@article{63616, author = {{Gude, Maik and Meschut, Gerson and Flügge, Wilko and Fröck, Linda and Wald, Christopher and Neßlinger, Vanessa and Dobrindt-Tittmann, Karsten and Troschitz, Juliane and Neubert, Fynn and Hofmann, Martin and Ostwald, Richard and Mathiszik, Christian and Schmale, Hans Christian and Wallmersperger, Thomas and Grundmeier, Guido}}, issn = {{0143-7496}}, journal = {{International Journal of Adhesion and Adhesives}}, publisher = {{Elsevier BV}}, title = {{{Corrosion of adhesively bonded alloys in maritime environments: A review}}}, doi = {{10.1016/j.ijadhadh.2026.104264}}, volume = {{147}}, year = {{2026}}, } @article{63676, abstract = {{ Purpose The purpose of this paper is to develop new methods of error representation to improve the accuracy and numerical efficiency of a posteriori and goal-oriented adaptive framework of elastoplasticity with Prandtl–Reuss type material laws. Design/methodology/approach To obtain new methods of error representation for a posteriori and goal-oriented error estimators, weak forms of primal and dual problems are investigated starting with the initial boundary value problem (IBVP). Then, we approximate both problems using temporal discretization. Additionally, we introduce a secant form considering the nonlinearity of elasto-plastic constitutive equations, which is approximated by a tangent form. Finally, we obtain numerical primal and dual solutions and their corresponding error approximations of discretized primal and dual problems, allowing to build several goal-oriented a posteriori error estimators on temporal and spatial adaptive refinement by inserting primal solutions, dual solutions and their error approximations as arguments in residuals of both weak forms as well as in the secant form of the bilinear residual. Findings An elasto-plastic material is investigated in a framework of goal-oriented error estimator by using separately several methods of error representation to deal with either temporal or spatial adaptive refinement, as well as with both refinements leading to an effective reduction of computational effort. Specifically, new error representations based on goal-oriented error estimators are presented and obtained from primal and dual residuals, which use only primal solutions or only dual solutions or a combination of primal and dual solutions as arguments. Error representations obtained from primal residuals and evaluated using only primal arguments do not require the formulation of a dual problem. Research limitations/implications The effectiveness of the different proposed methods is illustrated by an example of a perforated sheet for adaptive spatial refinement where new mesh adaptation methods of error representation are compared against existing mesh adaptation methods such as uniform mesh refinement, mesh refinement based on gradient indicators and adjoint-based methods in literature. The framework generates a balanced mesh consisting of fine, medium and coarse elements for accurate results, avoiding a numerically costly simulation with only fine elements. Originality/value All new proposed methods of error representation successfully estimate actual errors during mesh adaptivity. Furthermore, the proposed methods of error representation allow us to obtain significant reduction and equidistribution of spatial error at the end of the mesh adaptivity process. Their application to a framework of goal-oriented error estimation due to time and mesh adaptivity remains an open issue. }}, author = {{Tchomgue Simeu, Arnold and Caylak, Ismail and Ostwald, Richard}}, issn = {{0264-4401}}, journal = {{Engineering Computations}}, pages = {{1--40}}, publisher = {{Emerald}}, title = {{{Error representations for goal-oriented a posteriori error estimation in elasto-plasticity with applications to mesh adaptivity}}}, doi = {{10.1108/ec-12-2023-0975}}, year = {{2026}}, } @article{64187, abstract = {{Carbon fiber-reinforced plastics (CFRPs) have become increasingly significant in recent decades due to their remarkable mechanical properties and lightweight nature. This study aims to advance the understanding and simulation of CFRP behavior through the development of a hyperelastic-plastic-damage homogenization method combined with