Volume 22 Issue 2
Apr.  2022
Turn off MathJax
Article Contents
ZHAO Jian-you, GUO Wan-jiang, JIA Xing-li, CHEN Xing-peng. Numerical simulation and law analysis of water accumulation distribution at superelevation transition section of multilane expressway[J]. Journal of Traffic and Transportation Engineering, 2022, 22(2): 187-196. doi: 10.19818/j.cnki.1671-1637.2022.02.014
Citation: ZHAO Jian-you, GUO Wan-jiang, JIA Xing-li, CHEN Xing-peng. Numerical simulation and law analysis of water accumulation distribution at superelevation transition section of multilane expressway[J]. Journal of Traffic and Transportation Engineering, 2022, 22(2): 187-196. doi: 10.19818/j.cnki.1671-1637.2022.02.014

Numerical simulation and law analysis of water accumulation distribution at superelevation transition section of multilane expressway

doi: 10.19818/j.cnki.1671-1637.2022.02.014
Funds:

National Key Research and Development Program of China 2020YFC1512003

Key Research and Development Program of Shaanxi Province 2021SF-514

Science and Technology Project of Henan Department of Transportation 2019G-2-11

More Information
  • Author Bio:

    ZHAO Jian-you(1963-), male, professor, PhD, jyzhao@chd.edu.cn

    JIA Xing-li(1986-), male, associate professor, PhD, jiaxingli@chd.edu.cn

  • Received Date: 2021-12-23
  • Publish Date: 2022-04-25
  • In order to reveal the distribution law of water accumulation at the superelevation transition section of multilane expressway, the design parameters of the typical superelevation transition section of multilane expressway were selected based on the fluid dynamics theory, and the road design software BIM was used to establish 40 groups of 3D road models. By analyzing the relationship between road area water quantity and drainage facilities runoff, a rainfall simulation scheme considering the influence of drainage facilities and pavement structure depth was established. The discrete phase model and multiphase flow model were coupled to simulate the water accumulation state of road area under rainfall condition. By analyzing the water accumulation thickness data of superelevation transition section under different combination parameters, the influence modes of synthetic slope, road width, rainfall intensity and superelevation gradient rate on the water accumulation thickness were obtained. The maximum water accumulation thicknesses of each lane were calculated, and the horizontal distribution laws of water accumulation at six-lane and eight-lane transition sections were revealed. Analysis results show that the thickness of stagnant water is negatively correlated with synthetic slope and superelevation gradient rate, and positively correlated with rainfall intensity and road width. The rainfall intensity has the greatest influence on the ponding water thickness, and the superelevation gradation rate has the least influence on the ponding water thickness. When the synthetic slope is 2.02%-8.54% and the rainfall intensity is 1-5 mm·min-1, the minimum water thickness at the superelevation section of multilane expressway is 0.58 mm, and the maximum is 28.35 mm. When the rainfall intensity is 5 mm·min-1, the maximum water thicknesses of the inner and outer lanes at the superelevation transition section of the expressway are significantly different. The maximum water thickness ratio from the inner lane to the outer lane at the six-lane transition section is 1.0∶3.1∶3.3, and the ratio is 1.00∶0.96∶1.03∶1.36 at the eight-lane transition section. The peak value of water accumulation thickness at the superelevation transition section of multi-lane expressway first appears near the middle of the expressway and then moves outward, and the maximum water accumulation thickness generally appears in the outer lane. 3 tabs, 13 figs, 26 refs.

     

  • loading
  • [1]
    LUO Wen-ting, WANG K C P, LI Lin. Field test validation of water film depth (WFD) prediction models for pavement surface drainage[J]. International Journal of Pavement Engineering, 2019, 20(10): 1170-1181. doi: 10.1080/10298436.2017.1394099
    [2]
    LUO Wen-ting, LI Lin, WANG K C P, et al. Surface drainage evaluation of asphalt pavement using a new analytical water film depth model[J]. Road Materials and Pavement Design, 2020, 21(7): 1985-2004. doi: 10.1080/14680629.2019.1590220
    [3]
    PICCARDI A, COLACE L. Optical detection of dangerous road conditions[J]. Sensors, 2019, 19(6): 1360. doi: 10.3390/s19061360
    [4]
    SINGH A K, ZHU Y, HAN M, et al. Simultaneous load and temperature measurement using Lophine-coated fiber Bragg gratings[J]. Smart Materials and Structures, 2016, 25(11): 115019. doi: 10.1088/0964-1726/25/11/115019
    [5]
    罗京, 刘建蓓, 王元庆. 路面水膜深度预测模型验证试验[J]. 中国公路学报, 2015, 28(12): 57-63. doi: 10.3969/j.issn.1001-7372.2015.12.008

