### Filtern

#### Erscheinungsjahr

- 2012 (33) (entfernen)

#### Dokumenttyp

- Dissertation (33) (entfernen)

#### Sprache

- Englisch (33) (entfernen)

#### Schlagworte

- Transaction Costs (2)
- Arithmetic data-path (1)
- Bildverarbeitung (1)
- Bioinformatik (1)
- Carbon footprint (1)
- Chlamydomonas reinhardii (1)
- Cohen-Lenstra heuristic (1)
- Computeralgebra (1)
- Consistent Price Processes (1)
- Data path (1)

#### Fachbereich / Organisatorische Einheit

Image restoration and enhancement methods that respect important features such as edges play a fundamental role in digital image processing. In the last decades a large
variety of methods have been proposed. Nevertheless, the correct restoration and
preservation of, e.g., sharp corners, crossings or texture in images is still a challenge, in particular in the presence of severe distortions. Moreover, in the context of image denoising many methods are designed for the removal of additive Gaussian noise and their adaptation for other types of noise occurring in practice requires usually additional efforts.
The aim of this thesis is to contribute to these topics and to develop and analyze new
methods for restoring images corrupted by different types of noise:
First, we present variational models and diffusion methods which are particularly well
suited for the restoration of sharp corners and X junctions in images corrupted by
strong additive Gaussian noise. For their deduction we present and analyze different
tensor based methods for locally estimating orientations in images and show how to
successfully incorporate the obtained information in the denoising process. The advantageous
properties of the obtained methods are shown theoretically as well as by
numerical experiments. Moreover, the potential of the proposed methods is demonstrated
for applications beyond image denoising.
Afterwards, we focus on variational methods for the restoration of images corrupted
by Poisson and multiplicative Gamma noise. Here, different methods from the literature
are compared and the surprising equivalence between a standard model for
the removal of Poisson noise and a recently introduced approach for multiplicative
Gamma noise is proven. Since this Poisson model has not been considered for multiplicative
Gamma noise before, we investigate its properties further for more general
regularizers including also nonlocal ones. Moreover, an efficient algorithm for solving
the involved minimization problems is proposed, which can also handle an additional
linear transformation of the data. The good performance of this algorithm is demonstrated
experimentally and different examples with images corrupted by Poisson and
multiplicative Gamma noise are presented.
In the final part of this thesis new nonlocal filters for images corrupted by multiplicative
noise are presented. These filters are deduced in a weighted maximum likelihood
estimation framework and for the definition of the involved weights a new similarity measure for the comparison of data corrupted by multiplicative noise is applied. The
advantageous properties of the new measure are demonstrated theoretically and by
numerical examples. Besides, denoising results for images corrupted by multiplicative
Gamma and Rayleigh noise show the very good performance of the new filters.

Thermoplastic polymer-polymer composites consist of a polymeric matrix and a
polymeric reinforcement. The combination of these materials offers outstanding
mechanical properties at lower weight than standard fiber reinforced materials.
Furthermore, when both polymeric components originate from the same family or,
ideally, from the same polymer, their sustainability degree is higher than standard
fiber reinforced composites.
A challenge of polymer-polymer composites is the subsequent processing of their
semi-finished materials by heating techniques. Since the fibers are made of meltable
thermoplastic, the reinforcing fiber structure might be lost during the heating process.
Hence, the mechanical properties of an overheated polymer-polymer composite
would decline, and finally, they would be even lower than the neat matrix. A decrease
of process temperature to manage the heating challenge is not reasonable since the
cycle time would be increased at the same time. Therefore, this work pursues the
adaption of a fast and selective heating method on the use with polymer-polymer
composites. Inductively activatable particles, so-called susceptors, were distributed in
the matrix to evoke a local heating in the matrix when being exposed to an
alternating magnetic field. In this way, the energy input to the fibers is limited.
The experimental series revealed the induction particle heating effect to be mainly
related to susceptor material, susceptor fraction, susceptor distribution as well as
magnetic field strength, coupling distance, and heating time. A proper heating was
achieved with ferromagnetic particles at a filler content of only 5 wt-% in HDPE as
well as with its respective polymer fiber reinforced composites. The study included
the analysis of susceptor impact on mechanical and thermal matrix properties as well
as a degradation evaluation. The susceptors were identified to have only a marginal
impact on matrix properties. Furthermore, a semi-empiric simulation of the particle
induction heating was applied, which served for the investigation of intrinsic melting
processes.
The achieved results, the experimental as well as the analytic study, were
successfully adapted to a thermoforming process with a polymer-polymer material,
which had been preheated by means of particle induction.

