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Improvement in an Analytical Approach for Modeling the Melting Process in Single-Screw Extruders. <i>Polymers</i>, <i>16</i>(22), 3130. <a href=\"https://doi.org/10.3390/polym16223130\">https://doi.org/10.3390/polym16223130</a>","chicago":"Schöppner, Volker, Florian Brüning, and Felix Knaup. “Improvement in an Analytical Approach for Modeling the Melting Process in Single-Screw Extruders.” <i>Polymers</i> 16, no. 22 (2024): 3130. <a href=\"https://doi.org/10.3390/polym16223130\">https://doi.org/10.3390/polym16223130</a>.","ieee":"V. Schöppner, F. Brüning, and F. Knaup, “Improvement in an Analytical Approach for Modeling the Melting Process in Single-Screw Extruders,” <i>Polymers</i>, vol. 16, no. 22, p. 3130, 2024, doi: <a href=\"https://doi.org/10.3390/polym16223130\">10.3390/polym16223130</a>.","ama":"Schöppner V, Brüning F, Knaup F. Improvement in an Analytical Approach for Modeling the Melting Process in Single-Screw Extruders. <i>Polymers</i>. 2024;16(22):3130. doi:<a href=\"https://doi.org/10.3390/polym16223130\">10.3390/polym16223130</a>"},"year":"2024","volume":16,"date_created":"2025-04-02T09:51:32Z","author":[{"first_name":"Volker","last_name":"Schöppner","full_name":"Schöppner, Volker","id":"20530"},{"id":"72920","full_name":"Brüning, Florian","last_name":"Brüning","first_name":"Florian"},{"last_name":"Knaup","id":"45124","full_name":"Knaup, Felix","first_name":"Felix"}],"date_updated":"2025-04-02T11:21:00Z","doi":"10.3390/polym16223130","title":"Improvement in an Analytical Approach for Modeling the Melting Process in Single-Screw Extruders","publication":"Polymers","type":"journal_article","status":"public","abstract":[{"lang":"eng","text":"Most single-screw extruders used in the plastics processing industry are plasticizing extruders, designed to melt solid pellets or powders within the screw channel during processing. In many cases, the efficiency of the melting process acts as the primary throughput-limiting factor. If the material melts too late in the process, it may not be sufficiently mixed, resulting in substandard product quality. Accurate prediction of the melting process is therefore essential for efficient and cost-effective machine design. A practical method for engineers is the modeling of the melting process using mathematical–physical models that can be solved without complex numerical methods. These models enable rapid calculations while still providing sufficient predictive accuracy. This study revisits the modified Tadmor model by Potente, which describes the melting process and predicts the delay-zone length, extending from the hopper front edge to the point of melt pool formation. Based on extensive experimental investigations, this model is adapted by redefining the flow temperatures at the phase boundary and accounting for surface porosity at the beginning of the melting zone. Additionally, the effect of variable solid bed dynamics on model accuracy is examined. Significant model improvements were achieved by accounting for reduced heat flow into the solid bed due to the porous surface structure in the solid conveying zone, along with a new assumption for the flow temperature at the phase boundary between the solid bed and melt film."}],"department":[{"_id":"9"},{"_id":"321"},{"_id":"367"}],"user_id":"59363","_id":"59243","language":[{"iso":"eng"}],"keyword":["delay zone","extrusion","melting modeling"]},{"doi":"10.1038/s41529-024-00470-w","title":"Corrosion fatigue behavior of nanoparticle modified iron processed by electron powder bed fusion","date_created":"2025-11-18T12:11:06Z","author":[{"full_name":"Wackenrohr, Steffen","last_name":"Wackenrohr","first_name":"Steffen"},{"first_name":"Christof Johannes Jaime","full_name":"Torrent, Christof Johannes Jaime","last_name":"Torrent"},{"first_name":"Sebastian","full_name":"Herbst, Sebastian","last_name":"Herbst"},{"first_name":"Florian","last_name":"Nürnberger","full_name":"Nürnberger, Florian"},{"first_name":"Philipp","full_name":"Krooss, Philipp","last_name":"Krooss"},{"last_name":"Frenck","full_name":"Frenck, Johanna-Maria","first_name":"Johanna-Maria"},{"last_name":"Ebbert","full_name":"Ebbert, Christoph","id":"7266","first_name":"Christoph"},{"first_name":"Markus","id":"15182","full_name":"Voigt, Markus","last_name":"Voigt"},{"first_name":"Guido","full_name":"Grundmeier, Guido","id":"194","last_name":"Grundmeier"},{"last_name":"Niendorf","full_name":"Niendorf, Thomas","first_name":"Thomas"},{"first_name":"Hans Jürgen","full_name":"Maier, Hans Jürgen","last_name":"Maier"}],"volume":8,"date_updated":"2025-11-18T12:11:30Z","publisher":"Springer Science and Business Media LLC","citation":{"short":"S. Wackenrohr, C.J.J. Torrent, S. Herbst, F. Nürnberger, P. Krooss, J.-M. Frenck, C. Ebbert, M. Voigt, G. Grundmeier, T. Niendorf, H.J. Maier, Npj Materials Degradation 8 (2024).","bibtex":"@article{Wackenrohr_Torrent_Herbst_Nürnberger_Krooss_Frenck_Ebbert_Voigt_Grundmeier_Niendorf_et al._2024, title={Corrosion fatigue behavior of nanoparticle modified iron processed by electron powder bed fusion}, volume={8}, DOI={<a href=\"https://doi.org/10.1038/s41529-024-00470-w\">10.1038/s41529-024-00470-w</a>}, number={149}, journal={npj Materials Degradation}, publisher={Springer Science and Business Media LLC}, author={Wackenrohr, Steffen and Torrent, Christof Johannes Jaime and Herbst, Sebastian and Nürnberger, Florian and Krooss, Philipp and Frenck, Johanna-Maria and Ebbert, Christoph and Voigt, Markus and Grundmeier, Guido and Niendorf, Thomas and et al.}, year={2024} }","mla":"Wackenrohr, Steffen, et al. “Corrosion Fatigue Behavior of Nanoparticle Modified Iron Processed by Electron Powder Bed Fusion.” <i>Npj Materials Degradation</i>, vol. 8, no. 1, 49, Springer Science and Business Media LLC, 2024, doi:<a href=\"https://doi.org/10.1038/s41529-024-00470-w\">10.1038/s41529-024-00470-w</a>.","apa":"Wackenrohr, S., Torrent, C. J. J., Herbst, S., Nürnberger, F., Krooss, P., Frenck, J.-M., Ebbert, C., Voigt, M., Grundmeier, G., Niendorf, T., &#38; Maier, H. J. (2024). Corrosion fatigue behavior of nanoparticle modified iron processed by electron powder bed fusion. <i>Npj Materials Degradation</i>, <i>8</i>(1), Article 49. <a href=\"https://doi.org/10.1038/s41529-024-00470-w\">https://doi.org/10.1038/s41529-024-00470-w</a>","ama":"Wackenrohr S, Torrent CJJ, Herbst S, et al. Corrosion fatigue behavior of nanoparticle modified iron processed by electron powder bed fusion. <i>npj Materials Degradation</i>. 