Closed Hypersurfaces — Technology Transfer Project Receives Funding from the Hessian Digital Ministry
Within the framework of the funding initiative Distr@l of the Hessian Ministry for Digital Strategy and Development, a project of GSI/FAIR is funded this year with a sum of about 45,000 Euros. The so-called RoSEN methods are a software developed for the description of closed surfaces in multidimensional spaces. In a feasibility study the funding is to be used to test and evaluate application scenarios together with collaboration partners from industry. For example, the method could be used for applications in the medical and business management sectors or in photogrammetry.
With the help of RoSEN (Robust (hyper)Surface Extraction Prodecures in N Dimensions), data sets of any number of dimensions can be analyzed for similar data features. The resulting hypersurfaces of equal characteristic values can be identified, visualized and described, which, with the help of the results, enables a further digital processing, be it in the algebraic, numeric or graphical sense. The method was originally developed to evaluate experimental data and simulate complex physical phenomena in heavy ion physics, as they occur in accelerator experiments at GSI/FAIR.
"Compared to other methods, the RoSEN methods have been shown to have many advantages, such as a much lower error frequency, a more efficient computational performance, or the generality of being able to be used for data sets of arbitrary dimensionality," explains theoretical physicist Dr. Bernd Schlei. He develops software for the "System Design SIS 18 / SIS 100" department and is the inventor of the RoSEN method. "In particular, the efficiency and unlimited application bandwidth are properties that could be used for significant process innovations in existing digital tools and as product innovations in potential future application areas in the form of new digital tools."
In a feasibility study for future commercial use in four to five technical-economically relevant application fields, both potential process and product innovations are to be identified at an early stage to lay the foundation for a subsequent technology transfer project. The application scenarios will be tested in partnerships with cooperation partners, some of whom have already been preselected. "RoSEN is a good example of how findings derived from basic research can also be used for applications that can benefit society as a whole," says Dr. Tobias Engert, head of Technology Transfer at GSI/FAIR, in praise of the method. "We are interested in further cooperation partners, especially from the fields of medical technology, pharmacology and business administration, for the test phase."
GSI contracted TREAVES Research & Consult GmbH as a door opener to potential users and to coordinate the feasibility study. Treaves itself is a spin-off of graduates of the University of Applied Sciences and the Technical University Darmstadt and acts as a service provider for applied natural sciences. Particularly in the field of digitization, the company has already gained extensive experience in the implementation of funded projects and brings a wide range of contacts from industry.
Half of the project costs of around 91,000 euros will be financed by GSI/FAIR and the other half will be funded by the Distr@l funding from the Hessian Ministry for Digital Strategy and Development. The Distr@l funding program offers a needs-based funding program in the areas of digital innovations and research and development.
The fields of application currently planned for the RoSEN feasibility study are, on the one hand, the numerical simulation of technically relevant fluid and structural dynamic problems, such as the simulation of energy storage systems for regenerative energy supply, and, on the other hand, pharmacokinetic population modeling, which plays a major role in drug development and is also being used, for example, in the context of the current Covid 19 pandemic. In the view of Dr. Arthur Rudek, the founder and managing director of Treaves GmbH, further applications could lie in industrial photogrammetry, business management control or, more generally and across industries, in the more efficient execution of optimization studies with large data populations.
Photogrammetry is used, for example, to digitize technical facilities and buildings for computer-aided process or failure analysis. Image data processing also plays an important role in medical technology, for example in the time-dependent processing of three- to four-dimensional CT, MRI or X-ray images, in the diagnosis of diseases or injuries, or in the context of the Covid 19 pandemic, for example to investigate the late effects of impaired lungs. In the context of a use for business management control, multivariant parameter spaces of business key figures are to be used for the evaluation of the economic performance of individual parts of the company, thus enabling more efficient business management processes and increased profitability. (CP)