bluuebunny/crossref_metadata_2025_split huggingface dataset:
Modelling transient stresses in dynamically loaded elastic solids using the Lattice Boltzmann Method
Authors: Faust Erik , Steinmetz Felix , Schlüter Alexander , Müller Henning , Müller Ralf 
Published: May 2023

AbstractIn solids subjected to transient loading, inertial effects and S‐ or P‐wave superposition can give rise to stresses which significantly exceed those predicted by quasi‐static models. It pays to accurately predict such stresses – and the failures induced by them – in fields from mining to automotive safety and biomechanics. This, however, requires costly simulations with fine spatial and temporal resolutions.The Lattice Boltzmann Method (LBM) can be used as an explicit numerical solver for certain appropriately formulated conservation laws [1]. It encodes information about the field variables to be simulated in distribution functions, which are modified locally and propagated across a regular lattice. As the LBM lends itself to finely discretised simulations and is easy to parallelise [2, p.55], it is an intriguing candidate as a solver for dynamic continuum problems.Recently, Murthy et al. [3] and Escande et al. [4] adopted LBM algorithms to model isotropic, linear elastic solids. We extended these algorithms using local boundary rules that allow us to model arbitrary‐valued Dirichlet and Neumann boundaries. Here, we illustrate applications of the LBM for solids and the proposed additions by way of a simple numerical example – a glass pane subject to a sudden impact load.
Influence of Mean Stress on Lifetime Prediction of Adhesive Bonds
Authors: Köster Christian , Matzenmiller Anton 
Published: May 2023

AbstractThe importance of adhesive bonds in the field of joining technology is increasing due to their advantageous properties. One of these attributes is the possibility to reduce the weight compared to welded joints in group of components. For a safe design, the knowledge of the lifetime of these components is essential. Various methods are used for the prediction of the lifetime under cyclic loading. On the one hand there are test‐based methods, on the other hand simulation‐based approaches. Test‐based ones are often time‐consuming and cost‐intensive. In addition, a change in boundary conditions requires new tests. Using a simulation‐based method, it is possible to analyse new boundary conditions rapidly. The following contribution shows a damage model approach that is able to predict the lifetime of an adhesive bond with high accuracy, by taking into account the main influencing factors. First, various lifetime influencing factors are presented. Afterwards, the model approach is extended in regard to the consideration of the important mean stress influence. Finally, the model approach is validated by the comparison of the model‐based lifetime prediction to the one from test data under multiaxial loading.
Continuum Mechanical Modeling of the Inelastic Response of Woven Textile Membranes
Authors: Makhool Lubna , Balzani Daniel 
Published: May 2023

AbstractThis work discusses the derivation and numerical implementation of an elastoplastic model of textile membranes at finite strains. The mechanical model accounts for the anisotropic hyperelastic response [1], reached in the saturation region. The plastic anisotropy is modeled by implementing the yield surface and the flow rule as a function of the structural tensor [2]. Furthermore, the capability of the model to simulate the behavior of textile membranes under non‐proportional cyclic loading is investigated. For this purpose, a fitting procedure to identify the elastic and plastic parameters is presented.
Adaptive mesh refinement using Octree for finite cell simulation and its application for tunneling in saturated soils
Authors: Zendaki Yaman , Meschke Günther 
Published: May 2023

AbstractDuring simulations of complex engineering processes that include the domain evolution in time and space, it is often impossible to predict which regions should have finer numerical discretization in advance. In such cases, adaptive mesh refinement (AMR) can be used to achieve higher accuracy of the solution for as little computational cost as possible. This is achieved by locally refining the mesh only in areas of interest, which leads to a considerable saving in computational and storage requirements in comparison to global refinement [1]. Further, AMR reduces the effort needed by the user to tailor a high‐quality mesh for the specific problem at hand.Tree‐based refinement methods use a recursive encoding scheme and a hierarchical refinement of non‐overlapping elements, making them efficient and simple. These methods also ensure that the quality of the elements will not degrade and provide fine scale adaptivity [2]. Moreover, these methods are highly scalable with low overhead (see, e.g., [3]). The P4est library manages the AMR topology and uses tree‐based refinement to create a forest of octrees. It is also designed to work in parallel and scale well to a high number of processor cores. Hanging nodes resulting from bisection refinement are handled using constraints with the master‐slave elimination method. Data storage and data transfer between meshes are also handled.The effectiveness of the proposed framework is demonstrated by large scale simulations of the tunneling process in two‐phase soft soils [4]. A structured grid is used together with AMR to create meshes for arbitrary tunnel alignments which substantially reduces preprocessing time. The soil domain is modeled using the Finite Cell method (FCM) with a non‐boundary conforming mesh while the other tunneling components are modeled using a boundary fitted mesh.
Numerical Investigation of the Corrosion and Fatigue Behavior of Clinched Joints
Authors: Harzheim Sven , Hofmann Martin , Wallmersperger Thomas 
Published: May 2023

AbstractThe application area of clinched joints is steadily increasing. They are vastly used in the automotive industry to join car body parts. Clinched components are often exposed to different environmental conditions as well as cyclic mechanical loading. Those environments are common originators of multiple corrosion and material fatigue phenomena. It is thus important to include possible environmental factors into the design of the joining process, to ensure full functionality of the clinched joint during its service life. In order to estimate material failure in such joints, several experimental and numerical tools are available. However, the literature provides little knowledge about the combined influence of corrosion and high‐cycle fatigue on the service life of clinched joints. In this work, a modeling framework is given that combines the effects of corrosion products formation on the fatigue life of clinched EN AW‐6014/HCT590X+Z joints by means of numerical simulations.
Convergence study for composite gas flow in pipes
Authors: Nayak Ashwin S. , Grundel Sara 
Published: May 2023

AbstractUtilizing hydrogen in energy sources plays a crucial step towards a complete transition to renewable energies since production at‐scale is possible. The study works towards developing monitoring and control strategies of proportionally induced hydrogen in existing pipeline infrastructure. With this aim, a scalable model is utilized to compute the flow of composite gas along a pipe. The transient model is solved using finite element discretization and error convergence is studied for a test case. Coupling of species transport to track mixture composition along the pipe is also studied for a test case and error behaviors are investigated. Finally, simulations performed for a practical testcase are compared with a recently available open‐source tool for studying flow dynamics. The study highlights the deployment and usage of state‐of‐the‐art simulation tools against existing industrial necessities while providing invaluable insights into dynamics of gas mixtures.
Reduced order fluid modeling with generative adversarial networks
Authors: Kemna Mirko , Heinlein Alexander , Vuik Cornelis 
Published: May 2023

AbstractSurrogate models based on convolutional neural networks (CNNs) for computational fluid dynamics (CFD) simulations are investigated. In particular, the flow field inside two‐dimensional channels with a sudden expansion and an obstacle is predicted using an image representation of the geometry as the input. Generative adversarial neural networks (GANs) have been shown to excel at such image‐to‐image translation tasks. This motivates the focus of this work on investigating the specific effect of adversarial training on model performance. Numerical results show that the overall accuracy of the GANs is generally lower compared to an identical generator model trained directly on the ground truth using an L1 data loss. On the other hand, GAN predictions are often visually more convincing and exhibit a lower continuity residual.
Application of a microplane damage model for concrete to an isogeometric scaled boundary formulation for 3D solids
Authors: Kikis Georgia , Mester Leonie , Chudoba Rostislav , Klinkel Sven 
Published: May 2023

AbstractMicroplane models have the advantage of describing damage‐induced anisotropy, which is common in quasi‐brittle materials such as concrete, in a simple and straightforward way. Over the past decades, various microplane models have been formulated to describe different loading cases and phenomena in concrete structures. They include pure damage and pure plasticity based microplane models or a combination of these two approaches. In this work, as a first step, a microplane damage model, which is derived from the principle of energy equivalence, is applied in the framework of an isogeometric 3D solid in boundary representation. Isogeometric analysis has the advantage that it can represent exactly complex geometries, which can influence the correct description of damage evolution. In addition, the use of a boundary representation in combination with NURBS and B‐splines is in accordance with the modeling technique common in CAD and allows for a straightforward application of the design model to the analysis process. The boundary is described using bi‐variate NURBS while the interior of the solid is approximated using uni‐variate B‐splines. The combination of isogeometric analysis with a model that can capture the finely distributed cracking of the concrete matrix represents a modeling strategy that can effectively support the development of thin‐walled shell structures made of textile‐reinforced concrete. Several examples are studied in order to investigate the ability of the microplane damage model to correctly describe quasi‐brittle fracture in this kind of non‐standard discretization formulation. Furthermore, a comparison to the standard finite element method is conducted.
Internal prestressing of ultra‐high performance concrete using shape memory fibers
Authors: Descher Stefan , Krooß Philipp , Kuhl Detlef , Wetzel Alexander , Wolf Sebastian 
Published: May 2023

