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Xizhen Liang,Jian Wang,Tao Zhou,Hao Duan,Yueming Zhou 한국화학공학회 2015 Korean Journal of Chemical Engineering Vol.32 No.8
A modified model is established according to the analysis of energy balance acting on an agglomerate of binary mixed nanoparticles in a vibrated fluidized bed (VFB). The sizes of agglomerates of binary mixed nanoparticles are calculated with this model. The average agglomerate size estimated by the model of energy balance decreases with increasing superficial gas velocity. The vibration frequency had a comparatively significant impact on agglomerate sizes that seemed to change regularly and decreased with higher frequency. Both of the experimental and theoretical results showed that vibration led to a smaller agglomerate size, and the average agglomerate sizes calculated by this model provided the closest fit to those determined experimentally.
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The Impact of the Parking Spot’ Surroundings on Charging Decision: A Data-Driven Approach
Xizhen Zhou,Yanjie Ji,Mengqi Lv 대한토목학회 2024 KSCE Journal of Civil Engineering Vol.28 No.5
The charging behavior of drivers serves as a valuable reference for planning and managing charging facilities. This study examines the influence of surrounding environments on charging decisions using real trajectory data from electric vehicles. It considers the built environment, vehicle conditions, and the nearest charging station attributes. The mixed binary logit model was applied to capture the impact of unobserved heterogeneity. The findings indicate that the number of fast chargers in the charging station, parking prices, dwell time, and shopping services significantly influence charging decisions, while leisure services, scenic spots, and mileage since the last charging exhibit opposite effects. Additionally, factors related to unobserved heterogeneity include the number of fast chargers, parking and charging prices, and residential areas. The interaction effects of random parameters further illustrate the complexity of charging choice behavior. Overall, the results offer valuable insights for the planning and management of charging facilities.
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What Causes Curbside Illegal Parking Behavior: A Method Based on Structural Equation Model
Jie Yan,Xizhen Zhou,Yanjie Ji 대한토목학회 2023 KSCE Journal of Civil Engineering Vol.27 No.8
Reducing curbside illegal parking is a crucial aspect of urban parking management. However, there is currently a dearth of relevant research. Further analysis is required to determine the factors that influence curbside illegal parking behavior. To this end, a questionnaire survey was conducted in Nanjing, and exploratory factor analysis was used to evaluate the explanatory power of the measurement variables. From this, driver factors, traffic conditions, parking facilities and environment were identified as latent variables. A structural equation model was created to examine the relationship between these variables. The findings indicated that parking facilities and driver factors had a direct and positive correlation with curbside illegal parking behavior, while the environment had a direct and negative correlation with such behavior. Moreover, parking facilities had the greatest impact. The study highlighted the effectiveness of measures such as promoting traffic regulation awareness, optimizing public parking lot charging standards, and strengthening penalties for curbside illegal parking behavior. The results of this research will contribute to a greater comprehension of the phenomenon and provide a theoretical foundation for curbside parking management.
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