Raindrop Size Distribution (RSD) of tropical cyclone rainfall. 

Contexts in source publication

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... spires and floor roughness elements were used to simulate the target atmospheric boundary layer mean wind speed and turbulence intensity profiles. Preliminary validation of the wind flow was conducted through comparison of pressure measurements on building models to those obtained in the field and in conventional wind tunnel (Aly et al, 2011). In addition to the wind simulation, the raindrop size distribution (RSD) associated with tropical cyclone rain was simulated using agricultural spray nozzles placed behind the spires. ...

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... nozzle types were selected based on the range of drop sizes that they produce as compared to the target RSD derived from data collected during 2004 hurricane season. Figure 1 shows the target non-dimensional RSD curve and statistical values of gamma distribution parameters using combined RSD datasets from Hurricane Alex, Charley, and Gaston (2004). The field RSD data were acquired through Tropical Rainfall Measuring Mission (TRMM) at Wallops station, Wallops Island, Virginia, during Hurricane Alex (2004), Charley (2004), and Gaston (2004). ...

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... values of gamma distribution parameters using combined RSD datasets from Hurricane Alex, Charley, and Gaston (2004). The field RSD data were acquired through Tropical Rainfall Measuring Mission (TRMM) at Wallops station, Wallops Island, Virginia, during Hurricane Alex (2004), Charley (2004), and Gaston (2004). The normalized RSD shown in Fig. 1 was used to simulate wind-driven rain at different rain rates. The target wind-driven rain rate (sometimes referred as vertical rain rate: the mass flux of raindrops passing through a unit vertical area) was determined based the vertically falling rain rate spectrum during hurricanes as suggested by Lonfat et al (2004). For the ...

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... no slippage of wind flow over raindrops surface area, the lateral velocity of the raindrops was considered as the target wind speed and combined to the dimensional RSD to calculate the target wind-driven rate at that wind speed. Figure 2 presents the target wind-driven rain rate plot as a function of wind speed determined based of the RSD of Fig. 1 and a vertically falling rain rate of 25.4 mm/hr (1.0 in/hr). Once the target wind-driven rain rate and wind speed relationship was developed for the specified target RSD, the RSD was simulated in the experimental setup by manipulating the spray rate and the flow pressure using different types of spray nozzles. The simulation result ...

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... et al (2007) measured the wind-driven rain deposition on three low-rise buildings to provide data for model development and validation purposes. The measurements reported by Nore et al (2007) contained detailed meteorological measurements of wind and rain both on free- field and on building facades. The data collected were used to determine the distribution of raindrop accumulation on the buildings’ façades. The variation of wind direction during the wind-driven rain event was noted as an inherent challenge in assigning the ratios to a specific wind angle of attack. The wind direction for a measured rain distribution pattern on the buildings’ façade was determined by taking weighted average of wind direction based on wind speed and horizontal rain rate. Van-Mook (2002) also measured the rainwater accumulation on the west façade of the main building at the Eindhoven University of Technology (TUE). Driving- rain ratios were estimated at two locations on the building façade. Results showed wide dispersion of driving-rain ratios (50% of the mean values) as a function of reference wind velocity and horizontal rain rate (Van-Mook, 1999, 2002). A more extensive study of building exposure to wind-driven rain was conducted on five low-rise and three high-rise buildings located in British Columbia by Ge and Krpan (2009). The objective of the study was to improve the adequacy and use of a wind-driven rain index (wind-driven rain map) in the estimation of rain exposure during the design of building envelopes. The field measurement data suggested that wind-driven rain parameters such as catch ratios and/or wall factors (an alternative term for RAF) are not constant, but could vary with rain events (Ge and Krpan, 2007). The study also indicated that the presence of a 130mm overhang significantly reduced the catch ratios and wall factors on the building façade. Some early-time comprehensive review of wind-driven rain field measurements on building façades was published by Blocken and Carmeliet (2004) and Straube (1998). These field measurements and estimated RAF values demonstrated that the top edge and corners of a building are usually exposed to higher raindrop concentrations, which is largely attributed to the deflection of raindrops caused by the driving wind force as the consequence of the presence of the building itself. Section 2 covers methodology followed to acquire test-based data of wind-driven rain deposition on building façade with detailed descriptions of testing setup, simulation of tropical cyclone wind-driven rain, instrumentation, and testing protocol. Section 3 discusses the test results followed by some important deductions. The conclusions of the study along with summarized major findings are presented in Section 4. Prior to collecting test data of RAF and surface runoff rainwater on building façades, typical hurricane wind and wind-driven rain characteristics were simulated in the experimental setup to ensure a realistic representation in the test-based data for it to be applicable to the development of hurricane induced loss prediction models. Turbulent wind flow was generated using the newly built 12-fan Wall of Wind facility at Florida International University (FIU). Vertical spires and floor roughness elements were used to simulate the target atmospheric boundary layer mean wind speed and turbulence intensity profiles. Preliminary validation of the wind flow was conducted through comparison of pressure measurements on building models to those obtained in the field and in conventional wind tunnel (Aly et al, 2011). In addition to the wind simulation, 3 the raindrop size distribution (RSD) associated with tropical cyclone rain was simulated using agricultural spray nozzles placed behind the spires. The nozzle types were selected based on the range of drop sizes that they produce as compared to the target RSD derived from data collected during 2004 hurricane season. Figure 1 shows the target non-dimensional RSD curve and statistical values of gamma distribution parameters using combined RSD datasets from Hurricane Alex, Charley, and Gaston (2004). The field RSD data were acquired through Tropical Rainfall Measuring Mission (TRMM) at Wallops station, Wallops Island, Virginia, during Hurricane Alex (2004), Charley (2004), and Gaston (2004). The normalized RSD shown in Fig. 1 was used to simulate wind-driven rain at different rain rates. The target wind-driven rain rate (sometimes referred as vertical rain rate: the mass flux of raindrops passing through a unit vertical area) was determined based the vertically falling rain rate spectrum during hurricanes as suggested by Lonfat et al (2004). For the selected falling rain rate, the normalized RSD was converted to dimensional form using the liquid water content relationship derived used the combined dataset. Assuming no slippage of wind flow over raindrops surface area, the lateral velocity of the raindrops was considered as the target wind speed and combined to the dimensional RSD to calculate the target wind-driven rate at that wind speed. Figure 2 presents the target wind-driven rain rate plot as a function of wind speed determined based of the RSD of Fig. 1 and a vertically falling rain rate of 25.4 mm/hr (1.0 ...