AbstractUsing shape memory fibers to reinforce concrete is a novel concept in civil engineering. Pre‐stretched fibers are brought into concrete and after activating the shape memory effect, a compressive prestress state is introduced. The present work investigates this method numerically. A brief introduction to the relevant behavior of shape memory alloys is given. Fiber activation is modeled by an empirical phase transition model. Simulations are carried out by applying the Finite Element Method to solve the CAUCHY‐FOURIER equations. Results of studies are presented for single‐fiber, improved single‐fiber and multi‐fiber configurations. Special focus is put on the geometric type of strain release. Key findings are that compressive stresses can be introduced into the concrete, however, local tension will occur. By altering the fiber geometry and applying an elastomeric coating, these regions can be eliminated. Furthermore, when using multiple fibers, there are synergies between regions of compression.
A model order reduction technique for the linearised compressible flow equations
Authors: Toth Florian , Luo Likun 
Published: May 2023

AbstractViscous effects in acoustics are significant if the thickness of the oscillating viscous boundary layer (Stokes boundary layer) becomes comparable to characteristic problem dimensions. For air as an acoustic medium, this is frequently the case in small‐scale devices like micro‐electro‐mechanical systems or micro‐perforated panels for sound absorption. Accurate modelling of viscous effects can be done by the solution of the linearised compressible flow equations by the finite element method, which is computationally demanding due to the high number of unknowns arising in the problem: pressure, velocity and temperature. Furthermore, the discretisation must resolve the thin viscous boundary layers, creating a model with a high number of degrees of freedom. We suggest a projection‐based model order reduction procedure using the system eigenmodes as generalised coordinates. The procedure is tested based on a simple example problem in 2D. Here we show that the derived reduced order model is accurate and computationally highly efficient. The number of degrees of freedom can be reduced by several orders of magnitude, from around 30 000 to 100, thereby dramatically reducing the computation time for harmonic solutions.
Towards the evaluation of heat and mass transfer in pipe flows with cocurrent falling films using One‐Dimensional Turbulence
Authors: Medina Méndez Juan A. , Schmidt Heiko 
Published: May 2023

AbstractTurbulent mixed convection in an air‐water system is evaluated with a novel numerical solver implementing the stochastic One‐Dimensional Turbulence (ODT) model in a turbulent air flow surrounded by a laminar cocurrent water falling film in a cylindrical geometry. The ODT model is used as a reduced order surrogate model for the effects of turbulent advection, turbulent heat flux, and turbulent mass‐flux within a one‐dimensional domain. An ad‐hoc temporal‐to‐spatial transformation relying on the bulk flow gas velocity is used to obtain streamwise‐dependent statistics of the flow. The ODT simulation results are compared to simulations obtained with the assumption of a quasi‐laminar one‐dimensional gas flow, and to Reynolds‐Averaged Navier‐Stokes (RANS) reference data for a cocurrent water falling film evaporator [1]. The results show that the turbulent transport plays a decisive role in the estimation of interface gradients of temperature and vapor mass fraction. Although ODT predicts global quantities such as the interface temperature in a reasonable way, the model falls short of successfully predicting streamwise‐dependent radial profiles. Despite the shortcomings, the framework presented here is the first stepping stone towards the evaluation of complex multiphase momentum, mass, and heat transfer couplings with full scale resolution on potential evaporative devices. The model, thus, provides valuable information with minimal empiricism on the dynamics of the small scales for pioneering engineering applications.
Application of back propagation neural networks and random forest algorithms in material research of hydrogels
Authors: Wang Yawen , Wallmersperger Thomas , Ehrenhofer Adrian 
Published: May 2023

AbstractIn the fourth paradigm of science, which is data‐driven discovery, the big data collected from the first three paradigms can be analyzed to gain information of the research object. Especially in the field of material science, various big data‐driven methods are applied in the tasks, such as material detection, material analysis and material design. In the current research, we focus on how data‐driven methods, e.g., machine learning algorithms, play a big role in deciphering processing‐properties‐performance (PPP) relationships in hydrogels. We present the procedure of (i) normalization of hydrogel properties, (ii) feature engineering of hydrogels, which is to summarize the decisive features in each PPP section of hydrogels, and (iii) database building by data extraction from scientific literature of hydrogels. Finally, we select the two most promising machine learning algorithms, back propagation neural network and random forest algorithm. The back propagation neural network can contribute to prediction of hydrogels properties and the random forest algorithm can be applied to obtain deeper understanding of hydrogels in the early stage of the research.
Computational model for the semi‐analytical assessment of the free‐edge effect in composite laminated shells
Authors: Kappel Andreas , Mittelstedt Christian 
Published: May 2023

