Article(id=1239215314794247145, tenantId=1146029695717560320, journalId=1238823019242635269, issueId=1239215308985136031, articleNumber=null, orderNo=null, doi=10.12465/j.issn.0253-4339.2025.04.131, pmid=null, cstr=null, oa=null, hot=null, price=null, onlineType=0, articleFormat=0, articleType=null, articleTypeStr=research-article, receivedDate=1708358400000, receivedDateStr=2024-02-20, revisedDate=1710691200000, revisedDateStr=2024-03-18, acceptedDate=1715011200000, acceptedDateStr=2024-05-07, onlineDate=1773381554554, onlineDateStr=2026-03-13, pubDate=1755273600000, pubDateStr=2025-08-16, doiRegisterDate=null, doiRegisterDateStr=null, onlineIssueDate=1773381554554, onlineIssueDateStr=2026-03-13, onlineJustAcceptDate=null, onlineJustAcceptDateStr=null, onlineFirstDate=null, onlineFirstDateStr=null, sourceXml=null, magXml=null, createTime=1773381554554, creator=13701087609, updateTime=1773381554554, updator=13701087609, issue=Issue{id=1239215308985136031, tenantId=1146029695717560320, journalId=1238823019242635269, year='2025', volume='46', issue='4', pageStart='1', pageEnd='170', issueExtLink='null', onlineDate='null', pubDate='null', beforeIssueId=null, nextIssueId=null, price=null, status=1, issueComplete=1, articleOrder=1, issueType=-1, specialIssue=null, createTime=1773381553169, creator=13701087609, updateTime=1773381893131, updator=13701087609, preIssue=null, nextIssue=null, ext={EN=IssueExt(id=1239216734947824534, tenantId=1146029695717560320, journalId=1238823019242635269, issueId=1239215308985136031, language=EN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=), CN=IssueExt(id=1239216734947824535, tenantId=1146029695717560320, journalId=1238823019242635269, issueId=1239215308985136031, language=CN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=)}, issueFiles=null}, startPage=131, endPage=140, ext={EN=ArticleExt(id=1239215315003962352, articleId=1239215314794247145, tenantId=1146029695717560320, journalId=1238823019242635269, language=EN, title=Optimization and Comparison of 3-D Model of Steam Ejector with Non-Equilibrium Condensation, columnId=null, journalTitle=Journal of Refrigeration, columnName=null, runingTitle=null, highlight=null, articleAbstract=

Steam ejectors are vital components of ejector refrigeration systems and have attracted considerable attention owing to their energy savings and environmental protection. In this study, steam ejector models were optimized, validated, and compared by considering the three-dimensional and non-equilibrium condensation effects. The simulation results of the optimization model were compared with those of the ideal gas model. Based on the condensation model, the effects of the turbulence models (Reynolds-averaged Navier-Stokes (RANS) and large eddy simulation methods (LES)) on the simulation results were studied. Complex flow phenomena captured by different models, such as shock waves, non-equilibrium condensation, and boundary layer separation, were compared and analyzed. The results show that the optimized steam ejector model can credibly predict the ejector performance and capture the complex flow phenomena inside the ejector at the lowest computational cost. The maximum liquid mass fraction obtained using the large eddy simulation method is lower than that obtained using the Reynolds-averaged Navier-Stokes method. The maximum relative deviation against experiments of the entrainment ratio was obtained using the large eddy simulation method of 11%. The condensation model reduces the average relative deviations of the entrainment ratio and critical discharge pressure by 72.0% and 29.9%, respectively.

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Li Yiqiao, female, lecturer, Zhan Tianyou College of Dalian Jiaotong University, Bingshan Refrigeration and Heat Transfer Technologies Co., Ltd., 86-17824829321, E-mail: . Research fields: multiphase heat and mass transfer.
