Graduation Semester and Year
Summer 2025
Language
English
Document Type
Dissertation
Degree Name
Doctor of Philosophy in Civil Engineering
Department
Civil Engineering
First Advisor
Dr. MD Sahadat Hossain
Second Advisor
Dr. Xinbao Yu
Third Advisor
Dr. Warda Ashraf
Fourth Advisor
Dr. Muhammad N. Huda
Abstract
The uncontrolled proliferation of plastic waste has emerged as a global environmental crisis, with high-density polyethylene (HDPE) constituting a substantial fraction of the waste stream due to its extensive use in packaging and its resistance to degradation. In parallel, asphalt pavements particularly in urban infrastructure such as parking lots experience accelerated deterioration from raveling, rutting, and cracking as a result of thermal cycling, repetitive loading, and inadequate drainage. These converging challenges present an opportunity for innovative, circular-economy-based sustainable pavement technologies that simultaneously improve surface durability and mitigate plastic waste accumulation.
This research investigates the full-scale implementation and monitoring of HDPE modified Superpave asphalt mix designs in two high-volume parking lots at the University of Texas at Arlington. Shredded HDPE plastics, sourced from C Square Polymer and processed into uniform 5–10 mm particles, were incorporated at 8% by binder weight via a dry mixing method compatible with existing drum mix plant infrastructure. Two Superpave gradations, SP-C and SP-D, were designed using TxDOT approved aggregates. Plant production was conducted with Bridgeport aggregates, yielding mixtures that satisfied volumetric specifications and demonstrated high resistance to rutting and satisfactory indirect tensile strength. Statistical process control analyses of nuclear density gauge measurements confirmed stable field compaction with no significant deviation from laboratory trial mix performance.
To evaluate in-service distress progression, surface images were collected monthly over a 17-month period from four zones in Lot F10 and eleven zones in Lot 49. A machine learning based raveling detection framework was developed, incorporating feature extraction using gray-level co-occurrence matrix (GLCM) texture descriptors and RGB color metrics. A stochastic gradient descent–logistic regression (SGD-LR) model achieved reliable classification of raveling and non-raveling zones. Measured deterioration rates indicated superior performance of Lot F10, with an average raveling progression slope of 0.8% compared to 1.13% for Lot 49. At the end of the monitoring period, raveling coverage was 4.5% for Lot F10 and 7.5% for Lot 49, both within the “low severity” classification in the TxDOT Pavement Management Information System.
Future deterioration trends were forecasted using ARIMA and Holt’s Linear Trend time-series models applied to August 2023–August 2024 data. Forecast accuracy metrics confirmed predictive reliability, with ARIMA exhibiting marginally superior performance. Predicted August 2025 raveling was 7.5–8.35% for Lot F10 and 12.5–13.5% for Lot 49, indicating that the HDPE-modified mixes maintain low-severity raveling levels beyond two years of service.
This study evaluated the feasibility of using recycled HDPE plastics in full-scale field applications on parking lots. Results show that HDPE can be incorporated without compromising performance specifications or requiring plant modifications, while diverting approximately 4 tons of plastic waste from landfills. The findings provide practical evidence for a scalable solution that addresses plastic waste reduction and enhances pavement durability.
Keywords
Plastic road, Waste plastic, Field implementation, Construction, Pavement, Rutting, Distress detection, Monitoring, Plant production, Sustainable infrastructure
Disciplines
Civil Engineering
License
This work is licensed under a Creative Commons Attribution 4.0 International License.
Recommended Citation
Faruk, Ishraq, "Implementation and Performance Evaluation of Plastic Road Mix Design in Parking Lot" (2025). Civil Engineering Dissertations. 523.
https://mavmatrix.uta.edu/civilengineering_dissertations/523