Interview with Volkswagen AG after the end of ARIA project

Interview Carsten Othmer (Volkswagen AG)Within ARIA, Volkswagen AG has focused on a process known as “Interactive Aerodynamic Design.” This approach aims to speed up the iterative cycle between vehicle styling and aerodynamic assessment. The ROM methods addressed within ARIA are considered the key enablers for this process acceleration, as they…

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ARIA Use cases

In ARIA, Virtualmech provided data related to the optimization of the energy storage mechanism (melted salt) in concentrated solar plants and define the corresponding test case. VW in ARIA provided the following test cases to the consortium:• 2D Ahmed body [Ahmed et al., 1984] with variable slant angle: RANS and…

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ARIA members’ interviews

The interviews were made with ARIA’s use cases, beneficaries, secondees and associated partners of the project. Our members have shared their insight on the benefits of inter-sectoral exchange in order to narrow the gap between basic research carried out in academia and industrial needs. These benefits were achieved via the…

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The first edition of the ECCOMAS Young Investigators Committee Grant 2024 to Maria Strazzullo for the project:
“CRAFT: Control and Reg-reduction in Applications for Flow Turbulence”

Maria Strazzullo, a secondee of ARIA Project, has been awarded the prestigious €15,000 ECCOMAS Young Investigators Committee (EYIC) Grant for her project CRAFT (Control and Reg-reduction in Applications for Flow Turbulence). This award will guide her innovative ideas in the field of fluid dynamics related to the mathematical fundations and…

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ARIA Final Workshop

Introduction The ARIA Final Workshop will be an open international conference on Reduced Order Models (ROMs), aimed for the dissemination of the network results. The workshop will follow a high standard in the selection of presentations and papers by a programme committee of international experts of the domain. Organizers The…

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2024 summer school on numerical analysis

Introduction This school aims to introduce hybrid numerical modeling methodologies that combine partial differential equation models with high-fidelity data. These methodologies focus on achieving explainability, accuracy, and robustness while maintaining speed and efficiency for performance prediction, parametric optimization, control, and data assimilation in complex industrial systems.

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