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Approximate Normalization of Numeric Continuum State Wave Functions and Integral Processing of Residues in TRK Sums
CAO Wei, ZHU Yun-xia, LU Hui, HE Li-ming
CHINESE JOURNAL OF COMPUTATIONAL PHYSICS    2006, 23 (1): 115-119.  
Abstract302)      PDF (203KB)(705)      
With an improved Numerov algorithm, continuum state wave functions and its normalization are investigated. Cowan' s normalization is discussed and a more precise and effective calculation is offered. We calculate the Thomas-Reiche-Kuhn(TRK) sum of several hydrogen atomic states (l=0~3). The least-squared method is used to generate infinite asymptotical forms of TRK. The residues are approximately calculated with an integral processing.
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Scattering phase function for fibrous layer considering fiber orientation
Li Bingxi, Bie Rushan, Lu Huilin, Yang Lidan
CHINESE JOURNAL OF COMPUTATIONAL PHYSICS    1999, 16 (6): 592-598.  
Abstract256)      PDF (301KB)(684)      
Phase functions for fibrous layer are obtained for two types of fiber orientation:randomly oriented in space and randomly oriented in a plane parallel to the boundary surfaces of the layer.Two types of incident radiation are considered,namely,the radiation normal to the boundaries and the diffuse radiation.The phase functions for the fibrous layer are derived as a function of the polar angle measured within a coordinate system fixed to the fibrous layer.The effects of the type of incidence,size parameter,fiber orientation and complex refractive index are studied.
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Uniform shear flow of fluidized gas solid granular flow at low concentration
Lu Huilin, Zhao Guangbo, Liu Wentie, Bie Rushan
CHINESE JOURNAL OF COMPUTATIONAL PHYSICS    1999, 16 (4): 436-441.  
Abstract213)      PDF (223KB)(701)      
The steady uniform shear flow in a low concentration fluidized gas solid granular flow is studied on the basis of the kinetic theory of granular flow and a modified BGK model equation. Explicit expressions of the pressure tensor are obtained as a function of the restitution coefficient. The computation shows the different normal stresses distribution. The results agree well with the Jenkins Richman theories, although significant discrepancy appears for granular temperature distributions.
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MODELLING THE IONIZATION POTENTIAL OF HALO ALKANES BY NEURAL NETWORK APPROACH
He Liming, Bao Yushi, Lu Hui, Jin Qianyuan
CHINESE JOURNAL OF COMPUTATIONAL PHYSICS    1997, 14 (6): 770-776.  
Abstract255)      PDF (236KB)(763)      
The Back propagation(BP) model of neural network is used to calculate the first ionization potention(IP) of haloalkanes.By optimizing the neural network,the standard deviation of errors of prediction(SDEP) using leave one out method within the known samples is 0.34eV,which is better than the reported predicting and calculating results by PLS.
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