Consequence Models

Introduction

Consequence models translate structural damage states into economic losses and other impact metrics. These models are essential for converting fragility analysis results into actionable risk metrics for decision-making.

Damage-to-Loss Ratios

Damage-to-loss ratios map each damage state to an expected loss expressed as a fraction of a building’s replacement cost. The ratios used in this model are:

Structural Damage-to-Loss Ratios

Damage State

Mean Ratio

Description

DS1 (Slight)

0.05

Minor cosmetic repairs

DS2 (Moderate)

0.15

Moderate structural repairs

DS3 (Extensive)

0.60

Major structural repairs

DS4 (Complete)

1.00

Full replacement

Sources and Derivation

The damage-to-loss ratios are derived from:

Empirical Data

Post-earthquake damage and repair cost surveys (Di Pasquale et al. 2005; Bal et al. 2008)

Analytical Procedures

Component-based loss estimation methodologies (Martins et al. 2016; Aljawhari et al. 2023)

Loss Categories

Structural Losses

Losses associated with damage to the building’s lateral load-resisting system and gravity load-carrying elements.

Non-Structural Loss Functions (SLFs)

Storey Loss Functions (SLFs) relate engineering demand parameters (EDPs) directly to loss ratios for non-structural components. Two types of SLFs are provided:

  • Drift-sensitive SLFs: For components sensitive to interstorey drift (partitions, facades, stairs)

  • Acceleration-sensitive SLFs: For components sensitive to floor acceleration (ceilings, MEP systems)

The SLFs are available for different regions, building materials, component categories, and occupancy types.

Interactive SLF Viewer

Embodied Carbon Loss Functions

Carbon SLFs express embodied carbon loss (kg CO₂-eq per unit floor area) as a function of EDP, for structural and non-structural components. They follow the same region × material × component × occupancy structure as the non-structural SLFs above.

Interactive Carbon SLF Viewer

Contents Losses

Losses from damage to building contents including furniture, fixtures, equipment, machinery, personal belongings (residential), and inventory (commercial/industrial).

Casualty Consequence Models

Casualty models estimate fatalities and injuries based on building damage and collapse. The consequence ratios below represent the expected proportion of building occupants affected at each damage state.

Fatalities Consequence Ratios

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Injuries Consequence Ratios

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Affected Population

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Displaced Population

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Regional Variations

Consequence models may vary by region due to:

  • Construction costs: Labour and material costs differ globally

  • Repair practices: Different repair approaches for similar damage

  • Economic factors: Currency, inflation, and market conditions

  • Building standards: Code requirements for repairs/retrofits

Uncertainty Quantification

Uncertainty in damage-to-loss ratios is captured through:

Within-Damage-State Variability

Coefficient of variation for loss ratio given each damage state

Between-Building Variability

Differences in repair costs for buildings of the same class

The uncertainty is propagated through the vulnerability calculation using the formulations described in the Vulnerability Models section.

References

  • Di Pasquale G. et al. (2005). New developments in seismic risk assessment in Italy. Bulletin of Earthquake Engineering.

  • Bal I.E. et al. (2008). Detailed assessment of structural characteristics of Turkish RC building stock for loss assessment models. Soil Dynamics and Earthquake Engineering.

  • Martins L. et al. (2016). Development and assessment of damage-to-loss models for moment-frame reinforced concrete buildings. Earthquake Engineering & Structural Dynamics.

  • Aljawhari K. et al. (2023). Simulation-based consequence models of seismic direct loss and repair time for archetype reinforced concrete frames. Soil Dynamics and Earthquake Engineering.

  • FEMA (2012). Next-Generation Methodology for Seismic Performance Assessment of Buildings (FEMA P-58). Washington, D.C.