Influence of geometric alignment of expressway superelevation transition section on hydroplaning speed of minibus

JIA Xing-li; CHEN Xing-peng; HUANG Ping-ming; MA Qing-wei; LI Shuang-qing; YAN Meng-hua

doi:10.19818/j.cnki.1671-1637.2022.04.010

Volume 22 Issue 4

Aug. 2022

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Article Contents

Abstract

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0. introduction

1. The Relationship Model between Linear Index of Ultra high Transition Section and Skiing Speed

2. Calculation of water skiing speed for small passenger cars in ultra-high transition section

3. The Influence of Linear Index of Ultra high Transition Section on the Skiing Speed of Small Passenger Cars

4. conclusion

References

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JIA Xing-li, CHEN Xing-peng, HUANG Ping-ming, MA Qing-wei, LI Shuang-qing, YAN Meng-hua. Influence of geometric alignment of expressway superelevation transition section on hydroplaning speed of minibus[J]. Journal of Traffic and Transportation Engineering, 2022, 22(4): 140-147. doi: 10.19818/j.cnki.1671-1637.2022.04.010

Citation:

JIA Xing-li, CHEN Xing-peng, HUANG Ping-ming, MA Qing-wei, LI Shuang-qing, YAN Meng-hua. Influence of geometric alignment of expressway superelevation transition section on hydroplaning speed of minibus[J]. Journal of Traffic and Transportation Engineering, 2022, 22(4): 140-147. doi: 10.19818/j.cnki.1671-1637.2022.04.010

Citation:

JIA Xing-li, CHEN Xing-peng, HUANG Ping-ming, MA Qing-wei, LI Shuang-qing, YAN Meng-hua. Influence of geometric alignment of expressway superelevation transition section on hydroplaning speed of minibus[J]. Journal of Traffic and Transportation Engineering, 2022, 22(4): 140-147. doi: 10.19818/j.cnki.1671-1637.2022.04.010

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Influence of geometric alignment of expressway superelevation transition section on hydroplaning speed of minibus

doi: 10.19818/j.cnki.1671-1637.2022.04.010

1.
School of Highway, Chang'an University, Xi'an 710064, Shaanxi, China
2.
Xi'an Highway Research Institute Co., Ltd., Shaanxi Transportation Holding Group Co., Ltd., Xi'an 710065, Shaanxi, China
3.
College of Engineering, University of Wisconsin-Madison, Madison WI 53706, Wisconsin, USA

Funds:

National Key Research and Development Program of China 2020YFC1512003

National Key Research and Development Program of China 2021YFB2600403

Natural Science Basic Research Program of Shaanxi Province 2020JM-260

More Information

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

HUANG Ping-ming(1965-), male, professor, PhD, Hpming@vip.sina.com
Received Date: 2022-03-21
Available Online: 2022-10-08
Publish Date: 2022-08-25

Abstract

Abstract

In order to reveal the change laws of hydroplaning speed of minibus under different geometrical alignment factors at expressway superelevation transition section, the relationships among hydroplaning speed, water film thickness and superelevation transition geometric alignment factors were analyzed according to the tire force characteristics of minibus during hydroplaning process. Based on the multivariate linear regression and fluid simulation, a quantitative model of hydroplaning speed of minibus at superelevation transition section was established. Combined the rainfall intensity, longitudinal slope and superelevation transition rate, the critical hydroplaning speed of minibus was calculated. Taking the superelevation transition section of a typical four-lane expressway as an example, the influence law of rainfall intensity, longitudinal slope and superelevation transition rate on the hydroplaning speed of minibus was studied, and the recommended limit speed value at superelevation transition section was given. Research results show that the maximum value of hydroplaning speed of minibus is 115.5 km·h^-1 under the combination of longitudinal slope of 0.3%, superelevation transition rate of 1/200 and rainfall intensity of 20 mm·h^-1, and the minimum value of hydroplaning speed of minibus is 99.3 km·h^-1under the combination of longitudinal slope of 3.0%, superelevation transition rate of 1/330 and rainfall intensity of 80 mm·h^-1. Under the condition that rainfall intensity and superelevation transition rate are certain, the hydroplaning speed decreases gradually with the increase of longitudinal slope, and decreases by 2.68% when the longitudinal slope increases from 0.3% to 3.0%. Under the condition that the rainfall intensity and longitudinal slope are certain, the hydroplaning speed increases gradually with the increase of superelevation transition rate, and increases by 2.25% when the superelevation transition rate increases from 1/330 to 1/200. Increasing the longitudinal slope can reduce hydroplaning speed. However, when the rainfall intensity increases to a certain degree, the influence of longitudinal slope and superelevation transition rate on the hydroplaning speed tends to be flat. When the rainfall intensity is 20-80 mm·h^-1, the recommended limit speed is 95.0-115.0 km·h^-1, but not greater than the design speed.
- road engineering,
- expressway,
- superelevation transition section,
- hydroplaning speed,
- fluid dynamics simulation,
- range analysis,
- water film thickness

