@article{64251, abstract = {{ABSTRACT Clinching is a widely adopted joining technique in the automotive industry, enabling the fabrication of lightweight structures from dissimilar sheet materials. Accurate prediction of the fatigue life of clinched joints is essential for ensuring structural safety and minimizing development costs. However, full 3D fatigue simulations over millions of cycles are computationally intensive due to the complexity of contact mechanics. This study introduces a 2D numerical model that circumvents direct contact modeling by applying a slip condition at the sheet interface, significantly reducing computational demands. A micro‐slip friction model is used to represent the mechanical interface behavior, while a two‐scale damage model captures the fatigue damage evolution. The model is validated against experimental data and used to investigate the influence of friction coefficient and tangential contact stiffness on fatigue life, highlighting its efficiency and predictive capability.}}, author = {{Chen, Chin and Hofmann, Martin and Wallmersperger, Thomas}}, issn = {{1617-7061}}, journal = {{PAMM}}, number = {{1}}, publisher = {{Wiley}}, title = {{{A 2D Approach to Predict the High‐Cycle Fatigue Life of Clinched Joints}}}, doi = {{10.1002/pamm.70035}}, volume = {{26}}, 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{59740, abstract = {{ABSTRACTIn this contribution, we propose an innovative method for determining optimal control sequences for nonlinear systems with partially unknown dynamics, which further expands our previous work. Within the paradigm of model‐based design, the practicality and safety of commissioning feedforward controls and feedback controllers have priority. Our approach leverages probabilistic Gaussian processes to adjust for model inaccuracies from measured system data. This differs from conventional approaches that involve complicated analytical modeling and may entail a substantial time investment to acquire expertise and may prove impractical. Consequently, we address the limitations inherent in traditional design methodologies. Our research focuses on the formulation and solution of the hybrid1 optimal control problem using probabilistic state predictions and multiple shooting. This ensures adaptability, data efficiency, and resilience against uncertainties in system dynamics. These attributes are empirically substantiated through experimental validation on a chaotic and highly sensitive dynamical system—a double pendulum on a cart. Our methodology unfolds as an iterative learning process, systematically exploring diverse controls, accumulating data within each iteration, and refining the control strategy until the desired task is accomplished. The adoption of the two‐degree‐of‐freedom control structure allows for the distinct consideration of the feedforward and the feedback control signal. For the latter, we employ a time‐variant, linear quadratic regulator (LQR) designed to stabilize the system around its target trajectory. Furthermore, we integrate a probabilistic long‐term prediction through the unscented transform, enabling systematic anticipation of safety‐critical violations. Detailed insights into relevant implementation aspects are provided. To ascertain the real‐world applicability, we present an exemplary application involving a double pendulum on a cart. The objective is to bring the pendulum arms from the lower stable to the upper unstable equilibrium by horizontally moving the cart and subsequently stabilize them. In this scenario, we assume that the centrifugal forces, crucial to the system dynamics, have not been accurately modeled and must be learned from data. Solving the control task took only 5 iterations and 1 h of computation time, which surpasses our previous work [2], where we used the purely data‐driven PILCO framework and required 27 iterations and 57 h of computation time. The time of interaction with the system decreased by and the computation time is lowered by . It demonstrates significant practical applicability for commissioning control systems.}}, author = {{Hesse, Michael and Schwarzer, Luis and Timmermann, Julia and Trächtler, Ansgar}}, issn = {{1617-7061}}, journal = {{PAMM}}, number = {{2}}, publisher = {{Wiley}}, title = {{{Robust and Efficient Hybrid Optimal Control via Gaussian Process Regression and Multiple Shooting With Experimental Validation on a Double Pendulum on a Cart}}}, doi = {{10.1002/pamm.70004}}, volume = {{25}}, year = {{2025}}, } @article{52217, abstract = {{AbstractPolycarbonate (PC) is an amorphous polymer that is an extremely robust material with a high tenacity, and thus suitable for a lightweight construction with glass‐like transparency. Due to these advantageous properties, PC is often used in industry for example in medical devices, automotive headlamps, sporting equipment, electronics, and a variety of other products. PC is often subjected to uniaxial and biaxial loading conditions. Therefore, reliable material models have to take into account the various resulting experimental effects. For those reasons, we investigate PC specimens under uniaxial and biaxial loading by using different stretch rates and loading scenarios. In addition to that, we propose methods for optical measurement of local stretches to obtain the approximated local true stress. In future work, the displacement fields and the resulting reaction forces will be used for parameter identification of constitutive equations.}}, author = {{Hamdoun, Ayoub and Mahnken, Rolf}}, issn = {{1617-7061}}, journal = {{PAMM}}, keywords = {{Electrical and Electronic Engineering, Atomic and Molecular Physics, and Optics}}, publisher = {{Wiley}}, title = {{{Experimental investigations of uniaxial and biaxial cold stretching within PC‐films and bars using optical measurements}}}, doi = {{10.1002/pamm.202300114}}, year = {{2024}}, } @article{56212, abstract = {{AbstractTo increase the quality of computational results for heterogeneous materials like fiber‐reinforced composites with Prandtl–Reuss‐type material laws, goal‐oriented measures of the adaptive finite element method coupled to model adaptivity is established. The former is an adaptive mesh refinement on the macroscale, which allows to control the spatial discretization errors. The latter is an efficient combination of a numerically low cost nonuniform transformation field analysis (NTFA) and numerically high cost full‐field elasto‐plastic homogenization methods on the microscale. The present contribution deals with the application of the concept of downwind and upwind approximations to a goal‐oriented a posteriori error estimator based on duality techniques by means of reduced order homogenization schemes like NTFA, and with accuracy and numerical efficiency of the proposed goal‐oriented adaptive framework. NTFA consists of an offline phase and an online phase. During the offline phase, some relevant information of the micro system under consideration is precomputed allowing a reduced set of equations to be solved in the online phase. Thus, NTFA leads to a quite efficient homogenization method but less accurate compared to the full‐field homogenization method which is characterized with a high computational demand for accounting nonlinear microstructural mechanisms. Due to nonlinearities and time‐dependency of plasticity, the estimation of error transport and error generation are obtained with a backward‐in‐time dual method despite a high demand on memory capacity. In this contribution, the dual problem is solved with a forward‐in‐time dual method that allows estimating the full error during the resolution of the primal problem without the need for extra memory capacity. Several numerical examples illustrate the effectiveness of the proposed adaptive approach based on downwind and upwind approximations.}}, author = {{Tchomgue Simeu, Arnold and Mahnken, Rolf}}, issn = {{1617-7061}}, journal = {{PAMM}}, publisher = {{Wiley}}, title = {{{Mesh‐ and model adaptivity for NTFA and full‐field elasto‐plastic homogenization based on downwind and upwind approximations}}}, doi = {{10.1002/pamm.202400074}}, year = {{2024}}, } @article{54281, abstract = {{AbstractPolycarbonate (PC) is an amorphous polymer that is an extremely robust material with a high tenacity, and thus suitable for a lightweight construction with glass‐like transparency. Due to these advantageous properties, PC is often used in industry for example in medical devices, automotive headlamps, sporting equipment, electronics, and a variety of other products. PC is often subjected to uniaxial and biaxial loading conditions. Therefore, reliable material models have to take into account the various resulting experimental effects. For those reasons, we investigate PC specimens under uniaxial and biaxial loading by using different stretch rates and loading scenarios. In addition to that, we propose methods for optical measurement of local stretches to obtain the approximated local true stress. In future work, the displacement fields and the resulting reaction forces will be used for parameter identification of constitutive equations.