This work aims at including nonlinear elastic shell models in a multibody framework. We focus our attention to Kirchhoff-Love shells and explore the benefits of an isogeometric approach, the latest development in finite element methods, within a multibody system. Isogeometric analysis extends isoparametric finite elements to more general functions such as B-Splines and Non-Uniform Rational B-Splines (NURBS) and works on exact geometry representations even at the coarsest level of discretizations. Using NURBS as basis functions, high regularity requirements of the shell model, which are difficult to achieve with standard finite elements, are easily fulfilled. A particular advantage is the promise of simplifying the mesh generation step, and mesh refinement is easily performed by eliminating the need for communication with the geometry representation in a Computer-Aided Design (CAD) tool.
Quite often the domain consists of several patches where each patch is parametrized by means of NURBS, and these patches are then glued together by means of continuity conditions. Although the techniques known from domain decomposition can be carried over to this situation, the analysis of shell structures is substantially more involved as additional angle preservation constraints between the patches might arise. In this work, we address this issue in the stationary and transient case and make use of the analogy to constrained mechanical systems with joints and springs as interconnection elements. Starting point of our work is the bending strip method which is a penalty approach that adds extra stiffness to the interface between adjacent patches and which is found to lead to a so-called stiff mechanical system that might suffer from ill-conditioning and severe stepsize restrictions during time integration. As a remedy, an alternative formulation is developed that improves the condition number of the system and removes the penalty parameter dependence. Moreover, we study another alternative formulation with continuity constraints applied to triples of control points at the interface. The approach presented here to tackle stiff systems is quite general and can be applied to all penalty problems fulfilling some regularity requirements.
The numerical examples demonstrate an impressive convergence behavior of the isogeometric approach even for a coarse mesh, while offering substantial savings with respect to the number of degrees of freedom. We show a comparison between the different multipatch approaches and observe that the alternative formulations are well conditioned, independent of any penalty parameter and give the correct results. We also present a technique to couple the isogeometric shells with multibody systems using a pointwise interaction.
Sequential Consistency (SC) is the memory model traditionally applied by programmers and verification tools for the analysis of multithreaded programs.
SC guarantees that instructions of each thread are executed atomically and in program order.
Modern CPUs implement memory models that relax the SC guarantees: threads can execute instructions out of order, stores to the memory can be observed by different threads in different order.
As a result of these relaxations, multithreaded programs can show unexpected, potentially undesired behaviors, when run on real hardware.
The robustness problem asks if a program has the same behaviors under SC and under a relaxed memory model.
Behaviors are formalized in terms of happens-before relations — dataflow and control-flow relations between executed instructions.
Programs that are robust against a memory model produce the same results under this memory model and under SC.
This means, they only need to be verified under SC, and the verification results will carry over to the relaxed setting.
Interestingly, robustness is a suitable correctness criterion not only for multithreaded programs, but also for parallel programs running on computer clusters.
Parallel programs written in Partitioned Global Address Space (PGAS) programming model, when executed on cluster, consist of multiple processes, each running on its cluster node.
These processes can directly access memories of each other over the network, without the need of explicit synchronization.
Reorderings and delays introduced on the network level, just as the reorderings done by the CPUs, may result into unexpected behaviors that are hard to reproduce and fix.
Our first contribution is a generic approach for solving robustness against relaxed memory models.
The approach involves two steps: combinatorial analysis, followed by an algorithmic development.
The aim of combinatorial analysis is to show that among program computations violating robustness there is always a computation in a certain normal form, where reorderings are applied in a restricted way.
In the algorithmic development we work out a decision procedure for checking whether a program has violating normal-form computations.
Our second contribution is an application of the generic approach to widely implemented memory models, including Total Store Order used in Intel x86 and Sun SPARC architectures, the memory model of Power architecture, and the PGAS memory model.
We reduce robustness against TSO to SC state reachability for a modified input program.
Robustness against Power and PGAS is reduced to language emptiness for a novel class of automata — multiheaded automata.