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0. introduction

It can be seen that existing research focuses on analyzing the influence of factors such as tire texture, road surface structure, vehicle load, and water film thickness on the speed of vehicle hydroplaning, and lacks research on the influence of highway geometry on hydroplaning speed, especially in special sections such as ultra-high transition sections where road water accumulation is significantly affected by geometry; In addition, due to the lack of comprehensive consideration of multivariate combinations such as rainfall and road geometry, the existing research on the critical speed of vehicle hydroplaning cannot scientifically guide the speed management of vehicles in flooded sections of highways under rainy weather.

1. The Relationship Model between Linear Index of Ultra high Transition Section and Skiing Speed

1.1 The relationship between water skiing speed and water film thickness

The principle behind the phenomenon of car tire skidding is as follows:Figure 1As shown, when the vehicle quickly enters the water accumulation area, the relative relationship between the water accumulation and the tires can be divided into three areas: in Zone I, there is a large dynamic water pressure between the water accumulation on the road surface and the tires, and the tires will be subjected to upward lifting force, resulting in the separation of the tire surface from the road surface; In Zone II, there is a thin water film separating the tread from the road surface, and only a portion of the tire is lifted; In Zone III, the tire tread is in full contact with the road surface without any water film. As the vehicle speed gradually increases, the length of zones I and II will continue to increase, and the range of zone III will gradually decrease to disappear. Eventually, the tire will completely separate from the road surface, resulting in tire skidding.

Figure 1. Hydroplaning status of tire

DownLoad: Full-Size Img PowerPoint

$F=0.285 h^{0.313} v^{2.01}$

(1)

$N=F=0.285 h^{0.313} v^{2.01}$

(2)

In the formula:NLoad on vehicle tires.

This article takes small passenger cars as the research model, considering the most common tire types and axle loads in small passenger cars as input variables for calculation. The typical tire type is determined to be 225/50R16 92V, and the axle load is 6.17 kN^[26]Obtain the vehicle's water skiing speedvCompared to the thickness of the water filmhThe relationship between them is

$v=128.65 h^{-0.156}$

(3)

1.2 超高过渡段水膜厚度计算方法

$h=0.068 L^{0.32} q^{0.41} d^{1.17} I^{-0.31}$

(4)

Figure 2. Paths of water flows

DownLoad: Full-Size Img PowerPoint

$T=\left[\frac{2 b}{g \sin (s)}\right]^{0.5}$

(5)

In the formula:TFor drainage time;bThe width of the road surface;gAcceleration due to gravity;sThe cross slope gradient of the road.

$\left\{\begin{array}{l} t=\frac{T}{M} \\ x_m=\frac{1}{2} g t^2 \sin \left(s_m\right) \\ y_m=\frac{1}{2} g t^2 \sin \left(i_m\right) \end{array}\right.$

(6)

In the formula:s_mFor the thmThe cross slope gradient of the road within the section;i_mFor the thmThe longitudinal slope gradient of the road within the section.

