CN105179303A - Axial flow pump impeller all-operating-condition design method - Google Patents

Abstract

A method for designing the impeller of an axial flow pump under all working conditions, comprising the following steps: (1) Parametric modeling of the impeller of the axial flow pump: selecting k airfoil sections of the axial flow pump impeller, the cascade density and the total value of the airfoil placement angle 2k design parameters; (2) Optimal design for all working conditions: First, determine the conventional design parameters of the impeller; then perform numerical calculations on the design conditions of the axial flow pump impeller, and comprehensively analyze various losses in the pump to minimize the total loss Preliminary design of a pair of axial flow pump impellers with better hydraulic performance under the design working conditions; second, design guide vanes, water guide cones and water inlet and outlet channels for the impeller; The optimal weighted average efficiency is the goal, and the head is the constraint condition. The sequential quadratic programming method of the gradient optimization algorithm is used to continuously change the design parameters of the axial flow pump impeller, and iterative numerical calculations are performed on the pump device. The invention adopts CFD numerical calculation, has high design precision and reliable optimization result.

Description

A Design Method of Axial Flow Pump Impeller under All Working Conditions

technical field

The invention relates to a method for designing the impeller of an axial flow pump under all working conditions, and belongs to the technical field of water conservancy and power engineering.

Background technique

The traditional axial flow pump design method is a single design method only according to the design working conditions, that is, a certain set of design flow and design head values are put forward according to the application occasions, and the design of the whole pump is carried out, but the so-called design working conditions are actually only the head. - A point on the flow (H-Q) performance curve. The design using the traditional design method only guarantees the performance of the design point under ideal fluid and idealized flow conditions. As for the performance under non-design conditions, it cannot be guaranteed in the design, or can only be obtained from experiments. . In most cases, the site where the axial flow pump is applied cannot be fixed in the design conditions, and most of the time it operates under non-design conditions. The design requirements of the axial flow pump should be: as high as possible efficiency, suitable performance curve and good cavitation characteristics. However, the traditional axial flow pump design method only pursues higher efficiency requirements under design conditions, ignoring other hydraulic performance requirements. Therefore, the traditional design method of this design condition will be increasingly unable to meet the increasingly complex production requirements. The defects of the traditional design method of the axial flow pump impeller mainly include the following aspects:

1. The theory of the method is the Euler equation, and the Euler equation only establishes the relationship between the external characteristic parameters and the speed of the impeller inlet and outlet of the axial flow pump. It does not analyze the flow field and pressure field inside the impeller, although some designs consider the liquid The viscous effect has been corrected by the empirical formula, but it is still too rough.

2. The design process is aimed at the impeller of the axial flow pump itself, without considering the influence of the guide vane, inlet and outlet water passages and other flow components on the internal flow of the axial flow pump and the performance of the axial flow pump. Especially for the design conditions, it can only be said that it basically meets the requirements of the design conditions.

3. The design process is oversimplified, with large human factors and large errors.

4. The performance of the axial flow pump under non-design conditions cannot be balanced, and the efficiency under design conditions can only reach the level of the statistical data, and it is difficult to further improve.

5. The design is carried out sequentially, without considering the interaction between upstream and downstream and various losses.

However, with the development of numerical simulation technology and numerical optimization technology, and the innovation of the design concept of the impeller of the axial flow pump, the patent of the present invention proposes a design method for the full working condition of the axial flow pump.

Contents of the invention

The purpose of the present invention is to provide an axial flow pump impeller full working condition design method, using the inverse problem design method, considering multiple working condition points and multiple objectives to optimize the full working condition design of the axial flow pump. When optimizing the design, the hydraulic performance of the pump device is calculated as a whole, and the design scheme of the axial flow pump impeller is determined according to the calculation results of the pump device. During the calculation, the numerical simulation is carried out by the CFX flow simulation software, which has high calculation accuracy and reliable optimization results. The optimized design of the example shows that: the efficiency of the design operating point has been improved, but the increase is not obvious, but the efficiency of the large flow operating point and the small flow operating point are more obvious, and the efficiency of the large flow operating point has increased by about 7.4%. The efficiency of the small flow operating point is increased by about 2.6%, the range of the high-efficiency zone is obviously widened, and the effect of the optimized design is obvious.

