Mehrdad Shahmohammadi Beni
City University of Hong Kong
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Featured researches published by Mehrdad Shahmohammadi Beni.
Journal of Radiation Research | 2016
Mehrdad Shahmohammadi Beni; Dragana Krstic; D. Nikezic; K.N. Yu
Many studies on biological effects of neutrons involve dose responses of neutrons, which rely on accurately determined absorbed doses in the irradiated cells or living organisms. Absorbed doses are difficult to measure, and are commonly surrogated with doses measured using separate detectors. The present work describes the determination of doses absorbed in the cell layer underneath a medium column (DA) and the doses absorbed in an ionization chamber (DE) from neutrons through computer simulations using the MCNP-5 code, and the subsequent determination of the conversion coefficients R (= DA/DE). It was found that R in general decreased with increase in the medium thickness, which was due to elastic and inelastic scattering. For 2-MeV neutrons, conspicuous bulges in R values were observed at medium thicknesses of about 500, 1500, 2500 and 4000 μm, and these were attributed to carbon, oxygen and nitrogen nuclei, and were reflections of spikes in neutron interaction cross sections with these nuclei. For 0.1-MeV neutrons, no conspicuous bulges in R were observed (except one at ~2000 μm that was due to photon interactions), which was explained by the absence of prominent spikes in the interaction cross-sections with these nuclei for neutron energies <0.1 MeV. The ratio R could be increased by ~50% for small medium thickness if the incident neutron energy was reduced from 2 MeV to 0.1 MeV. As such, the absorbed doses in cells (DA) would vary with the incident neutron energies, even when the absorbed doses shown on the detector were the same.
Biointerphases | 2015
Mehrdad Shahmohammadi Beni; K.N. Yu
A promising application of plasma medicine is to treat living cells and tissues with cold plasma. In cold plasmas, the fraction of neutrals dominates, so the carrier gas could be considered the main component. In many realistic situations, the treated cells are covered by a fluid. The present paper developed models to determine the temperature of the fluid at the positions of the treated cells. Specifically, the authors developed a three-phase-interaction model which was coupled with heat transfer to examine the injection of the helium carrier gas into water and to investigate both the fluid dynamics and heat transfer output variables, such as temperature, in three phases, i.e., air, helium gas, and water. Our objective was to develop a model to perform complete fluid dynamics and heat transfer computations to determine the temperature at the surface of living cells. Different velocities and plasma temperatures were also investigated using finite element method, and the model was built using the comsol multiphysics software. Using the current model to simulate plasma injection into such systems, the authors were able to investigate the temperature distributions in the domain, as well as the surface and bottom boundary of the medium in which cells were cultured. The temperature variations were computed at small time intervals to analyze the temperature increase in cell targets that could be highly temperature sensisitve. Furthermore, the authors were able to investigate the volume of the plasma plume and its effects on the average temperature of the medium layer/domain. Variables such as temperature and velocity at the cell layer could be computed, and the variations due to different plume sizes could be determined. The current models would be very useful for future design of plasma medicine devices and procedures involving cold plasmas.
Heat Transfer Engineering | 2018
Wenzhong Zhou; Shripad T. Revankar; Rong Liu; Mehrdad Shahmohammadi Beni
ABSTRACT The development of ceramic-ceramic composite nuclear fuels benefits from thermal modeling by providing an understanding on how fabrication variables, such as phase fractions, densities, and geometry, will determine effective thermal conductivity. Finite element method (FEM) two and three dimensional programs were used to predict the thermal conductivity of composite UO2-BeO materials. The FEM modeling results were compared to the measured UO2-BeO fuel sample thermal conductivities. The comparison showed that the thermal modeling was in good agreement with the measured values. These benchmarking cases with the FEM thermal modeling method successfully demonstrated the potential of the models to accurately predict the effective thermal conductivity of an enhanced thermal conductivity oxide nuclear fuel. The FEM thermal modeling was used to predict UO2-BeO nuclear fuel thermal conductivities with different BeO percentages, and then the reactor fuel thermal behavior was analyzed using the UO2-BeO nuclear fuel thermal conductivities and other material properties. The analysis results show significant temperature decrease for the UO2-BeO nuclear fuel compared to the traditional UO2 fuel, and then the safety of the reactor would be improved.
