Article(id=1222513212059280213, tenantId=1146029695717560320, journalId=1210938733613449225, issueId=1222513210519970621, articleNumber=null, orderNo=null, doi=10.19666/j.rlfd.202302016, pmid=null, cstr=null, oa=null, hot=null, price=null, onlineType=0, articleFormat=0, articleType=null, articleTypeStr=null, receivedDate=1675440000000, receivedDateStr=2023-02-04, revisedDate=null, revisedDateStr=null, acceptedDate=null, acceptedDateStr=null, onlineDate=1769399462952, onlineDateStr=2026-01-26, pubDate=1700841600000, pubDateStr=2023-11-25, doiRegisterDate=null, doiRegisterDateStr=null, onlineIssueDate=1769399462952, onlineIssueDateStr=2026-01-26, onlineJustAcceptDate=null, onlineJustAcceptDateStr=null, onlineFirstDate=null, onlineFirstDateStr=null, sourceXml=null, magXml=null, createTime=1769399462952, creator=13701087609, updateTime=1769399462952, updator=13701087609, issue=Issue{id=1222513210519970621, tenantId=1146029695717560320, journalId=1210938733613449225, year='2023', volume='52', issue='11', pageStart='1', pageEnd='198', issueExtLink='null', onlineDate='null', pubDate='null', beforeIssueId=null, nextIssueId=null, price=null, status=1, issueComplete=1, articleOrder=1, issueType=-1, specialIssue=null, createTime=1769399462585, creator=13701087609, updateTime=1769405983425, updator=13701087609, preIssue=null, nextIssue=null, ext={EN=IssueExt(id=1222540560984957089, tenantId=1146029695717560320, journalId=1210938733613449225, issueId=1222513210519970621, language=EN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=), CN=IssueExt(id=1222540560984957090, tenantId=1146029695717560320, journalId=1210938733613449225, issueId=1222513210519970621, language=CN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=)}, issueFiles=null}, startPage=10, endPage=19, ext={EN=ArticleExt(id=1222513212378047329, articleId=1222513212059280213, tenantId=1146029695717560320, journalId=1210938733613449225, language=EN, title=Coupling optimization of supercritical carbon dioxide centrifugal impeller, columnId=1222513211350442816, journalTitle=Thermal Power Generation, columnName=Special topic on supercritical carbon dioxide cycle power generation technology, runingTitle=null, highlight=null, articleAbstract=

Self-recirculation casing treatment can significantly improve the aerodynamic performance of the supercritical carbon dioxide centrifugal impeller in small flow rate region, but the improvement is not obvious near the large flow rate region. Therefore, the coupling effect between the self-recirculation casing treatment and the key parameter of the impeller is considered, and the coupling optimization of the casing treatment geometry and the impeller blade sweep angle is carried out to achieve a comprehensive improvement of the impeller performance. After the coupling optimization, the efficiency of the impeller is increased by 3.51%, 2.60% and 4.43% respectively under the large flow rate condition, the design condition and the small flow rate condition. The mechanisms of the coupling optimization for stability and efficiency enhancements are as follows. Under the large flow rate condition, the flow incidence angle of impeller is improved, the subcritical zone inside the impeller is reduced, then the condensation is suppressed and the flow capacity of the impeller is improved. Under the design condition, the recirculation flow of casing treatment is increased, more low-energy fluid near the shroud tip is removed, and the flow field structure downstream of the impeller is improved. Under the small flow rate condition, the internal blockage of the impeller is effectively reduced, the flow stability of the impeller is enhanced, and the mixing loss caused by the recirculation flow is improved, so the impeller efficiency is improved.

