A Stochastic Convergence Analysis of Random Number Generators as applied to Error Propagation using Monte Carlo method and Unscented Transformation Technique

被引：0
|
作者：
Ram, Sangeetha Prasanna [1 ]
Nair, Jayalekshmi [2 ]
Ganesan, S. [3 ]
机构：
[1] VES Inst Technol, Instrumentat Dept, Bombay, Maharashtra, India
[2] VES Inst Technol, Bombay, Maharashtra, India
[3] BARC, Reactor Design & Dev Grp, Reactor Phys Design Div, Bombay, Maharashtra, India
来源：
2017 IEEE INTERNATIONAL CONFERENCE ON SIGNAL PROCESSING, INFORMATICS, COMMUNICATION AND ENERGY SYSTEMS (SPICES) | 2017年
关键词：
Monte Carlo method; Unscented transformation; Stochastic convergence; Random number generators; Nuclear data;
D O I：
暂无
中图分类号：
TM [电工技术]; TN [电子技术、通信技术];
学科分类号：
0808 ; 0809 ;
摘要：
This paper compares the stochastic convergence of the Uniform Random number generators of two simulation software namely Matlab and Python and establishes the significance in choosing the right random number generator for error propagation studies. It further discusses about the application of Gaussian type of these random number generators to nonlinear cases of Error propagation using the Monte Carlo method and unscented transformation technique by means of a nonlinear transformation of one dimensional random variable of nuclear data.
引用
收藏
页数：7
相关论文
共 38 条
  • [31] Mathematical modeling applied to the uncertainty analysis of a tank prover calibration: Understanding the influence of calibration conditions on the GUM validation using the Monte Carlo method
    Castro, H. F. F.
    FLOW MEASUREMENT AND INSTRUMENTATION, 2024, 96
  • [32] ANALYSIS OF MOLECULAR-NUMBER DENSITY UNDER FREE MOLECULAR-FLOW USING THE TIME-TRANSIENT MONTE-CARLO METHOD
    SESE, M
    KAWAMURA, Y
    JOURNAL OF CHEMICAL ENGINEERING OF JAPAN, 1989, 22 (05) : 562 - 564
  • [33] A Stability Analysis of the Direct Interpolation Boundary Element Method applied to acoustic wave propagation problems using the Modal Superposition Technique
    dos Santos, Aquila de Jesus
    Loeffler, Carlos Friedrich
    Lara, Luciano de Oliveira Castro
    LATIN AMERICAN JOURNAL OF SOLIDS AND STRUCTURES, 2024, 21 (01)
  • [34] Multigroup cross-sections generated using Monte-Carlo method with flux-moment homogenization technique for fast reactor analysis
    Wu, Yiwei
    Song, Qufei
    Feng, Kuaiyuan
    Vidal, Jean-Francois
    Gu, Hanyang
    Guo, Hui
    NUCLEAR ENGINEERING AND TECHNOLOGY, 2023, 55 (07) : 2474 - 2482
  • [35] Non-Deterministic Structural Response and Reliability Analysis Using a Hybrid Perturbation-Based Stochastic Finite Element and Quasi-Monte Carlo Method
    Wang, C.
    Gao, W.
    Yang, C. W.
    Song, C. M.
    CMC-COMPUTERS MATERIALS & CONTINUA, 2011, 25 (01): : 19 - 46
  • [36] Stochastic Optimal Selection and Analysis of Allowable Photovoltaic Penetration Level for Grid-Connected Systems Using a Hybrid NSGAII-MOPSO and Monte Carlo Method
    Abubakar, Ali
    Borkor, Reindorf Nartey
    Amoako-Yirenkyi, Peter
    INTERNATIONAL JOURNAL OF PHOTOENERGY, 2023, 2023
  • [37] Neutron-Induced Soft Error Analysis in MOSFETs from a 65nm to a 25 nm Design Rule using Multi-Scale Monte Carlo Simulation Method
    Abe, Shin-ichiro
    Watanabe, Yukinobu
    Shibano, Nozomi
    Sano, Nobuyuki
    Furuta, Hiroshi
    Tsutsui, Masafumi
    Uemura, Taiki
    Arakawa, Takahiko
    2012 IEEE INTERNATIONAL RELIABILITY PHYSICS SYMPOSIUM (IRPS), 2012,
  • [38] Erratum to: Using the Monte Carlo Method for Fast Simulation of the Number of “Good” Permutations on the SCIT-4 Multiprocessor Computer Complex (Cybernetics and Systems Analysis, 52,1, (52-57), 2016)
    Kuznetsov, N. Yu.
    Cybernetics and Systems Analysis, 2016, 52 (02)
1234