mean-field theory. The material responses of both the fiber and matrix are modeled using strain energy functions that account for damage evolution, while a complete linearization of the homogenization process is derived to ensure the consistent implementation of the Newton–Raphson iteration scheme in large deformation simulations. The innovative aspect of this work lies in the constitutive linearization for the hyperelastic-plastic-damage formulation within a mean-field homogenization framework, providing an efficient Newton algorithm for modeling the nonlinear behavior of CFRP. A failure criterion for the hyperelastic model of fibers is introduced, along with a damage saturation variable in rate form for the matrix, effectively capturing damage evolution. Through discrete formulations for the homogenization, the proposed model’s capability is demonstrated via three numerical examples and validated against experimental investigations, proving its effectiveness and reliability in simulating CFRP damage.}}, author = {{Zhan, Yingjie and Caylak, Ismail and Ostwald, Richard and Mahnken, Rolf and Barth, Enrico and Uhlmann, Eckart}}, issn = {{1081-2865}}, journal = {{Mathematics and Mechanics of Solids}}, publisher = {{SAGE Publications}}, title = {{{A fully implicit mean-field damage formulation with consistent linearization at large deformations}}}, doi = {{10.1177/10812865261420809}}, year = {{2026}}, } @article{63821, author = {{Gude, Maik and Meschut, Gerson and Flügge, Wilko and Fröck, Linda and Wald, Christopher and Neßlinger, Vanessa and Dobrindt-Tittmann, Karsten and Troschitz, Juliane and Neubert, Fynn Lucas and Hofmann, Martin and Ostwald, Richard and Mathiszik, Christian and Schmale, Hans Christian and Wallmersperger, Thomas and Grundmeier, Guido}}, issn = {{0143-7496}}, journal = {{International Journal of Adhesion and Adhesives}}, publisher = {{Elsevier BV}}, title = {{{Corrosion of adhesively bonded alloys in maritime environments: A review}}}, doi = {{10.1016/j.ijadhadh.2026.104264}}, volume = {{147}}, year = {{2026}}, } @article{63665, author = {{Gude, Maik and Meschut, Gerson and Flügge, Wilko and Fröck, Linda and Wald, Christopher and Neßlinger, Vanessa and Dobrindt-Tittmann, Karsten and Troschitz, Juliane and Neubert, Fynn and Hofmann, Martin and Ostwald, Richard and Mathiszik, Christian and Schmale, Hans Christian and Wallmersperger, Thomas and Grundmeier, Guido}}, issn = {{0143-7496}}, journal = {{International Journal of Adhesion and Adhesives}}, publisher = {{Elsevier BV}}, title = {{{Corrosion of adhesively bonded alloys in maritime environments: A review}}}, doi = {{10.1016/j.ijadhadh.2026.104264}}, volume = {{147}}, year = {{2026}}, } @article{65037, abstract = {{ABSTRACT Homogenization methods simulate heterogeneous materials like composites effectively, but high computational demands can offset their benefits. This work balances accuracy and efficiency by assessing model and discretization errors of the finite element method (FEM) through an adaptive numerical scheme. Two model hierarchies are introduced, combining mean‐field and full‐field methods, and nonuniform transformation field analysis (NTFA) with full‐field methods. Both hierarchies use a full‐field FEM solution of the representative volume element (RVE) as reference. The study highlights the benefits of using effective constitutive equations from mean‐field and full‐field methods as well as NTFA methods, with a goal‐oriented a posteriori error estimator based on duality techniques controlling mesh and model errors in a forwards‐in‐time manner.}}, author = {{Simeu, Arnold Tchomgue and Caylak, Ismail and Ostwald, Richard}}, issn = {{0029-5981}}, journal = {{International Journal for Numerical Methods in Engineering}}, number = {{6}}, publisher = {{Wiley}}, title = {{{Mesh and Model Adaptivity for Multiscale Elastoplastic Models With Prandtl‐Reuss Type Material Laws}}}, doi = {{10.1002/nme.70294}}, volume = {{127}}, year = {{2026}}, } @article{65266, abstract = {{ABSTRACT This work is concerned with the modeling of a cold‐box sand, a composition of sand grains and a resin binder. To this end, experiments are performed, which show the following characteristics: localization phenomena in the form of a shear band, softening