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Integrative Computational Design and Construction for Architecture (T3.0)
Research
Research Projects
RP 12-1 – Computational Design for Fibre Composite Building Systems

Computational Design for Fibre Composite Building Systems

Research Project 12-1 (RP 12-1)

COMPUTATIONAL CO-DESIGN FOR FIBRE COMPOSITE BUILDING SYSTEMS INCLUDING VISUAL ANALYTICS AND SIMULATION INTERFACES

Coreless winding of lightweight fibre composite systems enables highly differentiated placement of high-performance, load-bearing materials and creates new solution spaces for design and construction of lightweight fibrous structures.

In early design phases of such large-scale, coreless-wound fibre composite building systems, considerable effort is required to develop project-specific solutions due to the high complexity of interdependent parameters of design, construction and manufacturing demands. In addition, the need for physical prototypes and digital-physical iteration loops increases the workload and re-duces the depth of exploration. While multiple project-based computational solutions and tools have been developed, those were case-specific and used many assumptions to simplify the implementation and ensure computational tractability. Therefore, they cannot be directly transferred to general cases where the typology of the fibre network is not fully known in advance, or where the topology of fibre-fibre contact points cannot be predicted in advance. This reduces the design space to relatively simple typologies limited to the designer’s intuition and experience.

In order to process manifold interrelations within a multidisciplinary design and construction process, we aim to develop a framework of general design methods to make large fibre-based systems conceivable and extend the design space beyond structures based on experience and intuition, unlocking the full potential of coreless fibre winding. This framework should be aided by visual analytics tools, machine learning and optimization.

PRINCIPAL INVESTIGATORS

Prof. Achim Menges
Institute for Computational Design and Construction (ICD), University of Stuttgart
Prof. Dr. rer. nat. Daniel Weiskopf
Visualization Research Center (VISUS), University of Stuttgart
Prof. Dr. rer. nat. Marc Toussaint
Machine Learning and Robotics Lab (IPVS-MLR), University of Stuttgart

TEAM

Moataz Abdelaal (VIS)
Rebeca Duque (ICD)
Valentin Noah Hartmann (IPVS-MLR)
Fabian Kannenberg (ICD)
Tobias Schwinn (ICD)
Nicolai Grünvogel (IBB)

