Optimization method of guide vane based on model-to-prototype conversion of guide vane karman vortex of hydraulic turbine

Abstract

The application discloses a guide vane optimization method based on model-to-prototype water turbine guide vane Karman vortex conversion, and relates to the technical field of fluid machinery and engineering equipment. m ; S3, Karman vortex frequency f p of the prototype water turbine is calculated; S4, whether the prototype water turbine meets the vibration avoidance requirement is judged according to the Karman vortex frequency f p of the prototype water turbine, if not, the guide vane is optimized and steps S1-S4 are repeated until the vibration avoidance requirement can be met; and S5, the method ends. The application solves the calculation problem of Karman vortex shedding in the double-row cascade area of the water turbine. By constructing the water turbine model with the same proportion, the vortex separation point distribution circle diameter and the Karman vortex shedding frequency of the water turbine model are obtained, and then the vortex separation point position and the Karman vortex shedding frequency of the prototype are obtained, so that the guide vane is optimized.

Description

Technical Field

[0001] This invention relates to the field of fluid machinery and engineering equipment technology, and in particular to a guide vane optimization method based on Karman vortex conversion from model to prototype water turbine guide vanes. Background Technology

[0002] Currently, the main methods for calculating the Karman vortex frequency in the double-row blade region of a water turbine are: 1. Analytical methods based on a simplified single-blade model; 2. Transient numerical simulation of the entire flow field relying on CFD; 3. Posterior methods relying on model tests or real machine tests.

[0003] The analytical method based on a simplified single-blade cascade model is based on the core idea of ​​simplifying the source of the Karman vortex as an independent single-row cascade. It primarily relies on the classical Karman vortex frequency formula (Formula 1) for calculation, where the Struhauer number (St) is often derived from experimental data of standard geometries (such as cylinders or isolated airfoils). A drawback is that it neglects the periodic effect of the upstream flow field. In reality, the upstream operates in an unsteady incoming flow with varying intensity, direction, and frequency, which significantly alters the Karman vortex shedding frequency (f) and the Struhauer number (St). Therefore, the predicted results deviate considerably from actual operating conditions. Parameter distortion also exists: the incoming flow velocity (V) in the formula is not a constant value. The selection of characteristic thickness (L) often ignores the influence of boundary layer thickness, or it is difficult to accurately determine the location of the separation point. In order to capture complex flow fields more accurately, CFD full-flow field transient numerical simulation usually adopts three-dimensional, full-channel, transient CFD technology. By solving the unsteady Navier-Stokes equations, the entire process of Karman vortex generation, shedding and evolution from the guide vane to the runner is simulated.

[0004] The main drawback of analytical methods based on simplified single-leaf grating models is their extremely high computational cost: analyzing microscale vortex shedding requires an extremely dense computational grid and a very small physical time step, resulting in a single calculation consuming enormous computational resources (lasting several weeks) and incurring significant hardware costs. This makes them completely unsuitable for rapid iteration and optimization in the engineering design phase. Furthermore, the computation and result analysis processes are complex, making integration into convenient engineering design tools impossible, and lacking universality and ease of use.

[0005] For model turbines, which are relatively small in size (the runner diameter D of a model turbine is about 300-400mm), the computational load and manpower cost of obtaining the Karman vortex shedding frequency in the double-row blade cascade region using CFD calculations are acceptable. However, for calculating the Karman vortex shedding frequency in the double-row blade cascade region of a full-scale turbine, the computational load and manpower cost using CFD calculations are too large.

