Numerical modeling of the radiative transfer in a turbid medium using the synthetic iteration

Budak, Vladimir P.; Kaloshin, Gennady A.; Shagalov, Oleg V.; Zheltov, Victor S.

doi:10.1364/oe.23.00a829

Cited by 13 publications

(7 citation statements)

References 8 publications

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“…In [29,30] the performance assessment of MDOM was conducted. In particular, the computational time of MDOM was measured for computing the angular distributions of the reflected radiances with different values of N and M. At the same time, it was found that for all N and M the computed radiances coincide in the entire range of angles except for the small glory region.…”

Section: Synthetic Iteration Methodsmentioning

confidence: 99%

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Analysis of the Discrete Theory of Radiative Transfer in the Coupled “Ocean–Atmosphere” System: Current Status, Problems and Development Prospects

Afanas'ev

Basov

Budak

et al. 2020

JMSE

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In this paper, we analyze the current state of the discrete theory of radiative transfer. One-dimensional, three-dimensional and stochastic radiative transfer models are considered. It is shown that the discrete theory provides a unique solution to the one-dimensional radiative transfer equation. All approximate solution techniques based on the discrete ordinate formalism can be derived based on the synthetic iterations, the small-angle approximation, and the matrix operator method. The possible directions for the perspective development of radiative transfer are outlined.

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Section: Synthetic Iteration Methodsmentioning

confidence: 99%

“…A numerical comparison of the reflected radiance after the first iteration of MDOM is given in [29,30]. To calculate the glory region in the MDOM program, N = 801 and M = 256 are required, which corresponds to a sampling step of less than 0.5 • .…”

Section: )mentioning

confidence: 99%

Analysis of the Discrete Theory of Radiative Transfer in the Coupled “Ocean–Atmosphere” System: Current Status, Problems and Development Prospects

Afanas'ev

Basov

Budak

et al. 2020

JMSE

Self Cite

View full text Add to dashboard Cite

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“…Keeping in mind the advantages and limitations of the exact discrete ordinate approach and approximate solution techniques, we can formulate a hybrid approach based on synthetic iterations [29][30]. Originally such an approach was formulated in nuclear physics.…”

Section: Synthetic Iterationsmentioning

confidence: 99%

Methods Calculating the Slab Radiance Factor

Budak

Efremenko²

2020

Proceedings of the 30th International Conference on Computer Graphics and Machine Vision (GraphiCon 2020). Part 2

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One of the most critical problems of realistic visualization of the real-world objects is physically adequate modeling of their reflection of light. Reflection of light by objects occurs both from the surface and the bulk of matter (scattering). Accounting for the light reflection from the surface of objects was solved almost a century ago based on its representation as a Fresnel randomly rough surface. Scattering by a bulk of matter is the subject of radiation transfer theory, which has only recently received its known completion in the form of discrete transfer theory. Strict analytical methods for solving the radiation transport equation (RTE) are often not highly effective for calculating the radiance factor. For a long time, in the absence of effective numerical methods for solving problems and the unavailability of high-speed computers for practical calculations, approximate methods for solving RTE were developed. However, their accuracy and applicability limits were poorly defined. The discrete transfer theory allowed us to evaluate the existing approximate methods for solving the UPI, their accuracy, and the efficiency of application for calculating the radiance factor. It is shown that the most effective method is the method of synthetic iterations. The method is based on the selection of the solution anisotropic part based on a small-angle approximation of the RTE solution. The solution regular part can be calculated by any approximation. Then a simple iteration from the complete solution is performed to refine the angular distribution of the radiance factor.

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“…It excludes redundant information from the initial dataset and improves the efficiency of machine learning. This topic has been addressed frequently in the context of high-performance radiative transfer modelling (Natraj et al 2005;Liu et al 2006;Matricardi 2010;Efremenko et al 2014b;Budak et al 2015).…”

Section: Dimensionality Reductionmentioning

confidence: 99%

Volcanic SO₂ plume height retrieval from UV sensors using a full-physics inverse learning machine algorithm

Efremenko

Loyola

Hedelt

et al. 2017

International Journal of Remote Sensing

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Precise knowledge of the location and height of the volcanic sulphur dioxide (SO 2) plume is essential for accurate determination of SO 2 emitted by volcanic eruptions. Current SO 2 plume height retrieval algorithms based on ultraviolet (UV) satellite measurements are very time-consuming and therefore not suitable for near-real-time applications. In this work we present a novel method called the full-physics inverse learning machine (FP-ILM) algorithm for extremely fast and accurate retrieval of the SO 2 plume height. FP-ILM creates a mapping between the spectral radiance and the geophysical parameters of interest using supervised learning methods. The FP-ILM combines smart sampling methods, dimensionality reduction techniques, and various linear and non-linear regression analysis schemes based on principal component analysis and neural networks. The computationally expensive operations in FP-ILM are the radiative transfer model computations of a training dataset and the determination of the inversion operatorthese operations are performed off-line. The application of the resulting inversion operator to real measurements is extremely fast since it is based on calculations of simple regression functions. Retrieval of the SO 2 plume height is demonstrated for the volcanic eruptions of Mt. Kasatochi (in 2008) and Eyjafjallajökull (in 2010), measured by the GOME-2 (Global Ozone Monitoring Instrument-2) UV instrument on-board MetOp-A.

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Numerical modeling of the radiative transfer in a turbid medium using the synthetic iteration

Cited by 13 publications

References 8 publications

Analysis of the Discrete Theory of Radiative Transfer in the Coupled “Ocean–Atmosphere” System: Current Status, Problems and Development Prospects

Analysis of the Discrete Theory of Radiative Transfer in the Coupled “Ocean–Atmosphere” System: Current Status, Problems and Development Prospects

Methods Calculating the Slab Radiance Factor

Volcanic SO₂ plume height retrieval from UV sensors using a full-physics inverse learning machine algorithm

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Numerical modeling of the radiative transfer in a turbid medium using the synthetic iteration

Cited by 13 publications

References 8 publications

Analysis of the Discrete Theory of Radiative Transfer in the Coupled “Ocean–Atmosphere” System: Current Status, Problems and Development Prospects

Analysis of the Discrete Theory of Radiative Transfer in the Coupled “Ocean–Atmosphere” System: Current Status, Problems and Development Prospects

Methods Calculating the Slab Radiance Factor

Volcanic SO2 plume height retrieval from UV sensors using a full-physics inverse learning machine algorithm

Contact Info

Product

Resources

About

Volcanic SO₂ plume height retrieval from UV sensors using a full-physics inverse learning machine algorithm