05.09.2024

DFG: Priority Programme “Daring More Intelligence – Design Assistants in Mechanics and Dynamics”

Deadline: 8 January 2025

To respect ecological and societal responsibilities and challenges as well as to account for stricter and more complex regulations, future systems design has to become increasingly multidisciplinary. Computer-based support as employed today in mechanics and dynamics, mostly limited to system analysis, is not sufficient anymore. Even in advanced design workflows, usually large-scale, simulation-driven parameter studies are conducted and inspected only manually to iteratively alter a candidate design based on experience and expert knowledge. This process is not only very time-consuming but also typically based on subjective rather than on formalised mathematical objectives. 

The research in the established Priority Programme is to aim at the development of design assistance systems combining methods from optimisation, artificial intelligence and dynamics/mechanics to assist with and partially automate the interdisciplinary design of engineering systems. This may not only result in designs that are actually optimal with respect to formalised criteria, but such design assistants may equip design engineers with an artificial intuition supplementing their own specialised expertise. This way, criteria nowadays only considered in later design stages may be taken into account early on, improving resulting systems in a much more fundamental manner than today’s incremental improvements following established design paradigms. 

The key to realising design assistant systems of practical impact in dynamics and mechanics is to go beyond the state of the art in system analysis, optimisation and design by integrating methods from artificial intelligence and machine learning. For instance, machine learning methods can be valuable tools to infer surrogate models and response surfaces that can be used to achieve a manageable calculation effort for large-scale analysis as part of automated design procedures relying on multicriteria optimisation. Methods from artificial intelligence may even directly lead to certain creative design decisions. However, since machine learning and artificial intelligence have recently thrived mostly in fields far from the design of dynamic systems, it is as yet rather unclear which methods will be best suited and, in particular, how they can be combined with system analysis and optimisation to achieve better designs. Therefore, a central goal of the Priority Programme is to develop benchmark processes for various applications that can demonstrate the functioning and advantages of a design process supplemented by artificially intelligent design assistants. These benchmark processes are to make it possible to switch from an analysis-centric to a criteria-centric design process. Ideally, the design assistant components should be highly flexible with easily accessible interfaces so that they can be combined in a modular way to build up increasingly holistic, assisted design procedures, and to serve as a foundation for continued research in the second funding period.  

It is the aim to pool the expertise in dynamics/mechanics, mathematics, information technology and control engineering in Germany, and to create new and strengthen existing networks in order to achieve the set goals. 

In the second funding period, the Priority Programme will drive research towards the following areas: 

• replacement of subjective evaluation criteria by formalised objectives in all application fields of dynamics in mechanics and mechatronics, as well as the introduction of data-driven instead of rule-based criteria and the evaluation of new and advanced kinds of systems that incorporate, for example artificial intelligence, network communication and/or advanced dynamic control methods; 
• development of methods for the flexible coupling of different analysis programmes, used for the acceleration and systematisation of the search for optima by relying on machine learning and artificial intelligence; 
• validation of design assistant systems in various application fields, including the development of benchmark processes to demonstrate the resulting advantages; application fields and design goals may include, for example, the multicriteria optimisation of kinematic properties and the dynamic behaviour of mechanisms, robots and flexible multibody systems, the choice and design of control strategies for mechatronic systems, and the robustness of designs with respect to aleatoric and epistemic uncertainties;
• additionally, in the second funding period, a focus can also be on re-usage of already available data, e.g. from existing measurements, to derive models for design assistants or on model identification from data, especially considering nonlinearities. 

Proposals must be written in English and submitted to the DFG by 8 January 2025. 

The DFG strongly welcomes proposals from researchers of all genders and sexual identities, from different ethnic, cultural, religious, ideological or social backgrounds, from different career stages, types of universities and research institutions, and with disabilities or chronic illness. With regard to the subject-specific focus of this call, the DFG encourages female researchers in particular to submit proposals.

Further Information
https://www.dfg.de/de/aktuelles/neuigkeiten-themen/info-wissenschaft/2024/ifw-24-78