behavior in the force‐displacement curve, and asymmetric behavior for compression and tension. To model this complex material behavior, a micromorphic continuum is used. In the present contribution, we focus on the linear‐elastic regime and demonstrate the identifiability of micromorphic material parameters under deliberately induced inhomogeneous deformation states. In addition to the degrees of freedom of a classical continuum, the micromorphic model has additional degrees of freedom, introduced here in a phenomenological sense to represent kinematically enriched deformation modes associated with the granular microstructure. Accordingly, the micromorphic fields are not interpreted as a separate physical scale (e.g., “binder” vs. “grains”), but as an effective continuum description at the specimen scale. This contribution addresses parameter identification for a micromorphic model of cold‐box sand, with a clear separation between homogeneous deformation states governing classical elastic parameters and inhomogeneous states required to activate and identify micromorphic length‐scale parameters. The main challenge lies in identifying the micro material parameters. To determine these, the corresponding gradient terms in the constitutive formulation must be triggered via properly tuned experiments. Micro‐parameter identification is demonstrated using synthetic data generated from a boundary‐value problem with inhomogeneous displacement fields. The chosen benchmark enables controlled activation of gradient terms and thereby renders optimization‐based identification of micromorphic parameters feasible. The synthetic example is deliberately chosen to assess feasibility and identifiability under controlled conditions, thereby isolating micromorphic identifiability aspects from experimental uncertainties. The novelty of the contribution lies in explicitly linking micromorphic parameter identifiability to kinematic inhomogeneity, and in demonstrating this link within a tractable forward– inverse setting for a linear‐elastic micromorphic continuum.}}, author = {{Börger, Alexander and Mahnken, Rolf and Caylak, Ismail and Ostwald, Richard}}, issn = {{1617-7061}}, journal = {{Proceedings in Applied Mathematics and Mechanics}}, number = {{2}}, publisher = {{Wiley}}, title = {{{Aspects of Parameter Identification for a Micromorphic Continuum applied to a Cold‐Box Sand}}}, doi = {{10.1002/pamm.70093}}, volume = {{26}}, year = {{2026}}, } @article{61138, author = {{Zhan, Yingjie and Caylak, Ismail and Ostwald, Richard and Barth, Enrico and Uhlmann, Eckart}}, issn = {{2520-8160}}, journal = {{Multiscale and Multidisciplinary Modeling, Experiments and Design}}, number = {{10}}, publisher = {{Springer Science and Business Media LLC}}, title = {{{Damage-incorporated four-step mean-field method for simulating CFRP machining: a novel algorithmic approach}}}, doi = {{10.1007/s41939-025-01026-4}}, volume = {{8}}, year = {{2025}}, } @article{63662, abstract = {{The accurate prediction of crack initiation and propagation is essential for assessing the structural integrity of mechanically joined components and other complex assemblies. To overcome the limitations of existing finite element tools, a modular Python framework has been developed to automate three-dimensional crack growth simulations. The program combines geometric reconstruction, adaptive remeshing, and the numerical evaluation of fracture mechanics parameters within a single, fully automated workflow. The framework builds on open-source components and remains solver-independent, enabling straightforward integration with commercial or research finite element codes. A dedicated sequence of modules performs all required steps, from mesh separation and crack insertion to local submodeling, stress and displacement mapping, and iterative crack-front update, without manual interaction. The methodology was verified using a mini-compact tension (Mini-CT) specimen as a benchmark case. The numerical results demonstrate the accurate reproduction of stress intensity factors and energy release rates while achieving high computational efficiency through localized refinement. The developed approach provides a robust basis for crack growth simulations of geometrically complex or residual stress-affected structures. Its high degree of automation and flexibility makes it particularly suited for analyzing cracks in clinched and riveted joints, supporting the predictive design and durability assessment of joined lightweight structures.