Methodology for Probabilistic Modeling of Highway Bridge Infrastructure Condition: Accounting for Improvement Effectiveness and Incorporating Random Effects

Saeed, Tariq Usman; Qiao, Yanqiang; Chen, Sikai; Gkritza, Konstantina; Labi, Samuel

doi:10.1061/(asce)is.1943-555x.0000389

Cited by 52 publications

(11 citation statements)

References 30 publications

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“…• Empirical modelling approaches (Agrawal and Kawaguchi 2009;Lavrenz et al 2015;Moomen et al 2016;Saeed et al 2017a;Saeed et al 2017b;Tolliver and Pan 2011;Van Noortwijk and Klatter 2004;Veshosky et al 1994;Zhang et al 2003) • Discrete choice models (Saeed et al 2016;Saeed et al 2017c).…”

Section: Introductionmentioning

confidence: 99%

Polya urn model-based performance assessment of PSC bridges: prestress loss consideration

Rao

Anoop

2022

ABEN

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A methodology for performance assessment of prestressed concrete (PSC) girder bridge system, based on strain monitoring in limited number of girders, is proposed in this paper. The methodology uses Polya urn model for determining probabilities of the bridge system being in different condition states with respect to loss of prestress. Performability measure is used for describing the performance of the bridge system. A condition state is assigned for the bridge system from a predefined set of condition states. The time for detailed inspection is determined as the time instant at which the performability of the bridge system becomes less than the target/required performance level. Performance assessment of a bridge system with one hundred PSC girders is considered for illustrating the methodology. The obtained values of condition state probabilities and performability for the considered scenarios (i.e., different number of monitored girders with prestress loss exceeding the allowable value) suggest that the methodology is able to consider the value of available information.

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Section: Introductionmentioning

confidence: 99%

Polya urn model-based performance assessment of PSC bridges: prestress loss consideration

Rao

Anoop

2022

ABEN

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“…Since the collapse of a bridge leads to a major disaster, extensive studies have been conducted on the life cycle cost, management system, safety, and deterioration characteristics of bridges [6,[9][10][11][12][13][14][15][16][17][18][19][20][21]. Internationally, the condition of bridges is mostly expressed based on grades, which are generally divided into three to nine grades [6].…”

Section: Introductionmentioning

confidence: 99%

“…Major variables affecting the life expectancy of a bridge are classified into: (i) design factors such as materials (concrete, steel, etc. ), design load, the length and number of spans, and bridge width; (ii) operational factors including traffic volume and service life; and (iii) climate factors including precipitation, freeze index, and so on [6,[15][16][17][18]. These explanatory variables result in deviations of the life expectancy of approximately 10-30 years [15].…”

Section: Introductionmentioning

confidence: 99%

“…Despite the advantages and extensive utilizations, it has been noted that there is a limit to building realistic deterioration models due to the important property of the Markov process characterized as "Memorylessness" [18]. In addition, most of the existing studies applying the Markov chain apply the assumption that condition transition occurs only in one level lower (i.e., between two adjacent grades), and have a limitation in that it does not reflect explanatory variables in estimating the life expectancy and deriving the Markov Transition Probability (MTP) [13].…”

Section: Introductionmentioning

confidence: 99%

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Heterogeneous Deterioration Process and Risk of Deficiencies of Aging Bridges for Transportation Asset Management

Han

2021

Sustainability

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The government of the Republic of Korea has set the minimum service level of bridges as Grade B and has defined the risk management level as higher than 95 percent. To achieve this goal, it is necessary to understand the deterioration process and risk of deficiencies for bridges, and these characteristics should be reflected in the management strategy and budget investment plan. To this end, this study developed deterioration models according to the bridge ages to define heterogeneous deterioration characteristics of aging bridges. To build the deterioration models, this study collected and processed bridge diagnosis data for 10 years, and a Bayesian Markov mixed hazard model was introduced. Analysis results showed that the life expectancy of the aging bridges over 30 years was remarkably short, 1/3 of the average life expectancy of the network, and the probability of failure was seven times higher than that of new bridges within 10 years after completion. In addition, the optimal maintenance demand that satisfies a risk management level of 95 percent illustrated that 44.7 percent of the bridges at Grade C should be continuously maintained annually. The results showed that it is urgent to prepare a preemptive response strategy and budget-securing plan for aging bridges, which will rapidly increase to 39% in the next 10 years and 76% in 20 years.

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“…The imported NBI data contains structure numbers, condition states (deck, superstructure, substructure, channel, culvert), bridge deck areas, state codes, and locations codes, among several other data. Included in the NBI data are all bridges with a span of 20 feet or more (GPO 2004 (Gheitasi and Harris 2014), and probabilistic approaches to assist the bridge management process (Biondini et al 2014) (Saeed et al 2017). Also, uncertainties were added to no maintenance deterioration and under maintenance deterioration processes and bridge performances (Liu and Frangopol 2004).…”

Section: Data Processingmentioning

confidence: 99%

Performance-based Assessment of Bridge Preservation

Boy¹

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Bridges all over the world are facing different problems in case of deterioration, preservation, and the cost associated with it. During the life-cycle of a bridge, diverse maintenance and repair has to be done. Depending on the geographic location, weather deterioration, traffic impacts and other hazards need to be considered. Studying the preservation strategies of the present, with focus of Rhode Island, possible improvements could be identified. Therefore, performance measures for bridge preservation are proposed. After a description of bridge deterioration for different bridge materials, bridge preservation is discussed in detail. Before the process of analyzing National Bridge Inventory (NBI) data and authoring performance measures is presented, preservation costs are described. First, the data provided needs to be processed; it is filtered to give an overview of the current state of Rhode Island bridges, using R as supporting program. Afterwards, authoring performance measures for bridge preservation is ensured by merging both NBI data and NBI element data, defining National Bridge Elements (NBEs) and Bridge Management Elements (BMEs) and putting them into relationship. Further analysis of performance measures is provided by using equations to gain cost and time information, as well as compare preservation and replacement. Finally, a preservation program is proposed which uses funding data and time intervals to enable different scenarios. The results emphasizing that preservation of bridges is more cost effective then replacement and that bridge preservation in Rhode Island is needed. A total of 27.29% of Rhode Island bridge area is at-risk to deteriorate to poor condition comparing all NBEs with all BMEs. The number of at-risk bridges with bridge joints could be reduced up to 94% with the proposed preservation program. iii ACKNOWLEDGMENTS I would like to take this opportunity to thank my major advisor, Prof. Mayrai Gindy for her guidance throughout my time at the University of Rhode Island. She always gave me good advice regarding my academic career and was supportive in any way a student can think of. I would also like to thank my committee members, Prof. George Tsiatas and Prof. Farhad Atash for their time and commitment, as well as my chair of the defense Prof. Jyh-Hone Wang. Additionally, I want to thank the German Academic Exchange Service (DAAD) who made my stay at University of Rhode Island possible through an extensive scholarship. I am very grateful for this opportunity and wish also to thank everyone involved in the international engineering program, starting off with the program coordinator Dr.-Ing. Jörg Gattermann. Finally, I would like to thank my family for their great support throughout my year abroad. iv

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Methodology for Probabilistic Modeling of Highway Bridge Infrastructure Condition: Accounting for Improvement Effectiveness and Incorporating Random Effects

Cited by 52 publications

References 30 publications

Polya urn model-based performance assessment of PSC bridges: prestress loss consideration

Polya urn model-based performance assessment of PSC bridges: prestress loss consideration

Heterogeneous Deterioration Process and Risk of Deficiencies of Aging Bridges for Transportation Asset Management

Performance-based Assessment of Bridge Preservation

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