Analysis of error in soot characterization using scattering-based techniques

Ma, Lin

doi:10.1016/j.partic.2011.02.002

Cited by 8 publications

(1 citation statement)

References 29 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The balance between accuracy and computational expense is the main concern for calculation of the optical properties of nanoparticle systems. While RDG-FA is one of the fastest approaches available, Ma [10] compared angular scattering properties of soot aggregates comprised of 128 particles each having a diameter of 30 nm with m = 1.77 + 0.63i, and observed a relative error up to 10% in both S 11 and S 12 profiles calculated by RDG-FA and T-matrix methods. In another study, Zhao and Ma [11] studied the scattering cross section and some elements of Mueller matrix (S 11 , S 12 and S 33 ) of soot aggregates, and observed a relative error up to 15% in scattering cross section and up to 50% in the Mueller matrix elements.…”

Section: Introductionmentioning

confidence: 99%

Gaussian process and design of experiments for surrogate modeling of optical properties of fractal aggregates

Eriçok

Özbek

Cemgil

et al. 2019

Journal of Quantitative Spectroscopy and Radiative Transfer

View full text Add to dashboard Cite

A systematic approach based on the principles of supervised learning and design of experiments concepts is introduced to build a surrogate model for estimating the optical properties of fractal aggregates. The surrogate model is built on Gaussian process (GP) regression, and the input points for the GP regression are sampled with an adaptive sequential design algorithm. The covariance functions used are the squared exponential covariance function and the Matern covariance function both with Automatic Relevance Determination (ARD). The optical property considered is extinction efficiency of soot aggregates. The strengths and weaknesses of the proposed methodology are first tested with RDG-FA. Then, surrogate models are developed for the sampled points, for which the extinction efficiency is calculated by DDA. Four different uniformly gridded databases are also constructed for comparison. It is observed that the estimations based on the surrogate model designed with Matern covariance functions is superior to the estimations based on databases in terms of the accuracy of the estimations and the total number of input points they require. Finally, a preliminary surrogate model for S 11 is built to correct RDG-FA predictions with the aim of combining the speed of RDG-FA with the accuracy of DDA.

show abstract

Section: Introductionmentioning

confidence: 99%