Improvement of analytical method on radiative heat transfer in nongray media by Monte Carlo method
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An accelerated method is developed for radiative heat-transfer analysis in nongray media by the Monte Carlo method. Instead of deciding all the parameters of each energy particle used in the Monte Carlo procedure by a stochastic method, the wave number assigned to each energy particle is determined by a deterministic method in the present study. This change in the Monte Carlo algorithm reduces the computation time to one-ninth of the original time. To reduce the amount of iteration required to converge the temperature profile in a nongray media layer, an acceleration factor is incorporated to determine the new values of temperature in each iterational loop. The value of the acceleration factor is found to be related to the optical thickness of each media element. By using an appropriate acceleration factor, the amount of iteration is reduced to one-fourth of the original. Moreover, the total computation time becomes 1/36 of the original by the two improvements.Keywords:
Thermal Radiation
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The present work assesses different Monte Carlo methods in radiative heat transfer problems, in terms of accuracy and computational cost. Achieving a high scalability on numerous CPUs with the conventional forward Monte Carlo method is not straightforward. The Emission-based Reciprocity Monte Carlo Method (ERM) allows to treat each mesh point independently from the others with a local monitoring of the statistical error, becoming a perfect candidate for high-scalability. ERM is however penalized by a slow statistical convergence in cold absorbing regions. This limitation has been overcome by an Optimized ERM (OERM) using a frequency distribution function based on the emission distribution at the maximum temperature of the system. Another approach to enhance the convergence is the use of low-discrepancy sampling. The obtained Quasi-Monte Carlo method is combined with OERM. The efficiency of the considered Monte-Carlo methods are compared.
Quasi-Monte Carlo method
Monte Carlo integration
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Smoothing
Monte Carlo algorithm
Quasi-Monte Carlo method
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Kernel (algebra)
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The event value Wg ([rbar], Ω) has been derived in a form which can be obtained directly from existing adjoint Monte Carlo computer codes. It is demonstrated that the event value and the point value functions obtained from the adjoint Monte Carlo calculation can be used as the path-length biasing and the angular biasing in the forward Monte Carlo calculation, respectively. The iterative forward-adjoint Monte Carlo method using the source biasings is employed to reduce the standard deviation in the shielding problem. In addition, the effectiveness of the source biasing schemes is investigated in the same problem. The results indicate a significant reduction in the standard deviation and a substantial improvement in the efficiency of the Monte Carlo shielding calculations.
Variance reduction
Quasi-Monte Carlo method
Monte Carlo integration
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Reciprocity
Benchmark (surveying)
Radiant energy
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A new formulation of energy-space dependent propagation of errors has been derived for the Monte Carlo-Monte Carlo coupling technique which is applied to analysis of radiation streaming through a long path. In this formula, it is considered that the source uncertainty due to the statistical error of the preceding Monte Carlo calculation is handed down to a particle as an uncertainty of the particle weight. In the succeeding Monte Carlo calculation, the propagated weight error is scored together with the particle weight by flux estimators. The method has been implemented in the MORSE-ALB code system. As a sample problem, calculation of reaction rates in the main pump room of the primary coolant system of JOYO is performed with the Sn-AMC-AMC coupling technique. As a result, the present method turned out to be significant in estimating the Monte Carlo statistical error of the final value taking into consideration of the energy-space dependence of error propagation.
Propagation of uncertainty
Monte Carlo integration
Quasi-Monte Carlo method
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Thermal Radiation
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In this paper,the problem of mass concrete steady thermal field was solved by using Monte Carlo method with irregular grid random walk.By using this method,temperature value on any single node could be solved,without forming the total stiffness matrix,and the precisio could be easily controlled according to the times of Random Walks.The appropriate random walks model was offered and the method could be tested and verified with living example.The final calculation demonstrated that the result obtained by Monte Carlo method agreed well with that obtained by the other ones.
Monte Carlo integration
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The Monte Carlo method is combined with the thermal network method to solve the temperature field of a spacecraft. The radiative transfer coefficients for infrared radiation among the thermal network nodes and for solar radiation among the surface elements are calculated by the Monte Carlo method to eliminate the reasonless assumptions for the calculation of view factors. A software for calculating the radiative transfer coefficients and solving thermal network equations is developed to analyze the steady state temperature field of a satellite, by which the design scheme will be determined. The incident heat flux data needed for the calculation is presented by the NEVADA code. The investigation shows that the Monte Carlo method in combination with the thermal network method is flexible to the complicated structure of a system and the radiative characteristics of element surfaces, but the calculation is relatively heavy.
Thermal Radiation
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