A comparative study of micromorphic gradient-extensions for anisotropic damage at finite strains

Modern inelastic material model formulations rely on the use of tensor-valued internal variables. When inelastic phenomena include softening, simulations of the former are prone to localization. Thus, an accurate regularization of the tensor-valued internal variables is essential to obtain physically correct results. Here, we focus on the regularization of anisotropic damage at finite strains. Thus, a flexible anisotropic damage model with isotropic, kinematic, and distortional hardening is equipped with three gradient-extensions using a full and two reduced regularizations of the damage tensor. Theoretical and numerical comparisons of the three gradient-extensions yield excellent agreement between the full and the reduced regularization based on a volumetric-deviatoric regularization using only two nonlocal degrees of freedom

Discrete Empirical Interpolation Method for nonlinear softening problems involving damage and plasticity

Accurate simulations are essential for engineering applications, and intricate continuum mechanical material models are constructed to achieve this goal. However, the increasing complexity of the material models and geometrical properties lead to a significant increase in computational effort. Model order reduction aims to implement efficient methods for accelerating the simulation process while preserving a high degree of accuracy. Numerous studies have already demonstrated the benefits of this method for linear elastic material modeling. However, in the present work, we investigate a two-surface gradient-extended damage-plasticity model. We conducted complex simulations with this model, demonstrating both damage behavior and softening. The POD-based discrete empirical interpolation method (DEIM) is introduced and implemented. To accomplish simulations with DEIM and softening behaviour, we propose the implementation of a reduced form of the arc-length method. Existing research on calculating models with both damage and softening behavior using the DEIM and arc-length method is limited. To validate the methods, two numerical examples are thoroughly investigated in this study: a plate with a hole and an asymmetrically notched specimen. The results show that the proposed methods can create a reduced order model with high accuracy and a significant speedup of the simulation. For both examples, the analysis is conducted in three steps: first, plasticity without damage is examined, followed by damage without plasticity, and finally, the combination of plasticity and damage is investigated.Comment: 44 pages, 28 figures, 2 tables, 3 algorithm

Theory and implementation of inelastic Constitutive Artificial Neural Networks

Nature has always been our inspiration in the research, design and development of materials and has driven us to gain a deep understanding of the mechanisms that characterize anisotropy and inelastic behavior. All this knowledge has been accumulated in the principles of thermodynamics. Deduced from these principles, the multiplicative decomposition combined with pseudo potentials are powerful and universal concepts. Simultaneously, the tremendous increase in computational performance enabled us to investigate and rethink our history-dependent material models to make the most of our predictions. Today, we have reached a point where materials and their models are becoming increasingly sophisticated. This raises the question: How do we find the best model that includes all inelastic effects to explain our complex data? Constitutive Artificial Neural Networks (CANN) may answer this question. Here, we extend the CANNs to inelastic materials (iCANN). Rigorous considerations of objectivity, rigid motion of the reference configuration, multiplicative decomposition and its inherent non-uniqueness, restrictions of energy and pseudo potential, and consistent evolution guide us towards the architecture of the iCANN satisfying thermodynamics per design. We combine feed-forward networks of the free energy and pseudo potential with a recurrent neural network approach to take time dependencies into account. We demonstrate that the iCANN is capable of autonomously discovering models for artificially generated data, the response of polymers for cyclic loading and the relaxation behavior of muscle data. As the design of the network is not limited to visco-elasticity, our vision is that the iCANN will reveal to us new ways to find the various inelastic phenomena hidden in the data and to understand their interaction. Our source code, data, and examples are available at doi.org/10.5281/zenodo.10066805Comment: 54 pages, 14 figures, 14 table

A novel approach for the efficient modeling of material dissolution in electrochemical machining

This work presents a novel approach to efficiently model anodic dissolution in electrochemical machining. Earlier modeling approaches employ a strict space discretization of the anodic surface that is associated with a remeshing procedure at every time step. Besides that, the presented model is formulated by means of effective material parameters. Thereby, it allows to use a constant mesh for the entire simulation and, thus, decreases the computational costs. Based on Faraday's law of electrolysis, an effective dissolution level is introduced, which describes the ratio of a dissolved volume and its corresponding reference volume. This inner variable allows the modeling of the complex dissolution process without the necessity of computationally expensive remeshing by controlling the effective material parameters. Additionally, full coupling of the thermoelectric problem is considered and its linearization and numerical implementation are presented. The model shows good agreement with analytical and experimental validation examples by yielding realistic results. Furthermore, simulations of a pulsed electrochemical machining process yield a process signature of the surface roughness related to the specific accumulated electric charge. The numerical examples confirm the simulation's computational efficiency and accurate modeling qualities

Mechanical modeling of the maturation process for tissue-engineered implants: application to biohybrid heart valves

The development of tissue-engineered cardiovascular implants can improve the lives of large segments of our society who suffer from cardiovascular diseases. Regenerative tissues are fabricated using a process called tissue maturation. Furthermore, it is highly challenging to produce cardiovascular regenerative implants with sufficient mechanical strength to withstand the loading conditions within the human body. Therefore, biohybrid implants for which the regenerative tissue is reinforced by standard reinforcement material (e.g. textile or 3d printed scaffold) can be an interesting solution. In silico models can significantly contribute to characterizing, designing, and optimizing biohybrid implants. The first step towards this goal is to develop a computational model for the maturation process of tissue-engineered implants. This paper focuses on the mechanical modeling of textile-reinforced tissue-engineered cardiovascular implants. First, we propose an energy-based approach to compute the collagen evolution during the maturation process. Then, we apply the concept of structural tensors to model the anisotropic behavior of the extracellular matrix and the textile scaffold. Next, the newly developed material model is embedded into a special solid-shell finite element formulation with reduced integration. Finally, we use our framework to compute two structural problems: a pressurized shell construct and a tubular-shaped heart valve. The results show the ability of the model to predict collagen growth in response to the boundary conditions applied during the maturation process. Consequently, we can predict the implant's mechanical response, such as the deformation and stresses of the implant.Comment: Preprint submitted to Elsevie

