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Author:

Jia, Ruixin (Jia, Ruixin.) | Long, Jinxi (Long, Jinxi.) | Dong, Fang (Dong, Fang.) | Liu, Yue (Liu, Yue.) | Zhu, Shangqing (Zhu, Shangqing.) | Cai, Gang (Cai, Gang.)

Indexed by:

Scopus SCIE

Abstract:

To address the shortcomings of dynamic evaluation methods for simply supported girder bridges under moving loads, as well as the inefficiencies of traditional dynamic load test measurements, which are time-consuming and labor-intensive, this paper proposes a dynamic evaluation method incorporating the contact surface effect of actual wheels. This method refines a vehicle-bridge coupling model and verifies its accuracy through dynamic displacement measurements using millimeter-wave radar, complemented by modal analysis and dynamic load testing. The method also accounts for the effects of bridge deck roughness, vehicle speed, and weight on the impact coefficient of the bridge, comparing these effects with those outlined in the current code. The practical application of this method demonstrates that millimeter-wave radar, as a novel non-contact testing approach, can accurately measure the complex vibrations of bridges. The multi-point contact model predicts vehicle-bridge interactions more precisely than the single-point contact model, particularly under poor bridge deck conditions, with discrepancies between the models reaching up to 9.59% on Class D bridge deck roughness. The current code, which calculates the impact coefficient considering only a single factor, may not accurately reflect the actual impact coefficient of the bridge. In this study, an impact coefficient regression formula is also derived using vehicle speed and bridge deck roughness as independent variables, offering a tool for estimating the impact coefficients of similar bridges.

Keyword:

Vehicle-bridge coupling Millimeter-wave radar Deflection Wheel contact model Impact coefficient

Author Community:

  • [ 1 ] [Jia, Ruixin]Beijing Univ Technol, State Key Lab Bridge Engn Safety & Resilience, Beijing 100124, Peoples R China
  • [ 2 ] [Long, Jinxi]Beijing Univ Technol, State Key Lab Bridge Engn Safety & Resilience, Beijing 100124, Peoples R China
  • [ 3 ] [Dong, Fang]Beijing Univ Technol, State Key Lab Bridge Engn Safety & Resilience, Beijing 100124, Peoples R China
  • [ 4 ] [Dong, Fang]Minist Emergency Management, Shenzhen Urban Publ Safety & Technol Inst, Key Lab Urban Safety Risk Monitoring & Early Warni, Shenzhen 518038, Peoples R China
  • [ 5 ] [Liu, Yue]Univ Sci & Technol Beijing, Res Inst Urbanizat & Urban Safety, Sch Civil & Resource Engn, Beijing 100083, Peoples R China
  • [ 6 ] [Zhu, Shangqing]Beijing Municipal Bridge Maintenance Management Gr, Beijing 100043, Peoples R China
  • [ 7 ] [Cai, Gang]Chongqing Qiaoan IoT Technol Co Ltd, Chongqing 401135, Peoples R China

Reprint Author's Address:

  • [Liu, Yue]Univ Sci & Technol Beijing, Res Inst Urbanizat & Urban Safety, Sch Civil & Resource Engn, Beijing 100083, Peoples R China

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Source :

SCIENTIFIC REPORTS

ISSN: 2045-2322

Year: 2025

Issue: 1

Volume: 15

4 . 6 0 0

JCR@2022

Cited Count:

WoS CC Cited Count:

SCOPUS Cited Count:

ESI Highly Cited Papers on the List: 0 Unfold All

WanFang Cited Count:

Chinese Cited Count:

30 Days PV: 2

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