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Gesunde Kommune - Sport und Bewegung als Faktor der Stadt- und Raumentwicklung - Projektbericht 2011
(2012)
Sport und Bewegung sind seit jeher wesentliche Bestandteile des öffentlichen Lebens. Der in den letzten Jahren erkennbare und sich weiter verstärkende demographische und gesellschaftliche Wandel führt allerdings zu einer Veränderung des Sport- und Bewegungsverhaltens und damit auch der Nachfrage nach Sportstätten und Bewegungsräumen. Die sich zunehmend verändernde Situation von Sport und Bewegung findet bislang weder auf der politischen Ebene noch auf der Ebene der kommunalen Planung ausreichend Berücksichtigung. Vor dem Hintergrund stetig steigender Bedarfe zur Sicherung der kommunalen Daseinsvorsorge müssen jedoch zeitnah Lösungen gefunden werden, die den veränderten Rahmenbedingungen auch zukünftig gerecht werden. Ausgehend hiervon befasst sich das in den Jahren 2011 und 2012 durchgeführte Forschungs- und Entwicklungsprojekt „Gesunde Kommune – Sport und Bewegung als Faktor der Stadt- und Raumentwicklung“ mit der Bedeutung von Sport und Bewegung für die rheinland-pfälzischen Kommunen und verfolgt das Ziel, Verknüpfungen zwischen räumlichen und sportlichen Entwicklungsfeldern zu erschließen sowie Möglichkeiten zur gezielten Nutzung von Sport und Bewegung für die nachhaltige Raumentwicklung aufzuzeigen. Die raumwirksamen Leistungen von Sport und Bewegung werden hierbei unter den Aspekten Gesundheit, Ökonomie, Ökologie und Soziales betrachtet. Ein wesentliches Projektziel bildete darüber hinausgehend die Bewusstseinsbildung und Sensibilisierung aller relevanten Akteure auf Landes- und Kommunalebene. Das Projekt wurde Erarbeitet durch den Lehrstuhl Stadtplanung der TU Kaiserslautern in Kooperation mit dem Fachgebiet Sportwissenschaft der TU Kaiserslautern im Auftrag der Entwicklungsagentur Rheinland-Pfalz e.V..
Sport und Bewegung sind seit jeher wesentliche Bestandteile des öffentlichen Lebens. Der in den letzten Jahren erkennbare und sich weiter verstärkende demographische und gesellschaftliche Wandel führt allerdings zu einer Veränderung des Sport- und Bewegungsverhaltens und damit auch der Nachfrage nach Sportstätten und Bewegungsräumen. Die sich zunehmend verändernde Situation von Sport und Bewegung findet bislang weder auf der politischen Ebene noch auf der Ebene der kommunalen Planung ausreichend Berücksichtigung. Vor dem Hintergrund stetig steigender Bedarfe zur Sicherung der kommunalen Daseinsvorsorge müssen jedoch zeitnah Lösungen gefunden werden, die den veränderten Rahmenbedingungen auch zukünftig gerecht werden. Ausgehend hiervon befasst sich das in den Jahren 2011 und 2012 durchgeführte Forschungs- und Entwicklungsprojekt „Gesunde Kommune – Sport und Bewegung als Faktor der Stadt- und Raumentwicklung“ mit der Bedeutung von Sport und Bewegung für die rheinland-pfälzischen Kommunen und verfolgt das Ziel, Verknüpfungen zwischen räumlichen und sportlichen Entwicklungsfeldern zu erschließen sowie Möglichkeiten zur gezielten Nutzung von Sport und Bewegung für die nachhaltige Raumentwicklung aufzuzeigen. Die raumwirksamen Leistungen von Sport und Bewegung werden hierbei unter den Aspekten Gesundheit, Ökonomie, Ökologie und Soziales betrachtet. Ein wesentliches Projektziel bildete darüber hinausgehend die Bewusstseinsbildung und Sensibilisierung aller relevanten Akteure auf Landes- und Kommunalebene. Das Projekt wurde Erarbeitet durch den Lehrstuhl Stadtplanung der TU Kaiserslautern in Kooperation mit dem Fachgebiet Sportwissenschaft der TU Kaiserslautern im Auftrag der Entwicklungsagentur Rheinland-Pfalz e.V.. Die Dokumentation und Veröffentlichung erfolgte sowohl im Rahmen eines Projektberichts 2011 sowie eines Abschlussberichts 2012.
In the presented work, we make use of the strong reciprocity between kinematics and geometry to build a geometrically nonlinear, shearable low order discrete shell model of Cosserat type defined on triangular meshes, from which we deduce a rotation–free Kirchhoff type model with the triangle vertex positions as degrees of freedom. Both models behave physically plausible already on very coarse meshes, and show good
convergence properties on regular meshes. Moreover, from the theoretical side, this deduction provides a
common geometric framework for several existing models.
A simple transformation of the Equation of Motion (EoM) allows us to directly integrate nonlinear structural models into the recursive Multibody System (MBS) formalism of SIMPACK. This contribution describes how the integration is performed for a discrete Cosserat rod model which has been developed at the ITWM. As a practical example, the run-up of a simplified three-bladed wind turbine is studied where the dynamic deformations of the three blades are calculated by the Cosserat rod model.