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自循环机匣处理能够显著提升超临界二氧化碳离心叶轮小流量区域的气动性能,但对大流量工况附近的性能提升不明显。为此,考虑自循环机匣与叶轮关键参数的耦合效应,对机匣几何和叶轮叶片掠角实施耦合优化,实现了叶轮性能的全面提升。耦合优化后叶轮在大流量工况、设计工况及小流量工况下的效率分别提升了3.51%、2.60%、4.43%。耦合优化的扩稳增效机理为:在大流量工况下改善了叶片前缘进口攻角,减小了叶轮内部亚临界区,抑制了冷凝的同时改善了叶轮内部流通能力;设计工况下机匣的抽吸量增大,叶顶附近更多低能流体被移除,改善了叶轮下游流场结构;小流量工况下显著减小了叶轮内部堵塞面积,叶轮流动稳定性增强,同时改善了机匣回流造成的掺混损失,叶轮效率提升。

, correspAuthors=null, authorNote=null, correspAuthorsNote=
李孝检(1991),男,博士,助理研究员,硕士生导师,主要研究方向为叶轮机械流动稳定性,
, copyrightStatement=null, copyrightOwner=null, extLink=null, articleAbsUrl=null, sourceXml=YbKRSw8wnZnBIZKIXo5BPQ==, magXml=p6qCB/5dg15ll3Z3w1hFMw==, pdfUrl=null, pdf=G9txdB4uszsP1VUyG+x8TQ==, pdfFileSize=2040266, pdfExtLink=null, richHtmlUrl=null, mobilePdfUrl=null, reviewReport=null, pdfFirstPage=null, abstractGraph=vuX2I4rCcJ5dfJRK5Y8mLA==, abstractGraphContent=null, abstractVideo=null, citation=null, cebUrl=null, magXmlContent=qBFWxjk+WSu06LDHt6fngg==, mapNumber=null, authorCompany=null, fund=null, authors=

鲁雪(1998),女,硕士研究生,主要研究方向为离心叶轮设计与优化,

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鲁雪(1998),女,硕士研究生,主要研究方向为离心叶轮设计与优化,

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Geometry parameters of Sandia compressor

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项目数值项目数值
进口轮毂半径/mm2.54进口半径/mm18.98
进口轮缘半径/mm9.37出口半径/mm26.00
出口半径/mm18.68进口安装角/(°)42.44
叶片进口安装角/(°)37.13出口安装角/(°)71.50
叶片出口安装角/(°)–50扩压器叶片数17
叶片数6/6
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Sandia压缩机几何参数

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项目数值项目数值
进口轮毂半径/mm2.54进口半径/mm18.98
进口轮缘半径/mm9.37出口半径/mm26.00
出口半径/mm18.68进口安装角/(°)42.44
叶片进口安装角/(°)37.13出口安装角/(°)71.50
叶片出口安装角/(°)–50扩压器叶片数17
叶片数6/6
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Errors and calculation time of CO2 RGP tables with different resolutions

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分辨率最大相对误差/%计算时间/h
RGP1100×1007.863.00
RGP2300×3004.334.50
RGP3500×5001.455.25
RGP4800×8000.9511.25
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CO2不同分辨率RGP表的误差及计算时间

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分辨率最大相对误差/%计算时间/h
RGP1100×1007.863.00
RGP2300×3004.334.50
RGP3500×5001.455.25
RGP4800×8000.9511.25
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Preliminary design results of the baseline impeller

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设计参数数值几何参数数值
进口总温Tt1/K310进口轮盖直径D1s/mm16.57
进口总压pt1/MPa7.5进口轮毂直径D1h/mm1.57
设计流量m/(kg·s–1)2出口直径D2/mm41.16
设计压比ε1.80出口宽度b2/mm1.83
设计效率ηs0.85进口轮盖相对气流角β1s/(°)60
设计转速n/(r·min–1)75 000出口叶片安装角β2A/(°)–10
流量系数φ2r0.16叶顶间隙/mm0.20
比焓比σ1.06
进口马赫数Mc10.185
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基准叶轮初步设计结果

