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We are in the midst of an unprecedented growth in the development and widespread availability of advanced technological infrastructure enabling measurement and modelling of complex engineering systems. More than ever, these developments are bringing the need for transferable computational tools and their theoretical foundation to the forefront. The programme will deliver a major stepping stone in addressing this challenge against the background of specific applications from aerospace engineering, chemical engineering, environmental and geotechnical engineering. Within this broader vision data centric engineering (DCE) aims at developing and delivering a novel synthesis of approaches to engineering design and operation which leverage mathematical (mechanistic-based) and statistical (data-driven) modelling frameworks. A further step is taken under the digital twin concept, where one does not only expect a model to represent a given phenomena but in addition to enable dynamical updates and adjustments in accordance with an evolving set of data and environmental conditions, which leads to challenging questions in online data assimilation and online model adaptation and model reduction. Finally, we require tools to inform decisions as well as to optimize and control engineering structures. The programme will contribute to resolving these challenging issues through workshops, deepdive study periods connecting mathematicians and statisticians with practitioners from engineering, and a regular seminar series.
Deep-dive study periods
Building upon the tutorial workshop, several deepdive study sessions (each 1-2 week long) will further foster interactions between card-carrying engineers, applied and computational mathematicians and statisticians. Each of the deepdive study sessions will be devoted to methodological and computational challenges arising from specific engineering applications. The goal is to provide opportunity for programme participants and in particular students and postdocs to intensively engage with the challenges of new application areas. Leading practitioners from the relevant application area will deliver introductory talks and provide benchmark examples. These activities will be complemented by regular informal seminars, discussions and brainstorming sessions. Participants will also be invited to give an informal introduction to core concepts from their fields during lunchtime ‘What is …?’ meetings. The outcome of these deepdive study periods and follow-up work will be presented at the closing workshop of the programme.
Confirmed deep-dive sessions:
Mathematics and statistics for low carbon energy systems, 30/01-10/02 2023, organiser: Chris Dent
From physics-based to data-driven assessment of structures, 13/02-17/02/23, organiser: Tim Rogers
Optimal Control and Inference, 23/02-3/3 2023, organisers: Susana Gomes and Sebastian Reich
Data Driven Optimisation, 11/04-21/04 2023, organiser: Antonio del Rio Chanona
Data Driven (modeling and control for) Fluid Mechanics, 15/5-26/5 2023, organisers: Luca Magri and Karthik Duraisamy
Image credit: M. Kapteyn and K. Willcox
16 January 2023 to 20 January 2023
28 March 2023 to 30 March 2023
24 April 2023 to 28 April 2023
8 May 2023 to 12 May 2023
5 June 2023 to 9 June 2023
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