Development of a Fatigue Life Assessment Model for Pairing Fatigue-Damage Prognoses with Bridge Management Systems

dc.contributor.advisorFu, Chung Cen_US
dc.contributor.authorSaad, Timothyen_US
dc.contributor.departmentCivil Engineeringen_US
dc.contributor.publisherDigital Repository at the University of Marylanden_US
dc.contributor.publisherUniversity of Maryland (College Park, Md.)en_US
dc.date.accessioned2015-07-17T05:31:06Z
dc.date.available2015-07-17T05:31:06Z
dc.date.issued2015en_US
dc.description.abstractFatigue damage is one of the primary safety concerns for steel bridges reaching the end of their design life. Currently, federal requirements mandate regular inspection of steel bridges for fatigue cracks with evaluative reporting to bridge management systems. The quality of the inspection is subjective and time delayed due to inspection cycles, which are scheduled for every two years. However, structural health monitoring (SHM) data collected between inspection-intervals can provide supplementary information on structural condition that ameliorates some drawbacks of current inspection methods. Through the use of SHM and finite element models, fatigue performance assessments can be utilized throughout the service life of fatigue sensitive bridge elements for mitigating fatigue damage and preventing sudden fatigue failure. These assessments will additionally be useful to inspectors when reporting bridge condition evaluations to bridge management systems. The main goal of this study is to develop a fatigue life assessment method used for determining the remaining useful life of steel bridges and to map these results to existing bridge management systems. In order to achieve this goal, the current practices and methodologies associated with fatigue life of bridge elements and the use of bridge management systems are investigated. For analyses of fatigue damage, the fatigue life is split into two different periods of analyses: a crack initiation period and crack growth period. In order to quantify the effects of fatigue damage, each period of the fatigue life is associated with a unique assessment method, an empirical correlation assessment and a fracture mechanics assessment. Structural health monitoring techniques are employed to monitor the behavior of the bridge components and bridge elements. These two assessment methods are combined to form a damage accumulation model to estimate the fatigue life. The proposed damage accumulation model uses the acquired data from structural health monitoring alongside finite element modeling to derive a damage prognosis of bridge elements. The damage prognosis attempts to forecast the structure's performance by measuring the cumulative fatigue damage, estimating future loads, and ultimately determining the remaining useful life of the bridge element. A technique for mapping the results of the damage prognosis into condition state classifications is proposed. The suitability and applicability of the proposed damage accumulation model is illustrated on an existing highway bridge. This bridge was selected as a good candidate for fatigue monitoring due to the average daily truck traffic and the identification of existing and active fatigue cracks. The application of the damage accumulation model is demonstrated and a damage prognosis is derived. Finally, the damage accumulation results are integrated with current condition state classifications used in bridge management systems.en_US
dc.identifierhttps://doi.org/10.13016/M24S7G
dc.identifier.urihttp://hdl.handle.net/1903/16776
dc.language.isoenen_US
dc.subject.pqcontrolledCivil engineeringen_US
dc.subject.pqcontrolledEngineeringen_US
dc.subject.pquncontrolledBridge Management Systemsen_US
dc.subject.pquncontrolledDamage Prognosisen_US
dc.subject.pquncontrolledFatigue Damageen_US
dc.subject.pquncontrolledFatigue Lifeen_US
dc.subject.pquncontrolledFractureen_US
dc.subject.pquncontrolledStructural Health Monitoringen_US
dc.titleDevelopment of a Fatigue Life Assessment Model for Pairing Fatigue-Damage Prognoses with Bridge Management Systemsen_US
dc.typeDissertationen_US

Files

Original bundle
Now showing 1 - 1 of 1
Loading...
Thumbnail Image
Name:
Saad_umd_0117E_16206.pdf
Size:
5.96 MB
Format:
Adobe Portable Document Format