scholarly journals A Conceptual Model for Entrainment in Cumulus Clouds

2005 ◽  
Vol 62 (7) ◽  
pp. 2602-2606 ◽  
Author(s):  
Amit Agrawal
Keyword(s):  
Streamwise Velocity ◽  
Cloud Base ◽  
Cumulus Clouds ◽  
Proposed Model ◽  
Momentum Fluxes ◽  
Order Polynomial ◽  
Long Time ◽  
The Mean ◽  
Polynomial Factor ◽  
Fourth Order Polynomial

Abstract Cumulus clouds are generally modeled as a plume, and the model works well up until the cloud base is encountered, beyond which the continuously entraining model does not appear appropriate. Although it has been known for a long time that cumulus clouds have very little lateral entrainment, the reason for it is not evident. An expression for the mean streamwise velocity profile as a Gaussian multiplied by a fourth-order polynomial factor is hereby proposed such that the mass and momentum fluxes are decoupled. This model suggests that cumulus clouds differ from other shear flows in that the former need not interact with the ambient for some downstream distance. The proposed model replicates a number of characteristics of cumulus clouds like a conserved mass flux with varying momentum flux, and may therefore be employed to describe them, in a time-averaged sense, beyond the cloud base.

scholarly journals Differences between Nonprecipitating Tropical and Trade Wind Marine Shallow Cumuli

2016 ◽  
Vol 144 (2) ◽  
pp. 681-701 ◽  
Author(s):  
Virendra P. Ghate ◽  
Mark A. Miller ◽  
Ping Zhu
Keyword(s):  
Surface Fluxes ◽  
Cloud Base ◽  
Trade Wind ◽  
Cumulus Clouds ◽  
Wind Speeds ◽  
Lower Cloud ◽  
Observational Site ◽  
Velocity Scale ◽  
Atmospheric Radiation Measurement ◽  
The Mean

Abstract Marine nonprecipitating cumulus topped boundary layers (CTBLs) observed in a tropical and in a trade wind region are contrasted based on their cloud macrophysical, dynamical, and radiative structures. Data from the Atmospheric Radiation Measurement (ARM) observational site previously operating at Manus Island, Papua New Guinea, and data collected during the deployment of ARM Mobile Facility at the island of Graciosa, in the Azores, were used in this study. The tropical marine CTBLs were deeper, had higher surface fluxes and boundary layer radiative cooling, but lower wind speeds compared to their trade wind counterparts. The radiative velocity scale was 50%–70% of the surface convective velocity scale at both locations, highlighting the prominent role played by radiation in maintaining turbulence in marine CTBLs. Despite greater thicknesses, the chord lengths of tropical cumuli were on average lower than those of trade wind cumuli, and as a result of lower cloud cover, the hourly averaged (cloudy and clear) liquid water paths of tropical cumuli were lower than the trade wind cumuli. At both locations ~70% of the cloudy profiles were updrafts, while the average amount of updrafts near cloud base stronger than 1 m s−1 was ~22% in tropical cumuli and ~12% in the trade wind cumuli. The mean in-cloud radar reflectivity within updrafts and mean updraft velocity was higher in tropical cumuli than the trade wind cumuli. Despite stronger vertical velocities and a higher number of strong updrafts, due to lower cloud fraction, the updraft mass flux was lower in the tropical cumuli compared to the trade wind cumuli. The observations suggest that the tropical and trade wind marine cumulus clouds differ significantly in their macrophysical and dynamical structures.

Simple explicit model of liquid mean flow in region above axial impeller

1985 ◽  
Vol 50 (11) ◽  
pp. 2396-2410
Author(s):  
Miloslav Hošťálek ◽  
Ivan Fořt
Keyword(s):  
Vortex Flow ◽  
Flow Model ◽  
Quantitative Agreement ◽  
Mean Flow ◽  
Flat Bottom ◽  
Proposed Model ◽  
Minimum Number ◽  
The Mean ◽  
Model Equations ◽  
Radial Circulation

The study describes a method of modelling axial-radial circulation in a tank with an axial impeller and radial baffles. The proposed model is based on the analytical solution of the equation for vortex transport in the mean flow of turbulent liquid. The obtained vortex flow model is tested by the results of experiments carried out in a tank of diameter 1 m and with the bottom in the shape of truncated cone as well as by the data published for the vessel of diameter 0.29 m with flat bottom. Though the model equations are expressed in a simple form, good qualitative and even quantitative agreement of the model with reality is stated. Apart from its simplicity, the model has other advantages: minimum number of experimental data necessary for the completion of boundary conditions and integral nature of these data.