$p=\frac{b\left(S_2-S_1\right)}{D}$

(7)

By combining equations (5) to (7), the length of the water flow path can be obtainedLdo

$L=\sum\limits_{m=1}^M\left\{\left(s_0-\frac{p \sum\limits_{m=1}^{M-1} y_m}{b}\right) t^2+\frac{1}{2} g t^2 \sin \left(s_0-\frac{p \sum\limits_{m=1}^{M-1} y_m}{b}\right)+\right. \\ \left.\left[m g t^2 \sin \left(i_m\right)+\frac{1}{2} t^2 \sin \left(i_m\right)\right]^2\right\}$

(8)

$L=b^{0.31} i_m^{0, 61} p^{-0.89}$

(9)

Table 1. Fitting result

影响因素	标准误差	拟合优度
b	0.047	0.96
i_m	0.025
p	0.024

| Show Table

DownLoad: CSV

To verify the accuracy of equation (9), fluid simulation experiments were conducted for comparative verification. Based on the Fluent platform, establish a three-dimensional road model that is the same as the subsequent calculation of critical water skiing speed, and conduct 9 sets of simulation experiments on the length of water flow paths. One set of simulation results is as follows:Figure 3As shown.

Figure 3. Simulation result of flow path length

DownLoad: Full-Size Img PowerPoint

Figure 4. Comparison of theoretical calculation and simulation data

DownLoad: Full-Size Img PowerPoint

1.3 超高过渡段几何线形与滑水速度关系模型

$v=176.594 q^{-0.064} p^{0.044} i_m^{-0.03}\left(i_m^2+0.0004\right)^{0.024}$

(10)

2. Calculation of water skiing speed for small passenger cars in ultra-high transition section

From the force state of the tires during the water skiing process, it can be seen that the higher the vehicle's driving speed, the greater the water flow lifting force generated, and the more prominent the water skiing phenomenon. Therefore, the current maximum design speed of 120 km · h for Chinese highways is selected^-1To design speed control conditions. According to the relevant provisions of the "Highway Route Design Specification" (JTG D20-2017), the range of longitudinal slope gradient under this design speed is 0.3%~3.0%, and the range of superelevation gradient is 1/330~1/200. Wu Jianjun and others^[31]Research has found that short-term heavy rainfall has a greater impact on traffic safety. A rainfall of 50 mm or more within 3 hours is referred to as heavy rainfall, with rainfall intensity ranging from 20 to 80 mm · h^-1The range of factors affecting the speed of water skiing in the ultra-high transition section of this article is as follows:Table 2As shown.

Table 2. Ranges of influence factors

影响因素	纵坡坡度/%	超高渐变率	降雨强度/(mm·h^-1)
取值范围	0.3~3.0	1/330~1/200	20~80

| Show Table

DownLoad: CSV

Orthogonal experiments were conducted with longitudinal slope gradient, superelevation gradient rate, and rainfall intensity as variables to calculate the water skiing speed of small passenger cars in the superelevation transition section under multivariate combinations. The calculation results of water skiing speed when taking the extreme values of three influencing factors are as follows:Table 3As shown in the figure, it can be seen that for a two-way four lane expressway, the maximum water sliding speed of vehicles occurs at a longitudinal slope gradient of 0.3%, a superelevation gradient rate of 1/200, and a rainfall intensity of 20 mm · h^-1Under the combination, it is 115.5 km · h^-1The minimum value occurs when the longitudinal slope gradient is 3.0%, the superelevation gradient rate is 1/330, and the rainfall intensity is 80 mm · h^-1Under the combination, it is 99.3 km · h^-1.

