RFID technologies have advanced greatly and deployed successfully in many industry sectors in recent years.Construction industry could benefit from the applications of RFID technologies but as yet has not found suffic...RFID technologies have advanced greatly and deployed successfully in many industry sectors in recent years.Construction industry could benefit from the applications of RFID technologies but as yet has not found sufficient application areas.This project gives a comprehensive awareness of the RFID technologies,which focus on the investigation on the UK construction industry.The current status of RFID in construction and its potentials are specified in the analysis of questionnaires and case studies.Finally,basing on the investigations,some further tasks in developing RFID technologies are carried,including some recommendations,for the construction industry.展开更多
The large vibrations of stay cables pose significant challenges to the structural performance and safety of cable-stayed bridges. While magnetorheological dampers (MRDs) have emerged as an effective solution for suppr...The large vibrations of stay cables pose significant challenges to the structural performance and safety of cable-stayed bridges. While magnetorheological dampers (MRDs) have emerged as an effective solution for suppressing these vibrations, establishing accurate forward and inverse mapping models for MRDs to facilitate effective semi-active control of cable vibrations remains a formidable task. To address this issue, the current study proposes an innovative strategy that leverages Long Short-Term Memory (LSTM) neural networks for MRD modeling, thus enhancing semi-active control of stay cable vibrations. A high-fidelity data set accurately capturing the MRD dynamics is first generated by coupling finite element analysis and computational fluid dynamic approach. The obtained data set is then utilized for training LSTM-based forward and inverse mapping models of MRD. These LSTM models are subsequently integrated into dynamic computational models for effectively suppressing the stay cable vibrations, culminating in an innovative semi-active control strategy. The feasibility and superiority of the proposed strategy are demonstrated through comprehensive comparative analyses with existing passive, semi-active and active control methodologies involving sinusoidal load, Gaussian white noise load and rain–wind induced aerodynamic load scenarios, paving the way for novel solutions in semi-active vibration control of large-scale engineered structures.展开更多
文摘RFID technologies have advanced greatly and deployed successfully in many industry sectors in recent years.Construction industry could benefit from the applications of RFID technologies but as yet has not found sufficient application areas.This project gives a comprehensive awareness of the RFID technologies,which focus on the investigation on the UK construction industry.The current status of RFID in construction and its potentials are specified in the analysis of questionnaires and case studies.Finally,basing on the investigations,some further tasks in developing RFID technologies are carried,including some recommendations,for the construction industry.
基金support provided by the Institute of Bridge Engineering at the University at Buffalo has been invaluable in the completion of this work.
文摘The large vibrations of stay cables pose significant challenges to the structural performance and safety of cable-stayed bridges. While magnetorheological dampers (MRDs) have emerged as an effective solution for suppressing these vibrations, establishing accurate forward and inverse mapping models for MRDs to facilitate effective semi-active control of cable vibrations remains a formidable task. To address this issue, the current study proposes an innovative strategy that leverages Long Short-Term Memory (LSTM) neural networks for MRD modeling, thus enhancing semi-active control of stay cable vibrations. A high-fidelity data set accurately capturing the MRD dynamics is first generated by coupling finite element analysis and computational fluid dynamic approach. The obtained data set is then utilized for training LSTM-based forward and inverse mapping models of MRD. These LSTM models are subsequently integrated into dynamic computational models for effectively suppressing the stay cable vibrations, culminating in an innovative semi-active control strategy. The feasibility and superiority of the proposed strategy are demonstrated through comprehensive comparative analyses with existing passive, semi-active and active control methodologies involving sinusoidal load, Gaussian white noise load and rain–wind induced aerodynamic load scenarios, paving the way for novel solutions in semi-active vibration control of large-scale engineered structures.
