Three-dimensional solidification modeling of various materials using the lattice Boltzmann method with an explicit enthalpy equation

热力学 混合焓 介观物理学 格子Boltzmann方法 滞止焓 分布函数 材料科学 传热 统计物理学 化学 物理 量子力学
作者
Zheng Dai,Zhongyi Wang,Junhao Zhu,Xiaohu Chen,Qing Li,Zongrui Jin
出处
期刊:Physical review [American Physical Society]
卷期号:110 (2) 被引量:1
标识
DOI:10.1103/physreve.110.025301
摘要

Based on the mesoscopic scale, the lattice Boltzmann method (LBM) with an enthalpy-based model represented in the form of distribution functions is widely used in the liquid-solid phase transition process of energy storage materials due to its direct and relatively accurate characterization of the presence of latent heat of solidification. However, since the enthalpy distribution function itself contains the physical properties of the material, these properties are transferred along with the enthalpy distribution function during the streaming process. This leads to deviations between the enthalpy-based model when simulating the phase transition process of different materials mixed and the actual process. To address this issue, in this paper, we construct an enthalpy-based model for different types of materials. For multiple materials, various forms of enthalpy distribution functions are employed. This method still uses the form of enthalpy distribution functions for collisions and streaming processes among the same type of substance, while for heat transfer between different materials, it avoids the direct transfer of enthalpy distribution functions and instead applies a source term to the enthalpy distribution functions, characterizing the heat transfer between different materials through the energy change before and after mixing based on the temperature. To verify the accuracy of the method proposed in this paper, a detailed solidification model for two different materials is constructed using the example of water droplets solidifying in air, and the results are compared with experimental outcomes. The results of the simulation show that the model constructed in this paper is largely in line with the actual process.

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
天空之云发布了新的文献求助10
刚刚
lenon完成签到,获得积分10
2秒前
慕青应助苦瓜采纳,获得10
2秒前
Panpan完成签到,获得积分10
3秒前
FeLaN发布了新的文献求助30
3秒前
知123完成签到,获得积分10
3秒前
洁净雨发布了新的文献求助10
4秒前
专注之双完成签到,获得积分10
4秒前
江睿曦完成签到,获得积分10
5秒前
6秒前
牧青发布了新的文献求助10
6秒前
7秒前
Lucas应助小嘿采纳,获得10
7秒前
小吴完成签到,获得积分20
8秒前
江睿曦发布了新的文献求助10
8秒前
kira发布了新的文献求助20
10秒前
葫勒个娃完成签到,获得积分10
11秒前
北北完成签到 ,获得积分10
12秒前
一生悬命发布了新的文献求助10
12秒前
朴素豪完成签到,获得积分10
14秒前
深情安青应助zhangrf采纳,获得10
15秒前
15秒前
16秒前
16秒前
菠萝医生发布了新的文献求助10
17秒前
kira完成签到,获得积分10
18秒前
18秒前
微风418完成签到,获得积分10
18秒前
猪猪hero发布了新的文献求助10
19秒前
20秒前
潮流季发布了新的文献求助10
21秒前
苍露完成签到 ,获得积分10
21秒前
zyq完成签到 ,获得积分10
21秒前
sword发布了新的文献求助10
23秒前
24秒前
健壮不斜完成签到 ,获得积分10
25秒前
dwhnx发布了新的文献求助200
27秒前
27秒前
背后的诗双应助子云采纳,获得10
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
Research for Social Workers 1000
Signals, Systems, and Signal Processing 510
Discrete-Time Signals and Systems 510
Kinesiophobia : a new view of chronic pain behavior 500
《The Emergency Nursing High-Yield Guide》 (或简称为 Emergency Nursing High-Yield Essentials) 500
The Dance of Butch/Femme: The Complementarity and Autonomy of Lesbian Gender Identity 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 5889065
求助须知:如何正确求助?哪些是违规求助? 6651885
关于积分的说明 15712561
捐赠科研通 5010229
什么是DOI,文献DOI怎么找? 2698846
邀请新用户注册赠送积分活动 1643639
关于科研通互助平台的介绍 1596354