Table 3. Hydroplaning speeds under extreme combinations of influencing factors

降雨强度/(mm·h^-1)	纵坡坡度/%	超高渐变率	滑水速度/(km·h^-1)
20	0.3	1/330	110.0
	0.3	1/200	115.5
	3.0	1/330	108.5
	3.0	1/200	112.9
80	0.3	1/330	101.6
	0.3	1/200	104.3
	3.0	1/330	99.3
	3.0	1/200	102.0

| Show Table

DownLoad: CSV

3. The Influence of Linear Index of Ultra high Transition Section on the Skiing Speed of Small Passenger Cars

3.1 超高渐变率的影响

Figure 5. Influence of superelevation gradient rate on hydroplaning speed

DownLoad: Full-Size Img PowerPoint

3.2 纵坡坡度的影响

Select rainfall intensities of 20, 40, 60, and 80 mm · h respectively^-1Calculate the water skiing speed of small passenger cars under different longitudinal slope gradients, and the results are as follows:Figure 6As shown, it can be seen that under the same rainfall intensity, the water skiing speed of small passenger cars decreases with the increase of longitudinal slope gradient; At different rainfall intensities, the minimum water skiing speed occurs when the longitudinal slope gradient is 3.0%, which prolongs the length of the water flow path, increases the thickness of the collected water film, and reduces the water skiing speed; Under different combinations of rainfall intensity and ultra-high gradient rate, when the longitudinal slope gradient increases from 0.3% to 3.0%, the water skiing speed of small passenger cars decreases by about 2.68%.

Figure 6. Influence of longitudinal slope on hydroplaning speed

DownLoad: Full-Size Img PowerPoint

3.3 纵坡坡度与超高渐变率的影响程度比较

To compare the impact of longitudinal slope gradient and super-high gradient on the water skiing speed of small passenger cars, calculate the difference between the maximum and minimum water skiing speeds of small passenger cars under different longitudinal slope gradient conditions, and obtain the range of water skiing speed caused by longitudinal slope gradient. Similarly, obtain the range of water skiing speed caused by super-high gradient gradientFigure 7As shown. causeFigure 7It can be seen that under different rainfall intensities, the range of water skiing speed caused by longitudinal slope gradient and superelevation gradient is relatively close, but the influence of longitudinal slope gradient is always greater than that of superelevation gradient; As the intensity of rainfall increases, the impact of both on water skiing speed decreases and tends to flatten out.

Figure 7. Extreme values of hydroplaning speed

DownLoad: Full-Size Img PowerPoint

3.4 Consider limiting the speed of small passenger cars on a two-way four lane highway for water skiing

Table 4. Recommended limit speeds of car at superelevation transition section km·h^-1

降雨强度/(mm·h^-1)	纵坡坡度/%	超高渐变率
降雨强度/(mm·h^-1)	纵坡坡度/%	1/330	1/300	1/250	1/225	1/200
20	0.3	110	110	110	115	115
	1.0	110	110	110	110	110
	2.0	105	105	110	110	110
	3.0	105	105	105	110	110
40	0.3	105	105	105	105	105
	1.0	100	100	105	105	105
	2.0	100	100	100	100	105
	3.0	100	100	100	100	100
60	0.3	100	100	100	100	100
	1.0	100	100	100	100	100
	2.0	100	100	100	100	100
	3.0	95	100	100	100	100
80	0.3	100	100	100	100	100
	1.0	100	100	100	100	100
	2.0	95	100	100	100	100
	3.0	95	95	100	100	100

| Show Table

DownLoad: CSV

4. conclusion

(2) Analyzed the influence of longitudinal slope gradient and superelevation gradient on the water skiing speed of small passenger cars in the superelevation transition section. When the rainfall intensity is constant, the water skiing speed increases with the increase of the super-high gradient rate. The increase in longitudinal slope gradient leads to an increase in the length of the water flow path, which in turn reduces the speed of water skiing. The influence of longitudinal slope gradient on water skiing speed is greater than that of superelevation gradient rate, but as the rainfall intensity increases, the influence of longitudinal slope gradient and superelevation gradient rate on water skiing speed tends to be gentle.

(4) The study considered the influence of longitudinal slope gradient and geometric shape factors of superelevation gradient on water skiing speed. Further research is needed to consider the water skiing speed in the superelevation transition section of drainage facilities and heavy-duty vehicles.

