共查询到18条相似文献,搜索用时 156 毫秒
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涡轮大扩张过渡段的流动分离与控制数值研究 总被引:1,自引:1,他引:1
现代高性能涡轮机械中,研究者一直在努力提高其气动性能,体现在涡轮气动参数设计上就是:每个级利用最大焓降、最小的轴向长度、最少的每排叶片数、设计工况最高的效率。这些气动设计特点使得航空涡轮低压级静叶入口段具有较大的向外扩性,给发动机内外端壁及其高低压过渡段的设计带来了难度。通过数值模拟,探讨了一种减小扩压段流动分离的型线设计方法。 相似文献
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《内燃机学报》2016,(6)
针对某可调向心涡轮增压器,基于蜗壳流动周向非均匀性的分布规律,提出采用改进喷嘴座连接臂结构和非均匀布置可调导叶的设计方案,以降低涡轮级各部分的流动损失,提高涡轮效率.结果表明:改型后涡轮工作在发动机标定功率工况对应相似转速条件下效率相对提高值最大为5.18%,,发动机最大转矩工况对应相似转速条件下效率相对提高值最大为3.57%,;改型后蜗壳出口气流角变得更加均匀,蜗壳出口气流角与导叶开度角相接近,减小了喷嘴环区域的流动损失,解释了改型前、后涡轮效率提高的原因;改型后各叶轮流道流量的周向非均匀性明显降低,各叶轮叶片负荷周向分布更加均匀.证明改型方案对提高涡轮效率,降低叶片振动,延长涡轮有效使用寿命具有积极的影响. 相似文献
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对一个用于大推力液体火箭发动机氧涡轮泵的复速级涡轮的喷嘴叶栅进行了试验研究,以考察喷嘴叶栅的气动特性,验证喷嘴叶栅的气体设计。该复速级喷嘴叶栅采用先进的后加载流动控制技术,以减弱叶机的二次流损失,对喷嘴叶栅进行了四个进气口流角,三个出口等熵马赫数条件下的平面叶栅吹风试验,测取了型面压力分布,出口气流角以及叶栅损失等重要气动特性参数,试验研究表明氧涡轮的喷嘴叶栅的设计是成功的,具有良好的气动特性,可以有效地应用于液体火箭发动机的涡轮中,本研究也为该类喷雾叶栅的设计提供了有用的实验数据和指导意义的结论。 相似文献
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以超临界CO2为工质的闭式布雷顿循环系统具有结构紧凑、效率高等特征优势,符合可持续发展的需求。利用计算流体力学软件对某超临界CO2轴流透平的气动性能和流动特性进行数值模拟,对比了主流道及考虑气封间隙后的流动特性差异。结果表明:超临界CO2透平通流部分级等熵焓降和气流出口马赫数较低,不利于透平效率的提高;端壁二次流对于主流影响较大,末级出口的气流角仍有较大范围受端壁二次流影响;考虑气封间隙后,泄漏量占比非常大,第1级隔板气封处的泄漏量达到了总流量的7.4%,透平总静效率也下降了7.27%。该研究结果可为超临界CO2机组的设计提供参考和借鉴。 相似文献
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可转导叶由于端部间隙和转轴的存在,会产生复杂的二次流动。本文对LISA涡轮进行变几何改型,采用几何约化法对该1.5级变几何涡轮进行数值模拟,详细探究了可转导叶间隙高度对可转导叶(S1)涡系的流动细节和载荷的影响,并深入研究其非定常流动对下游叶排的干涉及二次流输运过程的影响。计算结果表明:泄漏涡(LV)、角涡(CV)和通道涡(PV)共同组成了可转导叶的涡系;可转导叶端部间隙高度影响流动损失和级效率大小,设计间隙下该变几何涡轮S1时均总压损失系数Y为10.32%,涡轮时均总总效率ηtt为82.26%;可转导叶的尾缘泄漏涡使第1级动叶(R1)流动产生强非定常性;可转导叶的尾缘泄漏涡和R1泄漏涡、壁面涡是造成第2级静叶(S2)流动非定常性的主要因素。 相似文献
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通过一维设计与三维数值模拟分析相结合的方法,对一台300kW向心汽轮机进行了气动设计。汽轮机整级焓降达到248.5kJ,压比达到4.17,为了提高整级效率,反动度值比较小,致使导叶栅中存在超音速流。对导叶和叶轮内部流动特性进行具体分析,并对设计过程中碰到的一些问题进行探讨。 相似文献
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《International Journal of Hydrogen Energy》2022,47(10):6898-6910
Rotating detonation as a kind of pressure gain combustion is expected to greatly improve efficiency when applied to gas turbine engines. In this paper, the operation of rotating detonation combustor and turbine rotor blade was studied. Firstly, the analysis of the interaction between detonation wave and turbine blade shows that the compression of gas by detonation wave and reflected wave will lead to a sharp increase in the temperature at the wall of blade. When the detonation wave propagates, the oscillation amplitudes of pressure and temperature at the turbine inlet are 70% and 75% respectively, and the detonation oblique shock will change the flow trajectory of the air flow, resulting in the flow direction deviating from the incident angle. Then the comparison between detonation and deflagration shows that the total pressure of detonation is higher and will have greater work potential. The torque generated by the blades under detonation has the characteristics of high-frequency oscillation, which may be detrimental to the operation of the engine. 相似文献
