bluuebunny/crossref_metadata_2025_split huggingface dataset:
On the mechanical modeling of cell components
Authors: Klinge Sandra , Wiegold Tillmann , Aygün Serhat , Gilbert Robert P. , Holzapfel Gerhard A. 
Published: January 2021

AbstractEukaryotic cells are complex systems which carry out a variety of different tasks. The current contribution gives insight into the modeling of some of their vital components and represents an overview of results achieved within the international D‐A‐CH project on computational modeling of transport processes in a cell. The first part of the contribution studies viscoelastic effects of cross‐linked actin network embedded in cytosol. The basic‐model is used to simulate the actin behavior at a microscopic level. It considers the influence of the physical length, the end‐to‐end distance and the stretch modulus in order to provide a relationship between the stretch of a single polymer chain and the applied tension force. The effective behavior of the cell cytoplasm is simulated by using the multiscale finite element method. Here, a standard large strain viscous approach is applied for the cytosol, while the generalized Maxwell model simulates viscous effects occurring in filaments due to deviatoric changes. The examples dealing with combinations of tension‐holding tests give insight into the effective behavior of the cytoplasm.The second part of the talk deals with the viral entry into a cell driven by the receptor motion. In the model developed, the receptor motion is described by the diffusion equation along with two boundary conditions. The first condition represents the balance of fluxes at the front of the contact area. To this end, the velocity is assumed to be proportional to the gradient of the chemical potential. The second condition deals with the energy balance and postulates that the difference in the energy behind and before the front causes the front's movement. The important energy contributions are energy due to the binding of receptors, the free energy of the membrane, the bending energy and the kinetic energy due to the motion of the receptors. The model yields a well‐posed moving boundary problem, which is numerically solved using the finite difference method. The change of receptor density over the membrane as well as the motion of the front of the adhesion zone is studied in the numerical simulations.
Iterative Sparse FFT for M‐sparse Vectors: Deterministic versus Random Sampling
Authors: Plonka Gerlind , von Wulffen Therese 
Published: January 2021

AbstractIn a recent paper [3] we have proposed a deterministic stable sparse FFT algorithm for M‐sparse vectors of length N = 2J with runtime 𝒪(M2 log2N) which generalizes the approach in [2]. Our method is based on a divide‐and‐conquer technique and requires to solve an equation system of Vandermonde type at each iteration step. To ensure numerical stability of the algorithm, the number of rows of the employed Vandermonde matrices at each step has been chosen adaptively in [3]. In this paper, we compare the results of [3] with a random sampling approach for determining the rows of the coefficient matrix.
Parametric Study on Ridges Inducing Secondary Motions in Turbulent Channel Flow
Authors: von Deyn Lars H. , Gatti Davide , Frohnapfel Bettina , Stroh Alexander 
Published: January 2021

AbstractA DNS parametric study of streamwise‐aligned rectangular ridges is carried out in a fully developed turbulent channel flow with constant flow rate at Reb = 18000. The simulations were carried out systematically varying the ridge height h, width w and structural wavelength S. The ridges generate a strong large‐scale secondary motion, which is measured in terms of the integral swirl strength. Of the presented cases, the configuration with the ridge height h = 0.1 δ, S/w = 4, S = 1 δ produces the strongest secondary flow of 4.5% Ub. The varying flow topology is discussed as a result of the varying ridge dimensions.
Stable Inversion for Flexible Multibody Systems Using the ANCF
Authors: Drücker Svenja , Seifried Robert 
Published: January 2021

AbstractFlexible robots are often non‐minimum phase systems. Thus, their inverse model must be computed by stable inversion. Here, a simplification to the stable inversion process is proposed, which enables its application to complex underactuated multibody systems. As an example, a flexible manipulator modeled by the absolute nodal coordinate formulation is considered.
Modelling shear wave propagation in soft tissue surrogates using a finite element‐ and finite difference method
Authors: Ohlsen Jakob , Neidhardt Maximilian , Schlaefer Alexander , Hoffmann Norbert 
Published: January 2021

