serves as a catalyst for accelerating your digitalization journey. At the same time, Siemens has long understood that the cloud and SaaS are the way of the future. And Software for industry is no exception. Therefore, Siemens is moving the Siemens Xclelerator portfolio to the cloud at a very high pace. From design software to operations and manufacturing, a growing portfolio of cloud-based products is offered under the "X" brand. Simcenter X will be an integral part of the Siemens Xcelerator SaaS ecosystem, coexisting with various other DISW products like NX X , Teamcenter X, and many more. This strategic alignment aims to achieve a comprehensive vision of digital integration, ensuring a seamless and cohesive user experience, as well as simplified licensing management for your IT teams across all our products. One place for all: Simcenter X and Siemens Xcelerator offer centralized cloud-licensing Managing licenses for a large and diverse set of engineering software poses significant challenges and efforts to IT teams. License server configuration becomes complex, deployment of on-premises licenses takes long and user management is difficult with an “anonymous” user profile. All this poses risks to reach the goal of maximizing engineering simulation software ROI by minimizing IT burdens and optimizing license utilization. The good news is: Simcenter X makes license management simple. With cloud-based entitlement and license management, hosted and owned by Siemens, Simcenter X will To significantly simplify the use and implementation of the products, both for the IT administrator and the end user. make waiting for a new license a thing of the past: The cumbersome process of waiting for the license administrator to generate, verify and send the license file, along with the customer installing and setting up the license server, will now be an old school story, enable the IT administrator to manage all products across Siemens Xcelerator through a single unified system known as the Siemens Xcelerator Admin Console allow for the allocation of resources across a global pool of users. But the simplification isn't limited to license implementation and user management… taking advantage of the opportunity, it was decided to significantly simplify the engineering simulation pricing table… Multidisciplinary engineering simulation and design exploration made simple From Computational Fluid Dynamics, through Mechanical and Systems simulation to MDAO, Simcenter X Advanced allows your engineers and engineering teams to seamlessly set-up and run multidiscipline simulation and MDAO. Your company will transform engineering simulation thanks to Unbeaten simplicity Use one license covering flagship Simcenter applications across engineering simulation domains (CFD, Mechanical, Systems and MDAO) Universal access Unlimited guaranteed access to pre-/postprocessing for all flagship applications across all solution domains through a named-user entitlement Ultimate flexibility Run any simulation and MDAO and explore any advanced capability with a single flexible token type Results you can trust through established industry-grade simulation technology To ensure you can gather trustworthy results, Simcenter X gives you access to proven, validated Simcenter simulation technology across domains. As such Simcenter X is based on established and best-rated flagship Simcenter products. Specifically, in the Mechanical domain Simcenter X Advanced gives you access to Simcenter Femap and Simcenter 3D . For CFD, your Simcenter X Advanced entitlement enables the usage of Simcenter STAR-CCM+ , for Systems simulation you get access to Simcenter Amesim and for MDAO to Simcenter HEEDS . While you will install these engineering simulation applications on your local hardware, all licensing is enabled through the cloud. On G2 , a trusted platform for software reviews, Simcenter’s suite of products, Simcenter HEEDS , Simcenter STAR-CCM+ , Simcenter 3D , Simcenter Amesim , and Simcenter Femap , have garnered significant praise in the simulation and CAE category, all taking leader and high-performer positions on the G2 performance grid. Building Simcenter X on these industry-leading established products guarantees a seamless transition for existing users with reliable simulation results for anyone while giving additional value stemming from cloud-powered technologies. Collaborate and keep simulations consistent, up-to-date, verifiable and available across domains At this point another foundational aspect of Simcenter X Advanced comes in handy: That is the provision of integrated data-management through Teamcenter X Essentials. This additional capability comes free of charge with every Simcenter X Advanced seat. Built in data-management will allow individual engineers, engineering teams and entire organizations to organize and store their simulation data in a secure manner communicate and collaborate across different departments right where the data is keep track of simulation data changes leverage a ready-to-use environment that is intuitive and simulation engineer centric embed the data-management into a wholistic digital thread with a ready-to-scale PLM solution Make better decisions, faster with AI Whether it’s choosing the most suitable modeling approach and applying respective best practices or finding better designs in a multidisciplinary optimization study, Simcenter X Advanced will equip you with AI capabilities to speed up your engineering decisions. Better modeling decision faster with an integrated AI chat Simcenter X Advanced will introduce another foundational technology that will be available across all domains: the integration of an AI chat that