scholarly journals Modeling the Excess Velocity of Low-Viscous Taylor Droplets in Square Microchannels

Fluids ◽  
2019 ◽  
Vol 4 (3) ◽  
pp. 162 ◽  
Author(s):  
Thorben Helmers ◽  
Philip Kemper ◽  
Jorg Thöming ◽  
Ulrich Mießner
Keyword(s):  
High Speed ◽  
Process Intensification ◽  
Continuous Phase ◽  
Channel Cross Section ◽  
Optimization Approach ◽  
Mean Flow ◽  
Bypass Flow ◽  
Wall Film ◽  
Proposed Model ◽  
The Mean

Microscopic multiphase flows have gained broad interest due to their capability to transfer processes into new operational windows and achieving significant process intensification. However, the hydrodynamic behavior of Taylor droplets is not yet entirely understood. In this work, we introduce a model to determine the excess velocity of Taylor droplets in square microchannels. This velocity difference between the droplet and the total superficial velocity of the flow has a direct influence on the droplet residence time and is linked to the pressure drop. Since the droplet does not occupy the entire channel cross-section, it enables the continuous phase to bypass the droplet through the corners. A consideration of the continuity equation generally relates the excess velocity to the mean flow velocity. We base the quantification of the bypass flow on a correlation for the droplet cap deformation from its static shape. The cap deformation reveals the forces of the flowing liquids exerted onto the interface and allows estimating the local driving pressure gradient for the bypass flow. The characterizing parameters are identified as the bypass length, the wall film thickness, the viscosity ratio between both phases and the C a number. The proposed model is adapted with a stochastic, metaheuristic optimization approach based on genetic algorithms. In addition, our model was successfully verified with high-speed camera measurements and published empirical data.

scholarly journals A Deep Learning Approach to Predict Autism Spectrum Disorder Using Multisite Resting-State fMRI

2021 ◽  
Vol 11 (8) ◽  
pp. 3636
Author(s):  
Faria Zarin Subah ◽  
Kaushik Deb ◽  
Pranab Kumar Dhar ◽  
Takeshi Koshiba
Keyword(s):  
Autism Spectrum Disorder ◽  
Resting State ◽  
State Of The Art ◽  
Resting State Fmri ◽  
Autism Spectrum ◽  
Spectrum Disorder ◽  
Bootstrap Analysis ◽  
Proposed Model ◽  
Art Methods ◽  
The Mean

Autism spectrum disorder (ASD) is a complex and degenerative neuro-developmental disorder. Most of the existing methods utilize functional magnetic resonance imaging (fMRI) to detect ASD with a very limited dataset which provides high accuracy but results in poor generalization. To overcome this limitation and to enhance the performance of the automated autism diagnosis model, in this paper, we propose an ASD detection model using functional connectivity features of resting-state fMRI data. Our proposed model utilizes two commonly used brain atlases, Craddock 200 (CC200) and Automated Anatomical Labelling (AAL), and two rarely used atlases Bootstrap Analysis of Stable Clusters (BASC) and Power. A deep neural network (DNN) classifier is used to perform the classification task. Simulation results indicate that the proposed model outperforms state-of-the-art methods in terms of accuracy. The mean accuracy of the proposed model was 88%, whereas the mean accuracy of the state-of-the-art methods ranged from 67% to 85%. The sensitivity, F1-score, and area under receiver operating characteristic curve (AUC) score of the proposed model were 90%, 87%, and 96%, respectively. Comparative analysis on various scoring strategies show the superiority of BASC atlas over other aforementioned atlases in classifying ASD and control.

scholarly journals Large-Eddy Simulations of a Drizzling, Stratocumulus-Topped Marine Boundary Layer

2009 ◽  
Vol 137 (3) ◽  
pp. 1083-1110 ◽  
Author(s):  
Andrew S. Ackerman ◽  
Margreet C. vanZanten ◽  
Bjorn Stevens ◽  
Verica Savic-Jovcic ◽  
Christopher S. Bretherton ◽  
...  
Keyword(s):  
Boundary Layer ◽  
Marine Boundary Layer ◽  
Cloud Water ◽  
Large Eddy Simulations ◽  
Cloud Base ◽  
Entrainment Rate ◽  
Liquid Water Path ◽  
Average Maximum ◽  
Large Eddy ◽  
The Mean

