چکیده مقاله
Despite rapid advances in structural monitoring, current approaches often lack integration between real time analytics, environmental sustainability, and stakeholder driven decision making—particularly in megacity contexts This study addresses this gap by introducing a human centric Digital Twin DT framework that fuses Structural Health Monitoring SHM with artificial intelligence AI , green project management principles, and sustainability metrics The proposed framework, tested on the Seyed Khandan Bridge in Tehran, integrates a high fidelity DT model with a hybrid CNN LSTM architecture for dynamic anomaly detection and predictive maintenance, supported by a network of 32 sensors capturing over 300 GB of multi modal data across 12 months Real time synchronization between physical sensors and digital simulations, enhanced through edge computing and low power IoT protocols, enabled high accuracy detection of structural anomalies, with CNN LSTM achieving a 92 4% accuracy and OC SVM reaching 87 5% confidence in classifying thermal and load induced stress events Modal analysis revealed frequency shifts of up to 0 3 Hz under high traffic and temperature variations, while Digital Twin simulations maintained over 93% correlation with observed structural responses Sustainability outcomes were substantial: carbon emissions dropped by 22%, energy use by 17%, and material consumption by 18%, accompanied by a 29% annual reduction in maintenance costs These findings demonstrate that AI enhanced DT frameworks can revolutionize infrastructure resilience and environmental performance in smart urban environments By integrating structural intelligence with eco conscious governance, this research establishes a scalable blueprint for resilient infrastructure management in high risk, data rich settings
کلیدواژهها
نویسندگان
آرش آپرناک
ایران - تهران - دانشگاه تهران
Rasoul Ghafari
PhD student in civil engineering majoring in engineering and construction management at the Islamic Azad University of Arak branch, Arak, Iran
زهرا علیرضائی
ایران - تهران - دانشگاه معماری و هنر پارس
Seyed Reza Samaei
Assistant professor, Faculty of Technical and Engineering, Science and Research Branch, Islamic Azad University, Tehran, Iran
محمد امین بالازاده
ایران - تهران - دانشگاه معماری و هنر پارس
علیرضا خلیلی
ایران - تهران - دانشگاه معماری و هنر پارس
شیوه ارجاع
Ghafari, Rasoul and Samaei, Seyed Reza,1404,A Human-Centric Digital Twin Framework For Structural Health Monitoring And Green Project Management: A Case Study On The Seyed Khandan Bridge In Tehran,18th International Conference on Mechanical, Construction Industrial & Civil Engineering
ارائهشده در
مجموعه مقالات هجدهمین کنفرانس بین المللی مکانیک، ساخت، صنایع و مهندسی عمران31 اردیبهشت 1404