The people modelers

In the picture

With its digital models of human beings, the SimTech Cluster of Excellence is contributing to medical Progress.
[Photo: University of Stuttgart/ Max Kovalenko]

For centuries, scientists have used models to describe complex phenomena. Simulations enable us to understand important aspects of the systems described in this way, to predict their states and to decide how such systems could be controlled. In our contemporary society, simulations have become an indispensable part of research and development in many different areas and make a key contribution towards technological progress. In terms of models, methods and computing aspects from an engineering perspective, the “Simulation Technology (SimTech) Cluster of Excellence” at the University of Stuttgart has been advancing simulation technology in terms of scope and depth since 2007, and has established it as an internationally visible research center with its interdisciplinary and methodical profile.

Building on the scientific findings and insights from the SimTech Cluster of Excellence, the successful new “Data Integrated Simulation Science Cluster of Excellence” (SimTech), established as part of the strategy of excellence for the promotion of cutting edge research at universities is now tackling a plethora of new pioneering research questions and a new class of modeling and computational methods. Its main focus is, in particular, on the simulation of multiphase flows, porous materials, mechanical structures and biological systems as well as overarching aspects of machine learning, the analysis of uncertainties and adaptive, ubiquitous IT infrastructures. But above all, SimTech is also contributing toward medical progress in the field of digital models of human beings.

The human being is a highly complex biological system characterized by a finely tuned, intelligent interaction between individual subsystems. It is considered to be energy efficient, fault resilient and highly integrated. A new project involving neuromuscular motion control is analyzing the generation and control of active biological movements to provide the foundations for functional assistance systems in the field of rehabilitation robotics. The group headed up by Professor Syn Schmitt and the junior research group under Daniel Häufle of the University of Tübingen's Hertie Institute of Clinical Brain Research are collaborating in the development of simulation models and technical bio-robots.

Thanks to simulations, it is possible to analyze the smallest building blocks of life. Professor Johannes Kästner and his team are investigating how enzymes, such as salicylate-dioxygenase, are able to take up and use oxygen to break down poisons and digestive waste products within the body and to excrete them. Such biochemical processes at the smallest scale could explain the function of larger units within the organism, such as the organelles or cells. In the course of the study, experimental data from the field of system biology will be combined with quantum-mechanical simulations.

A glioblastoma is a currently incurable type of brain tumor. Research is being conducted at the “Simulation of Large Systems” Department run by Professor Miriam Mehl in collaboration with a group headed up by Professor George Biros (ICES, UT Austin) and the University of Pennsylvania on a software tool for the inverse simulation of the growth of the tumor.

One very promising treatment method for deep seated glioblastomas is the “convection method”. Research is being carried out at the Institute of Applied Mechanics (Civil Engineering) (MIB) headed by Professor Wolfgang Ehlers into multiphase continuum mechanic models to provide the means to describe the dispersal of an injected drug in complex brain tissue and its effect on the tumor. In addition, data from tumor growth experiments will be included in the models in collaboration with the group run by Professor Markus Morrison of the Institute of Cell Biology and Immunology (IZI)

Perfusion MRI is a promising method for the supportive treatment of multiple sclerosis. However, the precise characterization of MS lesions remains difficult using contemporary approaches. Detailed, small-scale simulations of the MR contrast agent in the brain provide insights into the mechanisms that result in the characteristic MRI images of MS lesions and help to better interpret them.

The objective of the interdisciplinary and simulation- oriented research approach is to gain a holistic, integrative understanding of the neuromuscular system, whereby the focus is on obtaining a better understanding of the three-dimensional structure and bio-physical structure and functionality of skeletal muscles. Professor Oliver Röhrle and his team are attempting to model the chemo-electro-mechanical properties and development of new homogenization methods for the patient-specific material modelling of skeletal muscles. In addition, the scientists are developing forward-looking dynamic musculoskeletal system models.

One medical application from the field of structural mechanics is the numerical simulation of bone implant systems, which includes artifi cial hip joints and implants for healing bone fractures. These simulations should make it possible to support the development of new implants and to confi gure their functionality and design in as physiologically- compatible a way as possible to ensure an optimum healing process, the objective being to use them in everyday clinical practice. The micro-mechanical analysis of cancellous bone tissue, which is found in around the joints and is particularly affected by implants, also falls within the scope of structural mechanical simulation . It is hoped that a detailed mechanical analysis at the micro-structural level will provide further insights into the internal processes of human bone growth.

To be able to deploy complex biomechanical models in support of everyday clinical practice, projection-based model reduction methods are becoming increasingly important. Lengthy computational times and the cost of elaborate numerical simulations can be significantly reduced by using appropriate reduction methods, whereby the complex theoretical principles of the model formation are retained via previously generated simulations (offline calculations), enabling time-efficient numerical simulations (online calculations) with variable patient-specific parameters.

Mathematical models for cardiovascular systems are becoming increasingly important for the development of drugs and diagnostic technology. Compared with traditional methods from the field of medicine, mathematic modeling of cardiovascular systems provides important insights without having to perform costly test series. In the case of arteriosclerosis, a vascular disease that restricts blood flow through a build-up of deposits on the vascular walls, numerical simulation makes it possible to determine the degree of constriction as of which an sufficient blood supply to a given organ is at risk. Professor Rainer Helmig's research group is engaged in the development of various mathematical models for cardiovascular systems in a number of different projects.



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