Dr. Naser Vosoughi is a professor in Nuclear Energy Engineering at Department of Energy Engineering, SHARIF University of Technology in Tehran, IRAN.
He has aquired about 2 years international work experience in a capacity of academic visitor in Trieste University (Italy), Chalmers University (Sweden) and International Center for Theoretical Physics (ICTP). He has been the author and/or co-author of 2 books and more than 60 ISI journal papers.
Ph.D. in Mechanical Engineering, Nuclear Energy Engineering, 2004
SHARIF University of Technology, Tehran, Iran
M.Sc. in Nuclear Energy Engineering, 1999
Amir-Kabir University, Tehran, Iran
B.Sc. in Applied Physics, 1996
Tehran University, Tehran, Iran
1) Neutronic and Thermohydraulic Noise Analysis
2) Accident Prediction by Noise Analysis
3) Application of Discrete physics to Neutron and Gamma Transport
4) Application of Monte Carlo method to neutron and photon transport
5) Stochastic process in nuclear reactor
6) Radiation Application in Industry and Medicine
7) Ion therapy Simulation and Optimization
8) Radiation Detection and spectroscopy
9) Nuclear reactor physics
10) Plasma Focus (PF)
11) Nuclear reactor dynamic
12) Nuclear Data processing
13) Nuclear reactor simulation
Link of Google Scholar
This paper proposes a new method for solving the time-dependent neutron transport equation based on nodal discretization using the MCNPX code. Most valid nodal codes are based on the diffusion theory with differences in approximating the leakage term until now. However, the Monte Carlo (MC) method is able to estimate transport parameters without approximations usual in diffusion method. Therefore, improving the nodal approach via the MC techniques can substantially reduce the errors caused by diffusion approximations. In the proposed method, the reactor core is divided into nodes of arbitrary dimensions, and all terms of the transport equation e.g. interaction rates and leakage ratio are estimated using MCNPX. They are then employed within the time-dependent neutron transport equation for each node independently to compute the neutron population. Based on this approach, a time-dependent code namely MCNP-NOD (MCNPX code based on a NODal discretization) was developed for solving timedependent transport equation in an arbitrary geometry considering feed backs. The MCNP-NOD is able to simulate multi-group processes using appropriate libraries. Several test problems are examined to evaluate the method.
A highly reliable tool for transient simulation is vital in the safety analysis of a nuclear reactor. Despite this fact most tools still use diffusion theory and point-kinetics that involve many approximation such as discretization in space, energy, angle and time. However, Monte Carlo method inherently overcomes these restrictions and provides an appropriate foundation to accurately calculate the parameters of a reactor. In this paper fundamental parameters like multiplication factor (Keff) and mean generation time (tG) are calculated using Monte Carlo method and then employed in transient analysis for computing the neutron population, proportional to Keff, during a generation time considering precursors decay. Based on this approach, a dynamic Monte Carlo code named MCSP (Monte Carlo dynamic Simulation of Particles tracking) is developed for both the steady state and time-dependent simulation of particle tracking in an arbitrary 3D geometry. MCSP is able to use either continuous or multi-group energy cross section libraries. To speed up the simulation, the MCSP was empowered with parallel processing as well. Several test problems such as C5G7, LMW and TWIGL are examined to assess the performance of the method. https://www.sciencedirect.com/science/article/pii/S0149197019300897/.
AA novel approach for analyzing complex gamma-ray spectra using a sequential algorithm is introduced. The developed Sequential Gamma-ray Spectrum Deconvolution (SGSD) algorithm produces a sequence of spectra converging to the best estimation of output spectrum of a gamma-ray detector. In each point of sequence, an isotope of unknown gamma-ray source is identified and the respective response of the detector to unknown source is reconstructed. Effectiveness of the developed algorithm is demonstrated by two empirical and simulation studies. In the case of empirical study, a number of recorded gamma-ray spectra related to a mixed gamma-ray source including different combinations of 5 isotopes (Co-60, Cs-137, Na-22, Eu-152 and Am-241) are analyzed using whole information of spectra. Furthermore, a number of simulated gamma-ray spectra related to a mixed gamma-ray source including different combinations of 30 isotopes are analyzed in simulation study. Both man-made and natural radioisotopes like Ba-133, Co-60, Ir-192, Cs-137, K-40, Th-232 series, U-238 series, Ac-227 series, etc. are used for Monte Carlo simulations. The numerical results of the SGSD algorithm are compared with those of the conventional Non-Negative Least Squares (NNLS) algorithm. Based on the results, the identification procedure of the SGSD algorithm has a remarkable superiority over the NNLS algorithm.
Address: Department of Energy Engineering, SHARIF University of Technology, Tehran, Iran.
I am at my office from 8:00 am to 8:00 pm every working days, but you may send me an email to fix an appointment.
To Be Completed.