We present the derivation of a simple viscous damping model of Kelvin–Voigt type for geometrically exact
Cosserat rods from three–dimensional continuum theory. Assuming a homogeneous and isotropic material,
we obtain explicit formulas for the damping parameters of the model in terms of the well known stiffness
parameters of the rod and the retardation time constants defined as the ratios of bulk and shear viscosities to
the respective elastic moduli. We briefly discuss the range of validity of our damping model and illustrate
its behaviour with a numerical example.
In this paper, we propose multi-level Monte Carlo(MLMC) methods that use ensemble level mixed multiscale methods in the simulations of multi-phase flow and transport. The main idea of ensemble level multiscale methods is to construct local multiscale basis functions that can be used for any member of the ensemble. We consider two types of ensemble level mixed multiscale finite element methods, (1) the no-local-solve-online ensemble level method (NLSO) and (2) the local-solve-online ensemble level method (LSO). Both mixed multiscale methods use a number of snapshots of the permeability media to generate a multiscale basis.
As a result, in the offline stage, we construct multiple basis functions for
each coarse region where basis functions correspond to different realizations.
In the no-local-solve-online ensemble level method one uses the whole set of pre-computed basis functions to approximate the solution for an arbitrary realization. In the local-solve-online ensemble level method one uses the pre-computed functions to construct a multiscale basis for a particular realization. With this basis the solution corresponding to this
particular realization is approximated in LSO mixed MsFEM. In both approaches
the accuracy of the method is related to the number of snapshots computed based on different realizations that one uses to pre-compute a
multiscale basis. We note that LSO approaches share similarities with reduced basis methods [11, 21, 22].
In multi-level Monte Carlo methods ([14, 13]), more accurate (and expensive) forward simulations are run with fewer samples while less accurate(and inexpensive) forward simulations are run with a larger number of samples. Selecting the number of expensive and inexpensive simulations carefully, one can show that MLMC methods can provide better accuracy
at the same cost as MC methods. In our simulations, our goal is twofold. First, we would like to compare NLSO and LSO mixed MsFEMs. In particular, we show that NLSO
mixed MsFEM is more accurate compared to LSO mixed MsFEM. Further, we use both approaches in the context of MLMC to speed-up MC
calculations. We present basic aspects of the algorithm and numerical
results for coupled flow and transport in heterogeneous porous media.
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.
One of the fundamental problems in computational structural biology is the prediction of RNA secondary structures from a single sequence. To solve this problem, mainly two different approaches have been used over the past decades: the free energy minimization (MFE) approach which is still considered the most popular and successful method and the competing stochastic context-free grammar (SCFG) approach. While the accuracy of the MFE based algorithms is limited by the quality of underlying thermodynamic models, the SCFG method abstracts from free energies and instead tries to learn about the structural behavior of the molecules by training the grammars on known real RNA structures, making it highly dependent on the availability of a rich high quality training set. However, due to the respective problems associated with both methods, new statistics based approaches towards RNA structure prediction have become increasingly appreciated. For instance, over the last years, several statistical sampling methods and clustering techniques have been invented that are based on the computation of partition functions (PFs) and base pair probabilities according to thermodynamic models. A corresponding SCFG based statistical sampling algorithm for RNA secondary structures has been studied just recently. Notably, this probabilistic method is capable of producing accurate (prediction) results, where its worst-case time and space requirements are equal to those of common RNA folding algorithms for single sequences.
The aim of this work is to present a comprehensive study on how enriching the underlying SCFG by additional information on the lengths of generated substructures (i.e. by incorporating length-dependencies into the SCFG based sampling algorithm, which is actually possible without significant losses in performance) affects the reliability of the induced RNA model and the accuracy of sampled secondary structures. As we will see, significant differences with respect to the overall quality of generated sample sets and the resulting predictive accuracy are typically implied. In principle, when considering the more specialized length-dependent SCFG model as basis for statistical sampling, a higher accuracy of predicted foldings can be reached at the price of a lower diversity of generated candidate structures (compared to the more general traditional SCFG variant or sampling based on PFs that rely on free energies).
Granular systems in solid-like state exhibit properties like stiffness
dependence on stress, dilatancy, yield or incremental non-linearity
that can be described within the continuum mechanical framework.
Different constitutive models have been proposed in the literature either based on relations between some components of the stress tensor or on a quasi-elastic description. After a brief description of these
models, the hyperelastic law recently proposed by Jiang and Liu [1]
will be investigated. In this framework, the stress-strain relation is
derived from an elastic strain energy density where the stable proper-
ties are linked to a Drucker-Prager yield criteria. Further, a numerical method based on the finite element discretization and Newton-
Raphson iterations is presented to solve the force balance equation.
The 2D numerical examples presented in this work show that the stress
distributions can be computed not only for triangular domains, as previoulsy done in the literature, but also for more complex geometries.
If the slope of the heap is greater than a critical value, numerical instabilities appear and no elastic solution can be found, as predicted by
the theory. As main result, the dependence of the material parameter
Xi on the maximum angle of repose is established.