I report on two experiments, which were designed to test theoretical predictions about individual behavior in a duopolistic setting. With quantity being the choice variable a simultaneous Cournot game and a sequential Stackelberg game were tested over two periods. The key feature of both models was that players were able to lower marginal cost for period two if they successfully outperformed their competition in period one in terms of profit. Experimental results suggest that in the Cournot game players are very competitive in period one but become Cournot players in period two. In the Stackelberg game Cournot play is modal, suggesting that players have preferences for equality in payoffs, which maybe brought about by punishment of Stackelberg followers and fear of punishment of Stackelberg leaders . Overall, players earned more money in the Stackelberg game than in the Cournot game.

Development of New Methods for the Synthesis of Aldehydes, Arenes and Trifluoromethylated Compounds
(2012)

In the 1st project, successful development of 2nd generation of a palladium catalyst for the selective hydrogenation of carboxylic acids to aldehydes was accomplished. This project was done in cooperation with Dipl. Chem. Thomas Fett from Boeringer Ingelheim, Austria. The new catalyst is highly effective for the conversion of diversely functionalized aromatic, heteroaromatic and aliphatic carboxylic acids to the corresponding aldehydes in the presence of pivalic anhydride at 5 bar hydrogen pressure, which was otherwise achieved either at 30 bar of hydrogen pressure or by using waste intensive hypophosphite bases as reducing agent. Our method has increased the synthetic importance of this valuable transformation. Selective hydrogenation of carboxylic acids to the corresponding aldehydes is now possible with industrial hydrogenation equipment as well as laboratory scale glass autoclaves. It might also convince the synthetic organic chemists to use this transformation for routine aldehyde synthesis in the laboratories.
In the 2nd project, a microwave assisted Cu-catalyzed protodecarboxylation of arenecarboxylic acids to arenes is achieved. This work was done in collaboration with Dipl. Chem. Filipe Manjolinho under the supervision of Dr. Nuria Rodríguez. In the presence of 1-5 mol% of inexpensive CuI/1,10-phenanthroline catalyst generated in situ under microwave radiations, diversely functionalized arenes and heteroarene carboxylic acids have been decarboxylated to the corresponding arenes in good yields at 190 °C in 5-15 min. The loss of volatile arenes with the release of CO2 is controled by the use of sealed high pressure resistant microwave vessels. These reactions are highly beneficial for parallel synthesis in drug discovery due to their short reaction time. Microwave technology will also help in the future to develop more effective catalysts for protodecarboxylation rections.
Based on the microwave assisted protodecarboxylation strategy, decarboxylative coupling of arenecarboxylic acids with aryl triflates and tosylates was also conducted under microwave radiation which provided higher yields of the corresponding biphenyls from deactivated substrates in short reaction time compared to the conventional heating.
In the 3rd project, crystalline, potassium (trifluoromethyl)trimethoxyborate was successfully applied for the synthesis of benzotrifluorides under the oxidative conditions. This project was done in cooperation with Dipl. Chem. Annette Buba. In the presence of Cu(OAc)2 and molecular oxygen, arylboronates were coupled with K+[CF3B(OMe)3] in DMSO at 60 °C. A variety of benzotriflurides was synthesized in good yields under the optimized reaction conditions. This protocol for the oxidative trifluoromethylation of arylboronates is the base for the development of decarboxylative trifluoromethylation reaction of arenecarboxylic acids.
The 4th project discloses the simple and straightforward synthesis of trifluoromethylated alcohols by nucleophilic addition of potassium (trifluoromethyl)trimethoxyborate to carbonyl compounds. This project was done in cooperation with Dr. Thomas Knauber and Dipl. Chem. Annette Buba. In the presence of K+[CF3B(OMe)3] in THF at 60 °C, diversely functionalized aldehydes and ketones were successfully converted into the corresponding trifluoromethylated alcohols.
The 3rd and 4th projects demonstrate the successful establishment of crystalline and shelf stable potassium (trifluoromethyl)trimethoxyborate as highly versatile CF3-source in nucleophilic trifluoromethylation reactions. These new protocols are characterized by their user-friendliness and broad applicability under mild reaction conditions, thus they are beneficial for late stage introduction of CF3-group into organic molecules.

