Construction of debris flow protection structures is impossible without studying the processes first. Therefore, the purpose of this research was to calculate the magnitude of debris flows in three study areas. Initia...Construction of debris flow protection structures is impossible without studying the processes first. Therefore, the purpose of this research was to calculate the magnitude of debris flows in three study areas. Initial information was provided by JSC Sevkavgiprovodkhoz and the Research Center “Geodinamika”. The first object of this research was the river Ardon and its tributary the Buddon, because of disastrous consequences for Mizur village of passed debris flows and floods. Modeling of unsteady water movement was carried out for estimation of potential flooding. During modeling, 5 cases of flash floods and debris flows of various probabilities from 0.5% to 1% percent were considered. Therefore, maximum floods for the cross-sections above and in the Mizur village itself were obtained. The second study area was the Chat-Bash stream, which is also situated in the north of Caucasus mountains. For this stream, the maximum discharge that could impact the mining complex at Tyrnyauz was determined. The third study area was the Krasnoselskaia river due to frequent floods in Yuzhno-Sakhalinsk. Applying three cases of various probabilities from 10% to 0.1%, the model determined maximum discharge and water level for the last cross-section above confluence into the Susuya river. Numerical experiments for all study areas with different roughness values were conducted to identify optimal ones. Comparing the model results for all study areas with empirical formulas (Golubcov V.V., Herheulidze I.I., Kkhann, Sribnyj and ASFS of EMERCOM of Russia) revealed that formulas contain only average depth slope angle and empirical coefficients and do not allow estimating flood areas and maximum characteristics of the event with a certain degree of accuracy.展开更多
为提高智能网联(connected and automated,CA)卡车、小车及人工驾驶卡车、小车的混合流道路通行能力,提出基于排强度和渗透率的CA车辆单独编队和合作编队策略.分别设计两种策略下混合流车辆跟驰模式,推导出基于改进Markov模型,涵盖CA车...为提高智能网联(connected and automated,CA)卡车、小车及人工驾驶卡车、小车的混合流道路通行能力,提出基于排强度和渗透率的CA车辆单独编队和合作编队策略.分别设计两种策略下混合流车辆跟驰模式,推导出基于改进Markov模型,涵盖CA车辆渗透率和排强度的车辆状态转移概率;分析两种策略下CA车辆队列分布,建立各策略下的混合流道路容量模型,并通过理论证明和仿真实验予以验证.结果表明,与不编队策略相比,两种策略下道路容量分别提高1.23%~49.62%和1.47%~60.34%,合作编队策略与单独编队策略相比能将道路容量再提高11%;当CA车辆渗透率大于50%和排强度大于0时,编队策略对道路容量的提升效果更显著,容量能提高13.27%~60.34%;单独编队策略下CA小车和CA卡车最大队列规模分别为8辆和6辆,合作编队下CA车辆最大队列规模为8辆.展开更多
This paper integrates the maximum information principle with the Cell Transmission Model （CTM） to formulate the velocity distribution evolution of vehicle traffic flow. The proposed discrete traffic kinetic model us...This paper integrates the maximum information principle with the Cell Transmission Model （CTM） to formulate the velocity distribution evolution of vehicle traffic flow. The proposed discrete traffic kinetic model uses the cell transmission model to calculate the macroscopic variables of the vehicle transmission, and the maximum information principle to examine the velocity distribution in each cell. The velocity distribution based on maximum information principle is solved by the Lagrange multiplier method. The advantage of the proposed model is that it can simultaneously calculate the hydrodynamic variables and velocity distribution at the cell level. An example shows how the proposed model works. The proposed model is a hybrid traffic simulation model, which can be used to understand the self-organization phenomena in traffic flows and predict the traffic evolution.展开更多
文摘Construction of debris flow protection structures is impossible without studying the processes first. Therefore, the purpose of this research was to calculate the magnitude of debris flows in three study areas. Initial information was provided by JSC Sevkavgiprovodkhoz and the Research Center “Geodinamika”. The first object of this research was the river Ardon and its tributary the Buddon, because of disastrous consequences for Mizur village of passed debris flows and floods. Modeling of unsteady water movement was carried out for estimation of potential flooding. During modeling, 5 cases of flash floods and debris flows of various probabilities from 0.5% to 1% percent were considered. Therefore, maximum floods for the cross-sections above and in the Mizur village itself were obtained. The second study area was the Chat-Bash stream, which is also situated in the north of Caucasus mountains. For this stream, the maximum discharge that could impact the mining complex at Tyrnyauz was determined. The third study area was the Krasnoselskaia river due to frequent floods in Yuzhno-Sakhalinsk. Applying three cases of various probabilities from 10% to 0.1%, the model determined maximum discharge and water level for the last cross-section above confluence into the Susuya river. Numerical experiments for all study areas with different roughness values were conducted to identify optimal ones. Comparing the model results for all study areas with empirical formulas (Golubcov V.V., Herheulidze I.I., Kkhann, Sribnyj and ASFS of EMERCOM of Russia) revealed that formulas contain only average depth slope angle and empirical coefficients and do not allow estimating flood areas and maximum characteristics of the event with a certain degree of accuracy.
文摘为提高智能网联(connected and automated,CA)卡车、小车及人工驾驶卡车、小车的混合流道路通行能力,提出基于排强度和渗透率的CA车辆单独编队和合作编队策略.分别设计两种策略下混合流车辆跟驰模式,推导出基于改进Markov模型,涵盖CA车辆渗透率和排强度的车辆状态转移概率;分析两种策略下CA车辆队列分布,建立各策略下的混合流道路容量模型,并通过理论证明和仿真实验予以验证.结果表明,与不编队策略相比,两种策略下道路容量分别提高1.23%~49.62%和1.47%~60.34%,合作编队策略与单独编队策略相比能将道路容量再提高11%;当CA车辆渗透率大于50%和排强度大于0时,编队策略对道路容量的提升效果更显著,容量能提高13.27%~60.34%;单独编队策略下CA小车和CA卡车最大队列规模分别为8辆和6辆,合作编队下CA车辆最大队列规模为8辆.
基金Project supported by the National Natural Science Foundation of China(Grant No.71071024)the Hunan Provincial Natural Science Foundation(Grant No.12JJ2025)
文摘This paper integrates the maximum information principle with the Cell Transmission Model （CTM） to formulate the velocity distribution evolution of vehicle traffic flow. The proposed discrete traffic kinetic model uses the cell transmission model to calculate the macroscopic variables of the vehicle transmission, and the maximum information principle to examine the velocity distribution in each cell. The velocity distribution based on maximum information principle is solved by the Lagrange multiplier method. The advantage of the proposed model is that it can simultaneously calculate the hydrodynamic variables and velocity distribution at the cell level. An example shows how the proposed model works. The proposed model is a hybrid traffic simulation model, which can be used to understand the self-organization phenomena in traffic flows and predict the traffic evolution.
