FFAST · Future Fast Aeroelastic Simulation Technologies

The upstream FFAST project addresses the topic Design Systems and Tools (AAT.2008.4.1.1) by developing, implementing and assessing a range of numerical simulation technologies to accelerate future aircraft design. Critical load identification methods and reduced order modelling techniques developed will potentially provide a step change in the efficiency and accuracy of the dynamic aeroelastic “loads process” . Identifying the flight conditions that lead to the maximum loads on aircraft structures and introducing higher fidelity methods at these conditions will reduce the cost and turn around time of the loads process of conventional aircraft. This will lead to significant improvements to product development and manufacture, supporting the ACARE 2020 targets. In addition, innovative designs required for green aircraft can be evaluated more rapidly and at lower risk. Reduced order modelling techniques offer the potential for further step changes in the efficiency of the aeroelastic loads process. These offer the accuracy of high fidelity methods at a cost close to that of the current low fidelity methods. The target for the FFAST project is to demonstrate a speed up of 2 to 3 orders of magnitude over high fidelity methods. To meet this target research will be carried out in work packages to: improve identification of critical loads; develop reduced order modelling strategies for unsteady aerodynamic and aeroelastic simulation. A work package dedicated to validation and evaluation on a set of industrially relevant test cases will judge the success of the technologies developed and give industry confidence to make the necessary pull-through investment. Strong industrial support of FFAST allows direct exploitation of the results via focused future investment, the solution data base and early release software. The dissemination of FFAST to a wider audience is vital and will be achieved via a website, targeted lectures and workshops, conferences and journal publications.