scholarly journals Investigation of sheet-flow processes based on novel acoustic high-resolution velocity and concentration measurements

2015 ◽  
Vol 767 ◽  
pp. 1-30 ◽  
Author(s):  
Thibaud Revil-Baudard ◽  
Julien Chauchat ◽  
David Hurther ◽  
Pierre-Alain Barraud
Keyword(s):  
Large Scale ◽  
Reynolds Shear Stress ◽  
Sediment Flux ◽  
Ensemble Averaging ◽  
Sheet Flow ◽  
Two Phase ◽  
Interface Position ◽  
Suspension Layer ◽  
The Mean ◽  
The Impact

AbstractA new dataset of uniform and steady sheet-flow experiments is presented in this paper. An acoustic concentration and velocity profiler (ACVP) is used to measure time-resolved profiles of collocated 2C velocity ($u,w$) and sediment concentration and to measure the time evolution of the bed interface position. Ensemble averaging over 11 similar experiment realisations is done to evaluate the mean profiles of streamwise velocity, concentration, sediment flux and Reynolds shear stress. The repeatability, stationarity and uniformity of the flow are carefully checked for a Shields number ${\it\theta}\approx 0.5$ and a suspension number of $S=1.1$. The mean profile analysis allows to separate the flow into two distinct layers: a suspension layer dominated by turbulence and a bed layer dominated by granular interactions. The bed layer can be further subdivided into a frictional layer capped by a collisional layer. In the suspension layer, the mixing length profile is linear with a strongly reduced von Karman parameter equal to 0.225. The Schmidt number is found to be constant in this region with a mean value of ${\it\sigma}_{s}=0.44$. The present results are then interpreted in terms of existing modelling approaches and the underlying assumptions are discussed. In particular, the well-known Rouse profile is shown to predict the concentration profile adequately in the suspension layer provided that all the required parameters can be evaluated separately. However, the strong intermittency of the flow observed in the bed layer under the impact of turbulent large-scale coherent flow structures suggests the limitations of averaged steady two-phase flow models.

scholarly journals What Is the Impact of Additional Tropical Observations on a Modern Data Assimilation System?

2019 ◽  
Vol 147 (7) ◽  
pp. 2433-2449
Author(s):  
Laura C. Slivinski ◽  
Gilbert P. Compo ◽  
Jeffrey S. Whitaker ◽  
Prashant D. Sardeshmukh ◽  
Jih-Wang A. Wang ◽  
...  
Keyword(s):  
El Niño ◽  
Large Scale ◽  
El Nino ◽  
Mean Square ◽  
Observational Network ◽  
In Situ Observations ◽  
The Mean ◽  
The Impact ◽  
Assimilation System

Abstract Given the network of satellite and aircraft observations around the globe, do additional in situ observations impact analyses within a global forecast system? Despite the dense observational network at many levels in the tropical troposphere, assimilating additional sounding observations taken in the eastern tropical Pacific Ocean during the 2016 El Niño Rapid Response (ENRR) locally improves wind, temperature, and humidity 6-h forecasts using a modern assimilation system. Fields from a 50-km reanalysis that assimilates all available observations, including those taken during the ENRR, are compared with those from an otherwise-identical reanalysis that denies all ENRR observations. These observations reveal a bias in the 200-hPa divergence of the assimilating model during a strong El Niño. While the existing observational network partially corrects this bias, the ENRR observations provide a stronger mean correction in the analysis. Significant improvements in the mean-square fit of the first-guess fields to the assimilated ENRR observations demonstrate that they are valuable within the existing network. The effects of the ENRR observations are pronounced in levels of the troposphere that are sparsely observed, particularly 500–800 hPa. Assimilating ENRR observations has mixed effects on the mean-square difference with nearby non-ENRR observations. Using a similar system but with a higher-resolution forecast model yields comparable results to the lower-resolution system. These findings imply a limited improvement in large-scale forecast variability from additional in situ observations, but significant improvements in local 6-h forecasts.