    LUO Jing, LIU Jian-bei, WANG Yuan-qing. Validation test on pavement water film depth prediction model[J]. China Journal of Highway and Transport, 2015, 28(12): 57-63. (in Chinese) doi: 10.3969/j.issn.1001-7372.2015.12.008
    [6]
    罗京, 刘建蓓, 戈普塔, 等. 路面水膜厚度检验评价方法[J]. 交通信息与安全, 2016, 34(6): 54-59, 82. doi: 10.3963/j.issn1674-4861.2016.06.008

    LUO Jing, LIU Jian-bei, GOPTA P K, et al. An inspection and evaluation method of thickness of water film on road surface[J]. Journal of Transport Information and Safety, 2016, 34(6): 54-59, 82. (in Chinese) doi: 10.3963/j.issn1674-4861.2016.06.008
    [7]
    季天剑, 黄晓明, 刘清泉, 等. 沥青路面表面水膜厚度试验[J]. 公路交通科技, 2004, 21(12): 14-17. doi: 10.3969/j.issn.1002-0268.2004.12.004

    JI Tian-jian, HUANG Xiao-ming, LIU Qing-quan, et al. Test depth of water film on asphalt pavement surface[J]. Journal of Highway and Transportation Research and Development, 2004, 21(12): 14-17. (in Chinese) doi: 10.3969/j.issn.1002-0268.2004.12.004
    [8]
    黄镜入, 时海龙, 崔庚鑫. 基于无人机图像的高速公路积水预警系统设计[J]. 工业控制计算机, 2020, 33(3): 41-44. doi: 10.3969/j.issn.1001-182X.2020.03.016

    HUANG Jing-ru, SHI Hai-long, CUI Geng-xin. Design of highway water warning system based on UAV image[J]. Industrial Control Computer, 2020, 33(3): 41-44. (in Chinese) doi: 10.3969/j.issn.1001-182X.2020.03.016
    [9]
    孙婧. 基于改进LEACH算法的路面积水深度测量系统的设计与实现[J]. 计算机测量与控制, 2014, 22(4): 1297-1299. doi: 10.3969/j.issn.1671-4598.2014.04.102

    SUN Jing. Pavement water depth measurement system design based on LEACH algorithm[J]. Computer Measurement and Control, 2014, 22 (4): 1297-1299. (in Chinese) doi: 10.3969/j.issn.1671-4598.2014.04.102
    [10]
    LUO Wen-ting, LI Lin. Estimation of water film depth for rutting pavement using IMU and 3D laser imaging data[J]. International Journal of Pavement Engineering, 2021, 22(10): 1334-1349. doi: 10.1080/10298436.2019.1684495
    [11]
    LUO Wen-ting, LI Lin. Development of a new analytical water film depth (WFD) prediction model for asphalt pavement drainage evaluation[J]. Construction and Building Materials, 2019, 218: 530-542. doi: 10.1016/j.conbuildmat.2019.05.142
    [12]
    MA Yao-lu, GENG Yan-fen, CHEN Xian-hua, et al. Prediction for asphalt pavement water film thickness based on artificial neural network[J]. Journal of Southeast University (English Edition), 2017, 33(4): 490-495.
    [13]
    ZAGVOZDA M, ŽELJKO K. Analysis of solutions for superelevation design from standpoint of efficient drainage[J]. Road and Rail Infrastructure, 2016(5): 209-215
    [14]
    RESSEL W, WOLFF A, ALBER S, et al. Modelling and simulation of pavement drainage[J]. International Journal of Pavement Engineering, 2019, 20(7): 801-810 doi: 10.1080/10298436.2017.1347437
    [15]
    LIU Shi-he, TAI Wei, FAN Min, et al. Numerical simulation of atomization rainfall and the generated flow on a slope[J]. Journal of Hydrodynamics, 2012, 24(2): 273-279. doi: 10.1016/S1001-6058(11)60244-8
    [16]
    CHARBENEAU R, JEONG J, BARRETT M. Highway drainage at superelevation transitions[J]. Highway Design, 2008(3): 1-180.
    [17]
    季天剑, 黄晓明, 刘清泉, 等. 道路表面水膜厚度预测模型[J]. 交通运输工程学报, 2004, 4(3): 1-3. http://transport.chd.edu.cn/article/id/200403001

    JI Tian-jian, HUANG Xiao-ming, LIU Qing-quan, et al. Prediction model of rain water depth on road surface[J]. Journal of Traffic and Transportation Engineering, 2004, 4(3): 1-3. (in Chinese) http://transport.chd.edu.cn/article/id/200403001
    [18]
    季天剑, 高玉峰, 陈荣生. 轿车轮胎动力滑水分析[J]. 交通运输工程学报, 2010, 10(5): 57-60. http://transport.chd.edu.cn/article/id/201005010

    JI Tian-jian, GAO Yu-feng, CHEN Rong-sheng. Dynamic hydroplaning analysis of car tire[J]. Journal of Traffic and Transportation Engineering, 2010, 10(5): 57-60. (in Chinese) http://transport.chd.edu.cn/article/id/201005010
    [19]
    周海超, 陈磊, 翟辉辉, 等. 基于CFD的轮胎滑水及其性能影响因素分析[J]. 重庆交通大学学报(自然科学版), 2017, 36(1): 110-116. https://www.cnki.com.cn/Article/CJFDTOTAL-CQJT201701020.htm

    ZHOU Hai-chao, CHEN Lei, ZHAI Hui-hui, et al. Reserch on flow field and influencing factors of tire hydroplaning based on CFD method[J]. Journal of Chongqing Jiaotong University (Natural Science), 2017, 36(1): 110-116. (in Chinese) https://www.cnki.com.cn/Article/CJFDTOTAL-CQJT201701020.htm
    [20]
    HERMANGE C, OGER G, CHENADEC Y L, et al. A 3D SPH-FE coupling for FSI problems and its application to tire hydroplaning simulations on rough ground[J]. Computer Methods in Applied Mechanics and Engineering, 2019, 355: 558-590. doi: 10.1016/j.cma.2019.06.033
    [21]
    黄晓明, 刘修宇, 曹青青, 等. 积水路面轮胎部分滑水数值模拟[J]. 湖南大学学报(自然科学版), 2018, 45(9): 113-121. https://www.cnki.com.cn/Article/CJFDTOTAL-HNDX201809013.htm

    HUANG Xiao-ming, LIU Xiu-yu, CAO Qing-qing, et al. Numerical simulation of tire partial hydroplaning on flooded pavement[J]. Journal of Hunan University (Natural Sciences), 2018, 45(9): 113-121. (in Chinese) https://www.cnki.com.cn/Article/CJFDTOTAL-HNDX201809013.htm
    [22]
    李映夏, 焦圣明, 包云轩, 等. 高速公路路面干湿状态判别及积水模型应用研究[J]. 热带气象学报, 2017, 33(4): 558-567. https://www.cnki.com.cn/Article/CJFDTOTAL-RDQX201704013.htm

    LI Ying-xia, JIAO Sheng-ming, BAO Yun-xuan, et al. Dry and wet state discrimination and the application of water/snow accumulation model on the road surface of expressway[J]. Journal of Tropical Meteorology, 2017, 33(4): 558-567. (in Chinese) https://www.cnki.com.cn/Article/CJFDTOTAL-RDQX201704013.htm
    [23]
    张驰, 王博, 贺九平, 等. 基于行车动力学的高速公路积水路段行车风险分析[J]. 交通信息与安全, 2019, 37(5): 9-17. https://www.cnki.com.cn/Article/CJFDTOTAL-JTJS201905002.htm

    ZHANG Chi, WANG Bo, HE Jiu-ping, et al. Traffic risk analysis of ponding sections on freeways based on driving dynamics[J]. Journal of Transport Information and Safety, 2019, 37(5): 9-17. (in Chinese) https://www.cnki.com.cn/Article/CJFDTOTAL-JTJS201905002.htm
    [24]
    张驰, 郭鑫鑫, 崔卜心. 不均匀积水条件对路面行车安全的影响[J]. 公路交通科技, 2014, 31(10): 104-111. https://www.cnki.com.cn/Article/CJFDTOTAL-GLJK201410017.htm

    ZHANG Chi, GUO Xin-xin, CUI Bu-xin. Influence of uneven wet pavement surface condition on driving safety[J]. Journal of Highway and Transportation Research and Development, 2014, 31(10): 104-111. (in Chinese) https://www.cnki.com.cn/Article/CJFDTOTAL-GLJK201410017.htm
    [25]
    徐进, 彭其渊, 邵毅明. 直线路段积水路面车辆事故产生机理分析[J]. 中国公路学报, 2009, 22(1): 97-103. https://www.cnki.com.cn/Article/CJFDTOTAL-ZGGL200901018.htm

    XU Jin, PENG Qi-yuan, SHAO Yi-ming. Mechanism analysis of vehicle accident on surface gathered water in straight sections[J]. China Journal of Highway and Transport, 2009, 22(1): 97-103. (in Chinese) https://www.cnki.com.cn/Article/CJFDTOTAL-ZGGL200901018.htm
    [26]
    管朝鹏. 基于DPM及EWF模型的积水分布研究[D]. 重庆: 重庆交通大学, 2015.

    GUAN Chao-peng. Research on the distribution of accumulated water based on DPM and EWF model[D]. Chongqing: Chongqing Jiaotong University, 2015. (in Chinese)
  • 加载中

Catalog

    通讯作者: 陈斌, bchen63@163.com
    • 1. 

      沈阳化工大学材料科学与工程学院 沈阳 110142

    1. 本站搜索
    2. 百度学术搜索
    3. 万方数据库搜索
    4. CNKI搜索

    Article Metrics

    Article views (531) PDF downloads(71) Cited by()
    Proportional views
    Related

    /

    DownLoad:  Full-Size Img  PowerPoint
    Return
    Return