The reductions lead to new decidability results.
In particular, robustness is PSPACE-complete for all the considered memory models.
This thesis is concerned with stochastic control problems under transaction costs. In particular, we consider a generalized menu cost problem with partially controlled regime switching, general multidimensional running cost problems and the maximization of long-term growth rates in incomplete markets. The first two problems are considered under a general cost structure that includes a fixed cost component, whereas the latter is analyzed under proportional and Morton-Pliska
For the menu cost problem and the running cost problem we provide an equivalent characterization of the value function by means of a generalized version of the Ito-Dynkin formula instead of the more restrictive, traditional approach via the use of quasi-variational inequalities (QVIs). Based on the finite element method and weak solutions of QVIs in suitable Sobolev spaces, the value function is constructed iteratively. In addition to the analytical results, we study a novel application of the menu cost problem in management science. We consider a company that aims to implement an optimal investment and marketing strategy and must decide when to issue a new version of a product and when and how much
to invest into marketing.
For the long-term growth rate problem we provide a rigorous asymptotic analysis under both proportional and Morton-Pliska transaction costs in a general incomplete market that includes, for instance, the Heston stochastic volatility model and the Kim-Omberg stochastic excess return model as special cases. By means of a dynamic programming approach leading-order optimal strategies are constructed
and the leading-order coefficients in the expansions of the long-term growth rates are determined. Moreover, we analyze the asymptotic performance of Morton-Pliska strategies in settings with proportional transaction costs. Finally, pathwise optimality of the constructed strategies is established.
In this paper we propose a phenomenological model for the formation of an interstitial gap between the tumor and the stroma. The gap
is mainly filled with acid produced by the progressing edge of the tumor front. Our setting extends existing models for acid-induced tumor invasion models to incorporate
several features of local invasion like formation of gaps, spikes, buds, islands, and cavities. These behaviors are obtained mainly due to the random dynamics at the intracellular
level, the go-or-grow-or-recede dynamics on the population scale, together with the nonlinear coupling between the microscopic (intracellular) and macroscopic (population)
levels. The wellposedness of the model is proved using the semigroup technique and 1D and 2D numerical simulations are performed to illustrate model predictions and draw
conclusions based on the observed behavior.
It is well known that the structure at a microscopic point of view strongly influences the
macroscopic properties of materials. Moreover, the advancement in imaging technologies allows
to capture the complexity of the structures at always decreasing scales. Therefore, more
sophisticated image analysis techniques are needed.
This thesis provides tools to geometrically characterize different types of three-dimensional
structures with applications to industrial production and to materials science. Our goal is to
enhance methods that allow the extraction of geometric features from images and the automatic
processing of the information.
In particular, we investigate which characteristics are sufficient and necessary to infer
the desired information, such as particles classification for technical cleanliness and
fitting of stochastic models in materials science.
In the production line of automotive industry, dirt particles collect on the surface of mechanical
components. Residual dirt might reduce the performance and durability of assembled products.
Geometric characterization of these particles allows to identify their potential danger.
While the current standards are based on 2d microscopic images, we extend the characterization
In particular, we provide a collection of parameters that exhaustively describe size and shape
of three-dimensional objects and can be efficiently estimated from binary images. Furthermore,
we show that only a few features are sufficient to classify particles according to the standards
of technical cleanliness.
In the context of materials science, we consider two types of microstructures: fiber systems
Stochastic geometry grants the fundamentals for versatile models able to encompass the
geometry observed in the samples. To allow automatic model fitting, we need rules stating which
parameters of the model yield the best-fitting characteristics. However, the validity of such
rules strongly depends on the properties of the structures and on the choice of the model.
For instance, isotropic orientation distribution yields the best theoretical results for Boolean
models and Poisson processes of cylinders with circular cross sections. Nevertheless, fiber
systems in composites are often anisotropic.
