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The new Simcenter FLOEFD 2606 software release is now available in all its CAD-embedded CFD variants, and also the Simcenter 3D embedded variant. This release delivers focused improvements for electronics cooling analysis. This includes library enhancements for easy validated component re-use, efficient modeling of power sources on a die to identify hotspots for IC packages in system models, improvements to computationally efficient PCB thermal modeling, automation of EDA data import, and much more. Please read on below to explore each new feature organized by Simcenter pillars. Smart Die – modeling 1000’s of power sources To identify localized hotspots when IC packages are incorporated in a system, it is advantageous to model power distribution on the package die. In Simcenter FLOEFD 2606 the Smart Die has been introduced for modeling 100’s or 1000’s of power sources on a packaged semiconductor die in a computationally efficient manner suitable for this level of analysis. This means engineers can account for complexity such as power distribution spatial influences, overlapping sources, transient time variations, and thermal dependencies. You can detect leakage-driven hotspots that uniform die modeling approaches are not able to represent. How are power sources defined using the Smart Die? The die is subdivided into multiple polygons with distinct power characteristics. Polygons are defined by an imported CSV file and assigned to a body specified as a die. You can import power floorplan with leakage models assigned. A voxelized mesh resolves the die. This means you can import hundreds of overlapping polygons with dynamic and leakage power assigned to represent a complex power distribution. You can import polygon geometry from a CSV file using the polygons dialog. Several formats are supported, and the type is automatically then detected. Types include: Geometry definition table (name, nverts, vert1, vert2, …) Simcenter FLOEFD polygon table with full definition (Name, Polygons, Dynamic Power, Derating Factor, Leakage Model, Leakage Power at T0, Priority, Goal Discrete sources from Flotherm (name, X1, X2, Y1, Y2, P) Total Coverage Sources from Simcenter Flotherm (uniform grid with power values) You can explore these types when you upgrade to the latest version. Below are 2 videos showing the use of the new Smart Die feature. Video: Smart Die overview Video: Importing data into Simcenter FLOEFD Smart Die from Simcenter Flotherm This new Smart Die approach allows import of non-uniform disspation power sources from Simcenter Flotherm software into Simcenter FLOEFD 2606. (Simcenter Flotherm has enabled this CSV export since version 2604 from its Die Smartpart component) Smart PCB: FEM mesh based thermal analysis Enhancements to the computationally efficient and popular Smart PCB feature have been delivered in this release via the introduction of FEM mesh based thermal analysis and expanded results visualization options. The new FEM prism mesh based thermal modeling approach reduces memory usage and improves speed for modeling of high density, multi-layer boards with complex copper routing. In post processing, results visualization using this new Smart PCB modeling approach, users can leverage clearer insights into board internal temperature variations and more easily visualize heat flux plots to locate thermal bottlenecks. Video Demonstration: Smart PCB FEM mesh based thermal analysis Watch this short < 2 minute video that shows the new settings you use for Smart PCB FEM mesh based thermal modeling and results visualization examples. Library enhancements in Simcenter FLOEFD 2606 PCB thermal analysis workflow benefits from libraries of existing components due to the complexity of most board applications with 100’s, or thousands, of components mounted on them. Library ecosystem and browser You can now create custom component or model libraries and instantly reuse them across projects. . Libraries of of validated, reusable elements help you assemble and set up models much faster. As this also minimizes errors between models, for engineering teams this provides the opportunity to ensure consistent standards for groups of users using libraries. Library: edit parameter of features from component Parameters of features belonging to sub-components can now be edited directly from the top-level assembly. Each component instance can also be modified independently. Library: Local mesh settings based on absolute cell size Mesh refinement can now be defined using absolute cell size in library components. This enables local mesh settings for library items that are independent of top-level mesh settings for a project. This means a library author’s mesh decision transfer with library elements and there is no need for manual adjustment when re-using these. Video demo: Library enhancements in Simcenter FLOEFD 2606 Component Explorer updates in Simcenter FLOEFD 2606 a) Component Explorer: Network Assembly and Smart PCB New columns have been introduced to display power values assigned via Network Assembly and Smart PCB features. Users can review power at the individual component level or evaluate the total power budget. b) Component Explorer: minimum temperature column A new column shows the minimum temperature for each component, complementing the existing maximum and average values and enabling better analysis of temperature gradients. The launch of the component explorer as your model becomes extremely complex and high component numbers has been sped up through a code refactoring. Even for very large models, you can now access component features immediately in table view. Material Priority setting: Material priority values can now be edited directly within the table, eliminating significant manual clicks and steps. EDA Bridge automation – headless operation Automation of simulation tasks significantly increases throughput for thermal analysis projects for engineering teams. A step change has been delivered toward true headless automated import and processing of EDA data for PCB thermal analysis via enhancements to EDA Bridge used in conjunction Simcenter FLOEFD API capabilities. The ability to automate EDA Bridge operation enables teams to realize advanced cross-domain thermal optimization workflows linking simulation and ECAD-MCAD design flows. Video overview: EDA Bridge headless operation for automation Automation: other API enhancements Automation of simulation tasks continues to be a popular topic. EFDAPI, the new Simcenter FLOEFD API introduced back in version 2312, continues to be developed in each release based on user feedback. Beyond EDA Bridge automation, more functionality been added in Simcenter FLOEFD 2606 including: An easier select coordinate system method Enable/disable absorption in default solid Add from components, to re-use from sub projects Set default outer radiation surface Curious about PYTHON scripting? that was supported in EFDAPI as of version 2406 Speed-up: 100’s of 2R components contacting a Smart PCB For PCB thermal analysis studies where high numbers (100’s) of components modeled as two-resistor (2R) type components are in contact with a board modeled as a Smart PCB, an improvement in computational efficiency has resulted in test models achieving performance of almost 2x faster solution. This was achieved through optimizing mesh contact handling for non-conformal meshes with high cell size ratios. XTXML export enhances package model workflows XTXML export now supports contact resistance and radiative surfaces at version 2606 to enhance IC package thermal model creation and adding to libraries. XTXML export for component editing was introduced in the 2506 release  allowing 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 previous Simcenter FLOEFD 2512 release enhancement introduced the option to export models of 2R and Network Assembly components. Do you want to enhance your thermal simulation processes and unlock the full potential of the new features in Simcenter FLOEFD 2606? Schedule a meeting with CAEXPERTS and discover how these improvements can help your team accelerate analyses, update electronic designs, and boost the efficiency of your engineering workflows. WhatsApp: +55 (48) 98814-4798 E-mail: contato@caexperts.com.br

For engineers to collaborate effectively on multidisciplinary applications, being able to transfer results quickly, easily, and reliably from a Computational Fluid Dynamics (CFD) model to a structure mechanics Finite Element (FE) model is crucial. With Simcenter STAR-CCM+ we introduce a common data format for an efficient transfer of simulation results to Simcenter 3D (CFD-FEA coupling). Model the complexity of multiphysics applications Mechanical engineering is an engineering branch that combines engineering physics and mathematics principles with materials science, to design, analyze, manufacture, and maintain mechanical systems. (Source: Wikipedia) According to the definition above, mechanical engineering is about the design and analysis of mechanical systems. But before it’s even possible to design or analyze any mechanical system, a detailed understanding of the operating conditions and expect service loads is a must. Example of a recent engineering disaster Being unable to predict operating conditions and service loads have led to countless engineering disasters. A fairly recent one is the sinking of the MOL Comfort in the Indian Ocean. This event took place on June 17, 2013. Source: BMA-Investigation-Report-Loss-of-the-MOL-Comfort.pdf CFD-FEA coupling can help to predict service loads and operating conditions for Multiphysics applications. Continue to read this blog to find out how to use the results of a CFD model to define the service loads of a structure mechanics FE model. CFD-FEA coupling for a boat hull structure A boat with an overall length of 5.5m and a total weight of 1600kg (800kg boat only) is driving at 5 m/s through a series of waves with a height of 1m. The objective is to analyze the deflection of the bottom panel of the hull in a practical manner. CFD simulation of a small boat in waves. Pressure field at the hull delivers the key input to a CFD-FEA coupling simulation CFD-FEA coupling to analyze the deflection in a practical manner Fluid dynamics and structure mechanics models are often built by different analysts. A process that enables a smooth and efficient CFD-FEA coupling is key. From a physics perspective, it’s reasonable to assume that the deflection of the panels is small compared to the rigid body motion of the boat. Therefore, we may assume that the deflection of the panels will not have a significant impact on the flow. In other words, we may assume that the panel deflection is 1-way coupled in the direction fluid to structure. The fluid pressure deflects the panels, but the deflection of the panels doesn’t affect the flow. Stay integrated with CFD-FEA coupling in the Simcenter environment Set up your CFD model in Simcenter STAR-CCM+ The first part of the process is to set up the Computational Fluid Dynamics (CFD) model in Simcenter STAR-CCM+. Here we assume that the boat is rigid, and therefore we can model it as a six degree of freedom (6DOF) body. The mass, center of mass, and moments of inertia of the boat are an input for the 6DOF model. And they may be taken from the FE structure model. Export your simulation results to the Simcenter Data File While the boat floats through the waves, Simcenter STAR-CCM+ exports the pressure on the bottom panel of the hull is being to a file. Not any file, but a Simcenter Data File with the extension .scd5. Simcenter STAR-CCM+ exports the panel pressure on the native Computational Fluid Dynamics (CFD) mesh and the sampling frequency matches the time step size of the flow solver. Therefore, for the given model, the exported Simcenter Data File may be thought of as a persistent data source with the highest possible fidelity in space and time. Import the pressure in Simcenter 3D Next, the CFD engineer hands over the Simcenter Data File to the structure mechanics analysts. This team imports the hull pressure into the Simcenter 3D. After the import, Simcenter 3D stores the pressure within the simulation file as a Table of Fields. The frame of the boat is assumed to be rigid. Hence, a fix constraint is applied wherever the bottom panel is connected to the frame. The imported fluid pressure is defined as a load and automatically interpolated in space and time. As solver Simcenter Nastran Solution 401 is being used. An efficient CFD-FEA coupling The animation below shows the bottom panel of the hull from a diver’s perspective for the duration of about one-third of the wave period. In the left part of the animation, we can see the fluid pressure computed with the help of the Simcenter STAR-CCM+ CFD model. In the right part, we can see the panel deflection from the Simcenter Nastran 401 model. CFD-FEA coupling between Simcenter STAR-CCM+ and Simcenter 3D made easy and realiale through the common Sicmenter .scd5 data format Predict service loads and operating conditions Go faster with efficient data exchange across Simcenter products The example above demonstrates how a CFD-FEA coupling method can help to predict service loads and operating conditions for Multiphysics applications. Furthermore, it also demonstrates that being able to export simulation results from Simcenter STAR-CCM+ to the Simcenter Data File for a subsequent import into Simcenter 3D is extremely valuable. Run a productive and efficient workflow Admittedly, coupling, a Computational Fluid Dynamics (CFD) simulation to a structure mechanics FE simulation through a file is nothing revolutionary. However, the presented workflow has some subtle points to consider: The fluid pressure is exported to the Simcenter Data File on the native Computational Fluid Dynamics (CFD) mesh at every time step of the flow solver. The result is a persistent data source of the highest possible fidelity in space and time. The Simcenter Data File is imported into Simcenter 3D once. Then the data is being interpolated in space and time onto the Simcenter Nastran 401 model. Therefore, should the structure mechanics analyst want to investigate a different design of the structure (a different frame) there is no need to re-iterate with the flow analyst, not even to re-import the hull pressure. The two points above may appear subtle, but they are essential for a productive and efficient workflow. The Simcenter Data File is the only component that needs to be exchanged between the flow and the structure analyst. Hence, the required interaction and exchange of simulation results is kept to an absolute minimum. Transform complex simulation data into faster, more accurate engineering decisions. Schedule a meeting with CAEXPERTS and discover how the integration between Simcenter STAR-CCM+ and Simcenter 3D can make your structural analysis and CFD processes more efficient, collaborative, and reliable. WhatsApp: +55 (48) 98814-4798 E-mail: contato@caexperts.com.br

