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Prediction of the radiative properties of surfaces covered with particulate deposits.

Authors :
Lin, Qunqing
Xuan, Yimin
Han, Yuge
Source :
Journal of Quantitative Spectroscopy & Radiative Transfer. Jul2017, Vol. 196, p112-122. 11p.
Publication Year :
2017

Abstract

The heterogeneous particulate deposit has a significant impact on the radiative properties of surfaces. It is necessary to establish a physical model to describe the apparent spectral absorptance of surfaces covered with heterogeneous particulate deposits. In this paper, a general method combining the effective medium theory with the RTM-DRE (ray-tracing method based on the decomposition of radiation energy) method is presented to predict the apparent spectral absorptance of such surfaces. The effective optical constants of the inhomogeneous particles were determined by means of the effective medium theory, whereas the radiative properties of the surfaces were calculated by modeling the radiative transfer process based on the RTM-DRE method. Additionally, the experimental characterizations of the dust deposits were investigated to reveal the dust effect on the radiative properties of surfaces, and the experimental data and theoretical results were compared to validate the presented theoretical model. The mean relative errors lie within 11.0% of the solar band and 7.0% of the infrared waveband, which indicates the reliability of the theoretical model. Furthermore, the effect of the geometric structure parameters and material intrinsic properties on the radiative properties of the surfaces with heterogeneous particulate deposit was investigated based on the prediction model. Six main factors including the deposit thickness, particle size, bulk fraction, chemical compositions, H 2 O content, and substrate reflectance were considered. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
00224073
Volume :
196
Database :
Academic Search Index
Journal :
Journal of Quantitative Spectroscopy & Radiative Transfer
Publication Type :
Academic Journal
Accession number :
123374357
Full Text :
https://doi.org/10.1016/j.jqsrt.2017.04.001