Efficient numerical methods for the large‐scale,parallel solution of elastoplastic contact problems

Quasi‐static elastoplastic contact problems are ubiquitous in many industrial processes and other contexts, and their numerical simulation is consequently of great interest in accurately describing and optimizing production processes. The key component in these simulations is the solution of a single load step of a time iteration. From a mathematical perspective, the problems to be solved in each time step are characterized by the difficulties of variational inequalities for both the plastic behavior and the contact problem. Computationally, they also often lead to very large problems. In this paper, we present and evaluate a complete set of methods that are (1) designed to work well together and (2) allow for the efficient solution of such problems. In particular, we use adaptive finite element meshes with linear and quadratic elements, a Newton linearization of the plasticity, active set methods for the contact problem, and multigrid‐preconditioned linear solvers. Through a sequence of numerical experiments, we show the performance of these methods. This includes highly accurate solutions of a three‐dimensional benchmark problem and scaling our methods in parallel to 1024 cores and more than a billion unknowns. Copyright © 2015 John Wiley & Sons, Ltd.     

Validation of the Climate-SAF surface broadband albedo product: Comparisons with in situ observations over Greenland and the ice-covered Arctic Ocean

This paper describes a validation study performed by comparing the Climate-SAF Surface Albedo Product (SAL) to ground truth observations over Greenland and the ice-covered Arctic Ocean. We compare Advanced Very High Resolution Radiometer (AVHRR)-based albedo retrievals to data from the Greenland Climate Network (GCN) weather stations and the floating ice station Tara for polar summer 2007. The AVHRR dataset consists of 2755 overpasses. The overpasses are matched to in situ observations spatially and temporally. The SAL algorithm presented here derives the surface broadband albedo from AVHRR channels 1 and 2 using an atmospheric correction, temporal sampling of an empirical Bidirectional Reflectance Distribution Function (BRDF), and a narrow-to-broadband conversion algorithm. The satellite product contains algorithms for snow, sea ice, vegetation, bare soil, and water albedo. At the Summit and DYE-2 stations on the Greenland ice sheet, instantaneous SAL RMSE is 0.073. The heterogeneous surface conditions at satellite pixel scale over the stations near the Greenland west coast increase RMSE to > 0.12. Over Tara, the instantaneous SAL RMSE is 0.069. The BRDF sampling approach reduces RMSE over the ice sheet to 0.053, and to 0.045 over Tara. Taking into account various sources of uncertainty for both satellite retrievals and in situ observations, we conclude that SAL agrees with in situ observations within their limits of accuracy and spatial representativeness.     

Flexible multibody approach in forward dynamic simulation of locomotive strains in human skeleton with flexible lower body bones

A method for bone strain estimation is examined in this article. The flexibility of a single bone in an otherwise rigid human skeleton model has been studied previously by various authors. However, in the previous studies, the effect of the flexibility of multiple bones on the musculoskeletal model behavior was ignored. This study describes a simulation method that can be used to estimate the bone strains at both tibias and femurs of a 65-year-old Caucasian male subject. The verification of the method is performed by the comparison of the results with other studies available in literature. The results of the study show good correlation with the results of previous empirical studies. A damping effect of the flexible bones on the model is also studied in this paper.     

Die Rolle der Informatik im gesellschaftlichen Diskurs: Eine Neupositionierung der Informatik

