Evolve: Identifying when current design guidelines contribute to disproportionate collapse of reinforced concrete building structures.
Principal researcher:
NIRVAN MAKOOND
Team members:
- ANDRI SETIAWAN
- LISBEL RUEDA
Funding Agency:
Duration: 01/01/2024 – 31/12/2025
Reference: CIGE/2023/199
Abstract
In a world is threatened by climate change and geopolitical tensions, buildings are today increasingly exposed to extreme abnormal events. Such events usually cause local-initial failures that then propagate to the rest of the structure, resulting in a disproportionate collapse. To prevent such collapses, engineers aim to design robust structures that are insensitive to initial damage. Current robustness design methods rely on improving connectivity between components to provide alternative load paths for redistributing loads supported by failed components. However, when large initial failures occur, this increased connectivity can contribute to collapsing debris pulling down parts of the structure that would otherwise be unaffected. The conditions required for this unfavourable situation to occur are still not well understood. In fact, current building codes include no provisions for assessing whether the connectivity prescribed by commonly used robustness design methods can contribute to more disproportionate collapse after large initial failures. A better understanding of how connectivity can contribute to disproportionate collapse is therefore urgently needed.
The overall aim of Evolve is to develop a performance-assessment framework to identify when more connectivity and continuity can increase the risk of disproportionate collapse in reinforced concrete (RC) structures.
This aim will be achieved by: 1) calibrating a suitable computational modelling strategy to simulate all phases of a building collapse, 2) systematically analysing collapse propagation in a carefully defined set of realistic building designs using the calibrated computational modelling strategy, 3) defining performance objectives for determining optimal levels of continuity for enhanced robustness.