The object of the present invention is achieved through the following technical solutions, a design method for the full working condition of an axial flow pump impeller, comprising the following steps:

(1) Parametric modeling of axial flow pump impeller:

Select k airfoil section cascade density and airfoil placement angle of the axial flow pump impeller, a total of 2k design parameters;

(2) Optimized design for all working conditions:

First, determine the general design parameters of the impeller, design flow Q, design head H, speed n, unilateral clearance of the blade top, in mm; the number of impeller blades, the hub ratio of the axial flow pump impeller dd; then the axial flow pump impeller Numerical calculation is carried out under the design conditions, comprehensive analysis of various losses in the pump, and a pair of axial flow pump impellers with better hydraulic performance under the design conditions are preliminarily designed with the minimum total loss;

Second, design the guide vane, water guide cone and water inlet and outlet channels for the impeller, and determine the diffusion angle of the guide vane body, the number of guide vane blades, the size of the water guide cone and the water inlet and outlet channels;

Third, finally integrate the CFX numerical optimization software through the Isight numerical optimization platform to integrate the impeller, guide vane, water guide cone and water inlet and outlet channels into a pump device, aiming at the optimal weighted average efficiency of the pump device under all working conditions. Constraint conditions, using the sequential quadratic programming method of the gradient optimization algorithm, constantly changing the design parameters of the axial flow pump impeller, performing iterative numerical calculations on the pump device, and finally finding the design scheme of the axial flow pump impeller that maximizes the overall efficiency of the pump device through iteration .

Preferably, the calculation method of cascade density in the parametric modeling: by changing the density value a ₁ of the tip cascade and the multiple a ₂ of the density value a 2 of the root cascade, changing the cascade density value of each section, the cascade The calculation formula of density l/t(i) is:

l/t(i)=n+m/r(i)

m=(a ₂ -1)*a ₁ /(1/dd-1)

n=a ₁ -m

Among them, a ₁ is the density value of the blade tip cascade; a ₂ is the multiple of the density of the blade root cascade; dd is the hub ratio; n, m are the intermediate calculation quantities; i=1-k, k is the total number of airfoil sections; r(i) is the relative radius value of the i-th section, that is, the ratio of each section radius to the impeller radius; l/t(i) is the cascade density value of the i-th section.

Preferably, the calculation method of the airfoil placement angle in the parametric modeling is: according to the airfoil placement angle values of k sections of the impeller in the initial design working condition, the ten airfoil placement angles are calculated by quadratic polynomial Fitting, fitting to obtain the relationship between the airfoil placement angle β and the relative radius value r:

β＝a ₃ -a ₄ *r+a ₅ *r ²

Define the three coefficients of this quadratic polynomial as a ₃ , a ₄ , and a ₅ as the design variables of the optimal design. By controlling the changes of the three coefficients a ₃ , a ₄ , and a ₅ to control the placement angle of each section airfoil Changes to achieve parametric modeling of impeller blades.

Preferably, when selecting working conditions, the optimal design of the full working condition selects three flow working condition points, respectively selects the design flow working condition point, the small flow working condition point and the large flow working condition point: the design flow working condition point is Q ₀ , then the small flow point Q is _small = (0.7-0.9)*Q ₀ , and the large flow point Q is _large = (1.1-1.3)*Q ₀ ;

Under the three flow conditions, the head changes in a small range, and the value of the design variable of the axial flow pump blade is constantly changed, so that the efficiency of the pump device at the three flow conditions points reaches the optimal value, so as to broaden the efficiency of the axial flow pump device. Area range, and then determine the design scheme of the axial flow pump impeller;

The optimization model is as follows:

Objective function: maxη(x)=w ₁ η ₁ (x)+w ₂ η ₂ (x)+w ₃ η ₃ (x)(1)

Design variable: x＝[a _l , a ₂ , a ₃ , a ₄ , a ₅ ] ^T

Among them, η ₁ , η ₂ and η ₃ are the efficiencies of small flow working conditions, design working conditions and large flow working conditions respectively; w ₁ , w ₂ and w ₃ are the corresponding weight values respectively, and the weight values are based on the The actual running time of the working condition, the design working condition and the large flow working condition is determined; H ₁ , H ₂ and H ₃ are the head of the small flow working condition, the design working condition and the high flow working condition respectively, the unit is m; The impeller is the initial scheme, and the corresponding initial design variable values of the impeller are A ₁ , A ₂ , A ₃ , A ₄ , and A ₅ .

