(58i) Particle Scattering Photography Approach for Measurement of Multiphase Reactors: Theoretical Simulation and Experimental Optimization | AIChE

(58i) Particle Scattering Photography Approach for Measurement of Multiphase Reactors: Theoretical Simulation and Experimental Optimization

Authors 

Yang, C. - Presenter, Institute of Process Engineering, Chinese Academy of Sciences
Li, X., Institute of Process Engineering, Chinese Academy of Sciences
Mao, Z. S., Institute of Process Engineering, Chinese Academy of Sciences
Xie, M., Zhejiang Greatwall Mixers Co., Ltd

Particle scattering photography approach for measurement of multiphase reactors: theoretical simulation and experimental optimization

Yiting Xiao1,2,
Xiangyang Li1,
Zai-Sha Mao1, Minghui Xie3,
Chao Yang1,2*

1Key
Laboratory of Green Process and Engineering, Institute of Process Engineering,

Chinese Academy of Sciences,
Beijing 100190, China

2 University
of Chinese Academy of Sciences, Beijing 100049, China

3 Zhejiang
Greatwall Mixers Co., Ltd, Wenzhou, Zhejiang 325019, China

*Corresponding authors. Tel: +86-10-62554558;
E-mail: chaoyang@ipe.ac.cn (C. Yang)

Abstract

The local property distributions in
multiphase reactors are very important because they can directly reflect the
reactor performance and help to profoundly understand hydrodynamics therein.
Consequently, they have a major impact on design, scale-up and intensification of
multiphase reactors and validation of CFD models. Unfortunately, the existing
measuring techniques are ineffective in case of nearly industrial operating
conditions (particular physico-chemical environment, opaque walls, high gas
holdup or solid concentration, etc.), especially in three-phase systems.

With low-brightness
particles as the dispersed phase in multiphase reactors, the photographic
measurement is encountered with the great challenge in identifying particle
outlines. In this work, a novel approach based on
the light scattering principle is proposed to raise the brightness difference and
then the photography can be successfully implemented. A single-particle
scattering model based on non-coherent scattering hypothesis was developed to
evaluate the total scattering light intensity. A series of experiments were conducted
and tested the theoretical calculation in turn.

The quantitative relationships between scattering-light-intensity
and scattering coefficient/absorption coefficient were established. Further,
the partial light fluxes projected onto the focal plane by single particles
with different sizes were also calculated. On this basis, four representative
oxide powders, i.e., TiO2, Al2O3, CuO and SiO2
were chosen as scattering particles. Aided by scattering light of trace oxide
powders, the grayness differences between two particles-to-be-measured and
liquid phases in all images were improved with different degrees and the TiO2
particles performed the best. The grayness differences varied with the
TiO2 concentration, which was almost in a normal distribution and the
optimum concentrationwas about 7.3 mg/L. As expected, this particle
scattering approach (
<5%) was proved to be more accurate measurement than the reflector-aided
one (
>20%).

Some recent industrial application of
our measurement, mathematical models and numerical simulations of multiphase reactors/crystallizers
have brought about impressive economic benefit by reducing the materials and
energy consumption and pollution emissions and saving of equipment investment,
which make the industrial processes more sustainable and profitable.

Keywords: multiphase reactor; particle scattering
photography; measurement; bubble size
distribution; particle;
concentration

Acknowledgements: The National Key Research and Development Program
(2016YFB0301701), the Major National Scientific Instrument Development Project
(21427814), the National Natural Science Foundation of China (91534117,
21490584), the Key Research Program of Frontier Sciences, CAS
(QYZDJ-SSW-JSC030) and the Instrument Developing Project of Chinese Academy of
Sciences (YZ201641) are gratefully acknowledged.

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