WeChat Mini Program
Old Version Features

Enhancing the Flutter Performance of Long-Span Bridges Through Using Inerter-Based Dynamic Vibration Absorbers

ENGINEERING STRUCTURES(2025)

Beijing Univ Technol

Cited 0|Views8
Abstract
With the ever-growing of span length, the safety factor of flutter for long-span bridges, i.e., the ratio between the critical flutter wind velocity and flutter checking velocity, has become increasingly less. Utilizing mechanical devices as a supplemental measure to the aerodynamic measures has become a solution for enhancing the flutter performance of long-span bridges. In this study, the inerter-based dynamic vibration absorbers (IDVAs), featured by light-weight and broadband properties, are employed to improve the flutter performance of long-span bridges and are compared with conventional tuned mass damper (TMD). A numerical optimal design method for the bridge-IDVA systems under flutter is first proposed. Then, the performance of the control systems subjected to the uncertainty of flutter derivatives as well as hard and soft types of flutter is systematically investigated. Compared with TMD, utilizing IDVAs can not only increase the critical flutter wind velocity, but also reduce the failure probability after considering the uncertainty of flutter derivatives. When the flutter of a bridge is characterized by soft type, the advantages of the IDVAs will become more significant. The findings in this research can contribute to the flutter control of long-span bridges and promote the application studies of inerter-based devices.
More
Translated text
Key words
Long-span bridges,Flutter control,Inerter-based dynamic vibration absorbers,Optimal design,Dynamic and sensitivity analysis
求助PDF
上传PDF
Bibtex
AI Read Science
AI Summary
AI Summary is the key point extracted automatically understanding the full text of the paper, including the background, methods, results, conclusions, icons and other key content, so that you can get the outline of the paper at a glance.
Example
Background
Key content
Introduction
Methods
Results
Related work
Fund
Key content
  • Pretraining has recently greatly promoted the development of natural language processing (NLP)
  • We show that M6 outperforms the baselines in multimodal downstream tasks, and the large M6 with 10 parameters can reach a better performance
  • We propose a method called M6 that is able to process information of multiple modalities and perform both single-modal and cross-modal understanding and generation
  • The model is scaled to large model with 10 billion parameters with sophisticated deployment, and the 10 -parameter M6-large is the largest pretrained model in Chinese
  • Experimental results show that our proposed M6 outperforms the baseline in a number of downstream tasks concerning both single modality and multiple modalities We will continue the pretraining of extremely large models by increasing data to explore the limit of its performance
Upload PDF to Generate Summary
Must-Reading Tree
Example
Generate MRT to find the research sequence of this paper
Data Disclaimer
The page data are from open Internet sources, cooperative publishers and automatic analysis results through AI technology. We do not make any commitments and guarantees for the validity, accuracy, correctness, reliability, completeness and timeliness of the page data. If you have any questions, please contact us by email: report@aminer.cn
Chat Paper
Summary is being generated by the instructions you defined