will assist you in easily exploring and accessing our extensive documentation and knowledge base articles database in their natural language. The AI chat will help you to quickly extract the necessary information for efficient onboarding or expanding your knowledge, as well as exploring simulation options and enhancing your model choices. Find better designs faster, with AI-augmented optimization Simcenter X Advanced paired with Simcenter X Tokens will grant you access to Simcenter HEEDS’s AI simulation predictor. This accuracy-aware AI learns from past simulations to guide future ones and replace physics-based simulations with AI predictions where appropriate during an optimization study. With no expertise and optimization or AI technology you can easily accelerate design exploration, significantly reducing optimization times. Maximize accessibility and global license utilization Simcenter X Advanced combines named-user licensing with tokens Simcenter X is designed to enhance license utilization on a global scale, ensuring that engineering teams can access the software, solvers and advanced capabilities whenever they need it. This capability is crucial for maintaining productivity, especially in environments where model setup and analysis are time-sensitive. By implementing a named-user entitlement, users have guaranteed 24/7 access to do model setup and results analysis in the tools they are entitled to. This prevents issues like license hogging – commonly observed with shared flexible license pools, which often leads to frustrating denials for users who require immediate access. On the other hand, for compute intense tasks like meshing, solving or to access advanced modeling capabilities you don’t want to tie a license investment to a specific named-user as it would lead to costly idle-times. Therefore, Simcenter X Advanced combines the named-user license with a flexible, universal, and globally shared token pool, to grant users access to advanced capabilities and solver technology. This flexibility of a shared global token pool is combined with a controlled token allocation to individuals or groups. The approach not only optimizes access but also supports collaboration across different regions, making it easier for teams to work together seamlessly. At the same time, it allows for a more controlled distribution of license access across teams, ensuring that resources are used efficiently. Enabling users to immediately access advanced modeling capabilities through universal Simcenter X Tokens means no waiting time for a dedicated (evaluation) license, fostering the exploration of novel simulation methodologies. This enables engineering innovation at zero financial risk and without any time delays. Simcenter X – HPC & remote desktop offers cloud-hosted single-click HPC for CFD While the new Simcenter X Advanced and Simcenter X Tokens enable you to run CFD simulations on your on-premises hardware with a local installation of Simcenter STAR-CCM+ , the already established Simcenter X HPC & remote desktop solution augments this simulation deployment with a complete cloud-hosted solution. Simcenter X HPC & remote desktop means instant zero-install access to Simcenter STAR-CCM+ in your browser and single-click simulation job execution straight form within Simcenter STAR-CCM+ on Siemens managed HPC infrastructure. Simcenter X HPC & remote desktop capabilities are enabled through Credits. In contrast to tokens for Simcenter X Advanced, which are checked out from a pool and checked back in when the job is finished, credits are time-based and get consumed when used. Therefore, credits offer the ultimate pay–as-you-go option, incorporating all cost into an hourly rate. As such, Simcenter X HPC & Remote Desktop perfectly augments Simcenter X Advanced for CFD users. With its high flexibility it enables quick responses to changes in demand for HPC resources. Transform engineering with Simcenter X Let‘s summarize this exiting milestone for the engineering simulation community and look at Simcenter X at a glance. Simcenter X: fosters seamless multidiscipline simulation with a single license makes license management simple through centrally managed cloud-licensing increases accessibility with named-user license for pre-and postprocessing maximizes flexibility with a managed pool of tokens to access solvers and advanced capabilities is based on trusted flagship Simcenter simulation technology enabling existing Simcenter users a seamless transition, and create reliable simulation results for everyone fosters collaboration across teams with integrated scalable data-management helps to make smart modeling decisions faster with an integrated AI chat lets you find better designs faster through AI-augmented design exploration and optimization maximizes flexibility with pay-as-you-go credits for Siemens-hosted HPC to address peak loads and minimize CAPEX investments for CFD The time is now to transform your engineering simulation and minimize IT burdens – with Simcenter X Advanced. Want to understand how Simcenter X Advanced can reduce IT complexity, increase your engineers' productivity, and maximize the ROI of simulation in your company? Schedule a meeting with CAEXPERTS and discover how to implement this SaaS solution strategically, quickly, and in line with your engineering challenges. WhatsApp: +55 (48) 98814-4798 E-mail: contato@caexperts.com.br

