Search results

Retrospective 2023 - Top 5 Posts 🚀🔍 Welcome to the second part of our 2023 Retrospective! If you missed the first part, don't worry – click here to explore posts 10 to 6 that marked our year. Now, get ready to dive into the top five articles that were featured in CAEXPERTS. Let's quickly recap the previous posts: 10. Discover how Celera overcame challenges in LED luminaires.🔍 9. Explore Generative Design and perfection inspired by nature.🧩 8. Uncover Siemens Simulation and Digital Thread Workflows.⚙️ 7. Eliminate data migration worries using Solid Edge.🔄 6. Get to know behind the scenes of the CNPEM Sirius Project. Now, let's move on to the TOP 5 posts from the last year, where we cover everything from the revolution in the global energy matrix to the challenges and solutions in the design of transformers and electrical machines. 5. The Role of Green Hydrogen in Reshaping the Sustainable World Energy Matrix 🌍 Embark on an intriguing analysis of the impact of Green Hydrogen on the revolution in the global energy matrix. This article offers a critical and practical point of view, going beyond corporate marketing. Discover new ideas and solutions to energy challenges, revisiting concepts, reviewing foundations and exploring paths to a more sustainable future. By heating up the turbines, dive into how we can transform energy in innovative ways. 4. State of the Art in Electrical Machine Design ⚡ Enter the advanced world of electrical machine design in this exploration led by CAEXPERTS in collaboration with SIEMENS Digital Industries Software. Explore the frontiers of multidisciplinary optimization and multiphysics integration, discovering how digital tools are radically transforming the design of these engines. From analytical calculation to 2D analysis, multiphysics and system approach, learn the deep layers of electrical machine design for complete and efficient understanding. 3. The Digitalization of Engineering can transform the Foundry Industry 🏭 Explore the transformative possibilities of digital engineering in the foundry industry with CAEXPERTS. Discover how the strategic partnership between CAEXPERTS and Siemens Digital Industries Software can boost your company's competitiveness. From advanced part engineering with Simcenter 3D to casting process improvement with STAR-CCM+, dive into tools that will optimize your designs, reduce costs, and speed production. 2. Dramatically reduce cycle time using simulations⏳ Discover how a simulation-driven design approach can be the key to accelerating time to market. CAEXPERTS highlights three reasons why the "stop/start" is slowing down design teams. With an emphasis on saving time, explore how simulations can prevent unforeseen problems, enable accurate root cause analysis, and automate the sharing of design information. Download the e-book to explore the multidisciplinary approach to design and learn how incorporating simulations from the earliest stages of the design process can significantly enhance innovation in electronics design. 1. Why are power transformers so noisy? 🔊 Explore the intriguing world of power transformers and discover why they produce so much noise, known as 'transformer hum'. This post analyzes the basic structure of a three-phase transformer and highlights the influence of magnetostriction, a phenomenon associated with cold-rolled grain-oriented electrical steels. Learn how simulation, especially with Simcenter 3D, can be crucial to understanding and mitigating these effects. Also learn about Lorentz forces and the complexity of transformer joint design. If you are involved in transformer design, this reading offers valuable insights. Now, we invite you to take the next step in your innovation journey. Schedule a meeting with us at CAEXPERTS to explore how advanced engineering and simulation solutions can boost your business in 2024. Let's turn ideas into reality. Together, we will reach new horizons. Schedule your meeting now! 🚀📆

🚀 Review the Best Moments of 2023 Embark with CAEXPERTS on this journey through the 2023 retrospective, remembering the posts that sparked the passion for innovation and technology. Divided into two parts, this retrospective reveals the standout moments that shaped the engineering and simulation landscape. Prepare to be inspired and amazed by the incredible advancements that marked 2023. Let's go to Part 1 of our TOP 10 of 2023! 10. CASE of Success - CELERA: Challenges and Solutions in LED Luminaires💡🚥 Celera surprised us with a super interesting case study, delving into the challenges faced in optimizing high-power LED luminaires. Explore the innovative solutions that have emerged from advanced thermal simulation, including material substitution and the surprising strategy with graphite blankets. This reading is an invitation to unveil behind the scenes of innovation in lighting efficiency using Simcenter FLOEFD. 9. Generative Design - AI-Powered Innovation 🔄🌐 In ninth position, dive into the universe of Generative Design, where algorithms based on artificial intelligence intertwine with CAD and CAE platforms. Discover how Siemens redefines product optimization and scaling, taking inspiration from the perfection of nature's organic forms. An odyssey through innovation driven by artificial intelligence. 8. Simulation and Digital Thread Workflows: Systems Engineering in Action ⚙️🔗 In eighth place, we enter the exciting universe of "Model-Based Systems Engineering" with Siemens' Xcelerator portfolio. Uncover the mysteries behind how Siemens Xcelerator simplifies collaboration between engineers, designers and simulation experts. Simulation workflows become the backbone of efficiency from product conception to operation, a true revolution in modern engineering. 7. Solid Edge - Data Migration 🔄💻 Explore the smooth journey between different CAD tools with Solid Edge. Eliminate data migration worries by adopting this software, which offers two standard ways of migration at no additional cost. From directly opening a wide variety of file formats to advanced batch migration tools, Solid Edge is the guardian of project preservation and continuity engineering. 6. CASE of Success - CNPEM - Sirius Project🌌🔬 We uncover the behind-the-scenes of the Sirius project, a technological success story from CNPEM (National Center for Research in Energy and Materials). This advanced particle accelerator, a global reference in scientific research, used magnetic modeling with Siemens' Simcenter MAGNET software to develop a superbend with permanent magnet technology. This innovation is crucial for electron guidance and synchronous light emission, consolidating CNPEM's commitment to cutting-edge technologies. A fascinating journey through the confines of Brazilian scientific research. We have concluded the first part of this incredible retrospective of the year 2023 for CAEXPERTS. Each post shared was an informative journey, reflecting our commitment to excellence, innovation and advancement in engineering and simulation. The CAEXPERTS team wishes everyone a Happy New Year! 🌟 May this new year bring much prosperity, success and achievements to you. We look forward to continuing our journey together in 2024. Best wishes everyone! 🎉🎆 Improve your engineering in 2024! Schedule a meeting now with CAEXPERTS and discover how we can drive innovation in your projects. Turn challenges into opportunities. Click the button below to schedule your meeting and take the next step towards success. Don't miss the chance to turn your vision into reality!

CAEXPERTS reinforces its commitment to leading digital transformation in the industry, consolidating itself as a reference by offering the most complete range of simulators on the market, based on renowned SIEMENS software. This strategic partnership was recently expanded with the commercial launch of the innovative SIMCENTER CLOUD HPC, marking a significant step in CAEXPERTS' journey to optimize processes and drive efficiency in the industry. The use of this advanced platform by CAEXPERTS engineers not only represents a leap in simulation capabilities, but also redefines performance and effectiveness standards in the industry. Now, it is possible to execute cases in a few minutes that would previously require hours or even days on local high-performance workstations. Strategic Benefits with Cloud HPC: Rapid Delivery of Projects and Consultancies: The agility provided by SIMCENTER CLOUD HPC allows CAEXPERTS to deliver engineering projects and consultancies in significantly reduced deadlines, boosting competitiveness and customer satisfaction. High Complexity Simulation in Real Time: The expanded partnership enables the simulation of increasingly complex products at scales close to reality and in real time, enabling a more comprehensive and need. Agility in Product Development: The ability to quickly simulate changes during the product development process is a crucial differentiator, allowing agile and effective adaptations to market demands. Financial Optimization: The adoption of SIMCENTER CLOUD HPC results in a drastic reduction in investment costs (CAPEX), as it eliminates the need for high-performance local infrastructure, while maintaining a low operating cost. Advanced Data and Information Security: The partnership offers a secure environment for data and information management, ensuring the confidentiality and integrity of critical information. CAEXPERTS recognizes that while cloud computing for HPC is an exciting prospect, many companies face challenges in setting up and managing it. However, with SIEMENS HPC Cloud, these challenges are overcome: Fast Delivery of Projects and Consultancies: The agility provided by SIMCENTER CLOUD HPC allows CAEXPERTS to deliver engineering projects and consultancies in significantly reduced deadlines , boosting competitiveness and customer satisfaction. Instant, Hassle-Free Access: Without complex IT configuration and management requirements, SIEMENS HPC Cloud provides instant access to HPC in the cloud, delivering ease of use and speed. Flexibility and Efficient Collaboration: The ability to move simulations to the cloud and efficiently share results with the team increases flexibility and promotes more effective collaboration. Real-Time Monitoring: Simulation monitoring is simplified and can be carried out through dedicated software, web browsers and mobile devices, providing total control over the processes. Optimization with Integrated Hardware and Software: The integration of software and hardware on the same platform enables the simultaneous execution of multiple simulations and cases, optimizing operational efficiency. Importantly, high-performance companies are more likely to take advantage of cloud computing for HPC, and CAEXPERTS is ready to offer all the support you need in your next project. Enjoy the Future of Simulation with Expert Support from CAEXPERTS! Contact us to explore how to implement SIMCENTER CLOUD HPC in your operation and jumpstart your journey towards simulation excellence. Find out more at: Simcenter Cloud HPC 3 reasons why you should try Cloud HPC CASE STUDY Maritime Advisory DNVA DNV Maritime Advisory leverages on-demand cloud services to accelerate simulations. Using Simcenter to solve urgent problems with CFD in the cloud Company: DNV Maritime Advisory Industry: Marine Location: Oslo, Noruega Software: Simcenter 3D, STAR-CCM+

