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Evaluation of a new neutron energy spectrum unfolding code based on an Adaptive Neuro-Fuzzy Inference System (ANFIS)
- Source :
- Journal of Radiation Research
- Publication Year :
- 2018
- Publisher :
- Oxford University Press, 2018.
-
Abstract
- The purpose of the present study was to reconstruct the energy spectrum of a poly-energetic neutron source using an algorithm developed based on an Adaptive Neuro-Fuzzy Inference System (ANFIS). ANFIS is a kind of artificial neural network based on the Takagi–Sugeno fuzzy inference system. The ANFIS algorithm uses the advantages of both fuzzy inference systems and artificial neural networks to improve the effectiveness of algorithms in various applications such as modeling, control and classification. The neutron pulse height distributions used as input data in the training procedure for the ANFIS algorithm were obtained from the simulations performed by MCNPX-ESUT computational code (MCNPX-Energy engineering of Sharif University of Technology). Taking into account the normalization condition of each energy spectrum, 4300 neutron energy spectra were generated randomly. (The value in each bin was generated randomly, and finally a normalization of each generated energy spectrum was performed). The randomly generated neutron energy spectra were considered as output data of the developed ANFIS computational code in the training step. To calculate the neutron energy spectrum using conventional methods, an inverse problem with an approximately singular response matrix (with the determinant of the matrix close to zero) should be solved. The solution of the inverse problem using the conventional methods unfold neutron energy spectrum with low accuracy. Application of the iterative algorithms in the solution of such a problem, or utilizing the intelligent algorithms (in which there is no need to solve the problem), is usually preferred for unfolding of the energy spectrum. Therefore, the main reason for development of intelligent algorithms like ANFIS for unfolding of neutron energy spectra is to avoid solving the inverse problem. In the present study, the unfolded neutron energy spectra of 252Cf and 241Am-9Be neutron sources using the developed computational code were found to have excellent agreement with the reference data. Also, the unfolded energy spectra of the neutron sources as obtained using ANFIS were more accurate than the results reported from calculations performed using artificial neural networks in previously published papers.
- Subjects :
- Normalization (statistics)
Light
Computer science
Health, Toxicology and Mutagenesis
02 engineering and technology
01 natural sciences
Bin
Spectral line
Fuzzy Logic
0103 physical sciences
0202 electrical engineering, electronic engineering, information engineering
Regular Paper
Radiology, Nuclear Medicine and imaging
Computer Simulation
ANFIS
unfolding
neutron pulse height distribution
Neutrons
Adaptive neuro fuzzy inference system
Radiation
Americium
Artificial neural network
010308 nuclear & particles physics
Inverse problem
Neutron temperature
252Cf
Neutron source
020201 artificial intelligence & image processing
Neural Networks, Computer
Algorithm
neutron energy spectrum
241Am-9Be
Algorithms
Subjects
Details
- Language :
- English
- ISSN :
- 13499157 and 04493060
- Volume :
- 59
- Issue :
- 4
- Database :
- OpenAIRE
- Journal :
- Journal of Radiation Research
- Accession number :
- edsair.doi.dedup.....7851eba3cd6a7f2510ac9dec9f51d143