Starting from analytical results from the literature, we derive formulae for anisotropic
Poisson processes of cylinders with polygonal cross sections that can be directly used in
applications. We apply this procedure to a sample of medium density fiber board. Even
if image resolution does not allow to estimate reliably characteristics of the singles fibers,
we can fit Boolean models and Poisson cylinder processes. In particular, we show the complete
model fitting and validation procedure with cylinders with circular and squared cross sections.
Different problems arise when modeling cellular materials. Motivated by the physics of foams,
random Laguerre tessellations are a good choice to model the pore system of foams.
Considering tessellations generated by systems of non-overlapping spheres allows to control the
cell size distribution, but yields the loss of an analytical description of the model.
Nevertheless, automatic model fitting can still be obtained by approximating the characteristics
of the tessellation depending on the parameters of the model. We investigate how to improve
the choice of the model parameters. Angles between facets and between edges were never considered
so far. We show that the distributions of angles in Laguerre tessellations
depend on the model parameters. Thus, including the moments of the angles still allows automatic
model fitting. Moreover, we propose an algorithm to estimate angles from images of real foams.
We observe that angles are matched well in random Laguerre tessellations also when they are not
employed to choose the model parameters. Then, we concentrate on the edge length distribution. In
Laguerre tessellations occur many more short edges than in real foams. To deal with this problem,
we consider relaxed models. Relaxation refers to topological and structural modifications
of a tessellation in order to make it comply with Plateau's laws of mechanical equilibrium. We inspect
samples of different types of foams, closed and open cell foams, polymeric and metallic. By comparing
the geometric characteristics of the model and of the relaxed tessellations, we conclude that whether
the relaxation improves the edge length distribution strongly depends on the type of foam.
The present thesis describes the development and validation of a viscosity adaption method for the numerical simulation of non-Newtonian fluids on the basis of the Lattice Boltzmann Method (LBM), as well as the development and verification of the related software bundle SAM-Lattice.
By now, Lattice Boltzmann Methods are established as an alternative approach to classical computational fluid dynamics
methods. The LBM has been shown to be an accurate and efficient tool for the numerical simulation of weakly compressible or incompressible fluids. Fields of application reach from turbulent simulations through thermal problems to acoustic calculations among others. The transient nature of the method and the need for a regular grid based, non body conformal discretization makes the LBM ideally suitable for simulations involving complex solids. Such geometries are common, for instance, in the food processing industry, where fluids are mixed by static mixers or agitators. Those fluid flows are often laminar and non-Newtonian.
This work is motivated by the immense practical use of the Lattice Boltzmann Method, which is limited due to stability issues. The stability of the method is mainly influenced by the discretization and the viscosity of the fluid. Thus, simulations of non-Newtonian fluids, whose kinematic viscosity depend on the shear rate, are problematic. Several authors have shown that the LBM is capable of simulating those fluids. However, the vast majority of the simulations in the literature are carried out for simple geometries and/or moderate shear rates, where the LBM is still stable. Special care has to be taken for practical non-Newtonian Lattice Boltzmann simulations in order to keep them stable. A straightforward way is to truncate the modeled viscosity range by numerical stability criteria. This is an effective approach, but from the physical point of view the viscosity bounds are chosen arbitrarily. Moreover, these bounds depend on and vary with the grid and time step size and, therefore, with the simulation Mach number, which is freely chosen at the start of the simulation. Consequently, the modeled viscosity range may not fit to the actual range of the physical problem, because the correct simulation Mach number is unknown a priori. A way around is, to perform precursor simulations on a fixed grid to determine a possible time step size and simulation Mach number, respectively. These precursor simulations can be time consuming and expensive, especially for complex cases and a number of operating points. This makes the LBM unattractive for use in practical simulations of non-Newtonian fluids.
The essential novelty of the method, developed in the course of this thesis, is that the numerically modeled viscosity range is consistently adapted to the actual physically exhibited viscosity range through change of the simulation time step and the simulation Mach number, respectively, while the simulation is running. The algorithm is robust, independent of the Mach number the simulation was started with, and applicable for stationary flows as well as transient flows. The method for the viscosity adaption will be referred to as the "viscosity adaption method (VAM)" and the combination with LBM leads to the "viscosity adaptive LBM (VALBM)".
