Journal of Computational Methods in Engineering

Journal of Computational Methods in Engineering

Energy-Based Progressive Collapse Assessment of Steel FrameBuildings for Planning Multi-Stage Explosive Demolition

Document Type : Original Article

Authors
1 Faculty of Civil and Environmental Engineering, Tarbiat Modares University, Tehran, Iran.
2 Faculty of Civil and Environmental Engineering, Tarbiat Modares University, Tehran, Iran
Abstract
This study proposes a practical method for planning multi-stage explosive demolition of multi-story steel structures using nonlinear dynamic analysis and energy-based performance measures in SAP2000. A ten-story steel moment-resisting frame with composite floors is modelled by considering inelastic behaviour through concentrated plastic hinges, second-order effects, and direct time integration with viscous damping. Critical columns at one of the intermediate stories and at the ground story are divided into three blasting groups at each level and removed sequentially with a fixed short interval. At the same time, the delay between the two story-level sequences is treated as the main demolishing variable and examined across multiple scenarios. Performance is assessed using three dimensionless indicators representing collapse efficiency, kinetic response severity with residual motion, and energy-balance consistency. A hierarchical selection rule is applied first, excluding scenarios that fail the energy-consistency requirement and then, ranking the remaining cases primarily by collapse efficiency and secondly by the kinetic indicator. Results show that an intermediate inter-story delay produces a decisive gravity-driven collapse with strong but controlled motion, while very small or very large delays tend to cause incomplete collapse or persistent oscillations. Additional analyses on eight- and five-story steel structures indicate that the proposed assessment logic remains robust with changes in structural height and can support engineers in selecting effective blasting schedules.
Keywords
Subjects

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