TY - JOUR A1 - Strobl, Dominic A1 - Unger, Jörg F. A1 - Ghnatios, C. A1 - Klawoon, Alexander A1 - Pittner, Andreas A1 - Rethmeier, Michael A1 - Robens-Radermacher, Annika T1 - Efficient bead-on-plate weld model for parameter estimation towards effective wire arc additive manufacturing simulation JF - Welding in the World N2 - Despite the advances in hardware and software techniques, standard numerical methods fail in providing real-time simulations, especially for complex processes such as additive manufacturing applications. A real-time simulation enables process control through the combination of process monitoring and automated feedback, which increases the flexibility and quality of a process. Typically, before producing a whole additive manufacturing structure, a simplified experiment in the form of a beadon-plate experiment is performed to get a first insight into the process and to set parameters suitably. In this work, a reduced order model for the transient thermal problem of the bead-on-plate weld simulation is developed, allowing an efficient model calibration and control of the process. The proposed approach applies the proper generalized decomposition (PGD) method, a popular model order reduction technique, to decrease the computational effort of each model evaluation required multiple times in parameter estimation, control, and optimization. The welding torch is modeled by a moving heat source, which leads to difficulties separating space and time, a key ingredient in PGD simulations. A novel approach for separating space and time is applied and extended to 3D problems allowing the derivation of an efficient separated representation of the temperature. The results are verified against a standard finite element model showing excellent agreement. The reduced order model is also leveraged in a Bayesian model parameter estimation setup, speeding up calibrations and ultimately leading to an optimized real-time simulation approach for welding experiment using synthetic as well as real measurement data. KW - Proper generalized decomposition KW - Model order reduction KW - Hardly separable problem KW - Additive manufacturing KW - Model calibration KW - Wire arc additive manufacturing PY - 2024 UR - https://nbn-resolving.org/urn:nbn:de:kobv:b43-596502 DO - https://doi.org/10.1007/s40194-024-01700-0 SN - 0043-2288 SP - 1 EP - 18 PB - Springer AN - OPUS4-59650 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - JOUR A1 - Strobl, Dominic A1 - Unger, Jörg F. A1 - Ghnatios, C. A1 - Robens-Radermacher, Annika T1 - PGD in thermal transient problems with a moving heat source: A sensitivity study on factors affecting accuracy and efficiency JF - Engineering Reports N2 - Thermal transient problems, essential for modeling applications like welding and additive metal manufacturing, are characterized by a dynamic evolution of temperature. Accurately simulating these phenomena is often computationally expensive, thus limiting their applications, for example for model parameter estimation or online process control. Model order reduction, a solution to preserve the accuracy while reducing the computation time, is explored. This article addresses challenges in developing reduced order models using the proper generalized decomposition (PGD) for transient thermal problems with a specific treatment of the moving heat source within the reduced model. Factors affecting accuracy, convergence, and computational cost, such as discretization methods (finite element and finite difference), a dimensionless formulation, the size of the heat source, and the inclusion of material parameters as additional PGD variables are examined across progressively complex examples. The results demonstrate the influence of these factors on the PGD model’s performance and emphasize the importance of their consideration when implementing such models. For thermal example, it is demonstrated that a PGD model with a finite difference discretization in time, a dimensionless representation, a mapping for a moving heat source, and a spatial domain non-separation yields the best approximation to the full order model. KW - Additive manufacturing KW - Mapping for unseparable load KW - Model order reduction (MOR) KW - Thermal transient problem KW - Sensitivity analysis KW - Proper generalized decomposition (PGD) PY - 2024 UR - https://nbn-resolving.org/urn:nbn:de:kobv:b43-598001 DO - https://doi.org/10.1002/eng2.12887 IS - e12887 SP - 1 EP - 22 PB - John Wiley & Sons Ltd. CY - Berlin AN - OPUS4-59800 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - JOUR A1 - Diercks, Philipp A1 - Gläser, Dennis A1 - Lünsdorf, Ontje A1 - Selzer, Michael A1 - Flemisch, Bernd A1 - Unger, Jörg F. T1 - Evaluation of tools for describing, reproducing and reusing scientific workflows JF - ing.grid N2 - In the field of computational science and engineering, workflows often entail the application of various software, for