If you haven't yet checked out Part 1 of our retrospective, we recommend starting there to catch up on the content ranked 10th to 6th and get a complete picture of how computational simulation was present throughout 2025. Continuing the retrospective, this Part 2 brings together the posts that stood out most for their technical impact, depth of analysis, and direct relevance to critical industrial applications. These are articles that show how different simulation methods support safer, more efficient, and physics-based engineering decisions. 5️⃣ DEM simulation applied to boilers Discrete Element Method (DEM) allows for a highly detailed analysis of the behavior of solid particles in boilers, considering collisions, friction, deposition, and wear. In this post, we show how this approach helps to understand complex phenomena that are difficult to measure experimentally, contributing to more robust designs, reduced failures, and increased operational availability. 4️⃣ Case: Bronswerk Heat Transfer uses Simcenter FLOEFD to locate pressure losses This case study practically demonstrates the value of simulation applied to real-world engineering problems. Bronswerk Heat Transfer used Simcenter FLOEFD to identify bottlenecks and pressure losses in its equipment, enabling performance improvements with less need for physical prototyping, cost reduction, and increased efficiency. 3️⃣ How CFD Simulation Can Improve and Maximize Heat Exchanger Design and Performance Heat exchangers are present in numerous industrial processes and play a central role in energy efficiency. In this content, we detail how CFD simulation can be used to optimize geometries, increase thermal efficiency, and reduce pressure drops, supporting design decisions in both new developments and improvements to existing equipment. 2️⃣ Smoother gear operation with SPH fluid injection The application of the SPH (Smoothed Particle Hydrodynamics) method allows for a more realistic simulation of fluid injection lubrication in gears. This post shows how this approach contributes to the reduction of vibration, noise, and wear, as well as providing a more precise understanding of the loads acting on high-performance mechanical systems. 🥇 FEA Analysis of Pressure Vessels with Simcenter 3D At the top of the 2025 ranking is a classic and highly critical topic in engineering: the structural analysis of pressure vessels. This post shows how the use of FEA in Simcenter 3D allows for the evaluation of structural integrity, compliance with applicable standards and codes, and increased operational safety. A clear example of how simulation is indispensable for responsible decision-making in high-risk projects. As this is the first post of the year, the CAEXPERTS team takes this opportunity to wish everyone an excellent New Year. May 2026 be marked by new challenges, successful projects, and increasingly innovative and reliable engineering solutions. Count on CAEXPERTS throughout 2026. If you are looking to improve your projects, reduce uncertainties, and make more informed engineering decisions throughout the entire development cycle, talk to CAEXPERTS . Our work in computational simulation supports companies and engineers in transforming complex challenges into efficient, safe, and intelligent solutions. We are ready to continue this journey with you in 2026 and beyond. WhatsApp: +55 (48) 98814-4798 E-mail: contato@caexperts.com.br

Throughout 2025, CAEXPERTS published a series of technical articles reflecting an increasingly clear scenario: computational simulation has ceased to be merely a support tool and has taken on a central role in modern engineering. Whether to increase the reliability of critical systems, reduce development costs, meet regulatory requirements, or explore innovative solutions, simulation was present in virtually every challenge addressed throughout the year. This retrospective brings together the posts that stood out most in 2025, considering technical relevance, industrial applicability, and reader interest. More than a ranking, it offers a consolidated view of how different numerical methods—such as CFD, FEA, FSI, DEM, and SPH—were applied to solve real-world problems in diverse sectors. This Part 1 presents the articles ranked from 10th to 6th place. They demonstrate the breadth of simulation applications, ranging from electric mobility and medical devices to industrial processes and high-performance products. 🔟 Is your EV battery going to fail? With the advancement of electric mobility, concern about the safety, reliability, and lifespan of batteries is also growing. This post explores how multiphysics simulation allows for the anticipation of failures, evaluating phenomena such as heat generation, aging, degradation, and extreme operating conditions. By predicting problems during the design phase, engineers can reduce risks, increase safety, and make more informed decisions throughout the product lifecycle. 9️⃣ Peristaltic pump FSI simulation for safer dialysis In biomedical applications, small uncertainties can have large consequences. In this content, we show how Fluid-Structure Interaction (FSI) simulation is used to analyze peristaltic pumps employed in dialysis processes. By simultaneously considering fluid flow and component deformation, it is possible to reduce the risk of hemolysis, increase performance predictability, and raise the safety level of the device. 8️⃣ Clearances in gas turbines: the remarkable difference 1mm can make In gas turbine engineering, seemingly small geometric tolerances can have a significant impact on performance and efficiency. This post shows how simulation helps to understand the effect of clearances on losses, aerodynamic efficiency, and component lifespan, supporting more robust design decisions and avoiding surprises during testing or operation. 