References(31)

References

[1]	FENG Ting. The study of tire hydroplaning mechanism on wet road[D]. Qingdao: Qingdao University of Technology, 2018. (in Chinese)
[2]	DING Y M, WANG H. Computational investigation of hydroplaning risk of wide-base truck tyres on roadway[J]. International Journal of Pavement Engineering, 2020, 21(1): 122-133. doi: 10.1080/10298436.2018.1445249
[3]	WIES B, ROEGER B, MUNDL R. Influence of pattern void on hydroplaning and related target conflicts[J]. Tire Science and Technology, 2009, 37(3): 187-206. doi: 10.2346/1.3137087
[4]	ZHOU Hai-chao, JIANG Zhen, JIANG Bai-yu, et al. Optimization of tire tread pattern based on flow characteristics to improve hydroplaning resistance[J]. Proceedings of the Institution of Mechanical Engineers, Part D: Journal of Automobile Engineering, 2020, 234(13): 2961-2974. doi: 10.1177/0954407020932257
[5]	MARTIN C S. Hydrodynamics of tire hydroplaning[J]. Journal of Aircraft, 1967, 4(2): 136-140. doi: 10.2514/3.43810
[6]	ZHENG Bin-shuang, ZHU Sheng-ze, CHENG Yong-zhen, et al. Analysis on influence factors of adhesion characteristic of tire-asphalt pavement based on tire hydroplaning model[J]. Journal of Southeast University (Natural Science Edition), 2018, 48(4): 719-725. (in Chinese) https://www.cnki.com.cn/Article/CJFDTOTAL-DNDX201804019.htm
[7]	LIU Xiu-yu, CAO Qing-qing, ZHU Sheng-ze, et al. Numerical simulation of tire critical hydroplaning speed on asphalt pavement[J]. Journal of Southeast University (Natural Science Edition), 2017, 47(5): 1020-1025. (in Chinese) https://www.cnki.com.cn/Article/CJFDTOTAL-DNDX201705028.htm
[8]	ZHU Sheng-ze, LIU Xiu-yu, CAO Qing-qing, et al. Numerical study of tire hydroplaning based on power spectrum of asphalt pavement and kinetic friction coefficient[J]. Advances in Materials Science and Engineering, 2017, 2017: 5843061.
[9]	ZHENG Bin-shuang, HUANG Xiao-ming, ZHANG Wei-guang, et al. Adhesion characteristics of tire-asphalt pavement interface based on a proposed tire hydroplaning model[J]. Advances in Materials Science and Engineering, 2018, 2018: 5916180.
[10]	ONG G P, FWA T F. Prediction of wet-pavement skid resistance and hydroplaning potential[J]. Transportation Research Record, 2007, 2005: 160-171. doi: 10.3141/2005-17
[11]	ONG G P, FWA T F. Analysis of effectiveness of longitudinal grooving against hydroplaning[J]. Transportation Research Record, 2006, 1949: 112-125. doi: 10.1177/0361198106194900110
[12]	ONG G P, FWA T F, GUO J. Modeling hydroplaning and effects of pavement microtexture[J]. Transportation Research Record, 2005, 1905: 166-176. doi: 10.1177/0361198105190500118
[13]	DEHNAD M H, KHODAⅡ A. Effects of asphalt pavement texture on hydroplaning threshold speed[J]. Journal of Central South University, 2019, 26(1): 256-264. doi: 10.1007/s11771-019-3998-6
[14]	DEHNAD M H, KHODAⅡ A. Evaluating the effect of different asphalt mixtures on hydroplaning using a new lab-scale apparatus[J]. Petroleum Science and Technology, 2016, 34(20): 1726-1733. doi: 10.1080/10916466.2016.1221964
[15]	DONG Qiang-zhu, LI Yan-wei, SHI Xin, et al. Calculation and analysis of hydrodynamic pressure on road surface[J]. Journal of Chang'an University (Natural Science Edition), 2013, 33(5): 17-22. (in Chinese) https://www.cnki.com.cn/Article/CJFDTOTAL-XAGL201305005.htm