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蒸汽喷射器是喷射式制冷系统的关键设备,具有节能环保优势。同时考虑三维和非平衡凝结效应,优化、验证并对比了蒸汽喷射器模型。对比了考虑凝结效应的优化模型与理想气体模型的模拟结果。基于该凝结模型,研究了湍流处理方法(雷诺平均方法和大涡模拟方法)对模拟结果的影响。分析了不同模型捕捉到的非平衡凝结、激波等复杂流动现象。结果表明:优化后的蒸汽喷射器模型可以以最低计算成本可靠预测喷射器性能并捕捉其内部复杂流动现象,其中大涡模拟方法得到的最大液体质量分数低于雷诺平均方法,喷射系数与实验值的最大相对误差为11%;与理想气体模型相比,凝结模型可使喷射系数和临界出口压力与实验值之间的平均相对误差分别降低72.0%和29.9%。

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李熠桥,女,讲师,大连交通大学詹天佑学院,冰山冷热科技股份有限公司,17824829321,E-mail:。研究方向:多相流传热传质。
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1喷嘴;2接受室;3混合室;4扩散器。

, figureFileSmall=V40f5Hajvqiai6gahoqoZQ==, figureFileBig=L0ZMHcD9uypyIMbpiXwrEQ==, tableContent=null), ArticleFig(id=1239232345409123196, tenantId=1146029695717560320, journalId=1238823019242635269, articleId=1239215314794247145, language=EN, label=Fig.2, caption=Grid partition of steam ejector, figureFileSmall=Co9HwjIrcZjLgbwH6w1fug==, figureFileBig=QWcP9ElxaIT3+5TcA5jI7Q==, tableContent=null), ArticleFig(id=1239232345509786497, tenantId=1146029695717560320, journalId=1238823019242635269, articleId=1239215314794247145, language=CN, label=图2, caption=蒸汽喷射器网格分区, figureFileSmall=Co9HwjIrcZjLgbwH6w1fug==, figureFileBig=QWcP9ElxaIT3+5TcA5jI7Q==, tableContent=null), ArticleFig(id=1239232345589478280, tenantId=1146029695717560320, journalId=1238823019242635269, articleId=1239215314794247145, language=EN, label=Fig.3, caption=Different y+ cross-sectional grids, figureFileSmall=APjAIDNmZwy7j7GzIRJnAQ==, figureFileBig=tySDoFgxNVUGnf0cp8msEQ==, tableContent=null), 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算例pm/kPaTm/℃ps/kPaTs/℃pd/kPa
ag11.951.31.815.81.9~2.1
bf15.556.21.310.81.4~2.4
cf19.661.61.310.81.4~2.9
df24.866.81.310.81.4~3.2
be15.556.21.013.21.1~2.2
ce19.661.61.013.21.1~2.6
de24.866.81.013.21.1~3.3
), ArticleFig(id=1239232349334991842, tenantId=1146029695717560320, journalId=1238823019242635269, articleId=1239215314794247145, language=CN, label=表1, caption=计算参数, figureFileSmall=null, figureFileBig=null, tableContent=
算例pm/kPaTm/℃ps/kPaTs/℃pd/kPa
ag11.951.31.815.81.9~2.1
bf15.556.21.310.81.4~2.4
cf19.661.61.310.81.4~2.9
df24.866.81.310.81.4~3.2
be15.556.21.013.21.1~2.2
ce19.661.61.013.21.1~2.6
de24.866.81.013.21.1~3.3
), ArticleFig(id=1239232349444043750, tenantId=1146029695717560320, journalId=1238823019242635269, articleId=1239215314794247145, language=EN, label=Tab.2, caption=Calculated results of the GCI method, figureFileSmall=null, figureFileBig=null, tableContent=
参数Peext/%e21/%
平均值4.160.760.402.120.45
最小值0.114.80×10-34.60×10-50.951.17×10-4
最大值18.9918.215.92102.1526.48
), ArticleFig(id=1239232349527929835, tenantId=1146029695717560320, journalId=1238823019242635269, articleId=1239215314794247145, language=CN, label=表2, caption=不同模型的GCI计算结果, figureFileSmall=null, figureFileBig=null, tableContent=