PEER-REVIEWED PUBLICATIONS

2022
1. Richer, G., Pister, A., Abdelaal, M., Fekete, J.-D., Sedlmair, M., & Weiskopf, D. (2022). Scalability in Visualization. IEEE Transactions on Visualization and Computer Graphics, 1–15. https://doi.org/10.1109/TVCG.2022.3231230
  - BibTeX
  BibTeX
  @article{10003102, abstract = {We introduce a conceptual model for scalability designed for visualization research. With this model, we systematically analyze over 120 visualization publications from 1990 to 2020 to characterize the different notions of scalability in these works. While many papers have addressed scalability issues, our survey identifies a lack of consistency in the use of the term in the visualization research community. We address this issue by introducing a consistent terminology meant to help visualization researchers better characterize the scalability aspects in their research. It also helps in providing multiple methods for supporting the claim that a work is “scalable.” Our model is centered around an effort function with inputs and outputs. The inputs are the problem size and resources, whereas the outputs are the actual efforts, for instance, in terms of computational run time or visual clutter. We select representative examples to illustrate different approaches and facets of what scalability can mean in visualization literature. Finally, targeting the diverse crowd of visualization researchers without a scalability tradition, we provide a set of recommendations for how scalability can be presented in a clear and consistent way to improve fair comparison between visualization techniques and systems and foster reproducibility.}, author = {Richer, Gaëlle and Pister, Alexis and Abdelaal, Moataz and Fekete, Jean-Daniel and Sedlmair, Michael and Weiskopf, Daniel}, doi = {10.1109/TVCG.2022.3231230}, issn = {1941-0506}, journal = {IEEE Transactions on Visualization and Computer Graphics}, pages = {1-15}, title = {Scalability in Visualization}, year = 2022 }
2. Menges, A., Kannenberg, F., & Zechmeister, C. (2022). Computational co-design of fibrous architecture. Architectural Intelligence, 1(1), 6--. https://doi.org/10.1007/s44223-022-00004-x
  - BibTeX
  BibTeX
  @article{Menges2022CoDesignFiber, abstract = {Fibrous architecture constitutes an alternative approach to conventional building systems and established construction methods. It shows the potential to converge architectural concerns such as spatial expression and structural elegance, with urgently required resource effectiveness and material efficiency, in a genuinely computational approach. Fundamental characteristics of fibre composite are shared with fibre structures in the natural world, enabling the transfer of design principles and providing a vast repertoire of inspiration. Robotic fabrication based on coreless filament winding, a technique to deposit resin impregnated fibre filaments with only minimal formwork, as well as integrative computational design methods are imperative to the development of complex fibrous building systems. Two projects, the BUGA Fibre Pavilion as an example for long-span structures, and Maison Fibre as an example of multi-storey architecture, showcase the application of those techniques in an architectural context and highlight areas of further research opportunities. The highly interrelated aesthetic, structural and fabrication characteristics of fibre nets are difficult to understand and go beyond a designer’s comprehension and intuition. An AI powered, self-learning agent system aims to extend and thoroughly explore the design space of fibre structures to unlock the full design potential coreless filament winding offers. In order to ensure feedback between all relevant design and performance criteria and enable interdisciplinary convergence, these novel design methods are embedded in a larger co-design framework. It formalizes the interaction of involved interdisciplinary domains and allows for interactive collaboration based on a central data model, serving as a base for design optimisation and exploration. To further advance research on fibre composites in architecture, bio-based materials are considered, continuing the journey of discovery of fibrous architecture to fundamentally rethinking design and construction towards a novel, computational material culture in architecture.}, author = {Menges, Achim and Kannenberg, Fabian and Zechmeister, Christoph}, doi = {10.1007/s44223-022-00004-x}, issn = {27316726}, journal = {Architectural Intelligence}, number = 1, pages = {6--}, refid = {Menges2022}, title = {Computational co-design of fibrous architecture}, url = {https://doi.org/10.1007/s44223-022-00004-x}, volume = 1, year = 2022 }
3. Menges, A., & Wortmann, T. (2022). Synthesising Artificial Intelligence and Physical Performance. Architectural Design, 92(3), 94–99. https://doi.org/10.1002/ad.2819
  - BibTeX
  BibTeX