Large-scale fuel deposition patterns on northern Spanish shores following the ‘Prestige’ oil spill

2008 ◽  
Vol 88 (3) ◽  
pp. 463-468 ◽  
Author(s):  
José Luis Acuña ◽  
Araceli Puente ◽  
Ricardo Anadón ◽  
Consolación Fernández ◽  
María Luisa Vera ◽  
...  
Keyword(s):  
Large Scale ◽  
Northern Spain ◽  
The West ◽  
Deposition Patterns ◽  
Prestige Oil Spill ◽  
Cantabrian Coast ◽  
The Mean ◽  
The Impact ◽  
Oil Tanker ◽  
Fuel Deposition

Following the accident of the oil tanker ‘Prestige’, we surveyed the large scale fuel deposition patterns on the Cantabrian shore (northern Spain) covering three regions (from west to east): (i) Asturias, west of Cape Peñas (24 segments surveyed); (ii) Asturias, east of Cape Peñas (33 segments surveyed); and (iii) Cantabria (also east of Cape Peñas, 256 segments surveyed). Fuel arrived to the Cantabrian Coast as a single oil wave which was more intense to the east than to the west of Cape Peñas. The mean percentage of coast length affected was 25, 41 and 15% in western Asturias, eastern Asturias and Cantabria, respectively. However, less than 10% of the substrate was covered by fuel in oiled patches, thus the impact was moderate. We conclude that these patterns are consistent with fuel transport by the Iberian Poleward Current, a hydrographic feature typical of this region during winter.

Turbulent Vorticity Diffusion in the Stronger Wall Jet Managed by a Flat Plate Wing in the Outer Layer

2015 ◽  
Author(s):  
Takuma Katayama ◽  
Shinsuke Mochizuki
Keyword(s):  
Shear Stress ◽  
Flat Plate ◽  
Outer Layer ◽  
Large Scale ◽  
Reynolds Shear Stress ◽  
Three Dimensional ◽  
Quantitative Relationship ◽  
Wall Jet ◽  
Mean Velocity ◽  
The Mean

The present experiment focuses on the vorticity diffusion in a stronger wall jet managed by a three-dimensional flat plate wing in the outer layer. Measurement of the fluctuating velocities and vorticity correlation has been carried out with 4-wire vorticity probe. The turbulent vorticity diffusion due to the large scale eddies in the outer layer is quantitatively examined by using the 4-wire vorticity probe. Quantitative relationship between vortex structure and Reynolds shear stress is revealed by means of directly measured experimental evidence which explains vorticity diffusion process and influence of the manipulating wing. It is expected that the three-dimensional outer layer manipulator contributes to keep convex profile of the mean velocity, namely, suppression of the turbulent diffusion and entrainment.

Drivers of biases in the extratropical storm tracks in CMIP6

2020 ◽  
Author(s):  
Matthew Priestley ◽  
Duncan Ackerley ◽  
Jennifer Catto ◽  
Kevin Hodges ◽  
Ruth McDonald ◽  
...  
Keyword(s):  
Large Scale ◽  
Climate Models ◽  
Storm Track ◽  
Storm Tracks ◽  
Extratropical Cyclones ◽  
Ocean Coupling ◽  
Coupled Climate Models ◽  
The Mean ◽  
The Impact

<p>Extratropical cyclones are the leading driver of the day-to-day weather variability and wintertime losses for Europe. In the latest generation of coupled climate models, CMIP6, it is hoped that with improved modelling capabilities come improvements in the structure of the storm track and the associated cyclones. Using an objective cyclone identification and tracking algorithm the mean state of the storm tracks in the CMIP6 models is assessed as well as the representation of explosively deepening cyclones. Any developments and improvements since the previous generation of models in CMIP5 are discussed, with focus on the impact of model resolution on storm track representation. Furthermore, large-scale drivers of any biases are investigated, with particular focus on the role of atmosphere-ocean coupling via associated AMIP simulations and also the influence of large-scale dynamical and thermodynamical features.</p>