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Radial inflow turbine is one of the crucial components of organic Rankine cycle (ORC) system, which has great impact on the performance of system. R245fa was selected as the working fluid to recycle the waste heat source with a temperature of 350 to 400 K. The genetic algorithm (GA) was employed in thermodynamic design to optimize the 10 key design parameters, which are needed in aerodynamic design of the ORC turbine. Isotropic efficiency was the fitness function of 10 key variables in GA. The three‐dimensional geometry model was built based on the thermodynamic and aerodynamic design and then was imported into the commercial software ANSYS‐CFX to conduct viscous numerical simulation. Based on the three‐dimensional simulation, the off‐design performance in different mass flow rate, static inlet temperature coupled with different rotational speed was investigated respectively. The results show that at design condition, the maximum efficiency deviation is only 2.5% with the rotational speed variations among the range of 10%, so the radial inflow turbine designed in this research possesses great off‐design performance. 相似文献
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Introduction In turbofan engine technology of the 21st century, it is desired to select the best possible operating conditions for each engine section, to reduce the operating costs, fuel burn, and noise levels. The conventional mechanism in which the front fan is directly connected to the rest of the core engine arrests the optimization of the spool speed in order to avoid the flow blockage at the sonic speed. In such circumstances, the rotational speed of the front fan can be reduced using … 相似文献
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To study the feasibility of using machine learning technology to solve the forward problem(prediction of aerodynamic parameters)and the inverse problem(prediction of geometric parameters)of turbine blades,this paper built a forward problem model based on backpropagation artificial neural networks(BP-ANNs)and an inverse problem model based on radial basis function artificial neural networks(RBF-ANNs).The S2(a stream surface obtained by extending a radial curve in turbo blades)calculation program was used to generate the dataset for single-stage turbo blades,and the back propagation algorithm was used to train the model.The parameters of five blade sections in a single-stage turbine were selected as inputs of the forward problem model,including stagger angle,inlet geometric angle,outlet geometric angle,wedge angle of leading edge pressure side,wedge angle of leading edge suction side,wedge angle of trailing edge,rear bending angle,and leading edge diameter.The outputs are efficiency,power,mass flow,relative exit Mach number,absolute exit Mach number,relative exit flow angle,absolute exit flow angle and reaction degree,which are eight aerodynamic parameters.The inputs and outputs of the inverse problem model are the opposite of that of the forward problem model.The models can accurately predict the aerodynamic parameters and geometric parameters,and the mean square errors(MSEs)of the forward problem test set and the inverse problem test set are 0.001 and 0.00035,respectively.This study shows that machine learning technology based on neural networks can be flexibly applied to the design of forward and inverse problems of turbine blades,and the models built by this method have practical application value in regression prediction problems. 相似文献