AbstractShear Wave Elasticity Imaging (SWEI) has become a popular medical imaging technique [1] in which soft tissue is excited by the acoustic radiation forces of a focused ultrasonic beam. Tissue stiffness can then be derived from measurements of shear wave propagation speeds [2]. The main objective of this work is a comparison of a finite element (FEM) and a finite difference method (FDM) in terms of their computational efficiency when modeling shear wave propagation in tissue phantoms. Moreover, the propagation of shear waves is examined in experiments with ballistic gelatin to assess the simulation results. In comparison to the FEM the investigated FDM proves to be significantly more performant for this computing task.
Efficient mortar‐based algorithms for embedding 1D fibers into 3D volumes
Authors: Steinbrecher Ivo , Popp Alexander 
Published: January 2021

AbstractMany composite materials are based on 1D fibers being embedded into 3D solid volumes, e.g. carbon‐fiber reinforced plastics in aerospace engineering or fiber‐reinforced concrete in civil engineering to name only two prominent examples. The present contribution highlights the most important numerical methods and algorithmic building blocks for an efficient analysis of such systems based on cutting‐edge finite element formulations for nonlinear beams and a novel beam‐to‐solid volume coupling approach inspired by classical mortar methods. A particular emphasis is put on the efficient parallel implementation for large‐scale simulations, which includes suitable procedures for domain partitioning and geometry‐based search.
Unsupervised Data Labeling on Graphs by Self‐Assignment Flows
Authors: Zisler Matthias , Zern Artjom , Boll Bastian , Petra Stefania , Schnörr Christoph 
Published: January 2021

AbstractThis paper extends the recently introduced assignment flow approach for supervised image labeling to unsupervised scenarios where no labels are given. The resulting self‐assignment flow takes a pairwise data affinity matrix as input data and maximizes the correlation with a low‐rank matrix that is parametrized by the variables of the assignment flow, which entails an assignment of the data to themselves through the formation of latent labels (feature prototypes). A single user parameter, the neighborhood size for the geometric regularization of assignments, drives the entire process. By smooth geodesic interpolation between different normalizations of self‐assignment matrices on the positive definite matrix manifold, a one‐parameter family of self‐assignment flows is defined. Accordingly, our approach can be characterized from different viewpoints, e.g. as performing spatially regularized, rank‐constrained discrete optimal transport, or as computing spatially regularized normalized spectral cuts. Regarding combinatorial optimization, our approach successfully determines completely positive factorizations of self‐assignments in large‐scale scenarios, subject to spatial regularization. Various experiments including the unsupervised learning of patch dictionaries using a locally invariant distance function, illustrate the properties of the approach.
Reverse Engineering: Investigation of Optimization Techniques in Point Clouds Registration
Authors: Yacout George , Shoukry Mohamed Kamal 
Published: January 2021

AbstractThe Reverse Engineering industries has an increasing need for remanufacturing of worn out spare parts or spare parts with lost technical data like drawings or CAD models, in this project a new hybrid algorithm is proposed for the rigid registration of point clouds obtained from scanning of spare parts by a laser scanner. The hybrid algorithm is dividing the registration process into two stages called the coarse and fine registration, the coarse registration is performed by the Genetic Algorithm (GA) that yield an approximate transformation between the two point clouds, and then inherit its findings to the fine registration that is performed by the Interior Point method to reach the accurate transformation and the successful registration of the two point clouds. In this research two techniques for point clouds registration are applied, tested, evaluated and compared to each other. It was found that using the GA and Interior point method is a good alternative for registering point clouds. The objective of this work is to register two point clouds successfully with minimum error, and high reliability.
Kinematic Flexibility Analysis of Active and Inactive Kinase Conformations
Authors: Chen Xiyu , Leyendecker Sigrid , van den Bedem Henry 
Published: January 2021

