This research develops a parametric computational design model that generates rib layouts for metal casting tables, taking into account both structural constraints and casting constraints. An algorithm was developed that uses boundary and support positions as inputs to generate parametric rib layouts based on curve networks. The computational approach was tested on a 1:1 scale prototype of a metal cast table. The method was expanded to include casting constraints, such as the circular support positions, which also serve as pouring locations for molten metal. Aluminum flow constraints were incorporated into the generation of rib depth and width, and casting constraints were used to inform the density of the ribs. This design approach reduces weight and material consumption by distributing and aligning material along the flow path of forces while also accounting for the flow physics of molten metal during the casting process. Thus, the computational design model integrates structural optimization and casting constraints to optimize the design of metal cast tables.
Principal Investigators
Assistant Professor Dr. Mania Aghaei Meibodi (DART Laboratory) Benjamin Dillenburger (PI – dbt ETH Zurich)