Introduction
Office buildings concentrate occupants, services, and value-dense assets, making them priority targets for risk reduction under multi-hazard conditions. Materials and envelope systems decisively shape blast and fire consequences, out-of-plane wall response under shaking, and the ease of post-event clearance and repair. This study develops a rapid, material-centric, scenario-based evaluation framework for office buildings. Unlike case-specific assessments, the approach generalizes findings by integrating expert judgment with multi-criteria analysis and calibrating priorities to the prevailing context (scenarios), thereby producing actionable, defensible rankings without relying on a single project.
Methodology
Eight criteria were defined to appraise material and component choices in office buildings: (C1) blast-effect reduction, (C2) fire resistance, (C3) seismic performance, (C4) debris-removal facilitation, (C5) repairability, (C6) construction speed, (C7) execution complexity, and (C8) cost. Criterion weights were derived using SWARA, and indicator/option scores under each criterion were elicited via SMART on a 1–9 semantic scale (poor–excellent). Data were gathered from 15 domain experts (structural/architectural design, façade engineering, HSE/civil defense, and urban crisis management) through a staged survey with content validation, consistency checks, and sensitivity analysis. To reflect context dependence, a scenario calibration layer was applied to the SWARA weights: four complementary scenarios were analyzed—blast-focused (S1), fire-focused (S2), operations-focused (S3: speed/ complexity/ cost/ debris/ repair), and seismic-focused (S4)—by proportionally emphasizing the relevant criterion(-ia) and renormalizing before aggregating SMART scores to final rankings.
Results and discussion
Baseline SWARA prioritization shows blast mitigation carries the highest weight (0.2531), followed by fire resistance (0.1947), seismic performance (0.1693), debris removal (0.1254), cost (0.0963), repairability (0.0689), construction speed (0.0530), and execution complexity (0.0393). At the indicator level, glazing ranks first within blast mitigation; interior finishes dominate fire resistance; and the type of structural system leads complexity, speed, and cost. Overall material weight (light-/heavy-weight) is the top indicator for debris removal and consistently prevails alongside seismic and repairability considerations. Scenario analysis reveals a stable decision core across contexts: the structural system and exterior walls remain among the top drivers in all four scenarios. Emphasis shifts then lift specific levers: in S1 (blast), exterior walls, structural system, and glazing become most influential, highlighting continuous anchorage, out-of-plane restraint, laminated glazing, and robust façade attachments; in S2 (fire), exterior walls, structural system, and façade materials dominate, underscoring low-flame-spread surfaces, smoke-control layers, and structural fire protection; in S3 (operations) and S4 (seismic), material weight consistently enters the top tier with the structural system and exterior walls, indicating the cross-cutting benefits of light-weighting for faster execution, easier debris handling and repair, and lower seismic demand. These results clarify trade-offs between safety, constructability, and recovery, and provide transparent rankings that can guide budget allocation under different hazard and operational emphases.
Conclusion
The proposed SWARA–SMART, scenario-calibrated framework offers a transparent and rapid pathway to prioritize materials and components in office buildings under multi-hazard constraints. By revealing a robust core (structural system + exterior walls) and scenario-specific levers (glazing/façade under blast/fire; light-weighting under operations/ seismic), the method enables targeted investment without dependence on a single case study. The framework is readily transferable to similar projects by reusing the criteria set and scoring protocol and can be extended with uncertainty treatment and performance-based testing in future applications.