Publications (190)376.27 Total impact
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ABSTRACT: We consider asymptotic properties of two functionals on Euclidean shortestpath trees appearing in random geometric graphs in R2 which can be used, for example, as models for fixedaccess telecommunication networks. First, we determine the asymptotic bivariate distribution of the two backbone lengths inside a certain class of typical CoxVoronoi cells as the size of this cell grows unboundedly. The corresponding Voronoi tessellation is generated by a stationary Cox process which is concentrated on the edges of the random geometric graph and whose intensity tends to 0. The limiting random vector can be represented as a simple geometric functional of a decomposition of a typical PoissonVoronoi cell induced by an independent random sector. Using similar methods, we consider the asymptotic bivariate distribution of the total lengths of the two subtrees inside the CoxVoronoi cell.Statistics [?] Probability Letters 12/2015; 107:122130. DOI:10.1016/j.spl.2015.08.012 · 0.60 Impact Factor  [Show abstract] [Hide abstract]
ABSTRACT: The performance and durability of lithiumion batteries are highly dependent on the microstructures of their components. Recently, methods have been developed that make possible the simulation of electrochemical processes on 3D representations of lithiumion batteries. However, it is difficult to obtain realistic microstructures on which these simulations can be carried out. In this paper, we develop a stochastic model that is able to produce realistic microstructures of lithiumion battery anodes, which can serve as input for the simulations. We introduce the use of Gaussian random fields on the sphere as models for the particles that form the anodes. Using this new approach, we are able to model realistic particle geometries. The stochastic model also uses a number of techniques from stochastic geometry and spatial statistics. We carry out validation of our model, in order to demonstrate that it realistically describes the key features of the anode’s microstructure.Computational Materials Science 11/2015; 109:137  146. DOI:10.1016/j.commatsci.2015.06.025 · 2.13 Impact Factor  [Show abstract] [Hide abstract]
ABSTRACT: A strategy to mitigate typical reconstruction artefacts in missing wedge computed tomography is presented. These artefacts appear as elongations of reconstructed details along the mean direction (i.e. the symmetry centre of the projections). Although absent in standard computed tomography applications, they are most prominent in advanced electron tomography and also in special topics of Xray and neutron tomography under restricted geometric boundary conditions. We investigate the performance of the DIRECTT (Direct Iterative Reconstruction of Computed Tomography Trajectories) algorithm to reduce the directional artefacts in standard procedures. In order to be sensitive to the anisotropic nature of missing wedge artefacts, we investigate isotropic substructures of metal foam as well as circular disc models. Comparison is drawn to filtered backprojection and algebraic techniques. Reference is made to reconstructions of complete data sets. For the purpose of assessing the reconstruction quality, Fourier transforms are employed to visualize the missing wedge directly. Deficient reconstructions of disc models are evaluated by a lengthweighted kernel density estimation, which yields the probabilities of boundary orientations. The DIRECTT results are assessed at different signaltonoise ratios by means of local and integral evaluation parameters.Journal of Microscopy 09/2015; DOI:10.1111/jmi.12313 · 2.33 Impact Factor 
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ABSTRACT: As the Cordilleran and Laurentide Ice Sheets retreated, North America was colonized by human populations; however, the spatial patterns of subsequent population growth are unclear. Temporal frequency distributions of aggregated radiocarbon ((14)C) dates are used as a proxy of population size and can be used to track this expansion. The Canadian Archaeological Radiocarbon Database contains more than 35,000 (14)C dates and is used in this study to map the spatiotemporal demographic changes of Holocene populations in North America at a continental scale for the past 13,000 y. We use the kernel method, which converts the spatial distribution of (14)C dates into estimates of population density at 500y intervals. The resulting maps reveal temporally distinct, dynamic patterns associated with paleodemographic trends that correspond well to genetic, archaeological, and ethnohistoric evidence of human occupation. These results have implications for hypothesizing and testing migration routes into and across North America as well as the relative influence of North American populations on the evolution of the North American ecosystem.Proceedings of the National Academy of Sciences 09/2015; 112(39). DOI:10.1073/pnas.1505657112 · 9.67 Impact Factor 