Reconstruction of GRACE Total Water Storage Through Automated Machine Learning

2020 ◽  
Author(s):  
Alex Sun ◽  
Bridget Scanlon ◽  
Himanshu Save ◽  
Ashraf Rateb
Keyword(s):  
Machine Learning ◽  
Spatial Variability ◽  
Large Scale ◽  
Water Storage ◽  
Total Water ◽  
New Paradigm ◽  
Satellite Mission ◽  
Automated Machine Learning ◽  
The Mean ◽  
The Impact

<p>The GRACE satellite mission and its follow-on, GRACE-FO, have provided unprecedented opportunities to quantify the impact of climate extremes and human activities on total water storage at large scales. The approximately one-year data gap between the two GRACE missions needs to be filled to maintain data continuity and maximize mission benefits. There is strong interest in using machine learning (ML) algorithms to reconstruct GRACE-like data to fill this gap. So far, most studies attempted to train and select a single ML algorithm to work for global basins. However, hydrometeorological predictors may exhibit strong spatial variability which, in turn, may affect the performance of ML models. Existing studies have already shown that no single algorithm consistently outperformed others over all global basins. In this study, we applied an automated machine learning (AutoML) workflow to perform GRACE data reconstruction. AutoML represents a new paradigm for optimal model structure selection, hyperparameter tuning, and model ensemble stacking, addressing some of the most challenging issues related to ML applications. We demonstrated the AutoML workflow over the conterminous U.S. (CONUS) using six types of ML algorithms and multiple groups of meteorological and climatic variables as predictors. Results indicate that the AutoML-assisted gap filling achieved satisfactory performance over the CONUS. For the testing period (2014/06–2017/06), the mean gridwise Nash-Sutcliffe efficiency is around 0.85, the mean correlation coefficient is around 0.95, and the mean normalized root-mean square error is about 0.09. Trained models maintain good performance when extrapolating to the mission gap and to GRACE-FO periods (after 2017/06). Results further suggest that no single algorithm provides the best predictive performance over the entire CONUS, stressing the importance of using an end-to-end workflow to train, optimize, and combine multiple machine learning models to deliver robust performance, especially when building large-scale hydrological prediction systems and when predictor importance exhibits strong spatial variability.</p>

On the Climate Impact of Surface Roughness Anomalies

2008 ◽  
Vol 65 (7) ◽  
pp. 2215-2234 ◽  
Author(s):  
Daniel B. Kirk-Davidoff ◽  
David W. Keith
Keyword(s):  
Surface Roughness ◽  
Large Scale ◽  
Climate Impact ◽  
Water Model ◽  
Dynamic Mechanisms ◽  
Community Atmosphere Model ◽  
Horizontal Length ◽  
Rossby Wave Response ◽  
The Mean ◽  
The Impact

Abstract Large-scale deployment of wind power may alter climate through alteration of surface roughness. Previous research using GCMs has shown large-scale impacts of surface roughness perturbations but failed to elucidate the dynamic mechanisms that drove the observed responses in surface temperature. Using the NCAR Community Atmosphere Model in both its standard and aquaplanet forms, the authors have explored the impact of isolated surface roughness anomalies on the model climate. A consistent Rossby wave response in the mean winds to roughness anomalies across a range of model implementations is found. This response generates appreciable wind, temperature, and cloudiness anomalies. The interrelationship of these responses is discussed, and it is shown that the magnitude of the responses scales with the horizontal length scale of the roughened region, as well as with the magnitude of the roughness anomaly. These results are further elucidated through comparison with results of a series of shallow-water model experiments.

Statistical hydromechanics of disperse systems. Part 3. Pseudo-turbulent structure of homogeneous suspensions

1972 ◽  
Vol 56 (2) ◽  
pp. 313-336 ◽  
Author(s):  
Yu. A. Buyevich
Keyword(s):  
Large Scale ◽  
Random Motion ◽  
Pure Liquid ◽  
Upward Flow ◽  
Two Phase ◽  
Small Perturbations ◽  
The Mean ◽  
Locally Homogeneous ◽  
Solid Spheres ◽  
Many Particles