AbstractThe development of efficient computational models for the accurate prediction of the state variables in general composite laminated shells undergoing uniform edge loadings is a major challenge, especially when stress concentration phenomena such as the free‐edge effect have to be considered. This paper addresses this issue by introducing a higher‐order semi‐analytical approach for the assessment of the three‐dimensional stress field in circular cylindrical composite shells with arbitrary layups subjected to a uniform bending moment. The presented semi‐analytical approach combines a closed‐form analytical plane‐strain solution with a higher‐order layerwise approach, and the governing equations are derived by virtue of the principle of minimum elastic potential. The resulting system of coupled ordinary differential equations is then solved by means of the state‐space approach and the free constants are determined by evaluating the boundary conditions at the traction‐free edges. A comparison of the numerical results of the presented semi‐analytical method with finite element simulations for various composite laminates indicates that the developed method works with high accuracy, although being extremely efficient in terms of computational resources.
Model order reduction via substructuring for a nonlinear, differential‐algebraic machine tool model with moving loads
Authors: Aumann Quirin , Benner Peter , Saak Jens , Vettermann Julia 
Published: May 2023

AbstractMachine tools are permanently exposed to complex static, dynamic and thermic loads. This often results in an undesired displacement of the tool center point (TCP), causing errors in the production process and thus limiting the achievable workpiece quality. Recent research efforts try to counter these effects by process‐parallel solutions utilizing machine internal data. Therefore, fast simulation models are a fundamental requirement. Here, model order reduction (MOR) becomes crucial. The resulting low‐dimensional models are required for various applications, e.g., in digital twins, the correction of thermally induced errors at the TCP during the production process as well as for lifetime calculations in predictive maintenance. In this contribution, we present a strategy of MOR for a coupled thermo‐mechanical model with a nonlinear subsystem and moving loads, using the example of a feed axis with nonlinear machine components. Applying tailored substructuring techniques, we are able to separate the linear and nonlinear system components. This allows to apply classic linear MOR methods to the much larger linear part, whereas the small nonlinear part is kept, and thus enables drastically reduced computing times. The relative movement is considered by a switched system approach. Transient thermo‐mechanical interactions of the feed axis are calculated in a final investigation, comparing the performance of the resulting reduced‐order model and the original one.
Relaxed Incremental Formulations for Damage at Finite Strains Including Strain Softening
Authors: Köhler Maximilian , Neumeier Timo , Peterseim Daniel , Peter Malte A. , Balzani Daniel 
Published: May 2023

AbstractRelaxation is a promosing technique to overcome mesh‐dependency in computational damage mechanics originating from the non‐convexity of an underlying incremental variational formulation. This technique does not require an internal length scale parameter. However, in case of damage formulations, for many years the decrease of stresses with an increase of strains, referred to as strain‐softening, could not be modeled in the relaxed regime. This contribution discusses several possibilities of relaxation that lead to suitable models for stress‐ and strain‐softening.
Stiffness pairing in soft‐hard active‐passive actuators
Authors: Ehrenhofer Adrian 
Published: May 2023

AbstractSoft‐Hard Active‐Passive Embedded Structures (SHAPES) are composites that respond to the environments in which they are embedded. This reaction can be a mechanical actuation, but also an intrinsic computation that yields an adaptation as a result. The actuation capabilities primarily depend on the stiffness combination of the involved materials. Stiffness includes both material parameters (depending on the chosen material model, e.g., the Young's modulus) and geometry parameters (depending on the type of structure, e.g., the beam height). The active properties can be included using the Stimulus Expansion Model, which is based on the analogy of the active reponse to thermal expansion. SHAPES can be designed according to three different behaviors, Case Iconstrained, Case IIcombinedand Case IIIfree. In the current work, these cases, the modelling and design background, and various examples are presented.
Mechanical performance of carbon fiber‐reinforced polymer cellular structures manufactured via fused filament fabrication
Authors: Kepenekci Mehmet , Gharehpapagh Bahar , Yaman Ulas , Özerinç Sezer 
Published: May 2023

AbstractThis article investigates the mechanical behavior of polyamide and carbon fiber‐reinforced (CFR) polyamide structures produced by Fused Filament Fabrication. CFR improves solid polyamide's tensile strength and modulus by more than 200% and 800%, respectively. The enhancement is highest in the parallel raster due to the alignment of the fibers in the printing direction. The compression tests of gyroid, honeycomb, and Voronoi cellular structures revealed the effect of geometry and fiber reinforcement on energy absorption performance. CFR gyroid infill offers the best performance with a specific energy absorption capacity reaching 10 kJ/kg and an efficiency close to 50%. Fiber reinforcement improves energy absorption by a factor of four or higher while increasing the weight by only 10%. The energy absorption capacity of the reinforced polyamide offers enormous potential for developing new lightweight load‐bearing and impact‐absorbing structures.