7️⃣ Designing the perfect bicycle race bottle: Engineering in hydration Simulation also finds its place outside the traditional industrial environment. In this article, CFD techniques are applied to the design of hydration bottles for cycling, evaluating aspects such as flow, ergonomics, and aerodynamics. A clear example of how engineering fundamentals can be used to optimize everyday products, where performance and user experience go hand in hand. 6️⃣ Virtual Body: An efficient approach to painting and filling processes with STAR-CCM+ Processes such as painting and bottling involve multiple physical and operational interactions. The Virtual Body concept allows for the integrated simulation of these processes, anticipating problems, reducing rework, and optimizing material consumption. This content reinforces how simulation can increase efficiency, quality, and competitiveness in complex industrial environments. In Part 2 of the retrospective, we will present the content ranked 5th to 1st – posts that stood out for their high technical impact and direct application in critical energy systems, thermal processes, and structural engineering. Don't miss the continuation of this retrospective! The CAEXPERTS team wishes everyone an excellent end to 2025 and a Happy New Year. May 2026 be marked by new projects, technical achievements, and increasingly innovative solutions. Thank you for following us throughout this year and for trusting in our content and expertise. Let's build the next challenges together. If you're looking to make safer engineering decisions, optimize designs, and reduce uncertainty throughout product and process development, talk to CAEXPERTS . Our expertise in computational simulation can help transform complex challenges into intelligent, efficient, and reliable solutions. We're ready to support your engineering in 2026 and beyond. WhatsApp: +55 (48) 98814-4798 E-mail: contato@caexperts.com.br

Christmas is a time marked by gatherings, celebrations, and, of course, the preparation of traditional dishes. Among them, roast turkey occupies a prominent place. But what happens inside the oven while the roast is being prepared? To answer this question in a technical and accessible way, a simulation was performed using Simcenter FLOEFD , a Computational Fluid Dynamics (CFD) software, with the aim of analyzing air circulation and heat distribution in a convection oven during the preparation of a turkey. Model of a turkey in a convection oven in Simcenter FLOEFD The simulation scenario The turkey did not have exactly the correct dimensions, being just a solid block. There was no cavity for stuffing or for the neck, therefore the measurements were estimated visually and some cuts were made. As one of the most relevant issues was the amount of airflow through different spaces (in the cavities and under the turkey), some objects were created to collect this data. The oven was configured in convection mode, with a fan located at the rear, responsible for propelling air horizontally over the roasting area. For this model, the height of the rack is set at just over 1mm above the bottom of the roasting pan. Turkey cavity This model was run as a snapshot, meaning the turkey temperature was set at a point where it was not yet fully cooked (120°F). The oven temperature was set to 375°F, with the heating elements positioned at the bottom of the oven operating at a slightly higher temperature of 400°F. Boundary Conditions for Turkey Roaster Analysis Initially, the flow lines are observed, which are analogous to the smoke lines shown in wind tunnel tests used in car commercials. These lines indicate the direction of airflow. The fan was defined as the starting point of the flow lines. Although the flow lines exhibit quite chaotic behavior, it is possible to extract relevant information from them. By sectioning the model, the interior of the roaster and the turkey cavity become visible. Compared to the flow lines outside the turkey, it is observed that little air enters the roaster and passes under the turkey, and an even smaller amount passes through the interior of the turkey. This result was expected, especially regarding the airflow in the cavity. The fan propels the air transversely to the width of the turkey, not along its length. For the air to enter the cavity, it would be necessary to go around the turkey and then make a 180-degree turn, which is not physically plausible. Furthermore, due to the large size of the turkeys, it is not possible to orient them in the same direction as the airflow generated by the fan. The airflow from the oven fan surrounds the turkey, whose color varies according to the temperature The oven fan's airflow is directed towards the roasting pan and the turkey cavity Observing a contour plot of air velocity passing through the central plane of the turkey and the oven, it can be seen that the air velocity through and under the turkey is very low, while higher values ​​are observed above the turkey and below the roasting pan. Low-velocity air is considered to be air whose magnitude is comparable to that of a natural convection oven, where the typical air velocity is on the order of 0.2 m/s. Therefore, there is no significant gain in heat transfer provided by the fan, since most of the turkey's surface is subjected to air velocities below 0.2 m/s. Air Velocity Contour Graph For a more precise understanding of this behavior, a graph of the air velocity near the surface of the turkey is observed. The image has been divided into two parts: one representing the surface of the turkey facing the fan and the other showing the opposite side. The difference between the two regions is evident. As a consequence, one side of the turkey tends to cook or dry out more quickly than the other if the food is not rotated periodically. Higher