In order to obtain more reaction information of neutron or the other secondary particles by forcing the collision to occur within a small time step, three Monte Carlo Time Forced Collision (TFC) sampling methods called discrete, large cross section and uniform time sampling method are presented, derived and tested. TFC method can be used in more complicated eases. For example, particle transporte through continuously changing materials within a cut time. Numerical results of simple multiplication system show that the calculation efficiency of TFC method is higher than that of the analog method by 2~4 magnitudes.

A parallel algorithm for time-independent Monte Carlo transport is successful since particles are independent and they are distributed to multiple processors.However,for time-dependent Monte Carlo transport problems, the parallel efficiency reduces and the parallel scale is limited due to the communication of scattering source attribute and meshes in each time-step.We propose two algorithms in them adaptive processor assignment and optimized processor choice are obtained.With a Monte Carlo stratified sampling technique for scattering source treatment the communication cost is reduced greatly.The parallel expandability is improved.A large speedup over the basic algorithm is obtained.

In recent years an improved method develops for calculating the flux contribution of particle scattering within the solid angle subtended by finite detector, then the distribution sampling in local range becomes to be needed. Sampling of Klein-Nishina distribution within the limits of local range indicates that the sampling of out direction of photon is limited within local range in compton scattering. For this, four valid sampling methods of Klein-Nishina distribution in local range are presented, all of them are simulated in computer and compared each other.