bluuebunny/crossref_metadata_2025_split huggingface dataset:
3D Virtual Elements for Elastodynamic Problems
Authors: Cihan Mertcan , Aldakheel Fadi , Hudobivnik Blaž , Wriggers Peter 
Published: January 2021

AbstractA virtual element framework for nonlinear elastodynamics is outlined within this work. The virtual element method (VEM) can be considered as an extension of the classical finite element method. While the finite element method (FEM) is restricted to the usage of regular shaped elements, VEM allows to use non‐convex shaped elements for the spatial discretization [1]. It has been applied to various engineering problems in elasticity and other areas, such as plasticity or fracture mechanics as outlined in [3, 4]. This work deals with the extension of VEM to dynamic problems. Low‐order ansatz functions in two and three dimensions, with elements being arbitrary shaped, are used in this contribution. The formulations considered in this framework are based on minimization of energy, where a pseudo potential is used for the dynamic behavior. While the stiffness‐matrix needs a suitable stabilization, the mass‐matrix can be calculated fully through the projection part. For the implicit time integration, Newmark‐Method is used. To show the performance of the method, various numerical examples in 2D and 3D are presented.
Model order reduction for small strain elasto‐plasticity based on an adaptive strategy
Authors: Özmen Yasemin , Nigro Paulo S. B. , Scheunemann Lisa , Schröder Jörg 
Published: January 2021

AbstractIn this contribution, an online adaptive reduced order model is presented for small‐strain elasto‐plasticity. Using the GALERKIN method, the problem is projected to a lower subspace giving a reduced problem based on the displacement field snapshots. The adaptivity lies in the update of the projection operator, which is carried out in different parts of the simulation if certain criteria related to the convergence behavior are not fulfilled. With a relative POD analysis called Proper Snapshot Selection (PSS), the new basis is chosen and the simulation is proceeded.
A comparison of different approaches to enforce lattice symmetry in two‐dimensional crystals
Authors: Backofen Rainer , Sahlmann Lisa , Willmann Anna , Voigt Axel 
Published: January 2021

AbstractThe phase‐field crystal (PFC) model allows for the resolution of atomic‐scale structures on diffusive time scales. It is based on an approximation of the two‐particle direct correlation function in the free energy, which provides the symmetry of the lattice structure. Various approaches have been proposed to model common lattices. We here only focus on two‐dimensional crystals, review the different approaches and demonstrate that one, which is based on affine linear deformations, violates rotational invariance. The consequences of this physical inconsistency are shown numerically using a pseudospectral algorithm for the higher order equations.
Lagrangian transport in two‐dimensional time‐periodic cavity flow
Authors: Babor Lukas , Kuhlmann Hendrik C. 
Published: January 2021

AbstractThe Lagrangian transport in a laminar incompressible flow in a two‐dimensional square cavity driven by a harmonic tangential oscillation of a single cavity wall is investigated numerically for a range of Reynolds (Re) and Strouhal (Str) numbers. The topology of fluid trajectories is described by means of stroboscopic projections, which reveal the co‐existence of chaotic trajectories and regular Kolmogorov‐Arnold‐Moser (KAM) tori. The higher the frequency of the lid oscillation the more regular the fluid motion becomes and the size of the KAM tori increases. For low frequencies the KAM tori are strongly stretched along instantaneous streamlines of the flow, while for high frequencies they resemble streamlines of a mean flow.
Influence of Micro‐Inertia on the Macroscale ‐ A Fully‐Coupled Direct Homogenization Framework for Dynamics
Authors: Tamsen Erik , Balzani Daniel 
Published: January 2021

AbstractThis contribution presents a numerical example of a locally‐resonant microstructure, analyzed using a fully‐coupled large strain homogenization framework including dynamics at both scales. The fundamental assumptions the framework is based on are summarized and results showcasing the ability of the proposed homogenization method are given.
Algorithm‐Driven Optimization of Support‐Free Truss‐like Structures in Early‐Stage Design for Additive Manufacturing
Authors: Reintjes Christian , Lorenz Ulf 
Published: January 2021

