This study explores UAV-based 3D modeling for bridge damage assessment. UAVs with highresolution cameras captured images of two bridges at different life cycle stages and locations. These images were processed into detailed 3Dmodels, offeringmore accurate evaluations than traditional visual inspections (VI). The models provided precise damage localization, geometric data information, and identified areas requiring urgent maintenance, reducing repair costs and time. Despite the advantages, challenges such as model accuracy and flight planning precision were noted. The results showed that larger and more complex bridges require significantly greater resources for 3D modeling, including longer flight and processing times, higher data volumes, and increased detail in the models, as reflected in the differences between the two case studies. Future research should focus on optimizing data acquisition, enhancing algorithms, and integrating augmented reality (AR) to improve collaboration and decision-making in bridge inspections.

Reinforced concrete structures (RCSs) face increasing vulnerability due to aging, deterioration, and climate change, compounded by seismic events. This paper proposes a framework that integrates time-dependent deterioration mechanisms, climate projections, and seismic vulnerability analyses. The methodology develops deterioration profiles using site-specific data while employing Performance-Based Earthquake Engineering (PBEE) to evaluate seismic risks. Climate scenarios from the IPCC address non-stationary climate impacts, such as accelerated corrosion. This research represents a first step toward defining a systematic process for assessing these combined effects. The proposed framework addresses critical gaps in traditional vulnerability assessments and contributes to improving the resilience of aging infrastructure under combined environmental and seismic hazards.