bluuebunny/crossref_metadata_2025_split huggingface dataset:
How does policy innovation diffuse among Chinese local governments? A qualitative comparative analysis of River Chief Innovation
Authors: Zhang Yunxiang , Wang Shichen 
Published: January 2021

AbstractIt is well‐documented that interlocal learning and competition could drive policy innovation diffusion. However, their interconnection in non‐western regimes as China is less explored. Utilizing the method of qualitative comparative analysis on the case of River Chief Innovation, this article intends to explore the multiple conjunctural causation of Chinese policy diffusion and the impacts of central recognition. Our findings suggest that interlocal learning and tournament could intimately stimulate Chinese policy diffusion through different combinations. Different governments would adopt innovation for various reasons in a continuum of diffusion mechanisms, involving the technical learning, the championship‐induced learning, the mandate‐induced learning, and the innovation tournament. Hence, despite the ongoing centralization under Xi, space for local spontaneous learning remains. We also find that central recognition could activate the interlocal tournament and extend the diffusion continuum to the tournament side. Therefore, it facilitates policy diffusion toward governments that lack learning motivations and promotes the local implementation of central preferences.
An energy‐momentum space‐time discretization of a constrained micropolar continuum for 3D fiber‐reinforced composites
Authors: Groß Michael , Dietzsch Julian , Röbiger Chris 
Published: January 2021

AbstractIn 2D fiber‐reinforced composites, single fibers with a diameter in the range of micrometers are embedded in a matrix material. 3D fiber‐reinforced composites consist of fiber bundles (rovings) with diameters of millimeters. Therefore, 3D fiber‐reinforced composites require an extended material modelling, because a fiber bundle has to be considered as a beam‐like structure with curvature‐twist (twisting and bending) stiffness. By means of an extended continuum formulation, we modell a micro inertia and a curvature‐twist stiffness. We introduce these secondary effects by means of independent drilling degrees of freedom. The resulting constrained micropolar continuum is derived by a mixed principle of virtual power. In the discrete setting, this variational principle generates a mixed B‐bar method and an energy‐momentum scheme. We show transient numerical examples, which demonstrate the effect of micro inertia as well as the twisting and bending stiffness of the fiber bundles.
Asymptotics of Rounding Algorithms for Integer Control Problems in the Presence of Convexified Pointwise Mixed Constraints
Authors: Manns Paul 
Published: January 2021

AbstractThe analysis of computationally cheap algorithms to approximate the infimum of optimal control problems with discrete‐valued controls has been improved in recent literature. The overall method is often referred to as combinatorial integral approximation decomposition and the algorithms are often referred to as rounding algorithms.The studied algorithms have in common that they seek to minimize or at least bound a quantity called integrated control deviation. The algorithms operate on a grid (often called rounding grid) and the integrated control deviation vanishes when the grid constant of the grid on tends to zero. Assuming a suitable spatial coherence property of the grid refinement implies weak∗ convergence of the computed controls in L∞.When the integer optimal control problem features additional pointwise mixed state‐control constraints, the aforementioned rounding algorithms cannot be applied directly. There exist examples for which the observed infeasibility of the constraint after applying the algorithms does not vanish in an L∞‐sense when the grid constant is driven to zero. While modifications of the algorithms exist that resolve this problem, the asymptotics of the infeasibility without those modifications have not been analyzed so far. This work closes this gap in the existing literature and we show that the infeasibility vanishes in a pointwise almost everywhere sense.
Numerical study on shape functions for optimal exploitation of the acoustic black hole effect
Authors: Rothe Sebastian , Dorn Matthias , Langer Sabine Christine 
Published: January 2021

AbstractThe acoustic black hole (ABH) effect offers a great possibility to damp a whole construction in a very efficient way. The main idea of this approach is to weaken thin structures locally to concentrate the structure‐borne sound energy in this area. Therefor material is removed in a certain region, which is referred to as an ABH. This measure leads to a focusing of acoustically critical bending waves. By applying a damping measure, e.g. constraint‐layer damping, within the ABH, the structure is globally damped by a local measure.The shape function of an ABH is a major issue for optimizing the efficiency of damping. The material diminution, equivalent to the reduction of the mechanical impedance, has to be smooth in order to avoid reflection of bending waves. In literature, a power function with a higher order than two is recommended. Focusing the structure‐borne sound works better by increasing the order. The limit case is infinite order which is a sharp step transition. This is equivalent to an impedance step which is well known to lead to a high portion of reflection and therefor reducing the efficiency of the ABH area. There must be an optimum between these two limits, quadratic and infinite order, in an acoustical sense.In this paper, numerical studies are carried out to determine the optimal order for a power function approach as shape function of an ABH. For this purpose, a beam is used as a generic structure. In addition, alternative function approaches are investigated and compared.
The integrated control deviation of mixed‐integer optimal control problems with vanishing constraints
Authors: Bestehorn Felix , Kirches Christian 
Published: January 2021

