Expected Outcomes

The main expected outcomes of the project are:

  • more robust and reliable solutions for aircrafts and helicopters, based on an improved understanding on novel methodology and technologies by:
    • performing R&D work on A/C and H/C which include high-fidelity methods to simulate and understand complex interactions between fluid and structure during the ditching event (robust toolsets allowing performing ditching flight-physical simulation in time-domain using a fully coupled link (two-way) between a high-fidelity hydrodynamic flow solver (either Lattice-Boltzman or SPH) and a high-fidelity, nonlinear fem model)
    • by performing tests to calibrate high-fidelity and low-fidelity methods 
    • by developing/ improving low-fidelity tools which are very time-efficient and allow optimising ditching relevant parameters in order to reduce loads and improve safety
    • and finally by working on configurational solutions (how can we improve the structure with regards to ditching) addressing conventional as well as unconventional configurations 
  • an improved understanding of environmental phenoma as well as solutions to protect the aircraft/helicopter by analysing wave effects, ground effects and handling qualities 

in order to increase the safety of aircrafts and helicopters in ditching/ floatation situations.

SARAH addresses also more robust and cost-efficient solutions for the full life-cycle since the developed solutions within SARAH not only improve safety but allow calculating more accurate ditching loads which support the design process. Currently the sizing is done using conservative approaches, by improving state of-the-art approaches with solutions provided by SARAH less conservative loads resulting in a reduced aircraft or helicopter weight. This has a strong impact on the DOCs of all vehicles thus giving a positive effect on lifecycle by reducing costs. Since improved validated tools are created the design process itself is also more robust.





This project has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 724139.

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