scholarly journals Effect of discharge and upstream jam angle on the flow distribution beneath a simulated ice jam

2019 ◽  
Vol 46 (5) ◽  
pp. 413-423 ◽  
Author(s):  
Baafour Nyantekyi-Kwakye ◽  
Tanzim Ahmed ◽  
Shawn P. Clark ◽  
Mark F. Tachie ◽  
Karen Dow
Keyword(s):  
Pressure Gradient ◽  
Power Law ◽  
Reynolds Shear Stress ◽  
Measurement Techniques ◽  
Adverse Pressure Gradient ◽  
Mean Bias Error ◽  
Bias Error ◽  
Particle Image Velocimetry System ◽  
Ice Jam ◽  
Two Parameter

The velocity field beneath simulated rough ice jams under various upstream jam angles and discharge were investigated using a particle image velocimetry system. Three discharges were examined at 2.3 L/s, 3.4 L/s, and 4.0 L/s and two upstream ice jam angles were tested at 4° and 6°. Increasing the discharge resulted in high turbulence production beneath the jam. The adverse pressure gradient exerted on the flow increased the levels of the Reynolds shear stress. The measured velocities beneath the jam were used to assess the performances of three traditional field measurement techniques as well as the validity of the two-parameter power law. The two-point measurement technique performed remarkably well with the least mean bias error of 2.0%. The error associated with the different techniques showed their inability to accurately predict the average velocity under high discharge. The two-parameter power law accurately predicted velocity profiles within the equilibrium section of the jam, but failed within the boundary layers when the flow was subjected to a pressure gradient.

Errors and Uncertainties in Microwave Link Rainfall Estimation Explored Using Drop Size Measurements and High-Resolution Radar Data

2010 ◽  
Vol 11 (6) ◽  
pp. 1330-1344 ◽  
Author(s):  
Hidde Leijnse ◽  
Remko Uijlenhoet ◽  
Alexis Berne
Keyword(s):  
High Resolution ◽  
Power Law ◽  
Radar Data ◽  
Mean Bias Error ◽  
Bias Error ◽  
Error Statistics ◽  
Link Length ◽  
Taylor’S Hypothesis ◽  
High Resolution Radar ◽  
Microwave Link

Abstract Microwave links can be used for the estimation of path-averaged rainfall by using either the path-integrated attenuation or the difference in attenuation of two signals with different frequencies and/or polarizations. Link signals have been simulated using measured time series of raindrop size distributions (DSDs) over a period of nearly 2 yr, in combination with wind velocity data and Taylor’s hypothesis. For this purpose, Taylor’s hypothesis has been tested using more than 1.5 yr of high-resolution radar data. In terms of correlation between spatial and temporal profiles of rainfall intensities, the validity of Taylor’s hypothesis quickly decreases with distance. However, in terms of error statistics, the hypothesis is seen to hold up to distances of at least 10 km. Errors and uncertainties (mean bias error and root-mean-square error, respectively) in microwave link rainfall estimates due to spatial DSD variation are at a minimum at frequencies (and frequency combinations) where the power-law relation for the conversion to rainfall intensity is close to linear. Errors generally increase with link length, whereas uncertainties decrease because of the decrease of scatter about the retrieval relations because of averaging of spatially variable DSDs for longer links. The exponent of power-law rainfall retrieval relations can explain a large part of the variation in both bias and uncertainty, which means that the order of magnitude of these error statistics can be predicted from the value of this exponent, regardless of the link length.

PIV Study of Adverse and Favorable Pressure Gradient Turbulent Flows Over Transverse Ribs

2008 ◽  
Vol 130 (11) ◽  
Author(s):  
M. Agelinchaab ◽  
M. F. Tachie
Keyword(s):  
Pressure Gradient ◽  
Turbulent Flows ◽  
Reynolds Shear Stress ◽  
Adverse Pressure Gradient ◽  
Bottom Wall ◽  
Combined Effects ◽  
Mean Flow ◽  
Turbulent Statistics ◽  
Favorable Pressure Gradient ◽  
The Mean

This paper reports an experimental study of the combined effects of rib roughness and pressure gradient on turbulent flows produced in asymmetric converging and diverging channels. Transverse square ribs with pitch-to-height ratio of 4 were attached to the bottom wall of the channel to produce the rib roughness. A particle image velocimetry technique was used to conduct measurements at several streamwise-transverse planes located upstream, within, and downstream of the converging and diverging sections of the channel. From these measurements, the mean velocities and turbulent statistics at the top plane of the ribs and across the channel were obtained. The data revealed non-negligible wall-normal motion and interaction between the cavities and overlying boundary layers. The different drag characteristics of the rough bottom wall and the smooth top wall produced asymmetric distributions of mean velocity and turbulent statistics across the channel. The asymmetry of these profiles is most extreme in the presence of adverse pressure gradient. Because of the manner in which pressure gradient modifies the mean flow and turbulence production, it was found that the streamwise turbulence intensity and Reynolds shear stress in the vicinity of the ribs are lower in the adverse pressure gradient than in the favorable pressure gradient channel. The results show also that the combined effects of rib roughness and adverse pressure gradient on the turbulent intensity statistics are significantly higher than when roughness and adverse pressure gradient are applied in isolation.

Turbulent Boundary Layer With Negligible Wall Stress

2008 ◽  
Vol 130 (5) ◽  
Author(s):  
Noor Afzal
Keyword(s):  
Boundary Layer ◽  
Turbulent Boundary Layer ◽  
Pressure Gradient ◽  
Power Law ◽  
Asymptotic Expansions ◽  
Kinematic Viscosity ◽  
Adverse Pressure Gradient ◽  
Power Laws ◽  
Outer Flow ◽  
Half Power

The turbulent boundary layer subjected to strong adverse pressure gradient near the separation region has been analyzed at large Reynolds numbers by the method of matched asymptotic expansions. The two regions consisting of outer nonlinear wake layer and inner wall layer are analyzed in terms of pressure scaling velocities Up=(νp′∕ρ)1∕3 in the wall region and Uδ=(δp′∕ρ)1∕2 in the outer wake region, where p′ is the streamwise pressure gradient and ρ is the fluid density. In this work, the variables δ, the outer boundary layer thickness, and Uδ, the outer velocity scale, are independent of ν, the molecular kinematic viscosity, which is a better model of fully developed mean turbulent flow. The asymptotic expansions have been matched by Izakson–Millikan–Kolmogorov hypothesis leading to open functional equations. The solution for the velocity distribution gives new composite log-half-power laws, based on the pressure scales, providing a better model of the flow, where the outer composite log-half-power law does not depend on the molecular kinematic viscosity. These new composite laws are better and one may be benefited from their limiting relations that for weak pressure gradient yield the traditional logarithmic laws and for strong adverse pressure gradient yield the half-power laws. During matching of the nonlinear outer layer two cases arise: One where Uδ∕Ue is small and second where Uδ∕Ue of order unity (where Ue is the velocity at the edge of the boundary layer). In the first case, the lowest order nonlinear outer flow under certain conditions shows equilibrium. The outer flow subjected to the constant eddy viscosity closure model is governed by the Falkner–Skan equation subjected to the matching condition of finite slip velocity on the surface. The jet- and wakelike solutions are presented, where the zero velocity slip implying the point of separation, which compares well with Coles traditional wake function. In the second case, higher order terms in the asymptotic solutions for nearly separating flow have been estimated. The proposed composite log-half-power law solution and the limiting half-power law have been well supported by extensive experimental and direct numerical simulation data. For moderate values of the pressure gradient the data show that the proposed composite log-half-power laws are a better model of the flow.

The structure of wall-pressure fluctuations in turbulent boundary layers with adverse pressure gradient and separation

1998 ◽  
Vol 377 ◽  
pp. 347-373 ◽  
Author(s):  
Y. NA ◽  
P. MOIN
Keyword(s):  
Boundary Layer ◽  
Pressure Gradient ◽  
Separation Bubble ◽  
Reynolds Shear Stress ◽  
Pressure Fluctuations ◽  
Adverse Pressure Gradient ◽  
Wall Pressure ◽  
Spanwise Direction ◽  
Frequency Spectra ◽  
Wall Pressure Fluctuations

Space–time correlations and frequency spectra of wall-pressure fluctuations, obtained from direct numerical simulation, are examined to reveal the effects of pressure gradient and separation on the characteristics of wall-pressure fluctuations. In the attached boundary layer subjected to adverse pressure gradient, contours of constant two-point spatial correlation of wall-pressure fluctuations are more elongated in the spanwise direction. Convection velocities of wall-pressure fluctuations as a function of spatial and temporal separations are reduced by the adverse pressure gradient. In the separated turbulent boundary layer, wall-pressure fluctuations are reduced inside the separation bubble, and enhanced downstream of the reattachment region where maximum Reynolds stresses occur. Inside the separation bubble, the frequency spectra of wall-pressure fluctuations normalized by the local maximum Reynolds shear stress correlate well compared to those normalized by free-stream dynamic pressure, indicating that local Reynolds shear stress has more direct influence on the wall-pressure spectra. Contour plots of two-point correlation of wall-pressure fluctuations are highly elongated in the spanwise direction inside the separation bubble, implying the presence of large two-dimensional roller-type structures. The convection velocity determined from the space–time correlation of wall-pressure fluctuations is as low as 0.33U0 (U0 is the maximum inlet velocity) in the separated zone, and increases downstream of reattachment.

PIV Study of Turbulent Flow in Asymmetric Converging and Diverging Channels

2008 ◽  
Vol 130 (1) ◽  
Author(s):  
M. K. Shah ◽  
M. F. Tachie
Keyword(s):  
Turbulent Flow ◽  
Pressure Gradient ◽  
Turbulent Flows ◽  
Reynolds Shear Stress ◽  
Lower Boundary ◽  
Adverse Pressure Gradient ◽  
Pressure Gradients ◽  
Mean Flow ◽  
The Mean ◽  
Converging And Diverging Channels

An experimental investigation of turbulent flow subjected to variable adverse and favorable pressure gradients in two-dimensional asymmetric channels is reported. The floors of the diverging and converging channels were flat while the roofs of the channels were curved. Adverse pressure gradient flows at Reh=27,050 and 12,450 and favorable pressure gradient flow at Reh=19,280 were studied. A particle image velocimetry was used to conduct detailed measurements at several planes upstream, within the variable section and within the downstream sections. The boundary layer parameters were obtained in the upper and lower boundary layers to study the effects of pressure gradients on the development of the mean flow on the floor and roof of the channels. The profiles of the mean velocities, turbulence intensities, Reynolds shear stress, mixing length, eddy viscosity, and turbulence production were also obtained to document the salient features of pressure gradient turbulent flows in asymmetric converging and diverging channels.

scholarly journals Correction of Eddy Covariance Based Crop ET Considering the Heat Flux Source Area

Atmosphere ◽  
2021 ◽  
Vol 12 (2) ◽  
pp. 281
Author(s):  
Stuart L. Joy ◽  
José L. Chávez
Keyword(s):  
Heat Flux ◽  
Eddy Covariance ◽  
Agricultural Land ◽  
Flux Measurement ◽  
Source Area ◽  
Mean Bias Error ◽  
Bias Error ◽  
Crop Water ◽  
The Past ◽  
Measurement Results

Eddy covariance (EC) systems are being used to measure sensible heat (H) and latent heat (LE) fluxes in order to determine crop water use or evapotranspiration (ET). The reliability of EC measurements depends on meeting certain meteorological assumptions; the most important of such are horizontal homogeneity, stationarity, and non-advective conditions. Over heterogeneous surfaces, the spatial context of the measurement must be known in order to properly interpret the magnitude of the heat flux measurement results. Over the past decades, there has been a proliferation of ‘heat flux source area’ (i.e., footprint) modeling studies, but only a few have explored the accuracy of the models over heterogeneous agricultural land. A composite ET estimate was created by using the estimated footprint weights for an EC system in the upwind corner of four fields and separate ET estimates from each of these fields. Three analytical footprint models were evaluated by comparing the composite ET to the measured ET. All three models performed consistently well, with an average mean bias error (MBE) of about −0.03 mm h−1 (−4.4%) and root mean square error (RMSE) of 0.09 mm h−1 (10.9%). The same three footprint models were then used to adjust the EC-measured ET to account for the fraction of the footprint that extended beyond the field of interest. The effectiveness of the footprint adjustment was determined by comparing the adjusted ET estimates with the lysimetric ET measurements from within the same field. This correction decreased the absolute hourly ET MBE by 8%, and the RMSE by 1%.

scholarly journals CO2 Flux over the Contiguous United States in 2016 Inverted by WRF-Chem/DART from OCO-2 XCO2 Retrievals

2021 ◽  
Vol 13 (15) ◽  
pp. 2996
Author(s):  
Qinwei Zhang ◽  
Mingqi Li ◽  
Maohua Wang ◽  
Arthur Paul Mizzi ◽  
Yongjian Huang ◽  
...  
Keyword(s):  
United States ◽  
Spatial Resolution ◽  
High Spatial Resolution ◽  
Co2 Flux ◽  
Total Carbon ◽  
Mean Bias Error ◽  
Bias Error ◽  
Parallel Experiment ◽  
Concentration Measurements ◽  
Global Stocktake

High spatial resolution carbon dioxide (CO2) flux inversion systems are needed to support the global stocktake required by the Paris Agreement and to complement the bottom-up emission inventories. Based on the work of Zhang, a regional CO2 flux inversion system capable of assimilating the column-averaged dry air mole fractions of CO2 (XCO2) retrieved from Orbiting Carbon Observatory-2 (OCO-2) observations had been developed. To evaluate the system, under the constraints of the initial state and boundary conditions extracted from the CarbonTracker 2017 product (CT2017), the annual CO2 flux over the contiguous United States in 2016 was inverted (1.08 Pg C yr−1) and compared with the corresponding posterior CO2 fluxes extracted from OCO-2 model intercomparison project (OCO-2 MIP) (mean: 0.76 Pg C yr−1, standard deviation: 0.29 Pg C yr−1, 9 models in total) and CT2017 (1.19 Pg C yr−1). The uncertainty of the inverted CO2 flux was reduced by 14.71% compared to the prior flux. The annual mean XCO2 estimated by the inversion system was 403.67 ppm, which was 0.11 ppm smaller than the result (403.78 ppm) simulated by a parallel experiment without assimilating the OCO-2 retrievals and closer to the result of CT2017 (403.29 ppm). Independent CO2 flux and concentration measurements from towers, aircraft, and Total Carbon Column Observing Network (TCCON) were used to evaluate the results. Mean bias error (MBE) between the inverted CO2 flux and flux measurements was 0.73 g C m−2 d−1, was reduced by 22.34% and 28.43% compared to those of the prior flux and CT2017, respectively. MBEs between the CO2 concentrations estimated by the inversion system and concentration measurements from TCCON, towers, and aircraft were reduced by 52.78%, 96.45%, and 75%, respectively, compared to those of the parallel experiment. The experiment proved that CO2 emission hotspots indicated by the inverted annual CO2 flux with a relatively high spatial resolution of 50 km consisted well with the locations of most major metropolitan/urban areas in the contiguous United States, which demonstrated the potential of combing satellite observations with high spatial resolution CO2 flux inversion system in supporting the global stocktake.

scholarly journals Hourly Ground-Level PM2.5 Estimation Using Geostationary Satellite and Reanalysis Data via Deep Learning

2021 ◽  
Vol 13 (11) ◽  
pp. 2121
Author(s):  
Changsuk Lee ◽  
Kyunghwa Lee ◽  
Sangmin Kim ◽  
Jinhyeok Yu ◽  
Seungtaek Jeong ◽  
...  
Keyword(s):  
Cross Validation ◽  
Ground Level ◽  
Reanalysis Data ◽  
Training Dataset ◽  
Coefficient Of Determination ◽  
Mean Bias Error ◽  
Bias Error ◽  
Air Quality Model ◽  
Quality Model ◽  
Near Surface

This study proposes an improved approach for monitoring the spatial concentrations of hourly particulate matter less than 2.5 μm in diameter (PM2.5) via a deep neural network (DNN) using geostationary ocean color imager (GOCI) images and unified model (UM) reanalysis data over the Korean Peninsula. The DNN performance was optimized to determine the appropriate training model structures, incorporating hyperparameter tuning, regularization, early stopping, and input and output variable normalization to prevent training dataset overfitting. Near-surface atmospheric information from the UM was also used as an input variable to spatially generalize the DNN model. The retrieved PM2.5 from the DNN was compared with estimates from random forest, multiple linear regression, and the Community Multiscale Air Quality model. The DNN demonstrated the highest accuracy compared to that of the conventional methods for the hold-out validation (root mean square error (RMSE) = 7.042 μg/m3, mean bias error (MBE) = −0.340 μg/m3, and coefficient of determination (R2) = 0.698) and the cross-validation (RMSE = 9.166 μg/m3, MBE = 0.293 μg/m3, and R2 = 0.49). Although the R2 was low due to underestimated high PM2.5 concentration patterns, the RMSE and MBE demonstrated reliable accuracy values (<10 μg/m3 and 1 μg/m3, respectively) for the hold-out validation and cross-validation.

scholarly journals Evaluation of NASA POWER Reanalysis Products to Estimate Daily Weather Variables in a Hot Summer Mediterranean Climate

Agronomy ◽  
2021 ◽  
Vol 11 (6) ◽  
pp. 1207
Author(s):  
Gonçalo C. Rodrigues ◽  
Ricardo P. Braga
Keyword(s):  
Wind Speed ◽  
Bias Correction ◽  
Goodness Of Fit ◽  
Mediterranean Climate ◽  
Weather Data ◽  
Coefficient Of Determination ◽  
Mean Bias Error ◽  
Bias Error ◽  
Weather Variables ◽  
Weather Stations

This study aims to evaluate NASA POWER reanalysis products for daily surface maximum (Tmax) and minimum (Tmin) temperatures, solar radiation (Rs), relative humidity (RH) and wind speed (Ws) when compared with observed data from 14 distributed weather stations across Alentejo Region, Southern Portugal, with a hot summer Mediterranean climate. Results showed that there is good agreement between NASA POWER reanalysis and observed data for all parameters, except for wind speed, with coefficient of determination (R2) higher than 0.82, with normalized root mean square error (NRMSE) varying, from 8 to 20%, and a normalized mean bias error (NMBE) ranging from –9 to 26%, for those variables. Based on these results, and in order to improve the accuracy of the NASA POWER dataset, two bias corrections were performed to all weather variables: one for the Alentejo Region as a whole; another, for each location individually. Results improved significantly, especially when a local bias correction is performed, with Tmax and Tmin presenting an improvement of the mean NRMSE of 6.6 °C (from 8.0 °C) and 16.1 °C (from 20.5 °C), respectively, while a mean NMBE decreased from 10.65 to 0.2%. Rs results also show a very high goodness of fit with a mean NRMSE of 11.2% and mean NMBE equal to 0.1%. Additionally, bias corrected RH data performed acceptably with an NRMSE lower than 12.1% and an NMBE below 2.1%. However, even when a bias correction is performed, Ws lacks the performance showed by the remaining weather variables, with an NRMSE never lower than 19.6%. Results show that NASA POWER can be useful for the generation of weather data sets where ground weather stations data is of missing or unavailable.

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