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Journal articles on the topic 'Radiative transfer Monte Carlo method'

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1

Iwabuchi, Hironobu. "Efficient Monte Carlo Methods for Radiative Transfer Modeling." Journal of the Atmospheric Sciences 63, no. 9 (2006): 2324–39. http://dx.doi.org/10.1175/jas3755.1.

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Abstract Demands for Monte Carlo radiative transfer modeling have grown with the increase in computational power in recent decades. This method provides realistic simulations of radiation processes for various types of application, including radiation budgets in cloudy conditions and remote measurements of clouds, aerosols, and gases. Despite many advantages, such as explicit treatment of three-dimensional radiative transfer, issues of numerical efficiency can make the method intractable, especially in radiance calculations. The commonly used local estimation method requires computationally in
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2

Zhang, Jianing. "A guided Monte Carlo radiative transfer method using mixture importance sampling." Astronomy & Astrophysics 628 (August 2019): A105. http://dx.doi.org/10.1051/0004-6361/201935751.

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In order to investigate the source of uncertainties for the Monte Carlo radiative transfer method, a path space formulation is proposed which expresses the integral form of the radiative transfer equation. It has been determined that some of the uncertainties depend on the sampling of photon propagation directions. To reduce this kind of uncertainty, we propose a guided Monte Carlo (GMC) method based on a direction mixture importance sampling strategy for simulating radiative transfer in a scattering medium. We validated the GMC method by implementing it in a backward Monte Carlo radiative tra
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3

Howell, J. R. "The Monte Carlo Method in Radiative Heat Transfer." Journal of Heat Transfer 120, no. 3 (1998): 547–60. http://dx.doi.org/10.1115/1.2824310.

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The use of the Monte Carlo method in radiative heat transfer is reviewed. The review covers surface-surface, enclosure, and participating media problems. Discussion is included of research on the fundamentals of the method and on applications to surface-surface interchange in enclosures, exchange between surfaces with roughness characteristics, determination of configuration factors, inverse design, transfer through packed beds and fiber layers, participating media, scattering, hybrid methods, spectrally dependent problems including media with line structure, effects of using parallel algorith
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4

Baes, Maarten, Christian Peest, Peter Camps, and Ralf Siebenmorgen. "Optical depth in polarised Monte Carlo radiative transfer." Astronomy & Astrophysics 630 (September 23, 2019): A61. http://dx.doi.org/10.1051/0004-6361/201833796.

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Context. The Monte Carlo method is the most widely used method to solve radiative transfer problems in astronomy, especially in a fully general 3D geometry. A crucial concept in any Monte Carlo radiative transfer code is the random generation of the next interaction location. In polarised Monte Carlo radiative transfer with aligned non-spherical grains, the nature of dichroism complicates the concept of optical depth. Aims. We investigate, in detail, the relation between optical depth and the optical properties and density of the attenuating medium in polarised Monte Carlo radiative transfer c
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5

Modest, Michael F. "Backward Monte Carlo Simulations in Radiative Heat Transfer." Journal of Heat Transfer 125, no. 1 (2003): 57–62. http://dx.doi.org/10.1115/1.1518491.

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Standard Monte Carlo methods trace photon bundles in a forward direction, and may become extremely inefficient when radiation onto a small spot and/or onto a small direction cone is desired. Backward tracing of photon bundles is known to alleviate this problem if the source of radiation is large, but may also fail if the radiation source is collimated and/or very small. In this paper various implementations of the backward Monte Carlo method are discussed, allowing efficient Monte Carlo simulations for problems with arbitrary radiation sources, including small collimated beams, point sources,
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6

Gentile, N. A. "Implicit Monte Carlo Diffusion—An Acceleration Method for Monte Carlo Time-Dependent Radiative Transfer Simulations." Journal of Computational Physics 172, no. 2 (2001): 543–71. http://dx.doi.org/10.1006/jcph.2001.6836.

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7

Clouët, J. F., and G. Samba. "A Hybrid Symbolic Monte-Carlo method for radiative transfer equations." Journal of Computational Physics 188, no. 1 (2003): 139–56. http://dx.doi.org/10.1016/s0021-9991(03)00158-x.

