Fast image processing method for coal particle cluster box dimension measurement and its application in diffusion coefficient testing

分形维数 扩散 反向 维数(图论) 粒子(生态学) 投影(关系代数) 分形 图像处理 反问题 计算机科学 算法 生物系统 数学 图像(数学) 数学分析 人工智能 几何学 化学 物理 热力学 地质学 有机化学 纯数学 海洋学 生物
作者
Jingjing Liu,Ruihang Liu,Haoxiang Zhang,He Jiang,Qiqi Kou,Deqiang Cheng,Jiansheng Qian
出处
期刊:Fuel [Elsevier BV]
卷期号:352: 129050-129050 被引量:1
标识
DOI:10.1016/j.fuel.2023.129050
摘要

The diffusion coefficient is the key parameter used to characterize methane diffusion behavior in coal. The commonly used analytical solutions for diffusion coefficients require simplifying the particle shape to regular shapes, which greatly deviates from the actual shape of coal particles. The influence of coal particle shape on the diffusion coefficient is currently not well understood. Based on image processing techniques and inverse problem-based numerical simulation, a new method is proposed in this paper to determine the diffusion coefficients of irregular coal particles, and a feasible solution for quantitatively assessing the influence of particle shapes on the diffusion coefficient is provided. The implementation of this method is based on two aspects: the fast quantitative characterization of the shape features of coal particle clusters and inverse problem-based numerical simulation to solve the diffusion coefficient of irregularly shaped coal particles. First, image processing technology is used to quickly and accurately extract the 2D projection contour of batch particles, and an algorithm based on fractal theory is designed to obtain the box dimension of batch contours, which achieves the quantitative characterization for the shape features of coal particle clusters. At the same time, a comparison with Fraclab is conducted to validate the scientific effectiveness of the box dimension algorithm. Then, 3 coal particles with representative fractal dimensions are selected and their diffusion coefficients are obtained using the inverse problem numerical method. The results indicate that the desorption curves obtained through inverse problem optimization for the 3 particles are excellently consistent with the experimental data, with fitting degrees R2 all exceeding 99%. Therefore, the diffusion coefficients can be effectively obtained. Meanwhile, the influence of shape on the diffusion coefficient is analyzed quantitatively. The results show that the diffusion coefficient increases with the box dimension of the contour, and the particle shape has a considerable impact on determining the gas diffusion coefficient.

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
yy完成签到 ,获得积分10
3秒前
anna1992发布了新的文献求助10
3秒前
3秒前
CipherSage应助sulfor采纳,获得10
3秒前
kelakola完成签到,获得积分10
4秒前
4秒前
AAA小狗零售代理完成签到 ,获得积分10
5秒前
彭于晏应助郑航宇采纳,获得10
5秒前
8秒前
AAA小狗零售代理关注了科研通微信公众号
9秒前
李小晴天发布了新的文献求助10
9秒前
9秒前
科研通AI6.2应助嘀嘀咕咕采纳,获得10
10秒前
所所应助huangyulin2003采纳,获得10
11秒前
11秒前
小厂长QwQ完成签到,获得积分20
12秒前
12秒前
炙热初夏完成签到,获得积分10
13秒前
所所应助galaxy采纳,获得10
14秒前
踏实河马完成签到,获得积分10
15秒前
15秒前
sulfor发布了新的文献求助10
16秒前
雪白的以蓝完成签到,获得积分20
17秒前
1111chen发布了新的文献求助10
17秒前
科研通AI6.4应助王金金采纳,获得10
18秒前
粗犷的思萱完成签到 ,获得积分10
19秒前
19秒前
19秒前
酷波er应助Betty采纳,获得10
20秒前
ATH完成签到,获得积分10
22秒前
Felicity发布了新的文献求助10
23秒前
搜集达人应助健壮念寒采纳,获得10
23秒前
略略略关注了科研通微信公众号
23秒前
SONG完成签到,获得积分10
24秒前
小厂长QwQ发布了新的文献求助10
24秒前
25秒前
26秒前
xing_xing应助AN采纳,获得20
26秒前
JamesPei应助聪明的小白菜采纳,获得10
26秒前
大个应助寒冷书文采纳,获得10
27秒前
高分求助中
Markov Chain Monte Carlo 10000
(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
Common Foundations of American and East Asian Modernisation: From Alexander Hamilton to Junichero Koizumi 5000
How to Use Machine Learning in Chemistry: An Introduction 1000
Matrix Methods in Data Mining and Pattern Recognition Second Edition 510
Discerning Saints: Moralization of Intrinsic Motivation and Selective Prosociality at Work 500
Handbuch Trainingswissenschaft – Trainingslehre 500
热门求助领域 (近24小时)
化学 材料科学 医学 生物 纳米技术 工程类 有机化学 化学工程 生物化学 计算机科学 内科学 物理 复合材料 催化作用 细胞生物学 无机化学 光电子学 物理化学 电极 基因
热门帖子
关注 科研通微信公众号,转发送积分 7584089
求助须知:如何正确求助?哪些是违规求助? 9162837
关于积分的说明 19608306
捐赠科研通 7165970
什么是DOI,文献DOI怎么找? 3266369
关于科研通互助平台的介绍 2431345
邀请新用户注册赠送积分活动 2257929