Preferably, the change range of H ₂ is 0-0.2m; the change range of H ₁ and H ₃ is 0-1m.

Compared with the prior art, the present invention has the following beneficial effects:

First, using CFD numerical calculation, the design precision is high and the optimization result is reliable. Determine the final design scheme of the axial flow pump impeller by calculating the hydraulic performance of the pump device, fully consider the interaction of the flow parts of the pump device and various hydraulic losses, improve the efficiency of each working point of the pump device, and obtain a wider high-efficiency zone The efficiency curve of the pump device is obtained, and a more suitable performance curve of the water pump is obtained.

Second, with the construction of cross-basin water diversion projects and the implementation of national large-scale and small and medium-sized pumping station technical transformation, a total of thousands of pumping stations need to be newly built or updated, and the performance requirements of water pumps are getting higher and higher. Therefore, the application and implementation of this patent will achieve greater economic and social benefits.

Description of drawings

Figure 1 is a flowchart of the optimal design of the axial flow pump device.

Figure 2 is the numerical calculation model of the pump device.

Figure 3 is the performance curve of the pump device before and after optimization.

Wherein among Fig. 2 1. water inlet pipe 2. impeller 3. guide vane body 4. water outlet pipe.

Detailed ways

The axial flow impeller will be further described below in conjunction with the accompanying drawings.

1, the technical problem to be solved in the present invention

1) Using CFD numerical calculation as the subject analysis method, the design accuracy is high, and the manual design method based on experience is avoided.

2) The optimal design adopts the optimal design method for all working conditions, taking into account the hydraulic performance under non-design working conditions, and widens the range of high-efficiency zones as much as possible to obtain a more suitable performance curve.

3) The optimization design adopts the multi-objective optimization design method to improve the efficiency of each flow point as much as possible, and it should also have good cavitation performance.

4) Optimal design The final design scheme of the axial flow pump impeller is determined according to the optimal hydraulic performance of the pump device through numerical calculation. Different from the traditional sequential design, the interaction between the flow components and various losses of the pump device is fully considered.

2. Technical scheme of the present invention

1) Parametric modeling of axial flow pump impeller

Generally, when designing the impeller of an axial flow pump, the blades of the axial flow pump are divided into 11 two-dimensional airfoil sections for design. Then the designed cross-section airfoils are smoothly combined into an axial flow pump impeller. There are many design parameters for axial flow pump blades, and the shape of axial flow pump blades can be easily changed by changing the density of cascades in each section of the axial flow pump and the placement angle of the airfoil.

In the patent of the present invention, the cascade density (l/t) is an important parameter in the design of the blades of the axial flow pump, l: refers to the chord length of the airfoil section; t=2πr/z, where z is the number of blades, and r is the Radius value where the airfoil section is located. The tip cascade density refers to the cascade density value of the airfoil section at the outermost edge of the blade, and the blade root cascade density refers to the cascade density value of the airfoil section at the hub. The density multiple of the root cascade refers to the ratio of the density of the root cascade to the density of the tip cascade. For example, if the density of the tip cascade is 0.82 and the density multiple of the root cascade is 1.4, the Cascade density = blade tip cascade density 0.82 * root cascade density multiple 1.4 = 1.148. The density of cascades in each section in the middle changes linearly from the blade tip to the blade root. The placement angle of the airfoil is the angle between the chord length of the airfoil of each section and the horizontal line.

