scholarly journals NEUTRON DEPTH PROFILE CALCULATIONS USING ARTIFICIAL NEURAL NETWORKS

2021 ◽  
Vol 247 ◽  
pp. 06046
Author(s):  
K. Hossny ◽  
S. Magdi ◽  
F. Nasr ◽  
Y. Yasser ◽  
A. Magdy

Neutron depth profiling (NDP) is a non-destructive technique used for identifying the concentration of impurity isotopes below the sample surface. NDP is carried out by detection of the emitted charged particles resulting from bombarding the sample with neutrons. NDP specifies the isotopic concentration versus the sample depth for a few micrometers below the surface. The sample is bombarded inside a research reactor using a thermal neutron beam. Charged particles like alpha particles or protons are produced from the neutron induced reactions in the sample. Each neutron isotopic interaction produces a certain Q, indicating a specific kinetic energy for the emitted charged particle. As the charged particle travels through the sample to eject the surface, it loses energy to atoms (electrons) on its path. The charged particle energy loss holds information regarding the number of atoms by which the emitted particle passed, thus indicating its original depth. The purpose of this work is to check the capability of Artificial Neural Networks (ANNs) in predicting the boron concentration profile across a boro-silicate sample of thickness 3.5 μm divided into 10 layers. Each layer included different boron concentration than the other. Also, the boron concentration had the values {0.1, 0.2, 0.3, 0.4, 0.5, 0.6, 0.7, 0.8, 0.9, 1}. Training, validation, and test data were generated synthetically using MCNP6 in which the boron concentrations varied in the layer number from one sample to another. MCNP6 model consisted of a silicon barrier detector, boro-silicate sample, chamber body and an idealized thermal neutron source. The detector, sample, and the source were located in a voided chamber. The samples were irradiated with a 0.025 eV monoenergetic thermal neutron beam from a monodirectional disk source. To cover the whole area of the samples, the thermal neutron beam had a radius of 3 cm. The silicon detector active volume was modelled as a 100 μm thick and 3 cm radius facing the sample directly. The sample, beam, and the detector were placed on the same axis. Ten ANN regression models were developed, one for each layer boron concentration prediction where the input for each model was the alpha spectrum read by the detector, while the output was the boron concentration for each layer. Results showed regression values higher than 0.94 for all of the developed models. ANNs proved its capability of predicting the boron profile form the alpha spectrum read by the detector regarding neutron depth profiling in a boro-silicate samples.

Author(s):  
Hiroshi Fukuda ◽  
Toru Kobayashi ◽  
Taiju Matsuzawa ◽  
Keiji Kanda ◽  
Masamitzu Ichihashi ◽  
...  

2005 ◽  
Vol 35 (3b) ◽  
Author(s):  
Gevaldo L. de Almeida ◽  
Maria Ines Silvani ◽  
Rosanne C. A. A. Furieri ◽  
Marcelo J. Gonçalves ◽  
Ricardo Tadeu Lopes

2014 ◽  
Vol 2014 (8) ◽  
pp. 83H01-0 ◽  
Author(s):  
G. Croci ◽  
C. Cazzaniga ◽  
G. Claps ◽  
M. Tardocchi ◽  
M. Rebai ◽  
...  

Author(s):  
Peng Dan ◽  
Wu Xiaobo ◽  
Lu Jin ◽  
Hao Qian ◽  
Hong Jingyan ◽  
...  

Boron Neutron Capture Therapy (BNCT) is a kind of the targeted therapy with two element. It can kill the cancer cells while the effect on normal cells is very small, and it is suitable for the treatment of the various stage cancer so it will be the ideal radiotherapy for cancer treatment in the future. And Commercial Miniature Neutron Source Reactor (C-MNSR) was designed and constructed by CIAE, which is used for Neutron Activation Analysis (NAA), Training and teaching. The reactor with thermal power 27kW is an under-moderated reactor with pool-tank type, U-AL alloy with High Enriched Uranium (HEU) as fuel, light water as coolant and moderator, and metal beryllium as reflector. The fission heat produced by the reactor is removed by the natural circulation. Design C-MNSR with a epi-thermal neutron beam for BNCT is studied while the conversion from HEU to LEU (Low Enrichment Uranium) (235U percent≤20%) is carried on. As it has the advantages of MNSR safety, economy, easy operation and its application, and it can improve the epi-thermal neutron flux density and meet the requirements of BNCT. The fuel cage of C-MNSR with size of φ230×248mm in the reactor core, there are ton rows of 355lattices are concentrically arranged, the central lattice is reserved for central control rod, and four tie rods are uniformly arranged at the eighth row which link the upper and lower grid plates, the rest 350 fuel lattices are for fuel pins or dummies. The diameter of the fuel meat is 4.3mm, the height is 230mm, with Uranium enrichment is 17%; the diameter of the fuel element is 5.5mm, the height is 248mm. The frame design of the epithermal neutron beam is: Fluental material used as neutron moderation layer with its thickness is 50cm and its density is 2.85g/cm3; Cd with thickness of 0.1cm used as thermal neutron absorption layer, Lead with thickness of 10cm used as gamma ray shielding layer. And the neutron collimator parts is a composition of graphite, Cd and polythene with boron. The total length of the beam is 114.5cm, and the distance from the exit of the beam to the core is 130cm. The results show that the epithermal neutron flux density at the exit is 1.58 × 109n·cm-2·s-1 at full power of 27kW. and the fast neutron density at the exit is 5.45 × 107n · cm-2 · s-1 at full power. Fast neutron dose contamination (Df/ φepi) is 2.88 × 10−11Gy · cm2 · n−1 and gamma dose contamination (Dγ/φepi) 2.18× 10−14 Gy·cm2·n−1.


hamon ◽  
2006 ◽  
Vol 16 (2) ◽  
pp. 120-122 ◽  
Author(s):  
Naoto Metoki ◽  
Koji Kaneko

2019 ◽  
Vol 14 (01) ◽  
pp. P01017-P01017 ◽  
Author(s):  
L.M.S. Margato ◽  
A. Morozov ◽  
A. Blanco ◽  
P. Fonte ◽  
F.A.F. Fraga ◽  
...  

2019 ◽  
Author(s):  
J. Vacik ◽  
I. Tomandl ◽  
V. Hnatowicz ◽  
P. Horak ◽  
A. Cannavo ◽  
...  

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