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设计参数数值几何参数数值
进口总温Tt1/K310进口轮盖直径D1s/mm16.57
进口总压pt1/MPa7.5进口轮毂直径D1h/mm1.57
设计流量m/(kg·s–1)2出口直径D2/mm41.16
设计压比ε1.80出口宽度b2/mm1.83
设计效率ηs0.85进口轮盖相对气流角β1s/(°)60
设计转速n/(r·min–1)75 000出口叶片安装角β2A/(°)–10
流量系数φ2r0.16叶顶间隙/mm0.20
比焓比σ1.06
进口马赫数Mc10.185
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Baseline values and variable ranges of casing treatment design variables

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几何参数下限基准值上限
上游抽吸口宽度X10.51.02.5
机匣高度X23.03.74.5
机匣长度X36.37.010.5
空腔高度X40.81.01.2
下游抽吸口宽度X50.51.01.5
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机匣处理设计变量基准值及变化范围

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几何参数下限基准值上限
上游抽吸口宽度X10.51.02.5
机匣高度X23.03.74.5
机匣长度X36.37.010.5
空腔高度X40.81.01.2
下游抽吸口宽度X50.51.01.5
), ArticleFig(id=1241137068198392263, tenantId=1146029695717560320, journalId=1210938733613449225, articleId=1222513212059280213, language=EN, label=Tab.5, caption=

Baseline value and variable range of the leading-edge sweep angle

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几何参数下限基准值上限
掠角X6–5020
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前缘掠角基准值及变量范围

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几何参数下限基准值上限
掠角X6–5020
), ArticleFig(id=1241137068429078995, tenantId=1146029695717560320, journalId=1210938733613449225, articleId=1222513212059280213, language=EN, label=Tab.6, caption=

Comparison of design variables before and after coupling optimization

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几何参数优化前优化后
上游抽吸口宽度X1/mm1.01.9
机匣高度X2/mm3.73.6
机匣长度X3/mm7.08.2
空腔高度X4/mm1.00.9
下游抽吸口宽度X5/mm1.00.6
掠角X6/(°)019.6
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耦合优化前后设计变量对比

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几何参数优化前优化后
上游抽吸口宽度X1/mm1.01.9
机匣高度X2/mm3.73.6
机匣长度X3/mm7.08.2
空腔高度X4/mm1.00.9
下游抽吸口宽度X5/mm1.00.6
掠角X6/(°)019.6
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超临界二氧化碳离心叶轮耦合优化设计
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鲁雪 1 , 李孝检 1 , 刘彬 2
热力发电 | 超临界二氧化碳循环发电技术专题 2023,52(11): 10-19
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热力发电 | 超临界二氧化碳循环发电技术专题 2023, 52(11): 10-19
超临界二氧化碳离心叶轮耦合优化设计
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鲁雪1 , 李孝检1 , 刘彬2
作者信息
  • 1.天津大学机械工程学院,天津 300350
  • 2.中国航发湖南动力机械研究所,湖南 株洲 412002
  • 鲁雪(1998),女,硕士研究生,主要研究方向为离心叶轮设计与优化,

通讯作者:

李孝检(1991),男,博士,助理研究员,硕士生导师,主要研究方向为叶轮机械流动稳定性,
Coupling optimization of supercritical carbon dioxide centrifugal impeller
Xue LU1 , Xiaojian LI1 , Bin LIU2
Affiliations
  • 1.School of Mechanical Engineering, Tianjin University, Tianjin 300350, China
  • 2.Hunan Aviation Powerplant Research Institute, Aero Engine Corporation of China, Zhuzhou 412002, China
出版时间: 2023-11-25 doi: 10.19666/j.rlfd.202302016
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自循环机匣处理能够显著提升超临界二氧化碳离心叶轮小流量区域的气动性能,但对大流量工况附近的性能提升不明显。为此,考虑自循环机匣与叶轮关键参数的耦合效应,对机匣几何和叶轮叶片掠角实施耦合优化,实现了叶轮性能的全面提升。耦合优化后叶轮在大流量工况、设计工况及小流量工况下的效率分别提升了3.51%、2.60%、4.43%。耦合优化的扩稳增效机理为:在大流量工况下改善了叶片前缘进口攻角,减小了叶轮内部亚临界区,抑制了冷凝的同时改善了叶轮内部流通能力;设计工况下机匣的抽吸量增大,叶顶附近更多低能流体被移除,改善了叶轮下游流场结构;小流量工况下显著减小了叶轮内部堵塞面积,叶轮流动稳定性增强,同时改善了机匣回流造成的掺混损失,叶轮效率提升。

