Two-dimensional quantitative study of boiling flow evolution in vertical inner-heated annulus channel

Stereological studies are more and more frequent in literature, particularly in the development/evolution, pathology, and neurosciences areas. The stereology challenge is to understand the structural inner threedimensional arrangement based on the analysis of the structure slices only showing two-dimensional information. Cavalieri and Scherle's methods to estimate volume, and Buffon's needle problem, are commented in the stereological context. A group of actions is needed to appropriately quantify morphological structures (unbiased and reproducibly), e.g. sampling, isotropic and uniform randomly sections (Delesse's principle), and updated stereological tools (disector, fractionator, nucleator, etc). Through the correct stereology use, a quantitative study with little effort could be performed: efficiency in stereology means a minimum slices sample counting (little work), low cost (slices preparation), but good accuracy. In the present text, a short review of the main stereological tools is done as a background basis to non-expert scientists.

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Two-dimensional Exchange 35Cl NQR Spectroscopy of Chloral Hydrate

Zeitschrift für Naturforschung A ◽

10.1515/zna-2002-9-1007 ◽

2002 ◽

Vol 57 (9-10) ◽

pp. 53-57 ◽

Cited By ~ 1

Author(s):

N. Sinyavsky ◽

M. Mac̀kowiaka ◽

B. Blümich

Keyword(s):

Exchange Rate ◽

Quantitative Study ◽

Chloral Hydrate ◽

Two Dimensional ◽

Temperature Dependent ◽

Exchange Processes ◽

35Cl Nqr ◽

Temperature Ranges ◽

Optimisation Procedure ◽

Temperature Dependent Study

Two-dimensional exchange 35Cl NQR spectroscopy has been applied for studies of the CCl3- group reorientation processes in chloral hydrate. The experimental results are interpreted on the basis of the 2D-exchange NQR theory, which takes into account the off-resonance irradiation. The pulse-optimisation procedure, which is required by this theory, enabled the detection of the 2D-exchangeNQRspectrum andwas applied to the quantitative study of the exchange processes in chloral hydrate. A temperature dependent study of the exchange rate revealed two different activation processes in the temperature ranges from 240 to 295 K and from 295 to 310 K, respectively.

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Two dimensional quantitative study of the performance of low temperature epitaxial silicon emitter bipolar transistors with side-wall spacer

10.1109/bipol.1988.51055 ◽

2003 ◽

Author(s):

M.Y. Ghannam ◽

R.P. Mertens ◽

R. Van Overstraeten

Keyword(s):

Low Temperature ◽

Quantitative Study ◽

Side Wall ◽

Bipolar Transistors ◽

Two Dimensional ◽

Epitaxial Silicon

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2D Model of Transfer Processes for Water Boiling Flow in Microchannel

ChemEngineering ◽

10.3390/chemengineering5030042 ◽

2021 ◽

Vol 5 (3) ◽

pp. 42

Author(s):

Valery A. Danilov ◽

Christian Hofmann ◽

Gunther Kolb

Keyword(s):

Heat Transfer ◽

Experimental Data ◽

Temperature Profiles ◽

Two Dimensional ◽

Dimensional Model ◽

Transfer Processes ◽

Two Dimensional Model ◽

Boiling Flow ◽

Homogeneous Mixture Model ◽

2D Model

The modeling of transfer processes is a step in the generalization and interpretation of experimental data on heat transfer. The developed two-dimensional model is based on a homogeneous mixture model for boiling water flow in a microchannel with a new evaporation submodel. The outcome of the simulation is the distribution of velocity, void fraction and temperature profiles in the microchannel. The predicted temperature profile is consistent with the experimental literature data.

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Quantitative study of the short range order in B2O3 and B2S3 by MAS and two-dimensional triple-quantum MAS 11B NMR

Solid State Nuclear Magnetic Resonance ◽

10.1016/s0926-2040(96)01280-5 ◽

1997 ◽

Vol 8 (2) ◽

pp. 109-121 ◽

Cited By ~ 61

Author(s):

S.-J. Hwang ◽

C. Fernandez ◽

J.P. Amoureux ◽

J. Cho ◽

S.W. Martin ◽

...

Keyword(s):

Quantitative Study ◽

Short Range ◽

Short Range Order ◽

Range Order ◽

Two Dimensional ◽

11B Nmr

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Subgrid modelling for two-dimensional turbulence using neural networks

Journal of Fluid Mechanics ◽

10.1017/jfm.2018.770 ◽

2018 ◽

Vol 858 ◽

pp. 122-144 ◽

Cited By ~ 43

Author(s):

R. Maulik ◽

O. San ◽

A. Rasheed ◽

P. Vedula

Keyword(s):

Neural Networks ◽

A Priori ◽

Numerical Data ◽

Test Case ◽

Two Dimensional ◽

A Posteriori ◽

Optimization Analysis ◽

Turbulence Closures ◽

Flow Evolution ◽

Promising Development

In this investigation, a data-driven turbulence closure framework is introduced and deployed for the subgrid modelling of Kraichnan turbulence. The novelty of the proposed method lies in the fact that snapshots from high-fidelity numerical data are used to inform artificial neural networks for predicting the turbulence source term through localized grid-resolved information. In particular, our proposed methodology successfully establishes a map between inputs given by stencils of the vorticity and the streamfunction along with information from two well-known eddy-viscosity kernels. Through this we predict the subgrid vorticity forcing in a temporally and spatially dynamic fashion. Our study is botha priorianda posterioriin nature. In the former, we present an extensive hyper-parameter optimization analysis in addition to learning quantification through probability-density-function-based validation of subgrid predictions. In the latter, we analyse the performance of our framework for flow evolution in a classical decaying two-dimensional turbulence test case in the presence of errors related to temporal and spatial discretization. Statistical assessments in the form of angle-averaged kinetic energy spectra demonstrate the promise of the proposed methodology for subgrid quantity inference. In addition, it is also observed that some measure ofa posteriorierror must be considered during optimal model selection for greater accuracy. The results in this article thus represent a promising development in the formalization of a framework for generation of heuristic-free turbulence closures from data.

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