"Model-Based Systems Engineering" in action Siemens' Xcelerator portfolio is leading the charge in bringing together systems engineers, designers and simulation engineers to confidently conceptualize, develop, manufacture and commission products that meet your design requirements. Let's see how our imaginary classmates Ed and Sam work together to specify and verify a braking system as part of a new vehicle design. It's an all too familiar story – some engineers design a subsystem that does the required work, but are then asked to do the same thing at a lower cost. Now they need to spend time to: Find or recreate your original simulation models and data Review the design and look for cheaper ways to achieve the same performance Run more simulations to check performance Once a solution is found, communicate it to the rest of the team Fortunately for them, Siemens Xcelerator makes it easy to: Ed and Sam use workflow from simulation to performance segmentation, thanks to digital chaining in Teamcenter. MBSE and the digital segment not only save time, effort and money Because Ed is immediately able to locate the analysis work that led to the existing project selection, he can also reuse work already done to review this project. Even better, because everything is connected to the digital thread in Teamcenter, it can instantly evaluate that performance and validate it against requirements for all stakeholders to see. Fully integrated simulation workflow and verification management in action. Now, the project team can spend more time on engineering and less time on logistics and repeated efforts – meaning they can deliver higher quality work and make better-informed decisions. Imagine the added productivity gain if this happened for the entire plethora of systems and subsystems that make up the design of a modern car? Systems thinking brings your organization together It is common practice for systems engineers to work in a systems modeling environment. Mechanical designers are likely using a product lifecycle management (PLM) solution, and your simulation team may have a process simulation and data management (SPDM) solution. Does this make a digital thread? Not exactly. The key to unlocking the potential of the digital segment is for all this work to be done on a common platform. The backbone Siemens Teamcenter manages requirements, systems engineering, CAD (PLM), simulation, physical testing (SPDM) and verification management with complete traceability and visibility for all interested parties. Fundamentally, having all of this in place makes it possible to 'close the loop'. in verifying requirements, maintaining traceability and visibility for all interested parties. Final thoughts There are many examples in history where a lack of systems thinking led to product failure. EHR systems are an interesting example because anyone who has ever been treated by a doctor (and that's pretty much all of us) will instantly recognize the value of a well-designed solution, as well as some of the potential pitfalls. We must continue to embrace emerging and future technologies with a systems thinking mindset and work collaboratively to create products that are not only innovative but also sustainable and efficient. With the help of systems engineering and the expertise of companies like Siemens, we can create a world where technology serves as a force for good, promoting a sustainable and prosperous future for all. Schedule a meeting with us, CAEXPERTS, now and discover how our simulation workflow and digital thread solutions can help advance MBSE in your projects.

Dear CAEXPERTS readers, This Christmas, embark with us on a magical journey, full of innovation, overcoming and the charm of Engineering. In a year marked by unique challenges, even the iconic Santa Claus has had to rethink his approach to ensure the Christmas magic continues to shine. ✨ Modern Challenges at the North Pole With the rise of home working even among elves, Santa Claus faced a revolution in his workshop at the North Pole. Many elves were reluctant to leave the comforts of their elven homes, and who could blame them? But the good old man couldn't rely solely on remote work to ensure that all the gifts reached the good boys and girls (after all, taking care of 7 adult flying reindeer is not an easy task, especially when they insist on participating in virtual meetings! 🦌 ) . Innovation in Gift Delivery The solution came through Siemens, CAEXPERTS' technological partner. Inspired by the versatility of Simcenter Amesim, which transformed traditional reindeer into robotic reindeer using computer-aided engineering, simulating an efficient and agile delivery system. 💻 It's okay that they don't fly yet, but who knows next Christmas? 🚀  Santa Claus and his team decided to innovate in delivering gifts. 🎁 Boston Dynamics robots are getting into the Christmas spirit, pulling sleds with robotic precision. It looks like a real Christmas miracle! 🤖 Engineering: The Magic Behind Christmas Just as the elves adjusted their tools and skills to adapt to modern times, CAEXPERTS stands as a pioneer in the technological transformation of engineering, turning challenges into incredible opportunities. 💡 Our multidisciplinary team of CAE experts not only embraces the latest innovations in simulation and computer-aided engineering, but also leverages them, offering advanced, specific solutions to our clients' technological challenges. We are committed to providing a unique experience, where engineering becomes a journey full of discoveries and extraordinary solutions. 🛠️ Wishes for Innovation and a Bright Christmas This magical Christmas, we wish all CAEXPERTS readers health, happiness and the promise of a future full of innovation. May the light of new ideas continue to shine in each future project, just as it lit the path of Santa's sleigh! 🎅 Merry Christmas and a New Year full of achievements ❗ Sincerely, The CAEXPERTS Team

CAEXPERTS, a specialist in advanced engineering and computer simulation, is revolutionizing the naval industry in partnership with SIEMENS, which acquired FORAN technology. Acquisition of FORAN by Siemens: The Xcelerator Maritime Solution Siemens, a global technology leader, has acquired FORAN technology to create a comprehensive solution for the marine industry. This strategic partnership fills crucial gaps for shipyards around the world, offering everything from increased lifecycle management to more innovative design processes. FORAN is now part of Siemens Xcelerator, establishing itself as the market CAD/CAE/CAM standard for the marine industry. Complete Solution: From Conceptual Design to Production By integrating FORAN with Siemens Xcelerator, the resulting solution covers all aspects of the marine industry, from conceptual design to final production. Rafael de Gongora, Senior Director of Naval Construction at Siemens, highlights that this collaboration offers a unique and complete solution for shipyards, driving innovation and efficiency. “Siemens' Xcelerator marine solution is a winning solution for the market. It is a unique solution capable of offering the only combination required by shipyards. This offers a complete solution for our customers.” Rafael de Gongora – Senior Director of Naval Construction at Siemens Digital Industries Software “The acquisition of FORAN enhances our maritime digital twin by adding prominent capabilities to our integrated ship design and digital thread engineering solution... By adding FORAN's extensive tools to the Xcelerator portfolio and leveraging the team's industry expertise, we will be able to offer commercial and marine shipbuilding customers better control of their ship design and manufacturing process as they transition to Shipyard 4.0.” Tony Hemmelgarn – CEO and president of Siemens Digital Industries Software. No Worries for FORAN Customers Previous FORAN customers can rest assured during this transition as Siemens technology enables the migration of legacy data, ensuring continuity of design, manufacturing and data management. Siemens also offers FORAN customers the opportunity to migrate to the Xcelerator marine solution, providing access to the best software for all their shipbuilding needs. Commitment to a Sustainable Future In addition to offering a complete solution, CAEXPERTS and Siemens are aligned with the industry's sustainability ambitions. The Xcelerator marine solution facilitates the transition to greener practices, enabling rapid prototyping, waste elimination and more sustainable ship design, contributing to decarbonization and a greener future. Main Industries of the FORAN System: Merchant, Passenger, Ro-ro: FORAN has been successfully used to design ro-ros, passenger ships, bulk carriers, chemical ships, container ships, cement carriers, oil tankers etc. Military: FORAN meets the most demanding requirements of military shipbuilding, offering control over configuration, analysis of design options, interface with PLM tools, advanced form definition capabilities and criteria customization. Specific Vessels: FORAN has been successfully used to design tugs, work boats, hotel boats, trawlers, fish transport boats, oceanographic vessels, etc. Offshore: Widely used in the offshore industry, FORAN is used for floating, anchored and fixed platforms, as well as personnel transport boats, anchor ships, supply ships, rescue boats, firefighting boats and anti-pollution vessels. Project Phases with FORAN: Initial/Conceptual Project: Volume adjustment, layout definition, hull generation. Basic Project: Quick generation of 3D model, definition of the structure and positioning of equipment. Ship Detail: Detailed definition in all disciplines, with fast and flexible tools. Manufacturing and Assembly: Using the model to extract necessary information adapted to the needs of each shipyard. Operation: Continuous importance during operation for conversions, repairs, etc. FORAN – Advantages Flexible:  Highly adaptable, it offers customized solutions for shipyards of any size, with a modular structure for flexible and gradual implementation. Ideal for Modeling and Report Production:  Features full 2D drawing functionality and exclusive 3D model capabilities, with efficient management of product information in a single database. Easy to Use:  Simple graphical interface and specific focus on shipbuilding, allowing designers to learn, implement and use easily with minimal support. Reliable:  Generates accurate and reliable information for manufacturing and assembly, contributing to the reduction of material and labor costs. Efficient:  Integration of all disciplines and design phases, reducing costs and improving production quality. Automatically generates personalized purchasing models. Collaborative Engineering:  Facilitates collaboration between shipyards, engineering companies and subcontractors, eliminating risks of incompatibility and simplifying design team coordination. Open:  Simple data exchange with other technical and management systems due to the open structure of the FORAN database and system architecture with standard or customized interfaces. Technology FORAN's 3D boat design capabilities are based on specific shipbuilding technology. The system architecture combines an internal modeling and visualization kernel tuned to meet the needs of the shipping industry. The data management system is scalable, reliable and efficient. FORAN supports collaborative engineering in various environments, being able to exchange data in various formats, such as DWG, DXF, IGES, STEP, VDA, VRML and XML. It incorporates advanced features to optimize manufacturing and can be customized for any production equipment in the marine industry. In a scenario where innovation is essential, the partnership between CAEXPERTS and Siemens, with the integration of FORAN into Siemens Xcelerator and the assimilation of this technology in the market, redefines the standards of the naval industry. This collaboration offers a complete solution from conceptual design to production, addressing the specific needs of shipyards around the world. By adopting FORAN, you have access to a state-of-the-art CAD/CAM system that is flexible, adaptable and capable of boosting efficiency in all phases of naval design. From conception to operation, FORAN provides innovation, reliability and sustainability, aligning with the future demands of the industry. If you are looking to transform your approach to shipbuilding, schedule a meeting with CAEXPERTS now. Discover how advanced engineering and simulation solutions, combined with FORAN technology, can propel your company into the future. Let's shape the next chapter of shipbuilding together. Contact us and start this journey of innovation and efficiency. The future of your company starts here!

