Scaling law of the one-direction flow characteristics of symmetric Tesla valve

标度律 机械 缩放比例 流量(数学) 材料科学 物理 计算机科学 工程类 几何学 数学
作者
Zhe Liu,Wen-Qi Shao,Yong Sun,Bohua Sun
出处
期刊:Engineering Applications of Computational Fluid Mechanics [Taylor & Francis]
卷期号:16 (1): 441-452 被引量:47
标识
DOI:10.1080/19942060.2021.2023648
摘要

A Tesla valve is a kind of micro-valve without moving parts. Due to the great difference between the reverse and forward flow, the Tesla valve is often used in passive fluid control devices. However, most of the current Tesla valve components are optimized and designed based on asymmetric structures. In this study, a Tesla valve pipe system model with symmetric structure is proposed. The characteristics of fluid flow and pressure drop were studied by finite element method and dimensional analysis. First, the pressure drop characteristics of symmetric and asymmetric Tesla valves with different Reynolds number are considered. The results show that the better the symmetry, the better the one-direction flow characteristics of Tesla valve system. Afterwards, through parametric analysis, computational fluid dynamics was used to verify flow characteristics of completely symmetrical Tesla valve system. The shunt angle, shunt pipe diameter and number of valves have significant effects on the pressure drop characteristics of the system. Eventually, based on numerical simulation results, by using the dimensional analysis method, the modification parameter $ \alpha ( {\alpha = \alpha ( {\theta,d,N} )} ) $ was introduced to obtain the scaling law $ \Delta p \sim ({1 + \ln (1 + {N^{3/5R{e^{1/3}}}})})\rho {V^2}L{D^{ - 1}}Re^{ - 1/4} $ between the pressure drop and other parameters of the completely symmetrical Tesla valve piping system.
最长约 10秒,即可获得该文献文件

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
彭于晏应助1A采纳,获得10
刚刚
比奇堡的小鹿完成签到,获得积分10
刚刚
1秒前
3秒前
3秒前
谦让的元瑶完成签到,获得积分10
4秒前
刘总发布了新的文献求助10
4秒前
4秒前
4秒前
5秒前
天真的音完成签到,获得积分10
5秒前
5秒前
wanci应助hdc12138采纳,获得10
6秒前
6秒前
7秒前
8秒前
mimi完成签到 ,获得积分10
8秒前
8秒前
ksfh发布了新的文献求助10
8秒前
山谷完成签到,获得积分10
8秒前
8秒前
9秒前
As故发布了新的文献求助10
10秒前
hdc12138发布了新的文献求助10
11秒前
hdc12138发布了新的文献求助10
11秒前
hdc12138发布了新的文献求助10
11秒前
hdc12138发布了新的文献求助10
11秒前
hdc12138发布了新的文献求助10
11秒前
hdc12138发布了新的文献求助10
11秒前
鲁路修完成签到,获得积分10
11秒前
科研通AI6.4应助七月不远采纳,获得10
11秒前
蔡宇滔发布了新的文献求助10
12秒前
13秒前
科研通AI6.2应助phy采纳,获得10
13秒前
hdc12138发布了新的文献求助10
15秒前
15秒前
hdc12138发布了新的文献求助10
15秒前
hdc12138发布了新的文献求助10
15秒前
hdc12138发布了新的文献求助10
15秒前
东方元语应助四月采纳,获得20
16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
Reducing Compassion Fatigue, Secondary Traumatic Stress and Burnout 600
Comparative Elite Sport Development Systems, Structures and Public Policy 600
Matrix Methods in Data Mining and Pattern Recognition Second Edition 510
Auslegungsgeschichte 500
Cosmos as Art Object: Studies in Plato's Timaeus and Other Dialogues 500
What is the Future of Psychotherapy in Digital Age? Technology, AI Bots, and Psychotherapy after Covid 444
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 7637743
求助须知:如何正确求助?哪些是违规求助? 9211300
关于积分的说明 19758409
捐赠科研通 7204937
什么是DOI,文献DOI怎么找? 3275767
关于科研通互助平台的介绍 2437385
邀请新用户注册赠送积分活动 2272928