There are 22 design parameters for 11 airfoil sections, which will greatly reduce the efficiency of blade optimization during optimization. It is found through fitting that the density of cascades in each section of the axial flow pump has a linear relationship, so it is only necessary to change the blade tip The multiples of cascade density and root cascade density can change the cascade density values of 11 sections; and the placement angles of airfoils of 11 sections have a quadratic relationship. That is: β=a ₁ -a ₂ *r+a ₃ *r ² , only need to change the three coefficients of the quadratic relationship to change the setting angle of the airfoil of 11 sections. The hub ratio and the number of blades are selected according to the recommended values in relevant references. When optimizing the design, it is only necessary to change the values of the above five variables to change the twisted shape of the blades of the axial flow pump, thereby changing the hydraulic performance of the axial flow pump device, improving the efficiency of optimization, and shortening the design cycle. The program written by fortran can change the value of these five variables and then change the shape of the blades of the axial flow pump.

2) Optimized design for all working conditions

The basic idea of designing the impeller of the axial flow pump in the patent of the present invention: firstly carry out numerical calculation on the impeller of the axial flow pump according to the design working conditions according to the ideal flow conditions and the real liquid, comprehensively analyze various losses in the pump, and preliminarily design the design work with the minimum total loss A pair of axial flow pump impeller with optimal hydraulic performance under the condition, determine the geometric shape and design parameters of the impeller. Then design the guide vanes, water guide cones, and water inlet and outlet channels for the impeller, and at the same time carry out parametric modeling of the impeller, so that the geometry of the axial flow pump impeller can be easily changed by changing the design parameters. Finally, the CFX numerical optimization software is integrated through the iSIGHT numerical optimization platform, and the various flow components are integrated into a pump device. The goal is to optimize the weighted average efficiency of the pump device under all working conditions, and the lift is a constraint condition, and the design parameters of the axial flow pump impeller are constantly changed. , iteratively calculates the pump device, and finally finds the design scheme of the axial flow pump impeller that makes the overall efficiency of the pump device the highest through iteration.

Determination of optimal design working conditions:

In the optimal design of all working conditions, when selecting working conditions, three flow working condition points are mainly selected, and the design flow working condition point, the small flow working condition point and the large flow working condition point are respectively selected. For example: the design flow operating point is Q ₀ , then the small flow operating point Q is _small =0.8*Q ₀ , and the high flow operating point Q is _large =1.2*Q ₀ .

The goal of optimizing the design:

In the multi-objective optimization design, it is mainly considered that the efficiency of each flow condition point should be relatively high in the optimization design of all working conditions, so as to broaden the range of the high-efficiency zone of the performance curve. The efficiency of each operating point is normalized during optimization, that is, maxη(x)=w ₁ η ₁ (x)+w ₂ η ₂ (x)+w ₃ η ₃ (x), where η ₁ , η ₂ and η ₃ are the efficiencies of small flow conditions, design conditions and large flow conditions, respectively. w ₁ , w ₂ and w ₃ are corresponding weight values respectively. The weight value is determined according to the actual running time of each flow condition point of the pumping station.

Constraints for optimal design:

The constraints are mainly the head of each working point and the cavitation performance requirements of the design point. In order to ensure that the impeller of the axial flow pump can meet the operation requirements of the same pumping station before and after optimization, and keep the nominal specific speed consistent, the change range of the head at the design working point should be as small as possible, and the change range is recommended to be 0-0.2m. It is recommended that the head variation range at the design working point be 0~1m. It depends on the specific conditions of the pumping station.

Since the cavitation performance in non-design conditions, the numerical simulation calculation error is relatively large, so when optimizing the design of all working conditions, the necessary NPSH requirements of the design conditions can be considered only, and the smaller the necessary NPSH, the better . The necessary NPSH value of different impellers varies greatly. In order to ensure that the impeller has good cavitation performance, the constraint value of the necessary NPSH can be determined according to the specific impeller.

Choice of optimization algorithm:

The multi-objective optimization design of the axial flow pump under full working conditions is a constrained, nonlinear, multi-objective and non-unique optimization design problem. The gradient optimization algorithm Sequential Quadratic Programming (SQP) is selected. This method can directly deal with equality and inequality constraints, and is currently recognized as one of the excellent algorithms for solving nonlinear problems. It has very good global convergence and local superlinear convergence characteristics, fewer iterations, faster convergence speed, and strong boundary search ability. It is especially suitable for the optimization design problems with few design variables and few constraints in this paper.