Zusammenfassung  Entwicklungen im Bereich der Informations- und Kommunikationstechnologie führen derzeit zu fundamentalen Umw?lzungen der Gesellschaft. Eine Beschleunigung des Lebens und das Verschwimmen von Beruf und Privatleben sind nur zwei Beispiele hierfür. Ein Abweichen von dem gesellschaftlichen Ideal des mobilen, jungen und dynamischen Mitarbeiters erweist sich h?ufig als Weg in das Einsiedlerdasein eines Exoten. Ein Widerstreben gegen die wachsenden Begehrlichkeiten von Wirtschaft und Staat l?sst das Individuum verd?chtig erscheinen und kann zu einer weiteren Entkopplung aus der Gesellschaft führen. Eine entscheidende Aufgabe bei gesellschaftlichen Umw?lzungen ist die der Reflexion und Kritik. Diese Rolle scheint mehr und mehr den Juristen zuzukommen. Insbesondere beim Thema Datenschutz erfolgt h?ufig eine Reduktion auf die Verfassungskonformit?t einzelner staatlicher Ma?nahmen. Kritik sollte jedoch bereits weit früher geübt werden. Medien sollten diese zentrale Funktion unterstützen und der politische Diskurs sollte zu einer optimalen L?sung führen. Eine Gruppe, die in der Debatte viel beitragen k?nnte und müsste, wird h?ufig, wenn überhaupt, aufgrund ihres technischen Sachverstandes herangezogen – die Informatiker. Dies ist insbesondere verwunderlich, da Informatiker ma?geblich an der Ver?nderung der Gesellschaft beteiligt sind. Sie schaffen die technischen Grundlagen für neue Formen der Interaktion. Doch das daraus resultierende Bild der Informatik als Computerwissenschaft beraubt Informatiker ihrer gesellschaftskritischen Funktion, da sie auf die Rolle von Technikern reduziert werden. Eine Positionierung und Darstellung der Informatik als Struktur- und Koordinationswissenschaft sowie der Informatiker als interdisziplin?re Systementwickler und -analytiker würde es Informatikern erm?glichen die bedeutende Rolle der Gesellschaftskritiker einzunehmen und geh?rt zu werden.     

Toward large-scale Hybrid Monte Carlo simulations of the Hubbard model on graphics processing units

One of the most efficient non-perturbative methods for the calculation of thermal properties of quantum systems is the Hybrid Monte Carlo algorithm, as evidenced by its use in large-scale lattice quantum chromodynamics calculations. The performance of this algorithm is determined by the speed at which the fermion operator is applied to a given vector, as it is the central operation in the preconditioned conjugate gradient iteration. We study a simple implementation of these operations for the fermion matrix of the Hubbard model in d+1 spacetime dimensions, and report a performance comparison between a 2.66 GHz Intel Xeon E5430 CPU and an NVIDIA Tesla C1060 GPU using double-precision arithmetic. We find speedup factors ranging between 30 and 350 for d=1, and in excess of 40 for d=3. We argue that such speedups are of considerable impact for large-scale simulational studies of quantum many-body systems.     

Using results of eye movement signal analysis in the neural network recognition of otoneurological patients

We extracted a collection of eye movement signals employed for almost two decades in clinical otoneurological tests at a balance laboratory. During those years we designed and programmed signal analysis methods to analyse their features in detail and to compute medically important attributes. In the present study, using such attributes and their results computed we classified test cases into groups of healthy subjects and patients with multilayer perceptron neural networks. Classification succeeded in total accuracies from 60% to 90% depending on the type of eye movements, which were saccades, nystagmus, sinusoidal movements and vestibulo-ocular reflex stimulated in two different ways; these are the chief eye movement tests applied in otoneurology.     

Bridging the physical and virtual worlds by local connectivity-based physical selection

The prevalent visions of ambient intelligence emphasise natural interaction between user and functions and services embedded in the environment or available through mobile devices. In these scenarios the physical and virtual worlds seamlessly gear into each other, making crossing the border between these worlds natural or even invisible to the user. The bottleneck in reaching these scenarios appear in the natural mapping between the physical objects and their virtual counterparts. The emergence of local connectivity in mobile devices opens possibilities for implementing novel user interface paradigms to enhance this mapping. We present physical selection paradigm for implementing an intuitive human technology interaction for mobile devices. In order to demonstrate the feasibility of the paradigm we implemented two experimental set-ups using commercially available smart phones with IrDA connectivity. The experiments involved selecting a website by physically pointing at its symbol and making a phone call by pointing at an icon representing the person to be called. In tentative user experiments the physical selection method was more time-efficient and it was perceived more positively by the users than a conventional method.

Exploring US Business Cycles with Bivariate Loops Using Penalized Spline Regression

The phrase business cycle is usually used for short term fluctuations in macroeconomic time series. In this paper we focus on the estimation of business cycles in a bivariate manner by fitting two series simultaneously. The underlying model is thereby nonparametric in that no functional form is prespecified but smoothness of the functions are assumed. The functions are then estimated using penalized spline estimation. The bivariate approach will allow to compare business cycles, check and compare phase lengths and visualize this in forms of loops in a bivariate way. Moreover, the focus is on separation of long and short phase fluctuation, where only the latter is the classical business cycle while the first is better known as Friedman or Goodwin cycle, respectively. Again, we use nonparametric models and fit the functional shape with penalized splines. For the separation of long and short phase components we employ an Akaike criterion.