instance, for simulation or pre- and postprocessing. Typically, these components have to be combined in arbitrarily complex workflows to address a specific research question. In order for peer researchers to understand, reproduce and (re)use the findings of a scientific publication, several challenges have to be addressed. For instance, the employed workflow has to be automated and information on all used software must be available for a reproduction of the results. Moreover, the results must be traceable and the workflow documented and readable to allow for external verification and greater trust. In this paper, existing workflow management systems (WfMSs) are discussed regarding their suitability for describing, reproducing and reusing scientific workflows. To this end, a set of general requirements for WfMSs were deduced from user stories that we deem relevant in the domain of computational science and engineering. On the basis of an exemplary workflow implementation, publicly hosted at GitHub (https://github.com/BAMresearch/NFDI4IngScientificWorkflowRequirements), a selection of different WfMSs is compared with respect to these requirements, to support fellow scientists in identifying the WfMSs that best suit their requirements. KW - FAIR KW - Reproducibility KW - Scientific workflows KW - Tool comparison KW - Workflow management PY - 2023 UR - https://nbn-resolving.org/urn:nbn:de:kobv:b43-584832 DO - https://doi.org/10.48694/inggrid.3726 VL - 1 IS - 1 SP - 1 EP - 27 AN - OPUS4-58483 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - JOUR A1 - Diercks, Philipp A1 - Veroy, K. A1 - Robens-Radermacher, Annika A1 - Unger, Jörg F. T1 - Multiscale modeling of linear elastic heterogeneous structures via localized model order reduction JF - International Journal for Numerical Methods in Engineering N2 - In this paper, a methodology for fine scale modeling of large scale linear elastic structures is proposed, which combines the variational multiscale method, domain decomposition and model order reduction. The influence of the fine scale on the coarse scale is modelled by the use of an additive split of the displacement field, addressing applications without a clear scale separation. Local reduced spaces are constructed by solving an oversampling problem with random boundary conditions. Herein, we inform the boundary conditions by a global reduced problem and compare our approach using physically meaningful correlated samples with existing approaches using uncorrelated samples. The local spaces are designed such that the local contribution of each subdomain can be coupled in a conforming way, which also preserves the sparsity pattern of standard finite element assembly procedures. Several numerical experiments show the accuracy and efficiency of the method, as well as its potential to reduce the size of the local spaces and the number of training samples compared to the uncorrelated sampling. KW - Multiscale methods KW - Variational multiscale method KW - Localized model order reduction KW - Domain decomposition methods PY - 2023 UR - https://nbn-resolving.org/urn:nbn:de:kobv:b43-580671 DO - https://doi.org/10.1002/nme.7326 SN - 0029-5981 SP - 1 EP - 23 PB - Wiley online library AN - OPUS4-58067 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - JOUR A1 - Andrés Arcones, Daniel A1 - Weiser, M. A1 - Koutsourelakis, F. A1 - Unger, Jörg F. T1 - A Bayesian Framework for Simulation-based Digital Twins of Bridges JF - ce/papers Proceedings in civil engineering N2 - Simulation-based digital twins have emerged as a powerful tool for evaluating the mechanical response of bridges. As virtual representations of physical systems, digital twins can provide a wealth of information that complements traditional inspection and monitoring data. By incorporating virtual sensors and predictive maintenance strategies, they have the potential to improve our understanding of the behavior and performance of bridges over time. However, as bridges age and undergo regular loading and extreme events, their tructural characteristics change, often differing from the predictions of their initial design. Digital twins must be continuously adapted to reflect these changes. In this article, we present a Bayesian framework for updating simulation-based digital twins in the context of bridges. Our approach integrates information from measurements to account for inaccuracies in the simulation model and quantify uncertainties. Through its implementation and assessment, this work demonstrates the potential for digital twins to provide a reliable and up-to-date representation of bridge behavior, helping to inform decision-making for maintenance and management. T2 - Eurostruct 2023 CY - Vienna, Austria DA - 25.09.2023 KW - Digital Twins KW - Bayesian Inference KW - Bridge Monitoring KW - Uncertainty Quantification PY - 2023 UR - https://nbn-resolving.org/urn:nbn:de:kobv:b43-586803 UR - https://eurostruct.org/eurostruct-2023/ DO - https://doi.org/10.1002/cepa.2177 SN - 2509-7075 VL - 6 IS - 5 SP - 734 EP - 740 PB - Ernst & Sohn CY - Berlin AN - OPUS4-58680 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - JOUR A1 - Titscher, Thomas A1 - van Dijk, T. A1 - Kadoke, Daniel A1 - Robens-Radermacher, Annika A1 - Herrmann, Ralf A1 - Unger, Jörg F. T1 - Bayesian model calibration and damage detection for a digital twin of a bridge demonstrator JF - Engineering reports N2 - Using digital twins for decision making is a very promising concept which combines simulation models with corresponding experimental sensor data in order to support maintenance decisions or to investigate the reliability. The quality of the prognosis strongly depends on both the data quality and the quality of the digital twin. The latter comprises both the modeling assumptions as well as the correct parameters of these models. This article discusses the challenges when applying this concept to realmeasurement data for a demonstrator bridge in the lab, including the data management, the iterative development of the simulation model as well as the identification/updating procedure using Bayesian inference with a potentially large number of parameters. The investigated scenarios include both the iterative identification of the structural model parameters as well as scenarios related to a damage identification. In addition, the article aims at providing all models and data in a reproducibleway such that other researcher can use this setup to validate their methodologies. KW - Damage detection KW - Finite element analysis KW - Load identification KW - Model updating KW - Estimation KW - System identification KW - Variational Bayesian statistics PY - 2023 UR - https://nbn-resolving.org/urn:nbn:de:kobv:b43-574496 DO - https://doi.org/10.1002/eng2.12669 SN - 2577-8196 SP - 1 EP - 27 PB - Wiley CY - Hoboken, NJ AN - OPUS4-57449 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Robens-Radermacher, Annika A1 - Unger, Jörg F. A1 - Mezhov, Alexander A1 - Schmidt, Wolfram ED - Biondini, F. ED - Frangopo, D. M. T1 - Temperature dependent modelling approach for early age behavior of printable mortars T2 - Life-Cycle of Structures and Infrastructure Systems N2 - Structural build-up describes the stability and early-age strength development of fresh mortar used in 3D printing. lt is influenced by several factors, i.e. the composition of the print­ able material, the printing regime, and the ambient conditions. The existing modelling approaches for structural build-up usually define the model parameters for a specific material composition with­ out considering the influence of the ambient conditions. The goal of this contribution is to explicitly include the temperature dependency in the modelling approach. Temperature changes have signifi­ cant impact on the structural build-up process: an increase of the temperature leads to a faster dissol­ ution of cement phases and accelerates hydration. The proposed extended model includes temperature dependency using the Arrhenius theory. The new model parameters are successfully calibrated based on Viskomat measurement data using Bayesian inference. Furthermore, a higher impact of the temperature in the re-flocculation as in the structuration stage is observed. T2 - The Eighth International Symposium on Life-Cycle Civil Engineering (IALCCE 2023) CY - Milano, Italien DA - 02.07.2023 KW - 3D concrete printing KW - Material characterization KW - Structural build-up KW - Thixotropy KW - Model calibration PY - 2023 UR - https://nbn-resolving.org/urn:nbn:de:kobv:b43-582175 SN - 978-1-003-32302-0 DO - https://doi.org/10.1201/9781003323020-146 SN - 978-1-003-32302-0 VL - 1st Edition SP - 1193 EP - 1200 PB - CRC Press AN - OPUS4-58217 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - JOUR A1 - Bayerlein, Bernd A1 - Hanke, T. A1 - Muth, Thilo A1 - Riedel, Jens A1 - Schilling, Markus A1 - Schweizer, C. A1 - Skrotzki, Birgit A1 - Todor, A. A1 - Moreno Torres, Benjami A1 - Unger, Jörg F. A1 - Völker, Christoph A1 - Olbricht, Jürgen T1 - A Perspective on Digital Knowledge Representation in Materials Science and Engineering JF - Advanced Engineering Materials N2 - The amount of data generated worldwide is constantly increasing. These data come from a wide variety of sources and systems, are processed differently, have a multitude of formats, and are stored in an untraceable and unstructured manner, predominantly in natural language in data silos. This problem can be equally applied to the heterogeneous research data from materials science and engineering. In this domain, ways and solutions are increasingly being generated to smartly link material data together with their contextual information in a uniform and well-structured manner on platforms, thus making them discoverable, retrievable, and reusable for research and industry. Ontologies play a key role in this context. They