Turbulence Modeling and Simulation of Atmospheric Boundary Layers

1992 ◽  
Vol 114 (1) ◽  
pp. 40-44 ◽  
Author(s):  
T. W. Abou-Arab ◽  
M. A. Serag-Eldin
Keyword(s):  
Experimental Data ◽  
Surface Layer ◽  
Modeling And Simulation ◽  
Experimental Validation ◽  
Turbulence Modeling ◽  
Boundary Surface ◽  
Future Research ◽  
Surface Layers ◽  
Atmospheric Boundary Layers ◽  
Comparison With Experimental Data

The essence and shortcoming of turbulence modeling and simulation of atmospheric boundary/surface layers are discussed. The present approach rests on the extensively tested and widely used two-equation k-ε model to predict such flows. All features and constants of the standard version of the k-ε model as it is used for shear flows are retained here. This eliminates the requirement of rigorous experimental validation. However, the model with its set of boundary conditions features compatibility and realizability with the commonly reported stable, unstable and neutral atmospheric boundary/surface layer data. The paper presents also a comparison with experimental data and other models and the need for future research in this direction.

Experimental Validation of a Numerical Model for the Simulation of Tramcar Vehicle Dynamics

2005 ◽  
Author(s):  
Federico Cheli ◽  
Roberto Corradi ◽  
Giorgio Diana ◽  
Alan Facchinetti
Keyword(s):  
Experimental Data ◽  
Numerical Model ◽  
Vehicle Dynamics ◽  
Experimental Validation ◽  
Dynamic Behaviour ◽  
Operating Conditions ◽  
Structural Configuration ◽  
Railway Vehicles ◽  
Design Solutions ◽  
Comparison With Experimental Data

Tramcar vehicles significantly differ from traditional railway vehicles both for the adopted structural configuration and design solutions and for the operating conditions. For this reason, a new numerical model specific for the analysis of tramcar dynamics has been developed by Politecnico di Milano. Before the numerical model can be adopted as a useful mean to analyse tramcar operational problems, the capability of the model to reproduce the actual tramcar dynamic behaviour has to be verified. The paper deals with the validation of the developed numerical model by means of comparison with experimental data.

TUNNELING SPECTROSCOPY OF MANGANITES WITH NANOSCALE STRUCTURAL NON-UNIFORMITIES

2008 ◽  
Vol 22 (29) ◽  
pp. 2811-2819 ◽  
Author(s):  
V. M. SVISTUNOV ◽  
V. N. LEONOVA ◽  
M. A. BELOGOLOVSKII ◽  
Yu. V. MEDVEDEV ◽  
Yu. F. REVENKO ◽  
...  
Keyword(s):  
Experimental Data ◽  
Surface Layer ◽  
Charge Transport ◽  
Electron Tunneling ◽  
Differential Conductance ◽  
Surface Layers ◽  
Near Surface ◽  
Inelastic Tunneling ◽  
Metal Tip ◽  
Native Surface

We report on our recent electron-tunneling studies of bulk manganite samples that provide important information about the structure of the near-surface layers of the material and the nature of the charge transport across them. It is shown that the even part of the differential conductance of contacts formed by a metallic injector with the surface of a manganite is a power function of the voltage bias. High voltages applied to the sample are found to locally modify the conductance of the degraded native surface layer. Experiments aimed to monitor the force applied to a metal tip pressed into the surface of a manganite prove the presence of sub-surface layers with properties significantly different from those near the surface. Experimental data are analyzed and interpreted within the Glazman–Matveev theory taking into account inelastic tunneling through two metallic "drops" inside the insulating barrier.

scholarly journals Experimental Validation of Falling Liquid Film Models: Velocity Assumption and Velocity Field Comparison

Polymers ◽  
2021 ◽  
Vol 13 (8) ◽  
pp. 1205
Author(s):  
Ruiqi Wang ◽  
Riqiang Duan ◽  
Haijun Jia
Keyword(s):  
Experimental Data ◽  
Particle Image Velocimetry ◽  
Velocity Field ◽  
Experimental Validation ◽  
Particle Image ◽  
Velocity Fields ◽  
Number Range ◽  
Comparison Results ◽  
Image Velocimetry ◽  
Experimental Particle

