GPU-accelerated inverse identification of radiative properties of particle suspensions in liquid by the Monte Carlo method

Ma, Chunyang; Zhao, Junming; Liu, L.H.; Zhang, L.; Li, X.C; Jiang, Baocheng

doi:10.1016/j.jqsrt.2015.08.002

Cited by 23 publications

(7 citation statements)

References 33 publications

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“…Optimization algorithms based on metaheuristic principles use an entirely different approach. Different metaheuristic methods such as genetic algorithms [Kur20], simulated annealing [ZRL∗09, MES∗11], or particle swarm methods [MZL∗16] impose virtually no constraints on the objective function. Furthermore, they can be parameterized to search the parameter space globally, which can help to minimize the ill‐conditioning of the inverse problem albeit at the cost of longer search times.…”

Section: Inverse Methodsmentioning

confidence: 99%

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Survey of Models for Acquiring the Optical Properties of Translucent Materials

Frisvad

Jensen²,

Madsen³

et al. 2020

Computer Graphics Forum

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The outset of realistic rendering is a desire to reproduce the appearance of the real world. Rendering techniques therefore operate at a scale corresponding to the size of objects that we observe with our naked eyes. At the same time, rendering techniques must be able to deal with objects of nearly arbitrary shapes and materials. These requirements lead to techniques that oftentimes leave the task of setting the optical properties of the materials to the user. Matching the appearance of real objects by manual adjustment of optical properties is however nearly impossible. We can render objects with a plausible appearance in this way but cannot compare the appearance of a manufactured item to that of its digital twin. This is especially true in the case of translucent objects, where we need more than a goniometric measurement of the optical properties. In this survey, we provide an overview of forward and inverse models for acquiring the optical properties of translucent materials. We map out the efforts in graphics research in this area and describe techniques available in related fields. Our objective is to provide a better understanding of the tools currently available for appearance specification when it comes to digital representations of real translucent objects.

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Section: Inverse Methodsmentioning

confidence: 99%

“…In most cases, the flexibility afforded by Monte Carlo ray tracing overcomes this limitation. In addition, the recent development in graphics processing hardware has significantly improved the performance of Monte Carlo ray tracing and made it a competitive approach to solving the inverse problem [MZL∗16, NDVZJ19, LHJ19].…”

Section: Radiometric Modelsmentioning

confidence: 99%

Survey of Models for Acquiring the Optical Properties of Translucent Materials

Frisvad

Jensen²,

Madsen³

et al. 2020

Computer Graphics Forum

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“…This approach has been used to significantly increase accuracy and/or reduce computational time [96][97][98][99][100][101][102][103][104][105][106], often by orders-of-magnitude compared to conventional MC. Reverse tracing also allowed the straightforward treatment of many inverse problems in radiation [107][108][109][110][111][112][113][114][115][116][117]. Fig.…”

Section: Backward Monte Carlomentioning

confidence: 99%

The Past and Future of the Monte Carlo Method in Thermal Radiation Transfer

Howell

Daun

2021

Journal of Heat Transfer

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“…Other approaches without integrating sphere have been investigated such as goniometric measurement and detection of

and non-hemispherical

and

at fixed angles with MC based inverse algorithms. 12 , 13 …”

Section: Introductionmentioning

confidence: 99%

Rapid inverse radiative transfer solver for multiparameter spectrophotometry without integrating sphere

Jin,

Jones,

et al. 2024

J. Biomed. Opt.

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. Significance Multiparameter spectrophotometry (MPS) provides a powerful tool for accurate characterization of turbid materials in applications such as analysis of material compositions, assay of biological tissues for clinical diagnosis and food safety monitoring. Aim This work is aimed at development and validation of a rapid inverse solver based on a particle swarm optimization (PSO) algorithm to retrieve the radiative transfer (RT) parameters of absorption coefficient, scattering coefficient and anisotropy factor of a turbid sample. Approach Monte Carlo (MC) simulations were performed to obtain calculated signals for comparison to the measured ones of diffuse reflectance, diffuse transmittance and forward transmittance. An objective function has been derived and combined with the PSO algorithm to iterate MC simulations for MPS. Results We have shown that the objective function can significantly reduce the variance in calculated signals by local averaging of an inverse squared error sum function between measured and calculated signals in RT parameter space. For validation of the new objective function for PSO based inverse solver, the RT parameters of 20% Intralipid solutions have been determined from 520 to 1000 nm which took about 2.7 minutes on average to complete signal measurement and inverse calculation per wavelength. Conclusion The rapid solver enables MPS to be translated into easy-to-use and cost-effective instruments without integrating sphere for material characterization by separating and revealing compositional profiles at the molecular and particulate scales.

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GPU-accelerated inverse identification of radiative properties of particle suspensions in liquid by the Monte Carlo method

Cited by 23 publications

References 33 publications

Survey of Models for Acquiring the Optical Properties of Translucent Materials

Survey of Models for Acquiring the Optical Properties of Translucent Materials

The Past and Future of the Monte Carlo Method in Thermal Radiation Transfer

Rapid inverse radiative transfer solver for multiparameter spectrophotometry without integrating sphere

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