Besides the introduction of the VALBM, a goal of this thesis is to offer assistance in the spirit of a theory guide to students and assistant researchers concerning the theory of the Lattice Boltzmann Method and its implementation in SAM-Lattice. In Chapter 2, the mathematical foundation of the LBM is given and the route from the BGK approximation of the Boltzmann equation to the Lattice Boltzmann (BGK) equation is delineated in detail.
The derivation is restricted to isothermal flows only. Restrictions of the method, such as low Mach number flows are highlighted and the accuracy of the method is discussed.
SAM-Lattice is a C++ software bundle developed by the author and his colleague Dipl.-Ing. Andreas Schneider. It is a highly automated package for the simulation of isothermal flows of incompressible or weakly compressible fluids in 3D on the basis of the Lattice Boltzmann Method. By the time of writing of this thesis, SAM-Lattice comprises 5 components. The main components are the highly automated lattice generator SamGenerator and the Lattice Boltzmann solver SamSolver. Postprocessing is done with ParaSam, which is our extension of the
open source visualization software ParaView. Additionally, domain decomposition for MPI
parallelism is done by SamDecomposer, which makes use of the graph partitioning library MeTiS. Finally, all mentioned components can be controlled through a user friendly GUI (SamLattice) implemented by the author using QT, including features to visually track output data.
In Chapter 3, some fundamental aspects on the implementation of the main components, including the corresponding flow charts will be discussed. Actual details on the implementation are given in the comprehensive programmers guides to SamGenerator and SamSolver.
In order to ensure the functionality of the implementation of SamSolver, the solver is verified in Chapter 4 for Stokes's First Problem, the suddenly accelerated plate, and for Stokes's Second Problem, the oscillating plate, both for Newtonian fluids. Non-Newtonian fluids are modeled in SamSolver with the power-law model according to Ostwald de Waele. The implementation for non-Newtonian fluids is verified for the Hagen-Poiseuille channel flow in conjunction with a convergence analysis of the method. At the same time, the local grid refinement as it is implemented in SamSolver, is verified. Finally, the verification of higher order boundary conditions is done for the 3D Hagen-Poiseuille pipe flow for both Newtonian and non-Newtonian fluids.
In Chapter 5, the theory of the viscosity adaption method is introduced. For the adaption process, a target collision frequency or target simulation Mach number must be chosen and the distributions must be rescaled according to the modified time step size. A convenient choice is one of the stability bounds. The time step size for the adaption step is deduced from the target collision frequency \(\Omega_t\) and the currently minimal or maximal shear rate in the system, while obeying auxiliary conditions for the simulation Mach number. The adaption is done in the collision step of the Lattice Boltzmann algorithm. We use the transformation matrices of the MRT model to map from distribution space to moment space and vice versa. The actual scaling of the distributions is conducted on the back mapping, because we use the transformation matrix on the basis of the new adaption time step size. It follows an additional rescaling of the non-equilibrium part of the distributions, because of the form of the definition for the discrete stress tensor in the LBM context. For that reason it is clear, that the VAM is applicable for the SRT model as well as the MRT model, where there is virtually no extra cost in the latter case. Also, in Chapter 5, the multi level treatment will be discussed.
