Tritium breeding ratio optimization in simple multi-layer blanket with genetic algorithm

被引:1
|
作者
Lim, Soobin [1 ]
Chung, Kyoung-Jae [1 ]
Hwang, Y. S. [1 ]
机构
[1] Seoul Natl Univ, Seoul, South Korea
基金
新加坡国家研究基金会;
关键词
Genetic algorithm; Tritium breeding ratio; Optimization; DESIGN;
D O I
10.1016/j.fusengdes.2024.114365
中图分类号
TL [原子能技术]; O571 [原子核物理学];
学科分类号
0827 ; 082701 ;
摘要
Investigation on tritium production via fast neutrons generated by magnetically confined plasma in a tokamak device is conducted for optimization of tritium breeding ratio (TBR). The blanket is configured as a 1-dimensional multiple layer of materials for the wall, moderation, reflection, and tritium productions, and genetic algorithm is adopted to select the optimal material on each order and location. The configuration selected in the process is evaluated in aspect of tritium production to incoming neutron ratio. To construct the algorithm, the ratio of tritium production is parametrized by neutron energies from 0 to 14 MeV for the materials with Geant4 Monte Carlo simulation toolkit, and the simulated tritium in the algorithm are evaluated for the selection of parent for the next generation. Result configuration from the algorithm is put back to the Geant4 simulation for verification, and TBR is evaluated with blanket designs in other facilities.
引用
收藏
页数:7
相关论文
共 50 条
  • [21] Optimization of the multi-layer die for support shaft
    Huang, Xiaohui
    Zhang, Min
    Wang, Yao
    Zhao, Xinhai
    ADVANCED MANUFACTURING TECHNOLOGY, PTS 1, 2, 2011, 156-157 : 1665 - +
  • [22] Damage diagnosis for complex steel truss bridges using multi-layer genetic algorithm
    Wang F.L.
    Chan T.H.T.
    Thambiratnam D.P.
    Tan A.C.C.
    Journal of Civil Structural Health Monitoring, 2013, 3 (02) : 117 - 127
  • [23] Estimating Permittivity of Snow in a Multi-Layer Model Using Multi-Ray Simulation and a Genetic Algorithm
    Brown, Brandon C.
    Petersen, Brent R.
    PROCEEDINGS OF THE SEVENTH INTERNATIONAL CONFERENCE ON TELECOMMUNICATIONS AND REMOTE SENSING (ICTRS 2018), 2018, : 57 - 64
  • [24] Integrated forward and reverse logistics in cloud manufacturing: an agent-based multi-layer architecture and optimization via genetic algorithm
    Moghaddam, Simin Hamidi
    Akbaripour, Hossein
    Houshmand, Mahmoud
    PRODUCTION ENGINEERING-RESEARCH AND DEVELOPMENT, 2021, 15 (06): : 801 - 819
  • [25] Integrated forward and reverse logistics in cloud manufacturing: an agent-based multi-layer architecture and optimization via genetic algorithm
    Simin Hamidi Moghaddam
    Hossein Akbaripour
    Mahmoud Houshmand
    Production Engineering, 2021, 15 : 801 - 819
  • [26] Hybrid Wolf-Bat Algorithm for Optimization of Connection Weights in Multi-layer Perceptron
    Agrawal, Utkarsh
    Arora, Jatin
    Singh, Rahul
    Gupta, Deepak
    Khanna, Ashish
    Khamparia, Aditya
    ACM TRANSACTIONS ON MULTIMEDIA COMPUTING COMMUNICATIONS AND APPLICATIONS, 2020, 16 (01)
  • [27] A Hybrid Applied Optimization Algorithm for Training Multi-Layer Neural Networks in Data Classification
    Orkcu, H. Hasan
    Dogan, Mustafa Isa
    Orkcu, Mediha
    GAZI UNIVERSITY JOURNAL OF SCIENCE, 2015, 28 (01): : 115 - 132
  • [28] Facade design optimization for daylight with a simple genetic algorithm
    Torres, Santiago L.
    Sakamoto, Yuzo
    BUILDING SIMULATION 2007, VOLS 1-3, PROCEEDINGS, 2007, : 1162 - +
  • [29] Multi-Layer Perceptron Training Optimization Using Nature Inspired Computing
    Al Bataineh, Ali
    Kaur, Devinder
    Jalali, Seyed Mohammad J.
    IEEE ACCESS, 2022, 10 : 36963 - 36977
  • [30] A Method of the Green Product Configuration Design Based on Multi-layer Generalized Operator and Genetic Algorithm
    Liu Dianting
    Jia Feifei
    MECHANICAL ENGINEERING, MATERIALS AND ENERGY III, 2014, 483 : 542 - +