Optimization design method of centrifugal pump reverse rotation hydraulic turbine guide vane

Abstract

The invention discloses an optimization design method for a centrifugal pump reverse rotation hydraulic turbine guide vane. The optimization design method comprises the steps that full-flow-channel water body three-dimensional modeling is conducted, and analogue simulation is conducted; parameterizing the positive guide vane, and constructing an expression of the thickness and the mean camber line of the vane; constructing an agent model of the original model, and then determining relevant parameters of the shape of the guide vane; performing PSO algorithm optimization on the parameters, and obtaining an optimal parameter set of the proxy model; updating the blade profile of the guide blade, and judging whether a design target is reached or not; the method comprises the following steps: parameterizing a guide vane to construct a positive guide vane profile expression, constructing an agent model, optimizing influence factors, and reducing dynamic and static interference between the guide vane and an impeller, so that the energy loss of flow is reduced, the generation of vortex is reduced, and the flow is more stable; and improved PSO iterative optimization is carried out on the blade parameters of the positive guide vane, and finally the purposes of reducing the dynamic and static interference effect between the guide vane and the impeller and enabling the flow field in the turbine to be more stable are achieved.

Description

Technical Field

[0001] The invention belongs to the technical field of fluid mechanical energy recovery, and in particular relates to a method for optimizing the design of guide vanes of a centrifugal pump reverse-operating hydraulic turbine. Background Art

[0002] ‌Hydraulic turbine is a device used to recover redundant energy in industrial production processes. It is widely used in high-pressure waste energy recovery systems in many process industries such as petrochemicals, steel and metallurgy. Usually, a centrifugal pump reverse turbine structure is used, but the hydraulic design of the centrifugal pump is completely designed according to the working parameters of its pumping condition. It is worth noting that the efficiency of the traditional centrifugal pump reverse hydraulic turbine is relatively low compared with the pumping condition, and there is a lack of design methods for optimizing the guide vanes. Therefore, the optimization design of the guide vanes of hydraulic turbines is an important topic. One of the important reasons why hydraulic turbines are inefficient under operating conditions that deviate from the design conditions is that the dynamic and static interference between the guide vanes and the impeller of the hydraulic turbine causes flow instability and reduces efficiency. Therefore, there is an urgent need for a guide vane optimization design method that reduces the dynamic and static interference between the guide vane and the impeller, so as to achieve the purpose of improving the efficiency of the hydraulic turbine. Summary of the invention

[0003] The purpose of the present invention is to overcome the deficiencies in the prior art and provide a method for optimizing the guide vanes of a hydraulic turbine in a centrifugal pump in reverse operation. The guide vanes of the model hydraulic turbine are parameterized and expressions for the thickness and the mid-arc of the positive guide vanes are constructed to construct a proxy model. The parameters of the blade shape are then determined. The optimization goal is to reduce the dynamic and static interference between the guide vanes and the impeller to make the flow more stable. The optimization index is the efficiency of the hydraulic turbine, and ultimately the high-efficiency zone range of the hydraulic turbine is improved to solve the problems raised in the above-mentioned background technology.

[0004] To achieve the above object, the present invention provides the following technical solution: a method for optimizing the guide vane design of a centrifugal pump reverse hydraulic turbine, comprising the following steps: Step S1: perform three-dimensional modeling of the entire flow channel water body of the original model hydraulic turbine according to basic structural parameters, draw a calculation grid, and perform simulation to obtain the external characteristic results of the original guide vane; Step S2: parameterizing the positive guide vane of the original model guide vane, and constructing expressions for the thickness and the median camber of the positive guide vane; Step S3: construct a proxy model of the original model, and then determine the relevant parameters of the guide vane shape; Step S4: optimizing the positive guide vane parameters of the proxy model using an improved PSO algorithm, and obtaining an optimal parameter set of the proxy model; Step S5: updating the blade profile of the guide vane through the optimal parameter set of the proxy model; Step S6: For the new blade type, the optimized model parameters are used to model the three-dimensional water body of the entire flow channel, and a calculation grid is drawn for CFD simulation to determine whether the design goal is achieved by comparison with the original model. If not, the PSO algorithm is iteratively optimized for the impeller blades again until the design goal is achieved.