2024;8(1). doi:<a href=\"https://doi.org/10.1038/s41529-024-00470-w\">10.1038/s41529-024-00470-w</a>","chicago":"Wackenrohr, Steffen, Christof Johannes Jaime Torrent, Sebastian Herbst, Florian Nürnberger, Philipp Krooss, Johanna-Maria Frenck, Christoph Ebbert, et al. “Corrosion Fatigue Behavior of Nanoparticle Modified Iron Processed by Electron Powder Bed Fusion.” <i>Npj Materials Degradation</i> 8, no. 1 (2024). <a href=\"https://doi.org/10.1038/s41529-024-00470-w\">https://doi.org/10.1038/s41529-024-00470-w</a>.","ieee":"S. Wackenrohr <i>et al.</i>, “Corrosion fatigue behavior of nanoparticle modified iron processed by electron powder bed fusion,” <i>npj Materials Degradation</i>, vol. 8, no. 1, Art. no. 49, 2024, doi: <a href=\"https://doi.org/10.1038/s41529-024-00470-w\">10.1038/s41529-024-00470-w</a>."},"intvolume":"         8","year":"2024","issue":"1","publication_status":"published","publication_identifier":{"issn":["2397-2106"]},"language":[{"iso":"eng"}],"article_number":"49","user_id":"7266","department":[{"_id":"35"},{"_id":"302"},{"_id":"321"}],"_id":"62236","status":"public","abstract":[{"text":"<jats:title>Abstract</jats:title><jats:p>Due to its excellent biocompatibility, pure iron is a very promising implant material, but often features corrosion rates that are too low. Using additive manufacturing and modified powders the microstructure and, thus, the material properties, e.g., the corrosion properties, can be tailored for specific applications. Within the scope of this study, pure iron powder was modified with different amounts of CeO<jats:sub>2</jats:sub> or Fe<jats:sub>2</jats:sub>O<jats:sub>3</jats:sub> nanoparticles and subsequently processed by Electron Beam Powder Bed Fusion (PBF-EB/M). The corrosion-fatigue behavior of CeO<jats:sub>2</jats:sub> and Fe<jats:sub>2</jats:sub>O<jats:sub>3</jats:sub> modified iron was investigated using rotation bending tests under the influence of simulated body fluid (m-SBF). While the modification using Fe<jats:sub>2</jats:sub>O<jats:sub>3</jats:sub> showed reduced fatigue and corrosion-fatigue strengths, it could be demonstrated that the modification with CeO<jats:sub>2</jats:sub> is characterized by improved fatigue properties. The superior fatigue properties in air are attributed to the positive impact of dispersion strengthening. Additionally, an increased degradation rate compared to pure iron could be observed, eventually promoting an earlier failure of the specimens in the corrosion fatigue tests.</jats:p>","lang":"eng"}],"type":"journal_article","publication":"npj Materials Degradation"},{"language":[{"iso":"eng"}],"department":[{"_id":"952"},{"_id":"321"}],"user_id":"85414","_id":"62767","status":"public","abstract":[{"lang":"eng","text":"<jats:title>Abstract</jats:title>\r\n          <jats:p>In this study, we develop a novel multi-fidelity deep learning approach that transforms low-fidelity solution maps into high-fidelity ones by incorporating parametric space information into an autoencoder architecture. This method’s integration of parametric space information significantly reduces the amount of training data needed to effectively predict high-fidelity solutions from low-fidelity ones. In this study, we examine a two-dimensional steady-state heat transfer analysis within a heterogeneous materials microstructure. The heat conductivity coefficients for two different materials are condensed from a 101 <jats:inline-formula>\r\n              <jats:alternatives>\r\n                <jats:tex-math>$$\\times $$</jats:tex-math>\r\n                <mml:math xmlns:mml=\"http://www.w3.org/1998/Math/MathML\">\r\n                  <mml:mo>×</mml:mo>\r\n                </mml:math>\r\n              </jats:alternatives>\r\n            </jats:inline-formula> 101 grid to smaller grids. We then solve the boundary value problem on the coarsest grid using a pre-trained physics-informed neural operator network known as Finite Operator Learning (FOL). The resulting low-fidelity solution is subsequently upscaled back to a 101 <jats:inline-formula>\r\n              <jats:alternatives>\r\n                <jats:tex-math>$$\\times $$</jats:tex-math>\r\n                <mml:math xmlns:mml=\"http://www.w3.org/1998/Math/MathML\">\r\n                  <mml:mo>×</mml:mo>\r\n                </mml:math>\r\n              </jats:alternatives>\r\n            </jats:inline-formula> 101 grid using a newly designed enhanced autoencoder. The novelty of the developed enhanced autoencoder lies in the concatenation of heat conductivity maps of different resolutions to the decoder segment in distinct steps. Hence the developed algorithm is named microstructure-embedded autoencoder (MEA). We compare the MEA outcomes with those from finite element methods, the standard U-Net, and an interpolation approach as an upscaling technique. Our analysis shows that MEA outperforms these methods in terms of computational efficiency and error on representative test cases. As a result, the MEA serves as a potential supplement to neural operator networks, effectively upscaling low-fidelity solutions to high-fidelity while preserving critical details often lost in traditional upscaling methods, such as sharp interfaces features lost in the context of interpolation approaches.</jats:p>"}],"publication":"Computational Mechanics","type":"journal_article","doi":"10.1007/s00466-024-02568-z","title":"Introducing a microstructure-embedded autoencoder approach for reconstructing high-resolution solution field data from a reduced parametric space","volume":75,"date_created":"2025-12-03T12:37:08Z","author":[{"first_name":"Rasoul","last_name":"Najafi Koopas","full_name":"Najafi Koopas, Rasoul"},{"last_name":"Rezaei","full_name":"Rezaei, Shahed","first_name":"Shahed"},{"first_name":"Natalie","last_name":"Rauter","full_name":"Rauter, Natalie"},{"first_name":"Richard","id":"106876","full_name":"Ostwald, Richard","orcid":"0000-0003-2147-8444","last_name":"Ostwald"},{"last_name":"Lammering","full_name":"Lammering, Rolf","first_name":"Rolf"}],"publisher":"Springer Science and Business Media LLC","date_updated":"2025-12-03T12:51:26Z","page":"1377-1406","intvolume":"        75","citation":{"ieee":"R. Najafi Koopas, S. Rezaei, N. Rauter, R. Ostwald, and R. Lammering, “Introducing a microstructure-embedded autoencoder approach for reconstructing high-resolution solution field data from a reduced parametric space,” <i>Computational Mechanics</i>, vol. 75, no. 4, pp. 1377–1406, 2024, doi: <a href=\"https://doi.org/10.1007/s00466-024-02568-z\">10.1007/s00466-024-02568-z</a>.","chicago":"Najafi Koopas, Rasoul, Shahed Rezaei, Natalie Rauter, Richard Ostwald, and Rolf Lammering. “Introducing a Microstructure-Embedded Autoencoder Approach for Reconstructing High-Resolution Solution Field Data from a Reduced Parametric Space.” <i>Computational Mechanics</i> 75, no. 4 (2024): 1377–1406. <a href=\"https://doi.org/10.1007/s00466-024-02568-z\">https://doi.org/10.1007/s00466-024-02568-z</a>.","ama":"Najafi Koopas R, Rezaei S, Rauter N, Ostwald R, Lammering R. Introducing a microstructure-embedded autoencoder approach for reconstructing high-resolution solution field data from a reduced parametric space. <i>Computational Mechanics</i>. 2024;75(4):1377-1406. doi:<a href=\"https://doi.org/10.1007/s00466-024-02568-z\">10.1007/s00466-024-02568-z</a>","apa":"Najafi Koopas, R., Rezaei, S., Rauter, N., Ostwald, R., &#38; Lammering, R. (2024). Introducing a microstructure-embedded autoencoder approach for reconstructing high-resolution solution field data from a reduced parametric space. <i>Computational Mechanics</i>, <i>75</i>(4), 1377–1406. <a href=\"https://doi.org/10.1007/s00466-024-02568-z\">https://doi.org/10.1007/s00466-024-02568-z</a>","mla":"Najafi Koopas, Rasoul, et al. “Introducing a Microstructure-Embedded Autoencoder Approach for Reconstructing High-Resolution Solution Field Data from a Reduced Parametric Space.” <i>Computational Mechanics</i>, vol. 75, no. 4, Springer Science and Business Media LLC, 2024, pp. 1377–406, doi:<a href=\"https://doi.org/10.1007/s00466-024-02568-z\">10.1007/s00466-024-02568-z</a>.","short":"R. Najafi Koopas, S. Rezaei, N. Rauter, R. Ostwald, R. Lammering, Computational Mechanics 75 (2024) 1377–1406.","bibtex":"@article{Najafi Koopas_Rezaei_Rauter_Ostwald_Lammering_2024, title={Introducing a microstructure-embedded autoencoder approach for reconstructing high-resolution solution field data from a reduced parametric space}, volume={75}, DOI={<a href=\"https://doi.org/10.1007/s00466-024-02568-z\">10.1007/s00466-024-02568-z</a>}, number={4}, journal={Computational Mechanics}, publisher={Springer Science and Business Media LLC}, author={Najafi Koopas, Rasoul and Rezaei, Shahed and Rauter, Natalie and Ostwald, Richard and Lammering, Rolf}, year={2024}, pages={1377–1406} }"},"year":"2024","issue":"4","quality_controlled":"1","publication_identifier":{"issn":["0178-7675","1432-0924"]},"publication_status":"published"},{"abstract":[{"text":"<jats:title>Abstract</jats:title><jats:p>The open-source parameter identification tool ADAPT (A diversely applicable parameter identification Tool) is integrated with a machine learning-based approach for start value prediction in order to calibrate a Gurson–Tvergaard–Needleman (GTN) and a Lemaitre damage model. As representative example case-hardened steel 16MnCrS5 is elaborated. An artificial neural network (ANN) is initially trained by using load–displacement curves derived from simulations of a boundary value problem—instead of using data generated for homogeneous states of deformation at material point or one-element level—with varying material parameter combinations. The ANN is then employed so as to predict sets of material parameters that already provide close solutions to the experiment. These predicted parameter sets serve as starting values for a subsequent multi-objective parameter identification by using ADAPT. ADAPT allows for the consideration of input data from multiple scales, including integral data such as load–displacement curves, full-field data such as displacement and strain fields, and high-resolution experimental void data at the micro-scale. The influence of each data set on prediction quality is analyzed. Using various types of input data introduces additional information, enhancing prediction accuracy. The validation is carried out with respect to experimental void measurements of forward rod extruded parts. The results demonstrate, by incorporating void measurements in the optimization process, that it is possible to improve the quantitative prediction of ductile damage in the sense of void area fractions by factor 28 in forward rod extrusion.</jats:p>","lang":"eng"}],"status":"public","publication":"Archive of Applied Mechanics","type":"journal_article","language":[{"iso":"eng"}],"_id":"62770","department":[{"_id":"952"},{"_id":"321"}],"user_id":"85414","year":"2024","page":"2217-2242","intvolume":"        94","citation":{"chicago":"Gerlach, Jan, Robin Schulte, Alexander Schowtjak, Till Clausmeyer, Richard Ostwald, A. Erman Tekkaya, and Andreas Menzel. “Enhancing Damage Prediction in Bulk Metal Forming through Machine Learning-Assisted Parameter Identification.” <i>Archive of Applied Mechanics</i> 94, no. 8 (2024): 2217–42. <a href=\"https://doi.org/10.1007/s00419-024-02634-1\">https://doi.org/10.1007/s00419-024-02634-1</a>.","ieee":"J. Gerlach <i>et al.</i>, “Enhancing damage prediction in bulk metal forming through machine learning-assisted parameter identification,” <i>Archive of Applied Mechanics</i>, vol. 94, no. 8, pp. 2217–2242, 2024, doi: <a href=\"https://doi.org/10.1007/s00419-024-02634-1\">10.1007/s00419-024-02634-1</a>.","ama":"Gerlach J, Schulte R, Schowtjak A, et al. Enhancing damage prediction in bulk metal forming through machine learning-assisted parameter identification. <i>Archive of Applied Mechanics</i>. 2024;94(8):2217-2242. doi:<a href=\"https://doi.org/10.1007/s00419-024-02634-1\">10.1007/s00419-024-02634-1</a>","apa":"Gerlach, J., Schulte, R., Schowtjak, A., Clausmeyer, T., Ostwald, R., Tekkaya, A. E., &#38; Menzel, A. (2024). Enhancing damage prediction in bulk metal forming through machine learning-assisted parameter identification. <i>Archive of Applied Mechanics</i>, <i>94</i>(8), 2217–2242. <a href=\"https://doi.org/10.1007/s00419-024-02634-1\">https://doi.org/10.1007/s00419-024-02634-1</a>","mla":"Gerlach, Jan, et al. “Enhancing Damage Prediction in Bulk Metal Forming through Machine Learning-Assisted Parameter Identification.” <i>Archive of Applied Mechanics</i>, vol. 94, no. 8, Springer Science and Business Media LLC, 2024, pp. 2217–42, doi:<a href=\"https://doi.org/10.1007/s00419-024-02634-1\">10.1007/s00419-024-02634-1</a>.","bibtex":"@article{Gerlach_Schulte_Schowtjak_Clausmeyer_Ostwald_Tekkaya_Menzel_2024, title={Enhancing damage prediction in bulk metal forming through machine learning-assisted parameter identification}, volume={94}, DOI={<a href=\"https://doi.org/10.1007/s00419-024-02634-1\">10.1007/s00419-024-02634-1</a>}, number={8}, journal={Archive of Applied Mechanics}, publisher={Springer Science and Business Media LLC}, author={Gerlach, Jan and Schulte, Robin and Schowtjak, Alexander and Clausmeyer, Till and Ostwald, Richard and Tekkaya, A. Erman and Menzel, Andreas}, year={2024}, pages={2217–2242} }","short":"J. Gerlach, R. Schulte, A. Schowtjak, T. Clausmeyer, R. Ostwald, A.E. Tekkaya, A. Menzel, Archive of Applied Mechanics 94 (2024) 2217–2242."