  @article{menges2022synthesising, author = {Menges, Achim and Wortmann, Thomas}, doi = {https://doi.org/10.1002/ad.2819}, journal = {Architectural Design}, number = 3, pages = {94-99}, title = {Synthesising Artificial Intelligence and Physical Performance}, volume = 92, year = 2022 }
4. Gil Pérez, M., Zechmeister, C., Menges, A., & Knippers, J. (2022). Coreless filament-wound structures: toward performative long-span and sustainable building systems. In S. Xue, J. Wu, & G. Sun (Eds.), Proceedings of IASS Annual Symposia 2022: Innovation, Sustainability and Legacy (Vol. 2022, pp. 3366–3376). International Association for Shell and Spatial Structures (IASS).
  - BibTeX
  BibTeX
  @inproceedings{IASS2022gilperez, abstract = {Coreless filament winding (CFW) was developed in 2012 at the University of Stuttgart to reduce material waste during the fabrication of composite parts. This was achieved by diminishing the required formwork of state-of-the-art filament winding to discrete boundary frames. Then, impregnated fibers are wound between them, forming lightweight lattice structures. A series of pavilions at the University demonstrated the system's potential and enabled the transfer of CFW into practice, bringing along other engineering challenges, such as the requirement to prove structural integrity and safety. The BUGA Fibre Pavilion was the first long-span application using CFW. In this project, a series of full-scale structural tests successfully proved the structural capacity of the composite components. Maison Fibre expanded the research toward multi-story building systems and explored the combination of CFW components with timber plates as hybrid slabs. To improve the sustainability aspects of the system, the LivMatS Pavilion replaced the previously used carbon and glass fibers with natural fibers. This pavilion achieved different materiality, showing the potential of bio-composite filament wound structures. This paper describes and compares the design and engineering process in each system: long-span, hybrid slab, and natural fiber components, and reveals the potential and future research goals to achieve more sustainable building systems using CFW structures.}, author = {Gil Pérez, Marta and Zechmeister, Christoph and Menges, Achim and Knippers, Jan}, booktitle = {Proceedings of IASS Annual Symposia 2022: Innovation, Sustainability and Legacy}, editor = {Xue, Su-duo and Wu, Jin-zhi and Sun, Guo-jun}, eventdate = {September 19-22 2022}, eventtitle = {IASS/APCS 2022 Innovation, Sustainability and Legacy}, month = {September}, pages = {3366-3376}, publisher = {International Association for Shell and Spatial Structures (IASS)}, title = {Coreless filament-wound structures: toward performative long-span and sustainable building systems}, venue = {Beijing, China}, volume = 2022, year = 2022 }
5. Gil Pérez, M., Zechmeister, C., Kannenberg, F., Mindermann, P., Balangé, L., Guo, Y., Hügle, S., Gienger, A., Forster, D., Bischoff, M., Tarín, C., Middendorf, P., Schwieger, V., Gresser, G. T., Menges, A., & Knippers, J. (2022). Computational co-design framework for coreless wound fibre-polymer composite structures. Journal of Computational Design and Engineering, 9(2), 310--329. https://doi.org/10.1093/jcde/qwab081
  - BibTeX
  BibTeX
  @article{Gil_Perez_2022, abstract = {In coreless filament winding, resin-impregnated fibre filaments are wound around anchor points without an additional mould. The final geometry of the produced part results from the interaction of fibres in space and is initially undetermined. Therefore, the success of large-scale coreless wound fibre composite structures for architectural applications relies on the reciprocal collaboration of simulation, fabrication, quality evaluation, and data integration domains. The correlation of data from those domains enables the optimization of the design towards ideal performance and material efficiency. This paper elaborates on a computational co-design framework to enable new modes of collaboration for coreless wound fibre–polymer composite structures. It introduces the use of a shared object model acting as a central data repository that facilitates interdisciplinary data exchange and the investigation of correlations between domains. The application of the developed computational co-design framework is demonstrated in a case study in which the data are successfully mapped, linked, and analysed across the different fields of expertise. The results showcase the framework’s potential to gain a deeper understanding of large-scale coreless wound filament structures and their fabrication and geometrical implications for design optimization.}, author = {Gil Pérez, M and Zechmeister, C and Kannenberg, F and Mindermann, P and Balangé, L and Guo, Y and Hügle, S and Gienger, A and Forster, D and Bischoff, M and Tarín, C and Middendorf, P and Schwieger, V and Gresser, G T and Menges, A and Knippers, J}, doi = {10.1093/jcde/qwab081}, journal = {Journal of Computational Design and Engineering}, month = apr, note = {M. Gil Perez and C. Zechmeister: first authors equal contribution. F. Kannenberg and P. Mindermann: second authors equal contribution.}, number = 2, pages = {310--329}, publisher = {Oxford University Press ({OUP})}, title = {Computational co-design framework for coreless wound fibre-polymer composite structures}, url = {https://doi.org/10.1093%2Fjcde%2Fqwab081}, volume = 9, year = 2022 }