AbstractMaterial extrusion processes require internal or external or both support structures to support the printing process. These support structures generate costs due to additional material, printing time and energy. Contrary to the optimization strategy to minimize the need for additional support by optimizing the support structure itself and keeping the original part, we focus on designing a new part in a single step by optimizing the topology towards a support‐free lattice structure. Assuming that the support structures cannot be removed by non‐destructive post‐processing this optimization approach becomes necessary, since the force distribution in a lattice structure is manipulated by the additional support structures. We extend the work by [1] to model support‐free lattice structures considering a positioning of a static area load. We show how integer dependent constraints can be used to implement design standards for support‐free and extrusion‐based additive manufacturing.
Nonlinear computation of cables with high order solid elements using an anisotropic material model
Authors: Hildebrandt André , Sharma Prateek , Diebels Stefan , Düster Alexander 
Published: January 2021

AbstractDue to their complex structure cables exhibit an anisotropic behaviour and undergo large deformations in various applications. The large deformations are simulated using blended high order solid elements that can represent large deformations efficiently. To reduce the computational complexity the cross section consisting of many single wires and different layers of material is homogenized and represented by a transversely isotropic material model. Frictional effects and possible reordering of the parts are modelled through elastoplastic material behaviour with an anisotropic yield function. The simulations show that for a simple tension test and a free torsion test the material parameters can be satisfactorily identified.
An Adaptive Isogeometric Phase‐Field Model for Topology Optimization
Authors: Hennig Paul , Heindel Leonhard , Kästner Markus 
Published: January 2021

AbstractIn this contribution, we apply adaptive isogeometric analysis to a phase‐field model for topology optimization. To increase the efficiency of the computation, we perform local mesh refinement and coarsening between the time increments of the simulation. To provide a trial solution for the iterative solver of the next increment, state variables are projected from the old to the new mesh. The quality and efficiency of the approach are tested in a two‐dimensional benchmark.
Micromechanical analysis of failure in fiber reinforced polymer‐metal structures
Authors: Hirsch Franz , Natkowski Erik , Kästner Markus 
Published: January 2021

AbstractIn this contribution, the interface region of a fiber reinforced polymer and a metal component is considered within a representative volume element. The connecting surface exhibits a random height distribution with a defined roughness. Under shear loading, different failure mechanisms are studied with respect to the local interface roughness. Furthermore, adhesive failure of the interface and cohesive failure of the polymer are distinguished. The results show an enhanced bonding strength with increasing interface roughness.
Neural Networks for Structural Optimisation of Mechanical Metamaterials
Authors: Bronder Stefan , Diebels Stefan , Jung Anne 
Published: January 2021

AbstractMechanical metamaterials are man‐made designer materials with unusual properties, which are derived from the micro‐structure rather than the base material. Thus, metamaterials are suitable for tailoring and structural optimisation to enhance certain properties. A widely known example for this class of materials are auxetics with a negative Poisson's ratio. In this work an auxetic unit cell is modified with an additional half strut.During the deformation this half strut will get into contact with the unit cell and provide additional stability. This leads to a higher plateau stress and consequently to a higher energy absorption capacity. To achieve the maximum energy absorption capacity, a structural optimisation is carried out. But an optimisation exclusively based on finite element simulations is computationally costly and takes a lot of time. Therefore, in this contribution neural networks are used as a tool to speed up the optimisation. Neural networks are one of many machine learning methods and are able to approximate any arbitrary function on a highly abstract level. So the stress‐strain behaviour and its dependency from the geometry parameters of a type of microstructure can be learned by the neural network with only a few finite element simulations of varying geometry parameters. The modified auxetic structure is optimised with respect to the mass specific energy absorption capacity. As a result a qualitative trend for the optimal geometry parameters is obtained. However, the Poisson's ratio for this optimisation is close to zero.
Simulation of nonequilibrium effects in quantum cascade lasers
Authors: Jirauschek Christian 
Published: January 2021