Subject Analysis:

The subject analysis adopts the CFD numerical calculation method, and the traditional optimization method is carried out sequentially, and only optimizes the hydraulic performance of the axial flow pump impeller (single pump) under the design working condition, and then designs the guide vane and flow channel according to the optimized impeller , ignoring the interaction between impellers, guide vanes and other flow components. Another major innovation of the patent of the present invention is that CFD numerical calculation is used in the optimization to calculate the hydraulic performance of the pump device (including impeller, guide vane, water guide cone and water inlet and outlet channels) at multiple flow conditions, fully considering The interaction between the flow components of the axial flow pump device and various hydraulic losses.

Technical principle:

The flow of liquid in each flow-through part of the axial flow pump device can be considered as the best flow state under the design working condition, which is close to the ideal flow. However, when the actual operating condition deviates from the designed operating condition, due to the influence of water viscosity and other factors, adverse flow states such as vortex, backflow, stall and deflow will occur inside the axial flow pump and in the flow components. These unfavorable flow states will gradually intensify with the degree of deviation from the design conditions. Therefore, when designing an axial flow pump, we should not only focus on the hydraulic performance requirements of the design working conditions, but also consider and pay attention to the hydraulic performance requirements of the non-design working conditions. The patent of the present invention uses the inverse problem design method to optimize the design of the axial flow pump by considering multiple optimization targets at multiple operating points. When optimizing the design, the hydraulic performance of the pump device is calculated as a whole, and the design scheme of the axial flow pump impeller is determined according to the calculation results of the pump device. During the calculation, the numerical simulation is carried out by the CFX flow simulation software, and the calculation accuracy is high. Change the design parameters of the impeller of the axial flow pump to improve or delay the bad flow state inside the axial flow pump device, so as to achieve the purpose of improving the efficiency of each flow point.

3. Beneficial effects

Using CFD numerical calculation, the design precision is high and the optimization result is reliable. Determine the final design scheme of the axial flow pump impeller by calculating the hydraulic performance of the pump device, fully consider the interaction of the flow parts of the pump device and various hydraulic losses, improve the efficiency of each working point of the pump device, and obtain a wider high-efficiency zone The efficiency curve of the pump device is obtained, and a more suitable performance curve of the water pump is obtained.

Example 1

Using the patented optimization design method of the present invention, the multi-objective optimization design of the full working condition is carried out for an axial flow pump impeller with a nominal specific speed of 800. Design parameters: design flow Q=360L/s, design head H=6.0m, speed n=1450r/min, unilateral clearance of blade top is 0.2mm. The rear guide vane body is designed for the design conditions of the impeller. The divergence angle of the guide vane body is 6°, the number of guide vane blades is 7 pieces, the number of impeller blades is 4 pieces, and the hub ratio of the axial flow pump impeller is 0.4333. The water inlet straight pipe section and the water outlet elbow pipe section are modeled by Proe, and the impeller and guide vane body are modeled by Turbo-Grid according to their three-dimensional coordinate data points. The calculation model of the axial flow pump device is shown in Fig. 2.

1. Numerical simulation

Mesh division: ICEM software is used for structural grid division of the water inlet straight pipe section and water outlet elbow section, and the grid quality is above 0.4; the structural grid division of the axial flow pump impeller and guide vane body is carried out in Turbo-Grid. The grid quality is good and can meet the calculation requirements. The grid number of the axial flow pump impeller is 330928, the grid number of the guide vane body is 365274, and the grid number of the whole calculation domain is 1215277. During calculation iterations, the number of meshes for the impeller remains comparable, and the number of meshes for other parts remains constant.

Boundary condition setting: The inlet of the calculation domain of the pump device is the inlet of the water inlet pipe, and the inlet boundary condition is set as the total pressure condition, that is, the total pressure at the inlet is set to a standard atmospheric pressure. The outlet of the calculation domain of the pump device is the outlet of the outlet elbow section, the outlet boundary is set as the mass flow outlet, the impeller is set as the rotating domain, and the rest of the calculation domains are static domains. The static and dynamic interface adopts the stage model of velocity average, and the static and static interface adopts the None interface model.

2. Parametric modeling of axial flow pump impeller

The patent of the present invention chooses to change 22 design parameters of 11 airfoil section cascade densities and airfoil placement angles of the axial flow pump impeller during parametric modeling, which can easily change the shape of the axial flow pump blades.

