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蒙特卡洛算法在热防护服传热模型建立中的应用

Application of Monte Carlo Algorithm in Heat Transfer Model of Protective Clothing
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摘要 为了准确建立科学的热防护服传热模型,缩短热防护服研发周期,降低研发成本,结合热传导原理、傅里叶定律建立了初步的温度分布模型,并引入含控制参数的阻滞因子对模型进行修正,再利用蒙特卡洛算法求出修正温度分布模型中的相关参数,最终得到拟合效果优良的热防护服传热模型. Accurate establishment scientific heat transfer model for thermal protective clothing can reduce the costs and shorten the cycle of research and development.Therefore,a preliminary temperature distribution model is established based on heat conduction principles,and Fourier's law and is modified by retardation factors with controlling parameters.Monte Carlo algorithm is then applied to obtain the relevant parameters in the temperature distribution model according to the experimental data.Finally,an excellent heat transfer model of protective clothing is obtained.
作者 刘倩岚 雷亿辉 肖育江 董亚玲 LIU Qianlan;LEI Yihui;XIAO Yujiang;DONG Yaling(College of Mathematics and Statistics,Jishou University,Jishou 416000,Hunan China)
出处 《吉首大学学报(自然科学版)》 CAS 2021年第3期52-56,共5页 Journal of Jishou University(Natural Sciences Edition)
基金 湖南省大学生创新创业训练计划项目(3011) 吉首大学校级科研项目(JDX20026)。
关键词 蒙特卡洛算法 热传导 热防护服 传热模型 Monte Carlo algorithm heat conduction protective clothing heat transfer model
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  • 1刘立坡,刘义保.特征X射线激发效率的蒙特卡罗模拟[J].核技术,2007,30(8):672-674. 被引量:3
  • 2Sobol L M. 1967. The distribution of points in a cube and the approxi- mate evaluation of integrals [J]. USSR Comp. Math. and Math. Phys. , 7:86-112.
  • 3Tan K S, Phelim P, Boyle. 2000. Applications of randomized low dis- crepancy sequences to the valuation of complex securities[J], Journal of Economic Dynamics & Control, 24:1747-1782.
  • 4Wang Y, Fang K-T. 1994. Number theoretic methods intatistics [M]. chapman & Hall,New York.
  • 5Wang X-Q, Fang K-T. 2003. The effective dimension and quasi-Monte Carlo integration [J]. Journal of Complexity, 19 (2) : 101-124.
  • 6Zhang T,Liu Y-B,Wu H-X, and Gu J-H. 2009. Monte Carlo simulation of the exposure factor. China Physics B, 18 (06) :2217-2222.
  • 7Aline B, Koen L. 2008. Monte Carlo localization for mobile wireless sensor networks [J]. Ad Hoc Networks, 6 (5) , 718-733.
  • 8Andrea R. 2009. Random number generators in genetic algorithms for un- constrained and constrained optimization[J] , Nonlinear Analysis 71 : e679-e692.
  • 9Belen J, RafaelMiro, JuanM. Campayob, SergioDez, GumersindoVerdu. 2009. Radiotherapy treatment planning based on Monte Carlo tech- niques [J]. Nuclear Instruments and Methods in Physics Research A. 1-6.
  • 10Braaten E, Weller G. 1979. An improved low discrepancy sequence for multidimensional quasi-Monte Carlo integration [J]. Journal of Com- putational Physics,33 : 249-258.

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