离心泵作液力透平的能量转换特性及叶轮优化研究

发布时间：2017-12-28 03:34

本文关键词：离心泵作液力透平的能量转换特性及叶轮优化研究　出处：《兰州理工大学》2016年博士论文　论文类型：学位论文

【摘要】：在石油化工、煤化工、海水淡化等许多流程工业中,存在有大量的高压液体,高效回收利用这部分液体压力能具有重要的现实意义和经济价值。液力透平是回收利用液体压力能的一种装置,其中泵反转作液力透平是目前广泛应用的机型。从有关文献及生产实际中发现,目前泵反转作液力透平普遍存在能量转换效率不高的问题,这与泵用作液力透平时其内部能量转换特性认识不足有较大关系。为此,论文以离心泵反转作液力透平为研究对象,采用数值计算与实验相结合的方法对液力透平外特性进行了研究,通过实验结果验证了本文数值计算策略的准确性;采用数值计算的方法研究了液力透平叶轮及蜗壳内的能量转换特性,为后续优化设计提供参考依据;建立了基于代理模型和智能优化算法的液力透平优化系统;在上述的基础上对液力透平叶轮进行了优化研究。本文的主要研究内容分为以下3部分:1.空离心泵作液力透平的内部能量转换特性研究基于CFD技术,通过对液力透平叶轮不同径向位置流体所具有的能量、各区域输入的净能量、各区域传递给叶轮的能量、能量损失及蜗壳不同截面位置流体所具有能量、各区域能量损失等能量特征的分析,对液力透平叶轮和蜗壳内流体能量的传递与变化过程进行了研究。结果表明:对于叶轮,流体对叶轮做功主要表现为压力做功,做功的关键区域在叶轮的中前部,叶轮叶片后部区域在小流量工况对叶轮做功相对较少,而在大流量工况不仅对叶轮不做功,而且还消耗叶轮的机械能;叶轮整体能量转换效率不高。对于蜗壳,蜗型段内静压能沿流向基本呈线性减小的趋势,而动压能则沿流向呈现出波动现象;蜗壳收缩管段内静压能和动压能沿流向的变化均比较规律;蜗壳中能量损失主要在喉部之后的下游区域。2.空离心泵作液力透平叶轮优化系统的建立通过研究液力透平内部能量转换特性,为液力透平的优化设计提供了参考依据,但在优化设计时还需确立具体的优化设计方法。本文对液力透平叶轮几何参数进行优化时,其目标函数是由液力透平的水力性能参数构成,而液力透平叶轮几何参数与其水力性能间的隐式关系极其复杂,因此采用传统的优化方法很难实现,然而智能优化算法中的遗传算法是通过模仿自然界的选择与遗传机理来寻求目标函数最优解的方法,能有效地以概率的形式进行全局寻优,且对所求优化问题没有过多的数学要求,因此,本文选用遗传算法对液力透平的几何参数进行优化。但在寻优过程中,液力透平水力性能的CFD数值计算无疑是非常耗时的,因此本文还引入了非线性映射能力较强的GA-BP神经网络代替在寻优过程中获取液力透平性能参数的CFD数值计算,这样便形成了一种以GA-BP(Genetic Algorithm-Back Propagation)神经网络与遗传算法相结合的优化设计方法。最后,将优化过程中涉及到的各种技术通过程序控制,建立起本文的优化系统。3.离心泵作液力透平的叶轮优化设计通过对离心泵用作液力透平时叶轮轴面流动特点的分析,发现液力透平叶轮流道面积变化规律与其内部流动规律匹配性较差。针对于此,采用本文建立的优化系统对叶轮轴面投影图进行了优化设计。优化时以控制叶轮轴面形状的1?、2?、1R、2R和3R为设计变量,以液力透平在最优工况下的水力效率为目标函数,压头为性能约束条件进行优化,优化后液力透平性能较之前得到较大的改善。通过对离心泵反转作液力透平时叶轮内能量转换特性的分析,发现叶轮能量转换效率不高。在离心泵用作液力透平的叶轮内,能量转换的核心是叶片,因此离心泵用作液力透平的叶片有待优化改进。鉴于此,采用已建立的优化系统对该模型的叶片型线进行了优化设计。优化时采用三次非均匀B样条曲线参数化叶片型线,以控制叶片形状的控制点参数为设计变量,液力透平在最优工况附近三个工况点的水力效率为目标函数,三个工况点下的压头为约束条件对叶片型线进行优化,优化后液力透平的效率在指定的三个工况下分别得到了较大的提升,同时满足初始设定的压头约束,说明优化后叶片能量转换能力增强,同时表明采用该优化方法对液力透平叶片型线优化的可行性。通过对优化后液力透平叶轮的内流场分析,发现叶轮流道内仍存在较大的漩涡区域,采用增加叶片数的方法来进一步改善液力透平叶轮的性能。研究发现:叶轮叶片数的适当增加可以改善叶轮的内部流场,增强叶轮的做功能力,有利于液力透平效率的提升,但叶片数过多的增加,在叶轮出口产生较为严重的叶片排挤现象,同时,流体与叶片接触的总表面积会增大,导致流体与叶片表面的摩擦损失增大,反而不利于叶轮性能的提升。针对液力透平叶轮叶片增加过多时在叶片出口处造成严重排挤以及壁面摩擦损失增大的问题,可以采用添加分流叶片的方法来进一步解决。
[Abstract]:In many petrochemical industries, such as petrochemical industry, coal chemical industry, seawater desalination and so on, there are lots of high-pressure liquids. It is of great practical significance and economic value to recycle and utilize this part of liquid pressure efficiently. The hydraulic turbine is a device for the recovery and utilization of the pressure energy of the liquid, in which the pump is reversed as a hydraulic turbine, which is widely used at present. From related literatures and production practice, it is found that pump inverting hydraulic turbine generally has low energy conversion efficiency, which is related to insufficient understanding of the internal energy conversion characteristics of pump when used as hydraulic turbine. Therefore, the centrifugal pump reversal for hydraulic turbine as the research object, using the method of numerical simulation and experiment of combining the characteristics of hydraulic turbine are studied, the experimental results verify the accuracy of the numerical calculation method; studied by numerical simulation method of hydraulic turbine impeller and volute energy conversion characteristics, provide a reference the basis for the subsequent optimization design; a hydraulic turbine optimization system and intelligent agent model based on optimization algorithm; optimization study of the hydraulic turbine impeller on the basis of the above. The main content of this paper is divided into the following 3 parts: the study of the internal energy conversion characteristics of hydraulic turbine for 1. air centrifugal pump based on CFD technology, based on hydraulic turbine impeller at different radial positions of fluid energy, regional input, regional net energy transferred to the impeller energy, energy loss and different volute section position the fluid has energy, the regional energy loss characteristics of energy analysis of fluid energy hydraulic turbine impeller and volute transfer was studied and the process of change. The results show that: for the impeller, the impeller fluid pressure work mainly for work in key areas of work in front of the impeller, the impeller blades of the rear area in the small flow condition of impeller is relatively small, and in the large flow condition not only on the impeller does not work, but also consume the mechanical energy of the impeller impeller; the overall energy conversion efficiency is not high. For the volute, worm in static pressure along the flow direction can basically showed a trend of linear decrease, while showing a wave phenomenon and moving along the direction of pressure pipe; the volute systolic