TY - CONF A1 - He, Yuxiang A1 - Robens-Radermacher, Annika A1 - Noda, S. A1 - Wolf, Christoph A1 - Unger, Jörg F. A1 - Mai, I. ED - Ferrara, L. ED - Muciaccia, G. ED - di Summa, D. T1 - Automated Workflows for Concrete Additive Manufacturing for Design, Optimization, and Fabrication of Parametrized Elements N2 - 3D concrete printing is an innovative new construction technology offering the potential to enable the efficient production of individual structures with less consumption of resources. The technology will mainly shape the future construction philosophy. From the design of a structure to the printed component, many individual steps based on different software are required, which must be repeated for each new or even slightly changed design. The geometry of the structure is created in a CAD program. The print path is defined in slicer software leading to the machine code for the printer to print the structure. A numerical model of the printed structure makes optimization in design and fabrication possible, by predicting the behaviour of the structure and reducing the number of test prints and costs. For that, additional steps like meshing the design and running a simulation are required. In order to work efficiently, an automated workflow is necessary, which runs all of the individual steps without interacting with each software program. Furthermore, changes in parameters or the exchange of parts (different designs or printers) must be simple. One way to develop such an automated workflow is presented within this paper. The interfaces are defined in a way that allows running the full chain of tools as well as individual steps. The workflow is demonstrated based on the example of a parametrized wall element for extrusion-based concrete. Furthermore, a test series of cubes is printed, and the influence of different infill structures is numerically and experimentally compared. T2 - RSCC 2024 - RILEM Spring Convention and Conference 2024 CY - Milano, Italy DA - 07.04.2024 KW - 3D concrete printing KW - Automation KW - Workflow KW - Innovative technologies PY - 2024 SN - 978-3-031-70280-8 SN - 978-3-03170281-5 SN - 978-3-031-70283-9 DO - https://doi.org/10.1007/978-3-031-70281-5_28 SN - 2211-0844 SN - 2211-0852 N1 - Serientitel: RILEM Bookseries – Series title: RILEM Bookseries VL - 56 IS - 2 SP - 247 EP - 254 PB - Springer CY - Cham AN - OPUS4-61608 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - JOUR A1 - Robens-Radermacher, Annika A1 - Lacy Jr., T. E. A1 - Bednarcyk, B. A. A1 - Pineda, E. J. A1 - Arnold, S. M. A1 - Ricks, T. M. T1 - Solution of the nonlinear high-fidelity generalized method of cells micromechanics relations via order-reduction techniques N2 - The High-Fidelity Generalized Method of Cells (HFGMC) is one technique, distinct from traditional finite-element approaches, for accurately simulating nonlinear composite material behavior. In this work, the HFGMC global system of equations for doubly periodic repeating unit cells with nonlinear constituents has been reduced in size through the novel application of a Petrov-Galerkin Proper Orthogonal Decomposition order-reduction scheme in order to improve its computational efficiency. Order-reduced models of an E-glass/Nylon 12 composite led to a 4.8–6.3x speedup in the equation assembly/solution runtime while maintaining model accuracy. This corresponded to a 21–38% reduction in total runtime.Thesignificant difference in assembly/solution and total runtimes was attributed to the evaluation of integration point inelastic field quantities; this step was identical between the unreduced and order-reduced models. Nonetheless, order-reduced techniques offer the potential to significantly improve the computational efficiency of multiscale calculations. KW - High-Fidelity KW - Micromechanics KW - HFGMC PY - 2018 UR - https://nbn-resolving.org/urn:nbn:de:kobv:b43-445303 DO - https://doi.org/10.1155/2018/3081078 SN - 1024-123X SN - 1563-5147 VL - 2018 SP - Article ID 3081078-1 EP - 11 PB - Hindawi Publishing Corporation CY - Kairo, Ägypten AN - OPUS4-44530 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 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 - 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 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 - Robens-Radermacher, Annika A1 - Held, Felix A1 - Coelho Lima, Isabela A1 - Titscher, Thomas A1 - Unger, Jörg F. T1 - Efficient identification of random fields coupling Bayesian inference and PGD reduced order model for damage localization N2 - One of the main challenges regarding our civil infrastructure is the efficient operation over their complete design lifetime while complying with standards and safety regulations. Thus, costs for maintenance or replacements must be optimized while still ensuring specified safety levels. This requires an accurate estimate of the current state as well as a prognosis for the remaining useful life. Currently, this is often done by regular manual or visual inspections within constant intervals. However, the critical sections are often not directly accessible or impossible to be instrumented at all. Model‐based approaches can be used where a digital twin of the structure is set up. For these approaches, a key challenge is the calibration and validation of the numerical model based on uncertain measurement data. The aim of this contribution is to increase the efficiency of model updating by using the advantage of model reduction (Proper Generalized Decomposition, PGD) and applying the derived method for efficient model identification of a random stiffness field of a real bridge.” KW - Model reduction KW - Model updating KW - Proper generalized decomposition KW - Random field KW - Variational Bayesian Inference PY - 2021 UR - https://nbn-resolving.org/urn:nbn:de:kobv:b43-521275 DO - https://doi.org/10.1002/pamm.202000063 VL - 20 IS - 1 SP - e202000063 PB - Wiley Online Libary AN - OPUS4-52127 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 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 VL - 6 IS - 11 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 - CONF A1 - Robens-Radermacher, Annika A1 - Saif-Ur-Rehman, A1 - Wolf, Christoph A1 - Kujath, Cezary A1 - He, Yuxiang A1 - Mezhof, Alexander A1 - Hüsken, Götz A1 - Jeyifous, Olubunmi Anthony A1 - Unger, Jörg F. ED - Rogge, Andreas ED - Meng, Birgit T1 - Modellierung und Simulation von 3D Betondruck – Design- und Prozessoptimierung N2 - Der 3D Betondruck ermöglicht die effiziente und ressourcenschonendere Herstellung maßgeschneiderter Betonstrukturen. Trotz des großen Potentials gibt es bisher keine einheitlichen Normen und Standards für den sicheren und robusten 3D Betondruck. Der Beitrag zeigt das Potential numerischer Methoden und Modelle zur effizienten und ressourcenschonenden Design- und Prozessoptimierung des 3D Betondrucks. Dazu werden die aktuellen Forschungsarbeiten im Bereich der Entwicklung robuster und zuverlässiger numerischer Zwillinge, geeigneter Optimierungstools sowie digitaler Workflows diskutiert. T2 - 11. Jahrestagung des DAfStb mit 63. Forschungskolloquium der BAM Green Intelligent Building CY - Berlin, Germany DA - 16.10.2024 KW - Modellierung KW - Simulation KW - 3D Betondruck KW - Designoptimierung KW - Prozessoptimierung PY - 2024 UR - https://nbn-resolving.org/urn:nbn:de:kobv:b43-613023 SN - 978-3-9818564-7-7 SP - 132 EP - 137 PB - Bundesanstalt für Materialforschung und -prüfung (BAM) CY - Berlin AN - OPUS4-61302 LA - deu AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - JOUR A1 - Robens-Radermacher, Annika A1 - Unger, Jörg F. T1 - Efficient structural reliability analysis by using a PGD model in an adaptive importance sampling schema N2 - One of the most important goals in civil engineering is to guarantee the safety of the construction. Standards prescribe a required failure probability in the order of 10−4 to 10−6. Generally, it is not possible to compute the failure probability analytically. Therefore, many approximation methods have been developed to estimate the failure probability. Nevertheless, these methods still require a large number of evaluations