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8

Chen, Y., and K. N. Liou. "A Monte Carlo method for 3D thermal infrared radiative transfer." Journal of Quantitative Spectroscopy and Radiative Transfer 101, no. 1 (2006): 166–78. http://dx.doi.org/10.1016/j.jqsrt.2005.10.002.

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9

Yong, Huang, Shi Guo-Dong, and Zhu Ke-Yong. "BACKWARD AND FORWARD MONTE CARLO METHOD IN POLARIZED RADIATIVE TRANSFER." Astrophysical Journal 820, no. 1 (2016): 9. http://dx.doi.org/10.3847/0004-637x/820/1/9.

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10

Shi, Yi, Shuanggui Li, Heng Yong, and Peng Song. "An Essentially Implicit Monte Carlo Method for Radiative Transfer Equations." Journal of Computational and Theoretical Transport 48, no. 5 (2019): 180–99. http://dx.doi.org/10.1080/23324309.2019.1678484.

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11

Larsen, Edward W., and Bertrand Mercer. "Analysis of a Monte Carlo method for nonlinear radiative transfer." Journal of Computational Physics 71, no. 1 (1987): 50–64. http://dx.doi.org/10.1016/0021-9991(87)90019-2.

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12

Kersch, A., W. Morokoff, and A. Schuster. "Radiative heat transfer with quasi-monte carlo methods." Transport Theory and Statistical Physics 23, no. 7 (1994): 1001–21. http://dx.doi.org/10.1080/00411459408203537.

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13

Juvela, M. "Efficient Monte Carlo methods for continuum radiative transfer." Astronomy & Astrophysics 440, no. 2 (2005): 531–46. http://dx.doi.org/10.1051/0004-6361:20042615.

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14

Krieger, A., and S. Wolf. "Unbiased Monte Carlo continuum radiative transfer in optically thick regions." Astronomy & Astrophysics 635 (March 2020): A148. http://dx.doi.org/10.1051/0004-6361/201937355.

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Radiative transfer describes the propagation of electromagnetic radiation through an interacting medium. This process is often simulated by the use of the Monte Carlo method, which involves the probabilistic determination and tracking of simulated photon packages. In the regime of high optical depths, this approach encounters difficulties since a proper representation of the various physical processes can only be achieved by considering high numbers of simulated photon packages. As a consequence, the demand for computation time rises accordingly and thus practically puts a limit on the optical
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15

Ai, Qing, Hua Liu, Xinlin Xia, Chuang Sun, and Ming Xie. "Radiative Heat Transfer in Participating Medium and Dynamic Region Monte Carlo Method by Region Adaption." Mathematical Problems in Engineering 2015 (2015): 1–12. http://dx.doi.org/10.1155/2015/304708.

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A dynamic region Monte Carlo method (DRMC) is proposed to simulate radiative heat transfer in participating medium. The basic principle and solution procedure of this method is described; radiative heat transfer in a two-dimensional rectangular region of absorbing, emitting, and/or scattering gray medium is analyzed. A comparison between DRMC and the traditional Monte Carlo method (TMC) is investigated by analyzing the simulated temperature distribution, the computing time, and the number of the sampling bundles. The investigation results show that, to compare with TMC, the DRMC can obviously
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16

Han, Ya Fen, Xin Lin Xia, and Hai Dong Liu. "A Modified Monte Carlo Method for Phonon Radiative Transfer in Nanoscale Materials." Advanced Materials Research 652-654 (January 2013): 188–91. http://dx.doi.org/10.4028/www.scientific.net/amr.652-654.188.

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A Modified Monte-Carlo Method (MMCM) in which phonon bundles take non-energy is developed to model the steady state phonon radiative transfer in nanoscale materials. Heat transfer in silicon thin films is analyzed to examine the validity of the developed method. The temperature distributions and cross-plane thermal conductivity are determined by using the developed method for the silicon thin films and compared with the results in reference. The results indicate that the developed method has a good accuracy in solving the phonon radiative transfer in nanoscale materials. In addition, numerical
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17

Zhao, J. M., J. Y. Tan, and L. H. Liu. "Monte Carlo method for polarized radiative transfer in gradient-index media." Journal of Quantitative Spectroscopy and Radiative Transfer 152 (February 2015): 114–26. http://dx.doi.org/10.1016/j.jqsrt.2014.11.005.

