The Experts below are selected from a list of 360 Experts worldwide ranked by ideXlab platform
Hong Qin - One of the best experts on this subject based on the ideXlab platform.
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time domain global Similarity Method for automatic data cleaning for multi channel measurement systems in magnetic confinement fusion devices
Computer Physics Communications, 2019Co-Authors: Ting Lan, Jian Liu, Hong QinAbstract:Abstract To guarantee the availability and reliability of data source in Magnetic Confinement Fusion (MCF) devices, incorrect diagnostic data, which cannot reflect real physical properties of measured objects, should be sorted out before further analysis and study. Traditional data sorting cannot meet the growing demand of MCF research because of the low-efficiency, time-delay, and lack of objective criteria. In this paper, a Time-Domain Global Similarity (TDGS) Method based on machine learning technologies is proposed for the automatic data cleaning of MCF devices. The aim of traditional data sorting is to classify original diagnostic data sequences. The lengths and evolution properties of the data sequences vary shot by shot. Hence the classification criteria are affected by many discharge parameters and are different in various discharges. The focus of the TDGS Method is turned to the physical Similarity between data sequences from different channels, which are more independent of discharge parameters. The complexity arisen from real discharge parameters during data cleaning is avoided in the TDGS Method by transforming the general data sorting problem into a binary classification problem about the physical Similarity between data sequences. As a demonstration of its application to multi-channel measurement systems, the TDGS Method is applied to the EAST POlarimeter–INTerferometer (POINT) system. The optimal performance of the Method evaluated by 24-fold cross-validation has reached 0.9871 ± 0.0385.
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time domain global Similarity Method for automatic data cleaning for multi channel measurement systems in magnetic confinement fusion devices
arXiv: Plasma Physics, 2017Co-Authors: Ting Lan, Jian Liu, Hong QinAbstract:To guarantee the availability and reliability of data source in Magnetic Confinement Fusion (MCF) devices, incorrect diagnostic data, which cannot reflect real physical properties of measured objects, should be sorted out before further analysis and study. Traditional data sorting cannot meet the growing demand of MCF research because of the low-efficiency, time-delay, and lack of objective criteria. In this paper, a Time-Domain Global Similarity (TDGS) Method based on machine learning technologies is proposed for the automatic data cleaning of MCF devices. Traditional data sorting aims to the classification of original diagnostic data sequences, which are different in both length and evolution properties under various discharge parameters. Hence the classification criteria are affected by many discharge parameters and vary shot by shot. The focus of TDGS Method is turned to the physical Similarity between data sequences from different channels, which are more essential and independent of discharge parameters. The complexity arisen from real discharge parameters during data cleaning is avoided in the TDGS Method by transforming the general data sorting problem into a binary classification problem about the physical Similarity between data sequences. As a demonstration of its application to multi-channel measurement systems, the TDGS Method is applied to the EAST POlarimeter-INterferomeTer (POINT) system. The optimized performance of the Method has reached 0.9871.
Rama Subba Reddy Gorla - One of the best experts on this subject based on the ideXlab platform.
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unsteady three dimensional mhd flow of a nano eyring powell fluid past a convectively heated stretching sheet in the presence of thermal radiation viscous dissipation and joule heating
Journal of the Association of Arab Universities for Basic and Applied Sciences, 2017Co-Authors: B J Gireesha, B Mahanthesh, Rama Subba Reddy GorlaAbstract:Abstract The purpose of this study is to investigate the unsteady magnetohydrodynamic three-dimensional flow induced by a stretching surface. An incompressible electrically conducting Eyring-Powell fluid fills the convectively heated stretching surface in the presence of nanoparticles. The effects of thermal radiation, viscous dissipation and Joule heating are accounted in heat transfer equation. The model used for the nanofluid includes the effects of Brownian motion and thermophoresis. The highly nonlinear partial differential equations are reduced to ordinary differential equations with the help of Similarity Method. The reduced complicated two-point boundary value problem is treated numerically using Runge–Kutta–Fehlberg 45 Method with shooting technique. A comparison of the obtained numerical results with existing results in a limiting sense is also presented. At the end, the effects of influential parameters on velocity, temperature and nanoparticles concentration fields are also discussed comprehensively. Further, the physical quantities of engineering interest such as the Nusselt number and Sherwood number are also calculated.
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Mixed convection from a wavy surface embedded in a thermally stratified nanofluid saturated porous medium with non-linear Boussinesq approximation
International Communications in Heat and Mass Transfer, 2016Co-Authors: Peri K. Kameswaran, B. Vasu, P. V. S. N. Murthy, Rama Subba Reddy GorlaAbstract:Abstract In this article, we have made an attempt to study the convective heat transfer in the influence of non-linear Boussinesq approximation, thermal stratification and convective boundary conditions on non-Darcy nanofluid flow over a vertical wavy surface. The surface of the vertical wavy plate, put up at convective temperature and concentration. A coordinate transformation is used to transform the wavy surface into smooth surface. Using local Similarity and non-Similarity Method the governing nondimensional equations are transformed into coupled nonlinear ordinary differential equations. Effects of thermal convective parameter, thermal stratification parameter, Lewis number, Sherwood number on the wave geometry on the heat and mass transfer characteristics have been studied. Numerical results have been obtained for various physical parameters. A comparison of the present results is made with the earlier published results and is found to be in good agreement.
Ting Lan - One of the best experts on this subject based on the ideXlab platform.