of the investigated structure, usually finite element (FE) simulations, making full probabilistic design studies not feasible for relevant applications. The aim of this paper is to increase the efficiency of structural reliability analysis by means of reduced order models. The developed method paves the way for using full probabilistic approaches in industrial applications. In the proposed PGD reliability analysis, the solution of the structural computation is directly obtained from evaluating the PGD solution for a specific parameter set without computing a full FE simulation. Additionally, an adaptive importance sampling scheme is used to minimize the total number of required samples. The accuracy of the failure probability depends on the accuracy of the PGD model (mainly influenced on mesh discretization and mode truncation) as well as the number of samples in the sampling algorithm. Therefore, a general iterative PGD reliability procedure is developed to automatically verify the accuracy of the computed failure probability. It is based on a goal-oriented refinement of the PGD model around the adaptively approximated design point. The methodology is applied and evaluated for 1D and 2D examples. The computational savings compared to the method based on a FE model is shown and the influence of the accuracy of the PGD model on the failure probability is studied. KW - Reliability KW - Probability of failure KW - Adaptive importance sampling KW - Reduced order models KW - Proper Generalized Decomposition PY - 2020 UR - https://nbn-resolving.org/urn:nbn:de:kobv:b43-510345 DO - https://doi.org/10.1186/s40323-020-00168-z VL - 7 SP - Article number: 29 PB - SpringerOpen AN - OPUS4-51034 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 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 - GEN A1 - Diercks, Philipp A1 - Robens-Radermacher, Annika A1 - Rosenbusch, Sjard Mathis A1 - Unger, Jörg F. A1 - Saif-Ur-Rehman, Saif-Ur-Rehman T1 - fenics-constitutive N2 - This software enables the use of nonlinear constitutive models with FEniCSx. KW - Constitutive models KW - FEniCSx KW - Fenics-constitutive PY - 2024 DO - https://doi.org/10.5281/zenodo.13364955 PB - Zenodo CY - Geneva AN - OPUS4-62114 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - GEN A1 - Robens-Radermacher, Annika A1 - Strobl, Dominic T1 - PGDrome N2 - A FEniCS based python module of the Proper Generalized Decomposition (PGD) method. KW - Reduced Order Model KW - Proper Generalized Decomposition KW - Fenics PY - 2023 DO - https://doi.org/10.5281/zenodo.10075334 PB - Zenodo CY - Geneva AN - OPUS4-59134 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - GEN A1 - Bos, Freek A1 - Robens-Radermacher, Annika A1 - Muthukrishnan, S. A1 - Versteegen, J. A1 - Wolfs, R. A1 - Santhanam, M. A1 - Menna, C. A1 - Mechtcherine, V. T1 - Database of the RILEM TC 304-ADC interlaboratory study on mechanical properties of 3D printed concrete (ILS-mech) N2 - The RILEM TC 304-ADC has set up a large interlaboratory study on the mechanical properties of 3D printed concrete (ILS-mech). The study was prepared in 2022 by a preparation group leading to a Study Plan which the TC approved on 29 November 2022 (https://doi.org/10.14459/2023mp1705940). The ILS-mech was performed in 2023. The data was collected using a pre-prepared spreadsheet template. For data management, a database was derived and set-up in openBIS. The underlying Postgres database of openBIS was exported to the here-published SQLite database for sharing without maintaining a server. The structure of the database is described in (doi). The results are discussed in three associated papers focusing on the overall outcomes and evaluation of the procedures (doi), the compressive test results (doi), and the tensile test results (doi). KW - Additive manufacturing of concrete KW - 3d concrete printing KW - 3dcp KW - Test protocol KW - Compression KW - Flexure KW - Tension KW - E-modulus KW - Bending KW - Splitting PY - 2023 PB - Zenodo CY - Geneva AN - OPUS4-61022 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Robens-Radermacher, Annika T1 - Efficient model identification using a PGD forward model - Influence of surrogate accuracy and converergence approach N2 - There is a rising attention of using numerical models for effcient structural monitoring and ensuring the structure's safety. Setting up virtual models as twin for real structures requires a model identification process calculating the unknown model parameters, which mostly are only indirectly measurable. This is a computationally very costly inverse optimization process, which often makes it unfeasible for real applications. Effcient surrogate models such as reduced order models can be used, to overcome this limitation. But the influence of the model accuracy on the identification process has then to be considered. The aim is to automatically control the influence of the model's accuracy on the identification. Here, a variational Bayesian inference approach[3] is coupled with a reduced forward model using the Proper Generalized Decomposition (PGD) method. The influence of the model accuracy on the inference result is studied and measured. Therefore, besides the commonly used Bayes factor the Kullback-Leibler divergences between the predicted posterior pdfs are proposed. In an adaptive inference procedure, the surrogate's accuracy is iteratively increased, and the convergence of the posterior pdf is analysed. The proposed adaptive identification process is applied to the identification of spatially distributed damage modeled by a random eld for a simple example with synthetic data as well as a small, reinforced bridge with real measurement data. It is shown that the proposed criteria can mirror the influence of the model accuracy and can be used to automatically select a suffciently accurate surrogate model. T2 - The 8th European Congress on Computational Methods in Applied Sciences and Engineering (ECCOMAS) 2022 CY - Oslo, Norway DA - 05.06.2022 KW - Model order reduction KW - Model identification KW - Bayes factor KW - PGD KW - Kullback-Leibner divergence PY - 2022 AN - OPUS4-55112 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Robens-Radermacher, Annika T1 - Stiffness identification by efficient model calibration of random field variables for the Young's modulus N2 - The main challenge in using numerical models as digital twins in real applications for prognosis purposes, such as reliability analysis, is the calibration and validation of the models based on uncertain measurement data. Uncertainties are not limited to the measurement data, but the numerical model itself will not be perfect due to the modelling assumptions. In this contribution, a probabilistic inference method for model calibration, based on the Bayes’ Theorem, is used to face that issue. Such inference approaches include uncertainties on the data as well as on the model parameters, allowing to compute an a posteriori distribution for the model parameters as well as a noise term reflecting the measured data. However, such probabilistic inference methods require a lot of evaluations of the numerical forward model for different model parameters. An improvement of the efficiency is obtained by replacing the forward model with a reduced model. Model reduction, e.g. the proper generalized decomposition (PGD) method, is a popular concept to decrease the computational effort, where each evaluation of the reduced forward model is a pure less costly function evaluation. The heterogeneous spatial distribution of material parameters in the forward model is described by a lognormal random field. This allows identifying a variable stiffness over the spatial directions by identifying the random field variables with given measurement data. These changes can e.g. be caused by damage. The lognormal field is approximated as series expansion for the PGD problem. The derived efficient model identification procedure is shown using a real reinforced prestress demonstrator bridge and stereophotogrammetry measurement data. A digital twin for that demonstrator bridge is build up using a set of