Cascade density: By changing the density value of the tip cascade (a ₁ ) and the multiple of the root cascade density (a ₂ ), it is very convenient to change the density value of 11 section cascades. The procedure is as follows:

a ₁ ;

a ₂ ;

dd=0.4333

m=(a ₂ -1)*a ₁ /(1/dd-1)

n=a ₁ -m

doi=1,k

l/t(i)=n+m/r(i)

enddo

Among them, a ₁ is the density value of the blade tip cascade; a ₂ is the multiple of the density of the blade root cascade; dd is the hub ratio; n, m are the intermediate calculation quantities; k is the number of airfoil sections, and there are 11 sections in this example ;r(i) is the relative radius value of the i-th section, that is, the ratio of the radius of each section to the radius of the impeller. In this example, from the rim to the hub are: 1.000000; 0.9370334; 0.8740667; 0.8111000; 0.7481333; 0.5592333; 0.4962667; 0.4333000; 0.36667; l/t(i) is the cascade density value of the i-th section.

In this example, the wheel-hub ratio is a fixed value, so it is only necessary to give the density value of the blade tip cascade and the density value of the blade root cascade to obtain the cascade density value of each section, so as to conveniently control the geometric shape of the axial flow pump blade .

Airfoil placement angle: In this example, according to the initial design of the airfoil placement angle values of the 11 sections of the impeller, the ten airfoil placement angles are fitted by a quadratic polynomial, and the relationship between the airfoil placement angle and the relative radius value is obtained by fitting. relationship between:

β _m =90.504-129.96.4r+57.26r ²

Define the three coefficients of this quadratic polynomial as a ₁ , a ₂ , and a ₃ design variables for optimal design, and control the change of the placement angle of the airfoil of each section by controlling the changes of these three coefficient values, thereby realizing the parameterization of the impeller blades modeling.

3. Optimized design

Through CFX numerical analysis software and Isight numerical optimization software, the multi-objective optimization design of the axial flow pump is carried out under all working conditions. The final design scheme of the impeller of the axial flow pump is determined by calculating the hydraulic performance of the axial flow pump device.

1) Determination of working conditions:

In this paper, the optimal design of all working conditions is studied. In order to obtain a better performance curve, three working condition points of large flow, small flow and design flow are selected for optimal design. According to the design working condition Q=360L/s, about 0.8 times and 1.2 times of the selected design flow rate are used as the small flow working condition and the large flow working condition. 300L/s, Q=420L/s for large flow conditions.

2) Optimization algorithm:

Aiming at the constrained, nonlinear, multi-objective and non-unique hydraulic performance optimization design problem of the axial flow pump device under multiple operating conditions, the gradient optimization algorithm Sequential Quadratic Programming (SQP) is selected.

3) Optimization model establishment:

The purpose of optimization is to find the optimal value of the design parameters within the optimization range of the design variables of the axial flow pump impeller under the constraint conditions, so that the efficiency of the three operating points of the axial flow pump device is optimal. The multi-objective optimization design problem for axial flow pumps in all working conditions is defined as: under three flow conditions, the head changes in a small range, and the value of the axial flow pump blade design variable is constantly changed, so that the pump device at the three flow conditions The efficiency reaches the optimal value, so as to broaden the range of the high-efficiency zone of the axial flow pump device, and then determine the design scheme of the axial flow pump impeller. In this example, the impeller designed for the design working condition is taken as the initial scheme, and the initial design variables of the corresponding impeller are: a ₁ =0.9885, a ₂ =1.2897, a ₃ =90.504, a ₄ =-129.96, a ₅ =57.26.