[0006] Post-hoc methods relying on model testing or real-machine testing directly measure pressure pulsations or vibration signals on the blade surface using equipment such as pressure sensors and dynamic strain gauges, and identify the Karman vortex frequency through spectral analysis. The main drawbacks are: hysteresis and high cost risk: this method can only be performed after product manufacturing is complete, belonging to "post-hoc verification." Lack of predictive capability: the essence of this method is measurement rather than prediction, and it cannot proactively avoid risks during the design phase. Summary of the Invention

[0007] This invention aims to provide a guide vane optimization method based on the Karman vortex conversion from model to prototype turbine guide vanes, solving the computational challenge of Karman vortex shedding in the double-row blade region of a turbine. Through derivation and analysis, it is found that the Karman vortex shedding frequency is mainly related to the guide vane opening and the diameter of the distribution circle at the vortex separation point. By constructing a scaled-down turbine model, the diameter of the vortex separation point distribution circle and the Karman vortex shedding frequency of the turbine model are obtained, and then the vortex separation point location and Karman vortex shedding frequency of the prototype are obtained, thereby optimizing the guide vane.

[0008] To achieve the above-mentioned objectives, the technical solution of the present invention is as follows: A guide vane optimization method based on Karman vortex transformation from model to prototype turbine guide vanes includes the following steps: S1. Based on the prototype turbine design scheme, construct a scaled-down turbine model; S2. The Karman vortex frequency f of the turbine model is obtained through simulation. m ; S3, Karman vortex frequency f obtained through the turbine model m The Karman vortex frequency f of the prototype turbine was calculated. p ; S4. The Karman vortex frequency f of the prototype turbine p Determine whether the prototype turbine meets the vibration damping requirements. If not, optimize the guide vanes and repeat steps S1-S4 until the vibration damping requirements are met. S5, End.

[0009] In step S1, the runner size of the turbine model is greater than or equal to 0.25m; The runner size of a mixed-flow turbine is greater than or equal to 0.25m; the runner size of an oblique-flow turbine and an axial-flow turbine is greater than or equal to 0.3m. The model runner size cannot be smaller than the minimum value in order to ensure that the scale is not too large. The purpose is to ensure that the model and the prototype have good hydraulic similarity, to ensure that the normal manufacturing process can achieve the required dimensional accuracy, and to ensure the accuracy of test measurements, etc.

[0010] In step S1, the turbine model is a three-dimensional CFD flow field simulation model; In step S1, constructing the three-dimensional CFD flow field simulation model includes the following steps: S11. Construct a geometric model based on the dimensions of the model turbine; S12. Mesh the geometric model; S13. Establish a three-dimensional CFD flow field simulation model based on the geometric model after mesh generation; Step S2 includes the following steps: S21. Set the operating parameters in the three-dimensional CFD flow field simulation model. The operating parameters include flow rate and rotational speed. S22. Based on the three-dimensional CFD flow field simulation model, CFD simulation calculations were performed to obtain the Karman vortex shedding frequency of the double-row cascade. f m and the location of the separation point.

[0011] In step S21, setting the flow rate includes: constructing geometric models with different active guide vane openings, dividing the geometric models into meshes, selecting the geometric model with the required flow rate corresponding to the active guide vane opening to establish a three-dimensional CFD flow field simulation model for CFD simulation calculation.

[0012] In step S21, setting the rotational speed includes: calculating the model turbine rotational speed based on the unit rotational speed of an existing turbine when a Karman vortex occurs using the following formula: n 11 = (n*D) / sqrt(H); Where, n 11 n is the unit speed at which the existing turbine generates the Karman vortex; D is the turbine speed of the model; H is the runner diameter of the model turbine; and H is the head of the model turbine, which is a fixed value.

