Multiscale Analysis![]() (2) Robust equation-free detection and continuation of a Hopf bifurcation point: A robust numerical approach was suggested to detect a Hopf-bifurcation point in an equation-free framework and perform a two-parameter continuation of the Hopf bifurcation point. This is joint work with O. Corradi and P. Hjorth (DTU). For details see SIAM Journal on Applied Dynamical Systems (SIADS), 11(3), 1007-1032, 2012. |
Data Analysis and Analysis of Experiments(1)(2) Continuation of unstable states in laboratory experiments: Methods for tracing solutions including unstable ones in controlled lab experiment were further developed and extended such that stability information can be extracted from the experiments. This allows to obtain valuable experimental information which is important for model development and verification. By this, it is possible to systematically explore how stable and unstable steady state periodic vibrations depend on parameters. This is joint work with F. Schilder, E. Bureau, I. Santos and J.J. Thomsen (DTU). For details see Journal of Sound and Vibration 332 (22), 5883-5897, 2013; Journal of Sound and Vibration 333(21), 5464-5474, 2014; Journal of Sound and Vibration 358, 251-266, 2015. (3) Stability detection and continuation of bifurcation points in experiments: It is even possible to develop methods which allow to determine stability information of a laboratory experiment while tracking an unstable state with feedback control. This has been demonstrated in a laboratory experiment of the Zeeman catastrophe machine. For details, see SIAM Journal on Applied Dynamical Systems (SIADS) To Appear, 2023. Furthermore, a Method for the continuation of bifurcation points has been developed. This has been applied to the continuation of saddle-node bifurcation points which merge in a cusp bifurcation in the Zeeman catastrophe machine. For details, see SIAM Journal on Applied Dynamical Systems (SIADS) To Appear, 2023. (4) Decomposition and low-dimensional description of spatio-temporal data: Methods to decompose high-dimensional data and a few leading modes were developed on basis of statistical methods like PCA and ICA such that temporal changes of mode coefficients could subsequently be modeled and analysed. This is joint work with J. Reidl, J. Rübel, C. Lux (University of Heidelberg), D. Omer, A. Grinvald (Weizmann Institute of Science) and H. Spors (Max Planck Institute for medical research, Heidelberg). For details see e.g. Annals of Operations Research 119, Special Issue on Optimization in Medicine, 75-100, 2003; Journal of Mathematical Biology 51 (2), 157-170, 2005; NeuroImage 34, 94 - 108, 2007. ![]() |
Bifurcation Analysis![]() |
Pattern Formation and Waves(1) Traveling waves: The existence of traveling waves were shown both analytically and numerically in various situations and for different models in various applications. These include collaborations with P. Carter & B. Sandstede (Brown University, USA), Y. Gaididei (Kiev, Ukraine), R. Berkemer (DTU), P. L. Christiansen, M.P. Sørensen (DTU), J.J. Rasmussen (DTU), A. Kawamoto & T. Shiga (Toyota CRDL, Japan), M. Eiswirth, H. Rotermund, G. Ertl (Frith Haber Institut, Berlin). For details see Journal of Evolution Equations and Control Theory (EECT) 8(1), 73-100, 2019; SIAM Journal on Applied Mathematics 74(6), 1895-1918, 2014; NHM (Networks and Heterogeneous Media) 8(1), 261-273, 2013; New Journal of Physics 11, 073012, 2009; Europhysics Letters 73 (6), 820 - 825, 2006.(2) Pattern formation principles to control cooperative robots: Pattern formation principles were used to construct a self-organized control for distributed robots and flexible manufacturing sytems. It can be proven that only feasible solutions of the underlying combinatorial optimziation problem emerge from the pattern formation principle. This is in parts joint work with C. Ellsaesser, University of Heidelberg, T. Fukuda (Nagoya University), H. Haken (University of Stuttgart), P. Molnar (Clark Atlanta University) and M. Schanz (University of Stuttgart). For details see e.g. Physics Letters A 375, 2094 - 2098, 2011; The International Journal of Robotics Research 24, 465 - 486, 2005; IEEE Transactions on Systems, Men and Cybernetics: Part B, 31, No. 3, 433 - 436, 2001. (3) Pattern formation in many-particle systems: It is proven that a interacting many-particle system of different particle types with attracting interactions between particles of the same type and repulsive interactions between particles of different type converges under certain assumption to a sorted state. This is joint work