Depending on the target collision frequency and the target Mach number, the VAM can be used to optimally use the viscosity range that can be modeled within the stability bounds or it can be used to drastically accelerate the simulation. This is shown in Chapter 6. The viscosity adaptive LBM is verified in the stationary case for the Hagen-Poiseuille channel flow and in the transient case for the Wormersley flow, i.e., the pulsatile 3D Hagen-Poiseuille pipe flow. Although, the VAM is used here for fluids that can be modeled with the power-law approach, the implementation of the VALBM is straightforward for other non-Newtonian models, e.g., the Carreau-Yasuda or Cross model. In the same chapter, the VALBM is validated for the case of a propeller viscosimeter developed at the chair SAM. To this end, the experimental data of the torque on the impeller of three shear thinning non-Newtonian liquids serve for the validation. The VALBM shows excellent agreement with experimental data for all of the investigated fluids and in every operating point. For reasons of comparison, a series of standard LBM simulations is carried out with different simulation Mach numbers, which partly show errors of several hundred percent. Moreover, in Chapter 7, a sensitivity analysis on the parameters used within the VAM is conducted for the simulation of the propeller viscosimeter.
Finally, the accuracy of non-Newtonian Lattice Boltzmann simulations with the SRT and the MRT model is analyzed in detail. Previous work for Newtonian fluids indicate that depending on the numerical value of the collision frequency \(\Omega\), additional artificial viscosity is introduced due to the finite difference scheme, which negatively influences the accuracy. For the non-Newtonian case, an error estimate in the form of a functional is derived on the basis of a series expansion of the Lattice Boltzmann equation. This functional can be solved analytically for the case of the Hagen-Poiseuille channel flow of non-Newtonian fluids. The estimation of the error minimum is excellent in regions where the \(\Omega\) error is the dominant source of error as opposed to the compressibility error.
Result of this dissertation is a verified and validated software bundle on the basis of the viscosity adaptive Lattice Boltzmann Method. The work restricts itself on the simulation of isothermal, laminar flows with small Mach numbers. As further research goals, the testing of the VALBM with minimal error estimate and the investigation of the VALBM in the case of turbulent flows is suggested.
Lattice Boltzmann Methods have shown to be promising tools for solving fluid flow problems. This is related to the advantages of these methods, which are among others, the simplicity in handling complex geometries and the high efficiency in calculating transient flows. Lattice Boltzmann Methods are mesoscopic methods, based on discrete particle dynamics. This is in contrast to conventional Computational Fluid Dynamics methods, which are based on the solution of the continuum equations. Calculations of turbulent flows in engineering depend in general on modeling, since resolving of all turbulent scales is and will be in near future far beyond the computational possibilities. One of the most auspicious modeling approaches is the large eddy simulation, in which the large, inhomogeneous turbulence structures are directly computed and the smaller, more homogeneous structures are modeled.
In this thesis, a consistent large eddy approach for the Lattice Boltzmann Method is introduced. This large eddy model includes, besides a subgrid scale model, appropriate boundary conditions for wall resolved and wall modeled calculations. It also provides conditions for turbulent domain inlets. For the case of wall modeled simulations, a two layer wall model is derived in the Lattice Boltzmann context. Turbulent inlet conditions are achieved by means of a synthetic turbulence technique within the Lattice Boltzmann Method.
The proposed approach is implemented in the Lattice Boltzmann based CFD package SAM-Lattice, which has been created in the course of this work. SAM-Lattice is feasible of the calculation of incompressible or weakly compressible, isothermal flows of engineering interest in complex three dimensional domains. Special design targets of SAM-Lattice are high automatization and high performance.
Validation of the suggested large eddy Lattice Boltzmann scheme is performed for pump intake flows, which have not yet been treated by LBM. Even though, this numerical method is very suitable for this kind of vortical flows in complicated domains. In general, applications of LBM to hydrodynamic engineering problems are rare. The results of the pump intake validation cases reveal that the proposed numerical approach is able to represent qualitatively and quantitatively the very complex flows in the intakes. The findings provided in this thesis can serve as the basis for a broader application of LBM in hydrodynamic engineering problems.
