交通运输系统工程与信息 ›› 2015, Vol. 15 ›› Issue (3): 185-189.

• 系统工程理论与方法 • 上一篇    下一篇

不同气象数据精度对驼峰峰高设计的影响

张红亮*,杨浩,夏胜利   

  1. 北京交通大学交通运输学院,北京10044
  • 收稿日期:2014-12-30 修回日期:2015-03-10 出版日期:2015-06-25 发布日期:2015-06-29
  • 作者简介:张红亮(1981-),男,河南内黄人,讲师,博士.
  • 基金资助:

    中央高校基本科研业务费专项资金资助(2012JBM071,2011JBM247)

Effect of Meteorological Data Accuracy on Hump Height Design

ZHANG Hong-liang, YANG Hao, XIA Sheng-li   

  1. School of Traffic and Transportation, Beijing Jiaotong University, Beijing 100044, China
  • Received:2014-12-30 Revised:2015-03-10 Online:2015-06-25 Published:2015-06-29

摘要:

气象数据是驼峰峰高设计的重要资料,驼峰设计规范使用月均数据作为驼峰设计计算温度、风速的依据.本文采用日均数据对全路49 个主要编组站驼峰设计计算温度、风速分析发现,日均数据下南、北方地区驼峰设计计算温度分别较月均数据低 1.34 ℃、0.94 ℃,计算风速分别较月均数据高1.29 m/s、1.15 m/s,增幅达30%以上.本文从理论上分析了差异产生的原因,并以三间房编组站为例进行了实证.进一步从置信概率的角度分析了全路主要编组站不同数据精度下驼峰设计计算温度、风速,基于日均数据的驼峰设计温度、风速与预期差值最大仅1.83%,基于月均数据的风速与预期差值最小达 18.74%.在此基础上,研究了不同数据精度对峰高设计的影响,揭示出采用月均数据存在峰高设计偏低的问题,并提出至少采用日均数据的驼峰设计气象资料选用及设计规范修改建议.

关键词: 铁路运输, 气象资料, 数据精度, 峰高设计, 置信概率

Abstract:

The meteorological data is very important in hump design work. In the code for design on hump and marshalling yard of railway, monthly meteorological data is used for hump design temperature and wind speed calculation. In this paper, daily meteorological data is used in 49 humps’design temperature and wind speed calculation. The result shows that the temperature with daily meteorological data is 1.34 ℃, 0.94 ℃ lower than monthly meteorological data in south and north area, and the wind speed is 1.29m/s, 1.15m/s higher than monthly meteorological data and the amplification is more than 30%. Then, the paper analyzes the reason in theory and verified with the meteorological data of San Jianfang marshalling station. Confidence probability analyzing shows that the confidence probability of hump design wind speed and temperature with daily meteorological data is almost the same with expected, with only 1.826% of the maximum difference, but the hump design wind speed with monthly meteorological data is large, with 18.743% of minimum difference. Then, the impact on hump height design is studied with daily meteorological data and monthly meteorological data, and the problem that the hump height is lower than expected with monthly meteorological data is revealed. At last, the suggestions that daily meteorological data should be used in hump design wind speed and temperature calculation at least, and the code for design on hump and marshalling yard of railway should be revised is proposed.

Key words: railway transportation, meteorological data, data accuracy, hump height design, confidence probability

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