Reliability- and Cost-Oriented Optimal Bridge Maintenance Planning

Frangopol, Dan M.; Miyake, Masaru; Kong, Jung Sik; Gharaibeh, Emhaidy S.

doi:10.1061/40492(2000)21

Cited by 6 publications

(8 citation statements)

References 13 publications

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“…In this section, selected numerical examples describing reliability-based cost optimization of structural components and systems are briefly reviewed. Other examples of RLCCO can be found in various contributions such as Augusti et al [62], Frangopol and coworkers [63][64][65][66][67][68], Estes and Frangopol [69], and Kong and Frangopol [70].…”

Section: Examples In Civil Engineeringmentioning

confidence: 98%

Reliability-Based Optimization of Civil and Aerospace Structural Systems

Maute¹,

Frangopol²

2004

Engineering Design Reliability Handbook

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Section: Examples In Civil Engineeringmentioning

confidence: 98%

Reliability-Based Optimization of Civil and Aerospace Structural Systems

Maute¹,

Frangopol²

2004

Engineering Design Reliability Handbook

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“…Frangopol et al (2001) developed the basis for costeffective bridge management incorporating lifetime reliability and life cycle cost. Reliability and life cycle cost models are powerful tools for optimal bridge maintenance planning (Frangopol et al, 2004). Despite the advantages offered by the life cycle cost approach, there are certain difficulties in implementing this because of the complexities in predicting bridge deterioration and residual life; uncertainties in discount rate and inflation rate, to name a few (IRC, 2004).…”

Section: Literature Reviewmentioning

confidence: 99%

Prioritization of bridges for maintenance planning using data envelopment analysis

Wakchaure¹,

Jha

2011

Construction Management and Economics

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Resources-especially funds allotted-for the maintenance of bridges, are generally scanty. Thus, it becomes difficult to select bridges for maintenance from among several competing bridges to ensure their safety and serviceability to the desired level. A bridge health index is considered a reasonably accurate depiction of the condition of a bridge and hence is the basis for most of the decisions on fund allocation. However, it still remains to be seen whether such a decision-making tool results in an efficient fund allocation. From data collected on Indian bridges, it is observed that fund allocation based on bridge condition is not always judicious. Rather, a number of factors affect the final decision on fund allocation. Hence, an alternative approach of data envelopment analysis (DEA) has been used for scoring the efficiency of 14 bridges selected for the study. Depending on the availability of data, this method can take into account other factors besides the bridge health index that influence decisions on maintenance planning. The variables selected for the DEA are: bridge health index, deck area of the bridge, maintenance cost of the bridge, and the age of the bridge. The allocation of funds for the maintenance of bridges based on DEA has proved to be comparatively more efficient. This has been illustrated with the help of a numerical example. The proposed method would enable bridge authorities to formulate better strategies for planning and executing bridge maintenance activities in a cost-effective manner.

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“…The objective functions representing the target requirements for the optimal design are generally related to the cost of the structure (Frangopol 1999), including the initial construction cost and the costs of maintenance, repair and demolition, as well as to additional structural performance indicators (Furuta et al 2006, 2011, Frangopol & Liu 2007) such as safety, robustness, and redundancy, among others. The design variables may include the geometrical and mechanical properties of the structural system (Frangopol et al 1997b, Estes & Frangopol 2001b, Biondini & Marchiondelli 2008, Biondini & Frangopol 2009, Kwon & Frangopol 2010, 2011, as well as the time and reliability increments of maintenance and repair interventions (Frangopol et al 2002, Kong & Frangopol 2003b, Okasha and Frangopol 2009, Neves & Frangopol 2006a, 2006b.…”

Section: Life-cycle Reliability-based Designmentioning

confidence: 99%

“…In this way, based on a comparison among the costs of maintenance associated with different scenarios, the optimum repair and maintenance strategies could finally be selected. However, a rational approach to maintenance planning need to consider trade-off optimal solutions able to optimize the effects of several cost components, including the initial construction cost and the costs of maintenance, repair and failure (Frangopol et al 2002, Kong & Frangopol 2003b, Liu & Frangopol 2004.…”

Section: Life-cycle Assessment and Designmentioning

confidence: 99%

“…Significant advances have been accomplished in the fields of modeling, analysis, maintenance, repair, and design of deteriorating civil engineering systems (Frangopol 1999, Enright & Frangopol 1998a, 1998b, Frangopol & Furuta 2001, Frangopol et al 2004a, 2004b, 2008, Ellingwood 2005, 2011, Estes & Frangopol 2001a, Nowak & Frangopol 2005, Cho et al 2007, Biondini & Frangopol 2008a, Biondini 2009, Chen et al 2010, Furuta et al 2010, Biondini & Frangopol 2011, Strauss et al 2013, Frangopol & Biondini 2013 and novel approaches to lifecycle reliability assessment, maintenance planning, and optimal design of structural systems have been proposed (Mori & Ellingwood 1994a, 1994b, Frangopol 1995, Frangopol et al 1997a, 1997b, 2002, Fu & Frangopol 1999a, 1999b, Frangopol & Das 1999, Furuta et al 2004, Ciampoli & Ellingwood 2002, Enright & Frangopol 1999a, 1999b, Estes & Frangopol 1999, Frangopol & Maute 2003, Kong & Frangopol 2003b, Biondini et al 2004, 2006a, 2006b, 2008, 2011, Fr...…”

Section: Introductionmentioning

confidence: 96%

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Life-Cycle Performance of Structural Systems under Uncertainty

Biondini

Frangopol

2014

Structures Congress 2014

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The significant advances recently accomplished in the fields of modeling, analysis, and design of deteriorating civil engineering systems, are far from being explicitly addressed in design codes and effectively implemented into practice. There is, therefore, a strong need to promote further research in the field of life-cycle performance of structural systems under uncertainty and to fill the gap between theory and practice by incorporating life-cycle concepts in structural design codes and standards. An effort is currently ongoing within SEI/ASCE to meet this need. This paper is part of this effort and it is aimed at presenting a short overview of the main principles, concepts, methods and strategies associated with life-cycle assessment and design of deteriorating structural systems under uncertainty.

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Reliability- and Cost-Oriented Optimal Bridge Maintenance Planning

Cited by 6 publications

References 13 publications

Reliability-Based Optimization of Civil and Aerospace Structural Systems

Reliability-Based Optimization of Civil and Aerospace Structural Systems

Prioritization of bridges for maintenance planning using data envelopment analysis

Life-Cycle Performance of Structural Systems under Uncertainty

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