System simulation for medical device companies AGV and AMR manufacturers are under pressure to reduce the development time of highly customized solutions while also increasing the reliability of autonomous systems. In addition, the integration of vehicle dynamics, electric propulsion, sensors, navigation algorithms, and control systems makes each new project more complex. In this scenario, system simulation enables engineering decisions to be validated before physical prototypes are built. Today, autonomous robots are used in areas such as logistics, manufacturing, distribution centers, and mining. In a less common application, this type of technology is also present in hospitals. Currently, the medical device industry is following the broader trend toward more autonomous systems. Medical disinfection robots are used to sterilize hospitals, including waiting rooms and patient rooms, as well as parking lots, shopping malls, and other public spaces, with the major advantage of avoiding additional human exposure to viruses through the use of these robots. Autonomous medical disinfection robots in a 3D environment for sanitizing rooms In an application developed using Siemens engineering software and services, new dedicated AMRs were designed. They combine an electrically powered autonomous platform with a disinfection system mounted on top. Typically, this system includes liquid micro-spray nozzles that apply disinfectant to surfaces, or ultraviolet C (UVC) lights to purify the air. The goal is to destroy all airborne pathogenic microorganisms. In this way, disinfection robots sanitize these environments, allowing people to use them later for their normal activities. Development challenges and system simulation System simulation can help reduce development time by decreasing the number of costly physical prototypes and testing campaigns. A crucial factor in the development cycle of autonomous robots is autonomous operation and the ability to navigate new environments. This is achieved through a combination of computer vision, including cameras, LiDARs, short-range radars, and other sensors, sensor fusion, control logic, and vehicle dynamics, enabling robots to operate easily in different situations and on various types of flooring. When physical interaction with an infected environment represents a significant risk to humans, an autonomous robot can perform simple and repetitive tasks. Many robotics solutions control the robot’s movement remotely. However, an autonomous robot can move on its own to perform its functions. It uses computer vision, obtained through various onboard sensors, and a typical perception-reasoning-action algorithm, which provides the correct commands to the actuators without the need for human presence and, consequently, without the risk of viral contamination. Typical challenges for AGVs (“Automated Guided Vehicles”) and AMRs (“Autonomous Mobile Robots”) In this article, we would like to present some ideas on how a simulation-based approach can support the development of autonomous robots, from system sizing and sensor design to the verification and validation of the final control algorithms. A simulation framework for autonomous systems The simulation framework combines different Siemens tools that have already been successfully implemented in several autonomous applications across multiple industries. Examples include autonomous cars in the automotive industry, drones and UAMs, or urban air mobility, in the aeronautics sector, autonomous agricultural vehicles in heavy equipment, and even military tanks operating in hostile environments in the defense sector. Consequently, the same simulation architecture can be applied to emerging medical robot applications, which must meet slightly different requirements. This framework integrates several software tools that perform time-domain simulations. An alternative workflow would consist of directly connecting Simcenter Amesim and Simcenter Prescan through FMI, or Functional Mock-up Interface, which is available in both tools. Simulation framework with the different tools involved Simcenter Amesim® represents the vehicle dynamics and electric propulsion. Simcenter Prescan® represents the hospital environment and models the sensors that detect the presence of objects in the environment, such as cameras, LiDARs, short-range radars, and others. Simulink® connects Simcenter Amesim and Simcenter Prescan. In addition, ROS, or Robot Operating System, was used for sensor fusion and control algorithms, which provide the actuator commands to the vehicle model in Simcenter Amesim. Overview of the data flow and customized 3D scenes The robot state is transferred from Simcenter Amesim to Simulink, which provides the updated position and orientation of the robot to Simcenter Prescan. Simcenter Prescan then provides the virtual sensor data to the ROS operating system through Simulink. Finally, the ROS control algorithm sends the updated actuator commands to the Simcenter Amesim model so that it follows the correct path. At this point, the control loop is closed, and the robot can move autonomously within the environment, such as a hospital room, while avoiding collisions with detected obstacles. Scope of activities and domains in the design of an autonomous mobile robot (AMR) for medical use Regarding the modeling of environments such as hospitals, warehouses, or distribution centers, Simcenter Prescan allows the import of customized objects typical of these applications as CAD files: Various geometries of autonomous mobile robots (AMRs), Geometries for room layouts, corridors, slopes, beds, and obstacles, Adverse conditions imposed by the natural environment, such as day and night, among others. Thus, it is possible to represent real configurations and operating conditions. Modeling the dynamics of the robotic vehicle and its 3D environment The Simcenter Amesim model predicts the physical behavior and interactions of different subsystems in a three-wheeled vehicle. It features front-wheel drive, including the electric motors with their inverters, controllers, and a 24 V power supply battery, as well as passive rear-wheel drive. In addition, the model represents the vehicle dynamics, including its axles, chassis, and tires. The Simcenter Amesim digital twin was used to implement autonomous driving functions. The vehicle was then equipped with sensor models, and finally, the loop was closed by integrating the decision-making algorithm between the simulated sensor data and the vehicle model. Simcenter Amesim model of the disinfection robot with its vehicle dynamics and electric propulsion Multiple scenarios can be investigated, as well as how obstacle detection and avoidance functions allow the robot to move autonomously within this unknown 3D environment. The visualization of the 3D scene from different perspectives helps in understanding the simulation results. For this purpose, several camera orientations were used, along with sensor fusion from the ROS library for video processing. 3D views from different camera orientations It is now clear how the combination of Simcenter Amesim and Simcenter Prescan supports the development and validation of AGVs and AMRs throughout the entire design cycle. By integrating multidisciplinary models of the vehicle, environment, and sensors into a single simulation workflow, engineering teams can evaluate system performance much earlier in the development cycle. This approach reduces technical risks, anticipates integration issues, and accelerates decision-making during development. With a simulation platform, it is possible to validate the vehicle architecture, compare different sensor configurations such as LiDAR, cameras, and radars, analyze battery autonomy across different operating profiles, and optimize control and navigation strategies. It is also possible to verify the vehicle’s dynamic stability in different scenarios, test perception and path-planning algorithms in virtual environments, and validate the embedded software before conducting field tests. By transferring a significant portion of the verification steps to the virtual environment, physical testing campaigns become more focused and efficient, reducing the need for multiple prototypes and shortening development time. The result is a more agile engineering process, with lower validation costs and greater confidence in the performance of the AGV or AMR before its deployment in operation. Gibin Joe Zachariah and Sagar Milind Supe carried out the case study above as part of their investigation work. They work with advanced smart products at Siemens Digital Industries Software (DISW) in Michigan, United States. Both are part of the Siemens Simcenter Engineering and Consulting Services team. What a disinfection robot teaches us about the development of any modern AGV or AMR: system simulation enables faster development of intelligent devices, reducing prototype costs and validating autonomous solutions more efficiently. Want to understand how Simcenter technologies can support your engineering projects? Schedule a meeting with CAEXPERTS and discover how to apply advanced simulation to optimize your products and processes. WhatsApp: +55 (48) 98814-4798 E-mail: contato@caexperts.com.br

Postprocess modes at critical speeds and efficiency updates. Why do we need rotor dynamics analysis? Modern turbomachinery, from jet engines to industrial compressors, runs at high speeds and under heavy loads, where even small prediction errors can cause vibration, instability, or failure. Rotor dynamics analysis helps engineers assess how shafts and rotating assemblies behave across the operating range, identify critical speeds, and pinpoint modes that could trigger resonance and reduce performance, safety, or service life. Simcenter 3D Rotor Dynamics, including Simcenter Nastran SOL 414, helps engineers analyze vibration in rotating machinery, predict resonance at critical speeds, evaluate bearing loads, and assess system survivability under realistic operating conditions What’s new in Simcenter 3D Rotor Dynamics 2606 In the Simcenter 3D 2606 release, users can make the simulation process more efficient by accessing essential results in the analysis, with fast processing. In this blog, we present three highlights in the 2606 release: Postprocessing of modes at critical speeds Computation of energy distribution in the full assembly, (even if superelements are used) A faster results format: the Simcenter data file (.scd5) that uses HDF5 architecture Critical speeds of the rotating assembly The computation of an assembly’s critical speeds is essential to the design of a turbomachine. Furthermore, the operating speed range must be far enough from the critical speeds of the system to avoid the resonance phenomenon occurring and inducing high levels of vibrations. Later, we will discuss what ‘far enough’ means and how we can visualize the permitted operating speed range where the turbomachine can operate safely. With the 2606 release, modes corresponding to critical speeds of each rotor can now be output as results of a Nastran SOL414 complex modal analysis, together with the Campbell and stability diagram. In this picture, the complex modal analysis computes the Campbell diagram with modes corresponding to the critical speeds for rotor 1 (yellow circles) and rotor 2 (purple circles) when the speed ratio between the two rotors equals 2.0. This capability is more than a direct critical speeds analysis, as a direct critical speeds analysis is an undamped analysis, with constant bearing properties. With this new capability, you can output modes at critical speeds for each rotor. This removes the limitations of direct critical speeds analysis because damping can be defined in the simulation to compute the stability of the rotating system (viscous damping, modal damping, or hysteretic damping in the connections), and bearing coefficients can be functions of the rotation speeds, which is closer to the realistic conditions. Modes at critical speeds are output for critical speeds at order 1, for a simulation of one or multiple rotors, computed in an inertial frame. Rotors can be modeled by all types of modeling approaches: 1D beam, 2D Fourier multi-harmonic, 3D solid axisymmetric models, 3D cyclic symmetry including the Coleman transformation, and superelements. Results that can be output at critical speeds are mode shapes, stresses, energies, and energies distribution (strain, kinetic and dissipation) in groups of elements. By outputting modes at critical speeds only, instead of at all rotation speeds at every step of the computation, you can decrease the size of the results file by a factor 10, potentially saving a huge amount of resources when