Digital transformation has evolved from a mere option to an imperative for organizations seeking to secure their competitive advantage and prosper in the market. The integration of digital technologies has become essential for streamlining operations, elevating customer experiences and optimizing overall efficiency. Counting on Siemens' technological partnership, CAEXPERTS is committed to guiding you towards resounding success on your digital transformation journey. This article presents ten essential tips to achieve this success. 1. Set Clear Goals and Define Success Metrics Before embarking on the digital transformation journey, it is crucial to define clear objectives and identify KPIs aligned with business goals and vision. Companies with well-defined objectives are 1.6 times more likely to achieve successful results. “...when companies achieve transformation success, they are more likely to have certain leaders with digital expertise. Less than a third of all respondents say their organizations have hired a chief digital officer (CDO) to support their transformations. But those who do are 1.6 times more likely than others to report a successful digital transformation.” Excerpt taken from the article about the survey “Unlocking success in digital transformations” from October 29, 2018 by McKinsey 2. Promote a Culture of Innovation Digital transformation goes beyond the adoption of technologies; It is essential to promote a culture of innovation. According to PwC, organizations with strong innovation are 3.5 times more likely to achieve significant revenue growth. 3. Invest in the Right Technologies Choosing the right technologies is crucial. Conduct a thorough assessment to identify the technologies that best align with your goals, from cloud computing to artificial intelligence and data automation. 4. Adopt Agile Methodologies Agile methodologies allow quick iterations and adaptability to changes. They promote collaboration, continuous improvement and rapid response to market dynamics. 5. Empower Employees Through Training Ensure your employees are adequately trained to use new technologies. Empower them with the knowledge and skills they need to thrive in the digital age. 6. Protect Your Digital Assets The average cost of a data breach is $4.45 million, according to the IBM Cost of Data Breach Report 2023. As your digital footprint expands, cybersecurity becomes crucial. Implement robust measures to protect your digital assets, data and intellectual property. 7. Emphasize Customer Centricity Digital transformation is not just an internal process; it also affects interaction with customers. Emphasize customer-centricity by leveraging data insights to deliver personalized experiences and tailored solutions. 8. Collaborate with Strategic Partners Strategic partnerships can accelerate the digital transformation journey. According to a study by Accenture, 76% of executives believe that partnerships are essential to driving the success of digital transformation. Collaborate with technology providers, consultants, and industry experts for valuable support. 9. Monitor Progress and Continuously Adapt Digital transformation is continuous. Monitor progress against predefined metrics and be prepared to adapt your strategies based on ongoing data and insights. 10 Communicate Transparently Effective communication is vital. Keep all stakeholders informed about progress, challenges and results. Transparency builds trust and gains support from employees, customers and partners. In conclusion, a successful digital transformation journey requires planning, a culture of innovation, and adequate resources. CAEXPERTS, as a Siemens technological partner specializing in computer simulation and advanced engineering, offers consultancy services and projects for product development, cost reduction and studies aimed at the operation of industrial enterprises . By adopting the tips presented, your organization will be able to thrive in the digital age, unlocking new opportunities for growth and success. CAEXPERTS, committed to the digitalization of engineering, works with computer simulation to virtually test projects, concepts and processes in the most critical scenarios, allowing companies to remain competitive in the market. Schedule a meeting with us right now. We are ready to help your organization reach new heights in the digital era and help your company with digital transformation.

Simcenter System Analyst is a collaborative solution that creates industry-specific applications to drive system simulation models in collaborative environments to increase model use in actual product development. Empower your project teams with a system variant performance assessment tool that requires no computer-aided engineering (CAE) experience. With this solution, design engineers can efficiently focus on evaluating and analyzing the performance of mechatronic systems while decreasing the cost of model development. CAE experts are standardizing and sharing their system simulation models and submodel libraries with project teams. Complexity is hidden in Simcenter System Analyst's simple GUI, eliminating the need to rework submodels when connecting Simcenter Amesim, Modelica, FMUs, or Simulink submodels. Address a variety of performance attributes and ensure system simulation model continuity. Simcenter System Analyst capabilities include: Define, share and track system variants: End users can easily define their system variants from the predefined variants available in the company database, modifying components as needed. Quickly create system variant management and simulation tools: CAE experts define model architectures with Simcenter Amesim, Modelica, or Simcenter System Architect, importing them into Simcenter System Analyst with associated submodel libraries. Multi-Criteria Batch Analysis Tool: End users can perform multiple runs in parallel to explore various system variants, using HEEDS software as a complementary tool to conduct the Exploration Project. Gather and deploy your enterprise knowledge: CAE experts can reuse or create Python pre/post-processing scripts to generate enterprise-specific pre/post models by importing existing validated models and submodel libraries created with Simcenter Amesim, Modelica, FMUs or Simulink. “Address a variety of performance attributes while ensuring system simulation model continuity” Electrification and control augmentation strategies expand system and architectural complexity. Original equipment manufacturers (OEMs) and suppliers need to quickly evaluate numerous variants to meet local market specifics without compromising quality and performance. Systems simulation provides the answer to these challenges. Design engineers need a fast, easy-to-use solution to perform multi-variant analysis to evaluate design options and balance the performance of mechatronic systems. Siemens Digital Industries Software offers Simcenter™ System Analyst software, a collaborative solution that creates industry-specific applications to drive systems simulation models. Running variant analysis in an easy-to-use simulation environment Simcenter System Analyst is a versatile platform designed for design engineers or program engineers. It is a multi-industry platform that can be deployed by automotive and transportation, aerospace or heavy equipment companies, integrating system simulation model architectures and libraries into a database. Easy to use even for design engineers without CAE skills, Simcenter System Analyst allows you to quickly configure simulation models. Instead of directly assembling and configuring simulation models, engineers select system architectures, components, and scenarios from the database. A multi-attribute analysis can be configured with just a few clicks, allowing design teams to evaluate hundreds of system variations in an easy-to-use environment with customized pre- and post-processing. “With Simcenter System Analyst, design engineers can focus on matching technology to end product requirements rather than creating models.” Deploying a simulation factory Simcenter System Analyst completes a broader system simulation factory scenario. To help deal with complexity, systems architects prepare model and library architectures as well as specific pre- and post-processing before deployment to the database and handoff to system analysts such as design engineers or program engineers. System architects standardize models and structure the system simulation framework for design engineers' analysis activities. Model architectures can be prepared with Simcenter Amesim software or Simcenter™ System Architect software. The Simcenter System Analyst tool-independent simulation framework supports model libraries based on Simcenter Amesim, Simulink, or any other tool that supports the Functional Mockup Unit (FMU) standard. In the context of deploying large systems simulation, Simcenter System Analyst is essential for deploying a simulation factory across your enterprise. Through easy-to-use system simulation processes, Simcenter System Analyst helps expand model use across your entire project team. For more information about Simcenter System Analyst, watch the video: As SIEMENS technology partners, we at CAEXPERT , experts in simulation and advanced engineering, are committed to offering solutions that transform your approach to engineering! Don't miss the opportunity to unify your systems and accelerate product development! Schedule a meeting now and take your technological innovation to the next level!