参数Peext/%e21/%
平均值4.160.760.402.120.45
最小值0.114.80×10-34.60×10-50.951.17×10-4
最大值18.9918.215.92102.1526.48
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蒸汽喷射器非平衡凝结三维模型优化与对比
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李熠桥 1, 2 , 周丹 2 , 费继友 1
制冷学报 | 2025,46(4): 131-140
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制冷学报 | 2025, 46(4): 131-140
蒸汽喷射器非平衡凝结三维模型优化与对比
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李熠桥1, 2 , 周丹2, 费继友1
作者信息
  • 1大连交通大学詹天佑学院 大连 116028
  • 2冰山冷热科技股份有限公司 大连 116630

通讯作者:

李熠桥,女,讲师,大连交通大学詹天佑学院,冰山冷热科技股份有限公司,17824829321,E-mail:。研究方向:多相流传热传质。
Optimization and Comparison of 3-D Model of Steam Ejector with Non-Equilibrium Condensation
Yiqiao Li1, 2 , Dan Zhou2, Jiyou Fei1
Affiliations
  • 1.Zhan Tianyou College of Dalian Jiaotong University, Dalian, 116028, China
  • 2.Bingshan Refrigeration and Heat Transfer Technologies Co., Ltd., Dalian, 116630, China
出版时间: 2025-08-16 doi: 10.12465/j.issn.0253-4339.2025.04.131
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蒸汽喷射器是喷射式制冷系统的关键设备,具有节能环保优势。同时考虑三维和非平衡凝结效应,优化、验证并对比了蒸汽喷射器模型。对比了考虑凝结效应的优化模型与理想气体模型的模拟结果。基于该凝结模型,研究了湍流处理方法(雷诺平均方法和大涡模拟方法)对模拟结果的影响。分析了不同模型捕捉到的非平衡凝结、激波等复杂流动现象。结果表明:优化后的蒸汽喷射器模型可以以最低计算成本可靠预测喷射器性能并捕捉其内部复杂流动现象,其中大涡模拟方法得到的最大液体质量分数低于雷诺平均方法,喷射系数与实验值的最大相对误差为11%;与理想气体模型相比,凝结模型可使喷射系数和临界出口压力与实验值之间的平均相对误差分别降低72.0%和29.9%。

喷射器  /  大涡模拟  /  非平衡凝结  /  激波  /  边界层

Steam ejectors are vital components of ejector refrigeration systems and have attracted considerable attention owing to their energy savings and environmental protection. In this study, steam ejector models were optimized, validated, and compared by considering the three-dimensional and non-equilibrium condensation effects. The simulation results of the optimization model were compared with those of the ideal gas model. Based on the condensation model, the effects of the turbulence models (Reynolds-averaged Navier-Stokes (RANS) and large eddy simulation methods (LES)) on the simulation results were studied. Complex flow phenomena captured by different models, such as shock waves, non-equilibrium condensation, and boundary layer separation, were compared and analyzed. The results show that the optimized steam ejector model can credibly predict the ejector performance and capture the complex flow phenomena inside the ejector at the lowest computational cost. The maximum liquid mass fraction obtained using the large eddy simulation method is lower than that obtained using the Reynolds-averaged Navier-Stokes method. The maximum relative deviation against experiments of the entrainment ratio was obtained using the large eddy simulation method of 11%. The condensation model reduces the average relative deviations of the entrainment ratio and critical discharge pressure by 72.0% and 29.9%, respectively.

ejector  /  large eddy simulation  /  non-equilibrium condensation  /  shockwave  /  boundary layer
李熠桥, 周丹, 费继友. 蒸汽喷射器非平衡凝结三维模型优化与对比. 制冷学报, 2025 , 46 (4) : 131 -140 . DOI: 10.12465/j.issn.0253-4339.2025.04.131
Yiqiao Li, Dan Zhou, Jiyou Fei. Optimization and Comparison of 3-D Model of Steam Ejector with Non-Equilibrium Condensation[J]. Journal of Refrigeration, 2025 , 46 (4) : 131 -140 . DOI: 10.12465/j.issn.0253-4339.2025.04.131
蒸汽喷射器可利用蒸汽余压回收低压蒸汽,无需额外消耗机械能[1]。在工业制冷领域,传统电力驱动的机械压缩制冷系统越来越不符合节能环保需求。水兼具环保性和安全性,可在蒸汽喷射制冷系统中充当制冷剂,用蒸汽发生器和蒸汽喷射器取代压缩机,减少电能消耗,应用优势显著[2]
由于非平衡凝结、激波、边界层分离等复杂流动现象的存在,蒸汽喷射器流场涉及相变的快速发生和各种参数的突变,仅依靠实验难以对其内部过程进行深入研究[3]。尤其在超声速流体中尚无法实现精确无干扰测量,圆形横截面喷射器产生的光学畸变引起很大的实验误差问题尚无法解决,湍流的拟序结构无法得到[4]。因此,目前可视化实验技术无法实现蒸汽喷射器内复杂流动现象的定量机理性研究,但可以为验证数值模拟方法的准确性提供重要判断依据[5]。在验证数值模型可靠性基础上,数值模拟方法不仅比实验成本低,还可弥补实验方法的不足,捕获蒸汽喷射器内的复杂流动现象,并对其进行局部特征描绘,实现复杂因素作用下微观过程的详细分析,从而为研究物理本质提供依据[6]
计算流体力学中对湍流的处理方法有直接数值模拟(direct eddy simulation,DNS)方法、大涡模拟(large eddy simulation,LES)方法及雷诺平均方法(Reynolds-Averaged Navier-Stokes,RANS)。DNS无需任何湍流模型,而是直接求解湍流运动Navier-Stokes方程。虽然可以获得所有尺度的湍流脉动信息,但计算量巨大,尚无法应用于喷射器的计算。目前可应用于喷射器的数值模拟方法为RANS和LES。其中RANS最为常用,其核心是将N-S方程平均,用时均值和脉动值之和代替瞬时值,只能得到结果的平均值和湍流的宏观特性。在LES中,大尺度脉动用直接模拟方法计算,只将小尺度脉动对大尺度脉动的作用进行模型假设。LES不仅可以通过统计计算得到各个参数的平均量,还可以得到大于惯性子区尺度的脉动信息,以分析湍流拟序结构与宏观物理现象之间的内在关系和影响机理。因此,使用LES对喷射器进行数值模拟研究受到越来越多学者的关注,一些学者尝试使用该方法对空气喷射器进行数值模拟研究[7-9]。许常悦等[7]使用LES研究了超音速空气引射器的内部流动,阐释了工作流体和引射流体的混合和失稳过程。A. Bouhanguel等[8]将空气喷射器的LES结果与可视化实验结果进行对比。结果表明,LES可以预测超音速工作流体和亚音速引射流体相互作用期间在混合室直段中发生的流动不稳定性。然而,大涡模拟方法尚未被成功应用于涉及非平衡凝结的蒸汽喷射器,值得进一步探索。