},"publication_identifier":{"issn":["0939-1533","1432-0681"]},"quality_controlled":"1","publication_status":"published","issue":"8","title":"Enhancing damage prediction in bulk metal forming through machine learning-assisted parameter identification","doi":"10.1007/s00419-024-02634-1","date_updated":"2025-12-03T12:50:41Z","publisher":"Springer Science and Business Media LLC","volume":94,"author":[{"full_name":"Gerlach, Jan","last_name":"Gerlach","first_name":"Jan"},{"first_name":"Robin","last_name":"Schulte","full_name":"Schulte, Robin"},{"first_name":"Alexander","last_name":"Schowtjak","full_name":"Schowtjak, Alexander"},{"first_name":"Till","last_name":"Clausmeyer","full_name":"Clausmeyer, Till"},{"orcid":"0000-0003-2147-8444","last_name":"Ostwald","full_name":"Ostwald, Richard","id":"106876","first_name":"Richard"},{"first_name":"A. Erman","full_name":"Tekkaya, A. Erman","last_name":"Tekkaya"},{"first_name":"Andreas","full_name":"Menzel, Andreas","last_name":"Menzel"}],"date_created":"2025-12-03T12:46:31Z"},{"intvolume":"       314","citation":{"ama":"Najafi Koopas R, Rezaei S, Rauter N, Ostwald R, Lammering R. A spatiotemporal deep learning framework for prediction of crack dynamics in heterogeneous solids: Efficient mapping of concrete microstructures to its fracture properties. <i>Engineering Fracture Mechanics</i>. 2024;314. doi:<a href=\"https://doi.org/10.1016/j.engfracmech.2024.110675\">10.1016/j.engfracmech.2024.110675</a>","chicago":"Najafi Koopas, Rasoul, Shahed Rezaei, Natalie Rauter, Richard Ostwald, and Rolf Lammering. “A Spatiotemporal Deep Learning Framework for Prediction of Crack Dynamics in Heterogeneous Solids: Efficient Mapping of Concrete Microstructures to Its Fracture Properties.” <i>Engineering Fracture Mechanics</i> 314 (2024). <a href=\"https://doi.org/10.1016/j.engfracmech.2024.110675\">https://doi.org/10.1016/j.engfracmech.2024.110675</a>.","ieee":"R. Najafi Koopas, S. Rezaei, N. Rauter, R. Ostwald, and R. Lammering, “A spatiotemporal deep learning framework for prediction of crack dynamics in heterogeneous solids: Efficient mapping of concrete microstructures to its fracture properties,” <i>Engineering Fracture Mechanics</i>, vol. 314, Art. no. 110675, 2024, doi: <a href=\"https://doi.org/10.1016/j.engfracmech.2024.110675\">10.1016/j.engfracmech.2024.110675</a>.","apa":"Najafi Koopas, R., Rezaei, S., Rauter, N., Ostwald, R., &#38; Lammering, R. (2024). A spatiotemporal deep learning framework for prediction of crack dynamics in heterogeneous solids: Efficient mapping of concrete microstructures to its fracture properties. <i>Engineering Fracture Mechanics</i>, <i>314</i>, Article 110675. <a href=\"https://doi.org/10.1016/j.engfracmech.2024.110675\">https://doi.org/10.1016/j.engfracmech.2024.110675</a>","mla":"Najafi Koopas, Rasoul, et al. “A Spatiotemporal Deep Learning Framework for Prediction of Crack Dynamics in Heterogeneous Solids: Efficient Mapping of Concrete Microstructures to Its Fracture Properties.” <i>Engineering Fracture Mechanics</i>, vol. 314, 110675, Elsevier BV, 2024, doi:<a href=\"https://doi.org/10.1016/j.engfracmech.2024.110675\">10.1016/j.engfracmech.2024.110675</a>.","short":"R. Najafi Koopas, S. Rezaei, N. Rauter, R. Ostwald, R. Lammering, Engineering Fracture Mechanics 314 (2024).","bibtex":"@article{Najafi Koopas_Rezaei_Rauter_Ostwald_Lammering_2024, title={A spatiotemporal deep learning framework for prediction of crack dynamics in heterogeneous solids: Efficient mapping of concrete microstructures to its fracture properties}, volume={314}, DOI={<a href=\"https://doi.org/10.1016/j.engfracmech.2024.110675\">10.1016/j.engfracmech.2024.110675</a>}, number={110675}, journal={Engineering Fracture Mechanics}, publisher={Elsevier BV}, author={Najafi Koopas, Rasoul and Rezaei, Shahed and Rauter, Natalie and Ostwald, Richard and Lammering, Rolf}, year={2024} }"},"year":"2024","publication_identifier":{"issn":["0013-7944"]},"quality_controlled":"1","publication_status":"published","doi":"10.1016/j.engfracmech.2024.110675","title":"A spatiotemporal deep learning framework for prediction of crack dynamics in heterogeneous solids: Efficient mapping of concrete microstructures to its fracture properties","volume":314,"author":[{"last_name":"Najafi Koopas","full_name":"Najafi Koopas, Rasoul","first_name":"Rasoul"},{"last_name":"Rezaei","full_name":"Rezaei, Shahed","first_name":"Shahed"},{"first_name":"Natalie","full_name":"Rauter, Natalie","last_name":"Rauter"},{"last_name":"Ostwald","orcid":"0000-0003-2147-8444","full_name":"Ostwald, Richard","id":"106876","first_name":"Richard"},{"first_name":"Rolf","full_name":"Lammering, Rolf","last_name":"Lammering"}],"date_created":"2025-12-03T12:40:42Z","publisher":"Elsevier BV","date_updated":"2025-12-03T12:51:12Z","status":"public","publication":"Engineering Fracture Mechanics","type":"journal_article","language":[{"iso":"eng"}],"article_number":"110675","department":[{"_id":"952"},{"_id":"321"}],"user_id":"85414","_id":"62768"},{"department":[{"_id":"876"},{"_id":"9"},{"_id":"393"},{"_id":"321"}],"user_id":"103302","external_id":{"unknown":["https://dx.doi.org/10.2139/ssrn.4966589"]},"_id":"56289","language":[{"iso":"eng"}],"publication":"United States Association for Energy Economics (USAEE) & International Association for Energy Economics (IAEE) Research Paper Series","type":"preprint","status":"public","date_created":"2024-10-01T09:34:06Z","author":[{"full_name":"Seeger, Karl","last_name":"Seeger","first_name":"Karl"},{"last_name":"Genovese","full_name":"Genovese, Matteo","first_name":"Matteo"},{"first_name":"Alexander","id":"103302","full_name":"Schlüter, Alexander","orcid":"0000-0002-2569-1624","last_name":"Schlüter"},{"first_name":"Christina","last_name":"Kockel","full_name":"Kockel, Christina"},{"last_name":"Corigliano","full_name":"Corigliano, Orlando","first_name":"Orlando"},{"orcid":"0009-0007-2748-0074","last_name":"Díaz Canales","id":"105704","full_name":"Díaz Canales, Edith Benjamina","first_name":"Edith Benjamina"},{"first_name":"Petronilla","full_name":"Fragiacomo, Petronilla","last_name":"Fragiacomo"},{"first_name":"Aaron","last_name":"Praktiknjo","full_name":"Praktiknjo, Aaron"}],"date_updated":"2026-01-06T08:00:25Z","oa":"1","publisher":"Elsevier BV","main_file_link":[{"url":"https://dx.doi.org/10.2139/ssrn.4966589","open_access":"1"}],"title":"Evaluating Supply Scenarios for Hydrogen and Green Fuels from Canada, Chile, and Algeria to Germany via a Techno-Economic Assessment","publication_status":"published","citation":{"chicago":"Seeger, Karl, Matteo Genovese, Alexander Schlüter, Christina Kockel, Orlando Corigliano, Edith Benjamina Díaz Canales, Petronilla Fragiacomo, and Aaron Praktiknjo. “Evaluating Supply Scenarios for Hydrogen and Green Fuels from Canada, Chile, and Algeria to Germany via a Techno-Economic Assessment.” <i>United States Association for Energy Economics (USAEE) &#38; International Association for Energy Economics (IAEE) Research Paper Series</i>. Elsevier BV, 2024.","ieee":"K. Seeger <i>et al.