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 - GEN A1 - Strobl, Domninic 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 in 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 the application, e. g. for model parameter estimation or online process control. Model order reduction, a solution to preserve accuracy while reducing complexity, is explored. This paper addresses challenges in developing a reduced model 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 examples 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 KW - Proper generalized decomposition KW - Sensitivity analysis KW - Thermal transient problem PY - 2024 DO - https://doi.org/10.5281/zenodo.10102489 PB - Zenodo CY - Geneva AN - OPUS4-62235 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 - 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 - CONF A1 - Strobl, Dominic T1 - Reduced Order Model with Domain Mapping for Temperature Field Simulation of Wire Arc Additive Manufacturing N2 - Additive manufacturing (AM) has revolutionized the manufacturing industry, offering a new paradigm to produce complex geometries and parts with customized properties. Among the different AM techniques, the wire arc additive manufacturing (WAAM) process has gained significant attention due to its high deposition rate and low equipment cost. However, the process is characterized by a complex thermal history, dynamic metallurgy, and mechanical behaviour that make it challenging to simulate it in real-time for online process control and optimization. In this context, a reduced order model (ROM) using the proper generalized decomposition (PGD) method is proposed as a powerful tool to overcome the limitations of conventional numerical methods and enable the real-time simulation of the temperature field of WAAM processes. Though, the simulation of a moving heat source leads to a hardly separable parametric problem, which is handled by applying a novel mapping approach. Using this procedure, it is possible to create a simple separated representation of the model, also allowing to simulate multiple layers. In this contribution, a PGD model is derived for the WAAM procedure simulating the temperature field. A good agreement with a standard finite element method is shown. The reduced model is further used in a stochastic model parameter estimation using Bayesian inference, speeding up calibrations and ultimately leading to a calibrated real-time simulation. T2 - SIM-AM 2023 CY - Munich, Germany DA - 26.07.2023 KW - Additive manufacturing KW - Reduced Order Model PY - 2023 AN - OPUS4-58253 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Strobl, Dominic T1 - PGD model with domain mapping of Bead-on-Plate weld simulation for wire arc additive manufacturing N2 - Numerical simulations are essential in predicting the behavior of systems in many engineering fields and industrial sectors. The development of accurate virtual representations of actual physical products or processes allows huge savings in cost and resources. In fact, digital twins would allow reducing the number of real, physical prototypes, tests, and experiments, thus also increasing the sustainability of the production processes and products’ lifetime. Standard numerical methods fail in providing real time simulations, especially for complex processes such as additive manufacturing applications. This work aims to build up a reduced order model for efficient wire arc additive manufacturing simulations by using the proper generalized decomposition (PGD) [1,2] method. Model order reduction is a popular concept to decrease the computational effort, where each evaluation of the reduced forward model is faster than evaluations using classical methods, even for complex models. The simulation of a moving heat source leads to a hardly separable parametric problem, which is solved by a new mapping approach [3]. Using this procedure, it is possible to create a simple separated representation of the forward model. In this contribution, a PGD model is derived for the first part of wire arc additive manufacturing: bead-on-plate weld. An excellent agreement with a standard finite element method is shown. The reduced model is further used in a model calibration set up, speeding up calibrations and ultimately leading to an optimized real-time simulation. T2 - The 8th European Congress on Computational Methods in Applied Sciences and Engineering (ECCOMAS) 2022 CY - Oslo, Norway DA - 05.06.2022 KW - PGD KW - Model calibration KW - Hardly separable problem KW - Additive manufacturing PY - 2022 AN - OPUS4-55111 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Strobl, Domninic T1 - Reduced order model for temperature field simulation of wire arc additive manufacturing N2 - Additive manufacturing (AM) has revolutionized the manufacturing industry, offering a new paradigm to produce complex geometries and parts with customized properties. Among the different AM techniques, the wire arc additive manufacturing (WAAM) process has gained significant attention due to its high deposition rate and low equipment cost. However, the process is characterized by a complex thermal history making it challenging to simulate it in real-time for online process control and optimization. In this context, a reduced order model (ROM) using the proper generalized decomposition (PGD) method [1] is proposed as a powerful tool to overcome the limitations of conventional numerical methods and enable the real-time simulation of the temperature field of WAAM processes. These simulations use a moving heat source leading to a hardly separable parametric problem, which is handled by applying a novel mapping approach [2]. This procedure makes it possible to create a separated representation of the model, which is required to apply the PGD method, allowing a simulation of multiple layers. In this contribution, a PGD model is derived for the temperature field simulation of the WAAM process. A layer-by-layer simulation in combination with a compression of the PGD modes, without influencing the approximation error, is shown. The compression is an essential step since the modes sum up quickly over the layers and thus a reduction of the number of modes is needed. Furthermore, using an element birth technique leads usually to an update of the mesh or a new mesh in each time step. Though, this is not the case applying the mapping approach, where only a single nonchanging mesh is required to simulate the deposition of a whole layer. T2 - ECCOMAS Congress 2024 CY - Lisbon, Portugal DA - 03.06.2024 KW - Reduced Order Model KW - Proper Generalized Decomposition KW - Thermal transient problem KW - Additive manufacturing PY - 2024 AN - OPUS4-62231 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER -