The spread of an initial local failure from element to element resulting eventually in the collapse of an entire structure or a disproportionately large part of it, is called as progressive collapse. This review paper provides a comprehensive overview of the progressive collapse of multistorey Reinforced Concrete (RC) buildings, focusing on the causes, analysis methods, and mitigation strategies. The paper synthesizes current research and design guidelines from various codes, highlighting key factors influencing collapse resistance and the role of modern analytical techniques which will be helpful in the assessment of progressive collapse. It also discusses the critical aspects of load redistribution, structural redundancy, and ductility in preventing the severe events.
Introduction
Progressive collapse refers to the chain reaction of structural failure triggered by the loss of a primary load-bearing component, leading to widespread or total building collapse. This concept gained prominence after the collapse of a 22-storey apartment building in East London due to a small gas explosion.
The American Society of Civil Engineers (ASCE) defines progressive collapse as the “spread of an initial local failure from element to element, eventually causing the collapse of an entire structure or a disproportionately large portion of it.”
2. Objectives of the Study
Evaluate progressive collapse risk in multi-storey buildings.
Identify collapse patterns due to different failure points.
Study the importance of alternate load paths.
Measure changes in axial forces, bending moments, and shear forces post element removal.
Understand international safety standards and calculate Demand-Capacity Ratio (DCR).
Corrosion, substandard materials, fatigue, and creep.
C. Extreme or Abnormal Events
Explosions, vehicular impacts, earthquakes, strong winds, and fires.
4. Methodologies for Analysis
A. Analysis Techniques
Linear Static Analysis (LSA)
Simulates column removal with a Dynamic Increase Factor (DIF), typically 2.0.
Calculates DCR to assess vulnerability.
Non-Linear Static Analysis
More accurate; accounts for material/geometric nonlinearities and post-elastic behavior (e.g., catenary action).
Linear Dynamic Method
Uses finite element models and time-dependent analysis under elastic assumptions.
Good for early-stage design and vulnerability screening.
Non-Linear Dynamic Method
Most comprehensive; simulates realistic collapse progression but is computationally intensive.
B. GSA Guidelines for Column Removal
Prescribe removal of internal/external columns in critical zones (e.g., corners, mid-spans, load discontinuities).
Adjacent columns within 30% of bay width must also be removed simultaneously in some cases.
C. Demand-Capacity Ratio (DCR)
DCR = Demand / Capacity
Must be ≤ 2.0 (regular structures), ≤ 1.5 (irregular structures) to avoid critical failure.
5. Key Findings from Literature Review
Column location: Interior or corner column removal has greater collapse potential.
Structural configuration: Regular, symmetrical structures are more resilient.
Flat slab systems: Vulnerable to punching shear failure, need careful design without beams.
6. Proposed Future Research
Focused on a G+9 residential structure modeled in ETABS.
Using linear dynamic analysis (response spectrum method) as per GSA guidelines.
Structural parameters to be analyzed:
Axial loads
Lateral displacements
Storey drift
Storey stiffness
Demand-Capacity Ratio (DCR)
Model Inputs:
Plan size: 18.60 m × 14.30 m
Concrete grade: M30
Steel grade: Fe550
Wind speed: 39 m/s
Seismic Zone: III (Zone factor: 0.16)
Importance factor: 1.20
Response reduction factor: 5
Soil type: Type II (medium soil)
Conclusion
The literature emphasizes that factors such as load redistribution mechanisms, redundancy, continuity, and ductility significantly influence a building’s response to progressive collapse. Additionally, design strategies such as increasing the robustness of critical members, implementing alternate load paths, and adopting performance-based design criteria have proven effective in enhancing structural resilience. While available software packages offers powerful capabilities for simulating progressive collapse, it is essential to complement numerical results with experimental data and to consider limitations such as simplified assumptions and idealized boundary conditions. The use of linear static analysis provides a quick assessment the industry is moving towards more sophisticated nonlinear dynamic analysis to capture the true behaviour of a structure. Future research should also focus on integrating more realistic failure models and exploring hybrid approaches that combine software with other tools or physical testing to improve predictive accuracy. Continued research is essential to refine design codes and develop innovative solutions to ensure that modern buildings can withstand localized failures without disproportionate collapse.
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