UQOP is centered around four major symposia that reflect the range of research done within the realms of optimisation and uncertainty quantification within the H2020 ETN UTOPIAE since it started in 2016, and in the global communities in mathematics, sciences and engineering.
As modelling and numerical simulation are becoming omnipresent in science and engineering, the importance of uncertainties is increasingly essential. Indeed, accounting for uncertainties and assessing confidence level in model-based predictions is crucial yo attain the full potential of numerical approaches in research and development workflows and decision-making processes.
Despite their importance, the treatment of uncertainties usually remains a challenging task, especially in the context of complex models with a high computational cost. This symposium will focus on advanced uncertainty methods and their application to complex applications.
The scope of the symposium encompasses the whole spectrum of problematics concerning the uncertainties, with the construction of uncertainty models from data and a priori knowledge, the uncertain propagation problems, the uncertainty analyses (sensitivity), and uncertainty reduction methods.
The symposium will gather researchers working on advanced techniques for uncertainty treatment, including but not limited to surrogate-based methods, reduced-order modelling, statistical and machine learning methods, Bayesian inference and calibration, design of experiment, multi-level and multi-fidelity methods. Methodological, algorithmic and theoretical contributions are all welcomed, as well as applications to uncertainty methods to challenging problems in aerospace or other domains.
Imprecise Probability (IP) provides a framework of theories and methods to quantify uncertainty in a more general way than classical (precise) probability. It can reflect different kinds of uncertainty, e.g. based on the quantity and quality of statistical information available.
The symposium will consist of two sessions focusing on methodology and applications. Each session will consist of one invited keynote presentation and a few contributed presentations of accepted abstracts.
Design optimisation has become a key ingredient in many engineering fields. Here, the increasing competition pressure is making the added value of optimised products and processes clear. These products and processes can offer improved performance and cost effectiveness which are difficult to obtain with traditional design approaches.
Traditional approaches that make use of safety margins to account for uncertainty in design and manufacturing tolerances are not adequate to fully capture the growing complexity of engineering systems and provide reliable and optimal solutions. Robust design optimisation on the other hand deals with minimising the impact of the uncertainties on the optimal solution.
This symposium aims at bringing together researchers and practitioners in the field of design under aleatory and epistemic uncertainty (including applications to aerospace engineering problems) to share their knowledge and experiences and discuss problems and challenges, and to facilitate further improvements in this challenging field.
The aerospace industry has traditionally been at the forefront of the development of new technologies and was very often the first to introduce innovations, which then had an enormous and profound impact on the entire technological sector. Indeed, very often, the aerospace sector needs innovative solutions to solve problems otherwise out of the reach of technology.
This approach requires the use of substantial economic resources and the assumption of a very high business risk since technological developments, although significant, are often not able to repay the funds invested.
Therefore, the ability to foresee the risks of a project as soon as possible and to design sophisticated products quickly and robustly is vital for the aerospace industry, and, in this context, uncertainty quantification techniques and robust or reliability-based optimisation play an essential role.
In particular, an optimisation and design process capable of considering the possible sources of uncertainty from the initial stages and of directing the design process towards robust and resilient solutions can be fundamental to reduce the resources necessary for the development of advanced projects and to reduce the time-to-market of the most effective and innovative solutions.