Journal of Liaoning Petrochemical University
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Evaluation Model of High⁃Speed Railway Station Based on Machine Learning
Xu Ya′nan, Cao Yu, Wei Haiping, Li Qinqin, Zhang Luyue
Abstract205)   HTML    PDF (763KB)(140)      
The location of high⁃speed railway stations has always been in a contradiction. The government should not only reduce the impact of high⁃speed railway stations on people's lives, but also consider the cost of demolition. How to make the location of high⁃speed railway stations more scientific has become a problem that needs careful consideration. Therefore, the model of economic contribution degree was established by using linear regression analysis and grey prediction method to obtain the economic contribution degree of high⁃speed railway station to the city;based on the relevant data of high⁃speed railway in Liaoning Province, considering the construction cost, construction time, transfer convenience and economic contribution, a high⁃speed railway station location evaluation model based on principal component analysis was proposed and the evaluation model was used to analyze the siting of three high⁃speed railway stations in Liaoning Province. The results show that the siting of Shenyang North Railway Station is the most successful,and the passenger flow and distance from the city center are the important factors affecting the development of high⁃speed railway.
2021, 41 (3): 91-96. DOI: 10.3969/j.issn.1672-6952.2021.03.014
The Modification of Fe3O4@SiO2 by Silane Coupling Agent and Performance
Liang Jiling,Wang Liqun,Liu Lijuan,Tian Li,Zhang Lunqiu,Wang Weiqiang
Abstract748)   HTML    PDF (9892KB)(341)      
Spherical Fe3O4@SiO2 nanoparticles with good dispersibility (denoted as S1) were prepared by Stöber hydrolysis⁃polycondensation method, and the particle size was 300~430 nm.In order to investigate effect of carbon number in the organosilicone on 51 hydrophobicity and demusification of magnetic nanoparticles, the methyl triethoxysilane, n⁃hexyltriethoxysilane, n⁃dodecyltrimethoxysilane and n⁃octadecyltriethoxysilane were used to modify the surface of the S1 respectively, and the products were marked for S2—S5. The magnetic samples were characterized by electron microscopy (TEM), scanning electron microscope (SEM), X⁃ray diffraction (XRD), fourier transform infrared (FTIR) spectra and thermogravimetric analyses (TGA). The static water contact angle of magnetic nanoparticles (θW) were 10.6º、42.6º、113.6º、128.0º and 148.3º for S1—S5 respectively, and the results indicated that the θW increased with carbon number in the silane coupling agent increasing. Besides, the hydrophobic coating amount on the S1 surface of S2—S5 were estimated to be 0.005, 0.087, 0.092 g/g and 0.087 g/g respectively. The samples can be applied to removal the oil from water surfaces. Four kinds of silicone⁃modified magnetic particles can remove the surface oil, the n⁃dodecyltrimethoxysilane modified magnetic particles have the best effect of removing oil.
2019, 39 (6): 21-26. DOI: 10.3969/j.issn.1672-6952.2019.06.004
Study on the Characteristic of Dynamic Interfacial Tension between EOR Surfactants and Shengli Crude Oils
Wang Wei, Tian Yan, Wan Sheng, Fang Hongbo, Zhang Lei, Zhang Lu
Abstract421)      PDF (3383KB)(459)      
The dynamic interfacial tensions between five types of EOR surfactants and three types of Shengli crude oils were investigated, and the effect of surfactant concentration on interfacial tension was explored. The experimental results show that the different active components in crude oil could react under alkalescent condition and produce the surfaceactive soaps at the interface in situ. The interactions among the added surfactants, active components of crude oil and their products at interface together determined the characteristic behaviors of dynamic interfacial tension. Three types of characteristic dynamic interfacial tension curve might manifest as type "L", type "V" and type "W". The structure and concentration of surfactant and the type of crude oil were key factors impacting on the dynamic interfacial tension characteristics.
2015, 35 (2): 1-5,16. DOI: 10.3696/j.issn.1672-6952.2015.02.001