AbstractQuantum cascade lasers exploit optical transitions between quantized electronic energy levels in multi‐quantum‐well structures for light generation and detection. This design principle enables the realization of compact, semiconductor‐based lasers in the mid‐infrared and terahertz spectral regions. In this contribution, the modeling of such devices is discussed based on an ensemble Monte Carlo approach, enhanced by modifications obtained from the density matrix formalism. A special emphasis is put on the inclusion of nonequilibrium electron and phonon effects. The simulations are validated against available experimental data for a terahertz quantum cascade laser.
A hybrid approach for the multi‐scale simulation of irreversible material behavior incorporating neural networks
Authors: Hütter Geralf , Settgast Christoph , Lange Nils , Abendroth Martin , Kiefer Björn 
Published: January 2021

AbstractThe present contribution presents a hybrid approach for the multi‐scale modeling where the yield surface and evolution equations are represented by neural networks, for which micro‐scale simulations are used as training data. The approach and its implementation into a commercial finite element code are demonstrated for a ductile foam material. The results are verified by comparison with an FE2 simulation.
Investigations on modeling of freezing processes within the framework of the Theory of Porous Media
Authors: Schwarz Alexander , Bluhm Joachim , Schröder Jörg 
Published: January 2021

AbstractIn this contribution we present investigations on modeling of freezing processes between two ice floes. In detail we show results on the ice formation (mass exchange between the constituents) and the temperature distribution under calm sea conditions. For the detection of energetic effects regarding the characterization and the control of the phase transition, a thermodynamical consistent approach is presented, see [1]. In the later contribution the resulting finite element is a four field formulation in terms of ice displacements, liquid pressure, temperature and volume fraction of ice and is used in the present paper. An advanced numerical example show that the simplified model is capable of simulating the temperature development and phase change.
Mixed finite element formulations and energy‐momentum time integrators for thermo‐viscoelastic fiber‐reinforced continua
Authors: Dietzsch Julian , Groß Michael , Schuffenhauer Richard Friedrich 
Published: January 2021

AbstractToday, fiber‐reinforced materials and their exact dynamic simulation play a significant role in the construction of lightweight structures. These materials are used in aircraft, automobiles and wind turbines, for instance. The low density and the high modulus of elasticity play a major role, but also the thermal properties should not be neglected. First of all, the thermal expansion of the matrix part and the ability to conduct the heat in a directional way with the fibers. For these materials, volumetric locking effects of an incompressible matrix material as well as locking effects due to stiff fibers can occur. On the one hand, there are combinations of well known mixed elements with an independent approximation of the volume dilatation and an independent approximation of the right Cauchy‐Green tensor for the anisotropic part of the strain energy function to reduce these effects. On the other hand, we have developed mixed elements where fields for the fourth and fifth invariants are added, as well as a version with the corresponding tensor fields. For long‐term simulations it is necessary to use higher order time integrators to perform an accurate dynamic simulation. Galerkin‐based time integrators offer a good option for this application. To eliminate a huge energy error these have to be extended to an energy‐momentum time integration scheme. It is logical to combine these methods and thus combine the advantages of these methods. We formulate the mixed elements using Hu‐Washizu functionals and combine this with the mixed principle of virtual power. By adding a thermo‐mechanical coupling part in the strain energy and introducing Fourier's heat conduction we obtain a thermo‐mechanical formulation for the different mixed elements and a higher order Galerkin‐based time integrator. Dirichlet boundary conditions in the form of Lagrange multiplier methods as well as Neumann boundary conditions in the mechanical and thermal context are also provided. In addition, we extend the continuum so that we can model different fiber families and the directional heat conduction of the fibers. As numerical examples serve cook's cantilever beam as well as a rotating heat pipe. We primarily analyze the spatial and time convergence, the conservation properties as well as the effect of the heat conduction of the fibers.
Modeling of the Bayliss‐Effect in Vascular Smooth Muscles
Authors: Uhlmann Klemens , Balzani Daniel 
Published: January 2021