measurement data and verified by testing additional measurement data. PGD model error against the FEM model is discussed based on an importance sampling analysis computing the Bayes Factor. T2 - COMPLAS 2021 CY - Berlin, Germany DA - 08.09.2021 KW - Digital twin KW - Structure monitoring KW - Model updating KW - Proper generalized decomposition KW - Bayesian inferences PY - 2021 AN - OPUS4-53285 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Robens-Radermacher, Annika T1 - Advantages and challenges of data stores for interlaboratory studies – an example from mechanical test data of printed concrete structures N2 - Interlaboratory studies are common tools for collecting comparable data to implement standards for new materials or testing technologies. In the case of construction materials, these studies form the basis for recommendations and design codes. Depending on the study, the amount of data collected can be enormous, making manual handling and evaluation difficult. On the other hand, the importance of the FAIR (findable, accessible, interoperable, and reusable) principles for scientific data management, published by Wilkinson et al. in 2016, is constantly growing and changing the view on data usage. The benefits of using data management tools such as data stores/repositories or electronic laboratory notebooks are many. Data is stored in a structured and accessible way (at least within a group) and data loss due to staff turnover is reduced. Tools usually support data publishing and analysis interfaces. In this way, data can be reused years later to generate new knowledge with future insights. On the other hand, there are many challenges in setting up a data repository, such as selecting suitable software tools, defining the data structure, enabling data access, and understanding by others and ensuring maintenance, among others. This talk discusses the advantages and challenges of setting up and applying a data repository using the interlaboratory study on the mechanical properties of printed concrete structures carried out in RILEM TC 304-ADC as example. First, the definition of a suitable data structure including all information is discussed. The tool-dependent upload process is then described. Here, the data management system openBIS (open source software developed by ETH Zurich) is used. Since in most cases an open compute platform allowing access from different organisations is not possible or available due to data protection and maintenance issues, tool-independent export options are discussed and compared. Finally, the different query and analysis possibilities are demonstrated. T2 - RILEM spring convention & conference on advanced construction materials and processes for a carbon neutral society 2024 CY - Milan, Italy DA - 07.04.2024 KW - Data stores KW - Data structuring KW - Data evaluation KW - Automatization KW - Interlaboratory PY - 2024 UR - https://www.rilem.net/agenda/rilem-spring-convention-conference-on-advanced-construction-materials-and-processes-for-a-carbon-neutral-society-1530 AN - OPUS4-59906 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Robens-Radermacher, Annika T1 - Model identification coupling Bayesian Inference with PGD reduced models with random field material parameters N2 - The main challenge using numerical models as digital twins in real applications is the calibration and validation of the model based on uncertain measurement data. Therefore, model updating approaches which are inverse optimization processes are applied. This requires a huge number of computations of the same numerical model with slightly different model parameters. For that reason, model updating becomes computationally very expensive for real applications. Model reduction, e.g. the proper generalized decomposition method, is a popular concept to decrease the computational effort of complex numerical simulations. Therefore, a reduced model of the structure of interest is derived and will be used as surrogate model in a Variational Bayesian procedure to create a very efficient digital twin of the structure. An efficient model updating approach by means of a PGD reduced model with random field material stiffness parameters is shown. The random field allows, to calibrate the model considering parameter changes over the spatial direction. These changes can be caused by local damages as well as by production. As an exemplary application a demonstrator bridge is used. Digital twins can reduce the costs for maintenance and inspections especially for the costly civil infrastructure with high requirements at their performance over the whole lifetime. Currently, the current state of the structure is determined by regular manual and visual inspections within constant intervals. However, the critical sections are often not directly accessible or impossible to be instrumented at all. In this case, model-based approaches where a digital twin is set up can improve the process. Based on this digital twin, a prognosis of the future performance of the structure, e.g. the failure probability, can be computed. The influences of the reduction degree, the mesh discretization as well as the correlation length in the PGD Bayesian approach are studied by means of the digital twin of a simple pre-stressed concrete two field bridge. T2 - Annual Meeting of the International Association of Applied Mathematics and Mechanics (GAMM) 2020@21 CY - Online meeting DA - 15.03.2021 KW - Digital twin supporting KW - Proper generalized decomposition PY - 2021 AN - OPUS4-52317 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - JOUR A1 - Unger, Jörg F. A1 - Robens-Radermacher, Annika A1 - Tamsen, Erik T1 - Data provenance - from experimental data to trustworthy simulation models and standards N2 - FAIR (findable, accessible, interoperable and reusable) data usage is one of the main principals that many of the research and funding organizations include in their strategic plans, which means that following the main principals of FAIR data is required in many research projects. The definition of data being FAIR is very general. When implementing that for a specific application or project or even setting a standardized procedure within a working group, a company or a research community, many challenges arise. In this contribution, an overview about our experience with different methods and tools is outlined. We begin with a motivation on potential use cases for the application of FAIR data with increasing complexity starting from a reproducible research paper over collaborative projects with multiple participants such as Round-Robin tests up to data-based models within standardization codes, applications in machine learning or parameter estimation of physics-based simulation models. In a second part, different options for structuring the data (including metadata schema) are discussed. The first one is the openBIS system, which is an open-source lab notebook and PostgreSQL based data management system. A second option is a semantic representation using RDF based on ontologies for the domain of interest. In a third section, requirements for workflow tools to automate data processing are discussed and their integration into reproducible data analysis is presented with an outlook on required information to be stored as metadata in the database. Finally, the presented procedures are exemplarily demonstrated for the calibration of a temperature dependent constitutive model for additively manufactured mortar. A metadata schema for a rheological measurement setup is derived and implemented in an openBIS database. After a short review of a potential numerical model predicting the structural build-up behavior, the automatic workflow to use the stored data for model parameter estimation is demonstrated. KW - FAIR data KW - Semantic web KW - Scientific workflows KW - Metadata KW - Reproducible data processing PY - 2023 DO - https://doi.org/10.1016/j.matpr.2023.08.081 SP - 1 EP - 10 PB - Elsevier AN - OPUS4-58215 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - GEN A1 - Andrés Arcones, Daniel A1 - Diercks, Philipp A1 - Robens-Radermacher, Annika