Wechselnde Umweltbedingungen wie Temperaturveränderungen oder der Zugang zu Nährstoffen erfordern spezielle genetische Anpassungsprogramme, vor allem von sessilen Organismen wie Pflanzen. Ein solcher hochkonservierter Mechanismus, der unter anderem vor Temperaturspitzen schützt, ist die von Hitzeschockfaktoren (HSF) kontrollierte Hitzeschockantwort (HSR). Dabei werden vermehrt spezifische Hitzestressproteine (HSPs, Chaperone) gebildet, die Proteine vor Denaturierung schützen. In Pflanzen hat sich ein hochkomplexes regulatorisches Netzwerk gebildet, das aus über 20 HSFs besteht, das eine genaue Feinabstimmung der HSR auf die jeweiligen Stressbedingungen erlaubt.
Das hohe Maß an Komplexität der HSR in Pflanzen erschwert die wissenschaftliche Zugänglichkeit jedoch erheblich. Um die grundlegenden Prinzipien der HSR in Pflanzen zu verstehen griffen wir deshalb auf einen einfacheren Modellorganismus zurück, der Pflanzen sehr nahe steht aber nur einen einzigen HSF (HSF1) enthält, der einzelligen Grünalge Chlamydomonas reinhardtii. Im Rahmen dieser Arbeit wurden dazu drei Ansätze verfolgt.
Als erstes wurden verschiedene chemische Substanzen eingesetzt die unterschiedliche Schritte während der Aktivierung und Abschaltung der HSR hemmen um darüber die Regulation der HSR aufzuklären. Dabei wurde festgestellt, dass die Phosphorylierung von HSF1 eine entscheidende Rolle in der Aktivierung der HSR spielt, das auslösende Momentum die Anhäufung von falsch gefalteten Proteinen ist und das HSP90A aus dem Cytosol eine wichtige modulierende Rolle bei der HSR spielt.
Als zweites wurde die Veränderung sämtlicher Transkripte mithilfe von Microarrays gemessen, um vor allem pflanzenspezifische Prozesse zu identifizieren, die auf erhöhte Temperaturen gezielt angepasst werden müssen. Dabei konnte die Chlorophyll Biosynthese und der Transport von Proteinen in den Chloroplasten als neue, pflanzenspezifische Ziele der Stressantwort identifiziert werden. Des Weiteren konnte direkt gezeigt werden, das HSF1 auch plastidäre Chaperone reguliert, im Gegensatz zu mitochondrialen Chaperonen die getrennt gesteuert werden.
Als letztes wurde gezielt die Expression wichtiger Gene für die Stressantwort (HSF1/HSP70B) unterdrückt, um den Einfluss dieser Gene auf die HSR genauer zu studieren. Dazu habe ich ein in der einzelligen Grünalge neuartiges System entwickelt, basierend auf dem RNAi Mechanismus, dass es erlaubt abhängig von der Stickstoffquelle im Nährmedium auch essentielle Gene gezielt auszuschalten. Dieses System erlaubte es zu zeigen, dass HSF1 selbst während des Stresses die Expression seiner RNA erhöht, und dies gezielt tut um die Stressantwort weiter zu verstärken. Es konnte weiter gezeigt werden, dass das Chloroplasten Chaperon HSP70B ein essentielles Protein für das Zellwachstum ist, welches mithilfe des induzierbaren RNAi Systems genauer untersucht werden kann. Dabei wurde festgestellt, dass die HSP70B vermittelte Assemblierung und Disassemblierung des VIPP1 Proteins entscheidend ist für dessen Funktion in der Zelle. Des Weiteren konnte gezeigt werde, dass HSP70B wahrscheinlich verantwortlich ist für die Faltung eines oder mehrerer noch unbekannter Enzyme der Arginin Biosynthese oder der Stickstofffixierung, und das diese Prozesse wahrscheinlich die essentielle Funktion von HSP70B darstellen.

