Inversion of Optical Properties of Porous Membrane Materials Based on Monte Carlo Method
DOI:
https://doi.org/10.54097/yg7jwe57Keywords:
Monte Carlo method, genetic algorithm, cellulose acetate porous membrane.Abstract
Absorption and scattering are important parameters that reflect the radiation performance of porous materials but cannot be directly measured. By solving the radiation transfer equation by Monte Carlo method, the relationship between the material's absorptivity, scattering, reflectivity and transmittance can be established. Then, when the reflectivity and transmittance have been measured, the absorptivity and scattering can be obtained by genetic algorithm inversion. The absorptivity and scattering of cellulose acetate porous membrane samples were obtained by the above method, which proved the feasibility of the method.
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[1] Raman A P, Anoma M A, Zhu L, et al. Passive radiative cooling below ambient air temperature under direct sunlight[J]. Nature, 2014, 515(7528): 540-544.
[2] Hernández-Pérez I, Álvarez G, Xamán J, et al. Thermal performance of reflective materials applied to exterior building components—A review[J]. Energy and Buildings, 2014, 80: 81-105.
[3] Hunt A J. Light scattering for aerogel characterization[J]. Journal of non-crystalline solids, 1998, 225: 303-306.
[4] Zhao L, Yang S, Bhatia B, et al. Modeling silica aerogel optical performance by determining its radiative properties[J]. AIP Advances, 2016, 6(2).
[5] Eldridge J I, Spuckler C M, Markham J R. Determination of scattering and absorption coefficients for plasma‐sprayed yttria‐stabilized zirconia thermal barrier coatings at elevated temperatures[J]. Journal of the American Ceramic Society, 2009, 92(10): 2276-2285.
[6] P. Mudgett and L. Richards, Multiple scattering calculations for technology, Appliedoptics, vol. 10, no. 7, pp. 1485–1502, 1971.
[7] Eymard R, Gallouët T, Herbin R. Finite volume methods[J]. Handbook of numerical analysis, 2000, 7: 713-1018.
[8] Metropolis N, Ulam S. The monte carlo method[J]. Journal of the American statistical association, 1949, 44(247): 335-341.
[9] Zhu C, Liu Q. Review of Monte Carlo modeling of light transport in tissues[J]. Journal of biomedical optics, 2013, 18(5): 050902-050902.
[10] Wilson B C, Adam G. A Monte Carlo model for the absorption and flux distributions of light in tissue[J]. Medical physics, 1983, 10(6): 824-830.
[11] Dombrovsky L A. Radiation heat transfer in disperse systems[M]. Begell House, 1996.
[12] Lallich S, Enguehard F, Baillis D. Experimental determination and modeling of the radiative properties of silica nanoporous matrices[J]. 2009.
[13] Wang L, Jacques S L, Zheng L. MCML—Monte Carlo modeling of light transport in multi-layered tissues[J]. Computer methods and programs in biomedicine, 1995,
[14] Mosegaard K, Tarantola A. Monte Carlo sampling of solutions to inverse problems[J]. Journal of Geophysical Research: Solid Earth, 1995, 100(B7): 12431-12447.
[15] Holland J H. Genetic algorithms[J]. Scientific american, 1992, 267(1): 66-73.
[16] Bohren C F, Huffman D R. Absorption and scattering of light by small particles[M]. John Wiley & Sons, 2008.
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