PLOS ONE | 2017
Mehrdad Shahmohammadi Beni; C. Y. P. Ng; Dragana Krstic; D. Nikezic; K.N. Yu
Radiotherapy is a common cancer treatment module, where a certain amount of dose will be delivered to the targeted organ. This is achieved usually by photons generated by linear accelerator units. However, radiation scattering within the patient’s body and the surrounding environment will lead to dose dispersion to healthy tissues which are not targets of the primary radiation. Determination of the dispersed dose would be important for assessing the risk and biological consequences in different organs or tissues. In the present work, the concept of conversion coefficient (F) of the dispersed dose was developed, in which F = (Dd/Dt), where Dd was the dispersed dose in a non-targeted tissue and Dt is the absorbed dose in the targeted tissue. To quantify Dd and Dt, a comprehensive model was developed using the Monte Carlo N-Particle (MCNP) package to simulate the linear accelerator head, the human phantom, the treatment couch and the radiotherapy treatment room. The present work also demonstrated the feasibility and power of parallel computing through the use of the Message Passing Interface (MPI) version of MCNP5.
Journal of Radiation Research | 2017
Mehrdad Shahmohammadi Beni; Dragana Krstic; D. Nikezic; K.N. Yu
ABSTRACT A calibration coefficient R (= DA/DE) for photons was employed to characterize the photon dose in radiobiological experiments, where DA was the actual dose delivered to cells and DE was the dose recorded by an ionization chamber. R was determined using the Monte Carlo N-Particle version 5 (MCNP-5) code. Photons with (i) discrete energies, and (ii) continuous-energy distributions under different beam conditioning were considered. The four studied monoenergetic photons had energies E = 0.01, 0.1, 1 and 2 MeV. Photons with E = 0.01 MeV gave R values significantly different from unity, while those with E > 0.1 MeV gave R ≈ 1. Moreover, R decreased monotonically with increasing thickness of water medium above the cells for E = 0.01, 1 or 2 MeV due to energy loss of photons in the medium. For E = 0.1 MeV, the monotonic pattern no longer existed due to the dose delivered to the cells by electrons created through the photoelectric effect close to the medium–cell boundary. The continuous-energy distributions from the X-Rad 320 Biological Irradiator (voltage = 150 kV) were also studied under three different beam conditions: (a) F0: no filter used, (b) F1: using a 2 mm-thick Al filter, and (c) F2: using a filter made of (1.5 mm Al + 0.25 mm Cu + 0.75 mm Sn), giving mean output photon energies of 47.4, 57.3 and 102 keV, respectively. R varied from ~1.04 to ~1.28 for F0, from ~1.13 to ~1.21 for F1, and was very close to unity for F2.
PLOS ONE | 2017
Mehrdad Shahmohammadi Beni; Tak Cheong Hau; Dragana Krstic; D. Nikezic; K.N. Yu
Monte Carlo method was used to study the characteristics of neutron interactions with cells underneath a water medium layer with varying thickness. The following results were obtained. (1) The fractions of neutron interaction with 1H, 12C, 14N and 16O nuclei in the cell layer were studied. The fraction with 1H increased with increasing medium thickness, while decreased for 12C, 14N and 16O nuclei. The bulges in the interaction fractions with 12C, 14N and 16O nuclei were explained by the resonance spikes in the interaction cross-section data. The interaction fraction decreased in the order: 1H > 16O > 12C > 14N. (2) In general, as the medium thickness increased, the number of “interacting neutrons” which exited the medium and then further interacted with the cell layer increased. (3) The area under the angular distributions for “interacting neutrons” decreased with increasing incident neutron energy. Such results would be useful for deciphering the reasons behind discrepancies among existing results in the literature.
PLOS ONE | 2016
D. Nikezic; Mehrdad Shahmohammadi Beni; Dragana Krstic; K.N. Yu
Monte Carlo method has been used to determine the efficiency for proton production and to study the energy and angular distributions of the generated protons. The ENDF library of cross sections is used to simulate the interactions between the neutrons and the atoms in a polyethylene (PE) layer, while the ranges of protons with different energies in PE are determined using the Stopping and Range of Ions in Matter (SRIM) computer code. The efficiency of proton production increases with the PE layer thickness. However the proton escaping from a certain polyethylene volume is highly dependent on the neutron energy and target thickness, except for a very thin PE layer. The energy and angular distributions of protons are also estimated in the present paper, showing that, for the range of energy and thickness considered, the proton flux escaping is dependent on the PE layer thickness, with the presence of an optimal thickness for a fixed primary neutron energy.
Annals of Nuclear Energy | 2016
M.M. Rahman; Ji Dongxu; Mehrdad Shahmohammadi Beni; Ho Choi Hei; Weidong He; Jiyun Zhao
Results in physics | 2017
P.M. Chan; C. Y. P. Ng; Mehrdad Shahmohammadi Beni; S.S. Law; K.N. Yu
Annals of Nuclear Energy | 2018
Mehrdad Shahmohammadi Beni; Jiyun Zhao; K.N. Yu