AbstractMixed‐integer optimal control problems (MIOCPs) are often solved using a decomposition approach, consisting of solving a partial outer convexified relaxed problem and using a rounding scheme to obtain a discrete‐valued control. We show that even in the presence of Vanishing Constraints (VCs) a binary control with linearly bounded integrated control deviation exists, if the grid is equidistant. We note that this control can be computed efficiently and that the bound is tight.
Reduction of the vibration amplitude with variable excitation frequency
Authors: Simader Victoria , Holl Helmut J. 
Published: January 2021

AbstractIn many dynamic systems large vibration amplitudes occur if the operation frequency is near the resonance frequency. Also during the resonance passage large amplitudes result. In order to reduce the amplitude of the oscillation a suitable excitation can be applied. The force driven single degree of freedom harmonic oscillator is used to analyse the reaction of the dynamic system to a variable excitation frequency. The analysis starts with a mathematical transformation of the excitation signal in order to identify the influence of the different excitation parameters. It is shown that for specific parameters the natural frequency of the system can be eliminated from the excitation signal. In both cases, the operation near the resonance frequency and the passage through resonance, suitable numerical values, correlations between the parameters and functions can be found to reduce the resulting vibration amplitude of the system.
Investigation of heterogeneous fracture aperture distributions in a hydro mechanical setting using hybrid‐dimensional interface elements
Authors: Schmidt Patrick , Steeb Holger 
Published: January 2021

AbstractIn the community of porous and fractured geomaterials properties regarding underground fluid storage and matter are of high interest. Investigations on fluid‐filled fractures require strong hydro mechanical coupling of fracture and porous domain to reproduce deformation triggered, non‐local phenomena such as the Noordbergum effect. Special numerical treatment is necessary to solve the tightly coupled system consisting of high aspect ratio fractures and a surrounding porous matrix, since other approaches such as Direct Numerical Simulations fail due to technical issues (number of Degrees of Freedom (DoF)). Once heterogeneous initial aperture distributions are of interest coarse grained continuum approaches (Biot's poroelasticity theory) facing technical limitations since explicit meshing of the fracture geometry is required. This work uses hybrid‐dimensional interface elements in a fully coupled implicit formulation to investigate its capacities regarding heterogeneous fracture surfaces in three dimensions.
Simultaneous determination of Bingham material parameters using a ball probe concrete rheometer
Authors: Gerland Florian , Schomberg Thomas , Wetzel Alexander , Middendorf Bernhard , Wünsch Olaf 
Published: January 2021

AbstractA new evaluation method allowing direct determination of the Bingham parameters from ball probe rheometers. A non‐linear relationship between the direct measured variables and the material parameters is revealed through numerical parameter studies. The method was validated on two devices of the ball probe type with different dimensions. Comparison with other methods showed good agreement. It is pointed out how the evaluation method can be transferred to devices having other dimensions by performing a limited number of straightforward calibration experiments. This work closes the gap between established ball probe rheometer evaluations and objective material parameters. Objective material parameters can be extracted from every ball probe rheometer. Even existing data can be converted.
Nonlinear System Identification of a Furuta Pendulum Using Machine Learning Techniques
Authors: Rückwald Tobias , Drücker Svenja , Dücker Daniel-André , Seifried Robert 
Published: January 2021

AbstractUsually, dynamical systems can be described by differential equations. An accurate model is essential when designing and optimizing a controller. However, not every system can be modeled easily by physical models due to highly nonlinear behavior, such as friction or backlash. Then, a data based approach, such as machine learning, might be helpful. The focus in this work is set on modeling dynamical systems using neural networks and deep learning, which are growing subjects in research and industry to identify nonlinear dynamics.
Size Effects in Computational Homogenization of Polymer Nano‐Composites
Authors: Kumar Paras , Mergheim Julia 
Published: January 2021

AbstractNano‐particles, as compared to micro‐sized inclusions, result in a much better improvement to the mechanical properties of otherwise brittle polymers. Standard first‐order computational homogenization lacks the length scale necessary to capture this size effect. In this work, a computational homogenization scheme enhanced with interface energetics is considered and its applicability to polymer nano‐composites with different types of filler particles is assessed through systematic numerical experimentation. The study reveals that the method performs quantitatively much better in the case of softer inclusions as compared to the case where the inclusions are much stiffer than the matrix material, which happens in the case of silica nano‐particles.
Automatic differentiation of strain‐energy functions in the context of user‐defined materials for the FEM
Authors: Hillgärtner Markus , Guo Theron , Itskov Mikhail 
Published: January 2021

