摘要
为了探讨西部地区的集装箱内部的温度场影响因素,建立了集装箱内部流体的三维非稳态数学模型,通过仿真软件对内部温度场分布进行模拟,并利用试验验证了仿真结果,以大气温度和太阳辐射作为影响因子,对试验数据进行回归分析,研究空集装箱和载货集装箱在同一环境下内部温度场的分布。结果表明:大气温度是集装箱内部温度场的主要影响因素,其回归系数达0.9以上,太阳辐射作为箱壁的温度载荷也会造成局部的温度变化;内装货物的堆码方式也会造成箱内升温,仿真模拟数据和试验数据的误差范围在3℃以内,证明了所建立仿真模型的可行性,从而为集装箱运输保温隔热措施提供设计参考。
In order to explore the influencing factors of the temperature field inside containers in western China,a three-dimensional unsteady mathematical model of the fluid inside the container was established.Simulation software was used to simulate the internal temperature field distribution,and experimental verification was conducted to validate the simulation results.Atmospheric temperature and solar radiation were considered as influencing factors,and regression analysis was performed on the experimental data.The distribution of the internal temperature field of empty and loaded containers under the same environmental conditions was studied.The results show that atmospheric temperature is the main influencing factor of the internal temperature field of the container,with a regression coefficient of above 0.9.Solar radiation,as a thermal load on the container wall,also causes local temperature changes.The stacking method of the cargo inside the container can lead to a temperature rise.The error between simulation and experimental data is within 3℃,proving the feasibility of the established simulation model.This provides a design reference for thermal insulation measures in container transportation.
作者
尹芊蔚
张洪雨
王军
YIN Qianwei;ZHANG Hongyu;WANG Jun(School of Traffic and Transportation,Lanzhou Jiaotong University,Lanzhou 730070,Gansu,China;Key Laboratory of Railway Industry on Plateau Railway Transportation Intelligent Management and Control,Lanzhou 730070,Gansu,China;Department of Freight,China Railway Lanzhou Group Co.,Ltd.,Lanzhou 730000,Gansu,China)
出处
《铁路物流》
2025年第8期26-33,共8页
Railway Logisitics
基金
甘肃省联合科研基金项目(24JRRA851)
中国铁路兰州局集团有限公司科技发展项目(2024013-1,2023006-1)。
关键词
集装箱
铁路运输
温度场
耦合换热
回归分析
Container
Railway Transportation
Temperature Field
Coupled Heat Transfer
Regression Analysis