离心叶轮  /  超临界二氧化碳  /  自循环机匣处理  /  耦合优化

Self-recirculation casing treatment can significantly improve the aerodynamic performance of the supercritical carbon dioxide centrifugal impeller in small flow rate region, but the improvement is not obvious near the large flow rate region. Therefore, the coupling effect between the self-recirculation casing treatment and the key parameter of the impeller is considered, and the coupling optimization of the casing treatment geometry and the impeller blade sweep angle is carried out to achieve a comprehensive improvement of the impeller performance. After the coupling optimization, the efficiency of the impeller is increased by 3.51%, 2.60% and 4.43% respectively under the large flow rate condition, the design condition and the small flow rate condition. The mechanisms of the coupling optimization for stability and efficiency enhancements are as follows. Under the large flow rate condition, the flow incidence angle of impeller is improved, the subcritical zone inside the impeller is reduced, then the condensation is suppressed and the flow capacity of the impeller is improved. Under the design condition, the recirculation flow of casing treatment is increased, more low-energy fluid near the shroud tip is removed, and the flow field structure downstream of the impeller is improved. Under the small flow rate condition, the internal blockage of the impeller is effectively reduced, the flow stability of the impeller is enhanced, and the mixing loss caused by the recirculation flow is improved, so the impeller efficiency is improved.