The aim of this work was to synthesize and characterize new bidentate N,N,P-ligands and their corresponding heterobimetallic complexes. These bidentate pyridylpyrimidine aminophosphine ligands were synthesized by ring closure of two different enaminones ( 3-(dimethylamino)-1-(pyridine-2-yl)-prop-2-en-1-one or 3-(dimethylamino)-1-(pyridine-2-yl)-but-2-en-1-one) with excess amount of guanidinium salts in the presence of base. The novel phosphine functionalized guanidinium salts were prepared from 2-(diphenylphosphinyl)ethylamine or 3-(diphenyl-phosphinyl)propylamine. These bidentate N,N,P-ligands contain hard and soft donor sites which allows the coordination of two different metal centers and bimetallic complexes. These bimetallic complexes can exhibit a unique behavior as a result of a cooperation between the two metal atoms. First, the gold(I) complexes of all these four different ligands were synthesized. The gold metal coordinates only to the phosphorus atom. It was proved by X-Ray crystallography technique and 31P NMR spectroscopy. Addition to the gold(I)-monometallic complexes, trans- coordinated rhodium complex of (2-amino)pyridylpyrimidine aminophosphine ligand was successfully prepared. The characterization of this complex was achieved by NMR and IR spectroscopy. Reacting the mono gold(I) complexes with the different metal salts like Pd(PhCN)2Cl2, ZnCl2, [Ru(p-cymene)Cl2] dimer gave the target heterobimetallic complexes. The second metal centers coordinated to the N,N donor site which was proved by the help of NMR spectroscopy and ESI-MS measurements. The Au(I) and Au-Zn complexes of N,N,P-ligands were examined as catalysts for the hydroamidation reaction of cyclohexene with p-toluenesulfonamide. They did not show activities under the tested conditions. Further studies are necessary to understand the catalytic activities and cooperativity between the two metal atoms. In addition, bi-and trimetallic complexes with the rhodium compound could be synthesized and tested in different organic transformations. Furthermore, the chiral hydroxyl[2.2]paracyclophane substituted with five different aminopyrimidines were accomplished. These aminopyrimidine ligands were synthesized by a cyclization reaction with hydroxyl[2.2]paracyclophane substituted enaminone and excess amount of corresponding guanidinium salts under basic conditions. In the last part of this work, kinetic studies of cyclopalladation reaction of the 2-(arylaminopyrimidin-4-yl)pyridine ligands with Pd(PhCN)2 These measurements were carried out by using UV-Vis spectroscopy. The spectral studies of cyclometallation step showed that the reaction fits a second order kinetics. In addition to this, a full kinetic investigation was performed at different temperatures and the activation parameters of complex formation were calculated.
The last couple of years have marked the entire field of information technology with the introduction of a new global resource, called data. Certainly, one can argue that large amounts of information and highly interconnected and complex datasets were available since the dawn of the computer and even centuries before. However, it has been only a few years since digital data has exponentially expended, diversified and interconnected into an overwhelming range of domains, generating an entire universe of zeros and ones. This universe represents a source of information with the potential of advancing a multitude of fields and sparking valuable insights. In order to obtain this information, this data needs to be explored, analyzed and interpreted.
While a large set of problems can be addressed through automatic techniques from fields like artificial intelligence, machine learning or computer vision, there are various datasets and domains that still rely on the human intuition and experience in order to parse and discover hidden information. In such instances, the data is usually structured and represented in the form of an interactive visual representation that allows users to efficiently explore the data space and reach valuable insights. However, the experience, knowledge and intuition of a single person also has its limits. To address this, collaborative visualizations allow multiple users to communicate, interact and explore a visual representation by building on the different views and knowledge blocks contributed by each person.