The optimization model is as follows:

Objective function:

maxη(x)=w ₁ η ₁ (x)+w ₂ η ₂ (x)+w ₃ η ₃ (x)(1)

Design variable: x＝[a _l , a ₂ , a ₃ , a ₄ , a ₅ ] ^T

In the formula, η ₁ , η ₂ and η ₃ are the efficiencies of the small flow condition, the design condition and the large flow condition, respectively. w ₁ , w ₂ and w ₃ are corresponding weight values respectively. The weight value should be determined according to the actual running time of the pump station at each working point. In this example, the weight values are w ₁ =0.3, w ₂ =0.4 and w ₃ =0.3 respectively. H ₁ , H ₂ and H ₃ are the head of each working point respectively, unit m. In order to ensure that the design point of the impeller of the axial flow pump remains unchanged after the optimized design, and the specific speed remains consistent, the head variation range at the design working point is as small as possible, and the head variation range at the other two working points can be slightly larger.

4) Optimization results:

Constantly changing the design variables of the impeller of the axial flow pump, within the head constraint range, makes the total efficiency of the three operating points of the axial flow pump device the highest. After continuous iterative calculation, the final design scheme of the axial flow pump impeller was obtained. The comparison between the optimization results and the initial results is shown in Table 1.

Table 1 Numerical optimization results of the pump device

According to the results in Table 1, it can be seen that the denseness of the blade tip cascade decreases, the length of the outer edge airfoil decreases, and the multiple of the density of the blade root cascade increases, which reduces the length difference between the inner and outer airfoils, balances the blade outlet lift, and reduces The radial flow improves the hydraulic performance of the impeller; at the same time, according to the change of the airfoil placement angle fitting coefficient, it can be found that the placement angle of the wheel rim side airfoil increases, and the hub side airfoil placement angle decreases, which reduces the shape of the impeller blade. The distortion improves the working conditions of the airfoil, which is consistent with the idea of optimizing the impeller design of the axial flow pump. The optimization results show that the efficiency of the design operating point has improved, but the increase is not obvious, but the efficiency of the large flow operating point and the small flow operating point have improved significantly, among which the efficiency of the large flow operating point has increased by 7.4%, and the efficiency of the small flow operating point has increased by 7.4%. The efficiency of the operating point is increased by 2.6%, and the optimization effect is obvious.

The hydraulic performance of the pump device at the remaining working conditions is calculated by numerical simulation and compared with the hydraulic performance of the axial flow pump device before optimization, as shown in Figure 3.

According to the performance curves of the pump device before and after optimization in Fig. 3, it can be seen that after optimization, the head of the axial flow pump device under the small flow condition and the design condition is slightly reduced, but the efficiency is improved; the head of the large flow condition is increased, and the efficiency is also increased. improve. After optimization, the efficiency curve is raised as a whole, and the range of high-efficiency zone is widened, which improves the operation stability of the pump station and reduces the operation cost of the pump station. The optimization effect of the pump device is very obvious.

1) A complete set of multi-working-condition optimization design methods for axial flow pump devices based on numerical analysis and numerical optimization techniques is proposed. This method can greatly reduce the cost of optimal design of axial flow pumps and shorten the optimization design cycle.

2) The subject analysis method of CFD calculation is adopted, combined with the method of experimental research to replace the manual optimization method based on experience, which improves the reliability of the optimization results, and also confirms the reliability and high efficiency of the multi-working condition optimization design of the axial flow pump device. sex.

3) The efficiency of the small flow point of the axial flow pump device is increased by about 2.6%, the efficiency of the design point is increased by about 0.5%, and the efficiency of the high flow point is increased by about 7.4%. After optimization, the high-efficiency zone of the axial flow pump device is obviously wider, which greatly reduces the operating cost of the pump station, and the optimization effect is very obvious.

Claims (5)

1. an axial-flow pump impeller full working scope design method, is characterized in that, comprises the following steps:

(1) axial-flow pump impeller parametric modeling:

Select k aerofoil profile section cascade solidity of axial-flow pump impeller and aerofoil profile to lay angle value and amount to 2k design parameter;

(2) full working scope optimal design:

The first, first determine this impeller conventional design parameters, design discharge Q, rated lift H, rotating speed n, monolateral gap, leaf top, unit is mm; Impeller blade number, axial-flow pump impeller hub ratio dd; Then numerical calculation is carried out to axial-flow pump impeller design conditions, comprehensive analyze every loss in pump, go out hydraulic performance preferably one pair of axial-flow pump impeller under design conditions with the minimum proposal plan of total losses;