results files are stored in a data management system. Energy distribution in the different components of the rotating assembly When analyzing an assembly’s energy distribution at a given rotational speed, such as the critical speed, you can see for each mode which parts are most affected if the corresponding mode is resonant. The energy distribution for a group of elements is presented as a percentage of the total energy, for the strain, kinetic, and new in 2606, the dissipation energy associated with damping. In the demonstration below with the two connected rotors, the low-pressure rotor and high-pressure rotor, we can study the compressor and turbine parts. Then, four different groups can be studied separately for the energy distribution: the low-pressure rotor compressor and turbine, and the high-pressure rotor compressor and turbine. The first critical speed at order 1 (40 Hz) shows that most of the energy is found in the compressor part of the low-pressure rotor, indicating that this part has a higher risk of deformation if this mode is activated. This type of information is very important if we want to identify which modes are most dangerous and in which part of the structure they occur. What happens to the energy distribution when the structure is condensed into superelements Superelements are used a lot in rotor dynamics as this area of dynamics is used in the context of small deformations. Even if the rotor dynamics simulations can manage geometric nonlinearities, the structure is computed in the linear domain. The use of Craig-Bampton superelements is relevant and very efficient in this context to drastically reduce the computation time of the simulation. From past releases, we already know that Simcenter Nastran SOL 414 superelements for rotors enables you to output XY Plots at internal nodes of the superelements. This removes the requirement to define retained nodes on the structure that will only be used to monitor results. For energy distribution, if superelements were used in an assembly, it was not possible to access elements inside the superelements for the calculation of the energy distribution. Indeed, the energy distribution was output by considering the superelement as a whole entity. Starting from Simcenter 3D 2606, if engineers configure groups of elements for energy distribution at the creation step of a Simcenter Nastran SOL 414 superelement, for a rotor or a stator, those groups can be used later for outputting the strain, kinetic and dissipation energy tabulations when the simulation uses the structure condensed in superelements. This capability makes the process more efficient for engineers who leverage the advantages of superelements. Indeed, the recovery of results on the original structure is not needed in this process. The energy tables are generated directly by the simulation process during an eigenvalue analysis, complex modal analysis, or harmonic response. The demonstration hereafter differs from the previous demonstration in that it uses superelements. When the structure is condensed in superelements, the groups of elements are not available, but the user can ask the simulation to use the groups configured at the creation for outputting the energy distribution. Advantages of simcenter data files for the postprocessing Simcenter 3D Rotor Dynamics outputs the results in an efficient format based on an HDF5 architecture, the .scd5 (Simcenter data file) file. It can be easily and quickly uploaded to Simcenter 3D. This result file presents different advantages: there is one single .scd5 file for a simulation, which contains all the results: spatial results for the different subcases, on the selected nodes and elements, or on the whole structure, and the different XY Plots. For engineers working in gas turbine applications and working with API 616 requirements, they can ask for additional XY Plots that enable them to visualize the operating speed range that is ‘far enough’ from critical speeds. Where ‘far enough’ is computed by analytical formulae for the separation margins and amplification factors, provided by the API 616 requirements. Specific functions in the postprocessing of rotor dynamics results enables you to extract results such as the width of the operating speed range, the amplification factors of a selected vibration peak, and the frequency at which the peak occurs. These are then available for later use in an optimization or design of experiments process. Want to explore how Simcenter 3D Rotor Dynamics 2606 can accelerate your critical speed analyses, power distribution, and post-processing of results? The CAEXPERTS team can demonstrate how to apply these innovations to your turbomachinery, compressor, and rotating system projects, reducing simulation time and increasing the reliability of your assessments. Schedule a meeting with us and see in practice how to optimize your rotor dynamics flows. WhatsApp: +55 (48) 98814-4798 E-mail: contato@caexperts.com.br

The latest release of Simcenter Systems 2604 delivers powerful new capabilities that address the most pressing challenges facing engineers today. From advancements in battery pack design and thermal safety validation to expanded gas system simulation and enhanced collaboration workflows, this release empowers engineers to work faster, model greater complexity, and validate designs with unprecedented accuracy. Whether you’re designing next-generation electric vehicles, optimizing pneumatic systems, or pushing the boundaries of extreme-condition simulations, Simcenter Systems 2604 provides the tools you need to accelerate innovation and bring better products to market faster. Supercharge battery pack design and validation The electrification revolution continues, and with it comes increasingly complex challenges in battery pack design, thermal management, and safety validation. Simcenter Systems 2604 introduces six major enhancements to the battery pack assistant that fundamentally transform how engineers approach these critical tasks. Seamless integration with Simcenter Simlab One of the most significant workflow improvements in this release is the ability to import 3D models directly from Simcenter Simlab into the battery pack assistant. This integration eliminates the friction that previously existed when moving between structural and thermal simulation domains. Engineers can now leverage their existing CAD and meshing work from Simcenter Simlab, bringing detailed geometric representations into their battery pack thermal models without manual reconstruction or data translation. This seamless handoff across the Simcenter portfolio not only saves time but ensures consistency and accuracy throughout the development process. Non-conformal interface for flexible cooling layouts Thermal management is critical to battery performance, safety, and longevity, yet designing effective cooling systems has always presented modeling challenges, particularly when dealing with complex geometries where cooling plates and battery cells don’t align perfectly. The new non-conformal interface capability addresses this head-on by allowing engineers to model cooling layouts without requiring perfectly matching mesh interfaces between components. This flexibility means you can accurately simulate real-world cooling configurations, including offset cooling plates, irregular contact surfaces, and multi-layer thermal management systems, all while maintaining simulation accuracy and reducing mesh preparation time. Automated side cooling setup Building on the cooling enhancements, Simcenter Systems 2604 introduces an automated workflow specifically for side cooling configurations. Side cooling has become increasingly popular in battery pack designs due to its space efficiency and thermal performance characteristics, but setting up these models has traditionally been time-consuming and error-prone. The new guided workflow automates the placement, connection, and thermal coupling of side cooling components, dramatically reducing setup time while ensuring best practices are followed. Engineers can now explore multiple side cooling design variants quickly, accelerating the optimization process and helping identify the most effective thermal management strategy for their specific application. Faster sketch generation Performance improvements often go unnoticed until you experience them firsthand, but the 30x speed increase in sketch generation for the battery pack assistant is impossible to ignore. What previously took minutes now happens in seconds. This breakthrough performance enhancement transforms the interactive design experience, allowing engineers to rapidly iterate through different pack configurations, test various cell arrangements, and explore design alternatives without waiting. The impact extends beyond individual productivity. It fundamentally changes the design process, enabling more thorough exploration of the design space and ultimately leading to better-optimized battery packs. Advanced electrochemical modeling with blend electrodes Modern battery cells increasingly use blend electrodes, combining multiple active materials in the anode or cathode to optimize the balance between power density, energy density, cost, and lifespan. However, accurately simulating these multi-material cells has been challenging. Simcenter Systems 2604 enhances both the single particle model with electrolyte (SPME) and the pseudo-2D (p2d) electrochemical models with blend material definition capabilities. Engineers can now define multiple active materials within a single electrode and accurately predict how these blended materials interact during charge and discharge cycles. This capability enables precise optimization of material mixing ratios to achieve target performance characteristics. Critically, it allows for accurate modeling of aging mechanisms for each active material independently. The result is more accurate cell-level predictions that directly inform pack-level design decisions. SOC-dependent thermal runaway modeling Safety is paramount in battery design, and thermal runaway represents one of the most critical failure modes. The challenge is that thermal runaway behavior changes dramatically depending on the battery’s state of charge (SOC). A fully charged battery behaves very differently under thermal stress than a partially discharged one. Simcenter Systems 2604 introduces an enhanced thermal runaway model that explicitly incorporates SOC dependency, allowing engineers to simulate thermal runaway behavior accurately across varying load profiles and charge levels. This eliminates the need for manual kinetic parameter adjustment for each SOC condition, saving valuable engineering time while improving accuracy. Perhaps most importantly, this capability enables adoption of robust thermal runaway demonstration methodologies to accelerate pack validation. By accurately simulating these critical safety scenarios virtually, engineers can significantly reduce reliance on expensive and time-consuming physical testing while ensuring their designs meet stringent safety requirements across the full operational envelope. Expanding gas system simulation capabilities While battery electrification captures headlines, gas systems remain fundamental to countless applications, from pneumatic controls in industrial automation to compressors in HVAC systems and specialized gas handling in extreme environments. Simcenter Systems 2604 delivers three significant enhancements to the gas library that expand simulation capabilities and streamline workflows. Compressor map migration tool Engineers working with compressor models often need to migrate data from the legacy gas mixture library to the more advanced gas library, a process that historically required manual file editing. This tedious work consumed time and introduced potential for errors. The new compressor map migration tool automates this entire process, transforming compressor maps to the standard format used by gas library compressors with a single click. The tool launches directly from the compressor component itself, integrating seamlessly into existing workflows. It supports both table-based and constant efficiency inputs, ensuring flexibility for different types of compressor data, and produces ready-to-use output that’s immediately compatible with gas library models. This automation frees engineers to focus on higher-value design and analysis work rather than data wrangling. Tabulated thermo-physical properties Simulating systems involving specialty gases has always presented challenges. These gases operate at extreme temperatures or pressures, or they lack standard property correlations altogether. Simcenter Systems 2604 now allows tables to be used for defining thermodynamic and transport gas properties, providing unprecedented flexibility. Engineers can input experimental data or highly specialized property tables directly into simulations, defining gas density, enthalpy, entropy, viscosity, and thermal conductivity as functions of pressure and temperature with precision. This capability dramatically expands simulation applicability to non-conventional systems. A prime example is high-voltage circuit breakers involving plasmas reaching temperatures up to 40,000 Kelvin. These conditions fall far beyond the range of standard correlations. With tabulated properties, these extreme applications can now be modeled accurately. Valve builder for gas library Pneumatic valves come in an enormous variety of configurations, with different numbers of ports, positions, and flow characteristics. The sheer number of possible combinations far exceeds what any predefined model library can realistically cover. Engineers frequently need very specific valve configurations that aren’t immediately available, leading to workarounds or compromises. The new valve builder for the gas library solves this problem by