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18

Wolf, S., and Th Henning. "Accelerated self-consistent radiative transfer based on the Monte Carlo method." Computer Physics Communications 132, no. 1-2 (2000): 166–88. http://dx.doi.org/10.1016/s0010-4655(00)00144-2.

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19

Lu, Xiaodong, and Pei-feng Hsu. "Reverse Monte Carlo Method for Transient Radiative Transfer in Participating Media." Journal of Heat Transfer 126, no. 4 (2004): 621. http://dx.doi.org/10.1115/1.1773587.

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20

Densmore, Jeffery D., Todd J. Urbatsch, Thomas M. Evans, and Michael W. Buksas. "A hybrid transport-diffusion method for Monte Carlo radiative-transfer simulations." Journal of Computational Physics 222, no. 2 (2007): 485–503. http://dx.doi.org/10.1016/j.jcp.2006.07.031.

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21

Gomez, Christophe, and Olivier Pinaud. "Monte Carlo Methods for Radiative Transfer with Singular Kernels." SIAM Journal on Scientific Computing 40, no. 3 (2018): A1714—A1741. http://dx.doi.org/10.1137/17m1134755.

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22

Ergon, M., C. Fransson, A. Jerkstrand, C. Kozma, M. Kromer, and K. Spricer. "Monte-Carlo methods for NLTE spectral synthesis of supernovae." Astronomy & Astrophysics 620 (December 2018): A156. http://dx.doi.org/10.1051/0004-6361/201833043.

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We present JEKYLL, a new code for modelling of supernova (SN) spectra and lightcurves based on Monte-Carlo (MC) techniques for the radiative transfer. The code assumes spherical symmetry, homologous expansion and steady state for the matter, but is otherwise capable of solving the time-dependent radiative transfer problem in non-local-thermodynamic-equilibrium (NLTE). The method used was introduced in a series of papers by Lucy, but the full time-dependent NLTE capabilities of it have never been tested. Here, we have extended the method to include non-thermal excitation and ionization as well
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23

Šurlan, Brankica, and Jiří Kubát. "Line profiles of OB star winds using a Monte Carlo method." Proceedings of the International Astronomical Union 6, S272 (2010): 214–15. http://dx.doi.org/10.1017/s1743921311010404.

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AbstractThe solution of the radiative transfer in an expanding atmospheres using the Monte Carlo method is presented. We applied our method to winds of several OB stars. In our calculation, the velocity and density structure is assumed to be given. Selected line profiles are shown.
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24

Kobiyama, M. "Reduction of Computing Time and Improvement of Convergence Stability of the Monte Carlo Method Applied to Radiative Heat Transfer With Variable Properties." Journal of Heat Transfer 111, no. 1 (1989): 135–40. http://dx.doi.org/10.1115/1.3250634.

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A modified Monte Carlo method is suggested to reduce the computing time and improve the convergence stability of iterative calculations without losing other excellent features of the conventional Monte Carlo method. In this method, two kinds of radiative bundle are used: energy correcting bundles and property correcting bundles. The energy correcting bundles are used for correcting the radiative energy difference between two successive iterative cycles, and the property correcting bundles are used for correcting the radiative properties. The number of radiative energy bundles emitted from each
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25

Li, Guo-Jun, Jia-Qi Zhong, and Xiao-Dong Wang. "An improved Monte Carlo method for radiative heat transfer in participating media." Journal of Quantitative Spectroscopy and Radiative Transfer 251 (August 2020): 107081. http://dx.doi.org/10.1016/j.jqsrt.2020.107081.

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26

Ishii, Ayako, Naofumi Ohnishi, Hiroki Nagakura, Hirotaka Ito, and Shoichi Yamada. "Parallel computing of radiative transfer in relativistic jets using Monte Carlo method." High Energy Density Physics 9, no. 2 (2013): 280–87. http://dx.doi.org/10.1016/j.hedp.2013.01.002.

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27

Iwabuchi, Hironobu, and Rintaro Okamura. "Multispectral Monte Carlo radiative transfer simulation by the maximum cross-section method." Journal of Quantitative Spectroscopy and Radiative Transfer 193 (May 2017): 40–46. http://dx.doi.org/10.1016/j.jqsrt.2017.01.025.