[16]	ZAKERZADEH M, ABTAHI S M, ALLAFCHIAN A, et al. Effectiveness of superhydrophobic material on the hydroplaning risk of asphalt pavements[J]. International Journal of Pavement Engineering, 2021, 22(12): 1592-1600. doi: 10.1080/10298436.2019.1704756
[17]	LIU Ming-wei, CHIAKI M, OEDA Y, et al. Modelling fundamental diagrams according to different water film depths from the perspective of the dynamic hydraulic pressure[J]. Scientific Reports, 2020, 10(1): 6496. doi: 10.1038/s41598-020-63381-1
[18]	CHU L J, FWA T F. Pavement skid resistance consideration in rain-related wet-weather speed limits determination[J]. Road Materials and Pavement Design, 2018, 19(2): 334-352. doi: 10.1080/14680629.2016.1261723
[19]	PLATI C, POMONI M, GEORGOULI K. Quantification of skid resistance seasonal variation in asphalt pavements[J]. Journal of Traffic and Transportation Engineering (English Edition), 2020, 7(2): 237-248. doi: 10.1016/j.jtte.2018.07.003
[20]	PENG J, CHU L, FWA T F. Determination of safe vehicle speeds on wet horizontal pavement curves[J]. Road Materials and Pavement Design, 2021, 22(11): 2641-2653. doi: 10.1080/14680629.2020.1772350
[21]	SPITZHÜTTL F, GOIZET F, UNGER T, et al. The real impact of full hydroplaning on driving safety[J]. Accident Analysis and Prevention, 2020, 138: 105458. doi: 10.1016/j.aap.2020.105458
[22]	DING Yang-min, WANG Hao. Evaluation of hydroplaning risk on permeable friction course using tire-water-pavement interaction model[J]. Transportation Research Record, 2018, 2672(40): 408-417. doi: 10.1177/0361198118781392
[23]	NAZARI A, CHEN L, BATTAGLIA F, et al. Prediction of hydroplaning potential using fully coupled finite element-computational fluid dynamics tire models[J]. Journal of Fluids Engineering, 2020, 142(10): 101202. doi: 10.1115/1.4047393
[24]	LI Qiang, ZHANG Zhuo, ZHANG Li. Calculation and research of hydroplaning critical velocity[J]. Journal of Chongqing Jiaotong University (Natural Science), 2011, 30(5): 989-993. (in Chinese) https://www.cnki.com.cn/Article/CJFDTOTAL-CQJT201105021.htm
[25]	JI Tian-jian, HUANG Xiao-ming, LIU Qing-quan. Part hydroplaning effect on pavement friction coefficient[J]. Journal of Traffic and Transportation Engineering, 2003, 3(4): 10-12. (in Chinese) http://transport.chd.edu.cn/article/id/200304003
[26]	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
[27]	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) https://www.cnki.com.cn/Article/CJFDTOTAL-ZGGL201512009.htm
[28]	ZHANG Zhuo, GAO Jian-ping. Longitudinal slope at super-elevation sections of S curve considering flow path length[J]. Journal of Chongqing Jiaotong University (Natural Science), 2013, 32(4): 594-596, 691. https://www.cnki.com.cn/Article/CJFDTOTAL-CQJT201304012.htm
[29]	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) doi: 10.19818/j.cnki.1671-1637.2010.05.010
[30]	PAN Xiao-dong, WUQiong, HU Peng, et al. Research on the method of changing the wheel tracks transverse distribution based on visual interference[J]. Highway Engineering, 2012, 37(2): 64-67. (in Chinese) https://www.cnki.com.cn/Article/CJFDTOTAL-ZNGL201202018.htm
[31]	WU Jian-jun, YUAN Cheng-song, ZHOU Zeng-kui, et al. Impact of short term heavy rainfall on the monitoring and forecast of sudden visibility descent[J]. Scientia Meteorologica Sinica, 2010, 30(2): 274-278. (in Chinese)

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Influence of geometric alignment of expressway superelevation transition section on hydroplaning speed of minibus

doi: 10.19818/j.cnki.1671-1637.2022.04.010