A1 - Rosenbusch, Sjard Mathis A1 - Tamsen, Erik A1 - Tyagi, Divyansh A1 - Unger, Jörg F. T1 - FenicsXConcrete N2 - FenicsXConcrete is a Python package for the simulation of mechanical problems. The general PDE solving software FEniCSx is extended with classes describing experimental setups, mechanical problems, thermo-mechanical problems, additive manufacturing and sensors. KW - FEM KW - Fenics KW - Concrete modelling PY - 2023 UR - https://github.com/BAMresearch/FenicsXConcrete DO - https://doi.org/10.5281/zenodo.7780757 PB - Zenodo CY - Geneva AN - OPUS4-59121 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Unger, Jörg F. A1 - Robens-Radermacher, Annika A1 - Tamsen, Erik T1 - Data provenance - from experimental data to trustworthy simulation models and standards N2 - FAIR (findable, accessible, interoperable and reusable) data usage is one of the main principals that many of the research and funding organizations include in their strategic plans, which means that following the main principals of FAIR data is required in many research projects. The definition of data being FAIR is very general, and when implementing that for a specific application or project or even setting a standardized procedure within a working group, a company or a research community, many challenges arise. In this contribution, an overview about our experience with different methods, tools and procedures is outlined. We begin with a motivation on potential use cases for the applications of FAIR data with increasing complexity starting from a reproducible research paper over collaborative projects with multiple participants such as Round-Robin tests up to data-based models within standardization codes, applications in machine learning or parameter estimation of physics-based simulation models. In a second part, different options for structuring the data are discussed. On the one hand, this includes a discussion on how to define actual data structures and in particular metadata schema, and on the other hand, two different systems for storing the data are discussed. The first one is the openBIS system, which is an open-source Lab notebook and PostgreSQL based data management system. A second option are a semantic representations using RDF based ontologies for the domain of interest. In a third section, requirements for workflow tools to automate data processing are discussed and their integration into reproducible data analysis is presented with an outlook on required information to be stored as metadata in the database. Finally, the presented procedures are exemplarily demonstrated for the calibration of a temperature dependent constitutive model for additively manufactured mortar. Metadata schemata for a rheological measurement setup are derived and implemented in an openBIS database. After a short review of a potential numerical model predicting the structural build-up behaviour, the automatic workflow to use the stored data for model parameter estimation is demonstrated. T2 - 4th International Congress on Materials & Structural Stability CY - Rabat, Morocco DA - 08.03.2023 KW - Data provenance KW - Experimental data to trustworthy KW - Simulation models and Standards PY - 2023 UR - https://www.rsc-cmss23.asmatec.org/RILEM%20Committees%20Program.php SP - 1 EP - 9 CY - Rabat, Morocco AN - OPUS4-57349 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - GEN 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 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 bysolving 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 - Proper orthogonal PY - 2024 UR - https://arxiv.org/abs/2201.10374 DO - https://doi.org/10.48550/arXiv.2201.10374 PB - Arxiv; Cornell Tech CY - New York, NY AN - OPUS4-59803 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - JOUR A1 - Bos, Freek A1 - Menna, Constantino A1 - Robens-Radermacher, Annika A1 - Wolfs, Rob A1 - Roussel, Nicolas A1 - Lombois-Burger, Hélène A1 - Baz, Bilal A1 - Weger, Daniel A1 - Nematollahi, Behzad A1 - Santhanam, Manu A1 - Zhang, Yamei A1 - Bhattacherjee, Shantanu A1 - Jia, Zijian A1 - Chen, Yu A1 - Mechtcherine, Viktor T1 - Mechanical properties of 3D printed concrete: a RILEM TC 304-ADC interlaboratory study — approach and main results N2 - To show compliance to structural engineering codes and implement quality control measures, it is critical to obtain reliable mechanical properties of the materials in question. For conventional cast and precast concrete, the experimental procedures and relationships between mechanical properties, the material composition, and the production methods are globally known, but for 3D concrete printing (3DCP), these relations have not yet been established. Previous studies have shown little consistency in results, and the underlying experimental methods have not been established broadly. There is an urgent need to address these issues as the application of 3DCP in practice projects is growing rapidly. Therefore, RILEM TC 304-ADC: Assessment of Additively Manufactured Concrete Materials and Structures has set up a large interlaboratory study into the mechanical properties of 3D printed concrete. This paper presents key elements of the experimental approach detailed in the Study Plan and the supporting considerations. Furthermore, it reports on the response, consisting of 34 contributions from 30 laboratories, detailing global coverage, properties of the applied mixture designs and characteristics of the printing facilities that have been used. Subsequently, some fundamental results from compression, flexural, and E-modulus testing are presented and—considering cast specimens as a reference—discussed. On average, a reduction in strength was found in compression and E-modulus (all tested orientations). For flexure, on the other hand, an increase was found in two testing orientations, while a decrease was observed in the third orientation. Importantly, even though the applied experimental methods were found to be reasonably appropriate to obtain the required data, the differences found between individual contributions are significant and sometimes non-consistent, suggesting that testing on specific material-facility combinations is necessary to reliably determine the mechanical properties of objects produced from them. Furthermore, a theoretical framework needs to be developed to further explain the variations that were observed. Extensive analyses of all acquired data are out of the scope of this contribution, but presented in two associated papers, whereas a third presents the data management approach used to process the approximately 5,000 test results. KW - 3D printed concrete KW - 3DCP KW - Mechanical properties KW - Interlaboratory study PY - 2025 UR - https://nbn-resolving.org/urn:nbn:de:kobv:b43-634631 DO - https://doi.org/10.1617/s11527-025-02686-x VL - 58 IS - 5 SP - 1 EP - 29 PB - Springer Nature AN - OPUS4-63463 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 - 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 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 - CONF A1 - Robens-Radermacher, Annika T1 - Efficient cooling time optimization in Wire Arc Additive Manufacturing using a multi-layer reduced order model N2 - Additive manufacturing (AM) has transformed the industry by enabling the production of complex geometries and parts with customized properties. Among various AM techniques, wire arc additive manufacturing (WAAM) stands out due to its high deposition rate and low equipment cost. However, WAAM’s complex thermal history poses challenges for real-time simulation, essential for online process control and optimization. Consequently, experimental optimization remains the state-of-the-art approach. A critical parameter to optimize is the cooling phase duration, which prevents structural overheating, controls the molten pool size, and influences the mechanical properties of the final product. For efficient cooling time optimization, a fast-to-evaluate model of the temperature field during multi-layer deposition is necessary. This study proposes a reduced order model (ROM) using the proper generalized decomposition (PGD) method