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Bingham, E, Gibson, G E and Asmar, M E (2018) Measuring User Perceptions of Popular Transportation Project Delivery Methods Using Least Significant Difference Intervals and Multiple Range Tests. Journal of Construction Engineering and Management, 144(06).
Chang, C and Yu, S (2018) Three-Variance Approach for Updating Earned Value Management. Journal of Construction Engineering and Management, 144(06).
de la Garza, J M and Pishdad-Bozorgi, P (2018) Workflow Process Model for Flash Track Projects. Journal of Construction Engineering and Management, 144(06).
El-adaway, I H, Abotaleb, I S, Eid, M S, May, S, Netherton, L and Vest, J (2018) Contract administration guidelines for public infrastructure projects in the United States and Saudi Arabia: comparative analysis approach. Journal of Construction Engineering and Management, 144(06), 04018031.
Guo, H, Yu, Y, Ding, Q and Skitmore, M (2018) Image-and-Skeleton-Based Parameterized Approach to Real-Time Identification of Construction Workers’ Unsafe Behaviors. Journal of Construction Engineering and Management, 144(06).
Ham, N, Moon, S, Kim, J and Kim, J (2018) Economic Analysis of Design Errors in BIM-Based High-Rise Construction Projects: Case Study of Haeundae L Project. Journal of Construction Engineering and Management, 144(06).
Han, Y, Li, Y, Taylor, J E and Zhong, J (2018) Characteristics and Evolution of Innovative Collaboration Networks in Architecture, Engineering, and Construction: Study of National Prize-Winning Projects in China. Journal of Construction Engineering and Management, 144(06).
Kosonen, H K and Kim, A A (2018) Mental Model Approach to Wastewater Treatment Plant Project Delivery during Emergency Response. Journal of Construction Engineering and Management, 144(06).
Kwon, N, Song, K, Lee, H, Kim, J and Park, M (2018) Construction Noise Risk Assessment Model Focusing on Construction Equipment. Journal of Construction Engineering and Management, 144(06).
Liu, D, Lu, W and Niu, Y (2018) Extended Technology-Acceptance Model to Make Smart Construction Systems Successful. Journal of Construction Engineering and Management, 144(06).
Liu, X, Song, Y, Yi, W, Wang, X and Zhu, J (2018) Comparing the Random Forest with the Generalized Additive Model to Evaluate the Impacts of Outdoor Ambient Environmental Factors on Scaffolding Construction Productivity. Journal of Construction Engineering and Management, 144(06).
Liu, Z, Wang, H and Li, H (2018) Model of Equipment Sharing between Contractors on Construction Projects. Journal of Construction Engineering and Management, 144(06).
Nzabonimpa, J D and Hong, W (2018) Novel Precast Erection Method of Interlocking Mechanical Joints Using Couplers. Journal of Construction Engineering and Management, 144(06).
Rahimi, Y, Tavakkoli-Moghaddam, R, Iranmanesh, S H and Vaez-Alaei, M (2018) Hybrid Approach to Construction Project Risk Management with Simultaneous FMEA/ISO 31000/Evolutionary Algorithms: Empirical Optimization Study. Journal of Construction Engineering and Management, 144(06).
Raoufi, M and Fayek, A R (2018) Key Moderators of the Relationship between Construction Crew Motivation and Performance. Journal of Construction Engineering and Management, 144(06).
Shaofeng, L, Jincai, F, Pinghua, Z and Xiang, L (2018) Stability Analysis of Two Parallel Closely Spaced Tunnels Based on Convergence–Confinement Principle. Journal of Construction Engineering and Management, 144(06).
Sherratt, F, Welfare, K, Hallowell, M and Hoque Tania, M (2018) Legalized Recreational Marijuana: Safety, Ethical, and Legal Perceptions of the Workforce. Journal of Construction Engineering and Management, 144(06).
Vaux, J S and Kirk, W M (2018) Relationship Conflict in Construction Management: Performance and Productivity Problem. Journal of Construction Engineering and Management, 144(06).
Walters, J P, Kaminsky, J and Huepe, C (2018) Factors Influencing Household Solar Adoption in Santiago, Chile. Journal of Construction Engineering and Management, 144(06).
Yoon, S, Kang, K, Yoon, Y, Hastak, M and Ji, R (2018) Systematic Decision-Making Process for Composite Pavement Maintenance. Journal of Construction Engineering and Management, 144(06).
- Type: Journal Article
- Keywords: Composite pavement; Reflective cracking; Multinomial logit model; Principal component analysis;
- ISBN/ISSN: 0733-9364
- URL: https://doi.org/10.1061/(ASCE)CO.1943-7862.0001447
- Abstract:
The assessment of pavement condition rating (PCR) for hot mix asphalt (HMA) surfaces and exposed portland cement concrete (PCC) in composite pavements is an important component of the decision-making process for treating reflective cracking. Visual inspections such as PCR or falling weight deflectometer (FWD) have been conducted as current practices for reflective cracking treatment. However, these evaluation methods are not able to identify the severity of cracking in the underlying PCC slab. Furthermore, additional evaluation methods, such as coring tests, and milling operations could involve various types of costs including time delay costs, traffic control costs, and labor costs. Because of such extensive cost requirements, field engineers often tend to rely solely on visual inspection of the HMA surface without performing actual milling operations. Therefore a systematic decision-making process is needed to select appropriate maintenance treatments for reflective cracking in composite pavements. In response to this need, this research proposes a framework for composite pavement maintenance decision making that consists of three modules: (1) field evaluations to assess the condition of the pavement at the joint, (2) development of a PCC pavement condition prediction model to determine the severity of PCC cracking at the joint in a composite pavement, and (3) a treatment selection table to help determine a possible mitigation strategy for the treatment of each reflective crack type. A case study is conducted to validate the proposed prediction model, with the results showing 0.77 accuracy. Therefore the proposed systematic decision-making process is able to provide field engineers with a more accurate treatment selection process for reflective cracking in composite pavements than is currently available. Furthermore, the proposed process can reduce maintenance costs by simplifying field test evaluation methods and alleviating the need for milling the HMA surfaces.
Yu, J and Leung, M (2018) Structural Stakeholder Model in Public Engagement for Construction Development Projects. Journal of Construction Engineering and Management, 144(06).
Zhao, T, Liu, W, Zhang, L and Zhou, W (2018) Retracted: Cluster Analysis of Risk Factors from Near-Miss and Accident Reports in Tunneling Excavation. Journal of Construction Engineering and Management, 144(06).