TY - CHAP
T1 - Generative Structural Design
T2 - A Cross-Platform Design and Optimization Workflow for Additive Manufacturing
AU - Aziz, Saqib
AU - Kim, Ji Su
AU - Stephan, Dietmar
AU - Gengnagel, Christoph
N1 - Publisher Copyright:
© 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.
PY - 2022
Y1 - 2022
N2 - This paper explores a generative design, simulation, and optimization workflow for full-scale 3D printed building components using an array of different mixtures. Large-scale additive manufacturing in conjunction with algorithmic CAD design tools enables a vast amount of control when creating geometry. This can also be advantageous regarding the increasing demands to use more resourceful and sustainable construction methods and materials. The presented methodology aims to highlight these new technological advancements and offers a multimodal and integrative design solution with the potential for an immediate application in the AEC-Industry. The presented work will investigate a case study based on a structurally optimized waffle or two-way joist slab. The goal is to create permanent formwork that serves as molds during the pouring and fabrication process on-site and validates the structural integrity of those 3d concrete printed molds. For this, a hybrid validation strategy, using a digital and cross-platform simulation environment that is audited with physical prototyping is investigated. Various geometric attributes are parameterized and can be imported to a finite element method (FEM) software via a custom workflow. Here the structural behaviors and failure patterns of the molds during the pouring process are examined and incrementally optimized to satisfy minimum structural performance requirements to ultimately withstand the pressure of the cast-in-situ concrete. Subsequently, alternative and hybrid mixtures and materials, e.g., foam concrete and eco-friendly composites are numerically evaluated and compared. The results are fed back to the parametric design model to further optimize the generative workflow.
AB - This paper explores a generative design, simulation, and optimization workflow for full-scale 3D printed building components using an array of different mixtures. Large-scale additive manufacturing in conjunction with algorithmic CAD design tools enables a vast amount of control when creating geometry. This can also be advantageous regarding the increasing demands to use more resourceful and sustainable construction methods and materials. The presented methodology aims to highlight these new technological advancements and offers a multimodal and integrative design solution with the potential for an immediate application in the AEC-Industry. The presented work will investigate a case study based on a structurally optimized waffle or two-way joist slab. The goal is to create permanent formwork that serves as molds during the pouring and fabrication process on-site and validates the structural integrity of those 3d concrete printed molds. For this, a hybrid validation strategy, using a digital and cross-platform simulation environment that is audited with physical prototyping is investigated. Various geometric attributes are parameterized and can be imported to a finite element method (FEM) software via a custom workflow. Here the structural behaviors and failure patterns of the molds during the pouring process are examined and incrementally optimized to satisfy minimum structural performance requirements to ultimately withstand the pressure of the cast-in-situ concrete. Subsequently, alternative and hybrid mixtures and materials, e.g., foam concrete and eco-friendly composites are numerically evaluated and compared. The results are fed back to the parametric design model to further optimize the generative workflow.
KW - Additive manufacturing
KW - Computational design
KW - Design to fabrication
KW - Multimodal optimization
KW - Structural design
UR - http://www.scopus.com/inward/record.url?scp=85133212035&partnerID=8YFLogxK
U2 - 10.1007/978-3-031-06116-5_53
DO - 10.1007/978-3-031-06116-5_53
M3 - Chapter
AN - SCOPUS:85133212035
T3 - RILEM Bookseries
SP - 357
EP - 363
BT - RILEM Bookseries
PB - Springer Science and Business Media B.V.
ER -