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time domain global Similarity Method for automatic data cleaning for multi channel measurement systems in magnetic confinement fusion devices
Computer Physics Communications, 2019Co-Authors: Ting Lan, Jian Liu, Hong QinAbstract:Abstract To guarantee the availability and reliability of data source in Magnetic Confinement Fusion (MCF) devices, incorrect diagnostic data, which cannot reflect real physical properties of measured objects, should be sorted out before further analysis and study. Traditional data sorting cannot meet the growing demand of MCF research because of the low-efficiency, time-delay, and lack of objective criteria. In this paper, a Time-Domain Global Similarity (TDGS) Method based on machine learning technologies is proposed for the automatic data cleaning of MCF devices. The aim of traditional data sorting is to classify original diagnostic data sequences. The lengths and evolution properties of the data sequences vary shot by shot. Hence the classification criteria are affected by many discharge parameters and are different in various discharges. The focus of the TDGS Method is turned to the physical Similarity between data sequences from different channels, which are more independent of discharge parameters. The complexity arisen from real discharge parameters during data cleaning is avoided in the TDGS Method by transforming the general data sorting problem into a binary classification problem about the physical Similarity between data sequences. As a demonstration of its application to multi-channel measurement systems, the TDGS Method is applied to the EAST POlarimeter–INTerferometer (POINT) system. The optimal performance of the Method evaluated by 24-fold cross-validation has reached 0.9871 ± 0.0385.
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time domain global Similarity Method for automatic data cleaning for multi channel measurement systems in magnetic confinement fusion devices
arXiv: Plasma Physics, 2017Co-Authors: Ting Lan, Jian Liu, Hong QinAbstract:To guarantee the availability and reliability of data source in Magnetic Confinement Fusion (MCF) devices, incorrect diagnostic data, which cannot reflect real physical properties of measured objects, should be sorted out before further analysis and study. Traditional data sorting cannot meet the growing demand of MCF research because of the low-efficiency, time-delay, and lack of objective criteria. In this paper, a Time-Domain Global Similarity (TDGS) Method based on machine learning technologies is proposed for the automatic data cleaning of MCF devices. Traditional data sorting aims to the classification of original diagnostic data sequences, which are different in both length and evolution properties under various discharge parameters. Hence the classification criteria are affected by many discharge parameters and vary shot by shot. The focus of TDGS Method is turned to the physical Similarity between data sequences from different channels, which are more essential and independent of discharge parameters. The complexity arisen from real discharge parameters during data cleaning is avoided in the TDGS Method by transforming the general data sorting problem into a binary classification problem about the physical Similarity between data sequences. As a demonstration of its application to multi-channel measurement systems, the TDGS Method is applied to the EAST POlarimeter-INterferomeTer (POINT) system. The optimized performance of the Method has reached 0.9871.
Junhong Zhang - One of the best experts on this subject based on the ideXlab platform.
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flow and radiation heat transfer of a nanofluid over a stretching sheet with velocity slip and temperature jump in porous medium
Journal of The Franklin Institute-engineering and Applied Mathematics, 2013Co-Authors: Liancun Zheng, Chaoli Zhang, Xinxin Zhang, Junhong ZhangAbstract:Abstract In this paper, we present an investigation for the flow and radiation heat transfer of a nanofluid over a stretching sheet with velocity slip and temperature jump in porous medium. The Brownian motion and thermophoresis are taken into account according to Rosseland’s approximation. The governing coupled partial differential equations are non-dimensionalized and solved both numerically and analytically by local Similarity Method. The effects of involved parameters (velocity slip, temperature jump, thermal radiation, Prandtl number, Lewis number, Brownian motion, thermophoresis) on velocity, temperature and concentration profiles are presented graphically and analyzed. Moreover, the numerical results are compared with the analytical solutions obtained by Homotopy analysis Method with very good agreement to validate the present results.
M M Rashidi - One of the best experts on this subject based on the ideXlab platform.
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entropy analysis of convective mhd flow of third grade non newtonian fluid over a stretching sheet
Ain Shams Engineering Journal, 2017Co-Authors: M M Rashidi, Saeed Bagheri, E Momoniat, Navid FreidoonimehrAbstract:Abstract The purpose of this article is to study and analyze the convective flow of a third grade non-Newtonian fluid due to a linearly stretching sheet subject to a magnetic field. The dimensionless entropy generation equation is obtained by solving the reduced momentum and energy equations. The momentum and energy equations are reduced to a system of ordinary differential equations by a Similarity Method. The optimal homotopy analysis Method (OHAM) is used to solve the resulting system of ordinary differential equations. The effects of the magnetic field, Biot number and Prandtl number on the velocity component and temperature are studied. The results show that the thermal boundary-layer thickness gets decreased with increasing the Prandtl number. In addition, Brownian motion plays an important role to improve thermal conductivity of the fluid. The main purpose of the paper is to study the effects of Reynolds number, dimensionless temperature difference, Brinkman number, Hartmann number and other physical parameters on the entropy generation. These results are analyzed and discussed.
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analytic solution of steady three dimensional problem of condensation film on inclined rotating disk by differential transform Method
Mathematical Problems in Engineering, 2010Co-Authors: M M Rashidi, Seyyed AminAbstract:The differential transform Method (DTM) is applied to the steady three-dimensional problem of a condensation film on an inclined rotating disk. With Similarity Method, the governing equations can be reduced to a system of nonlinear ordinary differential equations. The approximate solutions of these equations are obtained in the form of series with easily computable terms. The velocity and temperature profiles are shown and the influence of Prandtl number on the temperature profiles is discussed in detail. The validity of our solutions is verified by the numerical results.
