Condition assessment of multispan masonry arch bridges

Condition assessment of multispan masonry arch bridges This paper presents a reliability-based condition assessment procedure of multispan masonry arch bridges. Considering axle load as assessment criterion, safety margins (limit state functions) are introduced for each arch of the bridge. The introduced safety margins consist of two variables: provisional axle load (PAL) which is estimated using MEXE methods and actual axle load (AAL) which is estimated using weigh-in-motion measurements of the bridge. Both variables are assumed to follow log normal distribution. Then, failure probabilities of each arch which were estimated from statistical parameters of variables are combined to get the failure probability of the bridge using reliability bounds. The reliability index of the bridge is estimated from the failure probability. Bridge condition is predicted by comparing the reliability index with its acceptable reliability index. Further, when the statistical parameters behave as interval numbers, corresponding reliability index changes are discussed. The introduced assessment procedure is illustrated by a four span brick masonry arch bridge in Sri Lanka. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Bridge Structures IOS Press

Condition assessment of multispan masonry arch bridges

Loading next page...
 
/lp/ios-press/condition-assessment-of-multispan-masonry-arch-bridges-RPyxAyrfES
Publisher
IOS Press
Copyright
Copyright © 2010 by IOS Press, Inc
ISSN
1573-2487
eISSN
1744-8999
DOI
10.3233/BRS-2010-011
Publisher site
See Article on Publisher Site

Abstract

This paper presents a reliability-based condition assessment procedure of multispan masonry arch bridges. Considering axle load as assessment criterion, safety margins (limit state functions) are introduced for each arch of the bridge. The introduced safety margins consist of two variables: provisional axle load (PAL) which is estimated using MEXE methods and actual axle load (AAL) which is estimated using weigh-in-motion measurements of the bridge. Both variables are assumed to follow log normal distribution. Then, failure probabilities of each arch which were estimated from statistical parameters of variables are combined to get the failure probability of the bridge using reliability bounds. The reliability index of the bridge is estimated from the failure probability. Bridge condition is predicted by comparing the reliability index with its acceptable reliability index. Further, when the statistical parameters behave as interval numbers, corresponding reliability index changes are discussed. The introduced assessment procedure is illustrated by a four span brick masonry arch bridge in Sri Lanka.

Journal

Bridge StructuresIOS Press

Published: Jan 1, 2010

There are no references for this article.

You’re reading a free preview. Subscribe to read the entire article.


DeepDyve is your
personal research library

It’s your single place to instantly
discover and read the research
that matters to you.

Enjoy affordable access to
over 18 million articles from more than
15,000 peer-reviewed journals.

All for just $49/month

Explore the DeepDyve Library

Search

Query the DeepDyve database, plus search all of PubMed and Google Scholar seamlessly

Organize

Save any article or search result from DeepDyve, PubMed, and Google Scholar... all in one place.

Access

Get unlimited, online access to over 18 million full-text articles from more than 15,000 scientific journals.

Your journals are on DeepDyve

Read from thousands of the leading scholarly journals from SpringerNature, Elsevier, Wiley-Blackwell, Oxford University Press and more.

All the latest content is available, no embargo periods.

See the journals in your area

DeepDyve

Freelancer

DeepDyve

Pro

Price

FREE

$49/month
$360/year

Save searches from
Google Scholar,
PubMed

Create folders to
organize your research

Export folders, citations

Read DeepDyve articles

Abstract access only

Unlimited access to over
18 million full-text articles

Print

20 pages / month

PDF Discount

20% off