AbstractProtein kinases are cellular enzymes that catalyze the transfer of phosphates from adenosine triphosphate (ATP) to their substrates. Phosphorylation regulates a multitude of cellular activities, and impaired kinase activity is frequently oncogenic. Inactive or activated forms of kinases are often classified into specific conformations of their activation loops and surrounding areas. This information is valuable for developing potent and selective kinase inhibitors. However, these classification schemes ignore how the dynamics of kinases can differ between states. Here, we apply kinematic flexibility analysis (KFA) to characterize differences in the degree of rigidification between active and inactive states for a large set of kinases in the Protein Data Bank (PDB). Overall, we found that the activation loop in the active state rigidifies kinase conformations, while this effect is less pronounced in the inactive state.
Numerical analysis of plain and fiber reinforced concrete structures during cyclic loading: Influence of frictional sliding and crack roughness
Authors: Gudžulić Vladislav , Neu Gerrit E. , Meschke Günther 
Published: January 2021

AbstractConcrete is a quasi‐brittle material, characterized by a non‐negligible, finite‐sized fracture process zone (FPZ) in which various toughening mechanisms play a significant role on crack development and propagation. Concrete is often reinforced with fibers to improve the serviceability and longevity of concrete structures by controlling the maximal crack widths and providing residual carrying capacity to initiated cracks. In quasi‐brittle materials such as concrete, toughening mechanisms such as crack deflection due to the presence of large heterogeneities, contact shielding, i.e., wedging and crack closure induced by debris and rough crack faces, crack bridging by tough aggregates, unbroken ligaments and fibers (in fiber‐reinforced concretes), are mostly governing damage evolution under monotonic and especially under cyclic loadings [1]. All these items contribute to a complex non‐linear response in terms of load‐displacement curves observed in experimental investigations. Many investigations have been performed on plain concrete, but not so many for high‐performance fiber‐reinforced concrete [2] which is the main subject of investigation within the DFG Priority Program 2020. In order to better understand the influence of these toughening mechanisms on the formation of hysteresis during cyclic loading‐unloading of plain and steel fiber‐reinforced high‐performance concrete, we model these mechanisms and their evolving influence on damage development using a discrete crack approach, and take into account the imperfect closure of cracks and friction between crack faces that come in contact during loading/unloading of the specimen. Within the scope of this contribution, we present the formulation of the model and illustrate its performance through selected numerical experiments under monotonic and cyclic loading of plain and fiber‐reinforced high‐performance concrete specimens. Model predictions are compared with laboratory measurements.
A least‐squares finite element formulation to solve incompressible non‐Newtonian fluid flow
Authors: Averweg Solveigh , Schwarz Alexander , Nisters Carina , Schröder Jörg 
Published: January 2021

AbstractThe Modeling of non‐Newtonian fluids is an essential issue for many industrial applications, for example in the field of chemistry, bioengineering and medical science. In this contribution we present a least‐squares (LS) finite element approach to model steady flow of incompressible non‐Newtonian fluids based on the Navier‐Stokes equations. The application of the least‐squares finite element method (LSFEM) especially in the case of fluid mechanics is motivated by some theoretical advantages compared to the well‐known (mixed) Galerkin method. The LSFEM is not restricted to the LBB‐condition and results in a minimization problem with symmetric positive definite equation systems also for differential equations with non self‐adjoint operators. Furthermore, the LSFEM provides an inherent a posteriori error estimator without additional costs, which enables an efficiency enhancement through adaptive mesh refinements.In this contribution the first‐order LS formulation in terms of stresses and velocities, as introduced in [4], is extended to consider the nonlinear dependence of the viscosity on the shear rate of the fluid. Therefore, the well‐known Carreau model for generalized Newtonian fluids, see for instance [1], is investigated. For the approximation of the independent variables, velocities and stresses, we apply conforming discretizations in H1 and H(div) using standard Lagrange interpolation polynomials and vector‐valued Raviart‐Thomas interpolations functions. A flow through a square domain with exact solution is considered to validate the proposed schemes with respect to accuracy and efficiency.
Around the clock ‐ capsule networks and image transformations
Authors: Schmidt Maximilian 
Published: January 2021