AbstractThis contribution presents a model for the smooth muscle contraction embracing a stretch‐dependent calcium function. It enables the coupling of the mechanical material answer with the chemical reactions on cellular level. Based thereon, simulation results of arteries under time‐dependent intravascular pressure, mimicking the scenario during heart‐beat, are analyzed.
Microstructure‐related modeling of timber constructions
Authors: Wiese Sandra , Dinkler Dieter 
Published: January 2021

AbstractWood is an organic porous material of cellulose fibers, which consist of a cell wall and a lumen. In this paper a microstructure‐related model utilizing the polygonal finite element method (PFEM) is presented. The PFEM enables the discrete modeling of the wooden cellular structure under application of shape functions based on mean value coordinates. The numerical integration scheme is based on the triangulation of the elements. In the scope of this framework the transverse compression behavior of wood is simulated. The deformation is presented and compared to the macrostructure‐related result.
Modelling basal‐cell carcinoma behaviour in avascular skin
Authors: Suditsch M. , Schröder P. , Lambers L. , Ricken T. , Ehlers W. , Wagner A. 
Published: January 2021

AbstractMalignant neoplasms are one of the most dangerous diseases. Within the framework of the well‐established Theory of Porous Media (TPM), a multi‐constituent model is derived. The model is mathematically formulated by a set of coupled partial differential equations which are solved within the well‐known framework of the finite‐element method. The general TPM model is applied to basal‐cell carcinoma in the avascular skin and representative numerical examples show the capabilities of the model.
Concentration‐Specific Constitutive Modeling of Gelatin Based on Artificial Neural Networks
Authors: Abdolazizi Kian P. , Linka Kevin , Sprenger Johanna , Neidhardt Maximilian , Schlaefer Alexander , Cyron Christian J. 
Published: January 2021

AbstractGelatin phantoms are frequently used in the development of surgical devices and medical imaging techniques. They exhibit mechanical properties similar to soft biological tissues [1] but can be handled at a much lower cost. Moreover, they enable a better reproducibility of experiments. Accurate constitutive models for gelatin are therefore of great interest for biomedical engineering. In particular it is important to capture the dependence of mechanical properties of gelatin on its concentration. Herein we propose a simple machine learning approach to this end. It uses artificial neural networks (ANN) for learning from indentation data the relation between the concentration of ballistic gelatin and the resulting mechanical properties.
The Capriccio method: a scale bridging approach for polymers extended towards inelasticity
Authors: Zhao Wuyang , Pfaller Sebastian 
Published: January 2021

AbstractIn this contribution we present an extension of the multiscale Capriccio method towards inelasticity. This enables coupled simulations of a particle domain embedded into a continuum with particular focus on polymer systems. Starting from the method's initial implementation of pure elasticity, we substitute the nonlinear elastic continuum constitutive law by a recently developed viscoelastic‐viscoplastic one which is able to capture the mechanical behaviour of the particle system in a much larger strain range. Furthermore, we discuss numerical aspects like the choice of time steps and iteration numbers.
Least Squares Finite Element Method for Hepatic Sinusoidal Blood Flow
Authors: Bertrand Fleurianne , Lambers Lena , Ricken Tim 
Published: January 2021

AbstractThe simulation of complex biological systems such as the description of blood flow in organs requires a lot of computational power as well as a detailed description of the organ physiology. We present a novel Least‐Squares discretization method for the simulation of sinusoidal blood flow in liver lobules using a porous medium approach for the liver tissue. The scaling of the different Least‐Squares terms leads to a robust algorithm and the inherent error estimator provides an efficient refinement strategy.
Study on the Interaction of Nonlinear Water Waves considering Random Seas
Authors: Hollm Marten , Dostal Leo , Fischer Hendrik , Seifried Robert 
Published: January 2021