pressure energy and dynamic pressure variation along the flow direction are law; energy loss in the downstream area in the main volute throat after. The establishment of optimization system for 2. air centrifugal pump as a hydraulic turbine impeller provides a reference for optimizing design of hydraulic turbine by studying the internal energy conversion characteristics of hydraulic turbine, but in the optimization design, we need to establish a specific optimization design method. The hydraulic turbine impeller geometry parameters were optimized in this paper, the objective function is composed of the hydraulic performance parameters of hydraulic turbine, hydraulic turbine impeller and the implicit relationship between the geometric parameters and the hydraulic performance is extremely complex, so the use of traditional optimization methods is very difficult to achieve, but intelligent genetic algorithm optimization algorithm is to seek a method the optimal solution of the objective function through the imitation of a natural selection and genetic mechanism, can effectively in the form of probability for the global optimization, and to solve the optimization problem does not require too much, so the geometric parameters of mathematics, genetic algorithm to optimize the hydraulic turbine. But in the process of optimization, numerical calculation of hydraulic turbine hydraulic performance of the CFD is very time-consuming, CFD numerical calculation this paper also introduces the GA-BP neural network strong nonlinear mapping ability instead of hydraulic turbine performance parameters obtained in the optimization process, thus forming a GA-BP (Genetic Algorithm-Back Propagation) optimization the design method of combining neural network and genetic algorithm. Finally, various technologies involved in the optimization process are controlled through program, and the optimization system of this paper is established. 3., the impeller optimization design of centrifugal pump as a hydraulic turbine. Through the analysis of the flow characteristics of the impeller on the axial surface of the centrifugal pump as a hydraulic penetration, it is found that the variation rule of the flow path area of the hydraulic turbine impeller has poor matching with its internal flow rule. In view of this, the optimization system of the axial plane of the impeller is optimized by the optimization system established in this paper. In optimization, we take 1, 2, 1R, 2R and 3R as the design variables to control the impeller shaft surface. The hydraulic efficiency of the hydraulic turbine is optimized under the optimal working condition as the objective function, and the pressure head is optimized by performance constraints. After optimization, the performance of the hydraulic turbine has been greatly improved. Through the analysis of the energy conversion characteristics in the impeller of the centrifugal pump, it is found that the energy conversion efficiency of the impeller is not high. As the centrifugal pump is used as the impeller of the hydraulic turbine, the core of the energy conversion is the blade, so the centrifugal pump is used as the blade of the hydraulic turbine to be improved. In view of this, the optimized design of the blade profile of the model has been carried out with the established optimization system. The three non uniform B spline curve parameters of blade profile optimization, in order to control the blade shape parameters as design variables, the hydraulic efficiency of hydraulic turbine in three operation points near optimal conditions for target function, optimize the head three operating point under the constraint conditions of the blade type line. After optimizing the efficiency of hydraulic turbine in three specified working conditions were improved obviously, while satisfying the constraint set initial pressure head, that leaves the energy conversion ability after optimization, also shows that the optimization method is feasible in hydraulic turbine blade profile optimization. Through the analysis of the flow field of the optimized hydraulic turbine impeller, it is found that there are still larger vortices in the impeller passage, and the number of blades is added to further improve the performance of the hydraulic turbine impeller. It is found that the proper increase of impeller blades can improve the impeller's internal flow field and enhance the impeller's work capacity, which is conducive to the improvement of hydraulic turbine efficiency, but the number of blades is increased.
【学位授予单位】：兰州理工大学
【学位级别】：博士
【学位授予年份】：2016
【分类号】：TH311

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