Optimizing computational workflows in bridge design through standardization, modularization, and interoperability

Abstract

The ongoing paradigm shift in the structural design industry, driven by computational design, is fundamentally altering the nature of design processes. Traditionally, structural design has followed a decentralized approach, granting designers significant autonomy, albeit at the cost of process fragmentation, low automation, and an inability to translate design processes into machine-readable formats. The aim of this study was to define a conceptual workflow model that harmonizes decentralized design practices with computational bridge design principles.

To achieve this, a series of interviews were conducted with computational bridge design experts at the host company, alongside an analysis of established computational workflows from different agencies and software vendors. These steps helped in identifying the major bottlenecks in current workflows and led to the formulation of potential solutions tailored to the host company’s operational environment. Additionally, the study examined workflow modularization pathways, as this significantly improves knowledge reusability and process optimization.

Key findings from this study highlight the effectiveness of plug-in components within the Grasshopper environment, particularly those from Sofistik and Tekla side, that are not native to Grasshopper environment. These components facilitate fast, accurate, and reliable data flow, aligning with the Single Point of Truth (SPOT) knowledge management system by establishing a direct link between the database and the geometric bridge definition in Grasshopper. Additionally, they enable the extraction of both, the Building Information Model (BIM) and the Finite Element Model (FEM) from a single geometric model in Rhinoceros. These plug-in components offer a potential solution to several of the contemporary challenges in computational bridge design and by predetermining input data structures, they pave the pathway for modularizing workflows in terms of data organization.

In conclusion, while some experts may already utilize these plug-in components for certain tasks, this research highlights their broader potential to carry out the entire design, albeit at a conceptual level, using these artifacts, with some potential improvements in their functionality.