The theory of concentrated two-phase mixtures developed in the previous parts of this paper is applied to analysis of the structure of the local random motion (pseudo-turbulence) occurring in flows of suspensions of small solid spheres. Suspensions under study are assumed to be locally homogeneous in the sense that large-scale agglomerates of many particles or voids filled with the pure liquid do not arise in their flows and particles can be approximately regarded as statistically independent units.Coefficients of the particle diffusion caused by pseudo-turbulence are calculated without restrictions imposed on the value of the Reynolds number Re characterizing the fluid flow around one particle. Other pseudo-turbulent quantities (the r.m.s. pseudo-turbulent velocities of both phases, their effective pseudo-turbulent viscosities in a shear flow, etc.) are considered for small Re. In particular, a natural explanation is given to the known effect of the reduced hydraulic resistance of a fluidized bed as compared with that of a stationary particulate bed of the same porosity.Additionally, some properties of the mean motion of a suspension influenced by pseudo-turbulence are discussed brifly. By way of example, two problems are considered: stability of the upward flow of a homogeneous suspension with respect to small perturbations depending upon the vertical co-ordinate and time, and the spatial distribution of particles suspended by the upward flow of a fluid under gravity.

Effect of Lean method implementation in the histopathology section of an anatomical pathology laboratory

2007 ◽  
Vol 61 (11) ◽  
pp. 1193-1199 ◽  
Author(s):  
S S Raab ◽  
D M Grzybicki ◽  
J L Condel ◽  
W R Stewart ◽  
B D Turcsanyi ◽  
...  
Keyword(s):  
Quality Improvement ◽  
Large Scale ◽  
Turnaround Time ◽  
Full Time ◽  
Pathology Laboratory ◽  
Quality Improvement Process ◽  
The Mean ◽  
Work Units ◽  
The Impact ◽  
Productivity Ratio

Background:In the USA, the lack of processes standardisation in histopathology laboratories leads to less than optimal quality, errors, inefficiency and increased costs. The effectiveness of large-scale quality improvement initiatives has been evaluated rarely.Aim:To measure the effect of implementation of a Lean quality improvement process on the efficiency and quality of a histopathology laboratory section.Methods:A non-concurrent interventional cohort study from 1 January 2003 to 31 December 2006 was performed, and the Lean process was implemented on 1 January 2004. Also compared was the productivity of the Lean histopathology section to a sister histopathology section that did not implement Lean processes. Pre- and post-Lean specimen turnaround time and productivity ratios (work units/full time equivalents) were measured. For 200 Lean interventions, a 5-part Likert scale was used to assess the impact on error, success and complexity.Results:In the Lean laboratory, the mean monthly productivity ratio increased from 3439 to 4074 work units/full time equivalents (p<0.001) as the mean daily histopathology section specimen turnaround time decreased from 9.7 to 9.0 h (p = 0.01). The Lean histopathology section had a higher productivity ratio compared with a sister histopathology section (1598 work units/full time equivalents, p<0.001) that did not implement Lean processes. The mean impact, success and complexity of interventions were 2.4, 2.7 and 2.5, respectively. The mean number of specific error causes affected by individual interventions was 2.6.Conclusion:It is concluded that Lean process implementation improved efficiency and quality in the histopathology section.

scholarly journals The effects of ionization feedback on star formation: a case study of the M 16 H II region

2019 ◽  
Vol 627 ◽  
pp. A27 ◽  
Author(s):  
Jin-Long Xu ◽  
Annie Zavagno ◽  
Naiping Yu ◽  
Xiao-Lan Liu ◽  
Ye Xu ◽  
...  
Keyword(s):  
Star Formation ◽  
Large Scale ◽  
Young Stellar Objects ◽  
Ionized Gas ◽  
Stellar Objects ◽  
Multi Wavelength ◽  
The Mean ◽  
The Impact ◽  
The Relationship

