Annual rehabilitation costs estimation for a bridge network

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• 作者：Yoojung Yoon ; Makarand Hastak
• 关键词：rehabilitation ; multi ; year planning ; bridge management ; time float ; rehabilitation costs ; annual cost estimation
• 刊名：KSCE Journal of Civil Engineering
• 出版年：2017
• 出版时间：January 2017
• 年：2017
• 卷：21
• 期：1
• 页码：27-36
• 全文大小：
• 刊物类别：Engineering
• 刊物主题：Civil Engineering; Industrial Pollution Prevention; Geotechnical Engineering & Applied Earth Sciences;
• 出版者：Korean Society of Civil Engineers
• ISSN：1976-3808
• 卷排序：21

文摘

The objective of this paper is to present an integrated multi-year rehabilitation planning model (IMRPM) for a bridge network. A multi-year capital program can provide an explicit, steady vision for financial and expenditure strategies as well as improve the efficiency of the allocation of limited resources. Estimating the precise annual rehabilitation needs for sound bridge management is essential to achieving the goals of a multi-year capital program; however, the current rehabilitation planning techniques tend to underestimate the annual rehabilitation costs by overlooking the potential rehabilitation needs which can arise by delaying of Maintenance/Repair (M/R) projects due to insufficient annual funding. The presented model integrates a multi-year rehabilitation capital program into an M/R program within the same multi-year period. The model engages a genetic algorithm for a project-level analysis process to identify M/R and rehabilitation projects over a defined multi-year analysis period (e.g., three, five, or ten years) for each M/R program and rehabilitation program. As a result of this process, the annual rehabilitation costs during a multi-year period initially can be estimated. Then, the initial annual rehabilitation costs can be finalized by including newly-identified rehabilitation needs, which are developed through the annual reanalysis process resulting from the delay of M/R projects in prior years. The annual reanalysis process considers the concept of time floats for M/R projects. The presented model is expected to be useful to efficiently control delayed M/R projects and to provide more reliable estimation for annual rehabilitation needs.