A Roe scheme for the bi-temperature model of magnetohydrodynamics

2008 ◽  
pp. 260-265 ◽  
Author(s):  
M. S. Brassier ◽  
G. Gallice
Keyword(s):  
Temperature Model

GENERAILIZED TWO-TEMPERATURE MODEL FOR COUPLED PHONONS IN NANOSIZED GRAPHENE

2018 ◽  
Author(s):  
Meng An ◽  
Qichen Song ◽  
Xiaoxiang Yu ◽  
Han Meng ◽  
Dengke Ma ◽  
...  
Keyword(s):  
Temperature Model ◽  
Two Temperature

scholarly journals Modeling of Thermal Effects in Semiconductor Structures

VLSI Design ◽  
1998 ◽  
Vol 8 (1-4) ◽  
pp. 53-58
Author(s):  
Christopher M. Snowden
Keyword(s):  
Thermal Effects ◽  
Large Scale ◽  
High Electron Mobility Transistors ◽  
Thermal Modelling ◽  
High Electron ◽  
Temperature Model ◽  
Active Devices ◽  
Electron Mobility Transistors ◽  
Fully Coupled ◽  
Scale Surface

A fully coupled electro-thermal hydrodynamic model is described which is suitable for modelling active devices. The model is applied to the non-isothermal simulation of pseudomorphic high electron mobility transistors (pHEMTs). A large-scale surface temperature model is described which allows thermal modelling of semiconductor devices and monolithic circuits. An example of the application of thermal modelling to monolithic circuit characterization is given.

A Theoretical Analysis of CO2 Absorption in Sun Versus Shade Leaves

1978 ◽  
Vol 100 (1) ◽  
pp. 20-24 ◽  
Author(s):  
R. H. Rand
Keyword(s):  
Experimental Data ◽  
Quantitative Estimate ◽  
Geometric Model ◽  
Model Parameters ◽  
Co2 Absorption ◽  
Temperature Model ◽  
Spongy Mesophyll ◽  
One Dimensional ◽  
Mesophyll Tissue ◽  
Shade Leaves

A one-dimensional, steady-state, constant temperature model of diffusion and absorption of CO2 in the intercellular air spaces of a leaf is presented. The model includes two geometrically distinct regions of the leaf interior, corresponding to palisade and spongy mesophyll tissue, respectively. Sun, shade, and intermediate light leaves are modeled by varying the thicknesses of these two regions. Values of the geometric model parameters are obtained by comparing geometric properties of the model with experimental data of other investigators found from dissection of real leaves. The model provides a quantitative estimate of the extent to which the concentration of gaseous CO2 varies locally within the leaf interior.

EIGEN-TEMPERATURE MODEL FOR THE ANNUAL AIR TEMPERATURE MOVEMENT EVALUATION AND FORECAST

2013 ◽  
Vol 04 (03) ◽  
pp. 1350008 ◽  
Author(s):  
ZONG-CHANG YANG
Keyword(s):  
Air Temperature ◽  
Principal Component ◽  
Ar Model ◽  
Temperature Model ◽  
Polynomial Curve ◽  
Actual Observation ◽  
Fitting Algorithm ◽  
Global Concern ◽  
Polynomial Curve Fitting ◽  
Result Analysis

Climate variability and its changes are issues of broader global concern. This study addresses the annual air temperature movement evaluation and forecasting based on principal component analysis (PCA). An Eigen-temperature model for describing the annual air temperature movement by employing PCA is introduced. Subspace for evaluation is generated by selecting principal orthogonal eigenvectors of covariance matrix of temperature data. The principal eigenvectors are called "Eigen-temperatures", since they are eigenvectors and each temperature movement is described by them. Each temperature movement is projected onto the subspace of eigenspace, and described by a linear combination of the Eigen-temperatures. Then, a forecast method for the temperature movement by employing the Eigen-temperatures is proposed. Forecast is implemented with polynomial curve fitting algorithm to estimate subsequent representation weights for the subsequent temperature movement with respect to the "Eigen-temperatures" generated by its previous temperature movements. The proposed Eigen-temperature model is applied to evaluation and forecasting for annual temperature movement at Tongchuan observation station of China from 1962 to 1971 and from 1994 to 2002. Experimental results agreeing well with actual observation values show workability of the proposed. Result analysis indicates its effectiveness that the proposed Eigen-temperature model is outperforming the classical AR model and the BP-ANN on the forecast tasks.

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