Project Details
Projekt
GRK 1932: Stochastic Models for Innovations in the Engineering Sciences
Subject Area
Mathematics
Term
from 2014 to 2018
Project identifier
Deutsche Forschungsgemeinschaft (DFG) - Project number 227401642
Many engineering disciplines have reached a point at which the emerging challenges can no longer be tackled with the traditional deterministic mathematical models and methods. Recent advances in areas such as miniaturisation, new materials and the increased complexity of manufacturing processes are characterised by an increasing number of non-negligible random effects. Thus, the Research Training Group focusses on the main resulting challenges with regard to their mathematical treatment: the development, implementation and improvement of stochastic models to be used in particular applications in the engineering sciences.
We follow an interdisciplinary approach bringing together mathematicians and engineers to demonstrate the high innovation potential of stochastic models in the engineering sciences and, vice versa, the potential of engineering challenges to inspire new developments in applied mathematics. Thereby, we focus on the four main themes of research:
(1) stochastic production processes with fibre and droplet dynamics,
(2) stochastic models for system-on-chip design and Monte Carlo hardware acceleration,
(3) stochastic and analytical methods from image processing for the characterisation of local properties of multiphase materials,
(4) stochastic modelling of the micro structure of fibre-reinforced concrete based on 3D image analysis.
To ensure the success of our interdisciplinary approach, we equip all our PhD students jointly with a full toolbox of advanced applied mathematical methods right from their start. We have implemented a detailed qualification and supervision programme to ensure that all PhD projects can be successfully completed within three years. The main ingredients of this interdisciplinary qualification and supervision programme are:
(1) specially designed compact courses and reading courses,
(2) individual PhD plans and
(3) supervision on three levels that besides the principal investigators includes the two postdoctoral researchers of the Research Training Group and the Fraunhofer Institute for Industrial Mathematics ITWM.
The qualification concept benefits from the experience gained in the research center (CM)², especially with regard to the appropriate choice and amount of soft skill activities. We, furthermore, offer a specific training programme on basic research skills for new PhD students.
We follow an interdisciplinary approach bringing together mathematicians and engineers to demonstrate the high innovation potential of stochastic models in the engineering sciences and, vice versa, the potential of engineering challenges to inspire new developments in applied mathematics. Thereby, we focus on the four main themes of research:
(1) stochastic production processes with fibre and droplet dynamics,
(2) stochastic models for system-on-chip design and Monte Carlo hardware acceleration,
(3) stochastic and analytical methods from image processing for the characterisation of local properties of multiphase materials,
(4) stochastic modelling of the micro structure of fibre-reinforced concrete based on 3D image analysis.
To ensure the success of our interdisciplinary approach, we equip all our PhD students jointly with a full toolbox of advanced applied mathematical methods right from their start. We have implemented a detailed qualification and supervision programme to ensure that all PhD projects can be successfully completed within three years. The main ingredients of this interdisciplinary qualification and supervision programme are:
(1) specially designed compact courses and reading courses,
(2) individual PhD plans and
(3) supervision on three levels that besides the principal investigators includes the two postdoctoral researchers of the Research Training Group and the Fraunhofer Institute for Industrial Mathematics ITWM.
The qualification concept benefits from the experience gained in the research center (CM)², especially with regard to the appropriate choice and amount of soft skill activities. We, furthermore, offer a specific training programme on basic research skills for new PhD students.
DFG Programme
Research Training Groups
Applicant Institution
Rheinland-Pfälzische Technische Universität Kaiserslautern-Landau
Spokesperson
Professor Dr. Ralf Korn
