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Title:

A Multisource-Data-Based Condition Assessment Model for Large Span Suspension Bridges

Accession Number:

01626659

Record Type:

Component

Abstract:

In the field of bridge condition assessment, previous research was concentrated in short to medium span reinforced concrete bridges, while relatively little attention has been given to large span, steel bridges. Moreover, those existing assessment models were based on a single source data, which cannot reflect comprehensive condition of bridges. This paper presents a multisource-data-based condition assessment model for large span steel suspension bridges. The presented model can make full use of existing data and reflect comprehensive condition of bridges. What’s more, data from different source can support each other. The condition assessment model should meet the five rules: comprehensiveness, simplicity, independence, objectivity and examinability. A questionnaire survey was conducted to collect and document experts’ detailed experience with condition assessment for large span bridges. Then, expert meetings were held to discuss the rationality and practicability of the assessment model, especially the examinability of the proposed indicators. Finally, the nationwide experts accepted the ultimate assessment model after several modifications. The assessment model consists of upper framework and bottom indicators. The upper framework is built by analyzing the components of suspension bridges in Jiangsu. The bottom indicators are determined by historical visual inspection data, special inspection data, nondestructive examination (NDE) data and structure health monitoring (SHM) data. This bridge assessment model is going to be applied to maintenance and management of the three large span suspension bridges in Jiangsu, which are Jiangyin Bridge, Runyang South Bridge and Taizhou Bridge.

Supplemental Notes:

This paper was sponsored by TRB committee AHD30 Standing Committee on Structures Maintenance.

Monograph Accession #:

01618707

Report/Paper Numbers:

17-02878

Language:

English

Corporate Authors:

Transportation Research Board

500 Fifth Street, NW
Washington, DC 20001 United States

Authors:

Xiang, Xu
Qiao, Huang
Yuan, Ren
Xiaoling, Liu
Ruonan, Chen

Pagination:

18p

Publication Date:

2017

Conference:

Transportation Research Board 96th Annual Meeting

Location: Washington DC, United States
Date: 2017-1-8 to 2017-1-12
Sponsors: Transportation Research Board

Media Type:

Digital/other

Features:

Figures; Photos; References; Tables

Geographic Terms:

Jiangsu Province (China)

Subject Areas:

Bridges and other structures; Data and Information Technology; Highways; Maintenance and Preservation

Source Data:

Transportation Research Board Annual Meeting 2017 Paper #17-02878

Files:

TRIS, TRB, ATRI

Created Date:

Dec 8 2016 11:04AM