In this dissertation, we explore the potential of subjective measurements and user emotional awareness in collaborative scenarios as well as support flexible and user- centered collaboration in information visualization systems running on tabletop displays. We commence by introducing the concept of user-centered collaborative visualization (UCCV) and highlighting the context in which it applies. We continue with a thorough overview of the state-of-the-art in the areas of collaborative information visualization, subjectivity measurement and emotion visualization, combinable tabletop tangibles, as well as browsing history visualizations. Based on a new web browser history visualization for exploring user parallel browsing behavior, we introduce two novel user-centered techniques for supporting collaboration in co-located visualization systems. To begin with, we inspect the particularities of detecting user subjectivity through brain-computer interfaces, and present two emotion visualization techniques for touch and desktop interfaces. These visualizations offer real-time or post-task feedback about the users’ affective states, both in single-user and collaborative settings, thus increasing the emotional self-awareness and the awareness of other users’ emotions. For supporting collaborative interaction, a novel design for tabletop tangibles is described together with a set of specifically developed interactions for supporting tabletop collaboration. These ring-shaped tangibles minimize occlusion, support touch interaction, can act as interaction lenses, and describe logical operations through nesting operations. The visualization and the two UCCV techniques are each evaluated individually capturing a set of advantages and limitations of each approach. Additionally, the collaborative visualization supported by the two UCCV techniques is also collectively evaluated in three user studies that offer insight into the specifics of interpersonal interaction and task transition in collaborative visualization. The results show that the proposed collaboration support techniques do not only improve the efficiency of the visualization, but also help maintain the collaboration process and aid a balanced social interaction.
In this work we focus on the regression models with asymmetrical error distribution,
more precisely, with extreme value error distributions. This thesis arises in the framework
of the project "Robust Risk Estimation". Starting from July 2011, this project won
three years funding by the Volkswagen foundation in the call "Extreme Events: Modelling,
Analysis, and Prediction" within the initiative "New Conceptual Approaches to
Modelling and Simulation of Complex Systems". The project involves applications in
Financial Mathematics (Operational and Liquidity Risk), Medicine (length of stay and
cost), and Hydrology (river discharge data). These applications are bridged by the
common use of robustness and extreme value statistics.
Within the project, in each of these applications arise issues, which can be dealt with by
means of Extreme Value Theory adding extra information in the form of the regression
models. The particular challenge in this context concerns asymmetric error distributions,
which significantly complicate the computations and make desired robustification
extremely difficult. To this end, this thesis makes a contribution.
This work consists of three main parts. The first part is focused on the basic notions
and it gives an overview of the existing results in the Robust Statistics and Extreme
Value Theory. We also provide some diagnostics, which is an important achievement of
our project work. The second part of the thesis presents deeper analysis of the basic
models and tools, used to achieve the main results of the research.
The second part is the most important part of the thesis, which contains our personal
contributions. First, in Chapter 5, we develop robust procedures for the risk management
of complex systems in the presence of extreme events. Mentioned applications use time
structure (e.g. hydrology), therefore we provide extreme value theory methods with time
dynamics. To this end, in the framework of the project we considered two strategies. In
the first one, we capture dynamic with the state-space model and apply extreme value
theory to the residuals, and in the second one, we integrate the dynamics by means of
autoregressive models, where the regressors are described by generalized linear models.
More precisely, since the classical procedures are not appropriate to the case of outlier
presence, for the first strategy we rework classical Kalman smoother and extended
Kalman procedures in a robust way for different types of outliers and illustrate the performance
of the new procedures in a GPS application and a stylized outlier situation.
To apply approach to shrinking neighborhoods we need some smoothness, therefore for
the second strategy, we derive smoothness of the generalized linear model in terms of
L2 differentiability and create sufficient conditions for it in the cases of stochastic and
deterministic regressors. Moreover, we set the time dependence in these models by
linking the distribution parameters to the own past observations. The advantage of
our approach is its applicability to the error distributions with the higher dimensional
parameter and case of regressors of possibly different length for each parameter. Further,
we apply our results to the models with generalized Pareto and generalized extreme value
Finally, we create the exemplary implementation of the fixed point iteration algorithm
for the computation of the optimally robust in
uence curve in R. Here we do not aim to
provide the most
exible implementation, but rather sketch how it should be done and
retain points of particular importance. In the third part of the thesis we discuss three applications,
operational risk, hospitalization times and hydrological river discharge data,
and apply our code to the real data set taken from Jena university hospital ICU and
provide reader with the various illustrations and detailed conclusions.