air velocities result in more intense convection, a principle illustrated by the act of blowing on soup to accelerate its cooling. Speed ​​close to the surface of the turkey, near the fan Air velocity near the surface of the turkey, opposite to that of the fan. Returning to the contour plot, when analyzing the temperature distribution, it is clearly observed that the air inside the turkey has significantly lower temperatures. This occurs due to air stagnation, since there is no effective circulation of hot air inside the turkey. It is also observed that, below the turkey, in the space of approximately 1 cm (0.4 inches) provided by the grill, the air temperature is lower than that of the rest of the oven. Again, this behavior is explained by the limited circulation of renewed hot air in this region. Air temperature contour graph along the centerline of the turkey The question arises as to why air has difficulty penetrating the space between the turkey and the bottom of the roasting pan. Observation of the flow lines indicates that the cause is essentially the same as that which prevents air from entering the inside of the turkey. The air from the fan tends to follow the path of least resistance. To flow under the turkey, the air would need to go around the wall of the roasting pan, descend through the space between the turkey and that wall, and then make a 90-degree turn to flow under the turkey. Along this path, there is a reduction in speed and a loss of temperature. Both factors are relevant, since colder air tends to descend. Furthermore, since the flow velocity is lower than that of a natural convection current, the warm, renewed air cannot displace the air already present in that region. For this reason, it is observed that the air reaches the roasting pan, but cannot advance under the turkey, instead recirculating near the wall of the roasting pan. Contour graph of air velocity and streamlines along the width of the turkey The images provide a good qualitative understanding of the phenomenon; however, in many cases, a quantitative analysis is necessary. Data evaluation indicates that the oven fan moves approximately 22.8 CFM of air. The airflow that effectively enters and exits the roaster is about 0.35 CFM, which corresponds to approximately 1.5% of the total fan flow. Regarding the air entering the turkey cavities, the inflow and outflow were analyzed in both the neck cavity and the larger rear cavity. The measured flow rates were 0.08 CFM and 0.146 CFM, respectively. From these results, it is concluded that the stuffing is not responsible for preventing air circulation inside the turkey, since this circulation is already intrinsically very limited. This does not exclude the effect of the additional thermal mass of the stuffing, which can result in longer cooking times and drier meat—a topic that deserves specific analysis. Nor should one expect significant air circulation under the turkey capable of producing a completely crispy skin. A higher rack or a roasting pan with lower sides might offer some improvement, although this effect is questionable. In practice, using a rack or vegetables like carrots, celery, or potatoes serves a similar function, elevating the turkey and keeping it away from the accumulated fat. Want to understand how simulation can bring that same level of technical analysis to the real-world challenges of your engineering? Schedule a meeting with CAEXPERTS and discover how CFD and advanced simulation solutions can optimize your projects and processes. We also take this opportunity to wish you a Merry Christmas and a Happy New Year! 🎄✨ WhatsApp: +55 (48) 98814-4798 E-mail: contato@caexperts.com.br

The new release of Simcenter Culgi 2511 brings significant advancements to empower your computational chemistry simulation workflows. With enhanced viscosity prediction, you can now achieve reliable results more quickly, with greater accuracy and even the most complex fluids, thereby reducing the need for extensive laboratory testing. The support for realistic crystalline structure modeling unlocks new possibilities for simulating complex materials, while auto-completion for Python scripting and a built-in library of physical constants streamline your workflow and minimize errors. These features collectively enable you to explore more complex systems, accelerate your material development process, and ensure higher precision in your results. Achieve dependable viscosity predictions validated against industry standards Measuring viscosity is a complex and time-consuming task, yet it is a critical property across many industries. Traditionally, obtaining accurate viscosity values for different formulations has required extensive lab work and sophisticated experimental setups, often leading to project delays. With the new release of Simcenter Culgi 2511 , you can now leverage state-of-the-art viscosity prediction methodologies, including the impact of shear, at both atomistic and coarse-grained levels. Simcenter Culgi 2511 integrates the SLLOD equation methodology, enabling you to predict viscosity under various conditions with ease. Additionally, the Stop-on-Met precision feature automatically halts measurements once a specified accuracy (such as 0.5%) is achieved, further optimizing your formulation development process. This comprehensive toolkit enables rapid candidate screening and significantly reduces the need for laboratory tests. As a result, you benefit from reliable, industry-standard, validated results, ensuring your predictions are both accurate and dependable. Ultimately, this empowers you to make informed decisions faster and with greater confidence, driving innovation in your