The newest Simcenter Systems Simulation version 2310 update is here, and it's packed with great new features to help you easily meet your daily challenges. Save time at every step of the engineering process by optimizing your workflow and managing complexity to keep pace with innovation. This post highlights some of the new features in this release, which include Simcenter Amesim , Simcenter Flomaster , and Simcenter System Analyst. Battery With the shift to electrification, the need to simulate efficient batteries, fuel cells and pipelines is critical. In Simcenter Amesim 2310, a refined and updated particle mesh method and a dedicated variable for lithium plating detection accurately estimate voltage and assess lithium plating risk in various scenarios, including fast charging at different temperatures. Electrochemical model of battery The new battery thermal management system demo suite available in Simcenter Amesim 2310 is perfect for teams designing thermal management systems. It offers a clear workflow to design your end-to-end thermal technology by leveraging advanced built-in tools and capabilities. Battery thermal management system demonstration Energy transition In version 2310, we are taking it a step further and expanding the Simcenter Amesim hydrogen injection demo by including a detailed injector and pressure regulator model for hydrogen injection systems. This model demonstrates that existing pneumatic component design libraries can be successfully used to create detailed models and gain important insights into specific behaviors of hydrogen injection systems. Hydrogen injection demonstration With the introduction of version 2310, solar engineers can perform accurate analysis on solar photovoltaic units, including energy production and revenue forecasting, thanks to the improvements introduced in the solar panel. These improvements include a simple definition of model parameters that can be found in the datasheet information. Additionally, engineers can transform photovoltaic cell units into solar panels and arrays effortlessly. Solar panel improvements Simcenter Amesim now offers a new reversible solid oxide fuel cell structure that includes reformers and a basic demonstrator. This framework is a comprehensive solution to address the challenges faced by the energy sector in terms of decarbonization. Predictive models embedded in the framework allow engineers to evaluate the performance of reversible solid oxide cells under various pressures, temperatures and species concentrations, including startup and shutdown sequences. With the new components, engineers can build Power-to-X systems with infinite possibilities. They can size components, optimize architecture, and define control strategies that take into account variability in green energy supply, costs, and CO2 emissions. Solid Oxide Fuel Cell Automotive and transport An important challenge for vehicle engineers is understanding how vehicle designs will perform in real-world scenarios, whether on or off-road. The Simcenter Amesim Track Import tool introduces a new 3D road generator; Powered by the HERE map database, it allows the generation of 3D roads from GPS data shared around the world for simulation with different driving profiles. Tracking Import Tool Simcenter Amesim 's new visual terrain model editor provides a tool for designing proving ground models for cars and off-road vehicles. This allows chassis design engineers to easily create various types of proving grounds, including obstacles of different shapes, heights and lengths. Additionally, the tool can run batch simulations to increase the value and ease of testing. Soil model visual editor The new Electric Vehicle database in Simcenter System Analyst is beneficial for CAE methodology groups who want to understand how the software works and what information it provides. The database contains several electric vehicle configurations that can be used for testing and using Simcenter System Analyst in a practical and conventional application. This means the user can simulate an existing electric vehicle with realistic parameter values, query the vehicle configuration with a single click, compare simulation results with publicly available information, and perform what-if scenarios by switching components between vehicles, changing driving scenarios. or adjusting parameter values. Electric Vehicle Database Aerospace and defense Simcenter Amesim 2310 offers turbine and burner pre-design applications that help gas turbine and engine performance engineers extract the information they need before CAD models are available. This allows engineers to evaluate design weight penalties, generate critical data, and understand engine transient behavior. These applications also provide clear views of turbine and burner layouts, making the design process more accessible and efficient. Turbine and Burner Pre-Design Applications Although the first attempts to send probes to MARS date back to the 1970s, the last decade has seen an increase in successful missions that have sent probes, rovers and even helicopters to the soil of Mars. To support what we might call a race to MARS, we have implemented in Simcenter Amesim 2310 a pre-calibrated Martian atmosphere that allows flight dynamics engineers to accurately evaluate the vehicle's flight performance on MARS. More specifically, engineers can precisely calibrate their guidance, navigation and control systems and find optimal trade-offs. User-defined environment definition Simcenter Amesim 2310 features CAD import sketch generation for tube handling filling . Engineers can now generate a ready-to-use thermofluid model directly from the CAD geometry of a fuel system. This reduces manual steps and model building time, allowing engineers to focus on analysis and explore a broader design space. The capability is aimed at the aerospace industry, but can be used in other industries such as automotive, marine and energy. CAD import sketch generation Fluid and thermal applications The new sketch animation extension in Simcenter Amesim 2310 offers direct temperature analysis, making it perfect for thermal teams sizing or integrating heat exchangers. In seconds, you can visually monitor the temperature of all constituents of your heat exchangers at all times. Sketch animation In real-life two-phase systems, it is sometimes possible for the liquid and vapor phases to flow at different speeds. This effect is not captured by a homogeneous model, but may have an impact on system performance. In Simcenter Amesim 2310 we have introduced new slip ratio correlations that offer the possibility of capturing velocity differences between the liquid and vapor phases. Using these new correlations along with state-of-the-art heat exchange modeling, engineers can achieve predictability in estimating load and pressure drops for their two-phase systems. Two-phase flow drift flow For those in the energy and process sectors, a new tube aging feature has been introduced in Simcenter Flomaster 2310 to understand solid material deposition changes in diameter, roughness and heat transfer behavior over time; helping you identify when maintenance and cleaning are needed to reduce operating costs. Pipe aging The latest Simcenter Flomaster update has improved the application of incompressible flow balancing by introducing additional components such as tubes and constant height reservoir for more options when balancing a system. Flow rate can now be maintained and a filter has been added to exclude pipes from view to help focus on critical components. A compressible flow balancing application was also introduced. These applications provide an automated workflow to balance systems more efficiently, allowing easy transition from flow balancing simulation to static or dynamic simulation. Incompressible Flow Balancing Application Platform improvements that increase productivity Making CAD software and system simulation applications more integrated is critical to an efficient digital thread, and the new model update in Simcenter Amesim 2310 provides the ability to apply design changes from the new 3D CAD part revision to a model existing system, improving this process. CAD model update The latest FMI enhancements in Simcenter Amesim 2310 provide strong and reliable startup capabilities and also offer a closer connection with machine learning applications. As a result, both experienced and novice users can now make the most of their Simcenter Amesim models with greater ease. Improvements to the IMF This new release also brings improvements to Teamcenter connectivity in Simcenter Amesim 2310 and Simcenter Flomaster 2310. This feature allows requirements management in Teamcenter to be linked to simulation models for easy verification of system requirements. Teamcenter Connectivity The new Merge with Conflicts feature in Simcenter Client for Git is ideal for users who work with branches and want to merge modifications from another branch. It provides the ability to resolve merge conflicts manually, making it easier to perform merges for most collection types with or without conflicts. Merge feature in Simcenter Client for Git Another improvement in the Simcenter Client for Git is what we call Delete collection from server . This new feature allows server administrators to delete unused collections from the server. This way, collections that are unused or that were uploaded by mistake can be removed by users with appropriate permissions. Collections can only be deleted when they are not associated with any other collection. This means that you cannot delete a collection required by other collections. Delete collection from server Learn more about Simcenter Systems simulation version 2310 Watch the video below to see the main new features of this version: At CAEXPERTS, we understand the importance of innovation and efficiency in computer simulation. In light of recent improvements to Simcenter Systems Simulator 2310, we offer specialized solutions for companies looking to virtually test their projects in critical scenarios. Our experienced team is ready to help your business make the most of new capabilities, from simulating batteries for electrification to evaluating hydrogen injection systems and fuel cell performance. If you are looking to optimize processes, reduce costs and drive innovation, schedule a meeting with us. Together, we can explore the possibilities that simulation offers to take your projects to new heights. Contact us now and discover how CAEXPERTS can be your strategic partner in the pursuit of engineering excellence. We are ready to boost your results.