The second, then the design carrying out stator, water guide cone and inlet and outlet channel for this impeller, determine the size of diffuser diffusion angle, the stator number of blade, water guide cone and inlet and outlet channel;

3rd, finally by Isight numerical optimization platform intergration CFX numerical optimization software, impeller, stator, water guide cone and inlet and outlet channel are integrated into pump-unit, optimum for target with the weighted average efficiency of pump-unit full working scope, lift is constraint conditio, selects the Sequential Quadratic Programming method of gradient optimal method, continuous change axial-flow pump impeller design parameter, iterations and numerical simulation is carried out to pump-unit, by iteration, finally finds the design proposal making axial-flow pump impeller that pump-unit overall efficiency is the highest.

2. axial-flow pump impeller full working scope design method according to claim 1, is characterized in that, the computational methods of cascade solidity in described parametric modeling: by changing blade tip cascade solidity value a ₁with blade root cascade solidity multiple a ₂, change section cascade solidity value, the formula of cascade solidity l/t (i) is:

l/t(i)＝n+m/r(i)

m＝(a ₂-1)*a ₁/(1/dd-1)

n＝a ₁-m

Wherein, a ₁for blade tip cascade solidity value; a ₂for blade root cascade solidity multiple; Dd is hub ratio; N, m are intermediate computations amount; I=1-k, k are aerofoil profile section sum; R (i) is the relative radius value of i-th section, i.e. the ratio of each cross sectional radii and impeller radius; L/t (i) is the cascade solidity value of i-th section.

3. axial-flow pump impeller full working scope design method according to claim 1, it is characterized in that, in described parametric modeling, the computational methods of aerofoil profile laying angle are: the aerofoil profile according to an impeller k section of initial designs operating mode lays angle value, by carrying out matching by quadratic polynomial to these ten aerofoil profile laying angles, matching obtains the relation between aerofoil profile laying angle β and relative radius value r:

β＝a ₃-a ₄*r+a ₅*r ²

Defining this quadratic polynomial three coefficients is a ₃, a ₄, a ₅for the design variable of optimal design, by controlling this three coefficient a ₃, a ₄, a ₅the change of value controls the change of each section wing laying angle, realizes the parametric modeling of impeller blade.

4. axial-flow pump impeller full working scope design method according to claim 1, it is characterized in that, described full working scope optimal design, when operating mode is selected, chooses three flow rate working conditions points, selects design discharge operating point, low flow rate condition point and large discharge operating point respectively: design discharge operating point is Q ₀, then low flow rate condition point Q _little=(0.7-0.9) * Q ₀, large discharge operating point Q _greatly=(1.1-1.3) * Q ₀;

Under three flow rate working conditions, lift change among a small circle, constantly changes the value of axial flow pump blade inner design variable, makes the efficiency of three flow rate working conditions point pump-units all reach optimum value, to widen the efficient district scope of axial-flow pump device, and then determine the design proposal of axial-flow pump impeller;

Optimized model is as follows:

Objective function: max η (x)=w ₁η ₁(x)+w ₂η ₂(x)+w ₃η ₃(x) (1)

Design variable scope $\left\{\begin{array}{c}{a}_1\\ a_2\\ a_3\\ a_4\\ a_5\end{array}\right.---\left(2\right)$

Constraint conditio $\left\{\begin{array}{c}{H}_1\\ H_2\\ H_3\end{array}\right.---\left(3\right)$

Design variable: x=[a _l, a ₂, a ₃, a ₄, a ₅] ^t

Wherein η ₁, η ₂and η ₃the efficiency of low flow rate condition, design conditions and large discharge operating mode respectively; w ₁, w ₂and w ₃be respectively corresponding weighted value, weighted value is determined according to the actual run time of pumping plant low flow rate condition, design conditions and large discharge operating mode; H ₁, H ₂and H ₃be respectively the lift of low flow rate condition, design conditions and large discharge operating mode, unit m; Impeller for design conditions design is initial scheme, and the initial designs variable of corresponding impeller is a ₁, a ₂, a ₃, a ₄, a ₅.

5. axial-flow pump impeller full working scope design method according to claim 4, is characterized in that, described H ₂excursion value 0-0.2m; H ₁, H ₃excursion value 0-1m.