Article: Stochastic 3D modeling of Ostwald ripening at ultrahigh volume fractions of the coarsening phase
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ABSTRACT: We present a (dynamic) stochastic simulation model for 3D grain morphologies undergoing a grain coarsening phenomenon known as Ostwald ripening. For low volume fractions of the coarsening phase, the classical LSW theory predicts a powerlaw evolution of the mean particle size and convergence toward selfsimilarity of the particle size distribution; experiments suggest that this behavior holds also for high volume fractions. In the present work, we have analyzed 3D images that were recorded in situ over time in semisolid Al–Cu alloys manifesting ultrahigh volume fractions of the coarsening (solid) phase. Using this information we developed a stochastic simulation model for the 3D morphology of the coarsening grains at arbitrary time steps. Our stochastic model is based on random Laguerre tessellations and is by definition selfsimilar—i.e. it depends only on the mean particle diameter, which in turn can be estimated at each point in time. For a given mean diameter, the stochastic model requires only three additional scalar parameters, which influence the distribution of particle sizes and their shapes. An evaluation shows that even with this minimal information the stochastic model yields an excellent representation of the statistical properties of the experimental data.Modelling and Simulation in Materials Science and Engineering 09/2015; 23(6). DOI:10.1088/09650393/23/6/065001 · 2.17 Impact Factor  [Show abstract] [Hide abstract]
ABSTRACT: Many important properties of particulate materials are heavily influenced by the size and shape of the constituent particles. Thus, in order to control and improve product quality, it is important to develop a good understanding of the shape and size of the particles that make up a given particulate material. In this paper, we show how the spherical harmonics expansion can be used to approximate particles obtained from tomographic 3D images. This yields an analytic representation of the particles which can be used to calculate structural characteristics. We present an estimation method for the optimal length of expansion depending on individual particle shapes, based on statistical hypothesis testing. A suitable choice of this parameter leads to a smooth approximation that preserves the main shape features of the original particle. To show the wide applicability of this procedure, we use it to approximate particles obtained from two different tomographic 3D datasets of particulate materials. The first one describes an anode material from lithiumion cells that consists of spherelike particles with different sizes. The second dataset describes a powder of highly nonspherical titanium dioxide particles.Materials Characterization 08/2015; 106. DOI:10.1016/j.matchar.2015.05.023 · 1.85 Impact Factor  [Show abstract] [Hide abstract]
ABSTRACT: The analysis of polycrystalline materials benefits greatly from accurate quantitative descriptions of their grain structures. Laguerre tessellations approximate such grain structures very well. However, it is a quite challenging problem to fit a Laguerre tessellation to tomographic data, as a highdimensional optimization problem with many local minima must be solved. In this paper, we formulate a version of this optimization problem that can be solved quickly using the crossentropy method, a robust stochastic optimization technique that can avoid becoming trapped in local minima. We demonstrate the effectiveness of our approach by applying it to both artificially generated and experimentally produced tomographic data.  [Show abstract] [Hide abstract]
ABSTRACT: Keywords: cermet; degradation; microstructure; tomography; conductivity; solid oxide fuel cells; NiYSZ; redox cycling This study investigates the influence of microstructure on the effective ionic and electrical conductivities of NiYSZ (yttriastabilized zirconia) anodes. Fine, medium, and coarse microstructures are exposed to redox cycling at 950 °C. FIB (focused ion beam)tomography and image analysis are used to quantify the effective (connected) volume fraction (Φeff), constriction factor (β), and tortuosity (τ). The effective conductivity (σeff) is described as the product of intrinsic conductivity (σ0) and the socalled microstructurefactor (M): σeff = σ0 × M. Two different methods are used to evaluate the Mfactor: (1) by prediction using a recently established relationship, Mpred = εβ0.36/τ5.17, and (2) by numerical simulation that provides conductivity, from which the simulated Mfactor can be deduced (Msim). Both methods give complementary and consistent information about the effective transport properties and the redox degradation mechanism. The initial microstructure has a strong influence on effective conductivities and their degradation. Finer anodes have higher initial conductivities but undergo more intensive Ni coarsening. Coarser anodes have a more stable Ni phase but exhibit lower YSZ stability due to lower sintering activity. Consequently, in order to improve redox stability, it is proposed to use mixtures of fine and coarse powders in different proportions for functional anode and current collector layers.Materials 08/2015; 8(9):5554. DOI:10.3390/ma8095265 · 2.65 Impact Factor  [Show abstract] [Hide abstract]
ABSTRACT: Mechanical stressstrain curves are estimated by means of numerical simulation in order to analyze and compare the mechanical properties of a real Strontiummodified AlSi alloy with virtually designed materials. The virtual materials are generated by a competitive stochastic growth model of the 3D corallike morphology of the eutectic Si in AlSi alloys. The experimental data for the real material was acquired using FEB/SEM tomography. The numerical simulations are based on finite element methods. The effects of coarsening the mesh size and using different degrees of the finite elements are discussed. The simulations show that there is high conformity between the mechanical properties of the real and virtual materials. Experiments are also performed to show that the mechanical behavior of the realizations of the stochastic model is sensitive to changes in the parameters that control the morphological characteristics of the Si component.Archive of Applied Mechanics 08/2015; 85(8). DOI:10.1007/s0041901409565 · 1.11 Impact Factor 
Article: Stationary Apollonian Packings
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ABSTRACT: The notion of stationary Apollonian packings in the ddimensional Euclidean space is introduced as a mathematical formalization of socalled random Apollonian packings and rotational random Apollonian packings, which constitute popular grain packing models in physics. Apart from dealing with issues of existence and uniqueness in the entire Euclidean space, asymptotic results are provided for the growth durations and it is shown that the packing is spacefilling with probability 1, in the sense that the Lebesgue measure of its complement is zero. Finally, the phenomenon is studied that grains arrange in clusters and properties related to percolation are investigated.Journal of Statistical Physics 07/2015; 161(1). DOI:10.1007/s1095501513266 · 1.20 Impact Factor  [Show abstract] [Hide abstract]
ABSTRACT: Three different electrode morphologies are generated from three different starting powders, spheres representing nonaggregated powders, agglomerates of spheres and high aspect ratio cylinders modelling splats formed in plasma sprays. Electrodes from each morphology are analysed using finite volumes to predict the effective transport coefficients, the triple phase boundary length and the performance of the electrode. The same structures are also analysed using morphological characterization which can be much more efficient. It was found that high aspect ratio base particles are favourable, and that constrictivity correlates best with the finite volume transport calculations.ECS Transactions 07/2015; 68(1):20372045. DOI:10.1149/06801.2037ecst  [Show abstract] [Hide abstract]
ABSTRACT: Lithium/sulphur batteries are promising candidates for future energy storage systems, mainly due to their high potential capacity. However low sulphur utilization and capacity fading hinder practical realizations. In order to improve understanding of the system, we investigate Li/S electrode morphology changes for different ageing steps, using Xray phase contrast tomography. Thereby we find a strong decrease of sulphur loading after the first cycle, and a constant loading of about 15% of the initial loading afterwards. While cycling, the mean sulphur particle diameters decrease in a qualitatively similar fashion as the discharge capacity fades. The particles spread, migrate into the current collector and accumulate in the upper part again. Simultaneously sulphur particles lose contact area with the conducting network but regain it after ten cycles because their decreasing size results in higher surface areas. Since the capacity still decreases, this regain could be associated with effects such as surfScientific Reports 06/2015; 5. DOI:10.1038/srep10921 · 5.58 Impact Factor 
Article: First passage percolation on random geometric graphs and an application to shortestpath trees