[0005] Preferably, step S2 further comprises: S21: Parameterization of the original model guide vane and positive guide vane: Cartesian coordinate system is selected for modeling, with the leading edge of the blade arc as the origin and the X-axis direction as the axial direction; the parameters for controlling the two-dimensional blade profile are introduced, which are: X m - length of the median arc; α1-inflow angle of the median camber, defined as the angle between the tangent of the median camber at the trailing edge point and the axis X; α2-outflow angle of the median arc, defined as the angle between the tangent of the median arc at the leading edge point and the axis X; φ - the wrap angle of the median camber, defined as the angle between the leading and trailing points of the median camber; R m - The radius of the circle at the arc midline at the leading edge point; X p - Axial position of the maximum point circle of the mid-arc; R p - The radius of the maximum point circle of the middle arc; S22: Construct the blade thickness parameter expression: The thickness of the positive guide vane is determined by R(x) using quadratic curve fitting. The blade thickness can be converted into the relationship between the parameter and the coordinate X. R(x) = ax 2 +bx+c Where a=f a (R m , R p ), b=f b (R m , R p ), c = f c (R m , R p ); S23: Construct the middle arc parameter expression: The middle arc is determined by y(x) using the cubic curve fitting method. Similarly, the middle arc can be converted into the relationship between the parameters and the coordinate X. y(x) = dx 3 + ex 2 +fx+g Where d = f d (α1, α2, φ), e=f e(α1, α2, φ), f=tan(α2π / 180), g=R; S24: Determine the factors affecting the blade shape: Perform Pearson coefficient correlation analysis on the blade parameterization to find the correlation.

[0006] Preferably, in step S3: Construct the approximate function of the surrogate model, evaluate the parameters, determine the relevant parameters, and the mathematical model is expressed as an equation: In the formula, y is the measured response, b0 is a constant, and b j , b jk and b jj is the regression coefficient, X j and X k are the coded values ​​of the independent factors.

[0007] Preferably, in step S4: The improved PSO optimization algorithm is used for global optimization to solve the parameters of the positive guide vane of the proxy model. First, the algorithm initializes a group of random particles, and then obtains the optimal solution through iteration. Assume that each group consists of M particles, X={x1, x2, …, x m}, where x i =[x i1 , x i2 , …, x im ], then the initial position and velocity of the ith particle can be expressed as k A vector of dimensions: In the formula, and are the position and velocity of the i-th particle in the hydraulic turbine hydraulic performance optimization process.

[0008] Preferably, step S4 further comprises: S41: Speed ​​and position update: The speed and position of the particle in the global are iteratively updated according to the approximate function of the proxy model, as follows: In the formula, and are the next speed and position respectively, c1 and c2 are constants that control the maximum step size within (0,2), r1 and r2 are acceleration weight coefficients that vary within (0,1); S42: The best position in the particle swarm. The position expression is as follows: .

[0009] Compared with the prior art, the present invention has the following beneficial effects: 1. A centrifugal pump reverse operation hydraulic turbine guide vane optimization design method is provided. By parameterizing the model hydraulic turbine guide vane and constructing the expression of the positive guide vane blade thickness and the mid-arc line, a proxy model is constructed, and then the parameters of the blade shape are determined. The optimization goal is to reduce the dynamic and static interference between the guide vane and the impeller to make the flow more stable. The optimization index is the efficiency of the hydraulic turbine, and finally the high-efficiency range of the hydraulic turbine is improved.

[0010] 2. The improved PSO optimization algorithm is used for global optimization to solve the parameters of the positive guide vanes of the proxy model, which is conducive to finding the optimal parameters of the positive guide vanes of the proxy model.