[0013] In step S1, the turbine model is a physical installation model; In step S1, constructing a scaled-down water turbine model specifically involves: machining the model water turbine according to its dimensions and installing it on a water turbine model test bench; Step S2 includes the following steps: S201. According to the test conditions, adjust the model turbine to the corresponding guide vane opening, set the motor to the corresponding speed, and start the test; S202. During the test, when the aperture is increased to the point where Karman vortices occur, the test personnel use non-contact measuring instruments to measure the location of the Karman vortex separation point and the vortex shedding frequency of the double-row blade cascade. f m ; In step S3, the Karman vortex frequency f of the prototype turbine is calculated through the following steps.p : S31. The incoming flow velocity of the water turbine is calculated using the following formula (1). V : V= Q / S' =Q / πD'bks =Q / k 1 D 2 (1) Q This represents the flow rate of the turbine passing through the double-row blade section at this time. S’ The area of ​​the water flow channel at the vortex separation point of the double-row blade grating; D’ The diameter of the distribution circle at the vortex separation point on the guide vane; b This refers to the guide vane height. k S This is a correction factor that adjusts the area of ​​the flow channel occupied by the guide vane at the vortex separation point. πD' B' The calculated area is actually larger than the channel area, so it needs to be corrected. k S =a / (L+a) , 0<kS<1 ; a For the opening degree of the guide vanes; L is the characteristic length of the blunt body, and in a double-row cascade, it is the distance between the vortex separation points on both sides of the guide vane; Let the coefficient k 1 =k S πbD' / D 2 ; D The diameter of the rotor is a fixed value. The following formula (2) is obtained: V=Q / k 1 D 2 (2); S32. The flow rate of the water turbine is calculated using the following formula (3): Q= nφD 3 π 2 / 240 (3) in, n This refers to the turbine speed; φ The turbine flow coefficient is positively correlated with the opening of the movable guide vanes. Let the coefficient k 2 =π 2 / 240, resulting in the following formula (4). Q=k 2 nφD 3 (4); S33. Substituting formulas (2) and (4) into formula (5) yields formula (6): f = S t V / L (5) f = St ( k 2 nφD) / (k 3 k 1 D) (6) in, f The frequency of turbine detachment; S t For Struhar numbers; V The incoming flow velocity to the water turbine; L is the characteristic length of the blunt body, and in a double-row cascade, it is the distance between the vortex separation points on both sides of the guide vane; S34. Formula (6) yields the following formula (7): f / n = St ( k 2 φ ) / ( k 3 k 1) Let the coefficient K=St k 2 / ( k 3 k 1), thus obtaining the following formula (8): f / n = Kφ (8); The coefficient K is a dimensionless number. As can be seen from formula (8), the main factor determining the Karman vortex shedding frequency is the flow coefficient. φ The guide vane opening and distribution circle diameter of the actual turbine and the model strictly adhere to the law of geometric similarity, while the flow coefficient... φ The flow coefficient is positively correlated with the opening of the movable guide vanes. When the opening of the movable guide vanes of the turbine model and the prototype turbine are the same, the flow coefficient of the turbine model and the prototype turbine is positively correlated. φ They are equal; therefore, the Karman vortex shedding frequency of the actual machine can be calculated by the following formula (9). f p : f p = n p f m / n m (9) Where: f pThe Karman vortex frequency of the prototype turbine; f m The Karman vortex frequency of the turbine model; n p The rotational speed of the prototype water turbine; n m The rotational speed of the water turbine model; Step S4 includes the following steps: S41. Obtain the natural frequencies of the actual machine structure through modal calculation. f ; S42, the natural frequency f Frequency of Karman vortex shedding from the actual machine f p Compare, if the inherent frequency f Karman vortex shedding frequency on the actual machine f p If the value is within -10% to +10%, the risk of turbine vibration is relatively high. S43. For high-risk turbines, modify the guide vane design, reconstruct a scaled-down turbine model, and calculate the Karman vortex shedding frequency until the Karman vortex shedding frequency differs significantly from the structure's natural frequency, thus meeting the vibration avoidance requirements.

[0014] The beneficial effects of this invention are: 1. This invention primarily addresses the calculation of Karman vortex shedding in the double-row blade region of a hydraulic turbine. By defining relevant parameters and conducting analysis, it can be deduced that the Karman vortex shedding frequency is mainly related to the guide vane opening and the diameter of the distribution circle at the vortex separation point. Through CFD calculations and other methods, the separation point location and vortex shedding frequency of the Karman vortex in the model turbine are obtained. Through scale conversion, the separation point location of the Karman vortex in the actual turbine can be obtained, and its shedding frequency is correlated with the shedding frequency of the model turbine at the same opening.

[0015] 2. The present invention uses model experiments or model CFD calculations, which has the advantage of quickly obtaining the Karman vortex shedding frequency in the double-row blade cascade region during the unit design stage. Compared with actual machine calculations (which require more meshes due to the large size of the actual machine), it saves time and computing resources, and facilitates the optimization design of the guide vanes.

[0016] 3. The scale of the proportionally reduced model in this invention serves to better simulate the performance of the actual aircraft through model testing, facilitating the measurement of the Karman vortex shedding frequency and separation point location of the model's double-row cascade. Since Karman vortices are difficult to measure on a real double-row cascade, the Karman vortex frequency of the real aircraft can be obtained through the operation of this invention.

[0017] 4. In this invention, if Karman vortices appear in the actual generator, they can cause vibration and noise, affecting the safety of the power plant unit. This invention predicts the Karman vortex frequency of the actual generator's double-bladed cascade to guide the structural design, so as to avoid resonant frequencies and ensure the safe and stable operation of the unit. Attached Figure Description Figure 1 This is a flowchart illustrating the guide vane optimization method based on Karman vortex conversion from model to prototype turbine guide vanes according to the present invention.

[0018] Figure 2 This is a schematic diagram of the three-dimensional CFD flow field simulation model in Application Example 1 of the present invention.

[0019] Figure 3 This is a schematic diagram of the physical installation model in application example 2 of the present invention. Detailed Implementation

[0020] The present invention will be further described in detail below with reference to embodiments, but the implementation of the present invention is not limited thereto.

[0021] Example: This invention provides a method such as Figure 1 The guide vane optimization method shown is based on the Karman vortex conversion from model to prototype turbine guide vanes, and includes the following steps: S1. Based on the prototype turbine design scheme, construct a scaled-down turbine model; S2. The Karman vortex frequency f of the turbine model is obtained through simulation. m ; S3, Karman vortex frequency f obtained through the turbine model m The Karman vortex frequency f of the prototype turbine was calculated. p ; S4. The Karman vortex frequency f of the prototype turbine p Determine whether the prototype turbine meets the vibration damping requirements. If not, optimize the guide vanes and repeat steps S1-S4 until the vibration damping requirements are met. S5, End.

[0022] This invention constructs a scaled-down model to obtain the Karman vortex frequency, which is then converted to the actual turbine frequency. This frequency is used to determine vibration damping compliance and iteratively optimize the design. Its purpose is to translate theoretical conversion methods into actionable engineering steps, clarifying the key aspects of model construction, frequency calculation, actual turbine conversion, vibration damping verification, and design iteration. It enables rapid prediction of Karman vortex risks in the actual turbine during the design phase, significantly reducing the cost of full-flow-field CFD calculations and the lag in actual turbine testing. This provides precise guidance for guide vane structure optimization, effectively avoiding resonance ranges, ensuring the safe operation of the turbine's double-row blade region, and improving design efficiency and reliability.

[0023] In an optional embodiment of the present invention, in step S1, the runner size of the turbine model is greater than or equal to 0.25m; the runner size of the mixed-flow turbine is greater than or equal to 0.25m; and the runner size of the diagonal-flow turbine and the axial-flow turbine is greater than or equal to 0.3m.

[0024] In this invention, in accordance with the IEC 60193 standard, for reaction turbines, the diameter of the model runner is not less than 0.25m to 0.30m (mixed-flow type: not less than 0.25m; diagonal-flow type: not less than 0.30m; axial-flow type: not less than 0.30m). The model runner size cannot be less than the minimum value in order to ensure that the scale is not too large, so as to ensure that the model and the prototype have good hydraulic similarity, ensure that normal manufacturing process can achieve the required dimensional accuracy, and ensure the accuracy of test measurement, etc.