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ABSTRACT: We consider Euclidean first passage percolation on a large family of connected random geometric graphs in the ddimensional Euclidean space encompassing various wellknown models from stochastic geometry. In particular, we establish a strong linear growth property for shortestpath lengths on random geometric graphs which are generated by point processes. We consider the event that the growth of shortestpath lengths between two (end) points of the path does not admit a linear upper bound. Our linear growth property implies that the probability of this event tends to zero subexponentially fast if the direct (Euclidean) distance between the endpoints tends to infinity. Besides, for a wide class of stationary and isotropic random geometric graphs, our linear growth property implies a shape theorem for the Euclidean first passage model defined by such random geometric graphs. Finally, this shape theorem can be used to investigate a problem which is considered in structural analysis of fixedaccess telecommunication networks, where we determine the limiting distribution of the length of the longest branch in the shortestpath tree extracted from a typical segment system if the intensity of network stations converges to 0.Advances in Applied Probability 06/2015; 47(2):328354. DOI:10.1239/aap/1435236978 · 0.71 Impact Factor  [Show abstract] [Hide abstract]
ABSTRACT: A parametric stochastic model of the morphology of thin polymer:fullerene films is developed. This model uses a number of tools from stochastic geometry and spatial statistics. The fullerenerich phase is represented by random closed sets and the polymerrich phase is given by their complement. The model has three stages. First, a point pattern is used to model the locations of fullerenerich domains. Second, domains are formed at these points. Third, the domains are rearranged to ensure a realistic configuration. The model is fitted to polymer:fullerene films produced using seven different spin coating velocities and validated using a variety of morphological characteristics. The model is then used to simulate morphologies corresponding to spin velocities for which no empirical data exists. The viability of this approach is demonstrated using crossvalidation.Modelling and Simulation in Materials Science and Engineering 06/2015; 23(4):045003. DOI:10.1088/09650393/23/4/045003 · 2.17 Impact Factor 
Article: A probabilistic approach to the prediction of area weather events, applied to precipitation
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ABSTRACT: In meteorology it is important to compute the probabilities of certain weather events occurring. There are a number of numerical and statistical methods for estimating the probability that a weather event occurs at a fixed location (a point). However, there are no widely applicable techniques for estimating the probability of such an event occurring in a geographical region (an area). In this paper, we propose a modelbased approach for the computation of area probabilities using point probabilities. We develop this approach in the context of estimating the probability of the meteorological event ‘occurrence of precipitation’. We treat the point and area probabilities as coverage probabilities of a germ–grain model, where the grains can roughly be interpreted as precipitation cells. The germ–grain model is completely characterized by a sequence of local intensities and a grain size. We compute these model characteristics using available point probabilities. A nonnegative leastsquares approach is used to determine the local intensities and a semivariogram estimation technique is used to find the grain size. We are then able to determine area probabilities either analytically or by repeated simulation of the germ–grain model. We validate our model, using radar observations to assess the precision of the computed probabilities.Spatial Statistics 05/2015; 12. DOI:10.1016/j.spasta.2015.01.002 · 1.61 Impact Factor  [Show abstract] [Hide abstract]
ABSTRACT: The internal microstructure of agglomerates has a great influence on their stability and breakage characteristics. Therefore, to optimize production processes and to improve characteristics of the final product, it is very important to understand dependencies between structural and mechanical properties of agglomerates. In this paper, we discuss usage of the discrete element method (DEM) for understanding the breakage behavior of spherical agglomerates under uniaxial compression depending on their microstructure. A flexible stochastic model has been developed to generate agglomerates with various types of microstructures. As an example, we investigate the effect of the primary particle size distribution on agglomerate strength and breakage behavior. In particular, the size distribution of primary particles is specified by a mixing of two fixed particle sizes. The model construction ensures that the size and mass of agglomerates as well as primary particles and binder content remain constant in all experiments. From the obtained results it can be seen that the breakage behavior of agglomerates is influenced in different ways. Breakage energy and the maximum force applied before the primary break depend on the mixing ratio and the variability inside the microstructure. On the other hand, the size of fragments is very similar for all mixing ratios.Advanced Powder Technology 04/2015; 26(3). DOI:10.1016/j.apt.2015.04.011 · 2.64 Impact Factor  [Show abstract] [Hide abstract]