AbstractIn order to implement material models as user‐defined material subroutines into implicit finite element method (FEM) codes, a stress tensor and a fourth‐order tangent tensor are required. In the context of hyperelasticity, these tensors can be obtained as the first and second derivative of the strain‐energy function. Manual formulation and implementation of these derivatives can be tedious and error‐prone.In this contribution, we discuss automatic differentiation (AD) as an easy‐to‐use alternative to express derivatives for the FEM [1] in an efficient way and without extensive manual implementation [2]. AD is applied to automatically obtain a user‐defined material subroutine for an implicit analysis based on source code of the strain‐energy. The approach is validated by utilizing a hyperelastic anisotropic model of arterial layers [3] in ABAQUS. Additionally, a pseudo‐elastic model of the Mullins effect in filled rubber [4] is implemented to evaluate the applicability of the discussed approach for inelastic behaviors which require internal variables.
Jump conditions in phase‐field modeling of interface fracture
Authors: Hansen-Dörr Arne Claus , Brummund Jörg , Kästner Markus 
Published: January 2021

AbstractIn this contribution, a variational framework for diffuse modeling of cracks in heterogeneous media is analyzed. A static order parameter smoothly bridges the discontinuity at material interfaces, while an evolving phase‐field captures the regularized crack. The key novelty is the combination of a strain energy split with a partial rank‐I relaxation in the vicinity of the diffuse interface. The former is necessary to account for physically meaningful crack kinematics like crack closure, the latter ensures the mechanical jump conditions throughout the diffuse region. The model is applied to crack propagation, where a significant influence on crack branching is observed, that underlines the necessity of a reasonable homogenization scheme for the diffuse interface region.
Linear stability of the flow in a cavity driven at yaw
Authors: des Boscs Pierre-Emmanuel , Kuhlmann Hendrik C. 
Published: January 2021

AbstractThe linear stability boundary of the flow in a square cavity driven by a tangentially moving lid having a non‐zero spanwise velocity is investigated by means of finite elements. For intermediate yaw angles, the linear stability boundary is lower than for the classical lid‐driven cavity. Consistent with results for bounded Couette flow the basic flow in the cavity is stabilized as the lid motion turns in spanwise direction.
Efficient identification of random fields coupling Bayesian inference and PGD reduced order model for damage localization
Authors: Robens-Radermacher A. , Held F. , Coelho Lima I. , Titscher T. , Unger J. F. 
Published: January 2021

AbstractOne of the main challenges regarding our civil infrastructure is the efficient operation over their complete design lifetime while complying with standards and safety regulations. Thus, costs for maintenance or replacements must be optimized while still ensuring specified safety levels. This requires an accurate estimate of the current state as well as a prognosis for the remaining useful life. Currently, this is often done by regular manual or visual inspections within constant intervals. However, the critical sections are often not directly accessible or impossible to be instrumented at all. Model‐based approaches can be used where a digital twin of the structure is set up. For these approaches, a key challenge is the calibration and validation of the numerical model based on uncertain measurement data.The aim of this contribution is to increase the efficiency of model updating by using the advantage of model reduction (Proper Generalized Decomposition, PGD) and applying the derived method for efficient model identification of a random stiffness field of a real bridge.
An efficient semi‐analytical solution of the Reynolds equation
Authors: Pfeil Simon , Gravenkamp Hauke , Duvigneau Fabian , Woschke Elmar 
Published: January 2021

AbstractA numerically efficient, semi‐analytical solution of the Reynolds equation for hydrodynamic journal bearings is developed based on the Scaled Boundary Finite Element Method. The pressure field is discretized along the circumferential coordinate of the lubrication gap, while an analytical formulation is used in the axial direction. A system of inhomogeneous ordinary differential equations is obtained, which is solved under consideration of the boundary conditions. The solution is verified, and its numerical efficiency is investigated in comparison to an FEM solution.
Deep Learning for Classification of Compton Camera Data in the Reconstruction of Proton Beams in Cancer Treatment
Authors: Basalyga Jonathan N. , Barajas Carlos A. , Gobbert Matthias K. , Maggi Paul , Polf Jerimy 
Published: January 2021

AbstractReal‐time imaging has potential to greatly increase the effectiveness of proton beam therapy in cancer treatment. One promising method of real‐time imaging is the use of a Compton camera to detect prompt gamma rays, which are emitted by the beam, in order to reconstruct their origin. However, because of limitations in the Compton camera's ability to detect prompt gammas, the data are often ambiguous, making reconstructions based on them unusable for practical purposes. Deep learning's ability to detect subtleties in data that traditional models do not use make it one possible candidate for the improvement of classification of Compton camera data. We show that a suitably designed neural network can reduce false detections and misorderings of interactions, thereby improving reconstruction quality.
Characterization of the objective function landscape using a modified Dijkstra algorithm
Authors: Weiser Stephan , Wulf Hans , Ihlemann Jörn 
Published: January 2021