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28

Qi, Peiyao, Xing Li, Xin Li, Shouxu Qiao, and Sichao Tan. "THE MONTE CARLO METHOD IN RADIATIVE HEAT TRANSFER OF HEAT REJECTION SUBSYSTEM." Proceedings of the International Conference on Nuclear Engineering (ICONE) 2019.27 (2019): 1116. http://dx.doi.org/10.1299/jsmeicone.2019.27.1116.

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29

Nisipeanu, Eugen, and Peter D. Jones. "Monte Carlo Simulation of Radiative Heat Transfer in Coarse Fibrous Media." Journal of Heat Transfer 125, no. 4 (2003): 748–52. http://dx.doi.org/10.1115/1.1571092.

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Direct Geometric Monte Carlo modeling of a fibrous medium is undertaken. The medium is represented as a monodisperse array, with known solidity, of randomly oriented cylinders of known index of refraction. This technique has the advantage that further radiative properties of the medium (absorption coefficient, scattering albedo, scattering phase function) are not required, and the drawback that its’ Snell- and Fresnel-generated dynamics suggest a limitation to large, smooth fibers. It is found that radiative heat flux results are highly dependent on bias in the polar orientation angle (relativ
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30

Wong, Basil T., and M. Pınar Mengüç. "Monte Carlo methods in radiative transfer and electron-beam processing." Journal of Quantitative Spectroscopy and Radiative Transfer 84, no. 4 (2004): 437–50. http://dx.doi.org/10.1016/s0022-4073(03)00261-9.

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31

Walters, Donald V., and Richard O. Buckius. "MONTE CARLO METHODS FOR RADIATIVE HEAT TRANSFER IN SCATTERING MEDIA." Annual Review of Heat Transfer 5, no. 5 (1994): 131–76. http://dx.doi.org/10.1615/annualrevheattransfer.v5.50.

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32

Vujičić, M. R., N. P. Lavery, and S. G. R. Brown. "Numerical Sensitivity and View Factor Calculation Using the Monte Carlo Method." Proceedings of the Institution of Mechanical Engineers, Part C: Journal of Mechanical Engineering Science 220, no. 5 (2006): 697–702. http://dx.doi.org/10.1243/09544062jmes139.

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In radiative heat transfer simulations, the geometrical view (configuration, form) factor plays a crucial role. Several different methods (deterministic and non-deterministic) such as integration, the Monte Carlo method, and the Hemi-Cube method have been introduced to calculate view factors in recent years. In this article, the Monte Carlo method combined with the finite-element (FE) technique is investigated. Results describing the relationships among different discretization schemes, number of rays used for the view factor calculation, CPU time, accuracy, and two origins of emanating rays a
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33

Palluotto, Lorella, Nicolas Dumont, Pedro Rodrigues, Olivier Gicquel, and Ronan Vicquelin. "Assessment of randomized Quasi-Monte Carlo method efficiency in radiative heat transfer simulations." Journal of Quantitative Spectroscopy and Radiative Transfer 236 (October 2019): 106570. http://dx.doi.org/10.1016/j.jqsrt.2019.07.013.

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34

Taniguchi, Hiroshi, Wen-Jei Yang, Kazuhiko Kudo, Hiroshi Hayasaka, Takeru Fukuchi, and Ichiro Nakamachi. "Monte Carlo method for radiative heat transfer analysis of general gas-particle enclosures." International Journal for Numerical Methods in Engineering 25, no. 2 (1988): 581–92. http://dx.doi.org/10.1002/nme.1620250219.

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35

Densmore, Jeffery D., Kelly G. Thompson, and Todd J. Urbatsch. "A hybrid transport-diffusion Monte Carlo method for frequency-dependent radiative-transfer simulations." Journal of Computational Physics 231, no. 20 (2012): 6924–34. http://dx.doi.org/10.1016/j.jcp.2012.06.020.

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36

Wu, S. H., and C. Y. Wu. "Integral Equation Solutions for Transient Radiative Transfer in Nonhomogeneous Anisotropically Scattering Media." Journal of Heat Transfer 122, no. 4 (2000): 818–23. http://dx.doi.org/10.1115/1.1315596.