AbstractCapsule networks are a promising new model class for image processing tasks. We investigate and compare their classification performance with convolutional neural networks on a new entry level image data set. In our experiments the capsules are able to learn the effect of rotated input images from data and outperform a comparable convolutional architecture. The results also show that convolutional and capsule networks need structural adjustment to respond to transformations that are not included in the training set.
Lagrangian analysis of long‐term dynamics of turbulent superstructures
Authors: Schneide Christiane , Padberg-Gehle Kathrin , Schumacher Jörg 
Published: January 2021

AbstractIn Rayleigh‐Bénard convection, turbulent superstructures are large‐scale patterns of circulation rolls created by hot ascending and cold descending thermal plumes. The evolution of these large‐scale patterns happens on very large time scales τ [1]. Spectral clustering applied to Lagrangian particle trajectories on time intervals smaller than τ can be used to create clusters displaying a structure similar to the patterns detected in the Eulerian frame of reference [2]. However, this technique is unfeasible for the analysis of the evolution of turbulent superstructures due to turbulent dispersion. Therefore, we test the application of concepts of evolutionary spectral clustering [3] on Lagrangian particle trajectories to analyze the long‐term dynamics of turbulent superstructures in the Lagrangian frame of reference.
Numerical modeling of the mechanical response of bacterial biofilm to flow by using an SPH poroviscoelastic model
Authors: Feng Dianlei , Neuweiler Insa , Liu Moubin , Nackenhorst Udo 
Published: January 2021

AbstractWe present a weakly‐compressible two‐phase poroviscoelastic biofilm model based on Smoothed Particle Hydrodynamics (SPH) method. The biofilm is modeled as a mixture of solid and fluid phases interacting via drag forces. Benefiting from the Lagrangian feature of the SPH method, large deformations of the solid structure can be modeled straightforwardly.
Enhanced integration scheme for unfitted polygonal elements
Authors: Petö Márton , Duvigneau Fabian , Juhre Daniel , Eisenträger Sascha 
Published: January 2021

AbstractIn this contribution a novel integration scheme, extending the conventional quadtree‐decomposition‐based approach by image compression techniques, is investigated for unfitted polygonal meshes with a particular focus on the rational Wachspress shape functions. It is shown that a meaningful reduction of integration points can be achieved without a significant loss in accuracy. However, the full potential of the method in terms of time savings can only be leveraged when applied to higher order polynomial elements. For more information on this topic see Enhanced Numerical Integration Scheme Based on Image Compression Techniques: Application to Rational Polygonal Interpolants by Petö et al. [1].
Large Scale Sea Ice Modeling – Problems and Perspectives.
Authors: Nisters Carina , Schröder Jörg 
Published: January 2021

AbstractThe visco‐plastic sea ice model based on [7] describes the movement of sea ice over large areas of several thousand square kilometers in time. This model has been considered in many publications and has been extended and adapted by numerically motivated and physically‐based approaches. The basic model for the simulation of sea ice circulation considers sea ice velocities and stresses coupled to the field quantities of sea ice thickness and concentration. Two transient advection equations describe the development of sea ice thickness and concentration coupled with sea ice velocity. Furthermore, the viscosity in the constitutive equation is dependent on the sea ice velocities in the sense of a non‐Newtonian fluid, which makes the constitutive relationship strongly nonlinear. An extension of the model is, for example, the elasto‐visco‐plastic constitutive law proposed by [10], which gives numerical stabilization. Recent research on the finite element implementation of the sea ice model is turned to formulations based on the (mixed) Galerkin variation approach, see for example [1] and [20]. Likewise, in [15], [16], and [18] solvers are proposed for the efficient solution of the problem.In this paper, we discuss the obstacles and possibilities of a sea ice model implementation, among others, within a least‐squares finite element method (LSFEM). The mixed LSFEM is well established in fluid mechanics, and a significant advantage of the method is its applicability to first‐order systems, see e.g. [12]. Thus, this method leads to stable and robust formulations for non‐self‐adjoint systems, as they are, for example, for the tracer equations. Based on the results of the Taylor least‐squares scheme and a first‐order Crank‐Nicolson time integrator scheme for the tracer equations, see [21], we discuss here possible steps towards an adequate solution strategy for the complete sea ice model.
Influence of the correlation lengths on the continuous mode conversion
Authors: Zimmmermann Eugen , Weber Wolfgang 
Published: January 2021

