log law
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2021 ◽  
Vol 2021 ◽  
pp. 1-15
Author(s):  
Kai Wang ◽  
Yun Guo ◽  
Xu Wang

The study of typhoon wind profiles, especially offshore typhoon wind profiles, has been constrained by the scarcity of observational data. In this study, the Doppler wind lidar was used to observe the offshore wind profiles during Super Typhoon Mangkhut and onshore wind profiles during Super Typhoon Lekima. Four wind profile models, including the power law, logarithmic law, Deaves–Harris (D-H), and Gryning, were selected in the height range of 0–300 m to fit the wind profile. The variations in the power exponent with the mean wind speed and roughness length were also analyzed. The results showed that the wind profiles fitted by the four models were generally in good agreement with the observed wind profiles with correlation coefficients greater than 0.98 and root mean square deviations less than 0.5 m s−1. For the offshore case, the fitting degree of all wind profile models improved with increasing mean wind speed. Specifically, the D-H model had the highest fitting degree when the horizontal mean wind speed at 40 m was in the range of 8–25 m s−1, while the log-law model had the highest fitting degree when the wind speed exceeded 30 m s−1. For the onshore case, the fitting degree of the four wind profile models deteriorated with increasing mean wind speed, and the log-law model had the highest fitting degree in all wind speed intervals from 8 to 30 m s−1. For both offshore and onshore cases, the power exponent was less affected by mean wind speed and increased with increasing roughness length, and the logarithmic empirical model proposed in this study could well characterize the relationship between the power exponent and roughness length.


2021 ◽  
Vol 91 ◽  
pp. 108857
Author(s):  
Andrew D. Bragg ◽  
Yixiang Liao ◽  
Jochen Fröhlich ◽  
Tian Ma
Keyword(s):  

2021 ◽  
Vol 918 ◽  
Author(s):  
Tobias Knopp ◽  
N. Reuther ◽  
M. Novara ◽  
D. Schanz ◽  
E. Schülein ◽  
...  

Abstract


Water ◽  
2020 ◽  
Vol 12 (10) ◽  
pp. 2753
Author(s):  
Liyuan Zhang ◽  
Faxing Zhang ◽  
Ailing Cai ◽  
Zhaoming Song ◽  
Shilin Tong

Bed shear stress is closely related to sediment transport in rivers. Bed shear stress estimation is very difficult, especially for complex flow fields. In this study, complex flow field measurement experiments in a 60° bend with a groyne were performed. The feasibility and reliability of bed shear stress estimations using the log-law method in a complex flow field were analyzed and compared with those associated with the Reynolds, Turbulent Kinetic Energy (TKE), and TKE-w′ methods. The results show that the TKE, Reynolds, and log-law methods produced similar bed shear stress estimates, while the TKE-w′ method produced larger estimates than the other methods. The TKE-w′ method was found to be more suitable for bed shear stress estimation than the TKE method, but the value of its constant C2 needed to be re-estimated. In a complex, strong, three-dimensional flow field, the height of the measurement point (relative or absolute) should be re-estimated when a single point measurement is used to estimate the bed shear stress. The results of this study provide guidance for experimental measurement of bed shear stress in a complex flow field.


Sensors ◽  
2020 ◽  
Vol 20 (16) ◽  
pp. 4504
Author(s):  
Yu Han ◽  
Tongshu Li ◽  
Shiyu Wang ◽  
Jian Chen

Precise flow measurement in the open channel is a key prerequisite to implementation of modern agricultural efficient water use. The channel with an arc-bottomed shape is the most common channel type in irrigation area at present. The paper has verified the log-law is along the normal line rather than along the vertical line in arc-bottom channel. By conducting the velocity distribution log-law, this paper derives the expression of the multiple characteristic sensing points location of the flow-velocity sensor in the channel section, which is along the normal line. Based on this, a new algorithm to estimate the discharge of the arc-bottomed channel flow is proposed. We have also developed the experiment of the arc-bottomed channels (including semicircular channels, arc-bottom trapezoidal channels and U-shaped channels) and utilize the data to verify the method. The results indicate that the sensing locations expression of the flow velocity measuring sensor such as acoustic doppler velocimetry and propeller is suitable for improving discharge estimation’s accuracy of the arc-bottomed channels. This method could be extensively used in estimating discharge of irrigation and drainage channels in agricultural water conservancy projects. It will enhance the efficiency and accuracy of water resources management departments in irrigation areas, which also meet the strategic requirements of agricultural sustainable development.


2020 ◽  
Vol 5 (3) ◽  
pp. 959-975
Author(s):  
Daniel Vassallo ◽  
Raghavendra Krishnamurthy ◽  
Harindra J. S. Fernando

Abstract. Model uncertainty is a significant challenge in the wind energy industry and can lead to mischaracterization of millions of dollars' worth of wind resources. Machine learning methods, notably deep artificial neural networks (ANNs), are capable of modeling turbulent and chaotic systems and offer a promising tool to produce high-accuracy wind speed forecasts and extrapolations. This paper uses data collected by profiling Doppler lidars over three field campaigns to investigate the efficacy of using ANNs for wind speed vertical extrapolation in a variety of terrains, and it quantifies the role of domain knowledge in ANN extrapolation accuracy. A series of 11 meteorological parameters (features) are used as ANN inputs, and the resulting output accuracy is compared with that of both standard log-law and power-law extrapolations. It is found that extracted nondimensional inputs, namely turbulence intensity, current wind speed, and previous wind speed, are the features that most reliably improve the ANN's accuracy, providing up to a 65 % and 52 % increase in extrapolation accuracy over log-law and power-law predictions, respectively. The volume of input data is also deemed important for achieving robust results. One test case is analyzed in depth using dimensional and nondimensional features, showing that the feature nondimensionalization drastically improves network accuracy and robustness for sparsely sampled atmospheric cases.


Open Physics ◽  
2020 ◽  
Vol 18 (1) ◽  
pp. 182-188
Author(s):  
O. González-Gaxiola ◽  
Anjan Biswas ◽  
Abdullah Kamis Alzahrani

AbstractThis paper presents optical Gaussons by the aid of the Laplace–Adomian decomposition scheme. The numerical simulations are presented both in the presence and in the absence of the detuning term. The error analyses of the scheme are also displayed.


2020 ◽  
Author(s):  
Rui M L Ferreira ◽  
Rigden Y Tenzin ◽  
Ana M Ricardo

<p>Open channel flows over granular mobile beds are affected by the nature and intensity of hyporheic/surface mass and momentum exchanges. Near-bed surface mean flow and turbulence find an equilibrium with the flow in the hyporheic region and with the type and amount of granular material transported in equilibrium conditions. The processes involved in these adaptive process are not well known. This work addresses this knowledge gap and it is aimed at describing the effect of the hydraulic conductivity on the friction factor and on the parameters of the log-law that is thought to constitute a valid model for the turbulent flow in the overlapping region of fully developed hydraulically rough boundary layers over mobile cohesionless beds. To fulfil the objectives, experimental tests performed in high conductivity beds (mono-sized glass sphere beads) are compared with the existing database of low conductivity beds of Ferreira et al. (2012), keeping constant the range of values of porosity, Shields parameters and roughness Reynolds numbers. The hydraulic conductivity is varied by changing the tortuosity (and the dimensions of the pore paths) and not the porosity.</p><p>A new database of instantaneous velocities was acquired with Particle Image Velocimetry (PIV) and processed to gather time-averaged velocities and space-time (double-averaged) quantities, namely velocities, Reynolds stresses and form-induced stresses. The hydraulic conductivity was measured for both types of bed.</p><p>The parameters of log-law obtained from high conductivity are compared with low conductivity of existing database, for mobile and immobile bed conditions. The main finding can be summarized as follows.</p><p>i. Hydraulic conductivity does not affect the location of the zero plane of the log-law, the thickness of the region above the crests where the flow is determined by roughness.</p><p>ii. Increasing the hydraulic conductivity does not appear to decrease the value of bed roughness parameters such as the roughness heigh.</p><p>iii. Higher hydraulic conductivity is associated to a structural change: the same near-bed velocity can be achieved with lower shear stress in the inner region. A lower friction factor, (<em>u</em><sub>*</sub>/<em>U</em>)<sup>2</sup>, is thus registered.</p><p>iv. Flows over high conductivity beds appear drag-reducing even if roughness parameters do not change appreciably.</p><p> </p><p>This research was partially supported by Portuguese and European funds, within the COMPETE 2020 and PORL-FEDER programs, through project PTDC/CTA-OHR/29360/2017 RiverCure</p>


2020 ◽  
Vol 20 (4) ◽  
pp. 953-986 ◽  
Author(s):  
Nadeeka S. Miguntanna ◽  
Hamish Moses ◽  
Muttucumaru Sivakumar ◽  
Shu-Qing Yang ◽  
Keith James Enever ◽  
...  

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