as a powerful tool to minimize computational effort. Given the moving heat source in WAAM processes, a mapping approach is employed to achieve a fully separated representation of the temperature field. Building on the authors’ previous one-layer approach, this contribution extends the model to multiple layers through enhanced mapping and compression techniques. The compression reduces the total number of PGD modes as the number of layers increases. The extended mapping allows computations with a fixed mesh over the simulation time, in contrast to standard methods such as the element birth technique. For cooling time optimization, the cooling duration of each layer is incorporated as PGD variables, enabling time-efficient computation of the temperature field for varying cooling times. The developed ROM is applied to optimize the cooling time of a multiple layer example. Therefore a 5-10 layer wall structure is investigated using the austenitic stainless steel 1.4404 (AISI 316 L). The resulting cooling times and the efficiency of the approach are discussed. T2 - 12th European solid mechanics conference (ESMC) CY - Lyon, France DA - 07.07.2025 KW - Model order reduction KW - Proper generalized decomposition KW - Welding KW - Additive manufacturing KW - Optimzation PY - 2025 UR - https://esmc2025.sciencesconf.org/ AN - OPUS4-63855 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - JOUR A1 - Robens-Radermacher, Annika A1 - Kujath, Cezary A1 - Bos, Freek A1 - Mechtcherine, Viktor A1 - Unger, Jörg F. T1 - Mechanical properties of 3D printed concrete: a RILEM TC 304-ADC interlaboratory study-Design and implementation of a database system for querying, sharing, and analyzing experimental data N2 - Interlaboratory studies are essential for implementing standardized test methods for new innovative materials or technologies such as 3D concrete printing, certifying reference materials, and validating methods. They provide the basis for recommendations and design standards. Typically, the collected data are used only for one study and are published in paper form, without open access to the raw data files. However, preserving the collected data and analysis procedures in a shareable and reusable way leads to advantages for further usage. New data with the same structure can be added or the data can be analyzed by a new analysis procedure generating new knowledge. Additionally, resources are saved by avoiding the repetition of the same measurements. In line with the recent digitalization trend in material science and engineering, a database for the interlaboratory study on mechanical properties of 3D printed concrete conducted in RILEM Technical Committee 304-ADC is established. The challenges and experiences from defining the data structure, uploading the data, and using the database for evaluations are discussed. The openBIS software is used to create and fill the database, while an export method to an SQLite format is developed and discussed to generate a shareable and reusable database. With the exported database, querying the data is possible independently of a particular data management system. Additionally, examples of data processing with reusable workflows automating the analysis procedure are demonstrated. KW - Data management KW - Interlaboratory study KW - 3D concrete printing KW - Database KW - Reusability PY - 2025 UR - https://nbn-resolving.org/urn:nbn:de:kobv:b43-634627 DO - https://doi.org/10.1617/s11527-025-02650-9 SN - 1871-6873 VL - 58 IS - 184 SP - 1 EP - 37 PB - Springer Nature AN - OPUS4-63462 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - JOUR A1 - Wolfs, Rob A1 - Versteegen, Jelle A1 - Santhanam, Manu A1 - Bhattacherjee, Shantanu A1 - Bos, Freek A1 - Robens-Radermacher, Annika A1 - Muthukrishnan, Shravan A1 - Menna, Costantino A1 - Ozturk, Onur A1 - Ozyurt, Nilufer A1 - Roupec, Josef A1 - Richter, Christiane A1 - Jungwirth, Jörg A1 - Miranda, Luiza A1 - Ammann, Rebecca A1 - Caron, Jean-François A1 - de Bono, Victor A1 - Monte, Renate A1 - Navarrete, Iván A1 - Eugenin, Claudia A1 - Lombois‑Burger, Hélène A1 - Baz, Bilal A1 - Sinka, Maris A1 - Sapata, Alise A1 - Harbouz, Ilhame A1 - Zhang, Yamei A1 - Jia, Zijian A1 - Kruger, Jacques A1 - Mostert, Jean‑Pierre A1 - Šter, Katarina A1 - Šajna, Aljoša A1 - Kaci, Abdelhak A1 - Rahal, Said A1 - Snguanyat, Chalermwut A1 - Arunothayan, Arun A1 - Zhao, Zengfeng A1 - Mai, Inka A1 - Rasehorn, Inken Jette A1 - Böhler, David A1 - Freund, Niklas A1 - Lowke, Dirk A1 - Neef, Tobias A1 - Taubert, Markus A1 - Auer, Daniel A1 - Hechtl, C. Maximilian A1 - Dahlenburg, Maximilian A1 - Esposito, Laura A1 - Buswell, Richard A1 - Kolawole, John A1 - Isa, Muhammad Nura A1 - Liu, Xingzi A1 - Wang, Zhendi A1 - Subramaniam, Kolluru A1 - Mechtcherine, Viktor T1 - Mechanical properties of 3D printed concrete: a RILEM TC 304-ADC interlaboratory study — flexural and tensile strength N2 - This paper discusses the flexural and tensile strength properties of 3D printed concrete, based on the results of a RILEM TC 304-ADC interlaboratory study on mechanical properties. These properties are determined using different testing techniques, including 3- and 4-point flexural tests, splitting tests, and uniaxial tension tests, on specimens extracted from large 3D printed elements in accordance with a prescribed study plan. The relationship between compressive and flexural or tensile strengths, cast or printed samples, different types of tests, and different loading orientations, are analysed to understand the influence of 3D printing. As expected, the strength can reduce significantly when the main tensile stress is acting perpendicular to the interface between layers. The role of deviations from the standard study procedure, in terms of the time interval between the placing of subsequent layers, or the adoption of a different curing strategy, are also assessed. While the increased time interval significantly impacts the strength in the critical direction, the use of variable curing conditions does not seem to have a clear-cut effect on the strength ratios of the printed to cast specimens. Additionally, the paper looks at the variability in the results for the printed specimens, in order to emphasize the need for multiple replicates for obtaining a proper result. An extensive insight into the aspects affecting the variability is presented in the paper. Finally, with the limited dataset available for specimens tested at a larger scale, it is difficult to arrive at a clear understanding of the role of specimen size (i.e., greater number of layers). KW - 3D concrete printing KW - Digital fabrication KW - Flexural strength KW - Tensile strength KW - Interlayer bond strength PY - 2025 UR - https://nbn-resolving.org/urn:nbn:de:kobv:b43-634655 DO - https://doi.org/10.1617/s11527-025-02687-w SN - 1871-6873 VL - 58 IS - 5 SP - 1 EP - 33 PB - Springer Nature AN - OPUS4-63465 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - JOUR A1 - Mechtcherine, Viktor A1 - Muthukrishnan, Shravan A1 - Robens-Radermacher, Annika A1 - Wolfs, Rob A1 - Versteege, Jelle A1 - Menna, Costantino A1 - Ozturk, Onur A1 - Ozyurt, Nilufer A1 - Roupec, Josef A1 - Richter, Christiane A1 - Jungwirth, Jörg A1 - Miranda, Luiza A1 - Ammann, Rebecca A1 - Caron, Jean‑François A1 - de Bono, Victor A1 - Monte, Renate A1 - Navarrete, Iván A1 - Eugenin, Claudia A1 - Lombois‑Burger, Hélène A1 - Baz, Bilal A1 - Sinka, Maris A1 - Sapata, Alise A1 - Harbouz, Ilhame A1 - Zhang, Yamei A1 - Jia, Zijian A1 - Kruger, Jacques A1 - Mostert, Jean‑Pierre A1 - Štefančič, Mateja A1 - Hanžič, Lucija A1 - Kaci, Abdelhak A1 - Rahal, Said A1 - Santhanam, Manu A1 - Bhattacherjee, Shantanu A1 - Snguanyat, Chalermwut A1 - Arunothayan, Arun A1 - Zhao, Zengfeng A1 - Mai, Inka A1 - Rasehorn, Inken Jette A1 - Böhler, David A1 - Freund, Niklas A1 - Lowke, Dirk A1 - Neef, Tobias A1 - Taubert, Markus A1 - Auer, Daniel A1 - Hechtl, C. Maximilian A1 - Dahlenburg, Maximilian A1 - Esposito, Laura A1 - Buswell, Richard A1 - Kolawole, John A1 - Isa, Muhammad Nura A1 - Liu, Xingzi A1 - Wang, Zhendi A1 - Subramaniam, Kolluru A1 - Bos, Freek T1 - Mechanical