Near-wall vortices and thermal simulation of coupled-domain transpiration cooling by a recursive regularized lattice Boltzmann method

雷诺数 湍流 物理 格子Boltzmann方法 涡流 机械 传热 大涡模拟 热力学
作者
Zhihui Zhang,Xiaoyu Wu,Xian Wang
出处
期刊:Physics of Fluids [American Institute of Physics]
卷期号:34 (10) 被引量:12
标识
DOI:10.1063/5.0111574
摘要

The present study aims to reveal the near-wall vortices and the effects of flow states in coupled-domain transpiration cooling using a recursive regularized thermal lattice Boltzmann method (RR-TLBM). Large-eddy simulations of turbulent flow and heat transfer have been conducted on high-resolution computational grids using a desktop-level computer with CUDA 11.6. Results indicate that the near-wall flow structures present spatial characteristics along the streamwise direction. The vortex evolution promotes the downstream heat dissipation, even though turbulence impairs the effective cooling area. The spanwise evolvement of vortices strengthens the mixing of coolant and hot gas, and small-scale structures are beneficial for turbulent heat transfer. Moreover, the transition onset occurs earlier at higher Reynolds numbers, and it weakens the downstream cooling. The cooling performance of the derived coolant film is improved as the Reynolds number varies from 5 × 103 to 3 × 104 with a blowing ratio of F = 10%, whereas the local cooling is impaired at the high Reynolds numbers exceeding 5 × 104. The variation in flow states has little influence on the cooling performance at the Reynolds numbers larger than 3 × 106. On the other hand, our in-house RR-TLBM solver is highly stable and efficient for the simulation of flow and heat transfer with high Reynolds numbers. Simultaneously, a high computational performance of 1127 million lattices updated per second is achieved for our simulation of a coupled-domain turbulent flow and heat transfer, using the desktop-level computer with three Tesla V100 graphics processing units.

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
刚刚
刚刚
xy发布了新的文献求助10
刚刚
1秒前
1秒前
1秒前
1秒前
2秒前
dfggb发布了新的文献求助10
2秒前
nina完成签到 ,获得积分10
3秒前
量子星尘发布了新的文献求助10
3秒前
哈哈哈完成签到,获得积分10
4秒前
万能图书馆应助FOREST采纳,获得10
4秒前
joy发布了新的文献求助30
4秒前
wang发布了新的文献求助10
5秒前
王硕发布了新的文献求助10
5秒前
李健应助光轮2000采纳,获得10
5秒前
5秒前
5秒前
六柳应助Butler采纳,获得10
6秒前
6秒前
Sepvvvvirtue发布了新的文献求助10
7秒前
Orange应助雪千羽采纳,获得10
8秒前
wodeqiche2007发布了新的文献求助10
8秒前
silveryyds完成签到,获得积分10
9秒前
ZT9发布了新的文献求助10
9秒前
李梦月发布了新的文献求助10
10秒前
充电宝应助dfggb采纳,获得10
10秒前
10秒前
臧磊应助落水无波采纳,获得30
10秒前
Linyongpeng发布了新的文献求助10
10秒前
11秒前
13秒前
13秒前
慕青应助123123123采纳,获得10
13秒前
量子星尘发布了新的文献求助10
14秒前
14秒前
单薄映天发布了新的文献求助10
14秒前
素素发布了新的文献求助10
14秒前
14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
2025-2031全球及中国金刚石触媒粉行业研究及十五五规划分析报告 6000
Real World Research, 5th Edition 680
Qualitative Data Analysis with NVivo By Jenine Beekhuyzen, Pat Bazeley · 2024 660
Superabsorbent Polymers 600
Handbook of Migration, International Relations and Security in Asia 555
Between high and low : a chronology of the early Hellenistic period 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 5675794
求助须知:如何正确求助?哪些是违规求助? 4949173
关于积分的说明 15154796
捐赠科研通 4835088
什么是DOI,文献DOI怎么找? 2589854
邀请新用户注册赠送积分活动 1543583
关于科研通互助平台的介绍 1501336