417 research outputs found
A multigrid perspective on the parallel full approximation scheme in space and time
For the numerical solution of time-dependent partial differential equations,
time-parallel methods have recently shown to provide a promising way to extend
prevailing strong-scaling limits of numerical codes. One of the most complex
methods in this field is the "Parallel Full Approximation Scheme in Space and
Time" (PFASST). PFASST already shows promising results for many use cases and
many more is work in progress. However, a solid and reliable mathematical
foundation is still missing. We show that under certain assumptions the PFASST
algorithm can be conveniently and rigorously described as a multigrid-in-time
method. Following this equivalence, first steps towards a comprehensive
analysis of PFASST using block-wise local Fourier analysis are taken. The
theoretical results are applied to examples of diffusive and advective type
Laudatio: Alphabetisierung als Aufgabenfeld der Medienpädagogik
Laudatio zur Verleihung des Promotionspreises der Sektion Medienpädagogik in der Deutschen Gesellschaft für Erziehungswissenschaft am 21.9.2017 in Magdeburg. Koppel, Ilka. 2017. Entwicklung einer Online-Diagnostik für die Alphabetisierung. Eine Design-Based Research-Studie. Wiesbaden: Springer Fachmedien Wiesbaden. https://doi.org/10.1007/978-3-658-15769-2
All-electrical measurement of spin injection in a magnetic - junction diode
Magnetic - junction diodes are fabricated to investigate spin-polarized
electron transport. The injection of spin-polarized electrons in a
semiconductor is achieved by driving a current from a ferromagnetic injector
(Fe), into a bulk semiconductor (-GaAs) via schottky contact. For detection,
a diluted magnetic semiconductor (-GaMnAs) layer is used. Clear
magnetoresistance was observed only when a high forward bias was applied across
the - junction.Comment: 4 pages, 4 figure
The Skill Structure of the Export Wage Premium: Evidence from German Manufacturing
We find a significant export wage premium for higher-skilled workers and a significant export wage discount for lower-skilled workers, using a matched employer-employee data set for German manufacturing firms. Estimates suggest that up to one third of the overall skill premia is associated with exporting. These results imply that increasing trade contributes to widening wage inequality by skill level in manufacturing. But an increase in exports also diminishes wage discrimination due to gender or nationality. In this way, trade contributes to narrowing wage gaps and mitigates wage inequality in German manufacturing
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Numerical upscaling of parametric microstructures in a possibilistic uncertainty framework with tensor trains
A fuzzy arithmetic framework for the efficient possibilistic propagation of shape uncertainties based on a novel fuzzy edge detection method is introduced. The shape uncertainties stem from a blurred image that encodes the distribution of two phases in a composite material. The proposed framework employs computational homogenisation to upscale the shape uncertainty to a effective material with fuzzy material properties. For this, many samples of a linear elasticity problem have to be computed, which is significantly sped up by a highly accurate low-rank tensor surrogate. To ensure the continuity of the underlying mapping from shape parametrisation to the upscaled material behaviour, a diffeomorphism is constructed by generating an appropriate family of meshes via transformation of a reference mesh. The shape uncertainty is then propagated to measure the distance of the upscaled material to the isotropic and orthotropic material class. Finally, the fuzzy effective material is used to compute bounds for the average displacement of a non-homogenized material with uncertain star-shaped inclusion shapes
Low rank surrogates for polymorphic fields with application to fuzzy-stochastic partial differential equations
We consider a general form of fuzzy-stochastic PDEs depending on the interaction of probabilistic
and non-probabilistic ("possibilistic") influences. Such a combined modelling of aleatoric
and epistemic uncertainties for instance can be applied beneficially in an engineering context for
real-world applications, where probabilistic modelling and expert knowledge has to be accounted
for. We examine existence and well-definedness of polymorphic PDEs in appropriate function
spaces. The fuzzy-stochastic dependence is described in a high-dimensional parameter space,
thus easily leading to an exponential complexity in practical computations.
To aleviate this severe obstacle in practise, a compressed low-rank approximation of the problem
formulation and the solution is derived. This is based on the Hierarchical Tucker format which
is constructed with solution samples by a non-intrusive tensor reconstruction algorithm. The performance
of the proposed model order reduction approach is demonstrated with two examples.
One of these is the ubiquitous groundwater flow model with Karhunen-Loeve coefficient field
which is generalized by a fuzzy correlation length
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Low rank surrogates for polymorphic fields with application to fuzzy-stochastic partial differential equations
We consider a general form of fuzzy-stochastic PDEs depending on the interaction of probabilistic and non-probabilistic ("possibilistic") influences. Such a combined modelling of aleatoric and epistemic uncertainties for instance can be applied beneficially in an engineering context for real-world applications, where probabilistic modelling and expert knowledge has to be accounted for. We examine existence and well-definedness of polymorphic PDEs in appropriate function spaces. The fuzzy-stochastic dependence is described in a high-dimensional parameter space, thus easily leading to an exponential complexity in practical computations. To aleviate this severe obstacle in practise, a compressed low-rank approximation of the problem formulation and the solution is derived. This is based on the Hierarchical Tucker format which is constructed with solution samples by a non-intrusive tensor reconstruction algorithm. The performance of the proposed model order reduction approach is demonstrated with two examples. One of these is the ubiquitous groundwater flow model with Karhunen-Loeve coefficient field which is generalized by a fuzzy correlation length
The Contribution of Trade to Wage Inequality: The Role of Skill, Gender, and Nationality
International trade has been cited as a source of widening wage inequality in industrial nations. Consistent with this claim, we find a significant export wage premium for high-skilled workers in German manufacturing and an export wage discount for lower skilled workers, using matched employer-employee data. Estimates suggest that the export wage premium to high-skilled workers represents up to one third of their overall skill premium. But, while an increase in exports increases wage inequality along the dimension of skill, it diminishes the wage inequality associated with both gender and nationality. In this way, trade contributes to narrowing wage gaps and mitigating wage inequality in German manufacturing.
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