Quantitative Structural Retrofit Assessment Models for Strengthening Existing Steel Buildings Under Increased Load Demands

Abstract

This study examined quantitative structural retrofit assessment models for strengthening existing steel buildings exposed to increased load demands. The problem addressed was the growing mismatch between the original design capacity of aging steel buildings and the higher structural demands created by occupancy intensification, heavy equipment installation, rooftop service additions, vertical expansion, functional conversion, and updated code requirements. The purpose of the study was to determine how load demand escalation, structural deficiencies, retrofit technique suitability, and retrofit decision drivers influence strengthening effectiveness and structural safety improvement. A quantitative, cross-sectional, case-based research design was adopted, using structured Likert-scale data from 210 technical respondents, including structural engineers, civil engineers, retrofit consultants, construction/project managers, and building assessors, all involved in steel building assessment or strengthening projects. The key variables were increased load demand, structural deficiency, retrofit technique suitability, retrofit decision drivers, and strengthening effectiveness. Data analysis was planned and conducted through descriptive statistics, Pearson correlation analysis, and multiple regression modeling. The findings showed strong agreement that retrofit assessment is necessary under increased load conditions, with mean scores of 4.18 for increased load demand, 4.09 for structural deficiency, 4.23 for retrofit suitability, 4.27 for retrofit decision drivers, and 4.31 for strengthening effectiveness. Connection weakness ranked as the leading structural deficiency (M = 4.17), while heavy equipment installation was the highest-ranked load escalation factor (M = 4.26). Connection strengthening was rated the most suitable retrofit technique (M = 4.35), and structural safety requirement was the highest decision priority (M = 4.41). Correlation results showed significant positive relationships between assessment variables and strengthening effectiveness, with coefficients ranging from r = 0.593 to r = 0.711, all at p < .001. Regression results further confirmed that the model explained 61.0% of the variance in strengthening effectiveness (R² = 0.610, F (4,205) = 80.13, p < .001), with retrofit suitability emerging as the strongest predictor (β = 0.331). The study implies that steel-building retrofit decisions should be guided by structured, data-based assessment models that align load demand, system deficiencies, intervention suitability, and safety-centered decision priorities to improve reliability and continued serviceability.