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The integral equation formulation for transient radiative transfer in two-dimensional cylindrical nonhomogeneous absorbing and linearly anisotropically scattering media with collimated pulse irradiation is presented. The integral equations are solved by the quadrature method. The results by the present method agree quite well with those obtained by the Monte Carlo method. The effects of spatially variable properties on transient radiative transfer are investigated for various optical sizes and extinction coefficient distributions. The blocking effect on transient two-dimensional radiative tran
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37

Kaminski, Deborah A. "Radiative Transfer From a Gray, Absorbing-Emitting, Isothermal Medium in a Conical Enclosure." Journal of Solar Energy Engineering 111, no. 4 (1989): 324–29. http://dx.doi.org/10.1115/1.3268330.

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Radiative heat transfer from an isothermal participating medium in a truncated, conical enclosure is investigated numerically. Two methods of solution are employed: the Monte-Carlo technique and the P1 differential approximation. The solution to the P1 representation is obtained from a control-volume-based discretization of the governing equation. The medium is assumed to be gray and nonscattering, and the absorption coefficient and temperature are uniform throughout the medium. Overall and local heat flux rates at the walls predicted by the P1 method are compared to the quasi-exact results of
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38

Kudo, Kazuhiko, Hiroshi Taniguchi, Akiyoshi Kuroda, Masakazu Obata, Maromu Otaka, and Hiroshi Yokota. "Improvement of Analytical Method on Radiative Heat Transfer in Nongray Media by Monte Carlo Method." Transactions of the Japan Society of Mechanical Engineers Series B 59, no. 560 (1993): 1265–70. http://dx.doi.org/10.1299/kikaib.59.1265.

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39

Mayer, B., S. W. Hoch, and C. D. Whiteman. "Validating the MYSTIC three-dimensional radiative transfer model with observations from the complex topography of Arizona's Meteor Crater." Atmospheric Chemistry and Physics Discussions 10, no. 5 (2010): 13373–405. http://dx.doi.org/10.5194/acpd-10-13373-2010.

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Abstract. The MYSTIC three-dimensional Monte-Carlo radiative transfer model has been extended to simulate solar and thermal irradiances with a rigorous consideration of topography. Forward as well as backward Monte Carlo simulations are possible for arbitrarily oriented surfaces and we demonstrate that the backward Monte Carlo technique is superior to the forward method for applications involving topography, by greatly reducing the computational demands. MYSTIC is used to simulate the short- and longwave radiation fields during a clear day and night in and around Arizona's Meteor Crater, a bow
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40

Mayer, B., S. W. Hoch, and C. D. Whiteman. "Validating the MYSTIC three-dimensional radiative transfer model with observations from the complex topography of Arizona's Meteor Crater." Atmospheric Chemistry and Physics 10, no. 18 (2010): 8685–96. http://dx.doi.org/10.5194/acp-10-8685-2010.

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Abstract. The MYSTIC three-dimensional Monte-Carlo radiative transfer model has been extended to simulate solar and thermal irradiances with a rigorous consideration of topography. Forward as well as backward Monte Carlo simulations are possible for arbitrarily oriented surfaces and we demonstrate that the backward Monte Carlo technique is superior to the forward method for applications involving topography, by greatly reducing the computational demands. MYSTIC is used to simulate the short- and longwave radiation fields during a clear day and night in and around Arizona's Meteor Crater, a bow
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41

Liu, J., and S. N. Tiwari. "Investigation of Radiative Transfer in Nongray Gases Using a Narrow Band Model and Monte Carlo Simulation." Journal of Heat Transfer 116, no. 1 (1994): 160–66. http://dx.doi.org/10.1115/1.2910850.

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The Monte Carlo method (MCM) is applied to analyze radiative heat transfer in nongray gases. The nongray model employed is based on the statistical narrow band model with an exponential-tailed inverse intensity distribution. The amount and transfer of the emitted radiative energy in a finite volume element within a medium are considered in an exact manner. The spectral correlation between transmittances of two different segments of the same path in a medium makes the statistical relationship different from the conventional relationship that only provides the noncorrelated results for nongray a
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42

Yu, Qizheng, Linhua Liu, Yingchun Pan, Donghui Zhang, Jiangang Ji, and Heping Tan. "Monte Carlo method for simulating the radiative characteristics of an anisotropic medium." Heat Transfer?Asian Research 28, no. 3 (1999): 201–10. http://dx.doi.org/10.1002/(sici)1523-1496(1999)28:3<201::aid-htj5>3.0.co;2-r.

