涡轮泵表面等效砂粗糙度的数值确定及其对泵特性的影响

IF 1.3 Q2 ENGINEERING, AEROSPACE International Journal of Turbomachinery, Propulsion and Power Pub Date : 2023-02-07 DOI:10.3390/ijtpp8010005
B. Torner, Deborah Duong, F. Wurm
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引用次数: 2

摘要

在技术系统(如涡轮机)中,正确计算粗糙表面上的流动是正确模拟其性能数据的一个重要问题。一旦在这些机器中充分计算出粗糙表面上的流动,模拟就变得更加可信,可以取代实验原型。粗糙度建模方法通常在求解器中实现,以说明流动模拟中的粗糙度影响。在这些方法中,必须将等效砂粗糙度ks定义为粗糙表面的特征参数。然而,很难确定表面粗糙度的相应ks值。在此背景下,本文提出了一种新的、时效性强的数值方法,即离散孔隙率法(DPM),该方法可用于确定粗糙表面的ks值。应用该方法,对涡轮泵蜗壳的不规则分布铸铁表面进行了通道流动模拟。在确定了完全粗糙的状态后,确定了等效砂粗糙度,并发现与文献数据中的ks值相匹配。随后,在具有粗糙壁的涡轮泵模拟中使用了铸铁的既定ks值。通过实验验证了该泵的性能数据,实验结果与模拟结果吻合较好。
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Numerical Determination of the Equivalent Sand Roughness of a Turbopump’s Surface and Its Roughness Influence on the Pump Characteristics
The correct computation of flows over rough surfaces in technical systems, such as in turbomachines, is a significant issue for proper simulations of their performance data. Once the flow over rough surfaces is adequately computed in these machines, simulations become more trustworthy and can replace experimental prototyping. Roughness modelling approaches are often implemented in a solver to account for roughness effects in flow simulations. In these approaches, the equivalent sand roughness ks must be defined as a characteristic parameter of the rough surface. However, it is difficult to determine the corresponding ks-value for a surface roughness. In this context, this paper shows a novel and time-efficient numerical method, the discrete porosity method (DPM), which can be used to determine the ks-value of a rough surface. Applying this method, channel flow simulations were performed with an irregularly distributed cast iron surface from a turbopumps volute. After identifying the fully rough regime, the equivalent sand roughness was determined and a match with ks-values from literature data was found. Subsequently, the established ks-value for cast iron was used in a turbopump simulation with rough walls. The performance data of the pump were validated by experiments and a good agreement between the experimental and simulated performance data was found.
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来源期刊
CiteScore
2.30
自引率
21.40%
发文量
29
审稿时长
11 weeks
期刊最新文献
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