}}, author = {{Krome, Sven and Duffe, Tobias and Kullmer, Gunter and Schramm, Britta and Ostwald, Richard}}, issn = {{2076-3417}}, journal = {{Applied Sciences}}, number = {{1}}, publisher = {{MDPI AG}}, title = {{{Validation and Verification of Novel Three-Dimensional Crack Growth Simulation Software GmshCrack3D}}}, doi = {{10.3390/app16010384}}, volume = {{16}}, year = {{2025}}, } @misc{63764, author = {{Weiß, Deborah and Krome, Sven and Duffe, Tobias and Kullmer, Gunter and Ostwald, Richard}}, publisher = {{LibreCat University}}, title = {{{Experimentelle Ermittlung von Rissablenkungswinkeln bei außerphasiger Mixed-Mode-Belastung mittels einer neuartigen Probengeometrie}}}, doi = {{https://doi.org/10.48447/BR-2025-490}}, year = {{2025}}, } @misc{65221, author = {{Kullmer, Gunter and Weiß, Deborah and Duffe, Tobias and Schramm, Britta and Ostwald, Richard}}, publisher = {{LibreCat University}}, title = {{{BESCHREIBUNG DES R- UND DES TEMPERATUREINFLUSSES SOWIE DES EINLAUFVERHALTENS BEI EXPERIMENTELL BESTIMMTEN RISSFORTSCHRITTSKURVEN MIT DEM EXPONENTIALANSATZ}}}, doi = {{https://doi.org/10.48447/BR-2025-492}}, year = {{2025}}, } @article{58309, abstract = {{This study evaluates four widely used fracture simulation methods, comparing their computational expenses and implementation complexities within the finite element (FE) framework when employed on heterogeneous solids. Fracture methods considered encompass the intrinsic cohesive zone model (CZM) using zero-thickness cohesive interface elements (CIEs), the standard phase-field fracture (SPFM) approach, the cohesive phase-field fracture (CPFM) approach, and an innovative hybrid model. The hybrid approach combines the CPFM fracture method with the CZM, specifically applying the CZM within the interface zone. The finite element model studied is characterized by three specific phases: inclusions, matrix, and the interface zone. This case study serves as a potential template for meso- or micro-level simulations involving a variety of composite materials. The thorough assessment of these modeling techniques indicates that the CPFM approach stands out as the most effective computational model, provided that the thickness of the interface zone is not significantly smaller than that of the other phases. In materials like concrete, which contain interfaces within their microstructure, the interface thickness is notably small when compared to other phases. This leads to the hybrid model standing as the most authentic finite element model, utilizing CIEs within the interface to simulate interface debonding. A significant finding from this investigation is that within the CPFM method, for a specific interface thickness, convergence with the hybrid model can be observed. This suggests that the CPFM fracture method could serve as a unified fracture approach for multiphase materials when a specific interfacial thickness is used. In addition, this research provides valuable insights that can advance efforts to fine-tune material microstructures. An investigation of the influence of interfacial material properties, voids, and the spatial arrangement of inclusions shows a pronounced effect of these parameters on the fracture toughness of the material.}}, author = {{Najafi Koopas, Rasoul and Rezaei, Shahed and Rauter, Natalie and Ostwald, Richard and Lammering, Rolf}}, issn = {{2076-3417}}, journal = {{Applied Sciences}}, number = {{1}}, publisher = {{MDPI AG}}, title = {{{Comparative Analysis of Phase-Field and Intrinsic Cohesive Zone Models for Fracture Simulations in Multiphase Materials with Interfaces: Investigation of the Influence of the Microstructure on the Fracture Properties}}}, doi = {{10.3390/app15010160}}, volume = {{15}}, year = {{2024}}, } @article{62767, abstract = {{Abstract In this study, we develop a novel multi-fidelity deep learning approach that transforms low-fidelity solution maps into high-fidelity ones by incorporating parametric space information into an autoencoder