AbstractTo detect damages using guided waves, the local mode conversion of a symmetric S0 mode into an antisymmetric A0 mode can be utilized. In simulations which use a homogeneous material model, the conversion will take place only at structural irregularities, e.g. damages. In contrast, the wave propagation in carbon reinforced plastics (CFRP) is more complex. Due to the irregular arrangement of the fibres, regions with varying fibre volume fraction are present. This spatial fluctuation causes an inhomogeneous material behaviour, which significantly influences the wave propagation. In addition to the primary induced symmetric S0 waves, secondary A0‐waves arise which are caused by the material itself and extends over the entire structure, they are continuous. These are also present if the structure is intact and consequently makes it more difficult to detect damage. In order to include the spatial variation of the material properties in the numerical model, second order random fields, which are fully represented by their mean and covariance, can be used. The random distribution of the material properties over a region can be achieved by Karhunen‐Loève decomposition. The spatial structure of the decomposition and therefore the random field depend on the chosen covariance function.
Topological electromagnetic and elastic states in phoxonic crystal cavity arrays
Authors: Ma Tian-Xue , Zhang Chuanzeng , Wang Yue-Sheng 
Published: January 2021

AbstractIn this paper, we investigate the topological characteristics of the phoxonic crystal (PxC) arrays. For the PxC system, the electromagnetic transverse electric mode and the elastic in‐plane mode are considered. The PxC possesses the photonic and phononic bandgaps simultaneously. Based on the bandgaps, we design the PxC cavity which can confine the electromagnetic and elastic waves. The interaction strength between the neighboring PxC cavities can be tuned by changing the distance between these cavities. The PxC cavity arrays with the topologically non‐trivial and trivial phases are obtained. We combine the PxC arrays with the topologically non‐trivial and trivial phases together. The electromagnetic and elastic topological interface states can be simultaneously observed at the interface of the PxC cavity arrays.
A robustness measure for singular point and index estimation in discretized orientation and vector fields
Authors: Hoffmann Karl B. , Sbalzarini Ivo F. 
Published: January 2021

AbstractThe identification of singular points or topological defects in discretized vector fields occurs in diverse areas ranging from the polarization of the cosmic microwave background to liquid crystals to fingerprint recognition and bio‐medical imaging. Due to their discrete nature, defects and their topological charge cannot depend continuously on each single vector, but they discontinuously change as soon as a vector changes by more than a threshold. Considering this threshold of admissible change at the level of vectors, we develop a robustness measure for discrete defect estimators. Here, we compare different template paths for defect estimation in discretized vector or orientation fields. Sampling prototypical vector field patterns around defects shows that the robustness increases with the length of template path, but less so in the presence of noise on the vectors. We therefore find an optimal trade‐off between resolution and robustness against noise for relatively small templates, except for the “single pixel” defect analysis, which cannot exclude zero robustness. The presented robustness measure paves the way for uncertainty quantification of defects in discretized vector fields.
Solving linear equation systems on noisy intermediate‐scale quantum computers
Authors: Mielke André , Ricken Tim 
Published: January 2021

AbstractQuantum computing promises classically unparalleled benefits for various applications. Its properties are exploited in the Harrow‐Hassidim‐Lloyd (HHL) algorithm that, in conjunction with quantum phase estimation, is capable of constructing quantum states that are proportional to the solution of linear equation systems and does so exponentially faster than the fastest known classical algorithms. We explore this capability by computing the nodal displacements of a 1‐dimensional loaded cantilever, discretized by using the finite element method (FEM).