properties of 3D printed concrete: a RILEM 304-ADC interlaboratory study – compressive strength and modulus of elasticity N2 - Traditional construction techniques, such as in-situ casting and pre-cast concrete methods, have well-established testing protocols for assessing compressive strength and modulus of elasticity, including specific procedures for sample preparation and curing. In contrast, 3D concrete printing currently lacks standardized testing protocols, potentially contributing to the inconsistent results reported in previous studies. To address this issue, RILEM TC 304-ADC initiated a comprehensive interlaboratory study on the mechanical properties of 3D printed concrete. This study involves 30 laboratories worldwide, contributing 34 sets of data, with some laboratories testing more than one mix design. The compressive strength and modulus of elasticity were determined under three distinct conditions: Default, where each laboratory printed according to their standard procedure followed by water bath curing; Deviation 1, which involved creating a cold joint by increasing the time interval between printing layers; and Deviation 2, where the standard printing process was used, but the specimens were cured under conditions different from water bath. Some tests were conducted at two different scales based on specimen size—“mortar-scale” and “concrete-scale”—to investigate the size effect on compressive strength. Since the mix design remained identical for both scales, the only variable was the specimen size. This paper reports on the findings from the interlaboratory study, followed by a detailed investigation into the influencing parameters such as extraction location, cold joints, number of interlayers, and curing conditions on the mechanical properties of the printed concrete. As this study includes results from laboratories worldwide, its contribution to the development of relevant standardized testing protocols is critical. KW - Additive manufacturing KW - Digital fabrication KW - Hardened concrete KW - Compressive strength KW - Young's modulus PY - 2025 UR - https://nbn-resolving.org/urn:nbn:de:kobv:b43-634672 DO - https://doi.org/10.1617/s11527-025-02688-9 SN - 1871-6873 VL - 58 IS - 5 SP - 1 EP - 30 PB - Springer Nature AN - OPUS4-63467 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - GEN A1 - Strobl, Dominic A1 - Unger, Jörg F. A1 - Chady, G. 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 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 flexibil- ity and quality of a process. Typically, before producing a whole additive manufacturing structure, a simplified experiment in form of a bead-on- 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 devel- oped, 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 tem- perature. 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 - Ermüdung PY - 2023 DO - https://doi.org/10.5281/zenodo.7456813 PB - Zenodo CY - Geneva AN - OPUS4-59651 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - JOUR A1 - Robens-Radermacher, Annika A1 - Schmidt, Wolfram A1 - Unger, Jörg F. A1 - Mezhov, Alexander T1 - Characterization of temperature influence on the structural build-up of 3D printed concrete N2 - 3D concrete printing technologies enhance design freedom while reducing material use and costs without the need for formwork. Thereby, structural build-up is the key property governing stability and early strength evolution of 3D printed concrete after placement. Structural build-up is influenced by various factors, i.e., environmental conditions such as temperature. In this paper, the influence of ambient temperature on structural build-up was investigated through experimental and numerical approaches. Three experimental setups (small amplitude oscillatory shear, constant shear rate, and small amplitude oscillatory extensional tests) were applied to materials of increasing complexity under varying temperature conditions. A common modeling framework based on the maturity approach was developed to capture the time and temperature evolution. A stochastic framework was employed to estimate the unknown model parameters using experimental data. Experimental results demonstrate a significant temperature influence on structural build-up, consistent across all test setups and materials. The calibrated models successfully predict the structural build-up under different temperatures, confirming the applicability of the maturity approach to rheological parameters at early age. Furthermore, the stochastic parameter estimation allows a correct quantification of the uncertainties, enhancing model reliability. The comparison of two time evolution formulations indicates that a model with an additional linear stage is required for predicting the increase of the storage moduli ( $${G}{\prime}$$ G ′ , $${E}{\prime}$$ E ′ ). In conclusion, the study demonstrates that temperature significantly affects the structural build-up, and that the proposed modeling approach allows to predict this behavior. KW - Structural build-up KW - 3D concrete printing KW - Rheology KW - Temperature influence KW - Modeling KW - Green intelligent building PY - 2026 UR - https://nbn-resolving.org/urn:nbn:de:kobv:b43-654138 DO - https://doi.org/10.1617/s11527-025-02931-3 SN - 1359-5997 VL - 59 IS - 2 SP - 1 EP - 20 PB - Springer Science and Business Media LLC AN - OPUS4-65413 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - GEN A1 - Robens-Radermacher, Annika T1 - Dataset for publication: Characterization of temperature influence on the structural built-up of 3D concrete N2 - Implementation, data, and results for the generation of the study "Characterization of temperature influence on the structural built-up of 3D concrete". In this study, the influence of temperature on structural build-up is investigated. A significant temperature influence is demonstrated for three experimental setups (small amplitude oscillatory shear, constant shear rate, and small amplitude oscillatory extensional tests) using different materials. A common modeling framework capturing the time- and temperature evolution is derived based on the maturity approach. Two alternative formulations for the time evolution were proposed. Both models were calibrated using a probabilistic approach, allowing for uncertainty quantification. The calibrated models successfully predict the structural build-up under different ambient temperature conditions. KW - Structural build-up KW - 3D concrete printing KW - Modeling KW - Parameter identification KW - Temperature influence PY - 2025 DO - https://doi.org/10.5281/zenodo.15845818 PB - Zenodo CY - Geneva AN - OPUS4-64982 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Robens-Radermacher, Annika T1 - Temperature dependent modelling approach for early age behavior of printable mortars N2 - For extrusion-based 3D concrete printing, the early age mechanical behavior is influenced by various time dependent phenomena: structural build-up, plasticity as well as viscosity. The structural build-up is governing the stability and early-age strength development of the fresh printable cementitious materials and with that influencing the printability, buildability, and open time of the printing process. Generally, it is influenced by a number of factors, i.e. composition of the printable material, printing regime, and ambient conditions (temperature, humidity, etc.). There are several approaches to model the structural build-up of cementitious materials. All models are based on a time-dependent internal structural parameter describing the flocculation state, which is assumed to be zero after mixing and increases with time. The approaches differ in the definition of the time dependency (linear, exponential, bi-linear). Usually, the parameters are defined for a specific material composition without considering the influence of ambient conditions. In this contribution, the bi-linear structural build-up model [Kruger et al., Construction and Building Materials 224, 2019] is extended by the temperature influence. Temperature changes will occur in real life printing processes due to changing ambient