projects. Model realistic crystalline structures with atomic precision As simulation techniques advance, the demand for modeling increasingly complex systems, such as crystalline structures, continues to grow. The limitations of traditional simulation geometries, often restricted to cubic or rectangular boxes, have made it challenging to accurately represent real-world crystalline forms. With Simcenter Culgi 2511 , you can now import and simulate non-rectangular simulation boxes, overcoming the previous constraints. This new capability allows you to import your unit cell and expand your crystalline structure for simulation, both at the atomistic and coarse-grained levels. By enabling realistic modeling of crystalline structures, you can reduce the need for physical testing and identify potential limitations before moving to experimental phases. This enhancement not only streamlines your workflow but also ensures that your simulations are more representative of actual materials, ultimately leading to better-informed decisions and more successful outcomes. Accelerate your scripting with 90% reduced command lookup time Engineers often appreciate the flexibility of exporting and integrating Simcenter Culgi scripts into advanced Python workflows. Remembering the multitude of Simcenter Culgi-specific commands and their functionalities can be a significant hurdle, especially when developing or modifying scripts from scratch. With the latest Simcenter Culgi 2511 release, you now have access to auto-completion and command help directly within your preferred Python IDE. As you write scripts, you can quickly look up native commands, access help by hovering, and autocomplete commands as needed. This accelerates the development of complex multiscale workflows, reduces the time spent searching for the right commands, and lowers the barrier to entry for new users. The result is a 90% reduction in command lookup time, enabling you to focus on innovation rather than routine tasks. Faster onboarding and improved user experience mean your team can deliver results more efficiently. Ensure improved calculation precision Coarse-grained simulations, such as Dissipative Particle Dynamics (DPD), are a hallmark of Simcenter Culgi, but they traditionally lack real units, requiring manual conversion to physical units. This process often involves manually entering physical constants, such as the Boltzmann constant or Avogadro number, which is both tedious and prone to error. With Simcenter Culgi 2511 , you benefit from a built-in library of the most common physical constants used in computational chemistry. Now, you can simply select the required constant and continue building your equations without worrying about transcription errors or loss of precision. This enhancement not only streamlines your workflow but also ensures that your results maintain the highest level of accuracy. By removing a common source of error and saving valuable time, you can develop multiscale workflows with greater confidence and efficiency. If you want to accelerate your projects, reduce lab testing, and increase the accuracy of your chemical simulations with the latest advancements in Simcenter Culgi 2511 , schedule a meeting with CAEXPERTS now and discover how we can support your team in getting the most out of these new features. WhatsApp: +55 (48) 98814-4798 E-mail: contato@caexperts.com.br

Believe it or not, the Smoothed-Particle Hydrodynamics (SPH) technology, which has significant applications today, was actually developed for astrophysical purposes. It was originally used to simulate the dynamics of galaxies and the behavior of stars and planets: Smoothed Particle Hydrodynamics | Annual Reviews Monaghan, J. J. 1992. “Smoothed Particle Hydrodynamics.”, Annual Review of Astronomy and Astrophysics 30:543-74. doi: 10.1146/annurev.aa.30.090192.002551. Just like cosmic formation, where countless particles coalesce into refined structures to form stars and planets, the SPH solver in Simcenter STAR-CCM+ 2510 now offers local particle refinement. But you don’t have to go to outer space to make use of this capability: it can actually be used for any down-to-earth application, like, for example, to better capture the oil around planetary gears. And no, planetary gears are not an astrophysical application, even though this thing is pretty close to one: Enhance simulation precision with SPH particle refinement technique In previous versions of SPH in Simcenter STAR-CCM+ , achieving higher fidelity required refining the particle size, which inevitably increased simulation time. Conversely, opting for faster simulations meant coarsening particle size, sacrificing accuracy. This is the classic CFD dilemma with no easy solution. Now, with version 2510, Simcenter STAR-CCM+ introduces local particle refinement for the SPH solver, allowing you to enhance flow accuracy precisely where it’s needed without necessitating a fine particle size across the entire fluid domain. This new capability enhances precision in critical areas while maintaining efficient simulation time, offering a balance between local high-fidelity results and computational performance. The performance improvement largely depends on the application and the size of the refinement area. In the SPH solver’s adaptive time-stepping, the chosen time step is still determined by the finest particle size. Consequently, the performance boost is not driven by the time step but achieved by reducing the total number of particles compared to a fully refined particle simulation. As a result, the more localized and specific the refinement areas are, the greater the performance gains you will experience. As illustrated in the animation, you now have the ability to locally create geometry particle refinement criteria using block, cylinder or/ and sphere shapes. In the example, cylinder refinement criteria have been defined around each gear to accurately capture the oil distribution close to the teeth. Your simulation can incorporate one or multiple refinement shapes, and they can even overlap as needed, especially when dealing with complex geometries such as gear teeth. You can define up to 10 levels of refinement, allowing particle size specifications to go below one micrometer, starting from a base particle size of 1 mm. Also noteworthy is the ability to assign a coordinate system to the refinement shapes. This is particularly useful if you need the refinement to follow a moving solid, ensuring it maintains an accurate resolution while moving along a trajectory in space. To demonstrate the higher fidelity benefit for this planetary gear application, this chart depicts the average wetted surface over time. As shown, the simulation using particle refinement (particle base size of 1 mm using two levels of refinement) achieves accuracy that closely matches the finest simulation (0.25 mm). In contrast, it outperforms the coarse simulation (1 mm), highlighting the effectiveness of particle refinement in balancing precision and computational efficiency. Another key advantage of particle refinement is its significant reduction in memory consumption. As illustrated above, using particle refinement results in a fourfold decrease in memory usage compared to the finest simulation, enabling you to efficiently handle more complex cases. Simplify planetary gearbox simulation with just a few clicks Just as effortlessly as planets revolve around the sun in our solar system, setting up a planetary gearbox in Simcenter STAR-CCM+ has never been easier. Starting with version 2506, the new kinematics solver allows for the use of Planetary Gear and Revolute Joint Body Couplings, enabling you to configure motions with just a few clicks. Additionally, version 2506 introduced enhanced data analysis capabilities. You can now measure mass flow or various other quantities across section planes, thanks to the compatibility of the SPH solver with constrained plane and arbitrary section-derived parts. Furthermore, visualization of the free surface is now possible using the SPH solver’s compatibility with the iso-surface derived part of the liquid volume fraction. Those enhancements in the motion and data analysis contribute to a faster setup and getting more insights into the quantitative solution. Accelerate SPH simulations with lightning-fast GPU workflows In Simcenter STAR-CCM+ 2510 , SPH simulation feels akin to traveling at the speed of light, thanks to seamless GPU acceleration compatibility throughout the entire workflow. The solver supports native GPU acceleration since version 2410 for single GPU and expanded to multiple GPUs in version 2502. With the latest version 2510, data analysis capabilities are now also ported to GPU hardware. As a result, you can now utilize and visualize point probes, free surfaces, constrained plane sections, and arbitrary sections derived parts up to five times faster compared to before. This allows for rapid solution analysis, maintaining your workflow at a lightning-fast pace. In this specific example, running the planetary gear lubrication simulation on an NVIDIA RTX6000 GPU achieves a speedup of nearly five times faster compared to using 56 CPU cores. This demonstrates that the entire workflow for this application, including particle refinement, is fully optimized and compatible with GPU acceleration. Explore new simulation frontiers with enhanced SPH capabilities Simcenter STAR-CCM+ continues to advance its SPH solver with significant enhancements, including local particle refinement, a streamlined workflow for planetary gears, and additional data analysis capabilities, as well as robust GPU acceleration. With more accuracy, faster setup, and runtime, the SPH solver may help you reconnect with your inner child by looking at all new types of planets and stars in planetary and sun gears. And ultimately, we want to enable you “to boldly go where no (wo)man has gone before.” Perhaps even for your SPH simulation, one day space will become the final frontier. Schedule a meeting with CAEXPERTS and discover how to leverage the full potential of SPH in Simcenter STAR-CCM+ to increase the accuracy of your simulations, reduce computational costs, and accelerate your GPU workflows—all with the expert technical support of those who deeply understand these technologies. Let's take your analyses to the next level? WhatsApp: +55 (48) 98814-4798 E-mail: contato@caexperts.com.br

In today’s competitive engineering landscape—defined by tight development timelines, limited budgets, and no tolerance for design failures—teams must quickly explore more design alternatives while optimizing increasingly complex systems to balance objectives such as performance and cost. Modern engineering solutions must bridge web and desktop environments to support distributed teams working from anywhere, while intelligently leveraging AI to automate routine tasks and accelerate decision-making. This combination of flexible access and intelligent automation enables engineers to focus on high-value creative work. This release delivers just that - Simcenter HEEDS 2510 for simulation-based design optimization and Simcenter HEEDS Connect 2510 for workflow integration address these needs with enhancements that make advanced optimization accessible and productive for teams of all sizes, accelerating innovation through simulation-driven design. SHERPA’s enhanced multi-objective capabilities: better trade-offs, faster results At the heart of this release is a major update to SHERPA's multi-objective search strategy, the HEEDS optimization strategy used to efficiently explore project spaces and find optimal engineering solutions. For teams tackling multi-objective trade-off studies with constraints, you’ll benefit from improved search strategies that help you discover more robust Pareto frontiers faster. Regardless of your use case or industry, the improved multi-objective SHERPA enables you to make informed decisions more quickly and with greater confidence. Benchmarking SHERPA’s enhanced multi-objective capabilities with an XLR UAV (analysis tool: Simcenter STAR-CCM+). Performance and speed comparisons are based on median values, represented by dotted lines, while the shaded areas indicate the 95% confidence intervals. AI-powered acceleration with more iterations, less waiting Simcenter HEEDS 2510 features an updated AI Simulation Predictor, leveraging artificial intelligence to accelerate optimization studies. By intelligently predicting simulation outcomes, this capability reduces optimization time by up to 30% without compromising solution quality. The intuitive interface democratizes AI-powered optimization, eliminating the need for machine learning expertise. This allows more design iterations, faster turnaround, and improved productivity, enabling teams to focus on innovation rather than waiting for results. Native HyperMesh integration: from mesh to results in one workflow Simcenter HEEDS 2510 enables seamless tool integration with specialized connectors for Altair HyperMesh and HyperView/HyperGraph . These connectors automate the entire optimization workflow: parameterized mesh morphing in HyperMesh , automated simulation execution, and consolidated results visualization in HyperView/HyperGraph . By eliminating manual file transfers and standardizing post-processing procedures, engineering teams can concentrate on design insights rather than data management, thereby reducing the time spent on each design iteration. Smarter optimization setup with intelligent guidance Setting up optimization studies can be challenging, particularly when deciding the appropriate number of evaluations. The new Optimization Intelligence feature offers automated settings for minimum evaluation counts, tailored to specific problem characteristics, including the number of design variables, response objectives, variable types, and workflow complexity. Optimization Intelligence analyzes your setup and recommends the minimum number of evaluations required for meaningful results. Visual alerts guide users toward best practices, reducing guesswork and helping both novice and experienced engineers in developing robust studies that deliver reliable results. This helps set realistic expectations and encourages the selection of evaluation budgets that reflect the available engineering budget. SHERPA’s adaptive algorithms continue to enhance solution quality with additional evaluations, allowing the discovery of superior design alternatives while requiring careful resource management. Simcenter HEEDS Connect: Seamless web-to-desktop workflow transitions Simcenter HEEDS Connect 2510 enables teams to collaborate and iterate efficiently, regardless of location. The new “Open in Desktop” feature bridges HEEDS Connect’s web environment with the full power of HEEDS MDO on the desktop. With project locking and automated data sync, users transition workflows between environments without losing context or data integrity. Teams can use the cloud for fast collaboration and the desktop for in-depth editing and analysis. Seamlessly move between Simcenter HEEDS Connect and Simcenter HEEDS desktop Workflow editing with real-time adjustments Building on previous workflow visualization capabilities, Simcenter HEEDS Connect 2510 now allows direct editing of key analysis parameters for Simcenter STAR-CCM+ , NX CAD , and Microsoft® Excel® integrations— directly within the browser. Engineers can make real-time adjustments to simulation setups, validate changes instantly, and collaborate on parameter modifications without needing to switch environments. This results in a more agile, accessible, and collaborative design exploration process. Edit analysis properties directly in Simcenter HEEDS Connect web interface Immersive 3D visualization for collaborative reviews With the addition of VCollab 3D Visualization, HEEDS Connect 2510 delivers an immersive, browser-based experience for reviewing CAD and CAE results. Teams can interactively explore complex geometries, annotate models, and measure features in real time to accelerate decision-making and foster more engaging design reviews. This capability enhances cross-team communication and streamlines the review cycle, helping organizations bring better products to market faster. Interactive 3D navigation, annotation, and measurement tools for detailed model exploration Designed for the engineering community Simcenter HEEDS 2510 and HEEDS Connect 2510 demonstrate our commitment to supporting the engineering community with integrated, intelligent, user-friendly solutions. Whether optimizing complex systems, collaborating across teams, or accelerating innovation, these releases provide the tools needed to succeed. If you want to leverage the full potential of Simcenter HEEDS' new features to accelerate your optimizations and integrate teams more intelligently, schedule a meeting with CAEXPERTS . We can show you how to apply these solutions directly to your workflow and transform your engineering efficiency. WhatsApp: +55 (48) 98814-4798 E-mail: contato@caexperts.com.br