6. Abdelaal, M., Schiele, N. D., Angerbauer, K., Kurzhals, K., Sedlmair, M., & Weiskopf, D. (2022). Supplemental Materials for: Comparative Evaluation of Bipartite, Node-Link, and Matrix-Based Network Representations. DaRUS. https://doi.org/10.18419/DARUS-3100
  - BibTeX
  BibTeX
  @dataset{darus-3100_2022, author = {Abdelaal, Moataz and Schiele, Nathan Daniel and Angerbauer, Katrin and Kurzhals, Kuno and Sedlmair, Michael and Weiskopf, Daniel}, doi = {10.18419/DARUS-3100}, publisher = {DaRUS}, title = {Supplemental Materials for: Comparative Evaluation of Bipartite, Node-Link, and Matrix-Based Network Representations}, url = {https://darus.uni-stuttgart.de/citation?persistentId=doi:10.18419/darus-3100}, year = 2022 }
7. Abdelaal, M., Amtsberg, F., Becher, M., Estrada, R. D., Kannenberg, F., Calepso, A. S., Wagner, H. J., Reina, G., Sedlmair, M., Menges, A., & Weiskopf, D. (2022). Visualization for Architecture, Engineering, and Construction: Shaping the Future of Our Built World. IEEE Computer Graphics and Applications, 42(2), 10–20. https://doi.org/10.1109/MCG.2022.3149837
  - BibTeX
  BibTeX
  @article{9709159, abstract = {Our built world is one of the most important factors for a livable future, accounting for massive impact on resource and energy use, as well as climate change, but also the social and economic aspects that come with population growth. The architecture, engineering, and construction industry is facing the challenge that it needs to substantially increase its productivity, let alone the quality of buildings of the future. In this article, we discuss these challenges in more detail, focusing on how digitization can facilitate this transformation of the industry, and link them to opportunities for visualization and augmented reality research. We illustrate solution strategies for advanced building systems based on wood and fiber.}, author = {Abdelaal, Moataz and Amtsberg, Felix and Becher, Michael and Estrada, Rebeca Duque and Kannenberg, Fabian and Calepso, Aimée Sousa and Wagner, Hans Jakob and Reina, Guido and Sedlmair, Michael and Menges, Achim and Weiskopf, Daniel}, doi = {10.1109/MCG.2022.3149837}, issn = {1558-1756}, journal = {IEEE Computer Graphics and Applications}, month = {March}, number = 2, pages = {10-20}, title = {Visualization for Architecture, Engineering, and Construction: Shaping the Future of Our Built World}, volume = 42, year = 2022 }
8. Abdelaal, M., Schiele, N. D., Angerbauer, K., Kurzhals, K., Sedlmair, M., & Weiskopf, D. (2022). Comparative Evaluation of Bipartite, Node-Link, and Matrix-Based Network Representations. IEEE Transactions on Visualization and Computer Graphics, 1–11. https://doi.org/10.1109/TVCG.2022.3209427
  - BibTeX
  BibTeX
  @article{9908291, abstract = {This work investigates and compares the performance of node-link diagrams, adjacency matrices, and bipartite layouts for visualizing networks. In a crowd-sourced user study (n = 150), we measure the task accuracy and completion time of the three representations for different network classes and properties. In contrast to the literature, which covers mostly topology-based tasks (e.g., path finding) in small datasets, we mainly focus on overview tasks for large and directed networks. We consider three overview tasks on networks with 500 nodes: (T1) network class identification, (T2) cluster detection, and (T3) network density estimation, and two detailed tasks: (T4) node in-degree vs. out-degree and (T5) representation mapping, on networks with 50 and 20 nodes, respectively. Our results show that bipartite layouts are beneficial for revealing the overall network structure, while adjacency matrices are most reliable across the different tasks.}, author = {Abdelaal, Moataz and Schiele, Nathan D. and Angerbauer, Katrin and Kurzhals, Kuno and Sedlmair, Michael and Weiskopf, Daniel}, doi = {10.1109/TVCG.2022.3209427}, issn = {1941-0506}, journal = {IEEE Transactions on Visualization and Computer Graphics}, pages = {1-11}, title = {Comparative Evaluation of Bipartite, Node-Link, and Matrix-Based Network Representations}, year = 2022 }
2021
1. Hägele, D., Abdelaal, M., Oguz, O. S., Toussaint, M., & Weiskopf, D. (2021). Visual analytics for nonlinear programming in robot motion planning. Journal of Visualization. https://doi.org/10.1007/s12650-021-00786-8
  - BibTeX
  BibTeX