AbstractThe nonlinear Schrödinger equation plays an important role in wave theory, nonlinear optics and Bose‐Einstein condensation. Depending on the background, different analytical solutions have been obtained. One of these solutions is the soliton solution. In the real ocean sea, interactions of different water waves can be observed at the surface. Therefore the question arises, how such nonlinear waves interact. Of particular interest is the interaction, also called collision, of solitons and solitary waves.Using a spectral scheme for the numerical computation of solutions of the nonlinear Schrödinger equation, the nonlinear wave interaction for the case of soliton collision is studied. Thereby, the influence of an initial random wave is studied, which is generated using a Pierson‐Moskowitz spectrum.
Sensitivity Analysis of a Simulated Hydrogel
Authors: Keller Karsten , Wallmersperger Thomas , Ricken Tim 
Published: January 2021

AbstractCrosslinked polyelectrolytic polymers embedded in an aqueous solution, so‐called hydrogels, show stimuli‐responsive behaviour under various kinds of stimulation. These “smart” reactions can be triggered by e.g. chemical, electrical, mechanical or thermal stimuli. The hydrogels react via uptake or delivery of mobile ions and solvent, and show enormous swelling capabilities. This behaviour can be used for chemo‐electro‐mechanical energy converters or as an actuator or sensor.The presented research investigates anionic hydrogels in the framework of a sensitivity analysis, by a design of experiment (DOE) with the use of ANSYS optiSLang. The hydrogel itself is modelled within a finite element code (Abaqus Unified FEA) as a user element. The applied stimuli are of different nature: chemical, electrical, mechanical and thermal.On the one hand, the stimulus is applied by the change of boundary conditions, e.g. for chemical stimulation by a change of the concentrations of the constituents themselves (Na+ and Cl−). For electrically stimulated hydrogels, two electrodes are incorporated at the boundaries and the electric potential is changed. On the other hand, the mechanical stimulus is defined by prescribed displacements at a boundary of the fixed hydrogel. The thermal stimulus is applied over the whole domain in the form of transient temperature changes with temperature‐dependent material parameters.
The reactions of the hydrogel differ – depending on the type of hydrogel and the stronger or weaker sensitivity – on the applied stimulus. The fully coupled three‐field description of the chemo‐electro‐mechanical model enhanced with thermal dependencies is capable of giving local concentrations, electric potential and displacements.
A variational concept and its experimental calibration for temperature‐induced rate‐dependent phase transformations in steel
Authors: Jaworek David , Waimann Johanna , Reese Stefanie 
Published: January 2021

AbstractIn forming processes of metals, different physical phenomena are observable which may alter the material properties and behavior severely. These observations can be attributed to changes in the surface layer of the material. This research is a part of the transregional collaborative research center SFB/TRR 136 which deals with surface layer modifications in 42CrMo4 steels and aims to determine process independent correlations between material loads and material modifications. These correlations are called process signatures. The present work is concerned with investigating thermally induced solid‐solid phase transformations in steels. An example of a predominantly thermal process is the induction hardening process. In this process, an initially ferritic‐pearlitic structure is at first heated until reaching a temperature that lies above the temperature at which homogeneous austenite is formed. During this heating process, the steel undergoes diffusion‐driven phase transformations which are heating‐rate‐ and time‐dependent. After sufficiently long incubation, a homogeneous austenitic microstructure is obtained. Then, the specimen temperature is lowered at a very high cooling rate. This invokes high‐temperature rates on the microstructure and results in an austenitic‐martensitic phase transformation, see e.g. [1]. Based on the Principle of the Minimum of the Dissipation Potential (PDMP) as presented in [2], the austenitic‐martensitic transformation has been widely discussed in the context of shape memory alloys. We present a material model which is also able to show the ferritic‐austenitic transformation. The individual phase transitions are modeled using a rate‐ and transformation‐process‐dependent formulation of the dissipation potential. The presented material model is finally tested with numerical simulations.