Development and validation of an enhanced filtered drag model for simulating gas-solid fluidization of Geldart A particles in all flow regimes

阻力 流态化 机械 阻力系数 湍流 双流体模型 工作(物理) 流量(数学) 热力学 流化床 物理
作者
Xi Gao,Tingwen Li,Avik Sarkar,Liqiang Lu,William A. Rogers
出处
期刊:Chemical Engineering Science [Elsevier]
卷期号:184: 33-51 被引量:163
标识
DOI:10.1016/j.ces.2018.03.038
摘要

Coarse-grid two-fluid simulation of gas-solid fluidized bed reactors based on the kinetic theory of granular flow exhibits a significant dependence on drag models, especially for Geldart A particles. Many drag models are available in the literature, which have been reported to work for different systems. This study focused on the evaluation of an enhanced filtered drag model along with other different drag models derived from different methods for three-dimensional two-fluid model simulations of gas-solid fluidized beds of Geldart A particles covering a broad range of fluidization regimes, including bubbling fluidization, turbulent fluidization, fast fluidization, and dilute phase transport regimes. Eight drag models were selected, which included five heterogeneous drag models and three homogeneous drag models. Comparison with the available experimental data demonstrates the need for modification of homogeneous drag models to account for the effect of mesoscale structures (i.e., bubbles and clusters). The enhanced filtered drag model and energy-minimization multi-scale (EMMS) drag models were found to achieve superior predictions in all fluidization regimes, while the other drag models were only capable of predicting certain fluidization regimes. The results of this work provide a guideline for choosing appropriate drag models for simulating Geldart A particles and suggestions on developing more reliable and general drag models applicable in all flow regimes.

科研通智能强力驱动
Strongly Powered by AbleSci AI
科研通是完全免费的文献互助平台,具备全网最快的应助速度,最高的求助完成率。 对每一个文献求助,科研通都将尽心尽力,给求助人一个满意的交代。
实时播报
3秒前
4秒前
fan完成签到,获得积分20
4秒前
温婉的紫霜完成签到,获得积分10
5秒前
5秒前
NexusExplorer应助奋斗迎波采纳,获得10
5秒前
竹筏过海应助Akhma16采纳,获得30
5秒前
SGOM完成签到 ,获得积分10
5秒前
搜集达人应助zzc采纳,获得10
6秒前
土豆发布了新的文献求助30
6秒前
淡定曼寒应助小鱼采纳,获得20
7秒前
由天与完成签到,获得积分10
7秒前
求助人员发布了新的文献求助10
9秒前
科研通AI6应助小张同学采纳,获得10
10秒前
小L完成签到,获得积分10
11秒前
杨华启完成签到,获得积分10
11秒前
12秒前
平常丝完成签到,获得积分0
13秒前
14秒前
NSS完成签到 ,获得积分10
14秒前
14秒前
崔懿龍发布了新的文献求助10
16秒前
KING发布了新的文献求助10
17秒前
17秒前
呼呼发布了新的文献求助10
17秒前
sci2025opt完成签到 ,获得积分10
18秒前
Criminology34应助123456采纳,获得10
18秒前
天天快乐应助拉长的紫安采纳,获得10
19秒前
19秒前
科研通AI6应助TX采纳,获得10
20秒前
21秒前
仲半邪完成签到,获得积分10
23秒前
嘟嘟嘟发布了新的文献求助20
23秒前
量子星尘发布了新的文献求助10
23秒前
zzc发布了新的文献求助10
24秒前
张虹完成签到,获得积分10
24秒前
mof发布了新的文献求助10
25秒前
25秒前
淡然冬灵应助非何云采纳,获得20
27秒前
28秒前
高分求助中
(应助此贴封号)【重要!!请各用户(尤其是新用户)详细阅读】【科研通的精品贴汇总】 10000
Encyclopedia of Reproduction Third Edition 3000
Comprehensive Methanol Science Production, Applications, and Emerging Technologies 2000
化妆品原料学 1000
1st Edition Sports Rehabilitation and Training Multidisciplinary Perspectives By Richard Moss, Adam Gledhill 600
小学科学课程与教学 500
Study and Interlaboratory Validation of Simultaneous LC-MS/MS Method for Food Allergens Using Model Processed Foods 500
热门求助领域 (近24小时)
化学 材料科学 生物 医学 工程类 计算机科学 有机化学 物理 生物化学 纳米技术 复合材料 内科学 化学工程 人工智能 催化作用 遗传学 数学 基因 量子力学 物理化学
热门帖子
关注 科研通微信公众号,转发送积分 5643294
求助须知:如何正确求助?哪些是违规求助? 4760914
关于积分的说明 15020418
捐赠科研通 4801640
什么是DOI,文献DOI怎么找? 2566917
邀请新用户注册赠送积分活动 1524783
关于科研通互助平台的介绍 1484355