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Multidisciplinary advanced computations: Fluid dynamics, Aeroacoustics, Structural dynamics 2 (MultFAS2)

Reference number
Coordinator Saab AB
Funding from Vinnova SEK 1 540 000
Project duration July 2023 - August 2024
Status Completed

Important results from the project

The main project goals have been fulfilled. The project purpose has been to establish methods and best practices for analysis of fluid-structure interaction of internal weapon bays (IWB) and its effect on internal aircraft noise. The first part was established during the first phase of MultFAS and the coupling to internal noise, has been established during this project. Moreover, according to the project goals, numerical studies wrt accuracy, efficiency and structural parameters have been performed and evaluation of methodology has started on a realistic aircraft integrated IWB.

Expected long term effects

The project has resulted in strengthening knowledge, it has made the foundation for planned scientific publications, refined methods and updated best practices, which will be applied and finalized within the granted continuation project MultFAS 3 (2024-03788). Furthermore, the established methodology and best practice form a good basis for industrial implementation and will contribute to increased capability wrt design and analysis of IWBs, primarily, which is highly relevant in future combat aircraft, but also for other fluid-structure and noise-related problems.

Approach and implementation

Through systematic work, the project has successfully established a methodology for connecting the building blocks in a coherent chain of analyzes that enables the analysis of the FSI between the external flow in IWBs and the cavity structure as well as its influence on the internal noise in the aircraft. The systematic work in evaluating and developing methodology as well as performing well-planned simulations have been key components for a successful outcome of the project, which has been highly computationally intensive and has required analysis of large amounts of data.

The project description has been provided by the project members themselves and the text has not been looked at by our editors.

Last updated 4 December 2024

Reference number 2023-01202