</i>, “Evaluating Supply Scenarios for Hydrogen and Green Fuels from Canada, Chile, and Algeria to Germany via a Techno-Economic Assessment,” <i>United States Association for Energy Economics (USAEE) &#38; International Association for Energy Economics (IAEE) Research Paper Series</i>. Elsevier BV, 2024.","ama":"Seeger K, Genovese M, Schlüter A, et al. Evaluating Supply Scenarios for Hydrogen and Green Fuels from Canada, Chile, and Algeria to Germany via a Techno-Economic Assessment. <i>United States Association for Energy Economics (USAEE) &#38; International Association for Energy Economics (IAEE) Research Paper Series</i>. Published online 2024.","apa":"Seeger, K., Genovese, M., Schlüter, A., Kockel, C., Corigliano, O., Díaz Canales, E. B., Fragiacomo, P., &#38; Praktiknjo, A. (2024). Evaluating Supply Scenarios for Hydrogen and Green Fuels from Canada, Chile, and Algeria to Germany via a Techno-Economic Assessment. In <i>United States Association for Energy Economics (USAEE) &#38; International Association for Energy Economics (IAEE) Research Paper Series</i>. Elsevier BV.","mla":"Seeger, Karl, et al. “Evaluating Supply Scenarios for Hydrogen and Green Fuels from Canada, Chile, and Algeria to Germany via a Techno-Economic Assessment.” <i>United States Association for Energy Economics (USAEE) &#38; International Association for Energy Economics (IAEE) Research Paper Series</i>, Elsevier BV, 2024.","bibtex":"@article{Seeger_Genovese_Schlüter_Kockel_Corigliano_Díaz Canales_Fragiacomo_Praktiknjo_2024, title={Evaluating Supply Scenarios for Hydrogen and Green Fuels from Canada, Chile, and Algeria to Germany via a Techno-Economic Assessment}, journal={United States Association for Energy Economics (USAEE) &#38; International Association for Energy Economics (IAEE) Research Paper Series}, publisher={Elsevier BV}, author={Seeger, Karl and Genovese, Matteo and Schlüter, Alexander and Kockel, Christina and Corigliano, Orlando and Díaz Canales, Edith Benjamina and Fragiacomo, Petronilla and Praktiknjo, Aaron}, year={2024} }","short":"K. Seeger, M. Genovese, A. Schlüter, C. Kockel, O. Corigliano, E.B. Díaz Canales, P. Fragiacomo, A. Praktiknjo, United States Association for Energy Economics (USAEE) &#38; International Association for Energy Economics (IAEE) Research Paper Series (2024)."},"year":"2024"},{"date_updated":"2026-01-06T08:14:34Z","publisher":" Faculty of Mechanical Engineering and Naval Architecture, Zagreb","date_created":"2024-10-07T10:15:05Z","author":[{"first_name":"Edith Benjamina","last_name":"Díaz Canales","orcid":"0009-0007-2748-0074","id":"105704","full_name":"Díaz Canales, Edith Benjamina"},{"first_name":"Alfredo","last_name":"Avila ","full_name":"Avila , Alfredo"},{"full_name":"Schlüter, Sabine ","last_name":"Schlüter","first_name":"Sabine "},{"first_name":"Erick","last_name":"Lacayo","full_name":"Lacayo, Erick"},{"first_name":"Alexander","orcid":"0000-0002-2569-1624","last_name":"Schlüter","id":"103302","full_name":"Schlüter, Alexander"}],"title":"Implementing Strategic Environmental Assessment (SEA) in the Global South, a challenge: Nicaragua as a case study.","conference":{"end_date":"2024-09-12","location":"Rome","name":"19th Conference on Sustainable Development of Energy, Water and Environment Systems (SDEWES)","start_date":"2024-09-08"},"publication_identifier":{"unknown":["2706-3690"]},"year":"2024","citation":{"short":"E.B. Díaz Canales, A. Avila , S. Schlüter, E. Lacayo, A. Schlüter, in: 19th Conference on Sustainable Development of Energy, Water and Environment Systems,  Faculty of Mechanical Engineering and Naval Architecture, Zagreb, 2024.","bibtex":"@inproceedings{Díaz Canales_Avila _Schlüter_Lacayo_Schlüter_2024, series={Digital Proceedings (Conference on Sustainable Development of Energy, Water and Environment Systems)}, title={Implementing Strategic Environmental Assessment (SEA) in the Global South, a challenge: Nicaragua as a case study.}, booktitle={19th Conference on Sustainable Development of Energy, Water and Environment Systems}, publisher={ Faculty of Mechanical Engineering and Naval Architecture, Zagreb}, author={Díaz Canales, Edith Benjamina and Avila , Alfredo and Schlüter, Sabine  and Lacayo, Erick and Schlüter, Alexander}, year={2024}, collection={Digital Proceedings (Conference on Sustainable Development of Energy, Water and Environment Systems)} }","mla":"Díaz Canales, Edith Benjamina, et al. “Implementing Strategic Environmental Assessment (SEA) in the Global South, a Challenge: Nicaragua as a Case Study.” <i>19th Conference on Sustainable Development of Energy, Water and Environment Systems</i>,  Faculty of Mechanical Engineering and Naval Architecture, Zagreb, 2024.","apa":"Díaz Canales, E. B., Avila , A., Schlüter, S., Lacayo, E., &#38; Schlüter, A. (2024). Implementing Strategic Environmental Assessment (SEA) in the Global South, a challenge: Nicaragua as a case study. <i>19th Conference on Sustainable Development of Energy, Water and Environment Systems</i>. 19th Conference on Sustainable Development of Energy, Water and Environment Systems (SDEWES), Rome.","ama":"Díaz Canales EB, Avila  A, Schlüter S, Lacayo E, Schlüter A. Implementing Strategic Environmental Assessment (SEA) in the Global South, a challenge: Nicaragua as a case study. In: <i>19th Conference on Sustainable Development of Energy, Water and Environment Systems</i>. Digital Proceedings (Conference on Sustainable Development of Energy, Water and Environment Systems).  Faculty of Mechanical Engineering and Naval Architecture, Zagreb; 2024.","chicago":"Díaz Canales, Edith Benjamina, Alfredo Avila , Sabine  Schlüter, Erick Lacayo, and Alexander Schlüter. “Implementing Strategic Environmental Assessment (SEA) in the Global South, a Challenge: Nicaragua as a Case Study.” In <i>19th Conference on Sustainable Development of Energy, Water and Environment Systems</i>. Digital Proceedings (Conference on Sustainable Development of Energy, Water and Environment Systems).  Faculty of Mechanical Engineering and Naval Architecture, Zagreb, 2024.","ieee":"E. B. Díaz Canales, A. Avila , S. Schlüter, E. Lacayo, and A. Schlüter, “Implementing Strategic Environmental Assessment (SEA) in the Global South, a challenge: Nicaragua as a case study.,” presented at the 19th Conference on Sustainable Development of Energy, Water and Environment Systems (SDEWES), Rome, 2024."