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A wavelet technique, the wavelet-Mie-representation, is introduced for the analysis and modelling of the Earth's magnetic field and corresponding electric current distributions from geomagnetic data obtained within the ionosphere. The considerations are essentially based on two well-known geomathematical keystones, (i) the Helmholtz-decomposition of spherical vector fields and (ii) the Mie-representation of solenoidal vector fields in terms of poloidal and toroidal parts. The wavelet-Mie-representation is shown to provide an adequate tool for geomagnetic modelling in the case of ionospheric magnetic contributions and currents which exhibit spatially localized features. An important example are ionospheric currents flowing radially onto or away from the Earth. To demonstrate the functionality of the approach, such radial currents are calculated from vectorial data of the MAGSAT and CHAMP satellite missions.
The article is concerned with the modelling of ionospheric current systems from induced magnetic fields measured by satellites in a multiscale framework. Scaling functions and wavelets are used to realize a multiscale analysis of the function spaces under consideration and to establish a multiscale regularization procedure for the inversion of the considered vectorial operator equation. Based on the knowledge of the singular system a regularization technique in terms of certain product kernels and corresponding convolutions can be formed. In order to reconstruct ionospheric current systems from satellite magnetic field data, an inversion of the Biot-Savart's law in terms of multiscale regularization is derived. The corresponding operator is formulated and the singular values are calculated. The method is tested on real magnetic field data of the satellite CHAMP and the proposed satellite mission SWARM.
Im Ausland zu studieren erfordert hohe Anpassungsleistungen kultureller, sozialer und psychischer Art. Viele Untersuchungsbefunde zeigen, dass soziale Unterstützung diesen Anpassungsprozess erleichtern und die Bewältigung psychischer Belastungen mindern kann. In der vorliegenden Studie wurden 96 ausländische und 171 inländische Studierende der Technischen Universität Kaiserslautern danach befragt, welche Art sozialer Unterstützung sie sich wünschen und inwieweit sie die erfahrene Unterstützung als angemessen erachten. Dazu wurden den Teilnehmern in einem Fragebogen drei potentiell belastende Studiensituationen geschildert: der Studienbeginn, Vorbereitung auf Prüfungen und das Erwägen eines Studienfachwechsels oder Studienortwechsels. Für jede dieser drei Situationen beurteilten die Befragten anhand standardisierter Aussagen, (a) welches Bewältigungsverhalten sie in dieser Situation anstrebten, (b) von welchen Personen bzw. Rollenträgern soziale Unterstützung hierfür gewünscht werde und (c) danach, welcher Art diese Unterstützung sein sollte. Die Ergebnisse zeigen, dass die ausländischen Studierenden diese Situationen sehr zielgerichtet und problemorientiert angehen. Sie bevorzugten sach- und studienfachbezogene Unterstützung gegenüber Unterstützung die auf die emotionale Bewältigung kritischer Situationen abzielt oft in stärkerem Maße als inländische Studierende. Dabei wünschen sich die ausländischen Befragten mehr Unterstützung durch Professoren, Assistenten und Fachschaftsangehörige als Hilfe von Freunden, Partnern oder Verwandten. Da ausländischen Studierenden soziale Unterstützung auch durch das Akademischen Auslandsamt zuteil wird, wurde auch erfragt, welche Dienstleistungsangebote des Auslandsamtes den Befragten bekannt sind bzw. welche sie schon einmal in Anspruch genommen haben. Die Ergebnisse erweitern die Grundlage für Entscheidungen über künftige Maßnahmen des Akademischen Auslandsamtes, diese Entscheidungen selbst sind jedoch nicht Bestandteil dieses Untersuchungsberichts.
In this paper, we discuss approaches related to the explicit modeling of human beings in software development processes. While in most older simulation models of software development processes, esp. those of the system dynamics type, humans are only represented as a labor pool, more recent models of the discrete-event simulation type require representations of individual humans. In that case, particularities regarding the person become more relevant. These individual effects are either considered as stochastic variations of productivity, or an explanation is sought based on individual characteristics, such as skills for instance. In this paper, we explore such possibilities by recurring to some basic results in psychology, sociology, and labor science. Various specific models for representing human effects in software process simulation are discussed.
We present a methodology to augment system safety step-by-step and illustrate the approach by the definition of reusable solutions for the detection of fail-silent nodes - a watchdog and a heartbeat. These solutions can be added to real-time system designs, to protect against certain types of system failures. We use SDL as a system design language for the development of distributed systems, including real-time systems.
The inverse problem of recovering the Earth's density distribution from data of the first or second derivative of the gravitational potential at satellite orbit height is discussed for a ball-shaped Earth. This problem is exponentially ill-posed. In this paper a multiscale regularization technique using scaling functions and wavelets constructed for the corresponding integro-differential equations is introduced and its numerical applications are discussed. In the numerical part the second radial derivative of the gravitational potential at 200 km orbitheight is calculated on a point grid out of the NASA/GSFC/NIMA Earth Geopotential Model (EGM96). Those simulated derived data out of SGG (satellite gravity gradiometry) satellite measurements are taken for convolutions with the introduced scaling functions yielding a multiresolution analysis of harmonic density variations in the Earth's crust. Moreover, the noise sensitivity of the regularization technique is analyzed numerically.
Many applications dealing with geometry acquisition and processing produce polygonal meshes that carry artifacts like discretization noise. While there are many approaches to remove the artifacts by smoothing or filtering the mesh, they are not tailored to any specific application subject to·certain restrictive objectives. We show how to incorporate smoothing schemes based on the general Laplacian approximation to satsify all those objectives at
the same time for the results of flow simulation in the application field of car manufacturing. In the presented application setting the major restrictions come from the bounding volume of the flow simulation, the so-called installation space. In particular, clean mesh regions (without noise) should not be smoothed while at the same time the installation space must not be violated by the smoothing of the noisy mesh regions. Additionally, aliasing effects at the boundary between clean and noisy mesh regions must be prevented. To address the fact that the meshes come from flow simulation, the presented method is versatile enough to preserve their exact volume and to apply anisotropic filters using the flow information.
Although the paper focuses on the results of a specific application, most of its findings can be transferred to different settings as well.
After a short introduction to the basic ideas of lattice Boltzmann methods and a brief description of a modern parallel computer, it is shown how lattice Boltzmann schemes are successfully applied for simulating fluid flow in microstructures and calculating material properties of porous media. It is explained how lattice Boltzmann schemes compute the gradient of the velocity field without numerical differentiation. This feature is then utilised for the simulation of pseudo-plastic fluids, and numerical results are presented for a simple benchmark problem as well as for the simulation of liquid composite moulding.
Iterative solution of large scale systems arising after discretization and linearization of the unsteady non-Newtonian Navier–Stokes equations is studied. cross WLF model is used to account for the non-Newtonian behavior of the fluid. Finite volume method is used to discretize the governing system of PDEs. Viscosity is treated explicitely (e.g., it is taken from the previous time step), while other terms are treated implicitly. Different preconditioners (block–diagonal, block–triangular, relaxed incomplete LU factorization, etc.) are used in conjunction with advanced iterative methods, namely, BiCGStab, CGS, GMRES. The action of the preconditioner in fact requires inverting different blocks. For this purpose, in addition to preconditioned BiCGStab, CGS, GMRES, we use also algebraic multigrid method (AMG). The performance of the iterative solvers is studied with respect to the number of unknowns, characteristic velocity in the basic flow, time step, deviation from Newtonian behavior, etc. Results from numerical experiments are presented and discussed.
Approximating illumination by point light sources, as done in many professional applications, suffers from the problem of the weak singularity: Numerical exceptions caused by the division by the squared distance between the point light source and the point to be illuminated must be avoided. Multiple importance sampling overcomes these problems by combining multiple sampling techniques by weights. Such a set of weights is called a heuristic. So far the estimators resulting from a heuristic only have been analyzed for variance. Since the cost of sampling is not at all constant for different sampling techniques, it is possible to find more efficient heuristics, even though they may hove higher variance. Based on our new stratification heuristic, we present a robust and unbiased global illumination algorithm. By numerical examples, we show that it is more efficient than previous heuristics. The algorithm is as simple as a path tracer, but elegantly avoids the problem of the weak singularity.