The discrete nature of the dispersed phase (swarm of droplet) in stirred and pulsed liquid-liquid extraction columns makes its mathematical modelling of such complex system a tedious task. The dispersed phase is considered as a population of droplets distributed randomly with respect to their internal properties (such as: droplet size and solute concentration) at a specific location in space. Hence, the population balance equation has been emerged as a mathematical tool to model and describe such complex behaviour. However, the resulting model is too complicated. Accordingly, the analytical solution of such a mathematical model does not exist except for particular cases. Therefore, numerical solutions are resorted to in general. This is due to the inherent nonlinearities in the convective and diffusive terms as well as the appearance of many integrals in the source term. However, modelling and simulation of liquid extraction columns is not an easy task because of the discrete nature of the dispersed phase, which consist of population of droplets. The natural frame work for taking this into account is the population balance approach.
In part of this doctoral thesis work, a rigours mathematical model based on the bivariate population balance frame work (the base of LLECMOD ‘‘Liquid-Liquid Extraction Column Module’’) for the steady state and dynamic simulation of pulsed (sieve plate and packed) liquid-liquid extraction columns is developed. The model simulates the coupled hydrodynamic and mass transfer for pulsed (packed and sieve plate) extraction columns. The model is programmed using visual digital FORTRAN and then integrated into the LLECMOD program. Within LLECMOD the user can simulate different types of extraction columns including stirred and pulsed ones. The basis of LLECMOD depends on stable robust numerical algorithms based on an extended version of a fixed pivot technique after Attarakih et al., 2003 (to take into account interphase solute transfer) and advanced computational fluid dynamics numerical methods. Experimental validated correlations are used for the estimation of the droplet terminal velocity in extraction columns based on single and swarm droplet experiments in laboratory scale devices. Additionally, recent published correlations for turbulent energy dissipation, droplet breakage and coalescence frequencies are discussed as been used in this version of LLECMOD. Moreover, coalescence model from literature derived from a stochastical description have been modified to fit the deterministic population model. As a case study, LLECMOD is used here to simulate the steady state performance of pulsed extraction columns under different operating conditions, which include pulsation intensity and volumetric flow rates are simulated. The effect of pulsation intensity (on the holdup, mean droplet diameter and solute concentration) is found to have more profound effect on systems of high interfacial tension. On the hand, the variation of volumetric flow rates have substantial effect on the holdup, mean droplet diameter and solute concentration profiles for chemical systems with low interfacial tension. Two chemical test systems recommended by the European Federation of Chemical Engineering (water-acetone (solute)-n-butyl acetate and water-acetone (solute)-toluene) and an industrial test system are used in the simulation. Model predictions are successfully validated against steady state and transient experimental data, where good agreements are achieved. The simulated results (holdup, mean droplet diameter and mass transfer profiles) compared to the experimental data show that LLECMOD is a powerful simulation tool, which can efficiently predict the dynamic and steady state performance of pulsed extraction columns.
In other part of this doctoral thesis work, the steady state performance of extraction columns is studied taking into account the effect of dispersed phase inlet condition (light or heavy phase is dispersed) and the direction of mass transfer (from continuous to dispersed phase and vice versa) using the population balance framework. LLECMOD, a program that uses multivariate population balance models, is extended to take into account the direction of mass transfer and the dispersed phase inlet. As a case study, LLECMOD is used to simulate pilot plant RDC columns where the steady state mean flow properties (dispersed phase hold up and droplet mean diameter) and the solute concentration profiles are compared to the available experimental data. Three chemical systems were used: sulpholane–benzene–n-heptane, water–acetone–toluene and water–acetone–n-butyl acetate. The dispersed phase inlet and the direction of mass transfer as well as the chemical system physical properties are found to have profound effect on the steady state performance of the RDC column. For example, the mean droplet diameter is found to persist invariant when the heavy phase is dispersed and the extractor efficiency is higher when the direction of mass transfer is from the continuous to the dispersed phase. For the purpose of experimental validation, it is found that LLECMOD predictions are in good agreement with the available experimental data concerning the dispersed phase hold up, mean droplet diameter and solute concentration profiles in both phases.
In a further part of this doctoral thesis, a mathematical model is developed for liquid extraction columns based on the multivariate population balance equation (PBE) and the primary secondary particle method (PSPM) introduced by Attarakih, 2010 (US Patent Application: 0100106467). It is extended to include the momentum balance for the dispersed phase. The advantage of momentum balance is to eliminate the need for often conflicting correlations used in estimating the terminal velocity of single and swarm of droplets. The resulting mathematical model is complex due to the integral nature of the population balance equation. To reduce the complexity of this model, while maintaining most of the information drawn from the continuous population balance equation, the concept of the PSPM is used. Based on the multivariate population balance equation and the PSPM a mathematical model is developed for any liquid extraction column. The secondary particle could be envisaged as a fluid particle carrying information about the distribution as it is evolved in space and time, in the meanwhile the primary particles carry the mean properties of the population such as total droplet concentration; mean droplet diameter dispersed phase hold up and so on. This information reflects the particle-particle interactions (breakage and coalescence) and transport (convection and diffusion). The developed model is discretized in space using a first-order upwind method, while semi-implicit first-order scheme in time is used to simulate a pilot plant RDC extraction column. Here the effect of the number of primary particles (classes) on the final predicted solution is investigated. Numerical results show that the solution converge fast even as the number of primary particle is increased. The terminal droplet velocity of the individual primary particle is found the most sensitive to the number of primary particles. Other mean population properties like the droplet mean diameter, mean hold up and the concentration profiles are also found to converge along the column height by increasing the number of primary particles. The predicted steady state profiles (droplet diameter, holdup and the concentration profiles) along a pilot RDC extraction column are compared to the experimental data where good agreement is achieved.
In addition to this a robust rigorous mathematical model based on the bivariate population balance equation is developed to predict the steady state and dynamic behaviour of the interacting hydrodynamics and mass transfer in Kühni extraction columns. The developed model is extended to include the momentum balance for the calculation of the droplet velocity. The effects of step changes in the important input variables (such as volumetric flow rates, rotational speed, inlet solute concentrations etc.) on the output variables (dispersed phase holdup, mean droplet diameter and the concentration profiles) are investigated.
The last topic of this doctoral thesis is developed to transient problems. The unsteady state analysis reveals the fact that the largest time constant (slowest response) is due to the mass transfer. On the contrary, the hydrodynamic response of the dispersed phase holdup is very fast when compared to the mass transfer due to the relative fast motion of the dispersed droplets with respect to the continuous phase. The dynamic behaviour of the dispersed and continuous phases shows a lag time that increases away from the feed points of both phases. Moreover, the solute concentration response shows a highly nonlinear behaviour due to both positive and negative step changes in the input variables. The simulation results are in good agreement with the experimental ones and show the usefulness of the model.

The goal of this work is to develop a simulation-based algorithm, allowing the prediction
of the effective mechanical properties of textiles on the basis of their microstructure
and corresponding properties of fibers. This method can be used for optimization of the
microstructure, in order to obtain a better stiffness or strength of the corresponding fiber
material later on. An additional aspect of the thesis is that we want to take into account the microcontacts
between fibers of the textile. One more aspect of the thesis is the accounting for the thickness of thin fibers in the
textile. An introduction of an additional asymptotics with respect to a small parameter,
the relation between the thickness and the representative length of the fibers, allows a
reduction of local contact problems between fibers to 1-dimensional problems, which
reduces numerical computations significantly.
A fiber composite material with periodic microstructure and multiple frictional microcontacts
between fibers is studied. The textile is modeled by introducing small geometrical
parameters: the periodicity of the microstructure and the characteristic
diameter of fibers. The contact linear elasticity problem is considered. A two-scale
approach is used for obtaining the effective mechanical properties.
The algorithm using asymptotic two-scale homogenization for computation of the
effective mechanical properties of textiles with periodic rod or fiber microstructure
is proposed. The algorithm is based on the consequent passing to the asymptotics
with respect to the in-plane period and the characteristic diameter of fibers. This
allows to come to the equivalent homogenized problem and to reduce the dimension
of the auxiliary problems. Further numerical simulations of the cell problems give
the effective material properties of the textile.
The homogenization of the boundary conditions on the vanishing out-of-plane interface
of a textile or fiber structured layer has been studied. Introducing additional
auxiliary functions into the formal asymptotic expansion for a heterogeneous
plate, the corresponding auxiliary and homogenized problems for a nonhomogeneous
Neumann boundary condition were deduced. It is incorporated into the right hand
side of the homogenized problem via effective out-of-plane moduli.
FiberFEM, a C++ finite element code for solving contact elasticity problems, is
developed. The code is based on the implementation of the algorithm for the contact
between fibers, proposed in the thesis.
Numerical examples of homogenization of geotexiles and wovens are obtained in the
work by implementation of the developed algorithm. The effective material moduli
are computed numerically using the finite element solutions of the auxiliary contact
problems obtained by FiberFEM.

Induction welding is a technique for joining of thermoplastic composites. An alternating
electromagnetic field is used for contact-free and fast heating of the parts to be
welded. In case of a suitable reinforcement structure heat generation occurs directly
in the laminate with complete heating in thickness direction in the vicinity of the coil.
The resulting temperature field is influenced by the distance to the induction coil with
decreasing temperature for increasing distance. Consequently, the surface facing the
inductor yields the highest, the opposite surface the lowest temperature.
The temperature field described significantly complicates the welding process. Due to
complete heating the laminate has to be loaded with pressure in order to prevent delamination,
which requires the usage of complex and expensive welding tools. Additionally,
the temperature difference between the inductor and the opposite side may
be greater than the processing window, which is determined by the properties of the
matrix polymer.
The induction welding process is influenced by numerous parameters. Due to complexity
process development is mainly based on experimental studies. The investigation
of parameter influences and interactions is cumbersome and the measurement
of quality relevant parameters, especially in the bondline, is difficult. Process simulation
can reduce the effort of parameter studies and contribute to further analysis of
the induction welding process.
The objective of this work is the development of a process variant of induction welding
preventing complete heating of the laminate in thickness direction. For optimal
welding the bondline has to reach the welding temperature whereas the other domains
should remain below the melting temperature of the matrix polymer.
For control of the temperature distribution localized cooling by an impinging jet of
compressed air was implemented. The effect was assessed by static heating experiments
with carbon fiber reinforced polyetheretherketone (CF/PEEK) and polyphenylenesulfide
(CF/PPS).
The application of localized cooling could influence the temperature distribution in
thickness direction of the laminate, according to the specifications of the welding
process. The temperature maximum was shifted from the inductor to the opposite side. This enables heating of the laminate to welding temperature in the bondline and
concurrently preventing melting and effects connected to this on the outer surface.
Inductive heating and the process variant with localized cooling were implemented in
three-dimensional finite-element process models. For that purpose, the finiteelement-
software Comsol Multiphysics 4.1 was used for the development of fully
coupled electromagnetic-thermal models which have been validated experimentally.
A sensitivity analysis for determination of different processing parameters of inductive
heating was conducted. The coil current, field frequency, and heat capacity were
identified as significant parameters. The cooling effect of the impinging jets was estimated
by appropriate convection coefficients.
For transfer of the developed process variant to the continuous induction welding
process, a process model was created. It represents a single overlap joint with continuous
feed. With the help of process modeling a parameter set for welding of
CF/PEEK was determined and used for joining of specimens. In doing so, the desired
temperature field was achieved and melting of the outer layers could be prevented.

