Flow resistance in fluvial open channels, especially in steep gravel-bed channels, still presents challenges to researchers and engineers. This article presents some new data from both the flume experiments and field ...Flow resistance in fluvial open channels, especially in steep gravel-bed channels, still presents challenges to researchers and engineers. This article presents some new data from both the flume experiments and field measurements. Data analysis using the divided hydraulic radius approach shows that the relative roughness plays a significant role in the bed form resistance. A new set of formulas that incorporate the relative roughness are proposed. As compared with several existing formulas, the proposed formulas can be used to better estimate the bed form resistance.展开更多
The calculation of speed prediction equations has been the subject of numerous researches in the past. The majority of them present models to predict free-flow speed in terms of the road geometry at the curved road se...The calculation of speed prediction equations has been the subject of numerous researches in the past. The majority of them present models to predict free-flow speed in terms of the road geometry at the curved road sections and more specifically in terms of the radiuses of the curves. Common characteristic is that none of them approaches the speed behavior of motorcycles since they are excluded from the datasets of the various studies. Instead, the models usually predict operating speed for other vehicle types such as passenger cars, vans, pickups and trucks. The present paper aims to cover this gap by developing speed prediction equations for motorcycles. For this purpose a new methodology is proposed while field measurements were carried out in order to obtain an adequate dataset of free-flow speeds along the curved sections of three different two lane rural roads. The aforementioned field measurements were conducted by two participants incorporating various road conditions (e.g. light conditions, experience level, familiarity with the routes). The ultimate target was the development of speed prediction equations by calculating the optimum regression curves between the curve radius’ and the corresponding velocities for the different road conditions. The research revealed that the proposed methodology could be used as a very useful tool to investigate motorcyclists’ behavior at curved road sections. Moreover it was feasible to draw conclusions correlating the speed adjustment with the various driving conditions.展开更多
基金Project supported by the National Natural Science Foundation of China(Grant No.50779082)the National Basic Research Program of China(973 Program,Grant No.2007CB407202)supported by the CSTC 2011
文摘Flow resistance in fluvial open channels, especially in steep gravel-bed channels, still presents challenges to researchers and engineers. This article presents some new data from both the flume experiments and field measurements. Data analysis using the divided hydraulic radius approach shows that the relative roughness plays a significant role in the bed form resistance. A new set of formulas that incorporate the relative roughness are proposed. As compared with several existing formulas, the proposed formulas can be used to better estimate the bed form resistance.
文摘The calculation of speed prediction equations has been the subject of numerous researches in the past. The majority of them present models to predict free-flow speed in terms of the road geometry at the curved road sections and more specifically in terms of the radiuses of the curves. Common characteristic is that none of them approaches the speed behavior of motorcycles since they are excluded from the datasets of the various studies. Instead, the models usually predict operating speed for other vehicle types such as passenger cars, vans, pickups and trucks. The present paper aims to cover this gap by developing speed prediction equations for motorcycles. For this purpose a new methodology is proposed while field measurements were carried out in order to obtain an adequate dataset of free-flow speeds along the curved sections of three different two lane rural roads. The aforementioned field measurements were conducted by two participants incorporating various road conditions (e.g. light conditions, experience level, familiarity with the routes). The ultimate target was the development of speed prediction equations by calculating the optimum regression curves between the curve radius’ and the corresponding velocities for the different road conditions. The research revealed that the proposed methodology could be used as a very useful tool to investigate motorcyclists’ behavior at curved road sections. Moreover it was feasible to draw conclusions correlating the speed adjustment with the various driving conditions.