},"_id":"56357","series_title":"Digital Proceedings (Conference on Sustainable Development of Energy, Water and Environment Systems)","user_id":"103302","department":[{"_id":"876"},{"_id":"321"},{"_id":"9"},{"_id":"393"}],"alternative_title":["SDEWES2024.1202"],"language":[{"iso":"eng"}],"type":"conference","publication":"19th Conference on Sustainable Development of Energy, Water and Environment Systems","status":"public"},{"publication_status":"published","quality_controlled":"1","publication_identifier":{"issn":["0094-243X"]},"citation":{"chicago":"Albrecht, Mirko, Max Oliver Bialaschik, Michael Gehde, and Volker Schöppner. “Serial Hot Gas Welding - Heating and Welding Behaviour of a Slot Nozzle.” In <i>AIP Conference Proceedings</i>, Vol. 3181. AIP Publishing, 2024. <a href=\"https://doi.org/10.1063/5.0192316\">https://doi.org/10.1063/5.0192316</a>.","ieee":"M. Albrecht, M. O. Bialaschik, M. Gehde, and V. Schöppner, “Serial hot gas welding - Heating and welding behaviour of a slot nozzle,” in <i>AIP Conference Proceedings</i>, 2024, vol. 3181, doi: <a href=\"https://doi.org/10.1063/5.0192316\">10.1063/5.0192316</a>.","ama":"Albrecht M, Bialaschik MO, Gehde M, Schöppner V. Serial hot gas welding - Heating and welding behaviour of a slot nozzle. In: <i>AIP Conference Proceedings</i>. Vol 3181. AIP Publishing; 2024. doi:<a href=\"https://doi.org/10.1063/5.0192316\">10.1063/5.0192316</a>","apa":"Albrecht, M., Bialaschik, M. O., Gehde, M., &#38; Schöppner, V. (2024). Serial hot gas welding - Heating and welding behaviour of a slot nozzle. <i>AIP Conference Proceedings</i>, <i>3181</i>. <a href=\"https://doi.org/10.1063/5.0192316\">https://doi.org/10.1063/5.0192316</a>","bibtex":"@inproceedings{Albrecht_Bialaschik_Gehde_Schöppner_2024, title={Serial hot gas welding - Heating and welding behaviour of a slot nozzle}, volume={3181}, DOI={<a href=\"https://doi.org/10.1063/5.0192316\">10.1063/5.0192316</a>}, booktitle={AIP Conference Proceedings}, publisher={AIP Publishing}, author={Albrecht, Mirko and Bialaschik, Max Oliver and Gehde, Michael and Schöppner, Volker}, year={2024} }","short":"M. Albrecht, M.O. Bialaschik, M. Gehde, V. Schöppner, in: AIP Conference Proceedings, AIP Publishing, 2024.","mla":"Albrecht, Mirko, et al. “Serial Hot Gas Welding - Heating and Welding Behaviour of a Slot Nozzle.” <i>AIP Conference Proceedings</i>, vol. 3181, AIP Publishing, 2024, doi:<a href=\"https://doi.org/10.1063/5.0192316\">10.1063/5.0192316</a>."},"intvolume":"      3181","year":"2024","author":[{"first_name":"Mirko","full_name":"Albrecht, Mirko","last_name":"Albrecht"},{"full_name":"Bialaschik, Max Oliver","id":"32297","last_name":"Bialaschik","first_name":"Max Oliver"},{"first_name":"Michael","full_name":"Gehde, Michael","last_name":"Gehde"},{"first_name":"Volker","full_name":"Schöppner, Volker","id":"20530","last_name":"Schöppner"}],"date_created":"2026-03-18T12:24:07Z","volume":3181,"date_updated":"2026-03-18T12:24:42Z","publisher":"AIP Publishing","doi":"10.1063/5.0192316","title":"Serial hot gas welding - Heating and welding behaviour of a slot nozzle","type":"conference","publication":"AIP Conference Proceedings","status":"public","user_id":"59363","department":[{"_id":"9"},{"_id":"321"},{"_id":"367"}],"_id":"65052","language":[{"iso":"eng"}]},{"title":"Mikromechanische Analyse von Eigenspannungen in direktgefügten kohlenstofffaserverstärkten Kunststoff-Stahl-Schichtverbunden","publisher":"BoD - Books on Demand","date_updated":"2026-03-19T10:57:29Z","author":[{"first_name":"Steffen Rainer","full_name":"Tinkloh, Steffen Rainer","last_name":"Tinkloh"}],"date_created":"2024-10-17T07:56:02Z","supervisor":[{"first_name":"Thomas","full_name":"Tröster, Thomas","last_name":"Tröster"},{"last_name":"Niendorf","full_name":"Niendorf, Thomas","first_name":"Thomas"}],"year":"2024","page":"168","citation":{"mla":"Tinkloh, Steffen Rainer. <i>Mikromechanische Analyse von Eigenspannungen in direktgefügten kohlenstofffaserverstärkten Kunststoff-Stahl-Schichtverbunden</i>. BoD - Books on Demand, 2024.","bibtex":"@book{Tinkloh_2024, title={Mikromechanische Analyse von Eigenspannungen in direktgefügten kohlenstofffaserverstärkten Kunststoff-Stahl-Schichtverbunden}, publisher={BoD - Books on Demand}, author={Tinkloh, Steffen Rainer}, year={2024} }","short":"S.R. Tinkloh, Mikromechanische Analyse von Eigenspannungen in direktgefügten kohlenstofffaserverstärkten Kunststoff-Stahl-Schichtverbunden, BoD - Books on Demand, 2024.","apa":"Tinkloh, S. R. (2024). <i>Mikromechanische Analyse von Eigenspannungen in direktgefügten kohlenstofffaserverstärkten Kunststoff-Stahl-Schichtverbunden</i>. BoD - Books on Demand.","ieee":"S. R. Tinkloh, <i>Mikromechanische Analyse von Eigenspannungen in direktgefügten kohlenstofffaserverstärkten Kunststoff-Stahl-Schichtverbunden</i>. BoD - Books on Demand, 2024.","chicago":"Tinkloh, Steffen Rainer. <i>Mikromechanische Analyse von Eigenspannungen in direktgefügten kohlenstofffaserverstärkten Kunststoff-Stahl-Schichtverbunden</i>. BoD - Books on Demand, 2024.","ama":"Tinkloh SR. <i>Mikromechanische Analyse von Eigenspannungen in direktgefügten kohlenstofffaserverstärkten Kunststoff-Stahl-Schichtverbunden</i>. BoD - Books on Demand; 2024."},"publication_identifier":{"isbn":["9783757887650"]},"publication_status":"published","keyword":["Hybride Werkstoffverbunde","Eigenspanungen","FFT-basierte Galerkin-Methode","Mikromechanik","Finite-Elemente-Methode"],"extern":"1","language":[{"iso":"ger"}],"_id":"56654","project":[{"name":"Computing Resources Provided by the Paderborn Center for Parallel Computing","_id":"52"}],"department":[{"_id":"9"},{"_id":"149"},{"_id":"321"}],"user_id":"71335","abstract":[{"text":"Residual stresses in directly joined laminates made of steel and carbon fiber reinforced epoxy resin reduce the interface and bond strength and thus have to be taken into account for the strength analysis of structural components. For a holistic description of residual stresses, a thermo-chemo-mechanical constitutive model is introduced in the present work and presented for the multi-scale analysis of residual stress patterns. In this context, the analysis of representative unit cells with regular and stochastic distribution of fibers gives information about the associated deformation and stress fields. Dehomogenization at macroscopically highly stressed regions, characterized by local stress peaks, reveals the effect of gradient deformation in the microstructure. Another aspect of this work is the development of FFT-based Galerkin methods, which allows an evaluation of the effect of defect densities, heterogeneities and morphologies on the applicability of