  @article{hagele2021visual, abstract = {Nonlinear programming is a complex methodology where a problem is mathematically expressed in terms of optimality while imposing constraints on feasibility. Such problems are formulated by humans and solved by optimization algorithms. We support domain experts in their challenging tasks of understanding and troubleshooting optimization runs of intricate and high-dimensional nonlinear programs through a visual analytics system. The system was designed for our collaborators’ robot motion planning problems, but is domain agnostic in most parts of the visualizations. It allows for an exploration of the iterative solving process of a nonlinear program through several linked views of the computational process. We give insights into this design study, demonstrate our system for selected real-world cases, and discuss the extension of visualization and visual analytics methods for nonlinear programming.}, author = {Hägele, David and Abdelaal, Moataz and Oguz, Ozgur S. and Toussaint, Marc and Weiskopf, Daniel}, doi = {10.1007/s12650-021-00786-8}, issn = {18758975}, journal = {Journal of Visualization}, refid = {Hägele2021}, title = {Visual analytics for nonlinear programming in robot motion planning}, url = {https://doi.org/10.1007/s12650-021-00786-8}, year = 2021 }
2. Duque Estrada, R., Kannenberg, F., Wagner, H. J., Yablonina, M., & Menges, A. (2021). Integrative Design Methods for Spatial Winding. Advances in Architectural Geometry 2020, 286–305. https://thinkshell.fr/wp-content/uploads/2019/10/AAG2020_15_Duque.pdf
  - BibTeX
  BibTeX
  @inproceedings{DuqueAAG2020, address = {Paris}, author = {Duque Estrada, Rebeca and Kannenberg, Fabian and Wagner, Hans Jakob and Yablonina, Maria and Menges, Achim}, booktitle = {Advances in Architectural Geometry 2020}, isbn = {978-2-85978-540-6}, pages = {286-305}, publisher = {Presses des Ponts}, title = {Integrative Design Methods for Spatial Winding}, url = {https://thinkshell.fr/wp-content/uploads/2019/10/AAG2020_15_Duque.pdf}, year = 2021 }
2020
1. Hägele, D., Abdelaal, M., Oguz, O. S., Toussaint, M., & Weiskopf, D. (2020). Visualization of Nonlinear Programming for Robot Motion Planning. Proceedings of the 13th International Symposium on Visual Information Communication and Interaction. https://doi.org/10.1145/3430036.3430050
  - BibTeX
  BibTeX
  @inproceedings{haegele2020nonlinear, abstract = {Nonlinear programming targets nonlinear optimization with constraints, which is a generic yet complex methodology involving humans for problem modeling and algorithms for problem solving. We address the particularly hard challenge of supporting domain experts in handling, understanding, and trouble-shooting high-dimensional optimization with a large number of constraints. Leveraging visual analytics, users are supported in exploring the computation process of nonlinear constraint optimization. Our system was designed for robot motion planning problems and developed in tight collaboration with domain experts in nonlinear programming and robotics. We report on the experiences from this design study, illustrate the usefulness for relevant example cases, and discuss the extension to visual analytics for nonlinear programming in general.}, address = {New York, NY, USA}, articleno = {10}, author = {Hägele, David and Abdelaal, Moataz and Oguz, Ozgur S. and Toussaint, Marc and Weiskopf, Daniel}, booktitle = {Proceedings of the 13th International Symposium on Visual Information Communication and Interaction}, doi = {10.1145/3430036.3430050}, isbn = {9781450387507}, location = {Eindhoven, Netherlands}, numpages = {8}, publisher = {Association for Computing Machinery}, series = {VINCI '20}, title = {Visualization of Nonlinear Programming for Robot Motion Planning}, url = {https://doi.org/10.1145/3430036.3430050}, year = 2020 }
2. Duque Estrada, R., Kannenberg, F., Wagner, H. J., Yablonina, M., & Menges, A. (2020). Spatial Winding: Cooperative Heterogeneous Multi-Robot System for Fibrous Structures. Construction Robotics, 4(3–4), 205–215. https://doi.org/10.1007/s41693-020-00036-7
  - BibTeX
  BibTeX
  @article{duqueestrada2020coro, author = {Duque Estrada, Rebeca and Kannenberg, Fabian and Wagner, Hans Jakob and Yablonina, Maria and Menges, Achim}, doi = {10.1007/s41693-020-00036-7}, journal = {Construction Robotics}, month = {9}, number = {3-4}, pages = {205-215}, publisher = {Springer Science and Business Media {LLC}}, title = {Spatial Winding: Cooperative Heterogeneous Multi-Robot System for Fibrous Structures}, volume = 4, year = 2020 }
3. Abdelaal, M., Lhuillier, A., Hlawatsch, M., & Weiskopf, D. (2020). Time-Aligned Edge Plots for Dynamic Graph Visualization. 2020 24th International Conference Information Visualisation (IV). https://doi.org/10.1109/IV51561.2020.00048
  - BibTeX
  BibTeX
  @conference{abdelaal2020timealigned, author = {Abdelaal, Moataz and Lhuillier, Antoine and Hlawatsch, Marcel and Weiskopf, Daniel}, booktitle = {2020 24th International Conference Information Visualisation (IV)}, doi = {10.1109/IV51561.2020.00048}, title = {Time-Aligned Edge Plots for Dynamic Graph Visualization}, year = 2020 }

