A locally conservative Galerkin (LCG) finite element method is proposed for two-phase flow simulations in heterogeneous porous media. The main idea of it is to use property of local conservation at steady state conditions to define a numerical flux at element boundaries. It provides a way to apply standard Ga/erkin finite element method in two-phase flow simulations in porous media. LCG method has all advantages of standard finite element method while explicitly conserving fluxes over each element. Several problems are solved to demonstrate accuracy of the method. All examples show that the formulation is accurate and robust, while CPU time is significantly less than mixed finite element method.

Hartree-Fock and hybrid DFT and Hartree-Fock methods am used to calculate Young modulus of carbon nanotubos on the basis of ab-initio theory with program Crystal03.Calculated result with Hartree-Fock approximation agrees with other theoretical and experimental ones-Result with hybrid DFT and Hartree-Fock is smaller.Young's modulus of C nanotube depends on geometric structure and electronic structure as well.

The differences of space distributions and time profiles between the γ-ray and proton induced showers in YBJ-ARGO experiment are studied using Monte Carlo simulation data.An artificial neural algorithm is used to identify the primary γ-ray and proton induced showers.It is shown that the separation of γ-rays and protons can be achieved with a good efficiency in the energy range of 0.1~10 TeV.

A Monte Carlo simulation for the hybrid experiment of air shower array and emulsion chambers at Yangbajing is done with different interaction models.The feasibility of distinguishing primary cosmic ray components by use of the method of artificial neural netwo rks is studied with the simulation data.T he analysis indicates that the showers induced by primary protons can be efficiently selected by using this method, but the results obtained appear to be dependent on interaction model.The corresponding systematic error is also estimated.

An interval method is given for solving constrained nonlinear programming. Continuous interval extension and the function test are used to delete all the unnecessary elements. The optimum solution and optimum value are obtained at the same time during the process of iteration. Numerical example is given and the result show that the method works well.