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... et al (2007) measured the wind-driven rain deposition on three low-rise buildings to provide data for model development and validation purposes. The measurements reported by Nore et al (2007) contained detailed meteorological measurements of wind and rain both on free- field and on building facades. The data collected were used to determine the distribution of raindrop accumulation on the buildings’ façades. The variation of wind direction during the wind-driven rain event was noted as an inherent challenge in assigning the ratios to a specific wind angle of attack. The wind direction for a measured rain distribution pattern on the buildings’ façade was determined by taking weighted average of wind direction based on wind speed and horizontal rain rate. Van-Mook (2002) also measured the rainwater accumulation on the west façade of the main building at the Eindhoven University of Technology (TUE). Driving- rain ratios were estimated at two locations on the building façade. Results showed wide dispersion of driving-rain ratios (50% of the mean values) as a function of reference wind velocity and horizontal rain rate (Van-Mook, 1999, 2002). A more extensive study of building exposure to wind-driven rain was conducted on five low-rise and three high-rise buildings located in British Columbia by Ge and Krpan (2009). The objective of the study was to improve the adequacy and use of a wind-driven rain index (wind-driven rain map) in the estimation of rain exposure during the design of building envelopes. The field measurement data suggested that wind-driven rain parameters such as catch ratios and/or wall factors (an alternative term for RAF) are not constant, but could vary with rain events (Ge and Krpan, 2007). The study also indicated that the presence of a 130mm overhang significantly reduced the catch ratios and wall factors on the building façade. Some early-time comprehensive review of wind-driven rain field measurements on building façades was published by Blocken and Carmeliet (2004) and Straube (1998). These field measurements and estimated RAF values demonstrated that the top edge and corners of a building are usually exposed to higher raindrop concentrations, which is largely attributed to the deflection of raindrops caused by the driving wind force as the consequence of the presence of the building itself. Section 2 covers methodology followed to acquire test-based data of wind-driven rain deposition on building façade with detailed descriptions of testing setup, simulation of tropical cyclone wind-driven rain, instrumentation, and testing protocol. Section 3 discusses the test results followed by some important deductions. The conclusions of the study along with summarized major findings are presented in Section 4. Prior to collecting test data of RAF and surface runoff rainwater on building façades, typical hurricane wind and wind-driven rain characteristics were simulated in the experimental setup to ensure a realistic representation in the test-based data for it to be applicable to the development of hurricane induced loss prediction models. Turbulent wind flow was generated using the newly built 12-fan Wall of Wind facility at Florida International University (FIU). Vertical spires and floor roughness elements were used to simulate the target atmospheric boundary layer mean wind speed and turbulence intensity profiles. Preliminary validation of the wind flow was conducted through comparison of pressure measurements on building models to those obtained in the field and in conventional wind tunnel (Aly et al, 2011). In addition to the wind simulation, 3 the raindrop size distribution (RSD) associated with tropical cyclone rain was simulated using agricultural spray nozzles placed behind the spires. The nozzle types were selected based on the range of drop sizes that they produce as compared to the target RSD derived from data collected during 2004 hurricane season. Figure 1 shows the target non-dimensional RSD curve and statistical values of gamma distribution parameters using combined RSD datasets from Hurricane Alex, Charley, and Gaston (2004). The field RSD data were acquired through Tropical Rainfall Measuring Mission (TRMM) at Wallops station, Wallops Island, Virginia, during Hurricane Alex (2004), Charley (2004), and Gaston (2004). The normalized RSD shown in Fig. 1 was used to simulate wind-driven rain at different rain rates. The target wind-driven rain rate (sometimes referred as vertical rain rate: the mass flux of raindrops passing through a unit vertical area) was determined based the vertically falling rain rate spectrum during hurricanes as suggested by Lonfat et al (2004). For the selected falling rain rate, the normalized RSD was converted to dimensional form using the liquid water content relationship derived used the combined dataset. Assuming no slippage of wind flow over raindrops surface area, the lateral velocity of the raindrops was considered as the target wind speed and combined to the dimensional RSD to calculate the target wind-driven rate at that wind speed. Figure 2 presents the target wind-driven rain rate plot as a function of wind speed determined based of the RSD of Fig. 1 and a vertically falling rain rate of 25.4 mm/hr (1.0 ...

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... et al (2007) measured the wind-driven rain deposition on three low-rise buildings to provide data for model development and validation purposes. The measurements reported by Nore et al (2007) contained detailed meteorological measurements of wind and rain both on free- field and on building facades. The data collected were used to determine the distribution of raindrop accumulation on the buildings’ façades. The variation of wind direction during the wind-driven rain event was noted as an inherent challenge in assigning the ratios to a specific wind angle of attack. The wind direction for a measured rain distribution pattern on the buildings’ façade was determined by taking weighted average of wind direction based on wind speed and horizontal rain rate. Van-Mook (2002) also measured the rainwater accumulation on the west façade of the main building at the Eindhoven University of Technology (TUE). Driving- rain ratios were estimated at two locations on the building façade. Results showed wide dispersion of driving-rain ratios (50% of the mean values) as a function of reference wind velocity and horizontal rain rate (Van-Mook, 1999, 2002). A more extensive study of building exposure to wind-driven rain was conducted on five low-rise and three high-rise buildings located in British Columbia by Ge and Krpan (2009). The objective of the study was to improve the adequacy and use of a wind-driven rain index (wind-driven rain map) in the estimation of rain exposure during the design of building envelopes. The field measurement data suggested that wind-driven rain parameters such as catch ratios and/or wall factors (an alternative term for RAF) are not constant, but could vary with rain events (Ge and Krpan, 2007). The study also indicated that the presence of a 130mm overhang significantly reduced the catch ratios and wall factors on the building façade. Some early-time comprehensive review of wind-driven rain field measurements on building façades was published by Blocken and Carmeliet (2004) and Straube (1998). These field measurements and estimated RAF values demonstrated that the top edge and corners of a building are usually exposed to higher raindrop concentrations, which is largely attributed to the deflection of raindrops caused by the driving wind force as the consequence of the presence of the building itself. Section 2 covers methodology followed to acquire test-based data of wind-driven rain deposition on building façade with detailed descriptions of testing setup, simulation of tropical cyclone wind-driven rain, instrumentation, and testing protocol. Section 3 discusses the test results followed by some important deductions. The conclusions of the study along with summarized major findings are presented in Section 4. Prior to collecting test data of RAF and surface runoff rainwater on building façades, typical hurricane wind and wind-driven rain characteristics were simulated in the experimental setup to ensure a realistic representation in the test-based data for it to be applicable to the development of hurricane induced loss prediction models. Turbulent wind flow was generated using the newly built 12-fan Wall of Wind facility at Florida International University (FIU). Vertical spires and floor roughness elements were used to simulate the target atmospheric boundary layer mean wind speed and turbulence intensity profiles. Preliminary validation of the wind flow was conducted through comparison of pressure measurements on building models to those obtained in the field and in conventional wind tunnel (Aly et al, 2011). In addition to the wind simulation, 3 the raindrop size distribution (RSD) associated with tropical cyclone rain was simulated using agricultural spray nozzles placed behind the spires. The nozzle types were selected based on the range of drop sizes that they produce as compared to the target RSD derived from data collected during 2004 hurricane season. Figure 1 shows the target non-dimensional RSD curve and statistical values of gamma distribution parameters using combined RSD datasets from Hurricane Alex, Charley, and Gaston (2004). The field RSD data were acquired through Tropical Rainfall Measuring Mission (TRMM) at Wallops station, Wallops Island, Virginia, during Hurricane Alex (2004), Charley (2004), and Gaston (2004). The normalized RSD shown in Fig. 1 was used to simulate wind-driven rain at different rain rates. The target wind-driven rain rate (sometimes referred as vertical rain rate: the mass flux of raindrops passing through a unit vertical area) was determined based the vertically falling rain rate spectrum during hurricanes as suggested by Lonfat et al (2004). For the selected falling rain rate, the normalized RSD was converted to dimensional form using the liquid water content relationship derived used the combined dataset. Assuming no slippage of wind flow over raindrops surface area, the lateral velocity of the raindrops was considered as the target wind speed and combined to the dimensional RSD to calculate the target wind-driven rate at that wind speed. Figure 2 presents the target wind-driven rain rate plot as a function of wind speed determined based of the RSD of Fig. 1 and a vertically falling rain rate of 25.4 mm/hr (1.0 ...