providing a dedicated tool for creating custom valve models. Using a flexible graphical interface, engineers can visually configure valve structure, define flow paths, and characterize behavior without writing code. Whether modeling a simple 2-way valve or a complex multi-port, multi-position directional control valve, the valve builder provides the freedom to define exactly what’s needed, unlocking new levels of simulation accuracy for pneumatic systems. Gas turbine simulation with Simcenter Flomaster Gas turbine design demands exceptional precision, particularly when it comes to blade cooling and thermal analysis. The extreme operating conditions, tight tolerances, and complex multi-physics interactions make accurate simulation essential for achieving performance targets while ensuring component durability. Simcenter Flomaster 2604 introduces three powerful enhancements specifically addressing the needs of gas turbine engineers. Enhanced duct scripting with local flow data Custom correlations are often essential for capturing the unique physics of proprietary gas turbine cooling designs, but applying these correlations accurately has been challenging when local flow and wall conditions vary significantly. The enhanced duct scripting interface in Simcenter Flomaster 2604 now exposes segment-level flow data and wall temperatures directly to custom friction and heat transfer calculations. Engineers can access static and total pressure, static and total temperature at each internal node, and wall temperatures broken down by segment and sector. The current segment number is also available, allowing calculations to vary along the length of the duct. Component metadata such as group, type, and title lets scripts know which component they’re running on, enabling reuse of the same script across different ducts with different behavior. This enhanced data access allows engineers to implement proprietary correlations using correct local conditions rather than relying on averaged or external assumptions, significantly increasing confidence in application-specific simulation results. Independent circumferential wall temperature control Cooling passages in gas turbine blades often experience dramatically different temperatures on different sides. For example, a cooling channel may have significantly different temperatures on the trailing edge versus the leading edge, or between the pressure and suction sides. Previously, Simcenter Flomaster could only apply a single wall temperature to the entire perimeter of a duct, forcing engineers to split ducts into multiple components to represent different wall conditions around the circumference. This artificial splitting complicated models and introduced potential for error. The internal duct component now supports up to four independent wall temperatures around the circumference, one per face, using the existing heat transfer and pipe run components. Each face of the duct can be connected to a different heat transfer boundary, eliminating the need for artificial duct splitting. Combined with the existing axial variation capability, engineers now have temperature control in both directions, along and around the passage, from a single component. This enhancement improves cooling performance prediction accuracy while simplifying model setup and reducing the potential for modeling errors. Fully coupled co-simulation for blade design Gas turbine blade design is inherently multi-physics. Aerodynamic loads affect structural deformation, which changes flow paths and cooling effectiveness, which in turn affects metal temperatures and thermal stresses. Loose coupling between thermo-fluid and structural analysis can cause inconsistent blade aero-thermal-structural design results, leading to design iterations, increased risk, and difficulty meeting the tight accuracy requirements demanded by modern blade designs. Simcenter Flomaster 2604 introduces fully coupled co-simulation with iteration-level thermo-fluid and structural synchronization between Simcenter Flomaster and Simcenter 3D. This true iteration-level coupling ensures consistent multi-physics convergence across tools, allowing engineers to meet blade design accuracy requirements that would be impossible with loose coupling approaches. The fully coupled predictions reduce design risk by capturing the true interaction between aerodynamic, thermal, and structural phenomena, providing engineers with the confidence that their virtual predictions accurately represent real-world blade behavior. This capability will be available with the Simcenter 3D 2606 release. Enhanced visualization and mechanical simulation Understanding simulation results is just as important as generating them, and visualization plays a crucial role in extracting insights from complex mechanical systems. Simcenter Systems 2604 introduces a new 3D mechanical domain within 3D scenes that modernizes how engineers visualize and communicate mechanical simulation results. This enhancement brings advanced animation capabilities and contemporary visualization techniques to mechanical domain models, making it easier to understand dynamic behavior, identify potential issues, and communicate findings to stakeholders. The modernized visualization environment provides clearer insights into mechanical system performance, supporting better decision-making throughout the development process. Seamless integration and collaboration Modern engineering is collaborative, and effective collaboration requires robust tools for model sharing, version control, and variant management. Simcenter Systems 2604 delivers three key enhancements that strengthen integration and collaboration workflows. Variable step solver in license-free FMUs Functional mock-up units (FMUs) have become a standard way to share validated simulation models across organizations and tools, but limitations in solver capabilities have sometimes constrained their applicability. Simcenter Systems 2604 now supports variable step solvers in license-free FMUs, providing more flexible and efficient model deployment. This enhancement allows exported FMUs to automatically adjust their time step based on system dynamics, improving both accuracy and computational efficiency. Engineers can now deploy sophisticated models to partners, suppliers, or other departments with confidence that they’ll run efficiently without requiring Simcenter licenses. Parameter sets for model variants Managing multiple variants of a model has traditionally meant maintaining separate model files or manually changing parameters, both error-prone approaches. Different configurations, operating conditions, or design alternatives all required careful tracking. The new parameter sets capability provides centralized management of model variants through organized parameter collections. Engineers can define multiple parameter sets within a single model, each representing a different configuration or operating scenario, and switch between them instantly. This approach reduces errors, ensures consistency, and makes it far easier to explore design alternatives or maintain models for different product variants. External Git repository integration Version control is essential for managing model evolution, enabling collaboration, and maintaining traceability, yet integrating simulation models with modern version control systems has often required external tools and manual processes. Simcenter Systems 2604 now provides direct integration with external Git repositories, including GitHub, GitLab, and Azure DevOps, directly from within Simcenter Amesim. Engineers can commit changes, track history, manage branches, and collaborate with team members using industry-standard git workflows without leaving their simulation environment. This integration brings simulation model management in line with modern software development practices, improving collaboration, traceability, and overall project management. Experience Simcenter Systems 2604 today Simcenter Systems 2604 represents a significant leap forward in systems simulation capabilities, with particular emphasis on battery pack design and validation, expanded gas system modeling, and enhanced collaboration. These enhancements empower engineers to tackle increasingly complex challenges with greater speed, accuracy, and confidence. Want to see in practice how the features of Simcenter Systems 2604 can accelerate your projects, from advanced battery development to complex system simulation and collaborative integration? Schedule a meeting with CAEXPERTS and discover how to apply these innovations to increase efficiency, reduce development cycles, and improve the accuracy of your simulations with the support of CAE solutions experts. WhatsApp: +55 (48) 98814-4798 E-mail: contato@caexperts.com.br

In Siemens' recent video on tips and tricks for Designcenter™ NX™ software, it was explored how Synchronous Modeling allows for quick and efficient modifications to 3D geometry. This set of commands makes it extremely easy to implement rapid design changes without needing to understand how a model was originally built, significantly increasing productivity, even in large assemblies. Check out the video below or scroll down to learn more about how to leverage Synchronous Modeling commands to make fast, flexible design changes across your models and assemblies. Move Face – Reposition Geometry with Ease One of the main features of Designcenter NX Synchronous Modeling is the ability to directly manipulate your geometry and the Move Face command is a perfect example of this. Rather than revisiting your modeling history or rebuilding features, Move Face allows you to simply select any face and reposition it instantly. You can click and drag using the directional arrows to adjust the distance or angle interactively, or manually type in precise values directly in the command window. Figure 1: Move Face command feature showing ability to offset a selected face Figure 2: Move Face command feature showing ability to adjust angle of a selected face The Move Face command gives you direct, intuitive control over your geometry no history required. This flexibility makes Move Face an ideal tool for rapid design iterations. Whether you need to shift a surface by a few millimeters or adjust the angle of a feature, the command adapts to your workflow, putting you in full control of your design without unnecessary complexity. Resize Hole Command When working with components that contain multiple holes, maintaining consistency is critical. The Resize Hole command within Synchronous Modeling allows users to quickly edit and resize hole features directly on the geometry. Once a hole face is selected, the command window presents the Face Finder tab, where the Find Clone option can be found. This powerful feature combined with the Resize Hole command allows you to select and edit multiple holes simultaneously saving time and ensuring consistency across your model. Figure 3: Resize Hole command with find clone selection filtering being demonstrated Figure 4: Resize Hole command demonstrating editing of four separate holes simultaneously This feature acts as a smart selection filter, automatically identifying and grouping identical holes so that you can edit all of them simultaneously in a single operation. Instead of modifying each hole individually, you can make a single change that propagates across all matching instances, ensuring uniformity and dramatically reducing the time spent on repetitive edits. Replace Face – Achieving Symmetry and Clean Geometry Designs often require a level of symmetry or uniformity that can be difficult to achieve through traditional modeling methods. The Synchronous Modeling Replace Face command addresses this by allowing users to replace selected faces with other selected faces, effectively combining or reshaping geometry to produce cleaner, more symmetrical models. The Replace Face command simplifies the process of achieving symmetrical and uniform geometry without the need to rebuild features from scratch. This command is particularly valuable when working with imported geometry or models without feature history, where traditional symmetry tools may not be available. By directly replacing faces, you can quickly bring your model into alignment with your design intent, regardless of how it was originally constructed. Delete Face Sometimes the most effective design change is the removal of unnecessary geometry. The Synchronous Modeling Delete Face command allows users to remove selected faces from a component, resulting in a cleaner, smoother part. Rather than suppressing features or editing a history tree, you can simply select the faces you want to remove and delete them directly. The Delete Face command streamlines your components by removing unwanted faces, producing smooth, clean geometry in just a few clicks. Figure 5: Delete Face command in action Figure 6: Results of Delete Face command removing unnecessary geometry This straightforward approach makes it easy to clean up imported models, remove outdated features, or simplify geometry for downstream processes all without the need to understand or navigate the original modeling history. Resize Pattern – Adjust Patterns On the Fly When working with patterned features such as bolt holes, the Resize Pattern command within Synchronous Modeling provides a fast and intuitive way to modify both the layout and count of a pattern. Accessible through the More drop-down in the Synchronous Modeling group, this command allows you to simply select one of the faces within the pattern, and Designcenter NX will automatically recognize and load the full pattern for editing. The Resize Pattern command automatically detects and loads existing patterns, allowing you to adjust count and pitch distance quickly and efficiently. Figure 7: Resize Pattern feature command window identifying pervious