centrifugal impeller  /  supercritical carbon dioxide  /  self-recirculation casing treatment  /  coupling optimization
鲁雪, 李孝检, 刘彬. 超临界二氧化碳离心叶轮耦合优化设计. 热力发电, 2023 , 52 (11) : 10 -19 . DOI: 10.19666/j.rlfd.202302016
Xue LU, Xiaojian LI, Bin LIU. Coupling optimization of supercritical carbon dioxide centrifugal impeller[J]. Thermal Power Generation, 2023 , 52 (11) : 10 -19 . DOI: 10.19666/j.rlfd.202302016
临界二氧化碳(supercritical carbon dioxide,S-CO2)布雷顿循环作为一种先进的功热转换技术[1-2],近年来受到广泛关注。S-CO2压缩机作为布雷顿循环的关键部件,其气动特性的优劣很大程度上决定了整个循环的性能[3-4]。高效率和宽稳定工况范围的压缩机有利于提高布雷顿循环的输出功率[5]
国内外学者在提高S-CO2压缩机气动性能方面开展了大量的设计与分析研究。Du等人[6]基于损失模型开发了S-CO2压缩机性能评估的一维设计方法,并与遗传算法相结合实施了S-CO2压缩机的优化。Li等人[7]基于叶轮最大流通能力和冷凝设计原则,提出了一种新的S-CO2压缩机初步设计方法,较好地平衡了循环效率与压缩机几何紧凑性及进口冷凝问题。Lettieri等人[8]对比了S-CO2离心压缩机匹配有叶和无叶扩压器的气动性能,发现有叶扩压器能使等熵效率提高3.5%。Cho等人[9]基于KAIST-TMD设计工具[10-11]对S-CO2离心叶轮的掠角进行参数分析,获得了使叶轮性能最优的最佳掠角。赵航等[12]通过削弱叶片通道内的二次流及通道涡,提高了S-CO2叶轮的效率。Pelton等人[13-14]借鉴空气压缩机的扩稳方法,在S-CO2压缩机的基础上加入自循环机匣处理,近失速工况下机匣处理能将叶顶附近的低能流体抽走(约占总流量的10%)并回流到叶轮入口,使得压缩机的稳定性增强。
综上所述,目前对于S-CO2压缩机的研究主要集中在叶轮/扩压器初步设计和气动优化,关于机匣处理对S-CO2离心压缩机扩稳增效的影响研究较少,机匣处理与叶轮设计参数的耦合效应还不明确。因此,本文主要探究机匣处理与叶轮关键参数耦合优化对S-CO2压缩机稳定性与效率的提升潜力,挖掘性能提升背后的流动机理,为S-CO2离心压缩机扩稳设计提供参考。
本文首先利用Sandia离心压缩机实验结果[15]确立S-CO2压缩机数值模拟方法,之后以某小流量系数S-CO2离心叶轮为研究对象,探究机匣处理与叶轮掠角耦合优化对压缩机稳定性与效率的提升潜力,最后分析耦合优化扩稳增效的机理。
以S-CO2为流动介质的数值模拟方法是研究S-CO2叶轮耦合优化的基础。本节利用实验数据较完备的Sandia S-CO2离心压缩机来确立可靠的数值模拟方法。由文献[15-16]获得Sandia压缩机几何参数见表1;根据这些参数对Sandia压缩机几何进行重构,具体如图1所示。
对Sandia压缩机单通道实施数值模拟。流动控制方程为雷诺平均Navier-Stokes方程。针对S-CO2压缩机湍流的模拟,目前较常用的是k-ε SST或k-ε模型[17],考虑到k-ε SST模型对无量纲壁面高度y+的要求较高,使得数值模拟的稳定性较差[18],本文选用稳定性更强的k-ε scalable wall function模型。计算域入口边界条件为总温/总压(306.4 K/7.89 MPa),出口边界条件为质量流量,固壁面满足绝热无滑移无穿透条件,动静交界面选择周向守恒法(质量、动量、能量严格守恒)。数值计算收敛指标为:残差小于10–6以及进出口质量流量恒定不变且相对误差不超过0.5%。
首先对叶轮单通道流体域进行网格划分,在叶片表面附近采用O型网格,其他区域采用H型网格,具体如图2所示。固壁面第1层网格高度为0.002 mm,对应的y+约为30。经网格无关性验证,最终确定单通道网格总数为290万。
由于S-CO2的物性与理想气体相差较大,因此在数值模拟中嵌入CO2实际气体物性表(real gas property,RGP)。该表由NIST-REFPROP数据库生成,覆盖了Sandia压缩机工作热力区间(T=230~450 K,p=3~25 MPa)。对于S-CO2压缩机数值模拟,RGP表分辨率越高,则数值模拟精度越高,但计算量会急剧增大且稳定性显著下降。为了达到计算精度与效率/稳定性的平衡,需要对RGP表的分辨率进行研究。分别生成4种分辨率的RGP表(表2),选用上述单通道网格实施数值模拟。选取Sandia压缩机设计工况下90%叶高进行精度对比:导出该叶高所有网格点的温度、压力和密度;以温度、压力为已知量,查询REFPROP数据库,获得对应的密度;计算所有网格点上2种密度的最大相对误差。表2给出了不同RGP的最大相对误差及数值模拟耗时。
表2可知,RGP4的最大相对误差最小,但其耗时最长,RGP3的最大相对误差虽略有增加,但计算时长减半。为较好地平衡计算精度和计算效率,选用RGP3进行后续计算。
图3给出了Sandia压缩机55 000 r/min转速下数值模拟结果与实验值[15,19]的对比。由于数值模拟的重构几何与真实几何存在微小差异,且数值模拟不考虑转静子间隙及轴承/机壳密封所产生的漏气损失、实验测量设备对流场的干扰等因素,使得数值模拟与实验值存在一定偏差,但二者的变化趋势是一致的,可以认为数值模拟方法是可靠的。
研究对象为课题组自主设计的小流量系数S-CO2离心叶轮(基准叶轮),其是基于平均流线方法进行初步设计的,设计流程如图4所示,初步设计结果见表3,三维模型如图5所示。数值模拟的网格拓扑与Sandia压缩机保持一致,固壁面第1层网格高度为0.002 mm,对应的y+约为30。
对基准叶轮进行数值模拟,数值方法采用第1节已确立的方法(包括控制方程、湍流模型、边界条件、RGP表格选取等)。首先对基准叶轮进行网格独立性验证,具体如图6所示。由图6可知,当网格总数增加到233万时等熵效率和总压比变化均小于1%,即认为网格对计算结果影响很小,因此采用233万网格进行后续研究,最终得到基准叶轮性能曲线如图7所示。由图7可知,等熵效率在设计流量下达到峰值,与设计预期一致。图8给出了基准叶轮子午平面的压力和温度分布。由图8可知,压力和温度在叶片通道内稳定上升,表明基准叶轮的三维设计是合理的。
为拓宽基准叶轮的稳定工况范围,在原叶轮基础上增加自循环机匣处理(self-recirculation casing treatment,SRCT)。该SRCT仿照空气离心叶轮机匣处理[20]进行设计,自循环机匣处理示意如图9所示。SRCT由上、下游抽吸口以及环形空腔组成,上游抽吸口连接叶轮入口静子段,下游抽吸口连接叶轮转子轮盖处。基准叶轮与SRCT叶轮特性曲线的对比如图10所示。
图10可知,引入SRCT后,叶轮效率除了大流量工况附近外均有较大幅值提升,其中设计点效率提高1.66%,小流量工况提高3.75%。由于单通道数值模拟方法很难确定S-CO2叶轮的失速点(周向周期性假设已不成立)及堵塞点(冷凝风险增大使得数值模拟不稳定而难以收敛),因此无法计算出具体的稳定工况范围量化指标,但是在引入机匣处理后叶轮在同一流量下(小流量工况)的效率和压比均有所提升,间接说明机匣处理实现了扩稳。
为进一步提升SRCT的性能,对机匣处理几何进行优化设计。图9定义了机匣的5个相互独立的设计变量:上/下游抽吸口宽度(X1X5)、机匣高度X2、机匣宽度X3及空腔高度X4。考虑到叶轮的几何约束,设计变量的变化上下限见表4
采用课题组已有的优化工具开展机匣全局多目标优化[21-22],优化目标为最大化小流量工况、设计工况、大流量工况的等熵效率。
图11对比了SRCT优化前后的效率曲线。由图11可知,最优的SRCT方案在设计工况及小流量工况下对叶轮效率有所提升,但仍不能改善大流量工况附近的性能,因此有必要考虑增大优化的设计空间,以全面提升S-CO2叶轮性能。
文献[23]表明,通过调整叶片前缘掠角,能够改善离心叶轮(介质为空气)大流量工况的性能。因此,在S-CO2基准叶轮基础上,单独改变叶片前缘掠角,获得不同掠角下的效率曲线如图12所示,掠角正/负分别表示前/后掠。由图12可知,掠角对S-CO2叶轮大流量区域气动特性影响明显,前掠可显著提升大流量工况点效率,但掠角对小流量区域影响很小。因此,考虑将前缘掠角作为一个优化设计变量,其变化范围见表5
综合图11图12可知,机匣处理和叶片前缘掠角具有很强的互补性,实施机匣处理/前缘掠角耦合优化将很可能全面提升叶轮的气动性能。因此,将表4表5合并,实施机匣处理/前缘掠角耦合优化,耦合优化流程如图13所示。
表6为叶轮耦合优化前后设计变量的对比,图14给出了耦合优化后叶轮性能曲线对比。
图14可知,耦合优化实现了叶轮全工况范围内性能的明显提升,这是单独机匣优化无法达到的。相较于基准叶轮,耦合优化在大流量工况、设计工况以及小流量工况下效率分别提高了3.51%、2.60%、4.43%,叶轮压比也有所提升;大流量和小流量工况效率的大幅提升表明耦合优化也实现了扩稳。对比最优SRCT叶轮和耦合优化叶轮可知,掠角的改变使得叶轮大流量工况性能明显提升。由于最优SRCT叶轮在小流量工况下与耦合优化性能曲线基本重合,在大流量工况下性能曲线与SRCT叶轮接近,因此在后续机理分析中将不再体现最优SRCT叶轮。接下来将通过对比基准叶轮、SRCT叶轮及耦合优化叶轮来进行扩稳增效机理分析。
大流量工况(2.88 kg/s)下,基准叶轮、SRCT叶轮及耦合优化叶轮的对比分别如图15图16图17所示。其中,图15为叶轮90%叶高相对马赫数分布云图,图16为叶片前缘速度矢量图,图17为耦合优化前后机匣回流量分布。
图15可以看出,加入机匣处理后(图15b)、图15c)),叶轮在叶片前缘A区以及吸力面侧B区的相对马赫数均有所减弱,这表明叶片前缘以及吸力面侧的局部加速效应减弱。
对于基准叶轮,叶片前缘驻点更靠近吸力面侧,产生负攻角(图16a)),导致叶片前缘压力面流动加速明显,A区相对马赫数较大。
对于SRCT叶轮,前缘马赫数的减小来源于机匣对进口负攻角的改善(图16b)),由机匣回流量分布(图17)可知,SRCT叶轮在大流量工况下将一部分流体直接通过机匣空腔带入到叶轮内部,减小了叶轮进口轴向速度,从而改善了进口攻角,A区马赫数减弱;同时未经叶轮旋转增压的流体(无周向速度)通过下游抽吸口汇入主流并掺混后,减弱了轮盖附近主流的相对速度,使得B区马赫数减小。
而对于耦合优化叶轮,其回流量相对于SRCT叶轮是减少的,因此耦合优化叶轮的攻角改善主要来自于掠角的改变。由表6可见,优化后叶轮掠角由0°增加至前掠19.6°,前掠将增大叶片进口安装角(与周向的夹角),进而增大叶轮气动喉口面积,使得叶轮流通能力增强[24]。因此同一流量下,进口负攻角将减小(图16c)),进口冲击减弱,局部加速减小;同时气动喉口面积的增加使得喉口附近流速降低,吸力面的流动加速减弱,B区马赫数降低。
图18对比了叶轮通道内亚临界区的分布(温度压力均低于临界点)。
图18可知:基准叶轮的叶片前缘局部加速(A区)与吸力面的流动加速(B区)所造成的亚临界区均较大,在叶轮喉口处甚至已连为一体,这不仅增加了冷凝风险也严重堵塞了叶轮通道;加入机匣后(图18b)),亚临界区有所减小,2类加速所造成的亚临界区相互脱离;实施耦合优化后(图18c)),由于2类加速均大幅减小,亚临界区被显著抑制,使得叶轮流通能力增强,内部流场改善,效率和压比均明显提升。
图19对比了设计工况(2.0 kg/s)下3种叶轮的等熵效率沿流向的分布。从图19可以看出:在流向位置1.0~1.3处,耦合优化叶轮的效率略低于基准叶轮和SRCT叶轮,这是由于耦合优化叶轮在设计点处回流量较大(图17),使得叶片前缘掺混损失较大,效率有所下降;但随着机匣抽吸叶顶低能流体,抽吸口下游的流场得到改善,使得在流向位置1.3~3.0处耦合优化叶轮始终具有最高的效率。为了确认这点,图20对比了不同流向位置熵分布。由图20可知,耦合优化后转子通道下游熵增损失有所减少,叶片尾缘处的尾迹/射流损失也明显减弱。因此耦合优化叶轮中下游通道流动明显改善,设计工况效率提升。
图21对比了小流量工况(0.99 kg/s)下3种叶轮在90%叶高截面处的堵塞面积(负轴向速度区域)。
