Uncertainty Treatment and OPtimisation In Aerospace Engineering
Acronym
UTOPIAE
Type
research
Duration
2017 - 2020
Content
UTOPIAE will be the first training network that addresses the challenge of finding the ideal compromise between enhancing reliability and safety and reducing resource utilisation. UTOPIAE will build upon the existing theoretical and practical developments in the areas of UQ and Optimisation and will incorporate elements of past and current EU and non-EU projects with the inclusion of Stanford University and partners that are in UMRIDA. <br /> From the control of manufacturing processes to air traffic management, from decision making on multi-phase programmes to space situational awareness, UQ plays a key role to deliver reliable solutions. At the same time optimised solutions have become a necessity and optimisation is now an essential tool to handle the complexity of our world. Different sectors and communities, deal with uncertainties and optimisation in different forms often equivalent or complementary. <br /> Even more interesting is the fine line separating sensitivity analysis and stochastic optimisation. UTOPIAE will look into all these similarities and, by promoting cross fertilisation, will exploit the intimate relationship between optimisation and UQ to make Optimisation Under Uncertainty (OUU) tractable. <br /> UTOPIAE consists of 15 PhD projects.
Our role
JSI leads the ESR11 project on the Efficient Computational Methods for Worst-case and Multi-level Optimisation. <br /> Objectives: To investigate efficient methods and algorithms for worst-case and multi-level optimisation; To develop algorithms that are optimal on expensive problems in Optimisation Under Uncertainty; To test these methods in the applications. <br /> Expected Results: A new set of optimisation algorithms, for the efficient solution of multi-level problems. Implementation of a new set of problem instances of multi-level optimisation. Evaluation framework with defined measures and classifying definitions targeting problems of robust optimisation and reliability-based optimisation.
Funding
H2020 - MSCA