Existing and new structures are subjected to different types of loads. Modern instrumentation methodologies and advancements in the Internet of Things (IoT) paradigm are opening new technology directions and challenges in the evaluation of the lifecycle of these structures.

Development of appropriate sensors, communication protocols, and cloud-based data analysis algorithms helps us to better understand the structural health of structures in terms of taking timely managerial decisions. However, the assessment of structures under complex loads is still limited. The performance and behavior analyses of structures in time and frequency domains under two or more dynamic loads can be used to assess the accurate performance of structures. Simulation and experimental or real measurements can be used to understand the actual performances of existing or new structures with support from the emerging Machine Learning (ML) paradigm.

This Special Issue aims to provide an opportunity for practicing structural and computing science researchers to share their original research and review articles based on novel theories, simulations, and experimental results regarding understanding the real behavior of structures. In addition, the evaluation of existing structures using ML/computational algorithm approaches is encouraged.

Potential topics include but are not limited to the following:

• Vibration evaluation of structures under complex loads
• Evaluation tools in the development of structures exposed to different loads
• Development of sensors for extracting the behavior of structures under multi-hazard dynamic responses
• Lifecycle and structural health monitoring systems for assessing the performance of existing structures
• Machine learning and computational algorithms for monitoring of structures under different loads