AbstractA decisive disadvantage of high dimensional optimization problems is the large number of parameters which make the identification process difficult. Many of this are reflected in the mathematical properties of the objective function used for parameter identification. Ideally, the objective function has a simple, paraboloid‐like form with a single minimum whose location corresponds to the desired parameter set. Instead, unfavorable “landscape forms” occur, for example “bumpy” areas with several local minima. In literature, the dominant methods are attempt to simplify high‐dimensional functions, or to research new, mostly stochastic optimization methods. This article examines a way to obtain information about the landscape of the objective function underlying an optimization problem. A path search algorithm based on the Dijkstra algorithm is presented. The purpose of the algorithm is to find the approximately deepest path between two local minima, which allows to obtain information about the characteristics of the objective function. It is tested on the Himmelblau and Rastrigin function and allows to examine the landscape between two local minima with respect to their topographic characteristics.
Time‐separated stochastic mechanics for simulating the visco‐elastic response of construction parts
Authors: Junker Philipp , Nagel Jan 
Published: January 2021

AbstractIn a series of papers, we investigated the problem of efficiently analyzing visco‐elastic materials with stochastic material properties. The related evolution equation could be solved analytically which allowed for a stochastic series expansion around the mean for the internal variable. This, in turn, gave access to analytical expressions for the stochastic stress and reaction force in a finite element setting such that expectation and variation could be expressed in terms of simple formulas. Consequently, our analysis separated the stochastic properties of the material from any boundary problem and any loads, i.e., the stochastic behavior was separated from all time‐dependent conditions such that we referred our method as time‐separated stochastic mechanics. Numerical results of our formulas were in excellent agreement to representative Monte‐Carlo (MC) simulations. This holds true for both material point computations as well as finite element simulations. Particularly for finite element simulations, the time consumption for our approach is smaller by orders of magnitude.In this contribution, we recall the basic aspects of our works and present a brief overview. After presenting the key idea of the TSM, we recall the numerical treatment and present several examples which we compare to Monte‐Carlo results. Our results show a similar quality as the reference solution but at a computational effort that is orders of magnitude smaller.
Comparison of Model Predictive and Graph Algebraic Approaches to Distributed Formation Control
Authors: Ebel Henrik , Eberhard Peter 
Published: January 2021

AbstractMotivated by the advantages that networked control may bring for the performance and flexibility of distributed robotic systems, this contribution considers two very distinct approaches to formation control. One approach, which is more prevalent in literature, is based on results from algebraic graph theory. The other approach draws from distributed model predictive control, allowing the explicit consideration of constraints and resulting in a controller that is rather simple to tune to the application's priorities by adjusting cost function weights and constraint bounds. Interesting observations from the comparison include differences in the conservativeness and performance of the control schemes with increasing numbers of cooperating robots. Experiments with custom‐built hardware robots demonstrate the practical applicability of the schemes.
Investigating different friction models for the stick‐slip effect with nodal contact
Authors: Akar Özge , Willner Kai 
Published: January 2021

AbstractFriction is an indispensable phenomenon since it appears in many natural phenomena as well as in industrial applications. Especially the so‐called stick‐slip‐effect in dynamic applications can cause undesirable effects like noise and wear. Hence, it is of great importance to investigate and understand friction in detail in order to avoid those phenomena with negative consequences. The goal of this investigation is to observe a three‐dimensional wire‐like beam clamped on one side and free on the other, that is excited at one node with a constant force. Thereby friction is induced to the system and the stick‐slip‐effect occurs. The Fast Nonlinear Analysis Algorithm is used to solve the nonlinear equation computationally. First, dry friction is simulated varying the number of sliders in the Iwan model and applying different friction distribution models. Viscous and Stribeck friction are included afterwards. The obtained results are compared with respect to the simulation time.
Water management of frost‐resistant plant tissues as a consequence of extracellular ice formation
Authors: Eurich Lukas , Wagner Arndt , Ehlers Wolfgang 
Published: January 2021

AbstractThe formation of extracellular ice within plant tissues is regarded as one of their crucial factors to withstand subzero temperatures without any (biologically irreversible) damage. In this regard, extracellular ice implies two important consequences, which are the dehydration of the tissue cells to prevent intracellular ice formation, which would be fatal for the plant, and the attraction of water towards the freezing site. However, the pattern of ice formation may vary significantly among various types of plants. There might be rather dispersed ice formation distributed in large parts of the plant or localised ice formation at internal surfaces. Within this contribution, the latter‐mentioned case is addressed with a macroscopic modelling approach based on the Theory of Porous Media. The appearing water management is discussed at a representative numerical example.