Design method for polyurethane-modified asphalt by using Kriging-Particle Swarm Optimization algorithm. (January 2023)

• Record Type: Journal Article
• Authors: Lu, Pengzhen; Ye, Kai; Jin, Tian; Ma, Yiheng; Huang, Simin; Zhou, Chenhao
• Is Part Of: Engineering applications of artificial intelligence. Volume 117:Part A(2023)
• Publication Date: 2023-01
• Subjects: Polyurethane-modified bitumen -- Preparation process -- Machine-learning algorithm -- Kriging-PSO model -- Design method; Engineering -- Data processing -- Periodicals; Artificial intelligence -- Periodicals; Expert systems (Computer science) -- Periodicals; Ingénierie -- Informatique -- Périodiques; Intelligence artificielle -- Périodiques; Systèmes experts (Informatique) -- Périodiques; Artificial intelligence; Engineering -- Data processing; Expert systems (Computer science); Periodicals; 620.00285
• DOI: 10.1016/j.engappai.2022.105609
• Languages: English
• ISSNs: 0952-1976

Abstract

Abstract: The preparation process of polyurethane (PU)-modified bitumen involves numerous design parameters and performance response indexes. Due to the variety of polyurethane modifiers, the preparation process of the polyurethane-modified bitumen is not universally applicable. However, the traditional methods such as the response surface method and orthogonal design method have some problems such as low accuracy and a large number of samples required in the preparation process design. Therefore, according to different application environments, the problem of determining the process parameters of the polyurethane-modified bitumen accurately and efficiently needs to be solved urgently. Using Kriging-Particle Swarm Optimization (PSO) algorithm, an efficient process design method for the preparation of polyurethane modified asphalt is proposed in this paper. Combined with the sensitivity analysis method, the relatively sensitive response indexes are screened out to reduce the number of samples and improve the design accuracy. Among them, the dispersion coefficient was evaluated by fluorescence microscopy test using the Christiansen coefficient method to evaluate the uniformity of the dispersed phase of the polyurethane modifier. According to the target performance, the main process parameters of PU modified asphalt were obtained by the Kriging-Particle Swarm Optimization algorithm: shear time 86 min, shear speed 2450 rpm, shear temperature 148 °C, and polyurethane content 18.6%. The polyurethane-modified bitumen prepared by this optimal process met the expected performance indicators. This study achieved the expected results with a small number of samples, indicating that this method can achieve the purpose of designing the ideal process parameters of polyurethane-modified asphalt efficiently.