}}, author = {{Hamdoun, Ayoub and Mahnken, Rolf}}, issn = {{1617-7061}}, journal = {{PAMM}}, publisher = {{Wiley}}, title = {{{Experimental investigations of uniaxial and biaxial cold stretching within PC‐films and bars using optical measurements}}}, doi = {{10.1002/pamm.202300114}}, year = {{2024}}, } @article{61412, abstract = {{AbstractMechanical clinching is a frequently used joining method for technical components. These joints are usually weak spots. Here, corrosion and fatigue are decisive influencing factors for the assessment of the service life of such joints. Corrosion generally leads to material deterioration and thus to premature failure of the joints. Under certain circumstances, however, corrosion can lead to an increased fatigue life. While this effect has not yet been fully understood, the present work provides a possible explanation and a modeling approach to predict the fatigue life of precorroded clinched joints. The increased fatigue life is observed when the clinched components are briefly (up to 3 weeks) exposed to a salt spray environment. During this time, a small layer of corrosion products protrudes from the metal surface and fills the gaps between the joined sheets. Due to the increased contact area, the mechanical stress in the joint decreases, resulting in an improved fatigue performance. Although there are a variety of corrosion phenomena, for example, pitting, intergranular, and transgranular corrosion as well as galvanic corrosion, experimental studies indicate that galvanic corrosion is the main contributor of this effect. In the present work, a coupled electro‐chemo‐mechanical corrosion model is presented and applied to two test cases. Case I: corrosion products growth, and Case II: corrosion products growth and mechanical loading.}}, author = {{Harzheim, Sven and Chen, Chin and Hofmann, Martin and Wallmersperger, Thomas}}, issn = {{1617-7061}}, journal = {{PAMM}}, number = {{4}}, publisher = {{Wiley}}, title = {{{Coupled chemo‐electro‐mechanical model for galvanic corrosion in clinched components}}}, doi = {{10.1002/pamm.202400028}}, volume = {{24}}, year = {{2024}}, } @inproceedings{60359, abstract = {{AbstractThe free‐surface lattice Boltzmann method uses a volume of fluid approach to simulate immiscible two‐fluid flow problems. It divides the simulation domain into three distinct phases—gas, fluid, and interface—where computation within the gas phase is disregarded. The interface delineates a one‐cell‐thick layer between the first two phases, validated physically for implementation in the HPC C++ multiphysics framework waLBerla but lacking an exhaustive performance analysis. This paper aims to shed light on node‐level performance on different architectures, employing continuous benchmarking, showing and analyzing weak scaling results on a modern HPC cluster, the Fritz supercomputer, and reporting energy consumption for the current implementation.}}, author = {{Plewinski, Jonas and Alt, Christoph and Köstler, Harald and Rüde, Ulrich}}, booktitle = {{PAMM}}, issn = {{1617-7061}}, number = {{3}}, publisher = {{Wiley}}, title = {{{Performance analysis of the free surface lattice Boltzmann implementation in waLBerla}}}, doi = {{10.1002/pamm.202400196}}, volume = {{24}}, year = {{2024}}, } @article{57893, abstract = {{AbstractControl engineering applications usually require a model that accurately represents the dynamics of the system. In addition to classical physical modeling, powerful data‐driven approaches are gaining popularity. However, the resulting models may not be ideal for control design due to their black‐box structure, which inherently limits interpretability. Formulating the system dynamics in port‐Hamiltonian form is highly beneficial, as its valuable property of passivity enables the straightforward design of globally stable controllers while ensuring physical interpretability. In a recently published article, we presented a method for data‐driven inference of port‐Hamiltonian models for complex mechatronic systems, requiring only fundamental physical prior knowledge. The resulting models accurately represent the nonlinear dynamics of the considered systems and are physically interpretable. In this contribution, we advance our previous work by including two key elements. Firstly, we demonstrate the application of the above described data‐driven PCHD models for controller design. Preserving the port‐Hamiltonian form in the closed loop not only guarantees global stability and robustness but also ensures desired speed and damping characteristics. Since control systems based on output measurements, which are continuously measured during operation due to the feedback structure, we secondly aim to use this data. Thus, we augment the existing modeling strategy with an intelligent adaptation approach to address uncertainties and (un)predictable system changes in mechatronic systems throughout their lifecycle, such as the installation of new components, wear, or temperature fluctuations during operation. Our proposed algorithm for recursively calculated data‐driven port‐Hamiltonian models utilizes a least‐squares approach with extensions such as automatically adjusting the forgetting factor and controlling the covariance matrix trace. We demonstrate the results through model‐based application on an academic example and experimental validation on a test bench.