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  5. Dynamic Axle Force and Road Profile Identification Using a Moving Vehicle
 
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Dynamic Axle Force and Road Profile Identification Using a Moving Vehicle

Author(s)
McGetrick, P.  
Kim, Chul-Woo  
González, Arturo  
O'Brien, Eugene J.  
Uri
http://hdl.handle.net/10197/7073
Date Issued
2012-10-24
Date Available
2015-09-21T16:29:39Z
Abstract
The axle forces applied by a vehicle through its wheels are a critical part of the interaction between vehicles, pavements and bridges. Therefore, the minimisation of these forces is important in order to promote long pavement life spans and ensure that bridge loads are small. Moreover, as the road surface roughness affects the vehicle dynamic forces, the monitoring of pavements for highways and bridges is an important task. This paper presents a novel algorithm to identify these dynamic interaction forces which involves direct instrumentation of a vehicle with accelerometers. The ability of this approach to predict the pavement roughness is also presented. Moving force identification theory is applied to a vehicle model in theoretical simulations in order to obtain the interaction forces and pavement roughness from the measured accelerations. The method is tested for a range of bridge spans in simulations and the influence of road roughness level on the accuracy of the results is investigated. Finally, the challenge for the real-world problem is addressed in a laboratory experiment.
Type of Material
Conference Publication
Subjects

Moving force identifi...

Dynamic axle forces

Road profile heights

Vehicle acceleration ...

Language
English
Status of Item
Peer reviewed
Conference Details
The 25th KKCNN Symposium on Civil Engineering, Busan, Korea, 22 - 24 October, 2012
This item is made available under a Creative Commons License
https://creativecommons.org/licenses/by-nc-nd/3.0/ie/
File(s)
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Name

C139.pdf

Size

386.09 KB

Format

Adobe PDF

Checksum (MD5)

dbdd25aca226f2d070ed4a0fccffc424

Owning collection
Civil Engineering Research Collection

Item descriptive metadata is released under a CC-0 (public domain) license: https://creativecommons.org/public-domain/cc0/.
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