Two-way axial flow pump energy loss reduction method based on flow characteristic improvement

Abstract

The invention provides a two-way axial flow pump energy loss reduction method based on flow characteristic improvement, and relates to the technical field of two-way axial flow pump optimization. Comprising the following six steps: establishing a reference two-way axial flow pump physical model, establishing and calibrating a reference two-way axial flow pump simulation model, identifying and quantifying a dominant energy loss source, establishing an optimization scheme of the dominant energy loss source, simulating and comparing the optimization scheme, and iterating and formulating the optimization scheme. According to the method, a solid foundation is laid for optimization design by calibrating a simulation performance curve and ensuring the reliability of a numerical model, then a key energy loss source is quantitatively analyzed by adopting an entropy yield method, directional design is carried out based on a flow mechanism, the optimization efficiency and effect are remarkably improved, energy loss is reduced, and finally, through a perfect iterative optimization mechanism, the optimization efficiency is improved. And in combination with the preset target threshold value and experimental verification, it is ensured that the optimization scheme meets the actual requirement, and therefore effective reduction of the energy loss of the two-way axial flow pump is achieved.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of bidirectional axial flow pump optimization, and particularly relates to a bidirectional axial flow pump energy loss reduction method based on flow characteristic improvement. BACKGROUND

[0002] As a new type of hydraulic machinery with drainage and irrigation functions, bidirectional axial flow pumps are widely used in coastal and river pump station projects and have a significant application prospect. However, bidirectional axial flow pumps face several key problems in practical applications, which seriously restrict their performance and long-term stable operation, mainly in the form of low efficiency and instability of hydraulic performance.

[0003] Firstly, the layout structure of the guide vane and the blade of the bidirectional axial flow pump is obviously different from that of the traditional unidirectional pump, and the hydraulic performance of the bidirectional axial flow pump is significantly lower than that of the unidirectional pump. The bidirectional flow characteristic makes the pump unstable in the two flow directions, resulting in generally low efficiency of the pump under different working conditions and a large energy loss. In addition, the flow passage design and the unsteady nature of the flow state of the pump are also important reasons for the low efficiency. This efficiency defect not only leads to a significant increase in energy consumption, but also causes strong pressure pulsation and vibration problems due to the unsteady flow excitation in the flow passage, thereby causing frequent mechanical failures such as mechanical seal failure and bearing wear.

[0004] Secondly, the bidirectional axial flow pumps in the prior art usually rely on empirical design and optimization methods, and lack in-depth analysis based on flow mechanism. This makes the optimization design have great limitations and cannot achieve ideal performance improvement effect under multiple working conditions. The traditional empirical improvement method often fails to effectively identify and quantify the energy loss sources (such as impeller loss, gap loss, etc.), resulting in an unclear optimization direction and a large uncertainty in optimization effect and efficiency improvement. Although some optimization methods have tried to improve the working efficiency of the pump, due to the lack of accurate flow analysis and optimization design guidance, these methods have unsatisfactory effects in practical applications and cannot effectively solve the above problems. Therefore, the present application proposes a bidirectional axial flow pump energy loss reduction method based on flow characteristic improvement to solve the problems in the prior art. SUMMARY

[0005] In view of the above problems, the purpose of the present application is to propose a bidirectional axial flow pump energy loss reduction method based on flow characteristic improvement, which can solve the problems in the prior art by deeply integrating experimental measurement, numerical simulation and theoretical analysis.

[0006] To achieve the purpose of the present application, the present application realizes the following technical scheme: a bidirectional axial flow pump energy loss reduction method based on flow characteristic improvement, comprising the following steps:

[0007] Step one, establishment of a physical model of a reference bidirectional axial flow pump

[0008] selecting an initial bidirectional axial flow pump as a physical prototype, obtaining experimental performance curves of the physical prototype in forward rotation and reverse rotation through experimental measurement, wherein the experimental performance curves include performance data at a rated flow point, a large flow point and a small flow point;

[0009] Step two, establishment and calibration of the benchmark bidirectional axial flow pump simulation model

[0010] obtaining simulation performance curves of the physical prototype in forward rotation and reverse rotation through three-dimensional unsteady numerical simulation of the physical prototype under the same working conditions by using computational fluid dynamics software, calibrating the simulation performance curves by using the experimental performance curves to obtain calibrated performance curves, and then outputting benchmark flow field data;

[0011] Step three, identifying and quantifying the dominant energy loss source

[0012] quantitatively calculating the spatial distribution and numerical value of impeller loss, gap loss, impact loss and secondary flow loss by using the benchmark flow field data and adopting the entropy production rate method, determining the dominant energy loss source and its type with the greatest impact on pump performance by comparison, and thereby locating the dominant energy loss source;

[0013] Step four, establishment of an optimization scheme for the main energy loss source

[0014] based on the type of the dominant energy loss source determined in step three, selecting and optimizing the key geometric parameters corresponding to the dominant energy loss source to obtain an optimization scheme;

[0015] Step five, simulation and comparison of the optimization scheme

[0016] obtaining an optimized performance curve by performing three-dimensional unsteady numerical simulation of the optimization scheme under the same working conditions by using computational fluid dynamics software, comparing the optimized performance curve with the calibrated performance curve, and quantifying the comparison results in a numerical manner;

[0017] Step six, iteration and formulation of the optimization scheme

[0018] pre-setting a target numerical threshold of the comparison results, comparing the comparison results of step five with the target numerical threshold, returning to step four to modify the optimization parameters if the target numerical threshold is not reached, and taking the optimization scheme as a final scheme if the target numerical threshold is reached, and manufacturing the bidirectional axial flow pump according to the final scheme.

[0019] Further improvements are that in step one, the rated flow point, the large flow point and the small flow point are 100%, 130% and 70%, respectively.

[0020] Further improvement in, in step two, the calculation domain of the computational fluid dynamics software simulation contains the complete inlet extension pipe and outlet extension pipe, while using a structured grid, the non-dimensional wall distance y+ value of the near-wall region grid is less than 1.

[0021] Further improvement in, in step three, the entropy production rate method is based on irreversible thermodynamics principles, and the entropy production rate is directly solved by calculating the viscous dissipation function.

[0022] Further improvement in, in step four, when the category of the dominant energy loss source is impeller loss or impact loss, the key geometric parameters are blade installation angle and profile parameters.

[0023] Further improvement in, in step four, when the category of the dominant energy loss source is gap loss, the key geometric parameters are blade tip gap size and sealing structure.

[0024] Further improvement in, in step four, when the category of the dominant energy loss source is secondary flow loss, the key geometric parameters are the profile parameters of the flow passage and guide vane and the number of blades.

[0025] Further improvement in, in step six, the setting standard of the target numerical threshold is that the efficiency of the optimized pump at the rated flow point in forward rotation and reverse rotation is improved by at least N percentage points compared with the initial model, wherein N is a preset positive number.

[0026] The beneficial effects of the present application are: the present application fuses the actual product and the simulation product, calibrates the simulation performance curve by using the experimental performance curve, ensures the reliability of the numerical model in macroscopic performance prediction, guarantees the basis of subsequent optimization, and then uses the entropy production rate method to quantitatively analyze the spatial distribution and contribution degree of key loss sources such as impeller loss and gap loss, so that the optimization direction is changed from traditional empirical improvement to directional design based on flow mechanism, the optimization efficiency and effect are improved, and finally a complete iterative optimization mechanism is formed, the optimization direction is controlled by the preset target threshold, the numerical comparison and experimental verification are combined, and it is ensured that the final scheme meets the actual requirements. Therefore, the present application deeply fuses experimental measurement, numerical simulation and theoretical analysis, and realizes effective reduction of energy loss of the bidirectional axial flow pump. BRIEF DESCRIPTION OF DRAWINGS

[0027] Figure 1 is a step flow schematic diagram of the present application. DETAILED DESCRIPTION

[0028] In order to deepen the understanding of the present application, the present application will be further described in combination with embodiments, and the present embodiment is only used to explain the present application and does not constitute a limitation on the protection scope of the present application.

[0029] According to Figure 1As shown, the embodiment proposes a bidirectional axial flow pump energy loss reduction method based on flow characteristics improvement, including the following steps:

[0030] Step one, the establishment of the reference bidirectional axial flow pump physical model

[0031] Select the initial bidirectional axial flow pump as the physical prototype. For the initial bidirectional axial flow pump, it needs to be suitable for bidirectional flow operation and can meet the requirements of flow, head, etc. in actual application to provide accurate experimental data. Then, through experimental measurement, the experimental performance curve under the conditions of forward rotation and reverse rotation is obtained, which includes performance data under the conditions of rated flow point, large flow point and small flow point.

[0032] Specifically:

[0033] The rated flow point is 100% Qn (rated flow), which is the normal working state of the initial bidirectional axial flow pump under design conditions, corresponding to the rated flow and rated head of the pump;

[0034] The large flow point is 130% Qn, indicating that the pump is running under the condition of exceeding the rated flow, which is used to evaluate the performance of the pump under high load conditions;

[0035] The small flow point is 70% Qn, indicating that the pump is running under the condition of less than the rated flow, which is used to evaluate the performance of the pump under low load conditions.

[0036] Then through experimental test, the following performance data are recorded: flow, head, power, efficiency, pressure and temperature distribution, vibration and noise. At the same time, during the experiment, the test of each working point needs to be measured for several times, and the average value is calculated to reduce the experimental error.

[0037] Further, based on the data of experimental test, the experimental performance curve of the pump under different working conditions is drawn, which is composed of flow-head performance curve (change of head under different flow conditions), flow-efficiency performance curve (change of efficiency under different flow conditions) and flow-power performance curve (power demand under different flow conditions).

[0038] Step two, the establishment and calibration of the reference bidirectional axial flow pump simulation model

[0039] The same working condition three-dimensional unsteady numerical simulation of the physical prototype is carried out by using computational fluid dynamics software. For the computational fluid dynamics software, it can simulate the flow changes of fluid in different time and space, is suitable for simulating bidirectional flow, and is suitable for turbulent flow model of pump equipment such as k-ε model, RNG model, etc. and can handle the dynamic influence of rotating parts of the pump (such as impeller) and simulate fluid-solid coupling effect.

[0040] In the simulation process, the setting of the calculation domain is crucial, so the calculation domain simulated by the computational fluid dynamics software includes the complete inlet and outlet extension pipes, that is, the simulation domain not only includes the inside of the pump (pump body, impeller, guide vane), but also extends to the inlet and outlet extension pipes. The inlet extension pipe is used to ensure that the fluid can enter the pump body stably, avoiding the influence of inlet disturbance on the flow, and the outlet extension pipe is used to ensure the stability of the fluid flowing out of the pump body, avoiding the influence of outlet back pressure on the pump performance.

[0041] At the same time, structured grids are used to divide the space in the calculation domain into small grid units, and the near-wall region grid is set to be fine enough near the solid surfaces of the pump shell, impeller, etc., to ensure the accurate calculation of the fluid boundary layer. Correspondingly, the near-wall region grid has a dimensionless wall distance y+ value less than 1, which ensures that the flow characteristics near the wall, especially the formation of vortex and turbulent boundary layer, can be accurately captured.

[0042] Further, the k-ε model is selected for CFD (computational CFD simulation accuracy) simulation, which is used for most engineering flows, especially external flows and unsteady flows of pump equipment. Correspondingly, in the CFD simulation, the flow characteristics of the pump in forward rotation (simulating the flow of the pump under normal working conditions, the pump impeller and guide vane rotate at a specified speed, and the fluid flows in the expected direction) and reverse rotation (simulating the performance of the pump in reverse flow, the direction of the impeller speed is opposite to that in the forward working condition, and the flow direction and head of the pump change) must be considered respectively, so the simulation performance curves of the pump in forward and reverse states are obtained.

[0043] Then, the simulation performance curves are calibrated using the experimental performance curves, that is, the experimental data and simulation data are compared, and the error is calculated (the error is set to a threshold condition, for example, 2%, so when the error is controlled within 2%, the calibration is completed), when the error does not meet the threshold condition, the turbulence model, boundary condition and other physical model parameters in the simulation model are adjusted according to the experimental data to ensure that the simulation results are consistent with the actual situation, and the calibrated performance curves are obtained, and then the benchmark flow field data is output.

[0044] For the benchmark flow field data, it includes flow distribution (flow distribution of each part of the pump, which helps to analyze the flow conditions in different regions), velocity vector diagram (which shows the velocity distribution of the fluid in the pump, especially in the impeller and guide vane area), turbulent kinetic energy distribution (which shows the intensity distribution of the turbulent flow in the flow field, which helps to understand the source of energy loss), pressure distribution cloud map (which shows the pressure distribution in the pump, which helps to analyze the source of pressure drop and loss), and efficiency distribution (which calculates the efficiency of different regions to evaluate the overall performance of the pump and the contribution of each part).

[0045] Step three, identify and quantify the dominant energy loss source

[0046] With the benchmark flow field data, the entropy generation rate method is used to quantitatively calculate the spatial distribution and numerical value of the impeller loss, gap loss, impact loss and secondary flow loss. Among them, the entropy generation rate method is based on the principle of irreversible thermodynamics, and the entropy generation rate is directly solved by calculating the viscous dissipation function. Entropy generation rate is an effective method to measure energy loss in fluid system. Correspondingly, the entropy generation rate (S gen ) is calculated as follows:

[0047]

[0048] In the formula, µ is the dynamic viscosity of the fluid, T is the temperature, u is the flow rate, is the velocity gradient, is the temperature gradient, dV is the micro volume element, which represents the volume of each small area in the calculation domain.

[0049] Then by using the entropy generation rate method, the energy loss distribution of each region in the bidirectional axial flow pump can be calculated. Further, according to the calculation results of entropy generation rate, the energy loss in the bidirectional axial flow pump is classified into the following four kinds:

[0050] Impeller loss: energy loss caused by friction between impeller surface and fluid and fluid pressure difference;

[0051] Gap loss: energy loss caused by the gap between the impeller and the pump shell;

[0052] Impact loss: when the fluid flow does not match the design of the leading edge of the impeller, the fluid will have a discontinuous impact, resulting in local energy loss;

[0053] Secondary flow loss: loss caused by flow separation, vortex motion or unstable flow of fluid in the pump shell, guide vane, volute and other areas.

[0054] Therefore, when performing entropy generation rate analysis, the calculation domain needs to be divided into multiple control volumes (grid elements), the entropy generation rate of each element is calculated, and the energy loss distribution in the pump is obtained on this basis. Specifically:

[0055] Quantification of impeller loss: by calculating the pressure difference between the impeller surface and the blade working surface and the suction surface, the friction loss and the shear stress distribution of the fluid, the entropy generation rate distribution of the impeller loss is obtained;

[0056] Quantification of gap loss: calculate the flow distribution at the blade tip, especially the fluid leakage and turbulent loss between the blade tip and the pump shell, and quantify its contribution to the total loss;

[0057] Quantification of impact loss: by the impact of fluid and blade leading edge and the influence of flow mismatch under non-design conditions, the energy loss caused by it is quantified;

[0058] Quantification of secondary flow loss: calculate the loss caused by flow separation, vortex and turbulence in the guide vane and pump casing, and determine the spatial distribution of secondary flow loss.

[0059] Thus, by adopting the entropy generation rate method to quantitatively calculate the spatial distribution and numerical value of impeller loss, gap loss, impact loss and secondary flow loss, and then comparing to determine the dominant energy loss source and its type that has the greatest impact on pump performance, i.e. according to the spatial distribution of entropy generation rate, comparing the numerical value of different loss sources to identify the dominant energy loss source that has the greatest impact on pump performance, and then judging the type of loss source according to the distribution characteristics of entropy generation rate.

[0060] Thus, the dominant energy loss source is located

[0061] Step four, establish an optimization scheme for the main energy loss source

[0062] Based on the category of the dominant energy loss source determined in step three, the key geometric parameters corresponding to it are selected for optimization design, and an optimization scheme is obtained. Specifically:

[0063] When the category of the dominant energy loss source is impeller loss or impact loss, the key geometric parameters are blade installation angle and profile parameters, wherein the installation angle of the blade determines the angle at which the fluid enters the impeller. If the installation angle is too large or too small, it may cause the fluid and the blade surface to be mismatched, resulting in unnecessary pressure loss or impact loss, affecting the efficiency of the pump. Therefore, the blade installation angle is adjusted to maximize the forward and reverse efficiency of the pump under different operating conditions, especially under large and small flow operating conditions, and the optimal angle is adjusted to reduce impact loss and flow resistance in the impeller. The profile parameters are the shape of the blade profile (such as thickness, curvature, bending position, etc.), which directly affects the fluid dynamic performance of the blade. Therefore, by adjusting the profile of the blade, the blade surface is made smoother and more streamlined to reduce the energy loss of the fluid in the impeller and optimize the pressure distribution on the blade surface;

[0064] When the category of the dominant energy loss source is gap loss, the key geometric parameters are the size of the tip clearance and the sealing structure, wherein the size of the tip clearance refers to the gap between the impeller and the pump casing, which can cause part of the fluid to leak, resulting in energy loss. Therefore, the size of the tip clearance is adjusted to ensure that the fluid remains in the impeller during high-efficiency operation and to avoid excessive leakage. The sealing structure is a design of a labyrinth sealing structure, which forms multiple sealing rings between the tip and the pump casing to reduce fluid leakage and pressure drop and reduce energy loss caused by fluid leakage;

[0065] When the category of the dominant energy loss source is secondary flow loss, the key geometric parameters are the profile parameters of the flow passage and the guide vanes and the number of vanes, wherein the profile parameters of the flow passage are the geometric shape of the flow passage (including curvature, width, etc.), which directly affect the flow stability of the fluid, and therefore the curvature and width of the flow passage are optimized to reduce flow separation and vortex, improve the path of the fluid through the pump, and reduce secondary flow loss. The profile parameters of the guide vanes (the curvature of the vanes, the inlet angle, etc.) directly affect the flow pattern of the fluid, and therefore the profile parameters of the guide vanes are adjusted to ensure the continuity of the flow on the surface of the guide vanes, reduce vortex and flow separation, and reduce secondary flow loss. By reasonably selecting the number of vanes, excessive vortex can be avoided, and the flow stability of the fluid can be improved, and therefore the optimal number of vanes is selected according to the actual working condition, the flow stability and the friction loss are balanced, and the secondary flow loss is reduced.

[0066] In the optimization process, a multi-objective optimization algorithm (genetic algorithm) is used to consider multiple objectives (such as efficiency improvement and energy loss minimization) at the same time, and the optimization design is performed to ensure that the performance of the optimized scheme under various working conditions is optimal. Finally, based on the optimized geometric parameters and structure, an optimized design scheme of the pump is generated.

[0067] Step five, simulation and comparison of the optimized scheme

[0068] According to the optimized scheme of step four, three-dimensional unsteady numerical simulation under the same working conditions is performed through computational fluid dynamics software, the working condition is the same as that of step two, and the optimized performance curve is obtained. The optimized performance curve is compared with the calibrated performance curve, and the comparison includes flow-head comparison (comparison of whether the optimized design improves the head under different flow conditions), flow-efficiency comparison (comparison of the efficiency improvement of the optimized design, especially at the rated flow point and the large flow point), and flow-power comparison (comparison of whether the optimized design reduces power consumption, especially at the large flow point and the small flow point).

[0069] In order to ensure the objectivity and accuracy of the comparison results, the comparison results are quantified in numerical form, that is, the results are quantified as percentage values.

[0070] Step six, iteration and formulation of the optimized scheme

[0071] The target numerical threshold of the comparison result is set in advance, and the target numerical threshold refers to the performance improvement standard that the optimized scheme should reach, and therefore the setting standard is that the efficiency of the optimized pump at the rated flow point in forward rotation and reverse rotation is improved by at least N percentage points compared with the initial model, wherein N is a positive number, for example, if N=3, the efficiency of the optimized pump should be improved by more than or equal to 3%. Correspondingly, the threshold is usually set according to the design requirements and application scenarios of the pump, and if the application scenario has higher energy saving requirements (such as high load operation and long time use), the threshold should be increased accordingly.

[0072] Then, the comparison result of step five (comparison of the optimized performance curve and the calibration performance curve) is compared with a target numerical threshold.

[0073] If the target numerical threshold is not reached, the optimization parameters are modified in step four.

[0074] If the target numerical threshold is reached, it is confirmed that the optimized design meets the expected target, and then the optimized scheme is taken as the final scheme, and the bidirectional axial flow pump is manufactured according to the final scheme.

[0075] The above shows and describes the basic principles, main features and advantages of the present application. It should be understood by those skilled in the art that the present application is not limited to the above embodiments, and the above embodiments and descriptions in the specification are only to illustrate the principles of the present application. Without departing from the framework and scope of the present application, various changes and improvements can be made to the present application, and these changes and improvements all fall within the scope of the claimed present application. The scope of protection of the present application is defined by the appended claims and their equivalents.

Claims

1. A method for reducing energy loss in a bidirectional axial flow pump based on improved flow characteristics, characterized in that: Includes the following steps: Step 1: Establishment of the physical model of the benchmark bidirectional axial flow pump An initial bidirectional axial flow pump was selected as the physical prototype. Its experimental performance curves in forward and reverse rotation states were obtained through experimental measurement. The experimental performance curves include performance data at rated flow point, high flow point and low flow point. Step 2: Establishment and calibration of the benchmark bidirectional axial flow pump simulation model The physical prototype was subjected to a three-dimensional unsteady numerical simulation under the same working conditions using computational fluid dynamics software. The simulated performance curves under forward and reverse rotation states were obtained. The simulated performance curves were calibrated using the experimental performance curves to obtain the calibrated performance curves, and then the reference flow field data were output. Step 3: Identify and quantify the dominant energy loss sources Using benchmark flow field data, the spatial distribution and magnitude of impeller loss, clearance loss, impact loss and secondary flow loss are quantitatively calculated using the entropy yield method. By comparison, the dominant energy loss sources and their types that have the greatest impact on pump performance are determined, thereby locating the dominant energy loss sources. Step 4: Establish optimization schemes for major energy loss sources. Based on the category of the dominant energy loss source determined in step three, the corresponding key geometric parameters are selected for optimization design to obtain the optimization scheme; Step 5: Simulation and Comparison of Optimization Schemes Based on the optimization scheme in step four, a three-dimensional unsteady numerical simulation under the same working conditions is performed using computational fluid dynamics software to obtain the optimized performance curve. The optimized performance curve is then compared with the calibration performance curve, and the comparison results are quantified numerically. Step Six: Iteration and Formulation of Optimization Schemes A target value threshold for the comparison results is preset, and then the comparison results in step five are compared with the target value threshold. If the target value threshold is not reached, the process returns to step four to modify the optimization parameters. If the target value threshold is reached, the optimization scheme is taken as the final scheme, and the bidirectional axial flow pump is manufactured according to the final scheme.

2. The method for reducing energy loss in a bidirectional axial flow pump based on improved flow characteristics according to claim 1, characterized in that: In step one, the rated flow point, high flow point, and low flow point are 100%, 130%, and 70%, respectively.

3. The method for reducing energy loss in a bidirectional axial flow pump based on improved flow characteristics according to claim 1, characterized in that: In step two, the computational domain simulated by the computational fluid dynamics software includes the complete inlet extension pipe and outlet extension pipe, and a structured mesh is used, with the dimensionless wall distance y+ value of the mesh in the near-wall region being less than 1.

4. The method for reducing energy loss in a bidirectional axial flow pump based on improved flow characteristics according to claim 1, characterized in that: In step three, the entropy yield method is based on the principle of irreversible thermodynamics and directly solves for the entropy yield by calculating the viscous dissipation function.

5. The method for reducing energy loss in a bidirectional axial flow pump based on improved flow characteristics according to claim 1, characterized in that: In step four, when the dominant energy loss source is impeller loss or impact loss, the key geometric parameters are the blade mounting angle and profile parameters.

6. The method for reducing energy loss in a bidirectional axial flow pump based on improved flow characteristics according to claim 1, characterized in that: In step four, when the dominant energy loss source is gap loss, the key geometric parameters are the tip clearance size and the sealing structure.

7. The method for reducing energy loss in a bidirectional axial flow pump based on improved flow characteristics according to claim 1, characterized in that: In step four, when the dominant energy loss source is secondary flow loss, the key geometric parameters are the profile parameters of the flow channel and guide vanes and the number of blades.

8. The method for reducing energy loss in a bidirectional axial flow pump based on improved flow characteristics according to claim 1, characterized in that: In step six, the standard for setting the target numerical threshold is: the efficiency of the optimized pump in forward and reverse rotation at the rated flow point is improved by at least N percentage points compared with the initial model, where N is a preset positive number.

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