This publication focuses on the experimental validation of film models by comparing constructed and experimental velocity fields based on model and elementary experimental data. The film experiment covers Kapitza numbers Ka = 278.8 and Ka = 4538.6, a Reynolds number range of 1.6–52, and disturbance frequencies of 0, 2, 5, and 7 Hz. Compared to previous publications, the applied methodology has boundary identification procedures that are more refined and provide additional adaptive particle image velocimetry (PIV) method access to synthetic particle images. The experimental method was validated with a comparison with experimental particle image velocimetry and planar laser induced fluorescence (PIV/PLIF) results, Nusselt’s theoretical prediction, and experimental particle tracking velocimetry (PTV) results of flat steady cases, and a good continuity equation reproduction of transient cases proves the method’s fidelity. The velocity fields are reconstructed based on different film flow model velocity profile assumptions such as experimental film thickness, flow rates, and their derivatives, providing a validation method of film model by comparison between reconstructed velocity experimental data and experimental velocity data. The comparison results show that the first-order weighted residual model (WRM) and regularized model (RM) are very similar, although they may fail to predict the velocity field in rapidly changing zones such as the front of the main hump and the first capillary wave troughs.

scholarly journals Thermodynamic analysis of synthesis of cyclopentanol from cyclopentene and comparison with experimental data

2015 ◽  
Vol 5 (2) ◽  
pp. 135-142 ◽  
Author(s):  
Benzhen Yao ◽  
Zhiqing Wang ◽  
Tiancun Xiao ◽  
Fahai Cao ◽  
Peter P. Edwards ◽  
...  
Keyword(s):  
Experimental Data ◽  
Thermodynamic Analysis ◽  
Comparison With Experimental Data

Experimental Study on Critical Shear Stress of Cohesive Soils and Soil Mixtures

2021 ◽  
Vol 64 (2) ◽  
pp. 587-600
Author(s):  
Xiaojing Gao ◽  
Qiusheng Wang ◽  
Chongbang Xu ◽  
Ruilin Su
Keyword(s):  
Experimental Data ◽  
Shear Stress ◽  
Critical Shear Stress ◽  
Cohesive Soil ◽  
Future Research ◽  
Cohesive Soils ◽  
List Type ◽  
Soil Mixture ◽  
Linear Relationships ◽  
Soil Mixtures

HighlightsErosion tests were performed to study the critical shear stress of cohesive soils and soil mixtures.Linear relationships were observed between critical shear stress and cohesion of cohesive soils.Mixture critical shear stress relates to noncohesive particle size and cohesive soil erodibility.A formula for calculating the critical shear stress of soil mixtures is proposed and verified.Abstract. The incipient motion of soil is an important engineering property that impacts reservoir sedimentation, stable channel design, river bed degradation, and dam breach. Due to numerous factors influencing the erodibility parameters, the study of critical shear stress (tc) of cohesive soils and soil mixtures is still far from mature. In this study, erosion experiments were conducted to investigate the influence of soil properties on the tc of remolded cohesive soils and cohesive and noncohesive soil mixtures with mud contents varying from 0% to 100% using an erosion function apparatus (EFA). For cohesive soils, direct linear relationships were observed between tc and cohesion (c). The critical shear stress for soil mixture (tcm) erosion increased monotonically with an increase in mud content (pm). The median diameter of noncohesive soil (Ds), the void ratio (e), and the organic content of cohesive soil also influenced tcm. A formula for calculating tcm considering the effect of pm and the tc of noncohesive soil and pure mud was developed. The proposed formula was validated using experimental data from the present and previous research, and it can reproduce the variation of tcm for reconstituted soil mixtures. To use the proposed formula to predict the tcm for artificial engineering problems, experimental erosion tests should be performed. Future research should further test the proposed formula based on additional experimental data. Keywords: Cohesive and noncohesive soil mixture, Critical shear stress, Erodibility, Mud content, Soil property.

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