Eine Plattform für die Wissenschaft: Bauingenieurwesen, Architektur und Urbanistik
Eine Plattform für die Wissenschaft: Bauingenieurwesen, Architektur und Urbanistik
Field test validation of water film depth (WFD) prediction models for pavement surface drainage
During storm events, unsafe water film would be formed if the rainwater cannot rapidly drain off pavement surface, leading to potential hydroplaning. Therefore, estimation of water film depth (WFD) is a critical process in analysing pavement hydroplaning safety. A number of models have been developed to predict WFD with empirical or analytical methodologies based on surface texture properties, pavement slope, rainfall intensity, and pavement types. However, their effectiveness in WFD predictions has not been verified with field test data. This study attempts to design a field test to validate the effectiveness of four widely used WFD prediction models. To achieve this goal, pavement texture and geometry data are acquired by the LS-40 surface texture analyzer and SurPro3500 walking profiler, respectively. In order to measure the rainfall intensity and WFD, Pavement Drainage Measuring Instrument (PDMI) is developed in this study. Six test sites covering different pavement material, geometry and texture features, are selected in this study for WFD models validation. Finally the Dunnett’s test is utilized to verify the predicted WFDs for flexible and rigid pavement based on the field data. Results indicate that: (1) the WFDs obtained from empirical PAVDRN and Gallaway models are more accurate than other two models; (2) these two models are more suitable for WFDs estimation of flexible pavement than that of rigid pavement; (3) rainfall intensity calculated by 5 min rainfall duration covers the effect of rainfall on WFD better.
Field test validation of water film depth (WFD) prediction models for pavement surface drainage
During storm events, unsafe water film would be formed if the rainwater cannot rapidly drain off pavement surface, leading to potential hydroplaning. Therefore, estimation of water film depth (WFD) is a critical process in analysing pavement hydroplaning safety. A number of models have been developed to predict WFD with empirical or analytical methodologies based on surface texture properties, pavement slope, rainfall intensity, and pavement types. However, their effectiveness in WFD predictions has not been verified with field test data. This study attempts to design a field test to validate the effectiveness of four widely used WFD prediction models. To achieve this goal, pavement texture and geometry data are acquired by the LS-40 surface texture analyzer and SurPro3500 walking profiler, respectively. In order to measure the rainfall intensity and WFD, Pavement Drainage Measuring Instrument (PDMI) is developed in this study. Six test sites covering different pavement material, geometry and texture features, are selected in this study for WFD models validation. Finally the Dunnett’s test is utilized to verify the predicted WFDs for flexible and rigid pavement based on the field data. Results indicate that: (1) the WFDs obtained from empirical PAVDRN and Gallaway models are more accurate than other two models; (2) these two models are more suitable for WFDs estimation of flexible pavement than that of rigid pavement; (3) rainfall intensity calculated by 5 min rainfall duration covers the effect of rainfall on WFD better.
Field test validation of water film depth (WFD) prediction models for pavement surface drainage
Luo, Wenting (Autor:in) / Wang, Kelvin C. P. (Autor:in) / Li, Lin (Autor:in)
International Journal of Pavement Engineering ; 20 ; 1170-1181
03.10.2019
12 pages
Aufsatz (Zeitschrift)
Elektronische Ressource
Englisch
Surface drainage evaluation of asphalt pavement using a new analytical water film depth model
| Taylor & Francis Verlag | 2020
Validation Study of Road Surface Water Film Depth Prediction Model
| Trans Tech Publications | 2014
| Europäisches Patentamt | 2017