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Academic Biography

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.

Education

  • Ph.D. 2004

    Ph.D. in Mechanical Engineering, Nuclear Energy Engineering, 2004

    SHARIF University of Technology, Tehran, Iran

  • M.S. 1999

    M.Sc. in Nuclear Energy Engineering, 1999

    Amir-Kabir University, Tehran, Iran

  • B.S. 1996

    B.Sc. in Applied Physics, 1996

    Tehran University, Tehran, Iran

Honors, Awards and Grants

  • 2016
    Distinguished Professor in Education and Training
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    Department of Energy Engineering in SHARIF University of Technology
  • 2015
    Distinguished Professor in Research
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    Department of Energy Engineering in SHARIF University of Technology
  • 2012
    Distinguished Professor in Education and Training
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    Department of Energy Engineering in SHARIF University of Technology
  • 2007
    Acceptance in Post-Doctoral position in Sweden, Chalmers University of Technology, Department of Physics, Nuclear Engineering Section
  • 2005-2010
    Associate Member of ICTP, Trieste, Italy
  • 2004
    Privileged graduated in Ph.D degree from Sharif University of Technology

Research Summary

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

Interests

  • [InterestSubject]
  • Stochastic Process
  • Transport Theory
  • Monte Carlo Method
  • Discrete Physics

Teaching

Current Teaching

  • 2007-Now
    Reactor Physics 1
  • 2008-Now
    Reactor Physics 2
  • 2008-Now
    Monte Carlo Method
  • 2008-Now
    Fuel Management
  • 2008-Now
    Transport Theory and Stochastic Process
  • 2008-Now
    Advanced Nuclear Computational Codes

Publications in Journals

Link of Google Scholar

https://scholar.google.com/citations?user=FcOTMpsAAAAJ&hl=enl


Application of deep learning techniques for nuclear power plant transient identification

Ramazani I., Vosoughi N., Ghofrani M.B.
[PublicationType] Paper Annals of Nuclear Energy ,2023 , Vol.194, 110113.

Axial-offset analysis in iPWR by developing the neutronic/ thermal-hydraulic core simulator based on coarse-mesh methods

Kolali A., Naghavi Dizji D., Ghaffari M., Vosoughi N.
[PublicationType] Paper Annals of Nuclear Energy ,2023 , Vol.181, 109566.

Development of a calculation model to simulate the effect of bowing of the VVER-1000 reactor fuel assembly on power distribution

Vosoughi J., Vosoughi N., Salehi A.A.
[PublicationType] Paper Annals of Nuclear Energy ,2023 , Vol.181, 109535.

Evaluation of the performance of different feature selection techniques for identification of NPPs transients using deep learning

Ramazani I.,Moshkbar Kh., Vosoughi N., Ghofrani M.B.
[PublicationType] Paper Annals of Nuclear Energy ,2023 , Vol.183, 109668.

Comparative assessment of passive scattering and active scanning proton therapy techniques using Monte Carlo simulations

Asadi A., Hosseini S.A., Akhavan A., Vosoughi N., Zeidi H.
[PublicationType] Paper Journal of Instrumentation,2022 ,17 P09008.

Investigation of the use of momentum and Galerkin weighting functions in high-order Nodal expansion method to solve the neutron diffusion equation

Kolali A., Naghavi Dizji D., Vosoughi N.
[PublicationType] Paper Radiation Physics and Engineering,2022 ,3(3): pages:39-45

Modeling and optimization of respiratory-gated partial breast irradiation with proton beams - A Monte Carlo study

Piruzan E., Vosoughi N., Mahani H.
[PublicationType] Paper Computers in Biology and Medicine,2022 ,Vol. 147.

Preclinical evaluation of 188-Re-HYNIC-PSMA as a novel therapeutic agent

Hadisi M., Vosoughi N., Yousefnia H., et. Al.
[PublicationType] PaperJOURNAL OF RADIOANALYTICAL AND NUCLEAR CHEMISTRY,2022 ,Vol. 331,pages 841-849.

Applications of Soft Computing in nuclear power plants: A review.

Ramazani, I., Moshkbar Kh., Vosoughi N.,Ghofrani M.B.
[PublicationType] Paper Progress in Nuclear Energy, Vol. 149,2022 , 104253.

Target motion management in breast cancer radiation therapy

Piruzan E., Vosoughi N., Mahdavi S.R., Khalafi L., Mahani H.
[PublicationType] Paper 2021 ,Radiology Oncology.

A new approach for solution of time dependent neutron transport equation based on nodal discretization using MCNPX code with feedback.

Ghaderi, M., Salehi A.A., Vosoughi N.
[PublicationType] Paper Annals of Nuclear Energy, Volume 133, 2019, Pages 519-526.

[Abstract]

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 time dependent Monte Carlo approach for nuclear reactor analysis in a 3-D arbitrary geometry.

Ghaderi, M., Salehi A.A., Vosoughi N.
[PublicationType] Paper Progress in Nuclear Energy, Volume 115, 2019, Pages 80-90.

Abstract

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/.

SGSD: A novel Sequential Gamma-ray Spectrum Deconvolution algorithm.

Shahabinejad H., Vosoughi N.
[PublicationType] Paper Annals of Nuclear Energy, Volume 132, 2019, Pages 369-380.

Abstract

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.

Contact & Meet Me

At My Office

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.

At My Home

To Be Completed.