Hysteresis modeling in Simcenter MAGNET™ software allows engineers and scientists to model a real-world scenario incorporating the effects of iron losses into the simulation of low-frequency electromagnetic devices. Accurately representing a ferromagnetic material by the full BH loop instead of the SV BH curve affects the local quantities, i.e., the magnetic field distributions. As a result, the device operating point and other global quantities such as input power, torque/force, etc. also change and this can be critical for multi-objective device optimization to find the best design. The incorporation of hysteresis is also a crucial step towards accurate modeling of these materials in multiphysics simulations of electromagnetic devices in the Simcenter© environment, where the magnetic properties of these materials are also affected by mechanical stresses and high temperatures. Introduction The finite element (FE) method is widely used in the commercial computer-aided design (CAD) software industry to analyze and design low-frequency electromagnetic devices such as actuators, motors, and transformers. Maxwell's equations are discretized to calculate magnetic fields in complex geometries, which would otherwise not be possible to simulate. Advanced numerical techniques have been developed to improve the accuracy of solutions for better prediction of the performance of these electromagnetic devices. However, field solutions will not be accurate if the magnetic properties of the ferromagnetic materials, from which these devices are manufactured, are not properly modeled in CAD simulations. In commercial software the magnetic properties of ferromagnetic materials are typically modeled by a single-valued nonlinear magnetization (SV) curve (known as the BH curve, an example is shown in Figure 1) for several reasons, including numerical stability, limited computational resources available and the lack of material data. Such an approximation leads to simulations without magnetic losses, which means that the overall results, for example the motor torque, do not include any magnetic (iron) losses. These are subsequently calculated in a post-processing phase, often with empirical loss formulas developed at the beginning of the 20th century. The following equation (1) represents the energy balance in this scenario. The terms Eohmic and EStoredMag in (1) represent the ohmic loss (I²R) and the magnetic energy stored in the material, respectively. It is important to note that there is no iron loss term in (1), indicating that the SV simulations do not incorporate iron loss in the field solutions. Figure 1: Single-value BH curve of 35WW300 non-oriented electrical steel. Incorporating hysteresis In reality, ferromagnetic materials do not exhibit a single-valued BH curve, but a BH loop (like the one shown in figure 2). Energy is dissipated within the material in the form of heat when the intensity of the applied magnetic field H changes. The loss resulting from this is called hysteresis loss. The inclusion of hysteresis in the FE simulation modifies the energy balance equation (1) as shown below. The term E hys in (2) represents both the hysteresis loss and the magnetic energy stored in the ferromagnetic material. For this reason, the stored magnetic energy and coenergy tab in Simcenter MAGNET is disabled for hysteresis simulations. This is demonstrated in detail in the Single Sheet Tester (SST) sample example in the next section. Figure 2: 35WW300 Non-Oriented Electrical Steel BH Loop Despite the advent of powerful computers and advanced numerical techniques, the inclusion of hysteresis in commercial software remains a rare practice. Although academic research has produced many hysteresis models, such as the Jiles-Atherton⁽¹⁾ and Preisach⁽²⁾ models, commercial FE software companies have generally not adopted them to accurately represent the magnetic behavior of ferromagnetic materials in electromagnetic simulation. modern. devices, e.g. actuators, magnetic storage and recording devices, power transformers, variable speed electric motors, etc. Now that simulation times have been reduced (as a result of faster processors), computationally expensive hysteresis models can be employed on a large scale in complex geometries of these devices. Simcenter MAGNET from Siemens Digital Industries Software is a general-purpose 2D/3D electromagnetic field simulation software used for virtual prototyping of simple to complex electromagnetic and electromechanical devices. Using Simcenter MAGNET , engineers and scientists can design motors, sensors, transformers, actuators, solenoids or any component with permanent magnets or coils, saving time and money. This article focuses on applying a new advanced feature of Simcenter MAGNET , which allows users to incorporate hysteresis into field solutions using the Jiles-Atherton (Hys) hysteresis vector model ⁽³⁾. The feature can be enabled when the simulation is solved using the Transient Solver in 2D (with and without movement). Application examples ​ In this section, we will discuss the effects of incorporating hysteresis on local magnetic fields and iron losses and global results such as currents, voltages, force/torque, and transients for a wide range of electromagnetic devices. Comparison with the conventional SV model will also be presented. 1. The Single Sheet Tester (SST) ⁽⁴⁾ The magnetic properties of steels are measured in the laboratory using steel strips (dimension: 30 mm x 250 mm x 0.35 mm) in magnetic testers, for example, a single sheet tester (SST), an Epstein structure, etc. the unique SST sample itself. The Simcenter MAGNET model of the SST sample is shown in figure 3 (a). An excitation coil surrounds the sample and the voltage on the coil can be adjusted to obtain the desired flux density B in the sample. Figure 3: Simulation model of a single strip of 35WW300 unoriented electrical steel (a) Solid view, uniform B-field calculated using single-value (SV) model (b) and hysteresis (Hys) model (c) a 15 milliseconds (peak sinusoidal excitation). The model is solved using the SV and Hys models for the non-oriented electrical steel 35WW300. B-field plots using both models are shown in Figures 3(b) and (c) at t = 15 ms. In the case of the SV model, iron losses are calculated in the post-processing stage using the empirical loss formula in Simcenter MAGNET , presented below. Where Khys , α and Keddy are the material loss coefficients that are identified using the user-supplied power loss curves. When using the Hys model, the hysteresis loss term in (3) i.e. KhysƒBᵃ is replaced by (4) which calculates the area of ​​the BH loop. The calculated coil currents corresponding to Bmax = 1.13 T in the sample using the two models are shown in figure 4 (a). A comparison of the measured and calculated (using the Hys model) BH loops is presented in figure 4 (b) to reflect the accuracy of the Hys model. A sinusoidal voltage of different amplitudes was applied to calculate the iron loss at different induction levels using the SV and Hys models, and the results are shown in Figure 5. Figure 4: (a) Coil current calculated using SV and Hys models at Bmax = 1.13 T (b) BH loops calculated and measured at Bmax = 1.13 T Figure 5: Iron losses measured and calculated using the SV and Hys models. The frequency is 50 Hz. The stored magnetic energies calculated by Simcenter MAGNET for the SST sample using the SV and Hys models are shown in figure 6. As explained previously, the hysteresis loss calculation using the Hys model also includes the stored magnetic energy, which continues to accumulate over time. over time. For this reason, the magnetic energy stored in the Simcenter MAGNET is disabled for the Hys case. However, hysteresis loss is not incorporated into field solutions when using the SV model, and the stored magnetic energy can be calculated directly from the SV curve. Figure 6: Stored magnetic energy. In the case of the Hys model, it represents the energy being dissipated as hysteresis loss that continues to increase over time. Table 1 shows the power balance using both models for a complete excitation cycle. It can be seen that the time-averaged stored magnetic energy is zero for the SV case. However, time-averaged stored magnetic energy (hysteresis loss) is part of the power balance equation. The small difference that arises in both cases is due to numerical integration error and can be ignored. Table 1 – Power balance (one excitation cycle, frequency = 50 Hz) 2. Team Problem 32⁽⁵⁾ The test bench is a three-member ferromagnetic core, as shown in figure 7 (a). The core is made of five laminations of 3.2 wt% Fe-Si, 0.48 mm thick, with conductivity σ = 1.78 MS/m and mass density δ = 7650 kg/m³. Two 90-turn windings are placed on the outer members; the DC resistance of each winding is 0.32 ohms. These windings can be connected in series or powered by two independently controlled voltage sources. Here we will only consider the case in which the two windings are excited by two independent sinusoidal sources with amplitude of 14.5 V, frequency of 10 Hz and phase differences of 90°. In this way, we will have a rotation of fields in the upper part of the central arm of the device (at point P in figure 7 (a)). The Simcenter MAGNET model of the problem is shown in figure 7 (b). The simulation was run for 125 milliseconds (for 1.25 excitation periods with 40 points per period) using the SV and Hys models. Shaded plots for B-fields calculated at t = 75 ms using both models are shown in figure 8 (a) and (b), respectively. It can be seen that for the Hys case (shown in figure 8(b)), almost no streamlines are present in the rightmost limb, and the streamlines are closing at the corners of the same limb. Arrow plots for fields B and H are shown in Figures 9 and 10, respectively, to investigate this phenomenon. It can be seen that the H field varies between 0 A/m (outer corner) to almost 100 A/m (inner corners) in the rightmost member. In the SV case shown in figures 9 (a) and 10 (a), the sign of B changes with H, that is, the SV BH curve passes through the origin (H = 0, B = 0). However, in the Hys case, the ferromagnetic material has coercivity, and the reversal of B happens when H reaches coercivity, so the field nodes have different signs from B in the same corner, that is, although H does not change sign, B changes. Figure 7: (a) Geometry of the 3-member transformer ⁽⁶⁾ (dimension in mm) (b) Simcenter MAGNET model. Figure 8: Shaded field plot B at t = 75 ms calculated using the (a) SV, and the (b) Hys models. Figure 9: B-field arrow plot at t = 75 ms calculated using the (a) SV, and the (b) Hys models. Figure 10: Arrow plot of H field at t = 75 ms calculated using the (a) SV, and (b) Hys models. The voltages and flux connections of both coils using both material models are shown in figure 11 (a) and (b), respectively. The phase difference in the Hys case is obvious due to the phase delay between fields B and H. The results for calculated and measured coil currents and magnetic flux densities at point P are shown in figure 12 (a) and (b) , respectively. The results for the first quarter of the excitations are not shown due to the initial magnetization curve. A good agreement is reached when using the Hys model, which is a good argument for its use in electromagnetic simulations. Figure 11: (a) Voltages in two coils and (b) flux connections in two coils using the SV and Hys models. Figure 12: (a) Calculated and measured coil currents, and (b) Flux densities Bx and By at point P. 3. An actuator: In this example, a load-driven electromagnetic actuator is simulated using Transient 2D with motion solver in Simcenter MAGNET . The actuator simulation model is shown in Figure 13 (a). The coil in the actuator is driven by a capacitor charged to 12 V. A spring holds the plunger against the top stop. At time t = 0, a switch closes to connect the charged capacitor to the coil. Both the body and the plunger are made of M47 – 24 Ga steel. The shaded plot for the B fields calculated at t = 26.9 ms for the SV and Hys models is shown in Figures 13 (b) and 13 (c), respectively. There's not much noticeable difference here. However, it is desired to accurately predict the position of the piston as a function of time. Figure 14 (a) illustrates the difference between the computed positions as a function of time using both models, and a lag can be observed between the SV case and the Hys case. This can be important for critical applications where precise position knowledge is desired. The coil currents calculated using both models are also shown in Figure 14(b). Figure 13: (a) Simcenter MAGNET model of an actuator. Shaded B field and arrow plot at t = 26.9 ms calculated using the (b) SV, and the (c) Hys models. Figure 14: (a) Actuator position and (b) Excitation coil current calculated using the SV and Hys models. 4. An induction machine [6] A Simcenter MAGNET simulation of a voltage-driven induction motor is presented here. Test engine nominal specifications are given in table 2. The complete Simcenter MAGNET model of the untilted motor is shown in figure 15. For simulation purposes, the quarterly model was solved for 25 power cycles (frequency = 50 Hz) using the 2D Transient solver with motion. Shaded plots for B fields calculated at t = 500 ms are shown in figure 16 for both the SV and Hys models. The difference in rotor position at 500 ms for both models can be noted. Table 2 – Induction machine specifications Figure 15: Simcenter MAGNET model 36-slot, 28-bar, 4-pole induction machine Figure 16: Shaded plot of the B field at t = 500 ms calculated using the (a) SV), and the (b) Hys models. The flow connections and currents of phase A are shown in figures 17 (a) and (b), respectively. It can be seen that there is a transient in the solution. The Hys model predicts higher overshoots in the current waveform, but the transients disappear more quickly than the SV model due to energy dissipation in the ferromagnetic material, changing the time constant of the system. This also implies that the steady state is reached earlier and hysteresis simulations can be performed for a smaller number of time steps in this case. An induction machine is a rotating transformer. Therefore, similar results can be expected in transformer simulations. Figure 17: (a) Flux linkage and (b) A-phase phase current calculated using the SV and Hys models. The speed and torque characteristics of the induction machine are shown in Figures 18 (a) and (b), respectively, and similar transient behavior is observed. There is no significant difference in the steady state values. Figure 19 presents the time-averaged power losses (hysteresis loss, eddy current loss and ohmic loss) in various parts of the machine calculated using the SV and Hys models. The hysteresis loss in the rotor is not presented here because the slip frequency, 0.5 Hz in this case, is very small, and obtaining the time-averaged hysteresis loss for a complete rotor frequency cycle in the Hys case will require many solution steps. Figure 18: (a) Speed ​​and (b) Torque calculated using the SV and Hys models. Figure 19: Power loss in different parts of the machine calculated using the SV and Hys models. 5. A Surface Mounted Permanent Magnet Fractional Slotted Internal Rotor Machine⁽⁷⁾ This example illustrates the current-driven simulation of a surface-mounted permanent magnet (SMPM), lumped winding, fractional slot synchronous machine, which is used for traction applications. Engine specifications are shown in table 3. Table 3 – SMPM machine specifications The complete Simcenter MAGNET model of the SMPM synchronous machine is shown in figure 20 and was solved in the low speed (frequency = 50 Hz) high torque region for five power cycles using the 2D Transient with motion solver. Shaded plots for the B fields calculated at t = 0 ms using the SV and Hys models are shown in Figures 21 (a) and (b), respectively. It can be seen that the stator teeth are in deep saturation (around 2 T) in the SV case, which means that the extrapolation of the SV BH curve overestimates the field values. Figure 20: Simcenter MAGNET model of a surface-mounted fractional PM slot machine with 12 slots and 10 poles. Figure 21: Shaded plot of the B field at t = 0 ms calculated using the (a) SV, and (b) Hys models. The A-phase flow connections and stresses calculated using the SV and Hys models are shown in Figures 22 (a) and (b), respectively. The flux bond in the Hys case is smaller than in the SV case, and the effects of the slots on voltage can be seen when using the Hys model. The torque calculated using both material models is shown in Figure 23. Since iron losses are incorporated into the field solution in the case of the Hys model, the resulting torque is smaller than that of the SV model. The iron losses calculated using both models are not very different and are shown in Figure 24. Figure 22: (a) Flux connection and (b) Phase A phase voltage calculated using the SV and Hys models. Figure 23: Torque calculated using the SV and Hys models. Figure 24: Power losses in different parts of machines calculated using the SV and Hys models. Timing performance The temporal performance of the Hys model is important to users. A solution that takes a lot of calculation time is generally not desirable for design engineers. Therefore, the total simulation times for solving the examples mentioned above using both the SV model and the Hys model are shown in Table 4, and their relationship is plotted in Figure 25. It is important to note that this graph provides an estimate of the temporal performance of the Hys model compared to the SV model and can vary greatly depending on the number of time steps per cycle, mesh density, polynomial order, etc. to collect the data provided in Table 4 are time steps per cycle = 100, polynomial order = 2, Newton tolerance = 1 percent. Reducing the Newton tolerance to very small values ​​increases the number of nonlinear iterations, which significantly increases simulation times. Table 4 – Relationship of simulation times for the SV and Hys models Figure 25: Temporal performance of the Hys model compared to the SV model. When exploring the application of hysteresis modeling in Simcenter MAGNET™, it became evident how incorporating this feature is crucial for more accurate and realistic simulations of electromagnetic devices. The ability to capture nuances such as iron losses at low frequencies offers a more complete view of the behavior of these systems, directly impacting device design and optimization. In this context, CAEXPERTS stands out as a strategic partner for companies seeking to improve their capabilities in computer simulation and advanced engineering. With an experienced and multidisciplinary team, CAEXPERTS is prepared to offer innovative solutions and boost the competitiveness of its customers. If your company is looking to maximize product development efficiency, reduce operational costs and gain valuable insights through advanced simulations, CAEXPERTS is the ideal partner. Our experience ranges from projects and consultancy to studies focused on reducing costs and increasing operational reliability. We see the integration of hysteresis modeling as a crucial step in the search for assertive and intelligent results. By combining CAEXPERTS expertise with the powerful solutions of SIEMENS Digital Industries, we offer a complete approach to boosting the performance of your products and processes. Schedule a meeting with us to explore together how we can optimize your operations and reach new levels of engineering excellence. CAEXPERTS is ready to be your strategic partner in the search for innovation and efficiency. Get in touch now and take the next step towards success. References D. C. Jiles and D. L. Atherton. “Theory of ferromagnetic hysteresis”, J. Magn. Magn. Mater., vol. 61, no. 1–2, pp. 48–60, 1986. F. Preisach. “Über die magnetische Nachwirkung”, Zeitschrift für Phys., vol. 94, no. 5–6, pp. 277–302, 1935. A. J. Bergqvist. “A simple vector generalization of the Jiles-Atherton model of hysteresis”, IEEE Trans. Magn., vol. 32, no. 5 PART 1, pp. 4213–4215, 1996. S. Hussain, Development of advanced material models for the simulation of low-frequency electromagnetic devices, Ph.D. Thesis, McGill University, Montreal, Canada, Feb. 2017. O. Bottauscio, M. Chiampi, C. Ragusa, L. Rege, and M. Repetto. “Description of TEAM Problem: 32 A test case for validation of magnetic field analysis with vector hysteresis”, 2010. [Available online] www.compumag.org/jsite/images/stories/TEAM/problem32.pdf S. Hussain, V. Ghorbanian, A. Benabou, S. Clénet, D. A. Lowther. “A study of the effects of temperature on magnetic and copper losses in electrical machines”, Proc. 2016 XXII Int. Conf. Elect. Mach., pp. 1277-1283, 2016. T. Rahman, R. C. P. Silva, K. Humphries, M. H. Mohammadi, D. A. Lowther. “Design and optimization of fractional slot concentrated winding permanent magnet machines for class IV electric vehicles”, Proc. IEEE Transp. Electrific. Conf. Expo. (ITEC), June 2016.

Get 3D insights into lithium-ion battery cell performance. Export CFD study results to create Reduced Order Models (ROM). Automate sophisticated simulation workflows. Evaluate the thermal comfort of the passenger cabin. Plus, many more features. With the release of Simcenter STAR-CCM+ 2310, we provide engineers across industries with computational fluid dynamics (CFD) capabilities to accelerate complexity modeling. Leverage exciting new capabilities to explore engineering possibilities and turn complexity into a competitive advantage. Quickly get detailed 3D insights into battery cell performance To virtually design reliable and high-performance lithium-ion cells, it is necessary to consider three-dimensional anisotropic effects in battery cell layers. Currently available simulation approaches neglect such effects or make crucial compromising simplifications, reducing the problem to representative descriptions of the two-dimensional battery layer. With the Simcenter STAR-CCM+ 2310, we are launching a unique new 3D cell design capability to design lithium-ion battery cells with high geometric and physical fidelity. This new high-fidelity cell design model enables the design of complete 3D lithium-ion cells, with geometrically resolved electrode layers, separators and flaps. Modeled simulation leverages dedicated, easy-to-use custom trees and the new Stages feature for a customized, tailored workflow for cell designers, with industry-standard terminology and units. It provides simplified mesh setup with a few inputs and clicks, and supports dedicated industry-standard post-processing to facilitate analysis of simulation results. Capability is driven by simulation models for industry standard cell formats. With the Simcenter STAR-CCM+ 2310 we launched the stack cell model; Cell models with cylindrical and prismatic windings will be available soon. Along with this automated workflow, the 3D cell design capability provides highly accurate electrochemical models through an improved physics-based model of the initial Newman-Doyle-Fuller formulation. The 3D cell design feature provides detailed information about cell performance at a glance. Investigate in-plane and through-thickness ion concentration to understand local and edge effects, or predict the effect of flaps and surface cooling to design better battery cells faster. The full potential of the tool requires the complementary battery license. Set up gas thermal runaway ventilation simulations in minutes Setting up gas vent thermal runaway simulation for a battery with hundreds of cells is a time-consuming and error-prone process. Therefore, in Simcenter STAR-CCM+ 2310, we start with consecutive launches of a dedicated workflow to speed up thermal runaway propagation simulation setup time. With the release of version 2310, we continue this effort with the integration of the gas vent configuration. As far as pre-processing is concerned, the new capability allows for very quick setup with easy selection of cell ventilation surfaces. Additionally, a dedicated field function manages the energy balance between the energy released by ventilation and that generated by the cell's internal parts, eliminating the need for complex field functions and monitors. Trigger and gas release conditions are now also simplified for some inputs. Ultimately, the workflow requires only one set of input parameters to deploy it across all battery cells. Integrated automation controls gas vent actuation upon reaching the trigger condition and post-processing is automatically managed with dedicated gas vent quantities in the “Battery Module Reports” tool. Overall, with the Simcenter STAR-CCM+ 2310, you will continue to benefit from rapid setup and analysis of thermal runaway simulations, now even including gas venting with minimal effort. The workflow can only be accessed in the Simcenter STAR-CCM+ Batteries add-on and therefore requires the associated add-on license. More efficient aerovibroacoustic simulation workflow Reduced CGNS file size and import time into Simcenter 3D through new mapping method for loosely coupled aerovibroacoustic workflow . Example: Assessment of side mirror-induced noise Vibroacoustic simulations are typically performed in two steps: After a CFD simulation in Simcenter STAR-CCM+, Simcenter 3D is used for vibration and acoustic field analysis. The legacy workflow consisted of exporting a very large CGNS file with the CFD mesh and force information, importing this file into Simcenter 3D, and mapping the results onto a coarse acoustic mesh. With Simcenter STAR-CCM+ 2310, we offer a new option to map a fine CFD mesh to a coarser acoustic mesh directly in Simcenter STAR-CCM+ before data export. This conservative maximum distance mapping ensures consistent results for the legacy process using the same mapping algorithm as Simcenter 3D, but significantly reduces the size of the resulting CGNS file. Depending on the case, the new CGNS file can be between 35% and 90% smaller with this new method, and the added mapping step has virtually no impact on the overall Simcenter STAR-CCM+ simulation time. Whenever you are looking to couple a fluid solution in Simcenter STAR-CCM+ with a structural analysis in Simcenter 3D, you will benefit from significantly more efficient process and data transfer. Improve the accuracy and speed of water management simulations Many multiphase applications require precise yet efficient handling of droplets sliding across surfaces. Typical use cases include tracking raindrops sliding across the surfaces of moving vehicles, including car windshields, mirrors, and sensor surfaces. Although it is in principle possible to use the high-fidelity Volume of Fluid (VOF) method, it is very expensive and for large numbers of sliding drops, VOF simulation is computationally prohibitive. To predict the dynamics of these droplets on surfaces, a Lagrangian approach is very efficient, but it is of fundamental importance to take into account the effects of surface tension with high precision. With Simcenter STAR-CCM+ 2310, we therefore introduce a new type of Lagrangian phase, so-called wall-bound droplets, and a new particle shape model called Spherical Cap Particles. The latter provides a more accurate prediction of particle drag and heat transfer. Droplets attached to the wall can also be absorbed into a fluid film to accurately model filament formation. A new adhesion force model allows capturing the typical adhesion and sliding motion for wall-attached droplets using the concept of contact angle hysteresis. This is of particular importance in applications such as cleaners. The entire new modeling structure, with its first submodels, allows you to run simulations with accurate and fast tracking of drops and sliding flows. This results in greater accuracy and speed of water management simulations. Accelerate multiphase EMP simulations with minimal loss of accuracy Acceleration of large-scale Eulerian multiphase simulations (EMP-LSI) via implicit multisteps. Nuclear industry application where cooling water is introduced, leading to a countercurrent of displaced gas with slug flow. The acceleration is shown with an increasing number of substeps along with the flow field at the end of the simulation. Source: Gas-liquid countercurrent flow in PWR [Deendarlianto et al., NED, 39 (2012)] Multiphase simulations are often computationally expensive or not sufficiently accurate. While smart hybrid multiphase solutions offer the ability to apply the most effective approach in each state of the multiphase, all respective submodels need to perform at their best to achieve maximum throughput. For this reason, in Simcenter STAR-CCM+ 2310, we have added several implicit steps for Eulerian Multiphase (EMP) targeting large-scale interface (LSI) simulations, mirroring equivalent capacity previously added for VOF and MMP. This leads to more efficient EMP-LSI simulations, reducing simulation time for a given level of accuracy; or increasing accuracy for a given runtime (budget). Significant reductions in execution time can be achieved by running N substeps within the flow time step and then increasing the flow time step by a factor N. This maintains the substep time scale associated with transporting the fraction of volume at the same level (CFL number), but because the computational cost of a substep is a small fraction of the cost of a full flow time step, there is a significant cost savings. Alternatively, this feature can be used to improve accuracy with a small additional computational cost by adding substeps for a given flow time step size. Optimize cabin design through standardized passenger thermal comfort assessment in a fully integrated manner Passenger thermal comfort is a significant factor in end customer satisfaction in any vehicle. While vehicles powered by internal combustion engines have made the work of HVAC (Heating, Ventilation and Air Conditioning) engineers and system energy management considerably easier thanks to the large amount of surplus heat, electric vehicles require much more diligent handling of the energy and heat, in exchange for comfort, safety and autonomy. With Simcenter STAR-CCM+ 2310 , you can now optimize vehicle cabin design and HVAC systems through a fully integrated suite of industry-standard passenger thermal comfort assessment models. A new state-of-the-art thermoregulation model is now available to calculate the thermal response of the human body as a function of cabin conditions (radiation, convection). The model also takes into account physiological factors, such as the level of metabolic activity, and uses them to accurately calculate skin temperature across the body. These temperatures are then used to calculate the Dynamic Thermal Sensation (DTS) and Predicted Percent Dissatisfaction (PPD) global comfort indices, as well as the Equivalent Homogeneous Temperature (EHT) local comfort indices. These are widely recognized industry standard metrics that are crucial for evaluating passengers' overall perception of comfort through DTS and PPD, as well as locally for each major body part through EHT. All new models mentioned are fully integrated with the latest Simcenter STAR-CCM+ automation features . This allows you to create leaner, more efficient end-to-end workflows for cabin design studies. Simulate more applications on GPUs The benefits of GPU-enabled CFD simulation acceleration are undoubtedly; Significantly lower simulation cost in the cloud, massive reduction in power consumption and replacement of hundreds of CPU cores with one GPU node. Over several release cycles, the excellent performance of Simcenter STAR-CCM+ on GPUs has been demonstrated. It is of fundamental importance to expand the ability to leverage GPUs for more models and, consequently, more applications. With Simcenter STAR-CCM+ 2310 , we therefore continue porting solvers and resources to make them equally available for native GPU and CPU simulations. With this release, you can leverage a GPU-native coupled solid energy solver , a GPU implementation of the Equilibrium Air equation of state, and the Gamma-ReTheta transition model. This means, for example, more efficient conjugate heat transfer, e.g. turbine blade cooling simulations, faster supersonic and hypersonic aerospace aerodynamics, and laminar-turbulent transition flows. Continuing our philosophy of a unified codebase for CPUs and GPUs, you can be confident that GPUs will provide CPU-equivalent streaming solutions. Access virtually unlimited computing resources in your simulation environment Running CFD simulations in the cloud offers greater flexibility and scalability on on-premises hardware, with on-demand access and unlimited capacity. However, configuring and accessing the cloud using third-party providers often requires significant time and expertise in cloud and HPC technologies and disrupts existing workflows. Directly from Simcenter STAR-CCM+ , Simcenter Cloud HPC provides instant access to the optimized Amazon Web Services (AWS) infrastructure, configured and managed by Siemens, with no additional configuration required. With the launch of the Simcenter STAR-CCM+ 2310 , we are expanding the availability of Simcenter Cloud HPC from the Americas to Asia Pacific, with the service expected to launch in Europe, the Middle East and Africa soon. For more information on how to access and try Simcenter Cloud HPC for free, contact CAEXPERTS at the link at the end of this post. Prepare large, complex geometries faster with Parallel Surface Wrapper Meshing time is a critical factor for fast overall CFD simulation response time, especially for complex assemblies. The Surface Wrapper has proven to be a very powerful tool for automatically preparing watertight surfaces for subsequent surface re-wrapping and volume-wrapping. Until now, the surface wrapper has employed shared memory parallelism. In Simcenter STAR-CCM+ 2310 , we are introducing the first phase of the distributed memory parallelized surface wrapper (MPI). In this first version, the pipeline from surface wrapping to gap closure has been parallelized. Overall, the speedup of the new algorithm is up to 2.4 times. Compared to the legacy surface wrapper , there is a reduction of approximately up to 43% in wrapping time for various industrial cases. Although the new MPI surface wrapper yields consistent results across various core counts, it locally provides enhanced positioning of gap-closing faces for improved mesh quality and generally exhibits better adherence to user input, such as gap-closing size. Create reduced order models (ROM) from CFD design exploration studies in just a few clicks Reduced-order models represent great opportunities to quickly explore the design space and create fast-running models for real-time feedback. However, to obtain valid conclusions, such models need to be provided with sufficient, validated and – without derogation – well-organized data. Compiling these training and validation datasets from CFD results to create the Reduced Order Model (ROM) can be a tedious and error-prone process if the interface for data transfer is not handled properly. With the release of the Simcenter STAR-CCM+ 2310 and the recently released Simcenter Reduced Order Modeling software, we enable the most seamless approach to go from scalar field screenshots of your steady-state CFD results directly to a static ROM. You can now export study data from Designer Manager with one click, ready to be used as a training and validation dataset in Simcenter Reduced Order Modeling. The current capability supports snapshots of scalar scenes with a fixed color scale from any type of design study. After export, Simcenter STAR-CCM+ creates a comprehensive package including all images from your snapshots. Simcenter 's reduced order modeling will then generate the ROM prediction using proper orthogonal decomposition (POD) and report a ROM fidelity index. Although the data export feature can generally be used for any type of parameter, the POD method works best for moderate parameter variations when rotation effects are negligible and geometry movement is small enough. Overall, the new ROM data export allows for rapid ROM construction from CFD simulation studies. You can now create fast-running models from CFD simulations with confidence and benefit from improved collaboration between CFD analysts and system