• views: 202
• date: 26 July 2024
• posted by: voska89

Simcenter Reduced Order Modeling is a game-changing tool that can help you achieve optimal results while simplifying your computational processes. The engineers at Plastic Omnium were previously relying on a spreadsheet for their calculations, which was time-consuming and limited their ability to model complex systems. However, since adopting Simcenter Amesim and Simcenter Reduced Order Modeling, Plastic Omnium has experienced a significant acceleration in their simulation models. With a detailed model now running much faster than real-time, Plastic Omnium has cut down their development time by an impressive 25 percent.
What's new Simcenter Reduced Order Modeling 2404
The latest Simcenter Reduced Order Modeling release incorporates a number of new features that lets you go faster with your connected digital thread, enabling you to unlock new insights and deliver smarter products to your customers.
Go Faster
Time domain vector fitting replaces the previous auto regressive model resulting in better accuracy and generalization performance towards unseen test conditions. The enhancement allows for more efficient fitting thus reducing the time to generate a reduced order model (ROM) which contributes to faster integration in downstream 1D modeling tools.

Further improvements to Static and Dynamic projects include the ability to transform raw data variables into new informative features, maximizing the ability to attain a better model fit enabling more accurate ROMs.

This release also sees improvements in Krylov reduction performance for both iterative and direct solvers. Turnaround time for 3D to 1D Krylov based ROMs is now over six times faster and applicable to large systems with many inputs or systems with low reduction error tolerances.


Reduced order modelsare computationally light models derived from more complex physical models. The goal of this reduction is to decrease the time needed to simulate the models. This is typically done by solving a given problem multiple times under a set of parameters, and then deducing from that a simpler model.
Simcenter Reduced Order Modelingprovides simulation, testing, production, and service professionals with a fast and easy way to create, evaluate, and export ROMs-and thanks to its advanced automation, no additional expertise is needed. Also this solution enables you to capture data that represents a model or process and effortlessly generate a precise, lower-fidelity version of this information with just a few clicks. The resulting reduced models come with unique features: they have a small memory footprint, are tool-agnostic, and can be operated in real time. As such, using Simcenter Reduced Order Modeling unleashes the power of existing models and data to provide extra value for design and operations.
Simcenter Reduced Order Modeling
This on-demand webinar shows how to simplify even complex 3D models into reduced-order models (ROMs) that can be used in a system simulation model using Simcenter Reduced Order Modeling.
Siemens Digital Industries Softwarehelps organizations of all sizes digitally transform using software, hardware and services from the Siemens Xcelerator business platform. Siemens' software and the comprehensive digital twin enable companies to optimize their design, engineering and manufacturing processes to turn today's ideas into the sustainable products of the future. From chips to entire systems, from product to process, across all industries.
Siemens Digital Industries (DI)is an innovation leader in automation and digitalization. Siemens Digital Industries has its global headquarters in Nuremberg, Germany, and has around 76,000 employees internationally.
Siemens AG (Berlin and Munich)is a leading technology company focused on industry, infrastructure, transport, and healthcare. From more resource-efficient factories, resilient supply chains, and smarter buildings and grids, to cleaner and more comfortable transportation as well as advanced healthcare, the company creates technology with purpose adding real value for customers.






   
   
   

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