Prediction and pareto-based multi-objective optimization of moisture and fatigue damages of asphalt mixtures modified with nano hydrated lime

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@Article{NAJAFIMOGHADDAMGILANI:2020:CBM,

• author = "Vahid {Najafi Moghaddam Gilani} and Seyed Mohsen Hosseinian and Hamid Behbahani and Gholam Hossein Hamedi",
• title = "Prediction and pareto-based multi-objective optimization of moisture and fatigue damages of asphalt mixtures modified with nano hydrated lime",
• journal = "Construction and Building Materials",
• volume = "261",
• pages = "120509",
• year = "2020",
• ISSN = "0950-0618",
• DOI = "doi:10.1016/j.conbuildmat.2020.120509",
• URL = "http://www.sciencedirect.com/science/article/pii/S0950061820325149",
• keywords = "genetic algorithms, genetic programming, Asphalt mixture, Moisture sensitivity, Fatigue failure, Surface free energy, Nano hydrated lime, GMDH, GP, Multi-objective optimization",
• abstract = "Moisture sensitivity can lead to damages due to adhesion and cohesion in asphalt mixtures that cause serious damages to the pavement. Adhesion between bitumen and aggregate is a basic prerequisite for the proper performance of asphalt mixtures. The role of nano hydrated lime (NHL) as an anti-stripping agent has been extensively studied in asphalt pavements. In this study, in addition to investigating the effect of NHL as bitumen modifier on moisture and fatigue damages, and bitumen-aggregate adhesion and bitumen membrane cohesion using surface free energy (SFE) concept, the prediction model to achieve optimal additive percentage with two objectives of moisture sensitivity and fatigue failure by multivariate regression (MVR), group method of data handling (GMDH) and genetic programming (GP) were provided. By the use of the modified non-dominated sorting genetic algorithm II (NSGA-II) approach, Pareto fronts were then plotted. In addition, boiling water testing was applied to examine the sensitivity of mixtures to moisture. To simulate environmental conditions, asphalt mixtures were placed in freeze-thaw (F-T) cycles of 1, 3 and 5. 85-100 penetration grade base bitumen was modified with 0.5percent, 1percent and 1.5percent NHL (by the weight of bitumen). The results indicated that by decreasing the number of yellow pixels in the image processing of modified mixtures with NHL, modification of bitumens decreased the moisture sensitivity of specimens. Using NHL increased the resistance of the specimens to moisture and fatigue damages. The amount of indirect tensile strength (ITS) and fatigue life of asphalt mixtures reduced by rising the number of F-T cycles. The highest increase in ITS and fatigue life was obvious in modified mixtures with 1.5percent and 1percent NHL, respectively. The results of calculating the surface free energy (SFE) components of the base and modified bitumens showed that using NHL enhanced the total SFE amount of bitumens. Also, using the NHL increased cohesion free energy (CFE), adhesion free energy (AFE) and debonding energy (DE) of modified bitumens and decreased the permeability of asphalt mixtures (PAMs) amount. Among the various methods, the GMDH method had the highest R2. So that the R2 value of GMDH for tensile strength ratio (TSR) and the ratio of fatigue life (NFR) was 93.9percent and 86.9percent, respectively. The two-objective optimization results indicated that 1.29percent NHL was the best optimal amount to maximize the TSR and NFR values simultaneously",

}

Genetic Programming entries for Vahid Najafi Moghaddam Gilani Seyed Mohsen Hosseinian Hamid Behbahani Gholam Hossein Hamedi

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