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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. 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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

The high degree of automation of SIEMENS DIGITAL INDUSTRIES tools ensures that, even while the engineering team rests, your company continues to generate value, products and innovative solutions. Structural, thermal, acoustic, electrical design and whatever else is needed. HEEDS; Topological CAD and CAE. Project Optimization In optimization, one can look for values minimizing/maximizing a mathematical function through the systematic choice of values that allows the comparison between different configurations and a detailed study of the models in different physics. Contact an Expert Keep designing, even after shifts Structural, thermal, acoustic, electrical design and whatever else is needed The high degree of automation of SIEMENS DIGITAL INDUSTRIES tools ensures that, even while the engineering team rests, your company continues to generate value, products and innovative solutions. This feature ensures that the engineering team can dedicate their time to the innovation and product development processes, while the software takes care of testing the solutions, delivering the best possible option. Optimization software from Siemens Digital Industries has the ability to deal with different physics together, integrating calculation routines already validated by companies with the most popular CAE applications on the market . This allows the complete integration of the entire production and design cycle, integrating the engineering areas, making it possible to optimize products and projects with a focus on reducing raw material costs, production time, efficiency and product robustness. All this in the same software , in an integrated and automated way. HEEDS Software specialized in optimization, capable of evaluating data from different sources in search of the best design alternatives using CAD/CAE parameters. ⇐ Voltar para Serviços

Simcenter Flomaster provides a suite of simulation tools for designing, commissioning and operating thermofluid piping systems. The system's digital twin from the engineering stage can be utilized during operation for online detection and monitoring. security efficiency; propulsion; steam; Flomaster Reduce operating costs while ensuring the safety of complex thermofluid piping systems of any scale and complexity. Simcenter Flomaster is the leading simulation tool for fluid engineering and offers reliable, accurate solvers and best-in-class built-in correlations. This means you can effectively size gas, liquid, and two-phase systems and components for maximum efficiency. With the same virtual model, you can simulate and analyze dynamic events such as different operating conditions, failure scenarios and emergencies to ensure safety. Simcenter Flomaster offers a comprehensive simulation toolset for designing, commissioning and operating thermofluid piping systems. This means that the digital twin of the system developed in the engineering phase can be reused during operation for virtual detection and online monitoring to improve efficiency and ensure safety. Simcenter Flomaster can connect to other relevant tools and platforms, including PLM, CAD, Simulation and Industrial IoT, enabling you to embrace digital transformation and innovate quickly. Contact an Expert Thermofluid systems engineering Simulation of the propulsion system System integration Thermofluid system simulation Simcenter Flomaster offers simulation solutions for thermofluid systems, helping you reduce cost and accelerate time to market. Analyze complex physical phenomena, which are critical to ensuring the safe and efficient operation of your systems, maximize return on investment by leveraging the digital twin of your thermofluid systems by controlling maintenance, repairs and operation throughout their lifecycle. Our program has a large library of components used in fluid transport, as well as a large database with information on the physical properties of Newtonian and non-Newtonian fluids. Thanks to your solverfast, reliable and rigorously tested, you can simulate the dynamic behavior of thermofluid systems of any size and complexity. Reuse the same templates you used during initial design for sizing systems and components in detailed designs for transient analysis. Address the growing complexity of propulsion systems for the automotive, aerospace, and marine industries. Gain the ability to model a wide range of propulsion technologies. Embrace model-driven design for a streamlined user experience. From components to the entire system, Simcenter Flomaster helps you focus on your engineering model and solve it as quickly as possible with the data available within the tool. Optimize the efficiency of your thermofluid systems, ensuring they always operate safely. Fluid systems play key roles in all industries. ⇐ Back to Tools

CAEXPERTS creates a work context in the engineering area whose objective is to integrate a multiverse of information, starting from 1D analysis and progressing through different subsidies in the design part, requirements gathering and approach methodologies in the areas of simulation and predictive engineering. Specialization Program in CAE Stand out among engineers with our CAE Specialization Program, designed for professionals seeking excellence through computer simulation, this program offers: Customization: from topic selection to project completion. Technology: access to the best CAE software on the market. Real Projects: hands-on experience with industry challenges. Knowledge: development of articles and procedures. Ideal for engineers and companies focused on overcoming technical complexities and innovating in their fields. Learn more and sign up Digitization of Engineering CAEXPERTS creates a work context in the engineering area whose objective is to integrate a multiverse of information, starting from the first 1D analyzes and progressing through different stages in the design part, requirements gathering and approach methodologies in the areas of simulation and predictive engineering. This integral focus ensures that factors that can influence the product life cycle are not overlooked at all stages of development, including validation, manufacturing and integral management processes for other areas of the company. In addition, it guarantees the control of external elements that interact with the project that was developed in engineering. Engineering Cycle In the engineering development cycle, improvements can be made in relation to durability and optimization of manufacturing processes, reaching the end of the elaboration process with an efficient design that matches the needs of the product's use. CAEXPERTS , in partnership with Siemens Digital Industries , has technologies that allow the development of highly sophisticated products that can have a multidisciplinary integration of the mechanical, electrical and manufacturing areas – the technologies of Siemens Digital Industries . Product Life Cycle Management of all processes, data, files, items, costs, BOM, development cycles, related to manufacturing-ready product development. It also extends the benefits of PDM to support the entire business throughout the product lifecycle, with applications for engineering, manufacturing, quoting, purchasing, suppliers, customers, sales and service. Areas of expertise Âncora 1 Âncora 2 ACOUSTICS ELECTROMAGNETIC COMPATIBILITY DESIGN OF ELECTRONICS CIRCUI S COMPUTATIONAL FLUID DYNAMICS THERMOFLUID DYNAMIC SYSTEMS WIRING AND WIRING HARNESS ELETRIC MACHINES STRUCTURAL ANALYSIS PROJECT OPTIMIZATION MATERIALS ENGINEERING ADDITIVE MANUFACTURING AUTOMATION