蒸汽喷射器中水蒸气经历迅速降压降温的跨声速膨胀过程,该过程中水蒸气逐渐偏离饱和平衡态。随着这种不平衡态的发展,喷射器内发生对流场和性能均产生重要影响的非平衡凝结现象[10]。刘中良团队[11-12]观察并分析了蒸汽喷射器中凝结液滴的运动轨迹和运动特征。研究发现,在超声速射流中充满大量的凝结液滴,其粒径在各个垂直位置中的分布不同;混合室端部存在逆向冷凝流动截面,周围不断产生大量凝结液滴。Yang Yan等[13]对比了凝结模型和理想气体模型对蒸汽喷射器的模拟结果。结果表明,理想气体模型夸大了蒸汽喷射器喷嘴中的膨胀特性,高估了膨胀不足情况下流体的马赫数,导致对流体温度的预测出现偏差。
近年来蒸汽喷射器的模型优化与对比研究引起了众多学者的关注,但相关研究中通常将蒸汽喷射器简化为二维轴对称模型,将水蒸气视为理想气体,因而忽略了三维效应和凝结效应对模拟结果的重要影响。本文同时考虑了三维效应和非平衡凝结现象,优化、验证并对比了蒸汽喷射器模型。对比了考虑凝结效应的优化模型与理想气体模型的模拟结果。基于该凝结模型,对比研究雷诺平均方法(RANS)中的6种湍流模型(标准k-ε模型、RNG k-ε模型、标准k-ω模型、SST k-ω模型、过渡SST模型和雷诺应力模型)和大涡模拟方法(LES)对模拟结果的影响。研究成果为蒸汽喷射器内复杂跨音速凝结流动现象与湍流拟序结构之间的内在关系和影响机理研究提供了方法可行性。
在可压缩流动的稳态计算中,湿蒸汽的质量、动量和能量守恒方程分别为:
水蒸气真实气体状态方程采用三阶维里型热力学方程[14]
蒸汽和水的物性方程、饱和蒸汽线和饱和液体线的方程详见文献[2]
假设汽液两相无滑移流动,小液滴包裹的蒸汽空间无限大。因此,Tl=Tvpl=pvvl=vv。而且液滴直径很小,液相密度远大于气相密度。因此,湿蒸汽的密度为:
推广至湿蒸汽的其他物性参数:
基于欧拉坐标系建立针对汽液两相混合物的控制方程。其中输运方程(7)和方程(8)分别控制了液相质量分数和单位体积液滴数[15]
当水蒸气处于过冷状态时,气液两相处于热力学不平衡状态。水蒸气凝结动力学中的核心问题是“成核理论”和“液滴生长理论”。水蒸气凝结涉及的成核是指当水蒸气处于一定的过冷状态下,水蒸气分子在分子作用力的作用下相互碰撞、不断聚集而形成微小分子团聚(凝结核)的过程;液滴生长则是水蒸气以凝结核为核心继续凝结,使液滴粒径继续变大的过程。因此,凝结过程中的液体质量生成率Г是由2部分质量增加构成的。式(9)中,右端第1项表示自发成核产生的液相质量(即临界尺寸液滴的形成),第2项表示成核后液滴增长产生的液相质量[15]
Vd为液滴平均体积:
为液滴平均半径,可由式(11)和式(12)联立推导:
采用学者们广泛使用的简化Young-Gyarmathy液滴生长模型[16]
1)入口边界:初始液相质量分数β0为0,并通过给定进口总压、进口总温来确定水蒸气的进口初始参数。为实现模型验证后的准确分析,蒸汽喷射器的结构、尺寸及计算参数均取自Chen Y. M.等[17]的喷射制冷循环系统实验,如图1表1所示。
2)出口边界:给定出口压力。
3)壁边界:绝热、无滑移、无渗透的固体壁面。
4)湍流边界条件:工作蒸汽和引射蒸汽的湍流黏度比分别为500和100,工作蒸汽和引射蒸汽的湍流强度分别为5%和2%。
建立蒸汽喷射器三维模型的六面体结构化网格。将蒸汽喷射器网格分为引射蒸汽流通的低速流区、喷嘴喉口至扩散器出口轴心区域的激波区以及近壁面的边界层区,如图2所示。低速流区雷诺数(Re)低、各种参数变化梯度小、涡尺度大,所需网格相对稀疏。激波区内存在复杂的超音速流动现象,如气动激波、凝结激波、壅塞和非平衡相变[18]。边界层区存在边界层分离和漩涡[19]。因此,激波区和边界层区的网格需局部加密。
在此基础上,基于有限体积法对上述数学模型进行稳态数值求解。采用k-ω SST湍流模型处理N-S方程[19]。使用密度耦合隐式求解器。变量梯度插值方法采用基于节点的Green-Gauss法。对流项和扩散项分别采用二阶迎风和Roe-FDS格式离散。
