東華大學圖書館 |

語系: 繁體中文

說明(常見問題)

回圖書館首頁

手機版館藏查詢

登入

回首頁

切換: 標籤 | MARC模式 | ISBD

Bridge network lifetime maintenance ...

Liu, Ming.

FindBook

Google Book

Amazon

博客來

Bridge network lifetime maintenance optimization under uncertainty.

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Bridge network lifetime maintenance optimization under uncertainty./
作者:	Liu, Ming.
面頁冊數:	304 p.
附註:	Source: Dissertation Abstracts International, Volume: 67-05, Section: B, page: 2725.
Contained By:	Dissertation Abstracts International67-05B.
標題:	Engineering, Civil. -
電子資源:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=3219201
ISBN:	9780542715471

Bridge network lifetime maintenance optimization under uncertainty.
Liu, Ming.

Bridge network lifetime maintenance optimization under uncertainty. - 304 p.

Source: Dissertation Abstracts International, Volume: 67-05, Section: B, page: 2725.

Thesis (Ph.D.)--University of Colorado at Boulder, 2006.

Bridge maintenance planning (BMP) currently faces a great challenge to balance limited funds and increasing needs for maintenance, repair and rehabilitation due to aging and deterioration of existing bridges. Prioritization of available maintenance resources to keep acceptable condition and safety levels while minimizing life-cycle costs of a bridge network will be the core value of future bridge management systems (BMS). This provides an excellent opportunity for applying advanced mathematical optimization techniques in BMP. As a matter of fact, BMP can be considered as a time-dependent optimization problem, where maintenance decisions and actions are made and taken moment by moment during the entire service lifetime of a bridge, based on possible future consequences on safety, economic and political impacts. In general, BMP has multiple objectives that need to be optimized in the views of multiple decision makers, with uncertain consequences of maintenance decisions and actions. This can be solved by using stochastic dynamic programming for multi-objective optimization problems associated with BMP.

ISBN: 9780542715471Subjects--Topical Terms:

783781
Engineering, Civil.

Bridge network lifetime maintenance optimization under uncertainty.
LDR:03679nmm 2200277 4500 001 1829880
005 20070323103008.5
008 130610s2006 eng d
020 $a 9780542715471
035 $a (UnM)AAI3219201
035 $a AAI3219201
040 $a UnM $c UnM
100 1 $a Liu, Ming. $3 1296862
245 1 0 $a Bridge network lifetime maintenance optimization under uncertainty.
300 $a 304 p.
500 $a Source: Dissertation Abstracts International, Volume: 67-05, Section: B, page: 2725.
500 $a Adviser: Dan M. Frangopol.
502 $a Thesis (Ph.D.)--University of Colorado at Boulder, 2006.
520 $a Bridge maintenance planning (BMP) currently faces a great challenge to balance limited funds and increasing needs for maintenance, repair and rehabilitation due to aging and deterioration of existing bridges. Prioritization of available maintenance resources to keep acceptable condition and safety levels while minimizing life-cycle costs of a bridge network will be the core value of future bridge management systems (BMS). This provides an excellent opportunity for applying advanced mathematical optimization techniques in BMP. As a matter of fact, BMP can be considered as a time-dependent optimization problem, where maintenance decisions and actions are made and taken moment by moment during the entire service lifetime of a bridge, based on possible future consequences on safety, economic and political impacts. In general, BMP has multiple objectives that need to be optimized in the views of multiple decision makers, with uncertain consequences of maintenance decisions and actions. This can be solved by using stochastic dynamic programming for multi-objective optimization problems associated with BMP.
520 $a This study reviews recent developments and applications of structural reliability and life-cycle costs analysis in bridge engineering, and develops a comprehensive mathematical model for bridge network performance evaluation, based on network connectivity, user's satisfaction, and performance of critical bridges in a highway network. This provides important weight assignments for multi-objective bridge network lifetime maintenance optimizations. BMP criteria are established in accordance with bridge condition and safety profiles, and both preventive and essential maintenance actions are studied, along with maintenance costs. Individual bridge maintenance planning is addressed by using stochastic dynamic programming (DP), importance ranking and multi-objective optimization methods. Finally, the multi-objective optimization in bridge network maintenance planning that involves a group of bridges with various remaining service lifetimes and different importance factors to the bridge network is solved by using a two-phase stochastic DP procedure. Phase I consists in identifying the optimal maintenance plans for individual bridges that have the minimum life-cycle maintenance costs, meanwhile satisfying both condition and safety requirements for a targeted service lifetime. This can be solved by using a specific DP optimization algorithm along with Monte Carlo simulations. Phase II is to rationally allocate annual maintenance budgets in such a way that the identified optimal maintenance plans can be satisfied for as many bridges as possible by using a binary integer programming algorithm. For this purpose, the computer program BMS-DP has been developed.
590 $a School code: 0051.
650 4 $a Engineering, Civil. $3 783781
690 $a 0543
710 2 0 $a University of Colorado at Boulder. $3 1019435
773 0 $t Dissertation Abstracts International $g 67-05B.
790 1 0 $a Frangopol, Dan M., $e advisor
790 $a 0051
791 $a Ph.D.
792 $a 2006
856 4 0 $u http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=3219201