Abstract Cloud water sedimentation and drizzle in a stratocumulus-topped boundary layer are the focus of an intercomparison of large-eddy simulations. The context is an idealized case study of nocturnal stratocumulus under a dry inversion, with embedded pockets of heavily drizzling open cellular convection. Results from 11 groups are used. Two models resolve the size distributions of cloud particles, and the others parameterize cloud water sedimentation and drizzle. For the ensemble of simulations with drizzle and cloud water sedimentation, the mean liquid water path (LWP) is remarkably steady and consistent with the measurements, the mean entrainment rate is at the low end of the measured range, and the ensemble-average maximum vertical wind variance is roughly half that measured. On average, precipitation at the surface and at cloud base is smaller, and the rate of precipitation evaporation greater, than measured. Including drizzle in the simulations reduces convective intensity, increases boundary layer stratification, and decreases LWP for nearly all models. Including cloud water sedimentation substantially decreases entrainment, decreases convective intensity, and increases LWP for most models. In nearly all cases, LWP responds more strongly to cloud water sedimentation than to drizzle. The omission of cloud water sedimentation in simulations is strongly discouraged, regardless of whether or not precipitation is present below cloud base.

Relationship between temporal and spatial averages in grid turbulence

2013 ◽  
Vol 730 ◽  
pp. 593-606 ◽  
Author(s):  
L. Djenidi ◽  
S. F. Tardu ◽  
R. A. Antonia
Keyword(s):  
Strong Support ◽  
Statistical Properties ◽  
Grid Turbulence ◽  
Mean Flow ◽  
Lateral Direction ◽  
Ergodic Hypothesis ◽  
Long Time ◽  
The Mean ◽  
Temporal And Spatial ◽  
Boltzmann Method

AbstractA long-time direct numerical simulation (DNS) based on the lattice Boltzmann method is carried out for grid turbulence with the view to compare spatially averaged statistical properties in planes perpendicular to the mean flow with their temporal counterparts. The results show that the two averages become equal a short distance downstream of the grid. This equality indicates that the flow has become homogeneous in a plane perpendicular to the mean flow. This is an important result, since it confirms that hot-wire measurements are appropriate for testing theoretical results based on spatially averaged statistics. It is equally important in the context of DNS of grid turbulence, since it justifies the use of spatial averaging along a lateral direction and over several realizations for determining various statistical properties. Finally, the very good agreement between temporal and spatial averages validates the comparison between temporal (experiments) and spatial (DNS) statistical properties. The results are also interesting because, since the flow is stationary in time and spatially homogeneous along lateral directions, the equality between the two types of averaging provides strong support for the ergodic hypothesis in grid turbulence in planes perpendicular to the mean flow.

scholarly journals Ceramic Cracks Segmentation with Deep Learning

2021 ◽  
Vol 11 (13) ◽  
pp. 6017
Author(s):  
Gerivan Santos Junior ◽  
Janderson Ferreira ◽  
Cristian Millán-Arias ◽  
Ramiro Daniel ◽  
Alberto Casado Junior ◽  
...  
Keyword(s):  
Deep Learning ◽  
Ceramic Plate ◽  
Ceramic Tiles ◽  
Entire Area ◽  
Manual Inspection ◽  
Optical Inspection ◽  
Proposed Model ◽  
Processing Step ◽  
Long Time ◽  
Automated Optical Inspection

Cracks are pathologies whose appearance in ceramic tiles can cause various damages due to the coating system losing water tightness and impermeability functions. Besides, the detachment of a ceramic plate, exposing the building structure, can still reach people who move around the building. Manual inspection is the most common method for addressing this problem. However, it depends on the knowledge and experience of those who perform the analysis and demands a long time and a high cost to map the entire area. This work focuses on automated optical inspection to find faults in ceramic tiles performing the segmentation of cracks in ceramic images using deep learning to segment these defects. We propose an architecture for segmenting cracks in facades with Deep Learning that includes an image pre-processing step. We also propose the Ceramic Crack Database, a set of images to segment defects in ceramic tiles. The proposed model can adequately identify the crack even when it is close to or within the grout.