enable the sustainable representation of expert knowledge and the semantically structured filling of databases with computer-processable data triples. In this perspective article, we present the project initiative Materials-open-Laboratory (Mat-o-Lab) that aims to provide a collaborative environment for domain experts to digitize their research results and processes and make them fit for data-driven materials research and development. The overarching challenge is to generate connection points to further link data from other domains to harness the promised potential of big materials data and harvest new knowledge. KW - Data infrastructures KW - Digital representations KW - Digital workflows KW - Knowledge graphs KW - Materials informatics KW - Ontologies KW - Vocabulary providers PY - 2022 UR - https://nbn-resolving.org/urn:nbn:de:kobv:b43-546729 DO - https://doi.org/10.1002/adem.202101176 SN - 1438-1656 SP - 1 EP - 14 PB - Wiley-VCH GmbH CY - Weinheim AN - OPUS4-54672 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - JOUR A1 - Coelho Lima, Isabela A1 - Robens-Radermacher, Annika A1 - Titscher, Thomas A1 - Kadoke, Daniel A1 - Koutsourelakis, P.-S. A1 - Unger, Jörg F. T1 - Bayesian inference for random field parameters with a goal-oriented quality control of the PGD forwardmodel's accuracy JF - Computational mechanics N2 - Numerical models built as virtual-twins of a real structure (digital-twins) are considered the future ofmonitoring systems. Their setup requires the estimation of unknown parameters, which are not directly measurable. Stochastic model identification is then essential, which can be computationally costly and even unfeasible when it comes to real applications. Efficient surrogate models, such as reduced-order method, can be used to overcome this limitation and provide real time model identification. Since their numerical accuracy influences the identification process, the optimal surrogate not only has to be computationally efficient, but also accurate with respect to the identified parameters. This work aims at automatically controlling the Proper Generalized Decomposition (PGD) surrogate’s numerical accuracy for parameter identification. For this purpose, a sequence of Bayesian model identification problems, in which the surrogate’s accuracy is iteratively increased, is solved with a variational Bayesian inference procedure. The effect of the numerical accuracy on the resulting posteriors probability density functions is analyzed through two metrics, the Bayes Factor (BF) and a criterion based on the Kullback-Leibler (KL) divergence. The approach is demonstrated by a simple test example and by two structural problems. The latter aims to identify spatially distributed damage, modeled with a PGD surrogate extended for log-normal random fields, in two different structures: a truss with synthetic data and a small, reinforced bridge with real measurement data. For all examples, the evolution of the KL-based and BF criteria for increased accuracy is shown and their convergence indicates when model refinement no longer affects the identification results. KW - Variational inference KW - Proper generalized decomposition KW - Goal-oriented KW - Digital twin KW - Random field PY - 2022 UR - https://nbn-resolving.org/urn:nbn:de:kobv:b43-555755 DO - https://doi.org/10.1007/s00466-022-02214-6 SN - 1432-0924 SP - 1 EP - 22 PB - Springer CY - Berlin AN - OPUS4-55575 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - JOUR A1 - Pohl, Christoph A1 - Smilauer, V. A1 - Unger, Jörg F. T1 - A three-phase transport model for high-temperature concrete simulations validated with X-ray CT data JF - Materials N2 - Concrete exposure to high temperatures induces thermo-hygral phenomena, causing water phase changes, buildup of pore pressure and vulnerability to spalling. In order to predict these phenomena under various conditions, a three-phase transport model is proposed. The model is validated on X-ray CT data up to 320 ◦C, showing good agreement of the temperature profiles and moisture changes. A dehydration description, traditionally derived from thermogravimetric analysis, was replaced by a formulation based on data from neutron radiography. In addition, treating porosity and dehydration evolution as independent processes, previous approaches do not fulfil the solid mass balance. As a consequence, a new formulation is proposed that introduces the porosity as an independent variable, ensuring the latter condition. KW - Concrete KW - Porous media KW - Spalling KW - Dehydration KW - Moisture transport KW - Heat transfer KW - Pore pressure KW - Porosity KW - Finite elements PY - 2021 UR - https://nbn-resolving.org/urn:nbn:de:kobv:b43-532840 UR - https://doi.org/10.5281/zenodo.4890635 DO - https://doi.org/10.3390/ma14175047 SN - 1996-1944 VL - 14 IS - 17 SP - 1 EP - 21 PB - MDPI CY - Basel AN - OPUS4-53284 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER -