Publications
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Featured Publications
Seismic Hazard and Structural Vulnerability: A Study of Building Damage in the 2017 Kermanshah Earthquake
Hedayat, S., Ciampi, P., and Scarascia Mugnozza, G.
This paper analyzes the structural vulnerabilities and seismic resilience factors leading to building damage and collapse in the 2017 Kermanshah Earthquake, providing insights for improved structural design and seismic resilience strategies.
Advancing Infrastructure Resilience through Smart Monitoring: Insights from the Genoa Bridge Catastrophe
Hedayat, S., Ziarati, T., Ciampi, P., Giannini, L.M.
This research evaluates the structural integrity and resilience of the Genoa San Giorgio Bridge using advanced analysis tools such as ABAQUS software, aiming to identify and address structural vulnerabilities that may have led to the tragic collapse of the bridge in 2018.
All Publications(4)
Seismic Hazard and Structural Vulnerability: A Study of Building Damage in the 2017 Kermanshah Earthquake
Hedayat, S., Ciampi, P., and Scarascia Mugnozza, G.
This paper analyzes the structural vulnerabilities and seismic resilience factors leading to building damage and collapse in the 2017 Kermanshah Earthquake, providing insights for improved structural design and seismic resilience strategies.
Advancing Infrastructure Resilience through Smart Monitoring: Insights from the Genoa Bridge Catastrophe
Hedayat, S., Ziarati, T., Ciampi, P., Giannini, L.M.
This research evaluates the structural integrity and resilience of the Genoa San Giorgio Bridge using advanced analysis tools such as ABAQUS software, aiming to identify and address structural vulnerabilities that may have led to the tragic collapse of the bridge in 2018.
Iran's Seismic Puzzle: Bridging Gaps in Earthquake Emergency Planning and Public Awareness for Risk Reduction
Ciampi, P., Giannini, L.M., Hedayat, S., Ziarati, T., and Scarascia Mugnozza, G.
This study designed surveys across various regions of Iran to gather data on public awareness of local hazard risks, utilizing QGIS and Excel to generate detailed maps and graphs integrating demographic, geographic, and hazard data. The research also modeled a machine learning system using XGBoost, Random Forests, and LSTM algorithms to predict potential earthquakes.
Smart Sustainability: The AI-Driven Future of Renewable Energy
Ziarati, T., Hedayat, S., Moscatiello, C., Sappa, G., and Manganelli, M.
This paper explores the integration of AI with renewable energy, notably in promoting sustainability in smart cities. The research emphasizes creative solutions, resulting in groundbreaking discoveries demonstrating AI's revolutionary potential in enhancing sustainable practices in the renewable energy environment.