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 - 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 - 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 - 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 - 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 - 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 - 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 - 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 -