图21可以发现:基准叶轮的堵塞面积几乎占据了整个叶片上游区域,这是由于叶轮内部间隙泄漏流在高背压作用下向叶片前缘运动,造成了大面积的堵塞区域,使得叶轮流动稳定性下降,效率降低;加入机匣后(图21b)),由于机匣对叶顶附近的低能流体进行抽吸,使得SRCT叶轮的堵塞面积在下游抽吸口处大幅减少,耦合优化叶轮的堵塞面积在下游抽吸口处基本消失,叶片前缘附近的通道堵塞显著改善,使得叶轮流动稳定性增强。
图22为3种叶轮的子午面静熵分布云图。从图22可以看出:SRCT叶轮相较于基准叶轮,在叶片前缘叶顶处具有较大熵增损失,这主要来源于机匣回流流体与主流的掺混损失;耦合优化后熵增损失大幅减小,这是由于耦合优化后叶轮的上游抽吸口宽度大幅增加(由1.0 mm增加至1.9 mm),回流流体速度降低,使得回流流体汇入主流的冲击和掺混损失减弱。
SRCT能够显著提升S-CO2离心叶轮小流量区域的气动性能,但对大流量区域特别是大流量工况附近提升不明显。本研究进一步对机匣几何和叶轮叶片掠角实施耦合优化,实现了叶轮性能的全面提升,主要结论如下。
1)对S-CO2叶轮初步设计了SRCT并进行优化,优化后的方案在设计工况及小流量工况效率均有明显提升,但大流量工况效率几乎不变。为了全面提升叶轮性能,对机匣几何及叶片前缘掠角进行耦合优化。结果表明,相较于基准叶轮,耦合优化叶轮在大流量工况、设计工况以及小流量工况下效率分别提升了3.51%、2.60%、4.43%,即实现了叶轮性能的全面提升,这是仅机匣优化无法达到的。
2)S-CO2叶轮耦合优化扩稳增效的机理是:在大流量工况下,SRCT叶轮有效改善进口攻角,缓解了吸力面的流动加速,叶轮内部冷凝风险降低;耦合优化叶轮由于叶片前缘掠角的改变,改善进口攻角的同时增大了叶轮气动喉口面积,缓解了进口堵塞,叶轮流通能力增强,效率和压比均明显提升。
3)对于设计工况,耦合优化叶轮的抽吸量增加,叶顶附近更多的低能流体被抽走,改善了叶轮下游流场结构。在小流量工况下,基准叶轮的堵塞面积已占据整个叶片通道,加剧了叶轮的流动不稳定性,加入机匣后缓解了叶轮堵塞效应,耦合优化后前缘堵塞效应几乎消除,叶轮的流动稳定性增强。同时,相较于SRCT叶轮,耦合优化叶轮的上游抽吸口宽度增加,使得回流流体汇入主流造成的冲击和掺混损失明显减弱,叶轮效率提高。
  • 国家自然科学基金项目(12102298)
  • 中国博士后科学基金(2021M702443)
  • 内燃机燃烧学国家重点实验室开放课题(K2022-09)
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2023年第52卷第11期
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doi: 10.19666/j.rlfd.202302016
  • 接收时间:2023-02-04
  • 首发时间:2026-01-26
  • 出版时间:2023-11-25
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  • 收稿日期:2023-02-04
基金
National Natural Science Foundation of China(12102298)
国家自然科学基金项目(12102298)
China Postdoctoral Science Foundation(2021M702443)
中国博士后科学基金(2021M702443)
State Key Laboratory of Engines (Tianjin University)(K2022-09)
内燃机燃烧学国家重点实验室开放课题(K2022-09)
作者信息
    1.天津大学机械工程学院,天津 300350
    2.中国航发湖南动力机械研究所,湖南 株洲 412002

通讯作者:

李孝检(1991),男,博士,助理研究员,硕士生导师,主要研究方向为叶轮机械流动稳定性,
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