conditions (summer, winter, day, night) as well as the printing process (pressure changes etc.) and have a significant impact on the structural build-up process: an increase of the temperature leads to a faster dissolution of cement phases, accelerates hydration and boosts the Brownian motion. For that reason, the model parameters are simulated as temperature dependent using an Arrhenius function. Furthermore, the proposed extended model is calibrated based on measurement data using Bayesian inference. A very good agreement of the predicted model data with the measured control data was reached. Additionally, the structural build-up model is integrated into a viscoelastic and elastoplastic mechanical model, simulating the whole mechanical behavior during layer deposition. T2 - Eighth International Symposium on Life-Cycle Civil Engineering (IALCCE 2023) CY - Milan, Italy DA - 03.07.2023 KW - 3D concrete printing KW - Material characterization KW - Structural build-up KW - Thixotropy KW - Model calibration PY - 2023 AN - OPUS4-58218 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Mezhov, Alexander A1 - Robens-Radermacher, Annika T1 - Temperature Impact on the Structural Build-Up of Cementitious Materials - Experimental and Modelling Study N2 - With increasing focus on industrialized processing, investigating, understanding, and modelling the structural build-up of cementitious materials becomes more important. The structural build-up governs the key property of fresh printable materials -- buildability -- and it influences the mechanical properties after the deposition. The structural build-up rate can be adjusted by optimization of the mixture composition and the use of concrete admixtures. Additionally, it is known, that the environmental conditions, i.e. humidity and temperature have a significant impact on the kinetic of cement hydration and the resulting hardened properties, such as shrinkage, cracking resistance etc. In this study, small amplitude oscillatory shear (SAOS) tests are applied to examine the structural build-up rate of cement paste subject to different temperatures under controlled humidity. The results indicate significant influences of the ambient temperature on the intensity of the re-flocculation (Rthix) rate, while the structuration rate (Athix) is almost not affected. A bi-linear thixotropy model extended by temperature dependent parameters coupled with a linear viscoelastic material model is proposed to simulate the mechanical behaviour considering the structural build-up during the SAOS test. T2 - Third RILEM International Conference on Concrete and Digital Fabrication (Digital Concrete 2022) CY - Loughborough, UK DA - 27.06.2022 KW - Structural build-up KW - Rheological properties KW - Modelling PY - 2022 AN - OPUS4-55581 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Mezhov, Alexander A1 - Robens-Radermacher, Annika ED - Mezhov, Alexander ED - Robens-Radermacher, Annika ED - Zhang, Kun ED - Kühne, Hans-Carsten ED - Unger, Jörg F. ED - Schmidt, Wolfram T1 - Temperature Impact on the Structural Build-Up of Cementitious Materials - Experimental and Modelling Study N2 - With increasing focus on industrialized processing, investigating, understanding, and modelling the structural build-up of cementitious materials becomes more important. The structural build-up governs the key property of fresh printable materials -- buildability -- and it influences the mechanical properties after the deposition. The structural build-up rate can be adjusted by optimization of the mixture composition and the use of concrete admixtures. Additionally, it is known, that the environmental conditions, i.e. humidity and temperature have a significant impact on the kinetic of cement hydration and the resulting hardened properties, such as shrinkage, cracking resistance etc. In this study, small amplitude oscillatory shear (SAOS) tests are applied to examine the structural build-up rate of cement paste subject to different temperatures under controlled humidity. The results indicate significant influences of the ambient temperature on the intensity of the re-flocculation (Rthix) rate, while the structuration rate (Athix) is almost not affected. A bi-linear thixotropy model extended by temperature dependent parameters coupled with a linear viscoelastic material model is proposed to simulate the mechanical behaviour considering the structural build-up during the SAOS test T2 - Third RILEM International Conference on Concrete and Digital Fabrication (Digital Concrete 2022) CY - Loughborough, UK DA - 27.06.2022 KW - Structural build-up KW - Rheological properties KW - Modelling PY - 2022 SN - 978-3-031-06116-5 DO - https://doi.org/10.1007/978-3-031-06116-5_49 VL - 37 SP - 330 EP - 336 PB - Springer International Publishing CY - Cham AN - OPUS4-55580 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 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 - Robens-Radermacher, Annika A1 - Unger, Jörg F. T1 - Efficient reliability analysis coupling importance sampling using adaptive subset simulation and PGD model reduction N2 - One of the most important goals in civil engineering is to guaranty the safety of constructions. National standards prescribe a required failure probability in the order of 10−6 (e.g. DIN EN 199:2010-12). The estimation of these failure probabilities is the key point of structural reliability analysis. Generally, it is not possible to compute the failure probability analytically. Therefore, simulation-based methods as well as methods based on surrogate modeling or response surface methods have been developed. Nevertheless, these methods still require a few thousand evaluations of the structure, usually with finite element (FE) simulations, making reliability analysis computationally expensive for relevant applications. The aim of this contribution is to increase the efficiency of structural reliability analysis by using the advantages of model reduction techniques. Model reduction is a popular concept to decrease the computational effort of complex numerical simulations while maintaining a reasonable accuracy. Coupling a reduced model with an efficient variance reducing sampling algorithm significantly reduces the computational cost of the reliability analysis without a relevant loss of accuracy. T2 - GAMM - Gesellschaft für Angewandte Mathematik und Mechanik e.V. CY - Wien, Austria DA - 18.02.2019 KW - PGD model reduction KW - Numerical models KW - FE modelling PY - 2019 DO - https://doi.org/10.1002/pamm.201900169 VL - 19 IS - 1 SP - 1 EP - 2 PB - Wiley- VCH Verlag GmbH CY - Weinheim AN - OPUS4-49786 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Robens-Radermacher, Annika T1 - Coupling PGD model reduction with importance sampling using adaptive subset simulation for reliability analysis N2 - The key point of structural reliability analysis is the estimation of the failure probability. This probability is defined as the integral over the failure domain which is given by a limit state function. Usually, this function is only implicit given by an underlying finite element simulation of the structure. It is generally not possible to solve the integral analytically. For that reason, numerical methods based on sampling and surrogates have been developed. Nevertheless, these sampling methods still require a few thousand calculations of the underlying finite element model, making reliability analysis computationally expensive for relevant applications. Coupling a reduced order model (proper generalized decomposition) with an efficient variance reducing sampling algorithm can reduce the computational cost of reliability analysis drastically. In the proposed method, an importance sampling technique is coupled with a reduced structural model by means of PGD to estimate the failure probability. Instead of calculating the design point e.g. with optimization algorithms, the design point is adaptively estimated by using the idea of subset simulation. The failure probability is estimated in an iterative scheme based on adaptively computing the design point and refining the PGD model. T2 - 5th international Workshop Reduced Basis, POD and PGD Model Reduction Techniques (MORTech) 2019 CY - Paris, France DA - 19.11.2019 KW - Reliability KW - Probability of failure KW - Importance sampling KW - Proper Generalized Decomposition KW - Reduced order models PY - 2019 AN - OPUS4-49801 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Robens-Radermacher, Annika T1 - Efficient reliability analysis by combining uncertain measurement data, Bayesian model updating and reduced order modeling N2 - The efficiency of structural model updating and the subsequent reliability analysis is increased by using the advantages of reduced order models. Coupling a reduced model of the structure of interest with a Bayesian model updating approach or an reliability analysis to estimate the failure probability reduce the computational cost of such complex analyses drastically. T2 - 8th Workshop on High-Dimensional Approximation (HDA) 2019 CY - Zurich, Switzerland DA - 09.09.2019 KW - Reduced order modeling KW - Bayesian model updating PY - 2019 AN - OPUS4-49035 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Robens-Radermacher, Annika T1 - Efficient reliability analysis coupling important sampling using adaptive subset simulation and PGD model reduction N2 - The key point of structural reliability analysis is the estimation of the failure probability (Pf), typically a rare event. This probability is defined as the integral over the failure domain which is given by a limit state function. Usually, this function is only implicit given by an underlying finite element simulation of the structure. It is generally not possible to solve the integral for Pf analytically. For that reason, simulation-based methods as well as methods based on surrogate modeling (or Response surface methods) has been developed. Nevertheless, these variance reducing methods still require a few thousand calculations of the underlying finite element model, making reliability Analysis computationally expensive for real applications. T2 - GAMM - Gesellschaft für Angewandte Mathematik und Mechanik e.V. CY - Vienna, Austria DA - 18.02.2019 KW - PGD model reduction PY - 2019 AN - OPUS4-48628 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - GEN A1 - Jafari, Abbas A1 - Titscher, Thomas A1 - Robens-Radermacher, Annika T1 - Bayem: Implementation and derivation of “variational Bayesian inference for a nonlinear forward model [Chappell et al 2008]“ for arbitrary, user-defined model errors N2 - A python implementation of an analytical variational Bayes algorithm of "Variational Bayesian inference for a nonlinear forward model", Chappell, Michael A., Adrian R. Groves, Brandon Whitcher, and Mark W. Woolrich, IEEE Transactions on Signal Processing 57, no. 1 (2008): 223-236, with an updated free energy equation to correctly capture the log evidence. The algorithm requires a user-defined model error allowing an arbitrary combination of custom forward models and measured data. KW - Implementation KW - Variational Bayesian inference KW - Nonlinear forward model PY - 2025 DO - https://doi.org/10.5281/zenodo.17804665 PB - Zenodo CY - Geneva AN - OPUS4-65268 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Robens-Radermacher, Annika T1 - Modeling the influence of temperature for extrusion based 3d concrete printing from material to structural stability N2 - Abstract: 3D concrete printing (3DCP) aims to revolutionize construction by increasing automation, reducing material usage, and enabling customized designs. Despite its potential, the lack of regulations and reliance on trial-and-error methods result in significant waste and inefficiencies. Reliable models are needed to predict and control the complex printing process with its various influencing factors from material, process, and environment. This study aims to develop a structural model to predict print stability and prevent buckling and material failure in extrusion-based 3D concrete printing (3DCP), with a focus on environmental influences, particularly temperature. The structural build-up of the material is crucial for stability but is influenced by material ingredients, water-binder ratio, and ambient conditions, which vary in real-world projects. It describes the process of cementitious material gaining strength and stability during its early ages due to thixotropy and early hydration. Modeling that, a time- and temperature-dependent model for the evolution of early-age material parameters, such as stiffness, is derived. The model employs the maturity method, using an equivalent time to capture the temperature influence. It is verified using experimental data on stiffness evolution from squeeze flow tests and yield stress evolution measured from rotational rheometer tests. The model parameters are estimated using Bayesian inference, and validation shows good agreement with experimental data for both parameters at the material level. Subsequently, the derived time- and temperature-dependent stiffness model is adapted into a structural simulation using an elastoplastic material law with nonlinear hardening to study the temperature effect on the stability of 3DCP. Layers are activated sequentially based on a pseudo-density approach. The method is illustrated with an example of a printed wall with a width of one layer under varying ambient temperatures. The temperature impact on buckling and material failure during printing is demonstrated and numerically investigated through a sensitivity study. T2 - 95 th Annual Meeting of the International Association of Applied Mathematics and Mechanics (GAMM) CY - Poznan, Poland DA - 07.04.2025 KW - 3D concrete printing KW - Structural build-up KW - Temperature KW - Maturity method KW - Structural simulation PY - 2025 AN - OPUS4-62966 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - JOUR A1 - Hüsken, Götz A1 - Strangfeld, Christoph A1 - Robens-Radermacher, Annika A1 - von Werder, Julia A1 - Weigel, Sandra A1 - Mezhov, Alexander T1 - 63. DAfStb-Forschungskolloquium in der BAM - Themenblock 3: Innovative Technologien N2 - Innovationen sind der Treiber des technologischen Fortschritts. Durch die Anwendung innovativer Technologien, Produktionsverfahren und neuer Materialien können Effizienzsteigerungen erzielt werden, die sowohl zu einer Kosten- als auch Materialreduzierung führen können. Gerade vor dem Hintergrund einer nachhaltigen Entwicklung sind Innovationen der Schlüssel zu einem verantwortungsvollen Umgang mit Ressourcen und Rohstoffen. Im Rahmen des 63. DAfStb-Forschungskolloquiums (Tagungsband: DOI 10.26272/opus4-61338) an der BAM wurden innovative Ansätze im Bereich effizienter Fertigungstechnologien und neuer Materialien vorgestellt, die nachfolgend kurz zusammengefasst werden. T2 - 11. Jahrestagung des DAfStb mit 63. Forschungskolloquium der BAM Green Intelligent Building CY - Berlin, Germany DA - 16.10.2024 KW - Additive Fertigung KW - Biorezeptive Oberflächen KW - Biopolymere PY - 2025 SN - 0005-9846 VL - 75 IS - 4 SP - 134 EP - 135 PB - concrete content UG CY - Schermbeck AN - OPUS4-63069 LA - deu AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Robens-Radermacher, Annika T1 - Modellierung und Simulation von 3D Betondruck – Design- und Prozessoptimierung N2 - Der 3D Betondruck ermöglicht die effiziente und ressourcenschonendere Herstellung maßgeschneiderter Betonstrukturen. Trotz des großen Potentials gibt es bisher keine einheitlichen Normen und Standards für den sicheren und robusten 3D Betondruck. Der Beitrag zeigt das Potential numerischer Methoden und Modelle zur effizienten und ressourcenschonenden Design- und Prozessoptimierung des 3D Betondrucks. Dazu werden die aktuellen Forschungsarbeiten im Bereich der Entwicklung robuster und zuverlässiger numerischer Zwillinge, geeigneter Optimierungstools sowie digitaler Workflows diskutiert. T2 - 11. Jahrestagung des DAfStb mit 63. Forschungskolloquium der BAM Green Intelligent Building CY - Berlin, Germany DA - 16.10.2024 KW - 3D Betondruck KW - Design- und Prozessoptimierung KW - Modellierung KW - Simulation PY - 2024 AN - OPUS4-61575 LA - mul AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER -