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Modern society relies on convenience services and mobile communication. Cloud computing is the current trend to make data and applications available at any time on every device. Data centers concentrate computation and storage at central locations, while they claim themselves green due to their optimized maintenance and increased energy efﬁciency. The key enabler for this evolution is the microelectronics industry. The trend to power efﬁcient mobile devices has forced this industry to change its design dogma to: ”keep data locally and reduce data communication whenever possible”. Therefore we ask: is cloud computing repeating the aberrations of its enabling industry?

The direction splitting approach proposed earlier in [6], aiming at the efficient solution of Navier-Stokes equations, is extended and adopted here to solve the Navier-Stokes-Brinkman equations describing incompressible flows in plain and in porous media. The resulting pressure equation is a perturbation of the
incompressibility constrained using a direction-wise factorized operator as proposed in [6]. We prove that this approach is unconditionally stable for the unsteady Navier-Stokes-Brinkman problem. We also provide numerical illustrations of the method's accuracy and efficiency.

This research for this thesis was conducted to develop a framework which supports the automatic configuration of project-specific software development processes by selecting and combining different technologies: the Process Configuration Framework. The research draws attention to the problem that while the research community develops new technologies, the industrial companies continue only using their well-known ones. Because of this, technology transfer takes decades. In addition, there is the fact that there is no solution which solves all problems in a software development project. This leads to a number of technologies which need to be combined for one project.
The framework developed and explained in this research mainly addresses those problems by building a bridge between research and industry as well as by supporting software companies during the selection of the most appropriate technologies combined in a software process. The technology transformation gap is filled by a repository of (new) technologies which are used as a foundation of the Process Configuration Framework. The process is configured by providing SPEM process pattern for each technology, so that the companies can build their process by plugging into each other.
The technologies of the repository were specified in a schema including a technology model, context model, and an impact model. With context and impact it is possible to provide information about a technology, for example, its benefits to quality, cost or schedule. The offering of the process pattern as output of the Process Configuration Framework is performed in several stages:
I Technology Ranking:
1 Ranking based on Application Domain, Project & Impact
2 Ranking based on Environment
3 Ranking based on Static Context
II Technology Combination:
4 Creation of all possible Technology Chains
5 Restriction of the Technology Chains
6 Ranking based on Static and Dynamic Context
7 Extension of the Chains by Quality Assurance
III Process Configuration:
8 Process Component Diagram
9 Extension of the Process Component Diagram
10 Instantiation of the Components by Technologies of the Technology Chain
11 Providing process patterns
12 Creation of the process based on Patterns
The effectiveness and quality of the Process Configuration Framework have additionally been evaluated in a case study. Here, the Technology Chains manually created by experts were compared to the chains automatically created by the framework after it was configured by those experts. This comparison depicted that the framework results are similar and therefore can be used as a recommendation.
We conclude from our research that support during the configuration of a process for software projects is important especially for non-experts. This support is provided by the Process Configuration Framework developed in this research. In addition our research has shown that this framework offers a possibility to speed up the technology transformation gap between the research community and industrial companies.

It is often helpful to compute the intrinsic volumes of a set of which only a pixel image is observed. A computational efficient approach, which is suggested by several authors and used in practice, is to approximate the intrinsic volumes by a linear functional of the pixel configuration histogram. Here we want to examine, whether there is an optimal way of choosing this linear functional, where we will use a quite natural optimality criterion that has already been applied successfully for the estimation of the surface area. We will see that for intrinsic volumes other than volume or surface area this optimality criterion cannot be used, since estimators which ignore the data and return constant values are optimal w.r.t. this criterion. This shows that one has to be very careful, when intrinsic volumes are approximated by a linear functional of the pixel configuration histogram.

The paper production is a problem with significant importance for the society
and it is a challenging topic for scientific investigations. This study is concerned
with the simulations of the pressing section of a paper machine. A two-dimensional
model is developed to account for the water flow within the pressing zone. Richards’
type equation is used to describe the flow in the unsaturated zone. The dynamic capillary
pressure–saturation relation proposed by Hassanizadeh and co-workers (Hassanizadeh
et al., 2002; Hassanizadeh, Gray, 1990, 1993a) is adopted for the paper
production process.
The mathematical model accounts for the co-existence of saturated and unsaturated
zones in a multilayer computational domain. The discretization is performed
by the MPFA-O method. The numerical experiments are carried out for parameters
which are typical for the production process. The static and dynamic capillary
pressure–saturation relations are tested to evaluate the influence of the dynamic
capillary effect.

In this work, some model reduction approaches for performing simulations
with a pseudo-2D model of Li-ion battery are presented. A full pseudo-2D model of processes in Li-ion batteries is presented following
[3], and three methods to reduce the order of the full model are considered. These are: i) directly reduce the model order using proper
orthogonal decomposition, ii) using fractional time step discretization in order to solve the equations in decoupled way, and iii) reformulation
approaches for the diffusion in the solid phase. Combinations of above
methods are also considered. Results from numerical simulations are presented, and the efficiency and the accuracy of the model reduction approaches are discussed.

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.

Annual Report 2011
(2012)

Annual Report, Jahrbuch AG Magnetismus

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.

In this paper we investigate the asymptotic behaviour of the parallel volume
of fixed non-convex bodies in Minkowski spaces as the distance \(r\) tends to infinity.
We will show that the difference of the parallel volume of the convex hull of a
body and the parallel volume of the body itself can at most have order \(r^{d-2}\) in a \(d\)-dimensional space. Then we will show that in Euclidean spaces this difference can at most have order \(r^{d-3}\). These results have several applications, e.g. we will use
them to compute the derivative of \(f_\mu(rK)\) in \(r = 0\), where \(f_\mu\) is the Wills functional
or a similar functional, \(K\) is a body and \(rK\) is the Minkowski-product of \(r\) and \(K\). Finally we present applications concerning Brownian paths and Boolean models and derive new proofs for formulae for intrinsic volumes.