Wind-Tunnel Study Of Atmospheric Stable Boundary Layers Over A Rough Surface

2001 ◽  
Vol 98 (1) ◽  
pp. 57-82 ◽  
Author(s):  
Yuji Ohya
Author(s):  
Marcio Cataldi ◽  
Juliana B. R. Loureiro ◽  
Atila P. Silva Freire

The objective of this work is to develop, in a wind tunnel environment, boundary layers with different states of development that simulate the structure present in the atmospheric boundary layer. The work analyses the dymamic and thermal characteristics of different types of thick, artificially-generated, turbulent boundary layers. The thermal boundary layer is obtained by two methods: wall surface heating, made through electrical resistance, can furnish an increase in wall temperature of up to 100 °C above the ambient temparatures and can be applied over a 5000 mm long surface with a controlled variation of 2 °C. The main flow heating is obtained by forcing the flow pass through an array of copper wires whose elements can be heated individually. The main flow can be heated up to 100 °C. The whole system can then be used to produce unstable, neutral and stable boundary layers. The parameters of the thermal boundary layers are qualified according to the following parameters: growth, structure, equilibrium, turbulent transport of heat and energy spectrum. The paper describes in detail the experimental arrangements, including the geometry of the wind tunnel and the instrumentation.


2001 ◽  
Vol 35 (13) ◽  
pp. 2253-2263 ◽  
Author(s):  
Alan Robins ◽  
Ian Castro ◽  
Paul Hayden ◽  
Nathan Steggel ◽  
Daniele Contini ◽  
...  

2014 ◽  
Vol 7 (6) ◽  
pp. 2599-2611 ◽  
Author(s):  
Y. Zhang ◽  
Z. Gao ◽  
D. Li ◽  
Y. Li ◽  
N. Zhang ◽  
...  

Abstract. Experimental data from four field campaigns are used to explore the variability of the bulk Richardson number of the entire planetary boundary layer (PBL), Ribc, which is a key parameter for calculating the PBL height (PBLH) in numerical weather and climate models with the bulk Richardson number method. First, the PBLHs of three different thermally stratified boundary layers (i.e., strongly stable boundary layers, weakly stable boundary layers, and unstable boundary layers) from the four field campaigns are determined using the turbulence method, the potential temperature gradient method, the low-level jet method, and the modified parcel method. Then for each type of boundary layer, an optimal Ribc is obtained through linear fitting and statistical error minimization methods so that the bulk Richardson method with this optimal Ribc yields similar estimates of PBLHs as the methods mentioned above. We find that the optimal Ribc increases as the PBL becomes more unstable: 0.24 for strongly stable boundary layers, 0.31 for weakly stable boundary layers, and 0.39 for unstable boundary layers. Compared with previous schemes that use a single value of Ribc in calculating the PBLH for all types of boundary layers, the new values of Ribc proposed by this study yield more accurate estimates of PBLHs.


2006 ◽  
Vol 63 (8) ◽  
pp. 2074-2091 ◽  
Author(s):  
Sukanta Basu ◽  
Fernando Porté-Agel

Abstract A new tuning-free subgrid-scale model, termed locally averaged scale-dependent dynamic (LASDD) model, is developed and implemented in large-eddy simulations (LES) of stable boundary layers. The new model dynamically computes the Smagorinsky coefficient and the subgrid-scale Prandtl number based on the local dynamics of the resolved velocity and temperature fields. Overall, the agreement between the statistics of the LES-generated turbulence and some well-established empirical formulations and theoretical predictions (e.g., the local scaling hypothesis) is remarkable. Moreover, the simulated statistics obtained with the LASDD model show relatively little resolution dependence for the range of grid sizes considered here. In essence, it is shown here that the new LASDD model is a robust subgrid-scale parameterization for reliable, tuning-free simulations of stable boundary layers, even with relatively coarse resolutions.


2019 ◽  
Vol 46 (11) ◽  
pp. 6090-6100 ◽  
Author(s):  
Changxing Lan ◽  
Heping Liu ◽  
Gabriel G. Katul ◽  
Dan Li ◽  
Dennis Finn

2006 ◽  
Vol 96 (22) ◽  
Author(s):  
T. K. Sengupta ◽  
A. Kameswara Rao ◽  
K. Venkatasubbaiah

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