patterns Figure 8: New pattern generated for Resize Pattern feature From there, you can adjust key parameters such as the count and pitch distance, preview your changes using the Show Results option, and confirm or discard the update as needed. This level of flexibility ensures that pattern modifications can be made rapidly and accurately. Radiate Face — Offset Geometry Along the Axis of Revolution For components with rotational geometry, the Radiate Face command in Synchronous Modeling offers a specialized and highly effective way to offset faces. Unlike a standard offset that moves faces normal to their surface, Radiate Face offsets geometry normal to the axis of revolution making it the ideal tool for maintaining the integrity of cylindrical and revolved features during design changes. This feature allows for proper modeling of shrinkage and machining stock and allows for the press or interference fit geometries. The Radiate Face command ensures that offsets on revolved geometry remain accurate and consistent by referencing the axis of revolution rather than the face normal. Figure 9: Radiate Face command showing offset of a geometry normal to the axis of revolution By simply selecting the faces you want to adjust and specifying the desired offset distance, Designcenter NX handles the complexity of the offset calculation, ensuring that your geometry remains accurate and well-defined throughout the modification. Summary of Synchronous Modeling Synchronous Modeling in Designcenter NX represents a fundamentally different and more flexible approach to design modification. By working directly with geometry rather than feature history, these commands Move Face, Resize Hole, Replace Face, Delete Face, Resize Pattern, and Radiate Face collectively empower users to make fast, precise, and confident design changes across any model or assembly, regardless of its origin. Whether you are refining an imported model, making rapid iterations on an existing design, or managing changes across a large assembly, Synchronous Modeling ensures that your workflow remains efficient, flexible, and fully in your control. Designcenter NX Synchronous Modeling transforms how engineering teams make design changes, bringing more agility, flexibility, and productivity even to complex assemblies. Want to discover how to apply these features to your workflow and accelerate your development processes? Schedule a meeting with CAEXPERTS and see how we can help your company get the most out of Designcenter NX. WhatsApp: +55 (48) 98814-4798 E-mail: contato@caexperts.com.br

Real-Time Collaborative Workflow Editing for Engineering Teams Engineering teams today are under constant pressure to explore more design alternatives, faster—all while managing increasingly complex, multidisciplinary systems. Yet collaboration often becomes the bottleneck. Disconnected workflows, lack of real-time visibility, and fragmented compute resource management make it difficult for distributed teams to work together efficiently and confidently. Simcenter HEEDS Connect 2604 tackles these challenges head-on. This release introduces breakthrough capabilities for real-time collaborative editing, AI‑accelerated design exploration, and centralized compute resource management, enabling teams to explore, iterate, and decide together—online and in real time. Packed with powerful enhancements, Simcenter HEEDS Connect 2604 transforms how engineering teams collaborate. Whether you’re building multidisciplinary system models, running AI-driven exploration studies, or coordinating complex workflows across organizations, this release removes friction from collaboration and accelerates results. Teams can now edit workflows together in real time, align instantly on decisions, and move from exploration to insight faster than ever before. Real‑Time Collaborative Workflow Authoring—Beyond Parameter Editing Simcenter HEEDS Connect 2604 delivers comprehensive workflow authoring capabilities that go far beyond simple parameter editing: Structural workflow editing: Modify groups, analyses, and connections directly in the web interface. Portal-specific settings: Configure analysis-specific settings for your workflows without leaving the collaborative environment. Loop configuration: Edit loop execution and output settings with immediate persistence across all users. Real-time collaboration: Instant synchronization to ensure consistency across your entire team. Seamless Simcenter HEEDS MDO integration: Changes made in Simcenter HEEDS Connect are immediately reflected in Simcenter HEEDS MDO, maintaining perfect alignment between environments. Engineering teams can now collaboratively shape workflow structures, respond instantly to evolving requirements, and continuously refine their design‑exploration processes — all directly in the web environment. This marks a significant leap toward fully cloud‑native workflow management, delivering the agility of the cloud without sacrificing the power and flexibility engineers rely on. Evaluate multidisciplinary systems with a single click Designing complex systems with interconnected disciplines has always been a challenge. How do you evaluate the response of a multidisciplinary system where outputs from one discipline feed into another? How do you propagate variables and files through a hierarchy of interconnected analyses? Simcenter HEEDS Connect 2604 introduces the Evaluation Matrix, a powerful new capability that transforms multidisciplinary system analysis. Previously, engineers had to manually coordinate multiple studies and transfer data between them—a time-consuming and error-prone process. The Evaluation Matrix eliminates this friction by enabling system-level analyses with automatic variable propagation. Key capabilities include: Efficiency built in: Feed-forward variable propagation automatically propagates outputs from higher-level studies to inputs of dependent studies. Maintain consistency: Shared variable management links inputs across multiple studies throughout your system. One click execution: Run your entire multidisciplinary system analysis with one click — no iterative loops, just clean hierarchical evaluation. Gain deeper insights: Streamlined system analysis enables you to evaluate the response of interconnected disciplines efficiently, understanding how your system behaves as a whole. Evaluate complex multidisciplinary systems with confidence, eliminating manual data transfer and enabling true system-level design exploration. Visualize and manage AI-accelerated studies Simcenter HEEDS Connect 2604 introduces comprehensive AI simulation predictor integration that makes AI-accelerated studies fully visible and manageable in the collaborative web environment. Explore boosted designs and configurations Clear design distinction: Filter and visualize predicted vs. simulated designs in database tables and scatter plots with custom coloring. Comprehensive model information: View prediction model parameters including initial designs, training models, prediction levels, and constraint confidence settings. Grouped parameter editing: Review boost parameters across multiple analyses simultaneously. Input/output visualization: Explore available and selected inputs and outputs for each boosted analysis. Multi-selection comparison: Select multiple boosted items and compare their properties concurrently, with common values clearly displayed. Engineers can now fully leverage AI Simulation Predictor capabilities with Simcenter HEEDS Connect, accelerating design exploration cycles while maintaining complete visibility into model configurations and prediction accuracy. Centralized compute resource management Simcenter HEEDS Connect 2604 introduces the Managed Resource Catalog, transforming how organizations manage and deploy compute resources across engineering teams: Administrator-controlled definitions: Simcenter HEEDS Connect administrators can define and maintain compute resources in a central catalog accessible to all users. Eliminate setup errors: Managed resources come with pre-defined analysis of portal configurations, eliminating setup errors. Shared Across All HEEDS MDO Users: Resources defined in Simcenter HEEDS Connect can be leveraged by all Simcenter HEEDS MDO users in your organization. Define once, apply everywhere: Eliminate duplicate definitions and maintain resource configurations across different installations. Reduced configuration errors: Standardized resource configurations eliminate inconsistencies from misaligned copies. Maintain consistent compute resource configurations across entire engineering organizations, reducing errors and simplifying resource management for everyone. Cloud-based licensing with named user licenses Simcenter HEEDS Connect 2604 joins the Simcenter Named User License portfolio, bringing cloud-based licensing capabilities to the collaborative design exploration platform: Centralized user support: Unique centralized session for each user operation to enable multiple users to work simultaneously without conflicts. Session management: View secure identifier session expiry dates and revoke sessions directly from Simcenter HEEDS Connect. Seamless cloud integration: Leverage the ease of use of Named User Licensing with automatic session management. Simcenter cloud licensing: Simcenter HEEDS Connect now aligns with the broader Simcenter cloud licensing infrastructure. Teams can now access Simcenter HEEDS Connect with the same cloud-based licensing convenience they enjoy across the Simcenter portfolio, with robust and centralized support for concurrent users. The bottom line Simcenter HEEDS Connect 2604 represents a significant step forward for engineering teams committed to advancing their collaborative design exploration capabilities: Comprehensive workflow editing with real-time collaboration Multidisciplinary system evaluation with the new Evaluation Matrix AI-accelerated design exploration with full AI simulation predictor integration Centralized resource management with the Managed Resource Catalog Cloud-based licensing with Named User License support As a leader in simulation and test solutions, Siemens continues to advance collaborative engineering capabilities that help teams across aerospace, automotive, and industrial equipment industries accelerate innovation. Whether you’re collaborating on complex workflows, evaluating multidisciplinary systems, leveraging AI predictions, or managing compute resources across your organization, Simcenter HEEDS Connect 2604 empowers you to explore possibilities faster, work together seamlessly, and deliver better designs — all while collaborating smarter in the cloud. Transform your engineering team's collaboration with Simcenter HEEDS Connect 2604. With real-time workflow editing, AI integration, and centralized resource management, your company can accelerate decisions and improve multidisciplinary projects with much greater efficiency. Schedule a meeting with CAEXPERTS and discover how to apply these innovations in practice to contribute to your results. WhatsApp: +55 (48) 98814-4798 E-mail: contato@caexperts.com.br

Modernized design optimization with AI surrogates, streamlined resource management and enhanced simulation integration This blog outlines how the latest release from Simcenter HEEDS 2604 accelerates design optimization workflows for engineers working with high frequency electromagnetic simulations, CFD, and multidisciplinary optimization – delivering faster compute resource management, AI-powered surrogates, and enhanced simulation integrations. Compute resource management reimagined Optimization projects often demand significant computational resources. Managing remote devices, schedulers, cloud services, and local execution a tedious effort – until now. The new resource catalog Simcenter HEEDS 2604 reworks the user experience for distributed execution by revamping remote execution capabilities into a new Resource Catalog that transforms how you manage and deploy compute resources: One-click resource creation: Set up any resource type with a just a few clicks. Managed catalogs: Download pre-configured managed resources from Simcenter HEEDS Connect for immediate use, or customize them by copying to your local catalog and modifying locked configurations. Multiple submission items: Create multiple submission items on the same device using direct submission, PBS, LSF, SLURM, MSHPC, or custom schedulers – all with automatically configured default parameters. Pre-configured job templates for Rescale: Leverage Rescale’s cloud computing power with pre-configured job template IDs that Simcenter HEEDS clones automatically. Easy resource access: Select pre-defined resources directly from the Process tab, with smart filtering to show only resources with portal-specific properties. Persistent configuration: Mapped local and remote drives mean you don’t have to redefine paths again – your resource configuration carries across all your Simcenter HEEDS projects. The payoff? No more tedious resource reconfiguration. Deploy analyses across diverse computing environments with confidence and consistency. Resource usage optimization for non-optimization studies Fast running analyses in design of experiments studies can fill up resources and consume significant disk space. Simcenter HEEDS 2604 allows for the option of enhanced control over resource allocation during the execution of DOE, Robustness and Reliability, and Evaluation Only studies. The new resource allocation option helps you balance computational efficiency with disk space management based on your study’s specific needs: Opt-in resource control: Prevent non-optimization studies from unexpectedly consuming excessive storage and execution resources. A modernized Neural Network builder with enhanced capabilities Simcenter HEEDS 2604 introduces a modernized Neural Network builder within Simcenter HEEDS POST