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43

Soucasse, Laurent, Philippe Rivière, and Anouar Soufiani. "Monte Carlo methods for radiative transfer in quasi-isothermal participating media." Journal of Quantitative Spectroscopy and Radiative Transfer 128 (October 2013): 34–42. http://dx.doi.org/10.1016/j.jqsrt.2012.07.008.

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44

Nashine, Prerana, and Ashok Kumar Satapathy. "Radiation Adhered with Conduction Heat Transfer Adopting Finite Volume Method." Applied Mechanics and Materials 592-594 (July 2014): 1746–50. http://dx.doi.org/10.4028/www.scientific.net/amm.592-594.1746.

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This article considers a radiative transport problem coupled with conduction in the one dimensional slab in the presence of participating media. The finite volume method of computation is presented to discretize the radiative transfer equation over the control volume and by using the error function, conduction term is being computed. In the mathematical derivation the RTE is integrated with respect to control volume and control angles with the freedom in choosing number of angular nodes. The results reveals that the proposed method is a promising alternative to the well-established practices l
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45

Juvela, Mika. "SOC program for dust continuum radiative transfer." Astronomy & Astrophysics 622 (January 31, 2019): A79. http://dx.doi.org/10.1051/0004-6361/201834354.

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Context. Thermal dust emission carries information on physical conditions and dust properties in many astronomical sources. Because observations represent a sum of emission along the line of sight, their interpretation often requires radiative transfer (RT) modelling. Aims. We describe a new RT program, SOC, for computations of dust emission, and examine its performance in simulations of interstellar clouds with external and internal heating. Methods. SOC implements the Monte Carlo RT method as a parallel program for shared-memory computers. It can be used to study dust extinction, scattering,
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46

Nersesian, Angelos, Sébastien Viaene, Ilse De Looze, et al. "High-resolution, 3D radiative transfer modelling." Astronomy & Astrophysics 643 (November 2020): A90. http://dx.doi.org/10.1051/0004-6361/202038939.

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Context. Investigating the dust heating mechanisms in galaxies provides a deeper understanding of how the internal energy balance drives their evolution. Over the last decade radiative transfer simulations based on the Monte Carlo method have emphasised the role of the various stellar populations heating the diffuse dust. Beyond the expected heating through ongoing star formation, older stellar populations (≥8 Gyr) and even active galactic nuclei can both contribute energy to the infrared emission of diffuse dust. Aims. In this particular study we examine how the radiation of an external heati
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47

YAN, Zhao-da. "SIMULATION OF IN-CYLINDER RADIATIVE HEAT TRANSFER OF DIESEL ENGINE WITH MONTE-CARLO METHOD." Journal of Zhejiang University SCIENCE 1, no. 3 (2000): 306. http://dx.doi.org/10.1631/jzus.2000.0306.

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48

Shi, Yi, Heng Yong, Chuanlei Zhai, Jin Qi, and Peng Song. "A Functional Expansion Tally Method for Gray Radiative Transfer Equations in Implicit Monte Carlo." Journal of Computational and Theoretical Transport 47, no. 7 (2018): 581–98. http://dx.doi.org/10.1080/23324309.2018.1505640.

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49

Zhang, Jin, Olivier Gicquel, Denis Veynante, and Jean Taine. "Monte Carlo method of radiative transfer applied to a turbulent flame modeling with LES." Comptes Rendus Mécanique 337, no. 6-7 (2009): 539–49. http://dx.doi.org/10.1016/j.crme.2009.06.024.

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50

Wu, Y., M. F. Modest, and D. C. Haworth. "A high-order photon Monte Carlo method for radiative transfer in direct numerical simulation." Journal of Computational Physics 223, no. 2 (2007): 898–922. http://dx.doi.org/10.1016/j.jcp.2006.10.014.

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