Abstract

This paper presents a qualitative examination of the responses of architects towards the idea for including a formfinding structural optimization method in the architectural schematic design phase. Recently, there has been a few emerging architectural parametric Computer-Aided Design (CAD) systems that enable architects to perform an early schematic form-finding structural optimization such as the coupling of Grasshopper (a visual programming language), Karamba (structural analysis plugin) and Galapagos (optimization plugin). However, the architectural schematic design phase is commonly characterized by free-form shapes without the embedded considerations of the material and structural system. On the other hand, the considerations of materiality and structural system are often more properly imposed by the structural engineers, who usually prefer to be involved as early as possible in the project. Seen from this perspective, this paper discusses the examination process and findings related to the difficulties in the traditional design workflow that separate the architectural form generation process from the engineering aspect of structural performance; the interoperability and integration of architectural parametric CAD tools, engineering analysis and optimization tools as well as the usability of these tools; and the implementation of structural optimization in the architectural schematic design phase. This paper discusses the process of the investigation of these concerns qualitatively using Grounded Theory for data collection and analysis, and for the software development and testing process. Clemson University students and faculty were sampled as research participants. Form-finding structural optimization software that couples Grasshopper, Matlab (a scientific programming language) and Abaqus (finite element analysis software) was developed as a design method to facilitate the interviewing process. The software MAXQDA is used for the qualitative data analysis.

Keywords: Collaboration; Schematic design; Structural optimization; Form-finding; Grounded theory