architecture. This method’s integration of parametric space information significantly reduces the amount of training data needed to effectively predict high-fidelity solutions from low-fidelity ones. In this study, we examine a two-dimensional steady-state heat transfer analysis within a heterogeneous materials microstructure. The heat conductivity coefficients for two different materials are condensed from a 101  $$\times $$ ×  101 grid to smaller grids. We then solve the boundary value problem on the coarsest grid using a pre-trained physics-informed neural operator network known as Finite Operator Learning (FOL). The resulting low-fidelity solution is subsequently upscaled back to a 101  $$\times $$ ×  101 grid using a newly designed enhanced autoencoder. The novelty of the developed enhanced autoencoder lies in the concatenation of heat conductivity maps of different resolutions to the decoder segment in distinct steps. Hence the developed algorithm is named microstructure-embedded autoencoder (MEA). We compare the MEA outcomes with those from finite element methods, the standard U-Net, and an interpolation approach as an upscaling technique. Our analysis shows that MEA outperforms these methods in terms of computational efficiency and error on representative test cases. As a result, the MEA serves as a potential supplement to neural operator networks, effectively upscaling low-fidelity solutions to high-fidelity while preserving critical details often lost in traditional upscaling methods, such as sharp interfaces features lost in the context of interpolation approaches.}}, author = {{Najafi Koopas, Rasoul and Rezaei, Shahed and Rauter, Natalie and Ostwald, Richard and Lammering, Rolf}}, issn = {{0178-7675}}, journal = {{Computational Mechanics}}, number = {{4}}, pages = {{1377--1406}}, publisher = {{Springer Science and Business Media LLC}}, title = {{{Introducing a microstructure-embedded autoencoder approach for reconstructing high-resolution solution field data from a reduced parametric space}}}, doi = {{10.1007/s00466-024-02568-z}}, volume = {{75}}, year = {{2024}}, } @article{62770, abstract = {{AbstractThe open-source parameter identification tool ADAPT (A diversely applicable parameter identification Tool) is integrated with a machine learning-based approach for start value prediction in order to calibrate a Gurson–Tvergaard–Needleman (GTN) and a Lemaitre damage model. As representative example case-hardened steel 16MnCrS5 is elaborated. An artificial neural network (ANN) is initially trained by using load–displacement curves derived from simulations of a boundary value problem—instead of using data generated for homogeneous states of deformation at material point or one-element level—with varying material parameter combinations. The ANN is then employed so as to predict sets of material parameters that already provide close solutions to the experiment. These predicted parameter sets serve as starting values for a subsequent multi-objective parameter identification by using ADAPT. ADAPT allows for the consideration of input data from multiple scales, including integral data such as load–displacement curves, full-field data such as displacement and strain fields, and high-resolution experimental void data at the micro-scale. The influence of each data set on prediction quality is analyzed. Using various types of input data introduces additional information, enhancing prediction accuracy. The validation is carried out with respect to experimental void measurements of forward rod extruded parts. The results demonstrate, by incorporating void measurements in the optimization process, that it is possible to improve the quantitative prediction of ductile damage in the sense of void area fractions by factor 28 in forward rod extrusion.