that makes AI-powered surrogates faster to train and seamless to integrate into optimization workflows. Explore the enhanced Neural Network Builder Simcenter HEEDS 2604 delivers a modernized Neural Network builder. Here’s what’s new: GPU-accelerated training: Significantly reduce model training time with GPU acceleration – enabling faster surrogate model development for optimization workflows Automatic early stopping: Prevent overfitting as the system automatically stops training as soon as your model converges. Seamless workflow integration: Export your trained neural networks to your optimization workflow with a single click. ONNX format compatibility: Models are automatically saved in ONNX format for maximum compatibility and portability. Easy comparison and extension: Save, evaluate, and compare your trained models with other surrogates in Simcenter HEEDS POST effortlessly. Need to refine your model? Simply extend or continue training without starting from scratch. Engineers can now easily replace computationally expensive analyses with accurate neural network surrogates, speeding up optimization cycles while maintaining the fidelity their designs demand. Monitor the convergence of your multi-objective study Designing products with competing objectives is always a challenge. How do you know if your multi-objective Pareto optimization is actually converging? How do you know when feasible solutions have emerged? And what if you need to justify additional computational budget to your stakeholders? Introducing the Pareto convergence plot Simcenter HEEDS 2604 introduces the Pareto convergence plot, a powerful new run-time analytics feature that transforms how you monitor multi-objective studies. Track convergence behavior during the optimization run and make informed decisions on the fly. Key capabilities include: Convergence monitoring: Track the evolution of Pareto solutions across optimization cycles to assess convergence effectiveness and determine if additional computational budget is justified – all while the study is running. Feasibility detection: See exactly when feasible solutions emerge. Monitor the convergence of your multi-objective studies, eliminating guesswork, and enabling smarter optimization budget allocation decisions. End-to-end automated Altair Feko analysis and optimization Simcenter HEEDS 2604 introduces a set of brand-new Altair Feko portals which deliver comprehensive optimization capabilities for high-frequency electromagnetic simulations: Integrated workflow: Set up complete CADFEKO, Feko Solver, and POSTFEKO processes directly within Simcenter HEEDS, with the capability to run each portal on a separate compute resource thereby streamlining turnaround time. Rich visualization: Get deeper insights with comprehensive visualization files for detailed results analysis. Interactive data exploration: Leverage Simcenter HEEDS-specific plot formats with hover-over data points for detailed, interactive insights into your optimization results. Now Altair Feko users can optimize antennas, RF components, and other high-frequency electromagnetic devices easily. Enhanced Ansys Fluent and Fluent Meshing Portals For engineers working with Ansys Fluent, Simcenter HEEDS 2604 brings significant enhancements powered by the Fluent’s Python API. The new and improved Fluent integration includes: Streamlined design process: Conduct geometry modifications, remeshing, and mesh/zone replacement all within a robust, parametric framework. Integrated geometry and meshing: Move from geometry to CFD simulation in one cohesive workflow. Use the new Fluent portals to execute complete parametric design-to-CFD workflows. Faster parsing for Siemens Designcenter (NX) and Simcenter 3D Working with large, complex designs from Siemens Designcenter (formerly NX) or Simcenter 3D? Simcenter HEEDS 2604 eases the integration of your models. The new release provides a solution to large, complex design challenges in Siemens Designcenter (NX) and Simcenter 3D with significant parsing improvements that transform the experience of working with enterprise-scale models: Faster parsing: Using a new group-based parsing approach, Simcenter HEEDS 2604 can process models with thousands of expressions significantly faster. The bottom line Simcenter HEEDS 2604 represents a significant step forward for engineers and organizations committed to advancing their design optimization capabilities: Centralized Resource Catalog for streamlined resource setup Modernized Neural Network with improved integration Run‑time Pareto convergence tracking with new plotting tool Expanded simulation support with Feko integration and enhanced Fluent portal As a leader in simulation and test solutions, Siemens continues to advance collaborative engineering capabilities that help teams across aerospace, automotive, and industrial equipment industries accelerate innovation. Whether you’re optimizing antennas, fluid flow, structural designs, or complex multi-physics systems, Simcenter HEEDS 2604 enables you to explore possibilities faster, make more confident decisions, and deliver better designs – all while working smarter, not harder. Ready to accelerate your results with AI-driven optimization and integrated simulations? Schedule a meeting with CAEXPERTS and discover how to apply Simcenter HEEDS 2604 to your engineering workflow, reducing computational costs, increasing analysis speed, and improving the quality of your design decisions. WhatsApp: +55 (48) 98814-4798 E-mail: contato@caexperts.com.br

Rotating systems such as Gas Turbines are used for power generation in the energy industry, or propulsion in the aerospace industry and are subjected to harsh conditions with high temperatures and loads. Under such stress, defects induced during the manufacturing process can have catastrophic effects on the performance of a part. When there is an imbalance in the external loading or when internal imperfections affect the symmetry of the system, vibrations can occur that, depending on the rotational speed and intrinsic characteristics of the system, damage part or the whole assembly. The thermal deformation (thermal bow) of a turbomachine appears in the presence of a vertical temperature gradient, induced by the cooling process after a shutdown of the engine. When the engine restarts, the rotor bow can be responsible for high vibrations in the engine and must be studied carefully. Bow can also be due to static forces or pressure. In such a system we can expect vibrations when the structure deforms due to temperature and static load. but vibrations of each rotating part can also be due to its imperfections, such as an eccentricity of the centre of mass of a bladed disk. Gas turbine where the high-pressure rotor (outer part at the centre) rotates three times faster than the compressor and turbine (inner part). Blades are modelled by lumped inertia on the rotor axis Moreover, many rotating systems are made of different components which do not rotate at the same speed. For example, in a gas turbine, the high-pressure turbine and compressor stages can rotate three times faster than the low-pressure turbine and compressor stages. It is therefore necessary to understand how rotation-dependent defects will be considered in the harmonic response. This post addresses two important scenarios in harmonic response: the dynamic unbalance induced by a deformed shape (thermal bow), and multiple unbalances on different rotating parts. When thermal and static deformation induce vibrations of a rotating structure Rotating systems often experience harsh conditions of temperature, pressure, or loads that might create vibrations of the system. Furthermore, the dynamics can be affected by defects in the rotor due to manufacturing, like the non-uniform distribution of mass or a misalignment of the shaft. In this blog, we see how the external conditions causing rotor deformation will influence the vibrational behaviour of the system. The bow shape induced by the thermal bow deforms the structure making it asymmetric about the rotor axis. This deformation moves the mass so that it is no longer uniformly distributed around the rotor axis. The eccentricities with respect to the rotor axis induce unbalanced loads that are proportional to the square of the rotation speed. In the above example (1), a rotating system is made of two rotors: the High-Pressure rotor rotates 3 times faster than the Low-Pressure rotor. The system is modelled by 2D Fourier elements (axisymmetric model with Fourier harmonics), which is the best alternative to 3D models, in terms of accuracy and CPU time. External conditions are such that a static force deforms the rotors in the form of a bow. (2) The bow shape breaks the symmetry of the rotor around the rotation axis. Consequently, it naturally induces an imbalance on both rotors that is equal to: Massa x ecc x Ω 2 Where Ω is the rotor speed of each rotor and ecc is the eccentricity deduced from the deformed shape. Those unbalances on both rotors cause vibrations in the whole system that can be studied in the operating frequency ranges, to ensure that levels of vibrations are acceptable. Vibrations are represented for a selected frequency and selected harmonic in (3), and orbit plot in (4) can reproduce the total vibration of the system for a selected location and frequency. Later in this blog, we will discuss how software can manage unbalanced loads that correspond to different rotational speeds. Imperfections in the rotating parts induce undesirable loads in the rotating system Initial defects coming from the manufacturing process are independent of the external loading on the structure. However, they induce loads in the structure that result in vibrations of the structure. Among the typical scenarios in rotor dynamics that require testing, the simulation of unbalanced defects is the top priority for engineers. An unbalanced defect occurs when the mass and geometric centres do not coincide. Unbalance creates a load that is amplified with the rotor’s rotation speed Ω, proportionally to Ω2. In the clip below, the unbalanced rotating system mounted on flexible bearings can show very high vibration amplitudes when the system rotates, especially for certain rotation speeds. The peaks in the response correspond to the unwanted critical speeds of the system. Multiple harmonics in frequency response In an assembly made of many rotors rotating at different speeds, multiple unbalanced defects can exist where each induces forces that are linked to different rotational speeds, and subsequently different frequencies. When studying the harmonic response, engineers are interested in the behaviour of the system for one full cycle, in a range of frequencies (or rotation speeds). With a single defect, the equation of motion is solved for a single frequency ω: or by defining the dynamic stiffness matrix Z(Ωω)q(ω)=g(ω) Now, for multiple defects corresponding to different rotation speeds, Simcenter 3D Rotor Dynamics uses multiple harmonics simultaneously to solve the simulation. Each harmonic corresponds to the individual frequency (rotation speed) of each rotor. Equation (5.1) becomes a system of equations to be solved, for different frequencies ω. Equations of the system are not coupled when the rotors are axisymmetric so the whole assembly can be solved in a fixed reference frame, with the bearings’ behavior represented by linear functions. In a simulation using multiple harmonics, results are output for each individual harmonics ω1, ω2,… , making postprocessing less intuitive compared to the mono-harmonic case. Fortunately, it is possible to recombine results of all harmonics in the time domain through orbit plots for one or several cycles to display the final result. In the example of the dual rotors, where the unbalances were deduced from the deformed shape, two harmonics (ω1 and ω2) were used according to the two rotor speeds Ω1 for the low-pressure rotor, and Ω2 =3Ω1 for the high-pressure rotor. For each reference frequency, the result for the displacement in the Y direction for harmonics ω1 and ω2 are shown in the picture below. Having identified the peak of displacements at ω1=55 Hz, we can check the total vibration by combining the two harmonics for the Displacement in the X and Y directions (perpendicular to the rotor axis): X (t) = X ω1 e i (w1 t + φ 1) + X ω2 e i (w2 t + φ 2) Y (t) = Y ω1 e i (w1 t + φ 1) + Y ω2 e i (w2 t + φ 2) Where (Xω1, Yω1) and (Xω2, Yω2) are the vibrations computed in the harmonic 1 and 2 respectively. A point on a rotor axis that is linked to a high-pressure rotor can be represented with an orbit plot (X(t), Y(t)). Where, one period at the reference frequency of the first (low pressure) rotor corresponds to 3 cycles of the second (high pressure) rotor: With such an orbit plot, the engineer can determine if the vibration in the operating frequency range is acceptable. A demo of how this can be done in Simcenter 3D is shown below. With harmonic response, the engineer has the possibility to study the behavior of their rotating system in a range of frequencies and rotation speeds. With such analysis, defects like unbalance or misalignment can be studied in a frequency range, and external loads can be applied as a function of frequency. In this blog post, we presented how Simcenter 3D Rotor Dynamics can study simultaneous unbalance defects on different rotors rotating at different speeds, but also the natural unbalance that can be deduced from a deformed geometry (thermal bow or static bow) due to external factors such as applied loads and temperature. Simcenter 3D streamlines the complete workflow from the definition of the geometry to the post-processing tools and includes dedicated tools to complete all the steps in the process. Ensure the reliability and performance of your rotating systems before vibrations and imbalances compromise your projects — talk to CAEXPERTS. Our experts can help you apply advanced simulations with Simcenter 3D to identify faults, optimize dynamic behavior, and reduce operational risks. Schedule a meeting and discover how to bring more safety and efficiency to your systems. WhatsApp: +55 (48) 98814-4798 E-mail: contato@caexperts.com.br

Introduction In the rapidly evolving realm of e-mobility and electrical stationary storage systems, it becomes crucial to have precise battery models for effective system design. Battery models can be broadly categorized into two types: the equivalent circuit model and the electrochemical model: The equivalent circuit model simplifies the complex electrochemical processes occurring within a battery by representing it as an electrical circuit composed of resistors, capacitors, and voltage sources. This model provides a practical and straightforward approach to simulate battery behavior and is widely used in system-level simulations (e.g., battery pack simulating) and real time application (e.g., battery management system in the vehicle). On the other hand, the electrochemical model or P2D (Pseudo-Two-Dimensional) model delves deeper into the intricate electrochemical processes that take place within a battery. It considers the various physical and chemical phenomena, such as lithium-ion diffusion, migration, and chemical reactions, to provide a more accurate representation of battery performance. The electrochemical model considers factors like electrode kinetics, concentration gradients, and temperature effects, making it suitable for detailed analysis and research-oriented studies. A brief comparison of both models is given in the table below. While the equivalent circuit model offers simplicity and ease of implementation, it may not capture all the nuances of battery behavior, such as lithium plating. Conversely, the electrochemical model provides a more comprehensive understanding but requires more computational resources and detailed input parameters. A brief comparison between the equivalent circuit model and the electrochemical model In this article, a focus is given to the electrochemical model in Simcenter Amesim. You will find out the main features of this model which allow you to get insight into different critical battery behaviors, such as: Electrochemical process inside the battery cell Lithium plating Aging Simulating the electrochemical process inside the battery Figure 1 gives a schematic representation of the battery P2D electrochemical model. The active materials are depicted as spherical particles for each electrode. Each electrode is discretized into multiple layers, with each layer containing one particle in contact with the electrolyte. Each particle is also discretized into multiple layers. This approach allows for a detailed understanding of the behavior and interactions of different elements (e.g., active materials, Li-ion, electrolyte) within the battery system. By representing the battery in this manner, the model can capture the intricacies of particle-level phenomena, contributing to a comprehensive analysis of battery internal behaviors, such as the Li-ion concentration at the surface of different particle surfaces, the voltage drops on different elements of the battery, the average anode potential, etc. Simcenter Amesim also offers a simplified version of the P2D model, known as the single particle model with electrolyte (SPMe), which reduces computational complexity by representing each electrode with a single particle. This version is well-suited for scenarios requiring quicker analysis while maintaining effective simulation accuracy. Figure 1: Schematic representation of the battery P2D electrochemical model Figure 2 shows the simulation results of a constant discharge with the P2D model in Simcenter Amesim for a 5Ah NMC/SiC battery cell. The parameter values of the P2D model are taken from the work of Chen et al. [2]. Besides the cell voltage, the model can simulate various internal indicators, including the ohmic and kinetic overpotential within each electrode, electrolyte lithium concentrations, and mean diffusion overvoltage in the electrolyte. Figure 2: Simulation results of a constant discharge with the battery P2D electrochemical model It is also possible to interconnect multiple Simcenter Amesim P2D models to have a first level discretization of the cell. Figure 3 shows such an example with a 4×3 discretization for a prismatic cell. Each discretization node has a P2D model coupled with a thermal mass to calculate the local temperature. The current collectors are also discretized by using resistances. Compared to a detailed CFD simulation with thousands of meshes of the cell, this approach helps to get fast simulation results and limit the scope of the detail simulations to be carried out in a CFD software such as the 3D cell design capabilities of Simcenter STAR-CCM+. Figure 3: Example of battery cell discretization for local thermal study Lithium-plating Lithium plating occurs when metallic lithium deposits on a battery’s negative electrode during improper charging (e.g., fast charging at low temperature), leading to reduced efficiency and safety hazards. As fast charging is one of the important usage scenarios for electric vehicles and other battery-based systems (e.g., eVTOL, battery stationary storage systems), employing techniques such as model estimation is crucial for understanding and preventing lithium plating. With the Simcenter Amesim electrochemical model, you can easily get access to an internal variable of the model to detect the risk of lithium plating occurrence. This variable is the negative electrode liquid to solid overpotential. During the charge, lithium plating can happen if the negative electrode liquid to solid overpotential drops below 0 V. Figure 4 shows an example of the CCCV charge simulations results for a 45 Ah NMC/C battery cell at two different temperatures. The results indicate that towards the end of the charge at 10 °C, there is a risk of lithium plating occurrence as the negative electrode liquid to solid overpotential drops below 0 V. Figure 4: Example of simulation results for CCCV charges for a 45Ah NMC/C cell Aging With the Simcenter Amesim battery electrochemical model, the battery aging behavior can also be simulated via the modeling of different aging mechanisms causing capacity loss such as the growth of the SEI layer and the lithium plating. Figure 5 presents an example to simulate the loss of capacity due to lithium plating for a high energy NMC/C cell at two different temperatures. Figure 5: Example of simulation results for capacity loss due to lithium plating at two different temperatures References 1. Astaneh, M.; Andric, J.; Löfdahl, L.; Maggiolo, D.; Stopp, P.; Moghaddam, M.; Chapuis, M.; Ström, H. Calibration Optimization Methodology for Lithium-Ion Battery Pack Model for Electric Vehicles in Mining Applications. Energies 2020, 13, 3532. 2. C.-H. Chen, F. B. Planella, K. O’Regan, D. Gastol, W. D. Widanage, and E. Kendrick, “Development of Experimental Techniques for Parameterization of Multi-scale Lithium-ion Battery Models,” J. Electrochem. Soc., vol. 167, no. 8, p. 080534, Jan. 2020 3. Demo “Electrochemical NMC-SiC Pseudo-Two-Dimensional (P2D) battery model comparison”, Simcenter Amesim Help, V2410, 2024 4. Demo “Charging strategies based on negative electrode overpotential – Lithium plating detection”, Simcenter Amesim Help, V2410, 2024 5. Demo “Lithium plating modeling”, Simcenter Amesim Help, V2410, 2024 Ensure more accurate decisions in battery development with expert support. Schedule a meeting with CAEXPERTS and discover how to apply advanced electrochemical models in Simcenter Amesim to improve the performance, safety, and lifespan of your systems. WhatsApp: +55 (48) 98814-4798 E-mail: contato@caexperts.com.br

Turbomachinery represents one of the most challenging and sophisticated fields of modern engineering. Its development demands operation under extreme conditions of temperature, pressure, and speed, imposing stringent requirements on materials, mechanical design, and operational reliability. Currently, jet engines and other turbines operate at temperatures exceeding 1,500 °C and under severe pressure levels, in regimes that surpass the conventional limits of most materials. Even so, these systems must maintain high efficiency, structural integrity, and low weight, especially in aeronautical applications. In this context, the advancement of turbomachinery depends directly on the ability to understand, predict, and control the behavior of its components and operating phenomena through experimental testing, rigorous simulations, and the continuous building of knowledge over time. Several engineering disciplines need to work together to create a gas turbine In other words, artificial intelligence needs good input data. The difference is that modern AI can process more data, learn from it faster, and apply those lessons on an unprecedented scale, shaping the future of turbomachinery in ways we are only beginning to understand. The hurdles OEMs face in a fast-paced world The future of turbomachinery depends on balancing multiple engineering challenges; all must be optimized simultaneously Today's turbomachinery manufacturers and suppliers face an ambitious challenge: designing and producing engines that are more flexible, more powerful, larger, with faster launch times, more sustainable, quieter, lighter, and with optimized cooling. Optimizing one attribute often means making concessions in another, requiring sophisticated tools and specialized knowledge to achieve the perfect balance. This balance will define the future of turbomachinery development. Furthermore, disconnected workflows between design and manufacturing create a problem. They disrupt the knowledge chain that should flow from design to production. When a design team in one location uses different tools and data standards than the manufacturing team in another, performance information is lost in translation. This can lead to inefficiencies, rework, and costly delays, including project launch delays, due to a lack of continuous information flow. Unplanned downtime can result in high costs for everyone involved. Accurately estimating the detailed thermal performance of subsystems, especially critical components such as cooled turbine blades and vanes, requires managing a complex convergence of CAD, aerodynamics, mechanical integrity, and aeromechanics. Each of these disciplines brings its own challenges, best practices, and the need to push boundaries through research to create the best possible engine. Siemens' Plan for Accelerated Innovation and the Future of Turbomachinery At Siemens, overcoming these challenges is considered to lie in a holistic approach that integrates cutting-edge technology with intelligent workflows. The proposed answer is integrated, AI-driven performance engineering, a robust convergence capable of dramatically accelerating innovation cycles while preserving the accumulated experience throughout engineering history. The so-called digital thread is often cited as the cornerstone of the future of turbomachinery engineering. The future of turbomachinery depends on seamless digital integration, from design to manufacturing Integrated information throughout the entire product lifecycle, from design to manufacturing, means connecting the CAE-CAD-CAM chain, drastically reducing production cycles and fostering a truly collaborative environment. But fundamentally, it means creating a single source of truth for all relevant data: design intent, simulation results, manufacturing tolerances, production variations, and ultimately, real-world performance. A comprehensive approach is adopted in which various engineering disciplines converge—aerodynamics, structures, thermodynamics, acoustics, and materials science—enabling holistic improvements. It ensures that every design decision is made with a complete understanding of its impact across all domains. When adjusting the geometry of a blade, it is necessary to immediately understand not only the aerodynamic benefits but also the structural implications, thermal consequences, and manufacturing feasibility. This requires that all relevant data be up-to-date, accurate, and readily available. Simulations of Combustion Turbine Interaction The era of isolated tools and fragmented workflows is over. This harmonized environment connects the tools, enabling automation and the exploration of large-scale analyses. When tools are disconnected, data is translated and re-entered multiple times, introducing errors and reducing the fidelity of the information flowing through the system. Unified tools preserve data integrity. Efficiency of Film Cooling Using Large Vortex Simulations Engineers are empowered with fast and accurate simulations, democratizing advanced simulation capabilities that lead to accelerated engineering insights and continuous development of parts and assemblies. Speed ​​is important, but accuracy is what truly matters. A fast simulation based on low-quality input data can lead to misinterpretations. Therefore, the goal is to ensure that the simulations performed are fast and reliable, based on validated models and high-quality input data. By combining virtual and physical tests, robust evidence of conformity is built. Simulations complement tests, but do not replace them. Data obtained from physical tests validate simulations, while validated simulations allow for the exploration of designs that would otherwise require physical testing. In this way, a virtuous cycle of progressively more accurate models and increasingly reliable decisions is established. AI-trained bird strike simulations and a testing platform for engine certification and verification Through the Siemens Xcelerator, manufacturing is transformed with an AI-based digital thread that creates a complete end-to-end connection between domains, from design to manufacturing. This encompasses CAD design and multiphysics optimization (noise, vibration, force, fluid, pressure, temperature) through CAM programming, data management, planning, CNC machining, and inspection. Gear pumps with optimized topology, 3D printing, and CNC simulations exemplify the future of turbomachinery: 80% faster when trained by AI The transformative power of AI and machine learning, based on solid data A machine learning model capable of predicting the fatigue life of turbine blades does so based on training performed using historical data on blade materials, operating conditions, failure modes, and observed results. The better the quality of this data, the more accurate the predictions tend to be, and the greater the reliability in defining the future direction of turbomachinery. The power of AI is combined with simulation to deliver better performance faster. AI-powered design exploration enables automated and intelligent optimization, helping engineers discover the best designs at each stage. Artificial Intelligence (AI) from Physics Trained on Common Manufacturing Deviations and Operational Defect Simulations Surrogate models are used for complex analyses, such as 3D finite element creep analysis, providing high accuracy in predicting critical locations and values ​​and significantly accelerating these time-consuming processes. These surrogate models are trained with high-fidelity simulation data; essentially, they learn the patterns that detailed physical simulations would capture. But, again, their accuracy depends entirely on the quality of the training data. Industry leaders are seizing every opportunity for data reuse, adopting AI at an accelerated pace through simulation with configuration management. Siemens Energy, for example, uses the HEEDS AI predictive simulator to streamline the integration of CAD and CAE processes across various engineering disciplines. Optimization of multidisciplinary projects accelerated by AI predictions Ready to tackle the most complex challenges in turbomachinery development with greater efficiency, integration, and innovation? Schedule a meeting with CAEXPERTS and discover how our solutions in simulation, integrated engineering, and digital transformation, such as Simcenter 3D and Simcenter STAR-CCM+ , can accelerate your projects, reduce risks, and take your results to a new level. WhatsApp: +55 (48) 98814-4798 E-mail: contato@caexperts.com.br

The latest version of Designcenter NX is not an incremental update; it's a strategic investment in digital transformation. We are providing the tools you need to compete in an AI-driven, cloud-connected, and model-based future. This new version features a broad set of enhancements in assembly, design, drawings, and user experience. This update focuses on expanding core modeling and construction capabilities, improving drawing creation and control, and continuously enhancing the overall usability of the browser-based experience. All new capabilities are underpinned by 4 fundamental pillars. These four pillars are: The 4 Pillars Designcenter X NX – Offering a Complete Collaboration Solution We are living in an era of transformation, in which global companies are migrating to Software as a Service (SaaS) models. There is a real desire in the industry to reduce time to market, manage increasing complexity, and ensure a simplified IT strategy to enable instant connectivity. Siemens research indicates that SaaS models result in a 19% increase in productivity and an almost 100% increase in uptime and reliability. Therefore, investment continues in the Designcenter X NX strategy to create a truly collaborative environment for users. Designcenter allows you to design for the future, whether through a browser or on a computer, offering unparalleled flexibility. It is the most complete and uniquely scalable environment for product development, with best-in-class product engineering software. Introducing Live Share Let's take a closer look. Cloud collaboration for globally distributed teams is fundamental as companies continue to migrate to a hybrid work model. There is a huge demand for companies to be able to work on product development in real time. Live Share enables real-time collaborative creation while preserving industry-proven security and business logic. With it, multiple engineers can work simultaneously on the same assembly or part in real time. Furthermore, it works with data managed both in the cloud and by Teamcenter® software. Live Share enables true concurrent engineering, reducing project cycle time by 30-50% and eliminating costly delays. Automation with Artificial Intelligence The power of Artificial Intelligence continues to transform the competitive landscape for engineers worldwide. AI is the primary area of ​​technology investment for manufacturers. New AI capabilities are reducing the need for repetitive tasks, accelerating the work of design engineers and freeing them to focus on innovation instead of manual operations. Early adopters of AI technologies report time savings exceeding 40% on common tasks, which is why it's at the heart of the continuous rollout strategy. Here are some of the new AI-based workflows in the latest version of Designcenter NX . Designcenter X NX Copilot Designcenter X NX Copilot is the engineering-focused generative AI assistant that brings innovation to life by transforming natural language into action. The new tool leverages industry best practices and Siemens' expertise to guide users through complex tasks with knowledgeable and informative responses. With Copilot, you can ask questions in plain language and everything will be translated into area-specific commands, assisting with everything from best design approaches to troubleshooting errors. The benefits are real; Copilot reduces the time and effort spent on complex tasks, streamlining workflows and making Designcenter X NX more accessible and user-friendly, especially for new users looking to unlock more features. CAD interface with mechanical model and Copilot displaying suggestions Digital Threads Let's take a look at digital threads and where this version focuses. New features for the Design for Manufacturing (DFM) Advisor DFM Advisor is a design-to-manufacturing application that provides critical information about part production during the design phase. It's a new application developed to identify problematic and high-cost manufacturing areas in any design model. For the new version of Designcenter NX , additional checkers have been added to support various manufacturing methods, including milling checkers, assembly checkers, and sheet metal checkers. New Ship Structure Capabilities Ship Structures is a highly productive and collaborative environment for modeling naval structures. With complete coverage of naval design workflows at all design stages, you can reuse design data for subsequent production information and drawing generation. New tools to enhance workflow support from production information to design, along with significant performance improvements and AI tools, have resulted in a 20-30% increase in performance for section views and updates. Ship sructure in the Ship Structures environment Design for Sustainability in Designcenter NX Finally, let's talk about the productivity gains associated with sustainability. Design for Sustainability is an application developed specifically for this purpose, which integrates sustainability into product design in a transparent way. It allows for data-driven decision-making through advanced visualization and reporting, enabling real-time environmental impact assessment. Furthermore, Design for Sustainability can be integrated with coatings and manufacturing to ensure that all sustainability goals are aligned with production efficiency. The Importance of Immersive Engineering Next, we will highlight the new features added in conjunction with immersive engineering. Immersive Engineering continues to transform the way engineers create products. It's a product for the future, allowing everyone to experience digital twins naturally in an immersive environment. A product not limited to a single sector, it's a tool that offers the only fully integrated XR CAD environment, meaning you can stay in your usual engineering application and ensure the security of your data. It's an award-winning solution, designed by engineers, for engineers. Live Updates in Immersive Collaborative Meetings The Immersive Engineering offering is being enhanced through Immersive Collaborator. Immersive Collaborator adds real value and facilitates decision-making by enabling live updates and design changes during meetings. Changes made by the session host are communicated to other users so they can observe and interact. Real-time updates are enabled for Animation Designer, Mechatronics Concept Designer (MCD), and other compatible design operations. This represents a true revolution for simulations and design changes, particularly in identifying collisions and the need to make rapid changes. Cyclist analysis with aerodynamic simulation in a virtual environment Expanded assembly capabilities in NX Centering Constraint. Position components in an assembly by centering them between two faces. Assembly workflows receive several important additions in this version, primarily regarding positioning, movement, and visualization. New constraint types, including center constraint, cylindrical joint, and sliding joint, expand the possibilities for defining and defining component behavior in an assembly. This allows for more realistic movements and positioning, such as allowing rotation and translation along a common axis or restricting movement to a single direction. To facilitate the visualization and communication of assemblies, a manual explode function has been introduced, allowing users to move and rotate components using the Intelligent Triad. This function can also be used to automatically refine exploded views. Additional improvements include the ability to copy components directly from the Assembly Browser using drag-and-drop workflows, expanded access to standard parts in various global standards, and improved performance when working with large assemblies. Faster and more flexible design workflows Delete Body. Removes bodies from the model associatively in the history tree. This feature can be suppressed to resurrect bodies. Design improvements in this version focus on making it easier to create, modify, and manage geometry, reducing difficulties. New features, such as the sketch pattern, allow users to quickly replicate geometry in linear or circular arrays, while the sketch chamfer adds more control when defining details at the sketch level. Model editing has also become more flexible with the addition of "delete body" and "delete face" options, which allow users to remove geometry while maintaining associativity in the history tree. These features can be suppressed to restore geometry if necessary. The main modeling commands have also been expanded, with extrude, revolve, and face replacement now supporting draft and thickness parameters. Updates to the shell command provide greater control over the direction of displacement, and enhancements to the query command facilitate access to detailed face information, such as surface area and centroid. More complete and customizable drawings Center mark, centerline, and primitive circle diameter. Use these annotations in drawings to communicate design intent, locate elements, and manufacture parts with precision. Drawing functionality has been significantly expanded to support more comprehensive documentation workflows. Users can now edit embedded drawings directly within the same NX part file, simplifying transitions between modeling and detailing. New layer controls allow for better management of drawing visibility and selection, helping to reduce clutter. Several new annotation and detailing features have been introduced, including center marks, centerlines, and primitive circle diameter annotations, along with expanded control over dimension and annotation settings. For sheet metal workflows, the addition of a bend table allows for the inclusion of specific manufacturing information, such as bend radius, angle, and direction, directly in the drawing. Additional updates to drawing view settings, preferences, parts lists, and hole tables provide more flexibility and control, helping teams align results with internal standards. Continuous improvements to usability and user experience Version Update Notification. Receive automatic notifications whenever the product is updated, with a link to information about the new features. This version also introduces several updates designed to improve usability and make the application more intuitive. Users can now select user profiles to align mouse and keyboard behavior with NX or other conventional CAD systems, reducing the learning curve. Dependencies between features are now easier to understand thanks to visual highlighting in the history tree, and direct sketch editing allows users to quickly modify geometry without having to navigate through features. Additional improvements include version update notifications, product version visibility, improved file path access, and simplified workflows for opening files, contributing to a smoother daily experience. The new 2026 version of Designcenter X NX brings significant advancements that make your engineering processes more agile, precise, and intuitive—from assembly to final documentation. Want to understand how to apply these improvements to your daily work and extract maximum value from the tool? Schedule a meeting with CAEXPERTS and discover, in practice, how to optimize your workflows and elevate the level of your projects with NX . WhatsApp: +55 (48) 98814-4798 E-mail: contato@caexperts.com.br