[0011] 3. The parameters can be iteratively optimized to determine whether the design goal is achieved by comparing with the original model. If not, the PSO algorithm of the impeller blades is iteratively optimized again until the design goal is achieved. BRIEF DESCRIPTION OF THE DRAWINGS

[0012] Figure 1 A flow chart of a method for optimizing the design of guide vanes of a centrifugal pump reverse hydraulic turbine according to the present invention; Figure 2 It is a parameterized schematic diagram of the positive guide vane model; Figure 3 This is a schematic diagram of the optimized guide vane water model; Figure 4 Comparison of dynamic and static interference turbulent kinetic energy diagrams at the junction of the front and rear guide vanes and impellers; a before optimization, b after optimization; Figure 5 Streamline diagram at the junction of the front and rear guide vanes and the impeller; a before optimization, b after optimization. DETAILED DESCRIPTION

[0013] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0014] The present invention will be further described in detail below in conjunction with the accompanying drawings.

[0015] The design requirements of the embodiment of the present invention are a rated speed of 2900 rpm, a designed rated flow rate of 25 m3 / h, and a working fluid of liquid water at room temperature.

[0016] See also Figure 1 The present invention provides a centrifugal pump reverse operation hydraulic turbine guide vane optimization design method, which comprises the following steps: Step S1: perform three-dimensional modeling of the entire flow channel water body of the original model hydraulic turbine according to basic structural parameters, draw a calculation grid, and perform simulation to obtain the external characteristic results of the original guide vane; Step S2: parameterizing the positive guide vane of the original model guide vane, and constructing expressions for the thickness and the median camber of the positive guide vane; Step S3: construct a proxy model of the original model, and then determine the relevant parameters of the guide vane shape; Step S4: optimizing the positive guide vane parameters of the proxy model using an improved PSO algorithm, and obtaining an optimal parameter set of the proxy model; Step S5: updating the blade profile of the guide vane through the optimal parameter set of the proxy model; Step S6: For the new blade type, the optimized model parameters are used to model the three-dimensional water body of the entire flow channel, and a calculation grid is drawn for CFD simulation to determine whether the design goal is achieved by comparison with the original model. If not, the PSO algorithm is iteratively optimized for the impeller blades again until the design goal is achieved.

[0017] By parameterizing the guide vanes of the model hydraulic turbine and constructing expressions for the thickness and median arc of the positive guide vanes, a proxy model is constructed, and then the factors affecting the blade shape are determined. The optimization goal is to reduce the dynamic and static interference between the guide vanes and the impeller to make the flow more stable. The optimization index is the efficiency of the hydraulic turbine, and ultimately the high-efficiency zone range of the hydraulic turbine is improved. The main method is to perform PSO iterative optimization on the positive guide vane parameters and perform computational fluid dynamics analysis on the full flow field model, ultimately achieving the goal of broadening the high-efficiency zone range of the hydraulic turbine.

[0018] like Figure 1-3 As shown, as a further embodiment, step S2 further includes: S21: Parameterization of the original model guide vane and positive guide vane: Cartesian coordinate system is selected for modeling, with the leading edge of the blade arc as the origin and the X-axis direction as the axial direction; the parameters for controlling the two-dimensional blade profile are introduced, which are: X m - length of the median arc; α1-inflow angle of the median camber, defined as the angle between the tangent of the median camber at the trailing edge point and the axis X; α2-outflow angle of the median arc, defined as the angle between the tangent of the median arc at the leading edge point and the axis X; φ - the wrap angle of the median camber, defined as the angle between the leading and trailing points of the median camber; R m - The radius of the circle at the arc midline at the leading edge point; Xp - Axial position of the maximum point circle of the mid-arc; R p - The radius of the maximum point circle of the middle arc; S22: Construct the blade thickness parameter expression: The thickness of the positive guide vane is determined by R(x) using quadratic curve fitting. The blade thickness can be converted into the relationship between the parameter and the coordinate X. R(x) = ax 2 +bx+c Where a=f a (R m , R p ), b=f b (R m , R p ), c = f c (R m , R p ); S23: Construct the middle arc parameter expression: The middle arc is determined by y(x) using the cubic curve fitting method. Similarly, the middle arc can be converted into the relationship between the parameters and the coordinate X. y(x) = dx 3 + ex 2 +fx+g Where d = f d (α1, α2, φ), e=f e (α1, α2, φ), f=tan(α2π / 180), g=R; S24: Determine the factors affecting the blade shape: perform Pearson coefficient correlation analysis on the blade parameterization to find the correlation; in this embodiment, the original model guide vane and positive guide vane are parameterized, the parameters for controlling the two-dimensional blade profile are introduced, and the parameter expressions of the blade thickness and the mid-arc parameter expressions are established, and the blade thickness and the mid-arc are converted into the relationship between the parameters and the coordinate X. After the Pearson coefficient correlation analysis of the blade parameterization, the results show that the key factors affecting the blade shape are the mid-arc wrap angle φ, the mid-arc inflow angle α1, the mid-arc outflow angle α2, and the mid-arc maximum point circle radius R p and the radius R of the circle at the trailing edge of the mid-arc line m , and their correlation coefficients are all above 0.6.