}}, author = {{Gerlach, Jan and Schulte, Robin and Schowtjak, Alexander and Clausmeyer, Till and Ostwald, Richard and Tekkaya, A. Erman and Menzel, Andreas}}, issn = {{0939-1533}}, journal = {{Archive of Applied Mechanics}}, number = {{8}}, pages = {{2217--2242}}, publisher = {{Springer Science and Business Media LLC}}, title = {{{Enhancing damage prediction in bulk metal forming through machine learning-assisted parameter identification}}}, doi = {{10.1007/s00419-024-02634-1}}, volume = {{94}}, year = {{2024}}, } @article{62768, author = {{Najafi Koopas, Rasoul and Rezaei, Shahed and Rauter, Natalie and Ostwald, Richard and Lammering, Rolf}}, issn = {{0013-7944}}, journal = {{Engineering Fracture Mechanics}}, publisher = {{Elsevier BV}}, title = {{{A spatiotemporal deep learning framework for prediction of crack dynamics in heterogeneous solids: Efficient mapping of concrete microstructures to its fracture properties}}}, doi = {{10.1016/j.engfracmech.2024.110675}}, volume = {{314}}, year = {{2024}}, } @article{62771, author = {{Schulte, Robin and Karca, Cavid and Ostwald, Richard and Menzel, Andreas}}, issn = {{0997-7538}}, journal = {{European Journal of Mechanics - A/Solids}}, publisher = {{Elsevier BV}}, title = {{{Machine learning-assisted parameter identification for constitutive models based on concatenated loading path sequences}}}, doi = {{10.1016/j.euromechsol.2022.104854}}, volume = {{98}}, year = {{2022}}, } @article{62773, abstract = {{AbstractA gradient‐enhanced damage model is combined with finite viscoelasticity and implemented in an Abaqus user subroutine, exploiting the heat equation solution capabilities for the damage regularisation, in order to simulate soft polymers. This regularised damage approach provides the advantage of mesh independent results and avoids localisation effects. In this work, a self‐diagnostic poly(dimethylsiloxane) (PDMS) elastomer is chosen as an example. To this end, an efficient two‐step parameter identification framework is developed to calibrate the corresponding model parameters.}}, author = {{Schulte, Robin and Ostwald, Richard and Menzel, Andreas}}, issn = {{1617-7061}}, journal = {{PAMM}}, number = {{1}}, publisher = {{Wiley}}, title = {{{A computational framework for gradient‐enhanced damage – implementation and applications}}}, doi = {{10.1002/pamm.202000215}}, volume = {{20}}, year = {{2021}}, } @article{62772, author = {{Schowtjak, Alexander and Schulte, Robin and Clausmeyer, Till and Ostwald, Richard and Tekkaya, A. Erman and Menzel, Andreas}}, issn = {{0020-7403}}, journal = {{International Journal of Mechanical Sciences}}, publisher = {{Elsevier BV}}, title = {{{ADAPT — A Diversely Applicable Parameter Identification Tool: Overview and full-field application examples}}}, doi = {{10.1016/j.ijmecsci.2021.106840}}, volume = {{213}}, year = {{2021}}, } @article{62777, abstract = {{The simulation of complex engineering components and structures under loads requires the formulation and adequate calibration of appropriate material models. This work introduces an optimisation-based scheme for the calibration of viscoelastic material models that are coupled to gradient-enhanced damage in a finite strain setting. The parameter identification scheme is applied to a self-diagnostic poly(dimethylsiloxane) (PDMS) elastomer, where so-called mechanophore units are incorporated within the polymeric microstructure. The present contribution, however, focuses on the purely mechanical response of the material, combining experiments with homogeneous and inhomogeneous states of deformation. In effect, the results provided lay the groundwork for a future extension of the proposed parameter identification framework, where additional field-data provided by the self-diagnostic capabilities can be incorporated into the optimisation scheme.}}, author = {{Schulte, Robin and Ostwald, Richard and Menzel, Andreas}}, issn = {{1996-1944}}, journal = {{Materials}}, number = {{14}}, publisher = {{MDPI AG}}, title = {{{Gradient-Enhanced Modelling of Damage for Rate-Dependent Material Behaviour—A Parameter Identification Framework}}}, doi = {{10.3390/ma13143156}}, volume = {{13}}, year = {{2020}}, } @article{62778, author = {{Langenfeld, Kai and Schowtjak, Alexander and Schulte, Robin and Hering, Oliver and Möhring, Kerstin and Clausmeyer, Till and Ostwald, Richard and Walther, Frank and Tekkaya, A. Erman and Mosler, Jörn}}, issn = {{0944-6524}}, journal = {{Production Engineering}}, number = {{1}}, pages = {{115--121}}, publisher = {{Springer Science and Business Media LLC}}, title = {{{Influence of anisotropic damage evolution on cold forging}}}, doi = {{10.1007/s11740-019-00942-y}}, volume = {{14}}, year = {{2020}}, }