ABSTRACT: We provide a parametric modeling approach suitable for various kinds of hierarchical networks based on random geometric graphs. In these networks, we have two kinds of components, socalled highlevel components (HLC) and lowlevel components (LLC). Each HLC is associated with a serving zone and all LLC within this area are connected to the corresponding HLC. Socalled sparse LLC networks, where only a few LLC occur in the typical serving zone, are a nonnegligible subdomain when investigating hierarchical networks. Therefore, we supply distributional results for structural characteristics where two LLC are independently and uniformly distributed along the segment system of the typical serving zone. In particular, we are interested in the joint distribution of three quantities, namely the length of the joint part of the shortest paths from the LLC to the HLC as well as the lengths of the corresponding disjoint remaining parts. In order to provide a parametric, threedimensional distribution function for these random variables, we utilize a pseudomaximum likelihood approach. More precisely, we fit parametric approximation formulas to the marginal density functions as well as parametric copula functions that match with the observed correlation structure. We also provide an asymptotic result for the joint distribution of the connection lengths as the size of the typical cell increases unboundedly. This general modeling approach is explicitly explained for the case that the random geometric graph is formed by the edges of random tessellations.Stochastic Models 04/2015; 31(2). DOI:10.1080/15326349.2014.999285 · 0.46 Impact Factor  [Show abstract] [Hide abstract]
ABSTRACT: We present an experimental approach to study the threedimensional microstructure of gas diffusion layer (GDL) materials under realistic compression conditions. A dedicated compression device was designed that allows for synchrotrontomographic investigation of circular samples under welldefined compression conditions. The tomographic data provide the experimental basis for stochastic modeling of nonwoven GDL materials. A plain compression tool is used to study the fiber courses in the material at different compression stages. Transport relevant geometrical parameters, such as porosity, pore size, and tortuosity distributions, are exemplarily evaluated for a GDL sample in the uncompressed state and for a compression of 30 vol.%. To mimic the geometry of the flowfield, we employed a compression punch with an integrated channelribprofile. It turned out that the GDL material is homogeneously compressed under the ribs, however, much less compressed underneath the channel. GDL fibers extend far into the channel volume where they might interfere with the convective gas transport and the removal of liquid water from the cell.The Review of scientific instruments 04/2015; 86(4):043702. DOI:10.1063/1.4918291 · 1.61 Impact Factor  [Show abstract] [Hide abstract]
ABSTRACT: A novel approach for the marking of deposited lithium on graphite anodes from large automotive lithiumion cells (≥6 Ah) is presented. Graphite anode samples were extracted from two different formats (cylindrical and pouch cells) of pristine and differently aged lithiumion cells. The samples present a variety of anodes with various states of lithium deposition (also known as plating). A chemical modification was performed to metallic lithium deposited on the anode surface due to previous plating with isopropanol (IPA). After this procedure an oxygenated species was detected by scanning electron microscopy (SEM), which later was confirmed as Li2 CO3 by Fourier transform infrared spectroscopy (FTIR) and Xray powder diffraction (XRPD). A valuation of the covered area by Li2 CO3 was carried out with an image analysis using energydispersive Xray spectroscopy (EDX) and quantitative Rietveld refinement. © 2015 WILEYVCH Verlag GmbH & Co. KGaA, Weinheim.Chemistry  A European Journal 03/2015; 21(16). DOI:10.1002/chem.201406606 · 5.73 Impact Factor
Publication Stats
2k  Citations  
376.27  Total Impact Points  
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Institutions

19962015

Universität Ulm
 Institute of Stochastics
Ulm, BadenWürttemberg, Germany


2009

Orange Labs
RhôneAlpes, France