[0019] like Figure 1-3 As shown, as a further embodiment, in step S3: Construct the approximate function of the surrogate model, evaluate the parameters, determine the relevant parameters, and the mathematical model is expressed as an equation: In the formula, y is the measured response, b0 is a constant, and b j , b jk and b jj is the regression coefficient, X j and X k is the coded value of the independent factor; in this embodiment, the proxy model approximation function is constructed, which can effectively evaluate the nonlinear influence of the parameters and the interaction between different parameters on the fitness value, and determine the relevant parameters.

[0020] like Figure 1-3 As shown, as a further embodiment, in step S4: The improved PSO optimization algorithm is used for global optimization to solve the parameters of the positive guide vane of the proxy model. First, the algorithm initializes a group of random particles, and then obtains the optimal solution through iteration. Assume that each group consists of M particles, X={x1, x2, …, x m}, where x i =[x i1 , x i2 , …, x im ], then the initial position and velocity of the ith particle can be expressed as k A vector of dimensions: In the formula, and are respectively the position and velocity of the ith particle in the process of hydraulic turbine hydraulic performance optimization; in this embodiment, the PSO optimization algorithm is introduced for global optimization, which is conducive to finding the optimal parameters of the positive guide vane of the proxy model.

[0021] like Figure 1-2 As shown, as a further embodiment, step S4 further includes: S41: Speed ​​and position update: The speed and position of the particle in the global are iteratively updated according to the approximate function of the proxy model, as follows: In the formula, and are the next speed and position respectively, c1 and c2 are constants that control the maximum step size within (0,2), r1 and r2 are acceleration weight coefficients that vary within (0,1); S42: The best position in the particle swarm. The position expression is as follows: In this embodiment, the parameters can be iteratively optimized to determine whether the design goal is achieved by comparison with the original model. If not, the PSO algorithm is iteratively optimized for the impeller blades again until the design goal is achieved.

[0022] By parameterizing the positive guide vane of the original model guide vane and optimizing it through the improved PSO optimization algorithm, the optimal parameter set of the proxy model can be obtained; the improved PSO optimization algorithm greatly improves the efficiency of optimization.

[0023] like Figure 4-5 As shown in the figure, under the premise of ensuring the efficiency of the hydraulic turbine, by comparing the numerical simulation turbulent kinetic energy cloud map and streamline map of the model before and after optimization, it can be clearly seen that the guide vane blade optimized by the improved PSO optimization algorithm improves the original flow channel of the hydraulic turbine, making its flow more stable, greatly reducing the generation of internal turbulence, and further optimizing the problem of low efficiency of the hydraulic turbine caused by the dynamic and static interference between the guide vane and the impeller.

[0024] Although embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that various changes, modifications, substitutions and variations may be made to the embodiments without departing from the principles and spirit of the present invention, and that the scope of the present invention is defined by the appended claims and their equivalents.