}}, author = {{Junker, Annika and Timmermann, Julia and Trächtler, Ansgar}}, issn = {{1617-7061}}, journal = {{PAMM}}, number = {{1}}, publisher = {{Wiley}}, title = {{{Adaptive Data‐Driven Models in Port‐Hamiltonian Form for Control Design}}}, doi = {{10.1002/pamm.202400154}}, volume = {{25}}, year = {{2024}}, } @article{59051, abstract = {{Model‐based state observers require high‐quality models to deliver accurate state estimates. However, due to time or cost shortage, modeling simplifications or numerical issues, models often have severe inaccuracies that may lead to insufficient and deficient control. Instead of attempting to iteratively model these deviations, we address the challenge by the concept of joint estimation. Thus, we assume a linear combination of suitable functions to approximate the inaccuracies. The parameters of the linear combination are supposed to be time invariant and augment the model's state. Subsequently, the parameters can be identified simultaneously to the states within the observer. Referring to the principle of Occam's razor, the parameters are claimed to be sparse. Our former work shows that estimating states and model inaccuracies simultaneously by a sparsity promoting unscented Kalman filter yields not only high accuracy but also provides interpretable representations of underlying inaccuracies. Based on this work, our contribution is twofold: First, we apply our approach finally on a real‐world test bench, namely a golf robot. Within the experimental setting, we investigate closed loop behavior as well as how suitable functions need to be chosen to approximate the inaccuracies in a physically interpretable way. Results do not only provide high state estimation accuracy but also meaningful insights into the system's inaccuracies. Second, we discuss and establish a method to automatically adapt and update the model based on collected data of the linear combination during operation. Examining past parameter estimates by principal component analysis, a moving window is utilized to extract the most dominant functions. These are kept characterizing the model inaccuracies, while nondominant functions are automatically neglected and refilled with novel function candidates. After analysis and rebuilding, this updated function set is subsequently fed back into the joint estimation loop and deployed for further estimation. Hence, we give a holistic paradigm of how to analyze and combat model inaccuracies while ensuring high state estimation accuracy. Within this setting, we once more investigate closed loop behavior and yield promising results. In conclusion, we show that the proposed observer provides a helpful tool to guarantee high estimation accuracy for models with severe inaccuracies or for situations with occurring deviations during operation, for example, due to mechanical wear or temperature changes.}}, author = {{Götte, Ricarda-Samantha and Timmermann, Julia}}, issn = {{1617-7061}}, journal = {{PAMM}}, number = {{1}}, publisher = {{Wiley}}, title = {{{Online Learning With Joint State and Model Estimation}}}, doi = {{10.1002/pamm.202400080}}, volume = {{25}}, year = {{2024}}, } @article{48464, abstract = {{AbstractInitial value problems can be solved efficiently by means of Runge–Kutta algorithms with adaptive step size control. Diagonally implicit Runge–Kutta (DIRK) methods are the most popular class among the diverse family of Runge–Kutta algorithms. In this paper, the novel class of low‐order explicit last‐stage diagonally implicit Runge–Kutta (ELDIRK) methods are explored, which combine implicit schemes with an additional explicit evaluation as an explicit last stage. ELDIRK Butcher tableaus are used to control embedded RK methods to obtain solutions of different orders. The lower‐order solution is obtained by classical implicit RK stages and the higher‐order solution is obtained by additional explicit evaluation. As a result, a significant reduction in computational cost is achieved by skipping the iterative solution of nonlinear systems for the additional step. The examination of the heat problem and the use of the innovative Butcher tableau in the finite‐element method are the main contributions of this work. Thus, it is possible to establish adaptive step size control for the new low‐order embedded methods based on an empirical method for error estimation. Two‐dimensional simulations are used to show an appropriate algorithm for the ELDIRK schemes. The new Runge–Kutta schemes' predictions of higher‐order convergence are confirmed, and their successful outcomes are illustrated.