Residual Alkaline Phosphatase Activity in Milks Subjected to Various Time-Temperature Treatments

1997 ◽  
Vol 60 (5) ◽  
pp. 525-530 ◽  
Author(s):  
C. J. PAINTER ◽  
R. L. BRADLEY
Keyword(s):  
Alkaline Phosphatase ◽  
Activity Levels ◽  
Milk Product ◽  
Milk Products ◽  
Alp Activity ◽  
High Temperature Short Time ◽  
Thermally Processed ◽  
Long Time ◽  
The Mean ◽  
Fluid Milk

Milk is routinely tested for proper pasteurization. The Scharer and Fluorophos methods, among others, test for residual alkaline phosphatase (ALP) activity to assure proper pasteurization. Until recently there were no tests available to accurately detect residual ALP activity levels below the U.S. legal limit of 1 μg of phenol or 350 mU of ALP per liter of milk. The new Fluorophos method can detect accurately residual ALP activity levels as low as 10 mU/liter. The Fluorophos method was used to investigate residual ALP activity levels in several fluid milk products. The milk products were thermally processed under various time and temperature protocols below, at, and above current U.S. Food and Drug Administration-mandated heat treatments for fluid milk and milk products. The data established values for residual ALP activity in milks pasteurized under high-temperature short-time (HTST) and low-temperature long-time (LTLT) treatments. The mean ALP activities for whole, 2% lowfat, 1% lowfat, skim, half and half, and chocolate-flavored milks thermally processed at the legal minimum HTST pasteurization treatment are 169.7 ± 12.3, 145.2 ± 9.3, 98.6 ± 8.9, 72.5 ± 4.2, 38.4 ± 4.6 and 157.3 ± 6.5 mU/liter, respectively. The mean ALP activities generated at the legal minimum LTLT pasteurization treatment are 81.8 ± 4.8, 66.4 ± 5.9, 56.4 ± 2.1, 39.1 ± 3.9, 35.0 ± 1.2 and 91.3 ± 7.7 mU/liter, respectively. The values for all milks pasteurized at the legal minimum heat treatment were significantly below the current legal cutoff for residual ALP activity of 350 mU/liter of milk or milk product.

scholarly journals Direct Calculation of Thermodynamic Wet-Bulb Temperature as a Function of Pressure and Elevation

2013 ◽  
Vol 30 (8) ◽  
pp. 1757-1765 ◽  
Author(s):  
Sayed-Hossein Sadeghi ◽  
Troy R. Peters ◽  
Douglas R. Cobos ◽  
Henry W. Loescher ◽  
Colin S. Campbell
Keyword(s):  
Air Temperature ◽  
Mean Absolute Error ◽  
Direct Calculation ◽  
Ambient Air ◽  
Absolute Error ◽  
Mean Square ◽  
Air Temperatures ◽  
Order Polynomial ◽  
The Mean ◽  
Very High

Abstract A simple analytical method was developed for directly calculating the thermodynamic wet-bulb temperature from air temperature and the vapor pressure (or relative humidity) at elevations up to 4500 m above MSL was developed. This methodology was based on the fact that the wet-bulb temperature can be closely approximated by a second-order polynomial in both the positive and negative ranges in ambient air temperature. The method in this study builds upon this understanding and provides results for the negative range of air temperatures (−17° to 0°C), so that the maximum observed error in this area is equal to or smaller than −0.17°C. For temperatures ≥0°C, wet-bulb temperature accuracy was ±0.65°C, and larger errors corresponded to very high temperatures (Ta ≥ 39°C) and/or very high or low relative humidities (5% < RH < 10% or RH > 98%). The mean absolute error and the root-mean-square error were 0.15° and 0.2°C, respectively.

scholarly journals Recommending Mobile Microblog Users via a Tensor Factorization Based on User Cluster Approach

2018 ◽  
Vol 2018 ◽  
pp. 1-11 ◽  
Author(s):  
Xiangwen Liao ◽  
Lingying Zhang ◽  
Jingjing Wei ◽  
Dingda Yang ◽  
Guolong Chen
Keyword(s):  
Network Centrality ◽  
Network Clustering ◽  
Tensor Factorization ◽  
Latent Factors ◽  
Cp Decomposition ◽  
Temporal Features ◽  
User Influence ◽  
Proposed Model ◽  
The Mean ◽  
Content Similarity

User influence is a very important factor for microblog user recommendation in mobile social network. However, most existing user influence analysis works ignore user’s temporal features and fail to filter the marketing users with low influence, which limits the performance of recommendation methods. In this paper, a Tensor Factorization based User Cluster (TFUC) model is proposed. We firstly identify latent influential users by neural network clustering. Then, we construct a features tensor according to latent influential user’s opinion, activity, and network centrality information. Furthermore, user influences are predicted by the latent factors resulting from the temporal restrained CP decomposition. Finally, we recommend microblog users considering both user influence and content similarity. Our experimental results show that the proposed model significantly improves recommendation performance. Meanwhile, the mean average precision of TFUC outperforms the baselines with 3.4% at least.

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