Unidirectional (UD) composites are the most competitive materials for the production
of high-end structures. Their field of application spreads from the aerospace up to
automotive and general industry sector. Typical examples of components made of
unidirectional reinforced composite materials are rocket motor cases, drive shafts or
pressure vessels for hydrogen storage. The filament winding technology, the pultrusion
process and the tape placement are processes suitable for the manufacturing
using UD semi-finished products. The demand for parts made of UD composites is
constantly increasing over the last years. A key feature for the success of this technology
is the improvement of the manufacturing procedure.
Impregnation is one of the most important steps in the manufacturing process. During
this step the dry continuous fibers are combined with the liquid matrix in order to create
a fully impregnated semi-finished product. The properties of the impregnated roving
have a major effect on the laminate quality, and the efficient processing of the
liquid matrix has a big influence on the manufacturing costs.
The present work is related to the development of a new method for the impregnation
of carbon fiber rovings with thermoset resin. The developed impregnation unit consists
of a sinusoidal cavity without any moving parts. The unit in combination with an
automated resin mixing-dosing system allows complete wet-out of the fibers, precise
calibration of the resin fraction, and stable processing conditions.
The thesis focuses on the modeling of the impregnation process. Mathematical expressions
for the fiber compaction, the gradual increase of the roving tension, the
static pressure, the capillarity inside the filaments of the roving, and the fiber permeation
are presented, discussed, and experimentally verified. These expressions were
implemented in a modeling algorithm. The model takes into account all the relevant
material and process parameters. An experimental set-up based on the filament
winding process was used for the validation of the model. Trials under different conditions
have been performed. The results proved that the model can accurately simulate
the impregnation process. The good impregnation degree of the wound samples
confirmed the efficiency of the developed impregnation unit. A techno economical
analysis has proved that the developed system will result to the reduction of the
manufacturing costs and to the increase of the productivity.

Filtering, Approximation and Portfolio Optimization for Shot-Noise Models and the Heston Model
(2012)

We consider a continuous time market model in which stock returns satisfy a stochastic differential equation with stochastic drift, e.g. following an Ornstein-Uhlenbeck process. The driving noise of the stock returns consists not only of Brownian motion but also of a jump part (shot noise or compound Poisson process). The investor's objective is to maximize expected utility of terminal wealth under partial information which means that the investor only observes stock prices but does not observe the drift process. Since the drift of the stock prices is unobservable, it has to be estimated using filtering techniques. E.g., if the drift follows an Ornstein-Uhlenbeck process and without
jump part, Kalman filtering can be applied and optimal strategies can be computed explicitly. Also in other cases, like for an underlying
Markov chain, finite-dimensional filters exist. But for certain jump processes (e.g. shot noise) or certain nonlinear drift dynamics explicit computations, based on discrete observations, are no longer possible or existence of finite dimensional filters is no longer valid. The same
computational difficulties apply to the optimal strategy since it depends on the filter. In this case the model may be approximated by
a model where the filter is known and can be computed. E.g., we use statistical linearization for non-linear drift processes, finite-state-Markov chain approximations for the drift process and/or diffusion approximations for small jumps in the noise term.
In the approximating models, filters and optimal strategies can often be computed explicitly. We analyze and compare different approximation methods, in particular in view of performance of the corresponding utility maximizing strategies.