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Gravel Road Performance Enhancements
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2025-03-01
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[PDF-17.71 MB]
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Edition:Final Report Research July 1, 2022 - May 31, 2025
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Abstract:Nearly 30% of roads in the U.S. are unpaved, significantly impacting rural connectivity with Nebraska alone having approximately 75% unpaved roads. This study systematically evaluates local materials to improve gravel road performance, reduce maintenance frequency, and decrease financial burdens on counties. Survey responses revealed that nearly 70% of counties follow NDOT specifications for gravel road design, while more than 90% lack knowledge of local material quality. The most common distresses identified were raveling, loss of crown, dust, and improper drainage. These findings indicate that construction practices rely heavily on experience, rather than systematic design, highlighting the need for a performance-based approach. To address this, commonly used gravel road materials were identified. Seventeen different materials—13 surface materials and 4 subgrade soils—were collected from four counties for laboratory evaluation. Comprehensive testing assessed index properties, while repeated triaxial tests determined the mechanical behavior of granular surface materials. Maximum dry unit weight (MDU) values ranged from 111 to 138 pcf, with corresponding optimum moisture content (OMC) values between 3% and 11.3%. Resilient modulus (MR) tests showed inconsistent results, ranging from 10 ksi for sand-dominant materials to 30 ksi for open-graded materials. Virgin materials performed poorly in permanent deformation (PD) tests and were deemed unsuitable for road surfaces due to constructability, maintenance, and drainage limitations. A granular stabilization technique was implemented by mixing additional granular materials (e.g., gravel, crusher run, and fine-grained soils) to correct deficiencies in particle size distribution (PSD), shape, and plasticity. After extensive trials, 31 optimized blends were proposed. These blends exhibited increased dry unit weights, averaging 134 pcf, and consistent stiffness, with MR values ranging from 8 ksi to 27 ksi, predominantly at the higher end. Additionally, they showed nearly a 100% improvement in permanent strain accumulation across most blends. Performance enhancements were attributed to increased mechanical interlock, inter-particle friction, and binding, as well as reduced aggregate breakdown. Exposure to freeze-thaw cycles had no effect on MR but increased PD, indicating a reduction in material stability under repeated cycles. Stepwise regression models were developed to predict MR and PD directly from index properties such as particle size distribution, specific gravity, and plasticity. An Excel-based gradation optimization tool was developed to determine the required proportions of existing and fresh aggregates for an optimized gradation range. This tool incorporates road geometry and material characteristics to provide precise material quantities, ensuring improved consistency and performance in gravel road construction and maintenance.
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