designers thanks to immediate previews of scenario variants via ROMs. Included in Design Manager, exporting CFD data does not require a license. For subsequent ROM generation, a Simcenter Reduced Order Modeling license is required. Explore and share engineering results in your browser Launching in early 2022, Simcenter STAR-CCM+ Web Viewer allows you to easily explore and share your engineering results directly from your browser. This powerful tool offers fast, interactive data analysis capabilities for free and from virtually any device with no installation effort, ultimately improving the communication of CFD results. However, when working with a scene file in Simcenter STAR-CCM+ Web Viewer, you need to be able to work as autonomously as possible without needing to go back to Simcenter STAR-CCM+ . So in version 2310, we're taking a big leap in that direction with the Simulation Framework feature. By providing the ability to freely hide and show objects across multiple view layers, it is easy to understand how a scene is configured and better understand the source simulation configuration. Frequent users of Simcenter STAR-CCM+ will immediately identify the similarities with displayers and their desktop client hide and show concepts. Users new to Simcenter STAR-CCM+ , on the other hand, become familiar with the different visualization layers through easy-to-understand nomenclature. The degree of control over visibility is very granular, ranging from high-level control of the display down to the surfaces of individual parts. This gives you unrestricted control over what should be shown and what should be hidden. Quickly automate sophisticated simulation workflows with Stages and the Automation node To model the complexity of today's products and simulate them under real-world conditions, you need to implement sophisticated multiphysics CFD simulation workflows. Traditionally, this task requires the use of scripts or the complicated and error-prone transfer of data from one simulation model to another. Simcenter STAR-CCM+ is designed around a simplified CAD-to-results pipeline, providing fully integrated native automation capabilities. Building on this foundation, the Simcenter STAR-CCM+ 2310 further extends simulation automation intelligence with Stages. Stages allow you to handle multiple physical configurations in a single simulation, reducing the need for scripts. With a single click, you can prepare different physical models, conditions – such as interface or boundary conditions and other settings. A staged object can have different settings for each stage. Objects that are not staged will maintain the same values ​​at all stages. Applications that immediately benefit from Stages are vehicle thermal absorption, the recently released battery cell design model, and more. Combined with Simulation Operations, this enables fast and consistent management of complicated simulation sequences. You can now manage complete stages of simulation configurations and orchestrate their execution without manual intervention or Java macros, and share these workflows with your colleagues in a single simulation file. To further increase your productivity, we are introducing a new node in the simulation tree: the Automation node. You will now benefit from one location in the simulation tree that contains all automation aspects of the simulation workflow. This allows you to generate automated workflows faster and increases the discoverability of already defined simulation workflows with better node organization and less clutter. Together, Stages and the automation node take the concept of an intelligent simulation file, enabling end-to-end automation, from CAD to results, to the next level. Enabling you to explore more projects and solve complex multi-physics problems faster. These are just a few highlights of the Simcenter STAR-CCM+ 2310 . These capabilities will enable you to design better products faster than ever before, turning today's engineering complexity into a competitive advantage. In short, the Simcenter STAR-CCM+ 2310 represents a significant leap in computational simulation capability, providing notable advances in battery cell modeling, thermal simulations, aerovibroacoustic simulations, and more. With features like Simcenter Cloud HPC, parallelized Surface Wrapper, and workflow automation, we give engineers powerful tools to accelerate product development and explore new frontiers of innovation. If your company seeks to stand out at the forefront of engineering, the specialized team at CAEXPERTS is ready to collaborate, applying these advanced solutions in simulation and engineering. Schedule a meeting with us to boost your competitiveness and transform challenges into opportunities.

Models are the core of all model-based techniques for design, control, optimization, simulation, etc. Detailed models are the core of design activities and can be complex and slow to compute. How to create simplified, multi-purpose versions to scale and deploy your usage? The answer is Reduced Order Models ( ROMs). ROMs are an efficient way to reduce the complexity of models and expand their range of applications. They are key components for various applications, such as integrating 3D models into 1D models, accelerating simulations, enabling digital twins and real-time applications, creating virtual sensors and protecting IP (Intellectual Property). Today's application will show you how to scale down electrical power systems using Simcenter's Reduced Order Modeling . The system represented in Figure 1 represents a transmission system in which the generated power (here represented by the input voltage source) is amplified by the transformer and transmitted to the load (battery) through the transmission line. Here, the complexity comes from the transmission line model. Basically, to capture transient phenomena well, the transmission line model is discretized in space where each section (here 50 sections per 100 km) is represented by a simple circuit, as shown in Figure 1 . When the number of snippets increases, the model will be more accurate, but the number of state variables will increase. This makes the entire model quite large and consumes a lot of memory. In this context, the objective behind creating a ROM is: Reduce the total number of state variables by simplifying the transmission part model (transformer + transmission line) Faithfully reproduce the transient phenomena resulting from different interconnections This will be done using Simcenter Reduced Order Modeling . The tool offers several ways to make ROMs: either from simulation data using, for example, Neural Networks and Response Surface Models (RSM) techniques or models such as state space matrices of a linearized model as in our application here. Figure 1 The entire process can be summarized in a few steps: Isolate the transmission part Use Simcenter Reduced Order Modeling to Create a ROM Connect the ROM to the rest of the system Check the accuracy of the results Let's start. Step 1: Before making a ROM, the transmission part is disconnected from the rest of the system as shown in Figure 2 and linearized using Simcenter Amesim. The input variables are the transformer input voltage as well as the voltages at the end of the transmission line. It was decided to consider the voltages at the connection points as inputs and the currents as outputs. This helps establish a physical connection between the ROM and the rest of the physical model. Figure 2 Now we are ready to start making a ROM. Step 2: The second step consists of loading the linearization data (matrices) into Simcenter Reduced Order Modeling , computing a reduced model, evaluating it and exporting it. Let's see how this works. The first step is to open Simcenter Reduced Order Modeling and create a state space project as illustrated below. Then load the linearized model you created before using the Add Data button. When selecting the Simcenter Amesim model of the transmission part, all computed linearized models are proposed. Let's choose the one calculated in 1 second. Figure 5 shows the properties of the loaded model. Figure 5 Now, let's go to the model tab and make a ROM. When you click on the New template button, different types of templates are proposed. Here we are dealing with a medium-sized model with 104 state variables. In this case, Balanced Truncation is a good candidate. When you click the start button , a ROM is automatically computed and evaluated. A truncation order of 58 is proposed here based on the Hankel singular values ​​of the model. The tool indicates an overall loyalty rate of 86% . Looking at the frequency response graph, it can be seen that the ROM covers a large frequency bandwidth (up to 2.6 kHz) of the original model, which is good enough for our application. The next step is to save the computed model using the Add Model feature as illustrated below. The computed model being saved, we go to the Export tab and export it. Step 3 To handle diverse applications, four targets are proposed when exporting state space ROMs. They allow connection to both Simcenter Amesim and other simulation tools using, for example, FMUs (Functional Mock-up Units) for co-simulation or binary files. Here, the computed ROM is exported as a Simcenter Amesim submodel . Back in Simcenter Amesim, we will now connect the exported ROM (available in the ROM library specified in the export stage) to the rest of the power system, as illustrated in Figure 9 . Two first-order phase shifts with a cutoff frequency of 2.5 kHz are added to keep the signals within the frequency range of interest (up to 2.6 kHz). Our reduced power system now has 62 state variables compared to 106 for the full power system depicted in Figure 1. The total size of the original model is then reduced by 41.5 %. Almost ready! All that remains now is to validate the ROM by comparing the full simulation results ( Figure 1 ) and the reduced power system models ( Figure 9 ). Figure 9 Step 4 Both power systems depicted in Figures 1 and 10 are simulated for 2 s with a variable step solver using Simcenter Amesim. Figure 10 shows the battery input voltage as well as its state of charge. Figure 10 The results show a high goodness of fit with fewer state variables ( 62 compared to 106 ). This is reflected in the loyalty metrics ( 86 % overall loyalty) indicated by Simcenter Reduced Order Modeling . In terms of usability, the ROM obtained can be used as a digital twin of the transmission part. It can also be shared between different partners working on the same application and possibly using different simulation tools. Conclusion It was shown here how to reduce electrical power systems using Simcenter Reduced Order Modeling . It allows you to easily minimize the number of state variables of a power system by creating a ROM of its transmission part. This has many advantages: It widens the scope of the model, making it less memory consuming Allows you to share models with different partners while preserving IP It enables rapid prototyping and design For this, Simcenter Reduced Order Modeling offers great features to easily create a ROM for a large-scale state space model. The workflow is simple and intuitive, with the ability to easily evaluate ROM fidelity based on different fidelity indicators. The tool also offers different export targets to suit all possible uses, so that the computed ROM can be used in different contexts. In summary, Simcenter Reduced Order Modeling offers an effective approach to simplify models in electrical power systems. By following the outlined process, you can achieve computational efficiency and facilitate model sharing, providing the ability for rapid prototyping and design. Leading this innovation, CAEXPERTS stands out as a company specialized in solving industrial challenges through digitalization and advanced engineering. Its experienced and multidisciplinary team uses cutting-edge technology, such as Simcenter Reduced Order Modeling, to offer assertive solutions with a high return on investment. To explore how CAEXPERTS can boost your efficiency and innovation, schedule a meeting with us now!