根据壁面法线距离,湍流流动划分为内层和外层流动。外层的流动是完全湍流区,内层流体运动受壁面流动条件的影响显著。y+为网格第1层节点距壁面的无量纲距离,它不仅影响壁面附近流场,对整体流动特性的影响也较大,通常存在一个合适的取值范围使模拟结果最佳[20]。若首先加密激波区或低速流区,势必影响近壁网格尺度(即y+),无法实现控制变量。因此,在蒸汽喷射器建模优化中应先确定最佳y+。
边界层的厚度与流体Re呈负相关,为了得到相同范围的y+,不同区域壁面加密程度不同。如图2所示,喷射器壁面附近是低速的引射蒸汽,流体Re最小,边界层最厚,近壁区网格无需大幅度加密即可满足y+需求;喷嘴出口附近的压力低于引射蒸汽压,压差导致接受室内引射蒸汽速度逐渐增大,Re逐渐增大,接受室内壁面边界层逐渐变薄,所以接受室内壁面近壁区网格需要进一步加密才可以满足y+需求;工作蒸汽在喷嘴喉口处达到音速,Re大幅增大,边界层变得极薄,需要大幅度加密喷嘴近壁区的网格以满足y+需求。因此,既要保证y+要求,又要使网格数尽可能少,喷射器壁、接受室内壁和喷嘴区的加密程度应不同。
保持激波区、低速流区网格数不变,逐级加密边界层区网格,直至模拟结果与边界层区网格数量无关。图3所示为当x=80 mm时(混合室收缩段,图2),喷射器三维网格的纵向剖面图,该位置可以同时显示出不同区域的网格疏密程度。
不同y+网格的模拟结果如图4所示。由图4可知,当所有壁面最大y+(y+max)等于2.5时,壁面切应力分布、轴线速度分布和喷射系数(引射蒸汽质量流量与工作蒸汽质量流量之比)均与y+max=0.85时几乎相同。因此,图3(b)所示网格的模拟结果不再随着y+值的减小而改变,即y+max=2.5时近壁区网格疏密程度最佳。在此之前,y+对壁面附近流场、激波区和整体性能均有很大影响。流体受激波压缩,流动参数发生突跃变化:压力、温度和密度突升,速度突降。因此,流体速度突降的次数和波动幅度与激波的数量和强度呈正相关,如图4(b)所示。
随着y+增大,接受室壁面边界层分离位置后移喷射器总长的5.9%,y+过大(y+max=18)无法捕捉到扩散器内的边界层分离(图4(a));捕获的激波强度增大、第1激波区激波个数由4个增至6个,第2激波区激波个数由2个增至3个(图4(b));引射蒸汽质量流量增大23%、工作蒸汽质量流量减小4%、喷射系数提高29%(图4(c))。
图3(b)所示的最佳近壁区网格的基础上,保持低速流区网格数不变,对激波区网格进行逐级粗化、细化,直至模拟结果与激波区网格数量无关,图5所示为当x=120 mm时(混合室收缩段,图2),喷射器三维网格的纵向剖面图,该位置可以显示激波区网格的疏密程度。中尺度网格的模拟结果独立于激波区网格数,如图6所示。此时激波区和边界层区网格的疏密程度均最佳。
图6可知,激波区网格主要影响激波区流场和整体性能。在达到最优网格之前,随激波区网格数增加,得到的激波强度越大,工作蒸汽质量流量不变、引射蒸汽质量流量和喷射系数均减小约6%。
图5(b)所示的最佳激波区和边界层区网格的基础上,逐级粗化、细化低速流区网格,直至模拟结果与网格数量无关,此时喷射器网格最佳。图7所示为当x=80 mm时,网格的纵向剖面图。图8所示为不同尺度的低速流区网格模拟结果,由图8可知,低速流区中尺度网格的模拟结果与细密网格结果一致。
图8所示,低速流区网格数主要影响引射蒸汽质量流量。模拟结果与网格数独立前,随低速流区网格数增多,工作蒸汽质量流量几乎不变,引射蒸汽质量流量和喷射系数均增大约17%,激波特性不变。