}}, author = {{Westermann, Hendrik and Mahnken, Rolf}}, issn = {{1617-7061}}, journal = {{PAMM}}, keywords = {{Electrical and Electronic Engineering, Atomic and Molecular Physics, and Optics}}, number = {{2}}, publisher = {{Wiley}}, title = {{{Numerical investigations of new low‐order explicit last stage diagonal implicit Runge–Kutta schemes with the finite‐element method}}}, doi = {{10.1002/pamm.202300071}}, volume = {{23}}, year = {{2023}}, } @article{49866, abstract = {{AbstractThe use of heterogeneous materials, such as composites with Prandtl‐Reuss‐type material laws, has increased in industrial praxis, making finite element modeling with homogenization techniques a well‐accepted tool. These methods are particularly advantageous to account for microstructural mechanisms which can be related to nonlinearities and time‐dependency due to elasto‐plasticity behavior. However, their advantages are diminished by increasing computational demand. The present contribution deals with the balance of accuracy and numerical efficiency of nonlinear homogenization associated with a framework of goal‐oriented adaptivity, which takes into account error accumulation over time. To this end, model adaptivity of homogenization methods is coupled to mesh adaptivity on the macro scale. Our new proposed adaptive procedure is driven by a goal‐oriented a posteriori error estimator based on duality techniques using downwind and upwind approximations. Due to nonlinearities and time‐dependency of the plasticity, the estimation of error transport and error generation is obtained with a backward‐in‐time dual method despite a high demand on memory capacity. In this contribution, the dual problem is solved with a forward‐in‐time dual method that allows estimating the full error during the resolution of the primal problem without the need for extra memory capacity. Finally, a numerical example illustrates the effectiveness of the proposed adaptive approach.}}, author = {{Tchomgue Simeu, Arnold and Mahnken, Rolf}}, issn = {{1617-7061}}, journal = {{PAMM}}, keywords = {{Electrical and Electronic Engineering, Atomic and Molecular Physics, and Optics}}, publisher = {{Wiley}}, title = {{{Downwind and upwind approximations for mesh and model adaptivity of elasto‐plastic composites}}}, doi = {{10.1002/pamm.202300136}}, year = {{2023}}, } @article{52219, abstract = {{AbstractCold‐box sand (CBS) belongs to the granular materials and consists of sand and a binder. The behavior of CBS is simulated with a micropolar model, whereby the additional degree of freedom of the model describes the rotation of the sand grains. The model is used to generate a shear band under pressure for three different meshes, where the force‐displacement curves of the three meshes converge so that no mesh dependence occurs. Another requirement of the model is the consideration of asymmetric behavior for compression and tension. Due to the additional degree of freedom the implicit implementation of the micropolar continuum is very time‐consuming. Therefore, an explicit implementation is considered as an alternative possibility. This paper compares the advantages and disadvantages of both methods and the results for both calculations.}}, author = {{Börger, Alexander and Mahnken, Rolf}}, issn = {{1617-7061}}, journal = {{PAMM}}, keywords = {{Electrical and Electronic Engineering, Atomic and Molecular Physics, and Optics}}, publisher = {{Wiley}}, title = {{{A micropolar model accounting for asymmetric behavior of cold‐box sand in relation to tensile and compression tests}}}, doi = {{10.1002/pamm.202300126}}, year = {{2023}}, } @article{54282, abstract = {{AbstractStretching of polycarbonate films leads to the formation of shear bands in the necking zone [1]. Standard viscoplastic material models render mesh size dependent results, which requires a mathematical regularization. To this end, we present a finite strain gradient theory for a viscoplastic, isotropic material model where we extend the model presented in [2] to a micromorphic model by introducing a new micromorphic variable as an additional degree of freedom with its first gradient [3, 4]. The variable here has the meaning of a micro plastic strain, and is coupled with the macro plastic by a micro penalty term, forcing the macro‐plastic strain to be close to the micro‐plastic strain for the targeted shear band regularization effect. We have implemented the model equations as a three dimensional initial boundary value problem in an in house FE‐tool, to simulate different geometries with different thickness and to compare it the experimental tests. The analysis is performed for a uniaxial tensile geometry as well as for a biaxial tensile geometry. The numerical examples show the ability of the model to regularize the shear bands and solve the problem of localization.