Journal
CONSTRUCTION AND BUILDING MATERIALS
Volume 264, Issue -, Pages -Publisher
ELSEVIER SCI LTD
DOI: 10.1016/j.conbuildmat.2020.120235
Keywords
Bio-oil; Rock asphalt; Composite modified asphalt; RSM; GA-ANN
Categories
Funding
- National Natural Science Foundation of China [51578081, 51608085]
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Applying bio-asphalt in road engineering can effectively resolve its shortage of petroleum asphalt, and enhance its environmental friendliness and sustainability. However, the poor high-temperature stability with added bio-oil is a key obstacle restricting its wide utilization. To broaden the application of bio-asphalt in road engineering, in this research was used rock asphalt to further improve bio-asphalt through the Box-Behnken Design (BBD). During the optimization of the design, bio-oil content, rock asphalt content, and shear time were defined as independent variables. Penetration, softening point, creep rate, stiffness modulus, and irrecoverable creep compliance of the modified asphalt were considered response values. Response surface method (RSM) model and Genetic algorithm optimization artificial neural network (GA-ANN) model were utilized to analyze the behavior of bio-oil/rock asphalt composite modified asphalt. Furthermore, the feasibility of both models was verified through experimental results. The results indicated that the incorporation of bio-oil and rock asphalt improved the low-temperature and high-temperature resistance of neat asphalt, respectively. Besides, the low-temperature crack resistance of composite modified asphalt was remarkably enhanced, and the high-temperature performance was similar to the one related to neat asphalt. GA-ANN model had higher feasibility for composite modified asphalt performance optimization. The optimal bio-oil content, rock asphalt content, and shear time determined by using RSM and GA-ANN model were equal to 6.3%, 11.2%, 52.8 min, and 6.3%, 12.9%, 76.6 min, respectively. The bio-oil/rock asphalt composite modified asphalt with targeted performance requirements can be achieved by combining the proposed weight function with the RSM model and GA-ANN model. Optimization with GA-ANN can further promote the recycling of both bio-oil and Buton rock asphalt, save energy, and lead to a greener construction material. This study can serve as a solid base for more efficient utilization of bio-asphalt in road engineering. (C) 2020 Elsevier Ltd. All rights reserved.
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