离散误差取决于网格大小和间隔。本文使用网格收敛指数(grid convergence index,GCI)方法验证网格离散化精度[20]。GCI方法基于Richardson外推法,根据3种不同尺度网格的计算结果,可以估算出无限细密网格得到的外推解,以确定上述3种不同尺度(细尺度网格1、中尺度网格2、粗尺度网格3)网格的离散化误差。选取轴线静压作为GCI计算结果的分析参数,计算结果如表2所示。根据文献[9]的判断标准,中尺度网格与细密网格模拟结果的相对误差e21、细密网格模拟结果与外推解的相对误差eex t均在可信范围内,验证了网格的离散化精度。因此,图7(b)中尺度网格不仅满足解与网格数的独立性,而且具有很好的离散化精度,还因具有较少的网格数而降低了计算成本和时间成本,为蒸汽喷射器最佳网格。
蒸汽喷射器三维六面体结构化网格如图9所示。优化后的网格数为180万,网格最大纵横比为16、最小正交质量为0.2、最小角度为70°、最低网格质量为0.7。蒸汽喷射器不同壁面的y+分布如图10所示。
将上述非平衡凝结优化模型与理想气体模型的模拟结果与Chen Y. M.等[17]实验结果进行对比,如图11所示(图中字母表示的工况参数见参考文献[17])。与实验值相比,非平衡凝结模型得到的喷射系数(Ermax)和临界出口压力的平均相对误差分别为4.9%和13.4%,具有很好的一致性。此外,非平衡凝结模型的模拟结果比理想气体模型的模拟结果更接近实验值。与理想气体模型相比,使用非平衡凝结模型可使Ermax与实验值的平均相对误差减小72.0%、最大相对误差减小45.6%,与实验值的平均相对误差减小29.9%、最大相对误差减小21.5%。这验证了本文非平衡凝结优化模型的可信性和优越性。
基于上述非平衡凝结模型,对比分析蒸汽喷射器内可压缩湍流的2种处理方法的模拟结果,即大涡模拟(LES)方法和雷诺平均方法(RANS)。图12统计了7种不同工况(表1)下,分别使用雷诺平均方法中6种湍流模型(k-ε Standard、k-ε RNG、k-ω Standard、k-ω SST、Transition SST、RSM)和大涡模拟方法得到的喷射系数与实验值的相对误差。k-ω Standard模型总是高估喷射系数,k-ε Standard、k-ε RNG、Transition SST、RSM模型总是低估喷射系数。k-ω SST和大涡模拟方法的模拟结果最接近实验值,喷射系数相对误差小于±11%,如图12中灰色区域所示。
图13对比了相同工况下(pm=11.9 kPa,ps=1.3 kPa,pd=1.4 kPa),大涡模拟方法和雷诺平均方法中的k-ω SST湍流模型、二维轴对称和三维RANS模型得到的蒸汽喷射器流场(液体质量分数云图)。湍流脉动的各向异性导致大涡模拟方法需应用于三维模型[21]。大涡模拟方法得到了不同时间下的工作蒸汽和引射蒸汽混合过程:混合室内射流区和扩散器内的2列激波链分别逐渐形成,强度先增大后减小,激波链位置向上游移动;混合室内的冷凝液质量分数先增大后减小,扩散器内的冷凝液质量分数逐渐减小。在最终稳定状态时,与三维RANS中的k-ω SST湍流模型模拟结果相比,LES得到的液体质量分数更低,尤其在扩散器区域。对比二维模型和三维模型的模拟结果可知,二维轴对称模型流场中的冷凝质量分数(β)明显小于三维轴对称和三维非轴对称模型,这是由于三维效应消耗了混合过程中的更多能量。应用耦合非平衡凝结模型的大涡模拟方法对蒸汽喷射器的数值模拟,为后续工作中进一步深入研究蒸汽喷射器内复杂跨音速凝结流动现象与湍流拟序结构之间内在关系和影响机理提供了可行性。
本文同时考虑三维和非平衡凝结效应,优化、验证并对比了适用于喷射式制冷系统的低压力工况下的蒸汽喷射器数值模型。优化后的蒸汽喷射器模型可以以最低计算成本可靠预测喷射器性能并捕捉其内部非平衡凝结、激波等复杂流动现象。得到如下结论:
1)蒸汽喷射器非平衡凝结模型得到的喷射系数和临界出口压力与实验值的平均相对误差分别为4.9%和13.4%。与理想气体模型相比,本文的凝结模型可使喷射系数和临界出口压力的平均相对误差分别降低72.0%和29.9%。
2)在蒸汽喷射器建模优化中,第1层网格节点距壁面的无量纲距离y+、对壁面附近流场、激波特性和整体性能均有很大影响。在满足模拟结果与y+独立之前,y+越大,捕获的激波强度越大、个数越多,引射蒸汽质量流量越大、工作蒸汽质量流量越小、喷射系数越大。y+过大时,无法捕捉到扩散器内的边界层分离。最佳近壁区网格的最大y+为2.5。未达到最优网格前,加密激波区网格,捕获的激波强度越大,工作蒸汽质量流量几乎不变、引射蒸汽质量流量和喷射系数均越小;加密低速流区网格,引射蒸汽质量流量越大,喷射系数越大。
3)耦合非平衡凝结模型的大涡模拟方法和雷诺平均方法中k-ω SST湍流模型对蒸汽喷射器的模拟结果吻合实验值,喷射系数的最大相对误差均小于11%。前者得到的液体质量分数更低,且该方法弥补了蒸汽喷射器内复杂跨音速凝结流动现象与湍流拟序结构之间内在关系研究的方法欠缺。
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2025年第46卷第4期
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doi: 10.12465/j.issn.0253-4339.2025.04.131
  • 接收时间:2024-02-20
  • 首发时间:2026-03-13
  • 出版时间:2025-08-16
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  • 收稿日期:2024-02-20
  • 修回日期:2024-03-18
  • 录用日期:2024-05-07
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    1大连交通大学詹天佑学院 大连 116028
    2冰山冷热科技股份有限公司 大连 116630

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李熠桥,女,讲师,大连交通大学詹天佑学院,冰山冷热科技股份有限公司,17824829321,E-mail:。研究方向:多相流传热传质。
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2种不同金属材料的力学参数

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Percentage of
total species (%)

Genus
种数
Number of
species
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Percentage of total
species (%)
鹅膏菌科Amanitaceae 2 11 5.26 鹅膏菌属 Amanita 10 4.78
小菇科 Mycenaceae 2 12 5.74 丝盖伞属 Inocybe 5 2.39
多孔菌科 Polyporaceae 8 14 6.70 蜡蘑属 Laccaria 5 2.39
红菇科 Russulaceae 3 23 11.00 小皮伞属 Marasmius 6 2.87
小菇属 Mycena 11 5.26
光柄菇属 Pluteus 5 2.39
红菇属 Russula 17 8.13
栓菌属 Trametes 5 2.39
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