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Title: Prediction of U-Mo dispersion nuclear fuels with Al-Si alloy using artificial neural network

Dispersion nuclear fuels, consisting of U-Mo particles dispersed in an Al-Si matrix, are being developed as fuel for research reactors. The equilibrium relationship for a mixture component can be expressed in the phase diagram. It is important to analyze whether a mixture component is in equilibrium phase or another phase. The purpose of this research it is needed to built the model of the phase diagram, so the mixture component is in the stable or melting condition. Artificial neural network (ANN) is a modeling tool for processes involving multivariable non-linear relationships. The objective of the present work is to develop code based on artificial neural network models of system equilibrium relationship of U-Mo in Al-Si matrix. This model can be used for prediction of type of resulting mixture, and whether the point is on the equilibrium phase or in another phase region. The equilibrium model data for prediction and modeling generated from experimentally data. The artificial neural network with resilient backpropagation method was chosen to predict the dispersion of nuclear fuels U-Mo in Al-Si matrix. This developed code was built with some function in MATLAB. For simulations using ANN, the Levenberg-Marquardt method was also used for optimization. The artificial neuralmore » network is able to predict the equilibrium phase or in the phase region. The develop code based on artificial neural network models was built, for analyze equilibrium relationship of U-Mo in Al-Si matrix.« less
Authors:
 [1] ;  [2]
  1. Center for Development of Nuclear Informatics, National Nuclear Energy Agency, PUSPIPTEK, Tangerang (Indonesia)
  2. Center for Nuclear Facilities Engineering, National Nuclear Energy Agency, PUSPIPTEK, Tangerang (Indonesia)
Publication Date:
OSTI Identifier:
22307858
Resource Type:
Journal Article
Resource Relation:
Journal Name: AIP Conference Proceedings; Journal Volume: 1615; Journal Issue: 1; Conference: ICANSE 2013: 4. international conference on advances in nuclear science and engineering, Denpasar, Bali (Indonesia), 16-19 Sep 2013; Other Information: (c) 2014 AIP Publishing LLC; Country of input: International Atomic Energy Agency (IAEA)
Country of Publication:
United States
Language:
English
Subject:
21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS; COMPUTERIZED SIMULATION; DISPERSION NUCLEAR FUELS; MATRIX MATERIALS; MELTING; MIXTURES; MOLYBDENUM; NEURAL NETWORKS; NONLINEAR PROBLEMS; OPTIMIZATION; PHASE DIAGRAMS; RESEARCH REACTORS; SILICON ALLOYS; URANIUM