OTHER PUBLICATIONS

2023
1. Gil Pérez, M., Zechmeister, C., Kannenberg, F., Mindermann, P., Balangé, L., Guo, Y., Hügle, S., Gienger, A., Forster, D., Bischoff, M., Tarín, C., Middendorf, P., Schwieger, V., Gresser, G. T., Menges, A., & Knippers, J. (2023). Object model data sets of the case study specimens for the computational co-design framework for coreless wound fibre-polymer composite structures. DaRUS. https://doi.org/10.18419/darus-3375
  - BibTeX
  BibTeX
  @dataset{darus-3375_2023, author = {Gil Pérez, Marta and Zechmeister, Christoph and Kannenberg, Fabian and Mindermann, Pascal and Balangé, Laura and Guo, Yanan and Hügle, Sebastian and Gienger, Andreas and Forster, David and Bischoff, Manfred and Tarín, Cristina and Middendorf, Peter and Schwieger, Volker and Gresser, Götz Theodor and Menges, Achim and Knippers, Jan}, doi = {10.18419/darus-3375}, publisher = {DaRUS}, title = {Object model data sets of the case study specimens for the computational co-design framework for coreless wound fibre-polymer composite structures}, url = {https://doi.org/10.18419/darus-3375}, version = {V1}, year = 2023 }
2022
1. Abdelaal, M. A. E., Amtsberg, F., Becher, M., Duque Estrada, R., Kannenberg, F., Calepso, A. S., Wagner, H.-J., Reina, G., Sedlmair, M., Menges, A., & Weiskopf, D. (2022). Visualization for Architecture, Engineering, and Construction : Shaping the Future of Our Built World. IEEE Computer Graphics and Applications, 217(May), 110624. https://doi.org/10.1109/MCG.2022.3149837
  - BibTeX
  BibTeX
  @article{abdelaal2022visualization, affiliation = {Abdelaal, M (Corresponding Author), Univ Stuttgart, D-70569 Stuttgart, Germany. Abdelaal, Moataz; Becher, Michael; Calepso, Aimee Sousa; Reina, Guido; Sedlmair, Michael; Weiskopf, Daniel, Univ Stuttgart, D-70569 Stuttgart, Germany. Amtsberg, Felix; Estrada, Rebeca Duque; Kannenberg, Fabian; Wagner, Hans Jakob; Menges, Achim, Univ Stuttgart, Inst Computat Design & Construct, D-70569 Stuttgart, Germany.}, author = {Abdelaal, Moataz Abdelfattah Elsayed and Amtsberg, Felix and Becher, Michael and Duque Estrada, Rebeca and Kannenberg, Fabian and Calepso, Aimée Sousa and Wagner, Hans-Jakob and Reina, Guido and Sedlmair, Michael and Menges, Achim and Weiskopf, Daniel}, doi = {10.1109/MCG.2022.3149837}, issn = {{0272-1716} and {1558-1756}}, journal = {IEEE computer graphics and applications}, language = {eng}, number = {May}, orcid-numbers = {Reina, Guido/0000-0003-4127-1897 Menges, Achim/0000-0001-9055-4039 Abdelaal, MOATAZ/0000-0003-4630-7916 Wagner, Hans Jakob/0000-0001-8600-8481}, pages = 110624, publisher = {IEEE}, research-areas = {Computer Science}, title = {Visualization for Architecture, Engineering, and Construction : Shaping the Future of Our Built World}, unique-id = {WOS:000792916200003}, volume = 217, year = 2022 }

DATA SETS

2023
1. Gil Pérez, M., Zechmeister, C., Kannenberg, F., Mindermann, P., Balangé, L., Guo, Y., Hügle, S., Gienger, A., Forster, D., Bischoff, M., Tarín, C., Middendorf, P., Schwieger, V., Gresser, G. T., Menges, A., & Knippers, J. (2023). Object model data sets of the case study specimens for the computational co-design framework for coreless wound fibre-polymer composite structures. DaRUS. https://doi.org/10.18419/darus-3375
  - BibTeX
  BibTeX
  @dataset{darus-3375_2023, author = {Gil Pérez, Marta and Zechmeister, Christoph and Kannenberg, Fabian and Mindermann, Pascal and Balangé, Laura and Guo, Yanan and Hügle, Sebastian and Gienger, Andreas and Forster, David and Bischoff, Manfred and Tarín, Cristina and Middendorf, Peter and Schwieger, Volker and Gresser, Götz Theodor and Menges, Achim and Knippers, Jan}, doi = {10.18419/darus-3375}, publisher = {DaRUS}, title = {Object model data sets of the case study specimens for the computational co-design framework for coreless wound fibre-polymer composite structures}, url = {https://doi.org/10.18419/darus-3375}, version = {V1}, year = 2023 }

Prof. Dr.-Ing. Jan Knippers

Deputy Director

Phone: +49 711 685 83280

E-Mail

Prof. Achim Menges

Director

Phone: +49 711 685 82786

E-Mail

Prof. Dr. rer. nat. Marc Toussaint

Principal Investigator

E-Mail

Prof. Dr. Daniel Weiskopf

Board of Directors

Phone: +49 711 685 88602

E-Mail

Prof. Dr.-Ing. habil. Manfred Bischoff

Principal Investigator

Phone: +49 711 685 66123

E-Mail

Prof. Dr.-Ing. Götz Gresser

Principal Investigator

Phone: +49 711 9340467

E-Mail