with S. Kokkendorff (DTU), J. Strotmann (University of Hohenheim), N. Hummel (University of Heidelberg). For details see SIAM Journal on Applied Mathematics (SIAP) 70(7), 2534 - 2555, 2010. Deterministic and Stochastic ModellingStochastic many-particle systems have been formulated and investigated. Construction of a mesoscopic stochastic lattice model for fast simulations of large particle numbers for systems with local mixing by diffusion. Fluctuation induced pattern formation was investigated. Limit equations of stochastic many particle systems were rigorously derived. This is joint work with M. Eiswirth, H. Rotermund, G. Ertl (Frith Haber Institut, Berlin), K. Oelschlaeger (University of Heidelberg) and C. Reichert (University of Heidelberg). For details see e.g. Europhysics Letters 73 (6), 820-825, 2006 or Journal of Chemical Physics 115, No 10, 4829-4838, 2001.Discrete and Continuous Optimization(1) Dynamical system approaches to combinatorial optimzation: A dynamical system was constructed to find feasible solutions of combinatorial optimization problems (in particular assignment problems). It was proven that the ω-limit set of the constructed dynamical system is identical to the set of feasible points of assignment problems. Details can be found in the chapter J. Starke: "Dynamical System Approaches to Combinatorial Optimization", Pages 1065-1124 in "Handbook of Combinatorial Optimization" (Eds. Pardalos, P., Du, D.-Z. and Graham, R.), 2nd Edition. Springer Verlag, Heidelberg, New York. 2013.(2) Iterative procedure to estimate parameter in differential equations: Joint work with J. Rübel and C. Lux (University of Heidelberg). For details see Annals of Operations Research 119, Special Issue on Optimization in Medicine, 75-100, 2003 and Journal of Mathematical Biology 51 (2), 157-170, 2005. (3) Shape optimization with eigenvalue contraints: This is joint work with F. Strauß (University of Heidelberg) and M. Inagaki (Toyota CRDL, Japan). For details see Structural and Multidisciplinary Optimization 34, 139-149, 2007. |
Analysis of emerging structures in pedestrian crowds![]() (2) Coarse analysis of a pedestrian model using diffusion maps: This is joint work with P. Liu, I. Kevrekidis (Princeton, USA) and C. Marschler (DTU). For details see Physical Review E 89(1), 013304-013314, 2014. (3) Control-based continuation in pedestrian flow simulations: This is joint work with I. Panagiotopoulos, W. Just (University of Rostock, Germany) and J. Sieber (University of Exeter, UK). For details see SIAM Journal on Applied Dynamical Systems (SIADS) To Appear, 2023. |
Stochastic Modelling and Deterministic Limit of Catalytic Surface Processes![]() |
Processing of Sensory Information in the Olfactory SystemThe olfactory system serves as important model case for other brain regions. It has a good experimental accessibility for several animals and relatively clear defined input and output. The odor signals are processed from receptor neurons over the glomeruli level to a neural network of mitral and granular cells while various types of nonlinear behaviour can be observed.(1) Model of intracellular Ca oscillations due to negative feedback: A mathematical model for Ca oscillations in the cilia of olfactory sensory neurons was suggested. The underlying mechanism is based on direct negative regulation of cyclic nucleotide-gated channels by calcium/calmodulin and does not require any autocatalysis such as calcium-induced calcium release. Predictions of the model are in quantitative agreement with experiment, both with respect to oscillations and to fast adaptation. Relevance of the model to calcium oscillations in other systems is discussed. This is joint work with J. Reidl (University of Heidelberg), P. Borowski (Max Planck Institute for Physics of Complex Systems), A. Sensse (Frith Haber Institut, Berlin), M. Zapotocky (Max Planck Institute for Physics of Complex Systems) and M. Eiswirth (Frith Haber Institut, Berlin). For details see Biophysical Journal 90, 1147-1155, 2006. ![]() ![]() |
Neural network formation due to learningAn equation-free bifurcation analysis allowed to anlayze the network formation due to learning for the audiory system of barn owls. The used model was a spike and response model with Hebbian learning. The results show a phase transition of a map formation in the network depending on the local changes in the synaptic efficacies. This is joint work with C. Marschler (DTU), J.L. van Hemmen (Technical University of Munich) and C. Ellsaesser (University of Heidelberg). For details see Europhysics Letters (EPL) 108, 4805, 6 Pages, 2014.