}}, author = {{Hamdoun, Ayoub and Mahnken, Rolf}}, issn = {{1617-7061}}, journal = {{PAMM}}, number = {{1}}, publisher = {{Wiley}}, title = {{{A finite strain gradient theory for viscoplasticity by means of micromorphic regularization}}}, doi = {{10.1002/pamm.202200074}}, volume = {{22}}, year = {{2023}}, } @article{44888, author = {{Lenz, Peter and Mahnken, Rolf}}, issn = {{1617-7061}}, journal = {{PAMM}}, keywords = {{Electrical and Electronic Engineering, Atomic and Molecular Physics, and Optics}}, number = {{1}}, publisher = {{Wiley}}, title = {{{Thermo‐chemo‐mechanical modelling of a curing process combined with mean‐field homogenization methods at large strains}}}, doi = {{10.1002/pamm.202200214}}, volume = {{22}}, year = {{2023}}, } @article{44891, author = {{Westermann, Hendrik and Mahnken, Rolf}}, issn = {{1617-7061}}, journal = {{PAMM}}, keywords = {{Electrical and Electronic Engineering, Atomic and Molecular Physics, and Optics}}, number = {{1}}, publisher = {{Wiley}}, title = {{{A thermodynamic framework for the phase‐field approach considering carbide precipitation during phase transformations}}}, doi = {{10.1002/pamm.202200080}}, volume = {{22}}, year = {{2023}}, } @article{44892, author = {{Hamdoun, Ayoub and Mahnken, Rolf}}, issn = {{1617-7061}}, journal = {{PAMM}}, keywords = {{Electrical and Electronic Engineering, Atomic and Molecular Physics, and Optics}}, number = {{1}}, publisher = {{Wiley}}, title = {{{A finite strain gradient theory for viscoplasticity by means of micromorphic regularization}}}, doi = {{10.1002/pamm.202200074}}, volume = {{22}}, year = {{2023}}, } @article{44890, author = {{Tchomgue Simeu, Arnold and Mahnken, Rolf}}, issn = {{1617-7061}}, journal = {{PAMM}}, keywords = {{Electrical and Electronic Engineering, Atomic and Molecular Physics, and Optics}}, number = {{1}}, publisher = {{Wiley}}, title = {{{Goal‐oriented adaptivity based on a model hierarchy of mean‐field and full‐field homogenization methods in elasto‐plasticity}}}, doi = {{10.1002/pamm.202200053}}, volume = {{22}}, year = {{2023}}, } @inproceedings{46813, abstract = {{Modelling of dynamic systems plays an important role in many engineering disciplines. Two different approaches are physical modelling and data‐driven modelling, both of which have their respective advantages and disadvantages. By combining these two approaches, hybrid models can be created in which the respective disadvantages are mitigated, with discrepancy models being a particular subclass. Here, the basic system behaviour is described physically, that is, in the form of differential equations. Inaccuracies resulting from insufficient modelling or numerics lead to a discrepancy between the measurements and the model, which can be compensated by a data‐driven error correction term. Since discrepancy methods still require a large amount of measurement data, this paper investigates the extent to which a single discrepancy model can be trained for a physical model with additional parameter dependencies without the need for retraining. As an example, a damped electromagnetic oscillating circuit is used. The physical model is realised by a differential equation describing the electric current, considering only inductance and capacitance; dissipation due to resistance is neglected. This creates a discrepancy between measurement and model, which is corrected by a data‐driven model. In the experiments, the inductance and the capacity are varied. It is found that the same data‐driven model can only be used if additional parametric dependencies in the data‐driven term are considered as well.}}, author = {{Wohlleben, Meike Claudia and Muth, Lars and Peitz, Sebastian and Sextro, Walter}}, booktitle = {{Proceedings in Applied Mathematics and Mechanics}}, issn = {{1617-7061}}, keywords = {{Electrical and Electronic Engineering, Atomic and Molecular Physics, and Optics}}, publisher = {{Wiley}}, title = {{{Transferability of a discrepancy model for the dynamics of electromagnetic oscillating circuits}}}, doi = {{10.1002/pamm.202300039}}, year = {{2023}}, } @article{21082, author = {{Itner, Dominik and Gravenkamp, Hauke and Dreiling, Dmitrij and Feldmann, Nadine and Henning, Bernd}}, issn = {{1617-7061}}, journal = {{PAMM}}, title = {{{Simulation of guided waves in cylinders subject to arbitrary boundary conditions for applications in material characterization}}}, doi = {{10.1002/pamm.202000232}}, year = {{2021}}, }