Funding Agency | Deutsche Forschungsgemeinschaft (DFG) |
Speaker | Prof. Dr. Volker Schulz |
Principal Investigator | Prof. Dr. Nicole Marheineke |
Participants | Marc Harmening, Lukas Kannengiesser, Lukas Mich, Britta Schmitt |
Dates | 2017 – 2025 |
Mathematical optimization is a discipline of high importance for economy, science, industry, policy support, and the public and private sector. Due to practical demand and the rise of computing capabilities, experts proficient in this field are needed in research and development. This research training group (RTG) therefore focuses on education in the field of algorithmic optimization.
ElAN — Efficient local waste heat utilization in low-temperature networks

Subproject: Structure-preserving approximations
Funding Agency | Federal Ministry of Education and Research (BMBF) |
Partner | University Konstanz, University Stuttgart, Fraunhofer ITWM, Rechenzentrum für Versorgungsnetze Wehr GmbH |
Participants | Prof. Dr. Nicole Marheineke |
Dates | 2022 – 2025 |
The goal of the subproject is the development and analysis of structure-preserving approximations for low-temperature subnetworks with fixed flow direction and their application in state estimation for model predictive control. The targeted data (snapshot) based reduction under compatibility constraints includes Galerkin projections for spatial discretization and model order reduction as well as complexity reduction for the nonlinearities.
MathEnergy — Mathematical key techniques for energy networks in a state of change

Subproject: Analysis and application of reduced models
Funding Agency | Federal Ministry for Economic Affairs and Energy (BMWi) |
Partner | Fraunhofer SCAI, Fraunhofer ITWM, Max-Planck-Institut Magdeburg, TU Berlin, TU Dortmund, HU Berlin, PSI AG |
Participants | Prof. Dr. Nicole Marheineke, Björn Liljegren-Sailer, Nadine Stahl |
Dates | 2016 – 2021 |
EiFer — Energy efficiency through smart district heating networks

Subproject: Development and numerical treatment of model hierarchies
Funding Agency | Federal Ministry of Education and Research (BMBF) |
Partner | TU Berlin, FAU Erlangen-Nürnberg, Fraunhofer ITWM, Technische Werke Ludwigshafen |
Participants | Prof. Dr. Nicole Marheineke |
Dates | 2018 – 2021 |
proMT — Prognostic model-based online MR-thermometry during minimally invasive thermoablation for the treatment of liver tumors

Subproject: Model reduction for prognostic online MR-thermometry
Funding Agency | Federal Ministry of Education and Research (BMBF) |
Partner | TU Kaiserslautern, Fraunhofer ITWM, Institute for Diagnostic and Interventional Radiology Frankfurt University Clinic, Siemens Healthcare GmbH |
Participants | Prof. Dr. Nicole Marheineke, Kevin Meligan |
Dates | 2016 – 2020 |
In view of the intended prognostic online simulation capability, this subproject aims at the development and analysis of reduced models by means of model order reduction (MOR) techniques. The combination of MOR and space-mapping promises a further increase in performance, which is assessed qualitatively and quantitatively for the specific application of MR-thermometry.
Funding Agency | German Research Foundation (DFG) |
Partner | Fraunhofer ITWM |
Participants | Prof. Dr. Nicole Marheineke, Manuel Wieland, Stefan Schießl |
Dates | 2014 – 2018 |
The objective of this project is the simulation of highly dynamic spinning processes, geared to the key challenge of understanding the melt-blowing process with its complex dependency on the driving turbulent hot air streams together with the arising large stretching of the liquid fiber jet. For the underlying instationary viscous Cosserat rod model, system of partial and ordinary differential equations with random source term, numerical schemes are developed with focus on appropriate refinement strategies.
Mathematical modeling, simulation and optimization at the example of gas networks

TP C02: Hierarchical PDAE-surrogate models and stable PDAE-discretiziation for simulating large instationary gas networks
Funding Agency | Collaborative Research Centre (SFB) / Transregio 154 |
Partner | FAU Erlangen-Nürnberg, HU Berlin, TU Berlin, TU Darmstadt, ZIB, WIAS, Univ. Duisburg-Essen |
Participants | Prof. Dr. Nicole Marheineke, Björn Liljegren-Sailer, Prof. Dr. Caren Tischendorf (HU Berlin) |
Dates | 2014 – 2018 (Ausscheiden wegen Universitätswechsel) |
The online (possible real-time) control and parametric optimization of gas transport requires the stabil and fast simulation of large instationary networks that are modeled by huge coupled systems of partial differential and algebraic equations. This project aims at the development of an appropriate numerical discretization adapted to the network topology and in regard of a small perturbation index. Establishing a PDAE-surrogate model hierarchy by using model order reduction techniques promises to yield an efficient compromise between complexity and accuracy.
Funding Agency | Federal Ministry of Education and Research (BMBF) |
Partner | FAU Erlangen-Nürnberg, TU Kaiserslautern, Fraunhofer ITWM, Autefa Solutions Germany GmbH, IDEAL Automotive GmbH |
Participants | Prof. Dr. Nicole Marheineke, Alexander Vibe |
Dates | 2013 – 2016 |
The manufacturing of modern lightweight components is often based on aerodynamic laydown processes. In the airlay-process a porous structure is formed by a fiber-loaded air flow on a conveyor belt and then bonded. The material properties of the finalized product, such as structural strength or bulk modulus, depend on the parameters of the production process. OPAL aims the optimization of the production process and the material properties on basis of the consistent mathematical description of the process chain. The focus of this subproject lies on the kinetic modeling of the fiber-loaded flow.
ProFil – Stochastic production processes in manufacturing of filaments and nonwoven materials

TP3: Turbulent fiber and fluid dynamics
Funding Agency | Federal Ministry of Education and Research (BMBF) |
Partner | TU Kaiserslautern, Univ. Kassel, Fraunhofer ITWM, ADVANSA GmbH, Johns Manville GmbH, Oerlikon Neumag |
Participants | Prof. Dr. Nicole Marheineke, Thomas Cibis |
Dates | 2010 – 2013 |
In the production process of nonwoven materials filaments are spun from a polymer melt by aerodynamic stretching, then entangled by turbulent air flows and finally delivered onto a conveyor belt. The quality of the product is fundamentally influenced by the stochastic properties of the production process. ProFil contributes to innovations in this field with regard to material savings and quality improvements through mathematical modeling and numerical simulation of the process chain «melting-spinning-entangling-deposition». This subproject deals with fiber-fluid interactions and turbulence modeling.