Claims

1. A centrifugal pump reverse hydraulic turbine guide vane optimization design method, characterized in that: The following steps are involved: Step S1: perform three-dimensional modeling of the entire flow channel water body of the original model hydraulic turbine according to basic structural parameters, draw a calculation grid, and perform simulation to obtain the external characteristic results of the original guide vane; Step S2: parameterizing the positive guide vane of the original model guide vane, and constructing expressions for the thickness and the median camber of the positive guide vane; Step S3: construct a proxy model of the original model, and then determine the relevant parameters of the guide vane shape; Step S4: optimizing the positive guide vane parameters of the proxy model using an improved PSO algorithm, and obtaining an optimal parameter set of the proxy model; Step S5: updating the blade profile of the guide vane through the optimal parameter set of the proxy model; Step S6: For the new blade type, the optimized model parameters are used to model the three-dimensional water body of the entire flow channel, and a calculation grid is drawn for CFD simulation to determine whether the design goal is achieved by comparison with the original model. If not, the PSO algorithm is iteratively optimized for the impeller blades again until the design goal is achieved.

2. The method for optimizing the guide vane design of a centrifugal pump counter-rotating hydraulic turbine according to claim 1, characterized in that: in, Step S2 also includes: S21: Parameterization of the original model guide vane and positive guide vane: Cartesian coordinate system is selected for modeling, with the leading edge of the blade arc as the origin and the X-axis direction as the axial direction; the parameters for controlling the two-dimensional blade profile are introduced, which are: X m - length of the median arc; α1-inflow angle of the median camber, defined as the angle between the tangent of the median camber at the trailing edge point and the axis X; α2-outflow angle of the median arc, defined as the angle between the tangent of the median arc at the leading edge point and the axis X; φ - the wrap angle of the median camber, defined as the angle between the leading and trailing points of the median camber; R m - The radius of the circle at the arc midline at the leading edge point; X p - Axial position of the maximum point circle of the mid-arc; R p - The radius of the maximum point circle of the middle arc; S22: Construct the blade thickness parameter expression: The thickness of the positive guide vane is determined by R(x) using quadratic curve fitting. The blade thickness can be converted into the relationship between the parameter and the coordinate X. R(x) = ax 2 +bx+c Where a=f a (R m , R p ), b=f b (R m , R p ), c = f c (R m , R p ); S23: Construct the middle arc parameter expression: The middle arc is determined by y(x) using the cubic curve fitting method. Similarly, the middle arc can be converted into the relationship between the parameters and the coordinate X. y(x) = dx 3 + ex 2 + fx + g where d = f d (α1, α2, φ), e = f e (α1, α2, φ), f = tan(α2π / 180), g = R; S24: Determine the factors affecting the blade shape: Perform Pearson coefficient correlation analysis on the blade parameterization to find the correlation.

3. The method for optimizing the guide vane design of a centrifugal pump counter-rotating hydraulic turbine according to claim 2, characterized in that: in, In step S3: Construct the approximate function of the surrogate model, evaluate the parameters, determine the relevant parameters, and the mathematical model is expressed as an equation: In the formula, y is the measured response, b0 is a constant, and b j 、b jk and b jj is the regression coefficient, X j and X k are the coded values ​​of the independent factors.

4. The method for optimizing the guide vane design of a centrifugal pump counter-rotating hydraulic turbine according to claim 3, characterized in that: in, In step S4: The improved PSO optimization algorithm is used for global optimization to solve the parameters of the positive guide vane of the proxy model. First, the algorithm initializes a group of random particles, and then obtains the optimal solution through iteration. Assume that each group consists of M particles, X={x1, x2, …, x m }, where x i =[x i1 , x i2 , …, x im ], then the initial position and velocity of the ith particle can be expressed as k A vector of dimensions: In the formula, and are the position and velocity of the i-th particle in the hydraulic turbine hydraulic performance optimization process.

5. The method for optimizing the guide vane design of a centrifugal pump counter-rotating hydraulic turbine according to claim 4, characterized in that: in, Step S4 also includes: S41: Speed ​​and position update: The speed and position of the particle in the global are iteratively updated according to the approximate function of the proxy model, as follows: In the formula, and are the next speed and position respectively, c1 and c2 are constants that control the maximum step size within (0,2), r1 and r2 are acceleration weight coefficients that vary within (0,1); S42: The best position in the particle swarm. The position expression is as follows: 。

Images