Traditionally, nonlinear time history analysis (NLTHA) is used to assess the performance of structures under future hazards which is necessary to develop effective disaster risk management strategies. However, this method is computationally intensive and not suitable for analyzing a large number of structures on a city-wide scale. Surrogate models offer an efficient and reliable alternative and facilitate evaluating the performance of multiple structures under different hazard scenarios. However, creating a comprehensive database for surrogate modelling at the city level presents challenges. To overcome this, the present study proposes meta databases and a general framework for surrogate modelling of steel structures. The dataset includes 30,000 steel moment-resisting frame buildings, representing low-rise, mid-rise and high-rise buildings, with criteria for connections, beams, and columns. Pushover analysis is performed and structural parameters are extracted, and finally, incorporating two different machine learning algorithms, random forest and Shapley additive explanations, sensitivity and explainability analyses of the structural parameters are performed to identify the most significant factors in designing steel moment resisting frames. The framework and databases can be used as a validated source of surrogate modelling of steel frame structures in order for disaster risk management.

This study presents a framework for assessing the resilience of steel special moment-resisting frame (SMRF) buildings under sequential earthquake–flood hazards. Surrogate models, including a stacked attention-based LSTM network (Stack-AttenLSTM) and CatBoost, are developed to predict key engineering demand parameters (EDPs), particularly maximum inter-storey drift ratios (MIDRs), avoiding the need for computationally expensive nonlinear time history analysis (NLTHA). The predicted EDPs are integrated with the FEMA P-58 methodology to estimate repair costs and durations, while the REDi framework is used to capture recovery delays and functionality loss. A two-storey code-compliant SMRF building is evaluated under a design-basis earthquake (DBE) with and without a subsequent 4.0 m flood. Results show that the combined hazard nearly doubles repair costs (from 0.33 to 0.77 of replacement value), increases downtime from 194 to over 411 days, and reduces the resilience index (R_i) from 0.873 to 0.265. These findings highlight the severe impacts of cascading multi-hazard events and the need to extend performance-based design toward resilience-focused strategies. The proposed surrogate-based framework provides a practical tool for evaluating multi-hazard risks and guiding the design of more resilient structures.