Aspects of Buildability for Automated Bridge Design
Paper in proceeding, 2025

Buildability and climate impact aspects are central in civil engineering projects, however, climate impact is not prioritized over buildability. Consequently, identifying designs that meet both buildability and climate impact objectives are challenging. Design automation with machine learning have been suggested as an approach, although a quantification of buildability is difficult. The purpose of this study was to explore practical buildability where the objective was to establish and list buildability aspects. A series of semi-structured interviews were conducted with experienced construction engineers. The result indicates that practical buildability encompasses systematic requirement management, capturing dependencies ramification, method decisions, design options, binary feasibility, resources, accessibility and availability, and time and schedule. Hence, a quantification could be possible, albeit specific for each buildability aspect.

bridge design

Automation

climate impact

buildability

machine learning

Author

Alexander Kjellgren

Chalmers, Architecture and Civil Engineering

Helén Broo

Chalmers, Architecture and Civil Engineering

Per Kettil

Chalmers, Architecture and Civil Engineering

Mikael Johansson

Chalmers, Architecture and Civil Engineering

Rasmus Rempling

Chalmers, Architecture and Civil Engineering

Mats Granath

University of Gothenburg

IABSE Symposium Tokyo 2025 Environmentally Friendly Technologies and Structures Focusing on Sustainable Approaches Report

1546-1554
9783857482069 (ISBN)

IABSE Symposium Tokyo 2025: Environmentally Friendly Technologies and Structures: Focusing on Sustainable Approaches
Tokyo, Japan,

Subject Categories (SSIF 2025)

Construction Management

Computational Mathematics

Infrastructure Engineering

DOI

10.2749/tokyo.2025.1546

More information

Latest update

7/2/2025 9