the incremental hole drilling method. It could be demonstrated that the incremental hole drilling method is particularly sensitive to defects running along the surface.","lang":"eng"},{"text":"Eigenspannungen in direktgefügten Werkstoffverbunden aus Stahl und kohlenstofffaserverstärktem Epoxidharz reduzieren die Grenzschicht- und Verbundfestigkeit und sind somit für die Festigkeitsbeurteilung von Strukturen zwingend zu berücksichtigen. Zur ganzheitlichen Beschreibung von Eigenspannungen wird in der vorliegenden Arbeit ein thermo-chemo-mechanisches Konstitutivmodell für die skalenübergreifende Bewertung von Eigenspannungsverteilungen vorgestellt. Die Analyse von repräsentativen Einheitszellen mit regulärer und stochastischer Verteilung von Fasern liefert in diesem Zusammenhang Informationen über die zugehörigen Deformations- und Spannungsfelder. Die Dehomogenisierung an makroskopisch hochbelasteten Bereichen, die durch lokale Spannungsüberhöhungen gekennzeichnet sind, zeigt die Auswirkung der gradientenbehafteten Deformation in der Mikrostruktur. Ein weiterer Aspekt dieser Arbeit ist die Entwicklung FFT-basierter Galerkin-Methoden, die es erstmalig erlauben, eine Bewertung der Auswirkung von Defektdichte, Heterogenität und Morphologie auf die Anwendbarkeit der inkrementellen Bohrlochmethode vorzunehmen. Es konnte nachgewiesen werden, dass die inkrementelle Bohrlochmethode insbesondere auf an der Oberfläche verlaufende Defekte sensitiv reagiert.","lang":"ger"}],"status":"public","type":"dissertation"},{"language":[{"iso":"eng"}],"ddc":["670"],"keyword":["additive manufacturing","direct energy deposition","laser metal deposition"],"abstract":[{"lang":"eng","text":"<jats:p>The optimization of process parameters in powder Directed Energy Deposition (DED) is essential for achieving consistent, high-quality bead geometries, which directly influence the performance and structural integrity of fabricated components. As a subset of additive manufacturing (AM), the DED process, also referred to as laser metal deposition (LMD), enables precise, layer-by-layer material deposition, making it highly suitable for complex geometries and part repair applications. Critical parameters, such as the laser power, feed rate, powder mass flow, and substrate temperature govern the deposition process, impacting the bead height, width, contact angle, and dilution. Inconsistent control over these variables can lead to defects, such as poor bonding, dimensional inaccuracies, and material weaknesses, ultimately compromising the final product. This paper investigates the effects of various process parameters, specifically the substrate temperature, on bead track geometry in DED processes for stainless steel (1.4404). A specialized experimental setup, integrated within a DED machine, facilitates the controlled thermal conditioning of sample sheets. Using Design of Experiments (DoE) methods, individual bead marks are generated and analyzed to assess geometric characteristics. Regression models, including both linear and quadratic approaches, are constructed to predict machine parameters for achieving the desired bead geometry at different substrate temperatures. Validation experiments confirm the accuracy and reliability of the models, particularly in predicting the bead height, bead width, and contact angle across a broad range of substrate temperatures. However, the models demonstrated limitations in accurately predicting dilution, indicating the need for further refinement. Despite some deviations in measured values, successful fabrication is achieved, demonstrating robust bonding between the bead and substrate. The developed models offer insights into optimizing DED process parameters to achieve desired bead characteristics, advancing the precision and reliability of additive manufacturing technology. Future work will focus on refining the regression models to improve predictions, particularly for dilution, and further investigate non-linear interactions between process variables.</jats:p>"}],"publication":"Metals","title":"Effect of Substrate Temperature on Bead Track Geometry of 316L in Directed Energy Deposition: Investigation and Regression Modeling","date_created":"2024-12-10T12:13:23Z","publisher":"MDPI AG","year":"2024","issue":"12","quality_controlled":"1","article_type":"original","article_number":"1353","user_id":"49504","department":[{"_id":"321"},{"_id":"149"},{"_id":"9"}],"_id":"57699","status":"public","type":"journal_article","main_file_link":[{"open_access":"1","url":"https://www.mdpi.com/2075-4701/14/12/1353"}],"doi":"10.3390/met14121353","author":[{"first_name":"Deviprasad","orcid":"https://orcid.org/ 0000-0002-3446-2444","last_name":"Chalicheemalapalli Jayasankar","id":"49504","full_name":"Chalicheemalapalli Jayasankar, Deviprasad"},{"last_name":"Gnaase","full_name":"Gnaase, Stefan","id":"25730","first_name":"Stefan"},{"first_name":"Dennis","id":"90491","full_name":"Lehnert, Dennis","last_name":"Lehnert"},{"first_name":"Artur","last_name":"Walter","full_name":"Walter, Artur"},{"full_name":"Rohling, Robin","last_name":"Rohling","first_name":"Robin"},{"full_name":"Tröster, Thomas","id":"553","last_name":"Tröster","first_name":"Thomas"}],"volume":14,"oa":"1","date_updated":"2026-03-20T08:44:28Z","citation":{"apa":"Chalicheemalapalli Jayasankar, D., Gnaase, S., Lehnert, D., Walter, A., Rohling, R., &#38; Tröster, T. (2024). Effect of Substrate Temperature on Bead Track Geometry of 316L in Directed Energy Deposition: Investigation and Regression Modeling. <i>Metals</i>, <i>14</i>(12), Article 1353. <a href=\"https://doi.org/10.3390/met14121353\">https://doi.org/10.3390/met14121353</a>","bibtex":"@article{Chalicheemalapalli Jayasankar_Gnaase_Lehnert_Walter_Rohling_Tröster_2024, title={Effect of Substrate Temperature on Bead Track Geometry of 316L in Directed Energy Deposition: Investigation and Regression Modeling}, volume={14}, DOI={<a href=\"https://doi.org/10.3390/met14121353\">10.3390/met14121353</a>}, number={121353}, journal={Metals}, publisher={MDPI AG}, author={Chalicheemalapalli Jayasankar, Deviprasad and Gnaase, Stefan and Lehnert, Dennis and Walter, Artur and Rohling, Robin and Tröster, Thomas}, year={2024} }","short":"D. Chalicheemalapalli Jayasankar, S. Gnaase, D. Lehnert, A. Walter, R. Rohling, T. Tröster, Metals 14 (2024).","mla":"Chalicheemalapalli Jayasankar, Deviprasad, et al. “Effect of Substrate Temperature on Bead Track Geometry of 316L in Directed Energy Deposition: Investigation and Regression Modeling.” <i>Metals</i>, vol. 14, no. 12, 1353, MDPI AG, 2024, doi:<a href=\"https://doi.org/10.3390/met14121353\">10.3390/met14121353</a>.","ama":"Chalicheemalapalli Jayasankar D, Gnaase S, Lehnert D, Walter A, Rohling R, Tröster T. Effect of Substrate Temperature on Bead Track Geometry of 316L in Directed Energy Deposition: Investigation and Regression Modeling. <i>Metals</i>. 2024;14(12). doi:<a href=\"https://doi.org/10.3390/met14121353\">10.3390/met14121353</a>","ieee":"D. Chalicheemalapalli Jayasankar, S. Gnaase, D. Lehnert, A. Walter, R. Rohling, and T. Tröster, “Effect of Substrate Temperature on Bead Track Geometry of 316L in Directed Energy Deposition: Investigation and Regression Modeling,” <i>Metals</i>, vol. 14, no. 12, Art. no. 1353, 2024, doi: <a href=\"https://doi.org/10.3390/met14121353\">10.3390/met14121353</a>.","chicago":"Chalicheemalapalli Jayasankar, Deviprasad, Stefan Gnaase, Dennis Lehnert, Artur Walter, Robin Rohling, and Thomas Tröster. “Effect of Substrate Temperature on Bead Track Geometry of 316L in Directed Energy Deposition: Investigation and Regression Modeling.” <i>Metals</i> 14, no. 12 (2024). <a href=\"https://doi.org/10.3390/met14121353\">https://doi.org/10.3390/met14121353</a>."},"intvolume":"        14","publication_status":"published","has_accepted_license":"1","publication_identifier":{"issn":["2075-4701"]}},{"publisher":"MDPI AG","date_created":"2024-09-10T10:19:32Z","title":"Advancements in Hybrid Additive Manufacturing: Integrating SLM and LMD for High-Performance Applications","quality_controlled":"1","issue":"7","year":"2024","keyword":["additive manufacturing (AM)","selective laser melting (SLM)","laser metal deposition (LMD)","hybrid manufacturing","process optimization","316L","1.2709"],"language":[{"iso":"eng"}],"publication":"Metals","abstract":[{"lang":"eng","text":"<jats:p>Additive manufacturing (AM) technologies enable near-net-shape designs and demand-oriented material usage, which significantly minimizes waste. This points to a substantial opportunity for further optimization in material savings and process design. The current study delves into the advancement of sustainable manufacturing practices in the automotive industry, emphasizing the crucial role of lightweight construction concepts and AM technologies in enhancing resource efficiency and reducing greenhouse gas emissions. By exploring the integration of novel AM techniques such as selective laser melting (SLM) and laser metal deposition (LMD), the study aims to overcome existing limitations like slow build-up rates and limited component resolution. The study’s core objective revolves around the development and validation of a continuous process chain that synergizes different AM routes. In the current study, the continuous process chain for DMG MORI Lasertec 65 3D’s LMD system and the DMG MORI Lasertec 30 3D’s was demonstrated using 316L and 1.2709 steel materials. This integrated approach is designed to significantly curtail process times and minimize component costs, thus suggesting an industry-oriented process chain for future manufacturing paradigms. Additionally, the research investigates the production and material behavior of components under varying manufacturing processes, material combinations, and boundary layer materials. The culmination of this study is the validation of the proposed process route through a technology demonstrator, assessing its scalability and setting a benchmark for resource-efficient manufacturing in the automotive sector.</jats:p>"}],"date_updated":"2026-03-20T08:44:23Z","oa":"1","volume":14,"author":[{"first_name":"Deviprasad","last_name":"Chalicheemalapalli Jayasankar","orcid":"https://orcid.org/ 0000-0002-3446-2444","id":"49504","full_name":"Chalicheemalapalli Jayasankar, Deviprasad"},{"id":"25730","full_name":"Gnaase, Stefan","last_name":"Gnaase","first_name":"Stefan"},{"first_name":"Maximilian Alexander","orcid":"0009-0008-1333-3396","last_name":"Kaiser","full_name":"Kaiser, Maximilian Alexander","id":"72351"},{"last_name":"Lehnert","full_name":"Lehnert, Dennis","id":"90491","first_name":"Dennis"},{"last_name":"Tröster","full_name":"Tröster, Thomas","id":"553","first_name":"Thomas"}],"doi":"10.3390/met14070772","main_file_link":[{"url":"https://www.mdpi.com/2075-4701/14/7/772","open_access":"1"}],"publication_identifier":{"issn":["2075-4701"]},"publication_status":"published","intvolume":"        14","citation":{"chicago":"Chalicheemalapalli Jayasankar, Deviprasad, Stefan Gnaase, Maximilian Alexander Kaiser, Dennis Lehnert, and Thomas Tröster. “Advancements in Hybrid Additive Manufacturing: Integrating SLM and LMD for High-Performance Applications.” <i>Metals</i> 14, no. 7 (2024). <a href=\"https://doi.org/10.3390/met14070772\">https://doi.org/10.3390/met14070772</a>.","ieee":"D. Chalicheemalapalli Jayasankar, S. Gnaase, M. A. Kaiser, D. Lehnert, and T. Tröster, “Advancements in Hybrid Additive Manufacturing: Integrating SLM and LMD for High-Performance Applications,” <i>Metals</i>, vol. 14, no. 7, Art. no. 772, 2024, doi: <a href=\"https://doi.org/10.3390/met14070772\">10.3390/met14070772</a>.","short":"D. Chalicheemalapalli Jayasankar, S. Gnaase, M.A. Kaiser, D. Lehnert, T. Tröster, Metals 14 (2024).","bibtex":"@article{Chalicheemalapalli Jayasankar_Gnaase_Kaiser_Lehnert_Tröster_2024, title={Advancements in Hybrid Additive Manufacturing: Integrating SLM and LMD for High-Performance Applications}, volume={14}, DOI={<a href=\"https://doi.org/10.3390/met14070772\">10.3390/met14070772</a>}, number={7772}, journal={Metals}, publisher={MDPI AG}, author={Chalicheemalapalli Jayasankar, Deviprasad and Gnaase, Stefan and Kaiser, Maximilian Alexander and Lehnert, Dennis and Tröster, Thomas}, year={2024} }","mla":"Chalicheemalapalli Jayasankar, Deviprasad, et al. “Advancements in Hybrid Additive Manufacturing: Integrating SLM and LMD for High-Performance Applications.” <i>Metals</i>, vol. 14, no. 7, 772, MDPI AG, 2024, doi:<a href=\"https://doi.org/10.3390/met14070772\">10.3390/met14070772</a>.","ama":"Chalicheemalapalli Jayasankar D, Gnaase S, Kaiser MA, Lehnert D, Tröster T. Advancements in Hybrid Additive Manufacturing: Integrating SLM and LMD for High-Performance Applications. <i>Metals</i>. 2024;14(7). doi:<a href=\"https://doi.org/10.3390/met14070772\">10.3390/met14070772</a>","apa":"Chalicheemalapalli Jayasankar, D., Gnaase, S., Kaiser, M. A., Lehnert, D., &#38; Tröster, T. (2024). Advancements in Hybrid Additive Manufacturing: Integrating SLM and LMD for High-Performance Applications. <i>Metals</i>, <i>14</i>(7), Article 772. <a href=\"https://doi.org/10.3390/met14070772\">https://doi.org/10.3390/met14070772</a>"},"_id":"56089","department":[{"_id":"9"},{"_id":"321"},{"_id":"149"}],"user_id":"49504","article_type":"original","article_number":"772","type":"journal_article","status":"public"}]