Date and Place: Thursdays and hybrid (live in 32-349/online via Zoom). For detailed dates see below!
In the Scientific Computing Seminar we host talks of guests and members of the SciComp team as well as students of mathematics, computer science and engineering. Everybody interested in the topics is welcome.
List of Talks
SC Seminar: Alessandro Gastaldi
11:00SC Seminar Room 32-349
Alessandro Gastaldi, Airbus Defence and Space
High-fidelity airframe shape and sizing optimisation for maximum aircraft performance
The objective of the aircraft development process is to formulate a design which provides the highest possible performance at specific operating conditions, while satisfying many, often competing requirements emerging from the various engineering disciplines involved. Multidisciplinary Design Optimization (MDO) can be used to systematically identify and efficiently resolve complex trade-offs at every stage of the aircraft design process. In this context, the performance of an aircraft is measured in terms of e.g. range or endurance, for a given mission or at specific flight regimes. To guarantee the feasibility of each solution, it is essential to define a complete criteria model including the design-driving constraints emerging from the various engineering disciplines involved. Allowing simultaneous variation of the internal structural layout and the external aerodynamic shape enables improved solutions which satisfy such structural, aerodynamic and aero-elastic criteria, beyond what is achievable by a sequential approach. Naturally, the analysis models employed in the optimisation must capture the phenomena and interactions which determine these quantities of interest. The ultimate objective of the present work is to combine the above elements in a robust and flexible software framework for aircraft performance optimisation through simultaneous shape and sizing optimisation, using fully coupled high-fidelity aerodynamic and structural solvers. This task includes the investigation of best practices for the integration of such a demanding multidisciplinary analysis in an optimisation process, in order to ensure manageable computational cost and robust, automated model evaluations.