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Highway filter drains: precursors for maintenance management

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posted on 2015-11-17, 11:32 authored by Theo Stylianides, Matthew FrostMatthew Frost, Paul FlemingPaul Fleming, Ali El-Jaber, Mark Mageean, Andrew Huetson, Tomasz Klimczak
This paper conceptualises and presents a number of asset management building blocks required to establish holistic management for highway filter drains in the UK roads network. This is accomplished by evaluating current maintenance and management thinking and by identifying how existing strategies are lacking and potentially unsustainable. A condition assessment regime is hence described, tied to a measure of filter drain level of service (drainability) and an asset-specific ageing/renewal model that adopts six discreet condition bands is proposed. For this model to hold true, the Markov process is assumed to represent cumulative damage in a network. Drawing from relevant asset management concepts, a decision support tool to inform and optimise managerial decisions in respect to maintenance planning and resources allocation is also described.

Funding

The research work described in this paper has been funded by the Engineering and Physical Sciences Research Council (EPSRC), Transport Scotland (TS), Connect Roads, Balfour Beatty and PTS.

History

School

  • Architecture, Building and Civil Engineering

Published in

Infrastructure Asset Management

Volume

2

Issue

4

Pages

159-172

Citation

STYLIANIDES, T. ...et al., 2015. Highway filter drains: precursors for maintenance management. UK, Infrastructure Asset Management, 2 (4), pp.159-172

Publisher

© ICE publishing

Version

  • VoR (Version of Record)

Publisher statement

This work is made available according to the conditions of the Creative Commons Attribution 4.0(CC BY 4.0) licence. Full details of this licence are available at: https://creativecommons.org/licenses/by/4.0/

Publication date

2015-11-26

Copyright date

2015

Notes

This is an Open Access article published by ICE and distributed under the terms of the Creative Commons Attribution Licence, https://creativecommons.org/licenses/by/4.0/.

ISSN

2053-0242

eISSN

2053-0250

Language

  • en

Location

UK

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