Traveling Waves in Traffic Models(1) Analytical travelling wave solutions of jam pattern formaton on a ring for a class of optimal velocity traffic models: A follow-the-leader model of traffic flow on a closed loop is considered in the framework of the extended optimal velocity model where a driver takes into account both the following car as well as the preceding car. Periodic wave train solutions which describe the formation of traffic congestion patterns were found analytically and their velocity and wave amplitudes were determined. This contains the standard forward-looking optimal velocity model as a special case. The analytical results are in very good agreement with the results of direct numerical simulation. This is a collaboration with Y. Gaididei (Kiev, Ukraine), R. Berkemer (DTU), P. L. Christiansen (DTU), A. Kawamoto & T. Shiga (Toyota CRDL, Japan) and M.P. Sørensen (DTU). For details see New Journal of Physics 11, 073012, 2009.![]() (3) Multi-Puls traffic jam solutions: We extended traffic models with velocity-dependent driver strategies and showed the existence of multi-puls traffic jam solutions both analytically as well as numerically. This is joint work with P. Carter & B. Sandstede (Brown University, USA), P. L. Christiansen & M.P. Sørensen (DTU). For details see SIAM Journal on Applied Mathematics 74(6), 1895-1918, 2014 (4) Equation-free approaches are used to investigate the macroscopic behaviour of single lane traffic models: Even though the considered models are defined on a microscopic level, the quantities of interest live on a macroscopic level but quite often for this no explicit model equations are available. By short simulation bursts of the microscopic model it is possible to obtain sufficient information for a detailed numerical analysis of the macroscopic dynamics including continuation techniques and bifurcation analysis. The investigations focus on travelling waves of traffic jams such as the ratio of cars being involved in the traffic jam depending on model parameters like driver sensitivity or maximal velocity. This is joint work with C. Marschler (DTU), J. Sieber (Exeter, UK), R. Berkemer (AKAD Stuttgart, Germany), A. Kawamoto (Toyota CRDL, Japan). For details see SIAM Journal on Applied Dynamical Systems (SIADS), 13(3), 1202-1238, 2014. |
Vibration Analysis in Mechanical Systems![]() ![]() (2) Mathematical modelling of rotor bearing systems with application to a turbocharger: A minimalist model for a rotor bearing system with oil film lubrication in a floating bush bearing system was developed and analyzed. This is joint work with M. Inagaki, A. Kawamoto, T. Abekura, A. Suzuki (Toyota CRDL, Japan) and J. Rübel (Heidelberg, Germany). See Journal of System Design and Dynamics 5(3), 461-473, 2011. (3) Shape optimization of rotating machinery: Reduction of vibration level in rotordynamics by design optimization We focus on the reduction of the vibration level of rotors by optimizing the shape of the body. The target is to reduce rotor weight and rotor vibrations leading to higher efficiency and less noise.We consider a finite element discretization of the rotor using a Rayleigh beam model which includes rotary inertia and gyroscopic moments leading to nonselfadjoint systems. We present a general algebraic framework for this case. The mass function is the objective function of the optimization problem and constraints are set on the nonlinear and nonconvex functions of critical speed and unbalance response. For the numerical solution, algorithms belonging to the class of sequential convex programming are applied for the example of a turbocharger. A remarkable reduction of mass of an initially given prototype could be achieved while significantly reducing the unbalance response and raising the critical speeds. This is joint work with F. Strauß (University of Heidelberg) and M. Inagaki (Toyota CRDL, Japan). For details see Structural and Multidisciplinary Optimization 34, 139-149, 2007. ![]() |
Robust Control of Flexible Manufacturing Systems![]() |
Analysis and visualization of orthodontic growth and shape changes![]() (2) Analysis of treatment effects: To obtain a simplified medical interpretation of the growth analysis one can overdraw certain growth modes in a kind of caricature. This is shown in the figure for a orthodontic treatment with the so-called activator. This is joint work with J. Rübel and C. Lux (University of Heidelberg). For details see The Cleft Palate-Craniofacial Journal 39(3), 341-352, 2002, Annals of Operations Research 119, Special Issue on Optimization in Medicine, 75-100, 2003 and Journal of Mathematical Biology 51 (2), 157-170, 2005. |
Jens Starke - last modified December 27, 2022