Consequences of Delayed Maintenance of Highway Assets

Chang, Carlos M.; Nazarian, Soheil; Vavrova, Marketa; Yapp, M T; Pierce, Linda M; Robert, W; Smith, Roger E.

doi:10.17226/24933

Cited by 6 publications

(6 citation statements)

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“…Performance models can incorporate these changes by analyzing condition survey data before and after the application of the treatment. The importance of modeling preventive maintenance and communicating the consequences of not applying treatments at the right time have been documented in previous studies by Chang et al ( 9 ).…”

Section: Current Study and Problemsmentioning

confidence: 85%

Developing Network Slurry Seal Performance Models Using Pavement Management Systems Data

Cheng

Smith

Tan

et al. 2022

Transportation Research Record

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As a popular pavement preservation treatment, a slurry seal is typically included in agencies’ maintenance and rehabilitation toolboxes, in decision trees of pavement management systems (PMS), or both. However, performance prediction models for slurry seals are mostly anecdotal or at undertaken at project level. The goal of this paper is to illustrate a method of developing data-driven performance models for slurry seal applications for use at a network level. A total of 537,891 pavement condition records were collected from 18 different agencies in the United States using the Metropolitan Transportation Commission’s PMS program, StreetSaver®. Of these records, 1,195 slurry seal projects met the requirements to be utilized in the development of slurry seal performance models. The development of slurry seal performance models includes grouping project-level modeling results into functional classes, and testing and validating the slurry seal performance models with test cases as well as on actual data produced by agencies. The performance models for slurry seals placed on an asphalt concrete pavement vary depending mainly on the existing pavement’s performance, the timing of the slurry seal application, the functional class, and surface type. The data-driven slurry seal models improved the accuracy of predicting slurry seal performance using PMS. The models could also be used to develop beneficial area curves, which are useful in estimating the cost-effectiveness of slurry seals constructed at various pavement condition index values and in identifying the optimal timings for slurry seal applications at a network level.

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Section: Current Study and Problemsmentioning

confidence: 85%

Developing Network Slurry Seal Performance Models Using Pavement Management Systems Data

Cheng

Smith

Tan

et al. 2022

Transportation Research Record

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“…Although there is an extensive body of civil engineering literature (e.g., Chang et al, 2017; National Research Council, 1990; Saha & Ksaibati, 2016), there are no solid theoretical and empirical models for understanding the determinants of asset maintenance spending, beyond technical factors, from a public administration or financial management perspective. This study is a first step toward building asset maintenance theory in public capital budgeting.…”

Section: Discussionmentioning

confidence: 99%

“…In public buildings, this can result in health and safety issues, power service loss, heating, ventilation, and air-conditioning system failure, higher energy cost, loss of assets, and so forth (National Research Council, 1990). For public roads, deferred routine maintenance results in poor pavement condition, reduced service life, and future increased costs for users and government, as well as safety, mobility, and environmental issues (Chang et al, 2017).…”

Section: Literature Reviewmentioning

confidence: 99%

Asset Maintenance Practices and Challenges in U.S. Counties

Kim

Ebdon

2020

Public Works Management & Policy

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This study explores capital asset maintenance practices and challenges in U.S. counties, which have been understudied in previous public administration research. We also compare the current practices with those found in the 2001 Government Performance Project (GPP) analysis. Interviews with 20 officials in 12 counties revealed six themes. Four of these are concerned with maintenance challenges: the economic environment, politics, human resources, and information systems. The other two themes relate to efforts that have been made by these counties to enhance maintenance through cost management and additional funding. Overall, we found that asset maintenance in these counties was negatively affected by the Great Recession, and that there is still a substantial level of unfunded maintenance, which is only slightly better than what was reported in the GPP, despite a recent focus on improvements.

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“…The life expectancy of UHPC is greater than conventional concrete, and it can reach up to 100 years (Farzad et al 2020). Based on the life expectancy of new concrete structural materials, the analysis period might be even extended over 100 years (Chang et al 2016). Previous studies have used 75 years to compare bridge systems with UHPC and conventional concrete (Dong 2018).…”

Section: Life Cycle Costmentioning

confidence: 99%

Modeling life expectancy and cost effectiveness for UHPC bridge retrofitting techniques

Hossain,

Chang

2024

ABEN

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Bridge components are subject to both structural loads and environmental stressors, rendering them susceptible to accelerated deterioration and potential collapse in the absence of effective maintenance and rehabilitation strategies. Moreover, the phenomenon of wet-dry cycling, coupled with elevated chloride concentrations prevalent in coastal regions, further expedites the degradation process of bridges, thereby escalating maintenance frequency and repair costs. In response to this challenge, the integration of innovative materials such as Ultra High-Performance Concrete (UHPC) is being explored for the development and implementation of maintenance and rehabilitation strategies. This study presents a comparative analysis between conventional methods and UHPC applications for bridge repairs, utilizing Life Cycle Cost Analysis (LCCA) to encompass both agency and user costs, and applies Monte Carlo simulation to account for the variability of the modeling factors. A practical case study illustrates the applicability of the LCCA methodology, revealing that the utilization of UHPC contributes to a reduction in the total life cycle cost for bridge maintenance and rehabilitation. Life expectancy, Average Daily Traffic (ADT), and the duration of construction activities during rehabilitation emerge as the most influential factors affecting life cycle costs. The main contributions of the study are the development of the life-expectancy model and step-by-step Life-Cycle Cost Analysis (LCCA) methodology. Findings from this study aim to identify cost-effective retrofitting techniques for maintaining bridges in a “State of Good Repair.”

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Consequences of Delayed Maintenance of Highway Assets

Cited by 6 publications

References 0 publications

Developing Network Slurry Seal Performance Models Using Pavement Management Systems Data

Developing Network Slurry Seal Performance Models Using Pavement Management Systems Data

Asset Maintenance Practices and Challenges in U.S. Counties

Modeling life expectancy and cost effectiveness for UHPC bridge retrofitting techniques

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