“…Classical sampling strategies include orthogonal experimental design, 57 Latin hypercube sampling (LHS), 58 uniform experimental design, 59 etc. In this research, the uniform experimental design sampling strategy with a 21×21 matrix is used, with a total of 441 sample points, as shown in Figure 9 Figure 9. The sampling plan for the KSM..…”
Wheel wear (W-wear) is one of the most critical issues affecting vehicle-track performances and operating costs. Currently, the works on W-wear behavior and W-wear reduction are mainly based on four aspects: wheel-rail (WR) tribology, WR profile, vehicle structure design and active control of vehicle suspensions. Little attention has been paid to the effects of track layout parameters, such as superelevation, gauge, and cant. To supplement the existing research, this work aims to investigate the relationship between W-wear and track layout parameters and ultimately reduce W-wear through optimizing track layout parameters. The framework consists of a series of steps. Firstly, a multibody dynamics simulation (MBS) model of an Sgnss wagon with 55 degrees of freedom (DOFs) is built. Then, taking a 375-m-radius curve as a case, the influence of track layout parameter (superelevation, gauge, and cant) on W-wear and vehicle derailment safety is investigated based on Kriging surrogate model (KSM). Finally, based on optimized results obtained by KSM and particle swarm optimization (PSO), two optimal regions and three reasonable suggestions concerning the layout of a 375-m-radius curve are given from the perspective of reducing W-wear. This study is promising for the parameter setting of those dedicated lines, on which the train speed is usually fixed, such as metro, light rail, and tram.
“…Classical sampling strategies include orthogonal experimental design, 57 Latin hypercube sampling (LHS), 58 uniform experimental design, 59 etc. In this research, the uniform experimental design sampling strategy with a 21×21 matrix is used, with a total of 441 sample points, as shown in Figure 9 Figure 9. The sampling plan for the KSM..…”
Wheel wear (W-wear) is one of the most critical issues affecting vehicle-track performances and operating costs. Currently, the works on W-wear behavior and W-wear reduction are mainly based on four aspects: wheel-rail (WR) tribology, WR profile, vehicle structure design and active control of vehicle suspensions. Little attention has been paid to the effects of track layout parameters, such as superelevation, gauge, and cant. To supplement the existing research, this work aims to investigate the relationship between W-wear and track layout parameters and ultimately reduce W-wear through optimizing track layout parameters. The framework consists of a series of steps. Firstly, a multibody dynamics simulation (MBS) model of an Sgnss wagon with 55 degrees of freedom (DOFs) is built. Then, taking a 375-m-radius curve as a case, the influence of track layout parameter (superelevation, gauge, and cant) on W-wear and vehicle derailment safety is investigated based on Kriging surrogate model (KSM). Finally, based on optimized results obtained by KSM and particle swarm optimization (PSO), two optimal regions and three reasonable suggestions concerning the layout of a 375-m-radius curve are given from the perspective of reducing W-wear. This study is promising for the parameter setting of those dedicated lines, on which the train speed is usually fixed, such as metro, light rail, and tram.
“…Uniform design can select a subset of typical test points from the entire set of test points, ensure the uniform distribution of test points in a test range, and reflect major features of the test system. The uniform design method is widely employed to investigate material composition and demonstrates excellent applicability and accuracy [ 36 , 37 ]. Therefore, in this paper, the uniform design method was employed for GMA composition design.…”
Section: Experimental Methods and Performance Evaluationmentioning
In this study, graphene-modified asphalt (GMA) was prepared from SK-70# matrix asphalt and ethylene bis(stearamide) (EBS). Based on the uniform design method, a model was created using Data Processing System (DPS) software and First Optimization (1stOpt) software using the graphene mixing amount, EBS mixing amount, shear rate, shear time, and shear temperature as factors and using the asphalt penetration, softening point, force ductility, SHRP-PG test, and multistress creep recovery data as indices. Calculations and analysis showed that the optimal composition and preparation parameters of GMA are as follows: the graphene proportion is 20‰, the EBS proportion is 1%, the shear rate is 6000 r.p.m., the shear time is 180 min, and the shear temperature is 140 °C. The prepared GMA had a significantly improved softening point, low-temperature fracture energy, antirutting factor, and creep recovery rate, indicating that adding graphene can improve the high- and low-temperature performance of asphalt. The prepared GMA was characterized by X-ray diffraction (XRD). The dispersibility of graphene in asphalt was evaluated by fluorescence microscopy and Image-Pro Plus imaging software. The results show that graphene can exist in asphalt in a stable form, which increases the loose-layered structure of stacked asphalt or gum. The intense adsorption effect of graphene strengthens the ordered structure of asphalt. However, due to its dispersibility characteristics, some graphene exists in asphalt in clustered form. When the graphene-to-dispersant ratio approaches the optimal value, the dispersant changes the form of graphene in asphalt from irregular clusters to regular clusters and from large, distinct clusters to small, indistinct clusters. When dispersant cannot uniformly disperse graphene in asphalt, graphene clusters primarily form medium-sized grains.
“…With the increase of heavy traffic, the improvement of high-temperature stability and anti-fatigue performance has become an urgent problem to be solved in bridge deck pavement [ 11 ]. Although Gussasphalt mixture technology has been successfully applied globally, and a series of achievements have been made, Gussasphalt concrete containing a large portion of fine aggregates (aggregate size less than 2.36 mm) and a high content of asphalt binder is a typically suspended density mixture [ 12 ]. In this material, the small amount of coarse aggregates cannot form a stable skeleton [ 13 ].…”
Epoxy asphalt concrete, mortar asphalt concrete and Gussasphalt concrete are commonly used types of deck pavement materials in bridge deck pavement engineering. However, achieving the high-temperature stability and anti-fatigue performance of the deck pavement materials is still challenging. In order to reduce the rutting and cracking risks of the asphalt mixture, this paper proposed pre-coated aggregates grouting asphalt concrete (PGAC) for bridge deck pavement. Laboratory tests were conducted to determine the optimum grouting materials and to evaluate the mechanical performances of the PGAC material. Test results showed that the mechanical properties for PGAC with grouting material of high-viscosity-modified asphalt binder blending with mineral filler were superior to that of GMA-10 used for the Hong Kong-Zhuhai-Macau Bridge deck pavement. Microstructural analysis showed that the PGAC had a more stable skeleton structure compared to other typical aggregate mixtures. This study highlights the performances of the proposed PGAC and sheds light on the deck pavement material improvement of both high-temperature stability and anti-fatigue performance that could be achieved.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
