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Application of a Neural Network to Store and Compute the Optical Properties of non-spherical particles

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Advances in Atmospheric Sciences 2022年第12期39卷 2024-2039页

作者： Jinhe YU Lei BI Wei HAN Xiaoye ZHANG Key Laboratory of Geoscience Big Data and Deep Resource of Zhejiang Province School of Earth SciencesZhejiang UniversityHangzhou 310027China Center for Earth System Modeling and Prediction China Meteorological AdministrationBeijing 100081China Numerical Weather Prediction Center China Meteorological AdministrationBeijing 100081China Key Laboratory of Atmospheric Chemistry of China Meteorological Administration Institute of Atmospheric CompositionChinese Academy of Meteorological SciencesBeijing 100081China

Radiative transfer simulations and remote sensing studies fundamentally require accurate and efficient computation of the optical properties of non-spherical *** paper proposes a deep learning(DL)scheme in conjunction with an optical property database to achieve this *** neural network(DNN)architectures were obtained from a dataset of the optical properties of super-spheroids with extensive shape parameters,size parameters,and refractive *** dataset was computed through the invariant imbedding T-matrix *** separate DNN architectures were created to compute the extinction efficiency factor,single-scattering albedo,asymmetry factor,and phase *** criterion for designing these neural networks was the achievement of the highest prediction accuracy with minimal DNN *** numerical results demonstrate that the determination coefficients are greater than 0.999 between the prediction values from the neural networks and the truth values from the database,which indicates that the DNN can reproduce the optical properties in the dataset with high *** addition,the DNN model can robustly predict the optical properties of particles with high accuracy for shape parameters or refractive indices that are unavailable in the ***,the ratio of the database size(~127 GB)to that of the DNN parameters(~20 MB)is approximately 6810,implying that the DNN model can be treated as a highly compressed database that can be used as an alternative to the original database for real-time computing of the optical properties of non-spherical particles in radiative transfer and atmospheric models.

关键词： non-spherical particles light scattering super-spheroid model deep learning neural network

DEM investigation of angle of repose for super-ellipsoidal particles

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Particuology 2020年第3期18卷 53-66页

作者： Hao Chen Shiwei Zhao Xiaowen Zhou State Key Laboratory of Subtropical Building Science South China University of TechnologyGuangzhou 510641China

We explore the effect of particle shape on the angle of repose (AoR) in granular packing using a three-dimensional discrete element ***-spherical particles were modeled using super-ellipsoids characterized by aspect ratio and *** relationship between AoR and particle shape was examined,followed by a series of analyses on the origin of AoR from a microscopic *** show that,with blockiness deviating from unity,AoR has an approximate "M" shape that exhibits a strong to weak trend with aspect ratio,matching results of previous *** finding suggests a parabolic relationship between normalized AoR and normalized coordination number,AoR increases with anisotropy related more with the anisotropy of particle orientation than with the anisotropy of contact *** shape is more likely to affect AoR by affecting the tangential force than the normal contact *** analysis based on traction indicates that dips in stress associated with the tangential force (compared with the normal force) and non-spherical particles (compared with spheres) are more *** various particle shapes,AoR is positively correlated with friction mobilization but is negatively correlated with friction mobilization for various coefficient of friction.

关键词： Discrete element Angle of repose non-spherical particles Granular fabric Packing

Axial segregation characteristics and size-induced flow behavior of particles in a novel rotary drum with curved sidewalls

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Particuology 2024年第4期87卷 1-19页

作者： Qiuhua Miao Wenchang Zhu Yudong Cao Peng Huang Chaobin Hu Minping Jia School of Mechanical Engineering Southeast UniversityNanjing211189China Jiangsu Key Laboratory for Elevator Inteligent Safety Changshu215500China

Particle mixing and segregation are common phenomena in rotary drums,which are challenging to be controlled and driven artificially in powder *** this work,the discrete element method(DEM)was applied to construct the novel rotary drum composed of different shaped curved *** varying the operation parameters of particle and sidewall shapes as well as the length-to-diameter(L/D)ratio of drums,the axial mixing and segregation processes of binary size-induced particles were *** results show that the axial flow velocity of the particle mixtures is noticeably weakened once the particle angularity increases,making the non-spherical particles to mix better in rotary drums compared to the spherical ***,in the short drums with size-induced spherical particles,the axial segregation characteristics are significantly enhanced by the convex sidewalls while suppressed by the concave ***,for size-induced non-spherical particles,the axial segregation structure can be present in rotary drums with plane and concave sidewalls while not in drums with convex ***,the axial segregation band structure of spherical particles eventually increases proportionally with the increased drum L/D *** contrast,the non-spherical particles cannot form obvious multi-proportional segregation bands.

