Data-drive multidisciplinary design optimization of aircraft structures (MOAD) under uncertainty
A collaboration between Cardiff University and Swansea University
Representative schema of robust design optimization of aircraft components.
The project tackles a complex industrial problem of a/c design optimization within a UQ&M framework with the objective of robust and efficient a/c performance under uncertainty (as in system or operational parameters, model discrepancy or measurement noise). The project is of urgent industrial necessity in order to address and embrace the paradigmatic shift towards efficient and fail-safe design solutions for the next generation of greener a/c. This scenario provides a challenging opportunity for the application of UQ&M tools to a multi-stage, complex and industry-grade robust design problem at the end of the conceptual a/c design phase in order to facilitate the evolution of a reference a/c configuration to the final design stage.
The main aim of the NRN industrial fellowship with Airbus is to build a data-driven computational framework (MOAD) for robust design and optimization of aircraft (a/c) structures in a multidisciplinary framework.
MOAD would integrate the uncertainty quantification and management (UQ&M) tools and robust design optimization modules around the industry grade a/c analysis tools such as ATLAS loads software (Airbus Transnational Loads Analysis Software) to establish the fail-safe limits of the a/c design and performance.Back
Dr Abhishek Kundu
T:+44(0)29 2087 5953
A strong industry-academia synergy for efficient, robust design of aircraft under uncertainty – a sustainable and reliable future for civil aviation…
Dr Hamed Haddad Khodaparast
Prof Michael I Friswell