Block your calendar for the next CAESES User Conference from September 9 to September 11, 2024. The event will take place in the Mercure Hotel in the historic city center of Potsdam, Germany.
FRIENDSHIP SYSTEMS AG, a leading provider of innovative simulation-driven design technology, has formed its wholly-owned subsidiary FRIENDSHIP SYSTEMS INC. in the United States. Established in May 2023 in New York City, the US office will support our customers and pursue opportunities in North America.
The new CAESES release 5.2 was developed with a strong focus on turbomachinery design and is dedicated to users with the CAESES add-on Turbo. It offers a wide selection of components, workflows, and methods to simplify and streamline the parametric modeling of turbomachinery geometries, while maintaining the high level of freedom and customization that CAESES is known for.
The CAESES Student Award goes into a 3rd round. Submit your report and participate.
The Winner of the CAESES Student Award 2022 is Johanna Serr, a Master of Science Student at the TUHH in Germany.
Submit your article in the field of “Simulation-driven Design of Maritime Systems”.
On the special occasion of the upcoming 90th birthday of Prof. Dr.-Ing. Dr. h.c. Horst Nowacki, former head of the section Ship Design at the Technical University Berlin, Germany, and former professor at the University of Michigan, USA, a special issue of Ship Technology Research shall be published in the first half of 2023.
We are excited to attend the Transport Research Arena (TRA) Conference in Lisbon, Portugal from November 14 to 17, 2022 with a presentation on “Holistic Ship Design for Green Shipping”.
The present case study looks at a Left Ventricular Assist Device (LVAD) based on an axial flow pump. CAESES was used as the central hub in the automation workflow. In addition to CAD generation, it was also used as the process integration and design optimization (PIDO) platform. CAESES was coupled to the Ansys Workbench in which the 3D meshing and CFD simulations took place, utilizing the CFX solver.
We are excited to announce the preliminary agenda for the CAESES User Conference 2022! We’ll have leading companies with us, such as Rolls-Royce Deutschland, KSB, Siemens Digital Industries and INEOS Britannia. See the event page for all details and registration.
In the process of geometry-based optimization, the problem of having to model a resulting geometry without knowing the exact values of characteristic parameters can arise. In order to open and further edit the optimized geometry inside the CAESES environment, the parameter set belonging to the new shape needs to be determined. The use of neural networks offers a great opportunity to solve this kind of problem since they are a powerful tool for constructing a predictive model based on data.