关键词： Axial flow behaviors Size-induced particles Curved sidewalls non-spherical particles Rotary drum

Connecting particle sphericity and circularity

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Particuology 2021年第1期19卷 1-4页

作者： John R.Grace Arian Ebneyamini Department of Chemical&Biological Engineering University of British ColumbiaVancouver V6T 1Z3Canada

Sphericity,a measure of how much a particle’s shape deviates from spherical,is useful as a shape factorwhen characterizing particulate ***,particle surface areas,required when determiningthe sphericity,are very difficult to *** a result,the circularity,derivable from microscopic views,is often measured instead and assumed to be equal to the *** paper shows that the twoquantities are generally not equal for simple non-spherical shapes and provides advice on improving theestimation of sphericity from circularity.

关键词： non-spherical particles Sphericity Circularity Shape factorsa

Numerical investigation of non-spherical particle deposition characteristics on filter media

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Building Simulation 2023年第8期16卷 1331-1343页

作者： Lumin Chen Ke Yuan Fuping Qian Zhimin Zheng Jinli Lu Yunlong Han School of Energy and Environment Anhui University of TechnologyMa'anshanAnhui 243002China School of Civil Engineering and Architecture Anhui University of TechnologyMa'anshanAnhui 243002China

In the building environment,PM2.5 seriously affects people’s health and quality of life,so it is necessary to study the particle deposition *** addition,it is essential for a thorough investigation of the dust removal mechanism to understand the non-spherical particles deposition *** stacking angle experiment was used to calibrate the discrete element simulation *** four simulation methods(CFD-DPM,CFD-DEM,API interface loading drag model based on EDEM software and EDEM simulation)were used to numerically simulate the non-spherical particles deposition *** optimal simulation method EDEM was applied to study the non-spherical particles deposition characteristics in filter media,which saves the calculation time *** this basis,the particle parameters on the particle deposition characteristics of filter media were *** results show that the deposition rate of non-spherical(special shape)particles with the same volume is basically consistent on the filter media,hence it is more realistic that the dust actual shape is simplified into the triangular-shaped *** the particle size increases,the number of deposited particles on the filter media *** the larger the particle size,the more dispersed the *** has a significant impact on the number of particles deposited on the filter media when the particle velocity is 0.1 m/*** particle deposits to the lower part of the filter media in the form of a parabola and deviates from the outlet seriously at 0.1 m/***,it has little effect on the number of particle deposition at the other velocities,and most particles are deposited on the upper part of the filter media with the increase of particle velocity.

关键词： particle deposition non-spherical particles calibration of stacking angle discrete element method

DEM simulations of tote blenders for enhanced axial mixing efficiency

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Particuology 2021年第2期19卷 199-208页

作者： Fuhai Yu Zhihao Yao Guojie Chen Yun Zhang Yang Zheng Department of Chemistry and Chemical Engineering Jining UniversityQufu 273155China College of Chemical Engineering and Safety Binzhou UniversityBinzhou 256603China College of Horticulture and Plant Protection Yangzhou UniversityYangzhou 225009China

The mixing performance of a multi-bladed tote blender is investigated using a graphics processing unit-based discrete element method *** positioning,dimensions,and applicability of the baffles are systematically studied according to the axial mixing *** results indicate that the novel inclined multi-bladed baffles can break the symmetrical axial granular flow and introduce a more efficient convective flow into the granular mixing in the axial direction of the tote *** to the joint effects of convective mixing and asymmetrical granular flow,the axial mixing efficiency is increased by a factor of nearly *** importantly,the novel baffle placement approach exhibits excellent applicability to different operating conditions,particle shapes,and blender ***,the inclined baffles can prevent the segregation caused by shape discrepancies and improve the mixing homogeneity in the steady *** novel baffle design is promising for applications in more complex industrial blenders for achieving a high axial mixing efficiency.

关键词： Discrete element method(DEM) Tote blender Axial mixing efficiency Inclined baffles non-spherical particles