Detailed assessment with sensitivity analysis of solid stress model in MP-PIC simulation for bubbling fluidized beds

IF 4.3 2区 材料科学 Q2 ENGINEERING, CHEMICAL Particuology Pub Date : 2025-04-01 Epub Date: 2025-03-08 DOI:10.1016/j.partic.2025.02.022
Chenxi Lu , Minmin Zhou , Hang Zhou , Jiwei Yao , Daoyin Liu , Yueming Wang , Lunbo Duan
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Abstract

Gas-solid granular flows are widely used in multiple industrial applications. The Multiphase Particle-In-Cell (MP-PIC) method is increasingly recognized for its capability to efficiently model these industrial-scale gas-solid granular flows. The solid stress model is crucial in MP-PIC method; however, its influence on the simulation results has not been thoroughly investigated. In this work, the pseudo-2D bubbling fluidized bed is modeled using MP-PIC method in OpenFOAM, in which the experiment operates at twice the minimum fluidization velocity condition using glass bead as the bed material. We primarily investigate the variation of the inter-particle solid stress values in the bed and its influence on the simulation results across a range of solid stress model parameters. The simulation results including bubble size, aspect ratio, and pressure drop and bed height, have been compared with the corresponding experimental data and empirical correlation. Sensitivity analysis narrows down the solid stress model parameter space and identify the most sensitive parameter is the close-packed volume fraction of particles. Results demonstrate that solid stress plays a significant role in dense particle flow, making particles more dispersed. Increasing solid stress reduces bubble size, aspect ratio, and pressure drop fluctuations, with minimal impact on bed height and average pressure drop. By comparing simulations and experiments, the optimal parameters of the model are determined. Moreover, the obtained optimal parameters effectively predict gas-solid flow across varying fluidization velocities and three-dimensional fluidized beds. This study provides a detailed analysis of solid stress effects, offering a more comprehensive understanding of the parameters for future MP-PIC simulations and validations.

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鼓泡流化床MP-PIC模拟中固体应力模型的详细评价及灵敏度分析
气固颗粒流广泛应用于多种工业应用中。多相颗粒池(MP-PIC)方法因其能够有效地模拟这些工业规模的气固颗粒流动而日益得到认可。在MP-PIC方法中,固体应力模型是关键;然而,其对模拟结果的影响尚未得到深入研究。本文采用OpenFOAM软件中的MP-PIC方法对拟二维鼓泡流化床进行建模,实验以最小流化速度的两倍为条件,以玻璃微珠为床层材料。我们主要研究了床层颗粒间固体应力值的变化及其在一系列固体应力模型参数下对模拟结果的影响。模拟结果包括气泡尺寸、长径比、压降和床层高度,并与相应的实验数据和经验相关性进行了比较。灵敏度分析缩小了固体应力模型参数空间,确定了最敏感的参数是颗粒的密实体积分数。结果表明,固体应力对致密颗粒流动起着重要作用,使颗粒更加分散。增加固体应力可以减小气泡尺寸、纵横比和压降波动,对床层高度和平均压降的影响最小。通过仿真与实验对比,确定了模型的最优参数。此外,所得到的最优参数可以有效地预测不同流化速度和三维流化床的气固流动。该研究提供了固体应力效应的详细分析,为未来的MP-PIC模拟和验证提供了更全面的参数理解。
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来源期刊
Particuology
Particuology 工程技术-材料科学:综合
CiteScore
6.70
自引率
2.90%
发文量
1730
审稿时长
32 days
期刊介绍: The word ‘particuology’ was coined to parallel the discipline for the science and technology of particles. Particuology is an interdisciplinary journal that publishes frontier research articles and critical reviews on the discovery, formulation and engineering of particulate materials, processes and systems. It especially welcomes contributions utilising advanced theoretical, modelling and measurement methods to enable the discovery and creation of new particulate materials, and the manufacturing of functional particulate-based products, such as sensors. Papers are handled by Thematic Editors who oversee contributions from specific subject fields. These fields are classified into: Particle Synthesis and Modification; Particle Characterization and Measurement; Granular Systems and Bulk Solids Technology; Fluidization and Particle-Fluid Systems; Aerosols; and Applications of Particle Technology. Key topics concerning the creation and processing of particulates include: -Modelling and simulation of particle formation, collective behaviour of particles and systems for particle production over a broad spectrum of length scales -Mining of experimental data for particle synthesis and surface properties to facilitate the creation of new materials and processes -Particle design and preparation including controlled response and sensing functionalities in formation, delivery systems and biological systems, etc. -Experimental and computational methods for visualization and analysis of particulate system. These topics are broadly relevant to the production of materials, pharmaceuticals and food, and to the conversion of energy resources to fuels and protection of the environment.
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