Aims. We aim to investigate the impact of the ionized radiation from the M 16 H II region on the surrounding molecular cloud and on its hosted star formation. Methods. To present comprehensive multi-wavelength observations towards the M 16 H II region, we used new CO data and existing infrared, optical, and submillimeter data. The 12CO J = 1−0, 13CO J = 1−0, and C18O J = 1−0 data were obtained with the Purple Mountain Observatory (PMO) 13.7 m radio telescope. To trace massive clumps and extract young stellar objects (YSOs) associated with the M 16 H II region, we used the ATLASGAL and GLIMPSE I catalogs, respectively. Results. From CO data, we discern a large-scale filament with three velocity components. Because these three components overlap with each other in both velocity and space, the filament may be made of three layers. The M 16 ionized gas interacts with the large-scale filament and has reshaped its structure. In the large-scale filament, we find 51 compact cores from the ATLASGAL catalog, 20 of them being quiescent. The mean excitation temperature of these cores is 22.5 K, while this is 22.2 K for the quiescent cores. This high temperature observed for the quiescent cores suggests that the cores may be heated by M 16 and do not experience internal heating from sources in the cores. Through the relationship between the mass and radius of these cores, we obtain that 45% of all the cores are massive enough to potentially form massive stars. Compared with the thermal motion, the turbulence created by the nonthermal motion is responsible for the core formation. For the pillars observed towards M 16, the H II region may give rise to the strong turbulence.

scholarly journals Reynolds-number-dependent turbulent inertia and onset of log region in pipe flows

2014 ◽  
Vol 757 ◽  
pp. 747-769 ◽  
Author(s):  
C. Chin ◽  
J. Philip ◽  
J. Klewicki ◽  
A. Ooi ◽  
I. Marusic
Keyword(s):  
Reynolds Number ◽  
Large Scale ◽  
Reynolds Shear Stress ◽  
Wall Turbulence ◽  
Viscous Force ◽  
Advective Transport ◽  
Leading Order ◽  
Pipe Flows ◽  
Change Of Scale ◽  
The Mean

AbstractA detailed analysis of the ‘turbulent inertia’ (TI) term (the wall-normal gradient of the Reynolds shear stress,$\mathrm{d} \langle -uv\rangle /\mathrm{d} y $), in the axial mean momentum equation is presented for turbulent pipe flows at friction Reynolds numbers$\delta ^{+} \approx 500$, 1000 and 2000 using direct numerical simulation. Two different decompositions for TI are employed to further understand the mean structure of wall turbulence. In the first, the TI term is decomposed into the sum of two velocity–vorticity correlations ($\langle v \omega _z \rangle + \langle - w \omega _y \rangle $) and their co-spectra, which we interpret as an advective transport (vorticity dispersion) contribution and a change-of-scale effect (associated with the mechanism of vorticity stretching and reorientation). In the second decomposition, TI is equivalently represented as the wall-normal gradient of the Reynolds shear stress co-spectra, which serves to clarify the accelerative or decelerative effects associated with turbulent motions at different scales. The results show that the inner-normalised position,$y_m^{+}$, where the TI profile crosses zero, as well as the beginning of the logarithmic region of the wall turbulent flows (where the viscous force is leading order) move outwards in unison with increasing Reynolds number as$y_m^{+} \sim \sqrt{\delta ^{+}}$because the eddies located close to$y_m^{+}$are influenced by large-scale accelerating motions of the type$\langle - w \omega _y \rangle $related to the change-of-scale effect (due to vorticity stretching). These large-scale motions of$O(\delta ^{+})$gain a spectrum of larger length scales with increasing$\delta ^{+}$and are related to the emergence of a secondary peak in the$-uv$co-spectra. With increasing Reynolds number, the influence of the$O(\delta ^{+})$motions promotes viscosity to act over increasingly longer times, thereby increasing the$y^{+}$extent over which the mean viscous force retains leading order. Furthermore, the TI decompositions show that the$\langle v \omega _z \rangle $motions (advective transport and/or dispersion of vorticity) are the dominant mechanism in and above the log region, whereas$\langle - w \omega _y \rangle $motions (vorticity stretching and/or reorientation) are most significant below the log region. The motions associated with$\langle - w \omega _y \rangle $predominantly underlie accelerations, whereas$\langle v \omega _z \rangle $primarily contribute to decelerations. Finally, a description of the structure of wall turbulence deduced from the present analysis and our physical interpretation is presented, and is shown to be consistent with previous flow visualisation studies.

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