A gradient-extended anisotropic damage-plasticity model in the logarithmic strain space

Within this contribution, we discuss additional theoretical as well as numerical aspects of the material model developed in [1, 2], where a `two-surface' damage-plasticity model is proposed accounting for induced damage anisotropy by means of a second order damage tensor. The constitutive framework is stated in terms of logarithmic strain measures, while the total strain is additively decomposed into elastic and plastic parts. Moreover, a novel gradientextension based on the damage tensor's invariants is presented using the micromorphic approach introduced in [3]. Finally, going beyond the numerical examples presented in [1, 2], we study the model's ability to cure mesh-dependency in a three-dimensional setup

A novel gradient-extended anisotropic two-surface damage-plasticity model for finite deformations.

A material model to deal with finite plasticity coupled with anisotropic damage will be presented. The presentation addresses mesh regularization problems and a novel approach for using gradient-extension in the context of damage. Since finite strains are considered, the strain measures chosen are logarithmic strains. To give the interested audience an idea of the behavior of the model, numerical examples are used for illustration

A thermo-coupled constitutive model for semi-crystalline polymers at finite strains: Application to varying degrees of crystallinity and temperatures

Thermoplastic materials are widely used for thermoforming and injection moulding processes, since their low density in combination with a high strength to mass ratio are interesting for various industrial applications. Semi-crystalline polymers make up a subcategory of thermoplastics, which partly crystallize after cool-down from the molten state. During the thermoforming process, residual stresses can arise, due to complex material behavior under different temperatures and strain rates. Therefore, computational models are needed to predict the material response and minimize production errors. This work presents a thermomechanically consistent phenomenological material formulation at finite strains, based on [1]. In order to account for the highly nonlinear material behavior, elasto-plastic and visco-elastic contributions are combined in the model formulation. To account for the crystalline regions, a hyperelastic-plastic framework is chosen, based on [2, 3]. Kinematic hardening of Arruda-Boyce form is incorporated in the formulation, as well as associated plastic flow. The material parameters depend on both, the temperature as well as the degree of crystallinity. A comparison to experiments with varying degrees of crystallinity and temperatures is presented, where a special blending technique ensures stable crystallinity conditions

Bulge n and B/T in High Mass Galaxies: Constraints on the Origin of Bulges in Hierarchical Models

We use the bulge Sersic index n and bulge-to-total ratio (B/T) to explore the fundamental question of how bulges form. We perform 2D bulge-disk-bar decomposition on H-band images of 143 bright, high stellar mass (>1.0e10 solar masses) low-to-moderately inclined (i<70 degrees) spirals. Our results are: (1) Our H-band bar fraction (~58%) is consistent with that from ellipse fits. (2) 70% of the stellar mass is in disks, 10% in bars, and 20% in bulges. (3) A large fraction (~69%) of bright spirals have B/T<0.2, and ~76% have low n<2 bulges. These bulges exist in barred and unbarred galaxies across a wide range of Hubble types. (4) About 65% (68%) of bright spirals with n<2 (B/T<0.2) bulges host bars, suggesting a possible link between bars and bulges. (5) We compare the results with predictions from a set of LCDM models. In the models, a high mass spiral can have a bulge with a present-day low B/T<0.2 only if it did not undergo a major merger since z<2. The predicted fraction (~1.6%) of high mass spirals, which have undergone a major merger since z<4 and host a bulge with a present-day low B/T<0.2, is a factor of over thirty smaller than the observed fraction (~66%) of high mass spirals with B/T<0.2. Thus, contrary to common perception, bulges built via major mergers since z<4 seriously fail to account for the bulges present in ~66% of high mass spirals. Most of these present-day low B/T<0.2 bulges are likely to have been built by a combination of minor mergers and/or secular processes since z<4.Comment: Accepted by the Astrophysical Journal. 42 pages of text, 27 figures, 12 table

EGASP: the human ENCODE Genome Annotation Assessment Project

Background: Non-long terminal repeat (non-LTR) retrotransposons have contributed to shaping the structure and function of genomes. In silico and experimental approaches have been used to identify the non-LTR elements of the urochordate Ciona intestinalis. Knowledge of the types and abundance of non-LTR elements in urochordates is a key step in understanding their contribution to the structure and function of vertebrate genomes. Results: Consensus elements phylogenetically related to the I, LINE1, LINE2, LOA and R2 elements of the 14 eukaryotic non-LTR clades are described from C. intestinalis. The ascidian elements showed conservation of both the reverse transcriptase coding sequence and the overall structural organization seen in each clade. The apurinic/apyrimidinic endonuclease and nucleic-acid-binding domains encoded upstream of the reverse transcriptase, and the RNase H and the restriction enzyme-like endonuclease motifs encoded downstream of the reverse transcriptase were identified in the corresponding Ciona families. Conclusions: The genome of C. intestinalis harbors representatives of at least five clades of non-LTR retrotransposons. The copy number per haploid genome of each element is low, less than 100, far below the values reported for vertebrate counterparts but within the range for protostomes. Genomic and sequence analysis shows that the ascidian non-LTR elements are unmethylated and flanked by genomic segments with a gene density lower than average for the genome. The analysis provides valuable data for understanding the evolution of early chordate genomes and enlarges the view on the distribution of the non-LTR retrotransposons in eukaryotes