[0025] In an optional embodiment of the present invention, in step S1, the turbine model is a three-dimensional CFD flow field simulation model; the construction of the three-dimensional CFD flow field simulation model in step S1 includes the following steps: S11. Construct a geometric model based on the dimensions of the model turbine; S12. Mesh the geometric model; S13. Establish a three-dimensional CFD flow field simulation model based on the geometric model after mesh generation.

[0026] In this invention, digital modeling is completed in three steps: establishing a geometric model according to the model dimensions, mesh generation, and establishing a 3D CFD flow field simulation model. This provides a high-precision, repeatable virtual simulation platform for calculating the Karman vortex frequency, replacing physical models and eliminating the need for fabrication and installation. By constructing a scaled-down 3D CFD flow field simulation model, the modeling cycle is significantly shortened, experimental costs and hardware investment are reduced, and the guide vane structure and operating parameters can be flexibly adjusted. It can quickly adapt to multiple iterative schemes, accurately obtain flow field details and Karman vortex characteristics in the double-row blade region, and provide reliable data support for subsequent frequency conversion and guide vane optimization, improving design efficiency and simulation accuracy.

[0027] In an optional embodiment of the present invention, step S2 includes the following steps: S21. Set the operating parameters in the three-dimensional CFD flow field simulation model. The operating parameters include flow rate and rotational speed. S22. Based on the three-dimensional CFD flow field simulation model, CFD simulation calculations were performed to obtain the Karman vortex shedding frequency of the double-row cascade. f m and the location of the separation point.

[0028] In step S21, setting the flow rate includes: constructing geometric models with different active guide vane openings, dividing the geometric models into meshes, selecting the geometric model with the required flow rate corresponding to the active guide vane opening to establish a three-dimensional CFD flow field simulation model for CFD simulation calculation.

[0029] In step S21, setting the rotational speed includes: calculating the model turbine rotational speed based on the unit rotational speed of an existing turbine when a Karman vortex occurs using the following formula: n 11 = (n*D) / sqrt(H); Where, n 11 n is the unit speed at which the existing turbine generates the Karman vortex; D is the turbine speed of the model; H is the runner diameter of the model turbine; and H is the head of the model turbine, which is a fixed value.

[0030] In this invention, operating parameters such as flow rate and rotational speed are set in a three-dimensional CFD flow field simulation model. The target flow rate is matched by a multi-aperture geometric model and mesh generation to conduct simulation calculations to obtain the Karman vortex shedding frequency and separation point location. The true flow state of the double-row blade region of the model turbine is reproduced, and the quantitative extraction of Karman vortex characteristics is completed. Key data can be efficiently obtained without physical experiments, supporting rapid traversal across multiple openings and operating conditions. This ensures accurate and reliable frequency and separation point location calculations, providing stable input for subsequent frequency conversion from model to prototype and guide vane vibration damping verification, significantly improving simulation efficiency and design iteration speed.

[0031] In an optional embodiment of the present invention, in step S1, the turbine model is a physical installation model; In step S1, constructing a scaled-down water turbine model specifically involves: machining the model water turbine according to its dimensions and installing it on a water turbine model test bench; Step S2 includes the following steps: S201. According to the test conditions, adjust the model turbine to the corresponding guide vane opening, set the motor to the corresponding speed, and start the test; S202. During the test, when the aperture is increased to the point where Karman vortices occur, the test personnel use non-contact measuring instruments to measure the location of the Karman vortex separation point and the vortex shedding frequency of the double-row blade cascade. f m .

[0032] In this invention, a physical installation model is used for testing. The model is fabricated to a scaled-down size and installed on a test bench. Tests are conducted by adjusting the guide vane opening and motor speed. The location of the Karman vortex separation point and the shedding frequency are measured using non-contact instruments. This physical experiment realistically reproduces the flow field and vortex shedding characteristics of the double-row blade region, obtaining highly reliable measured data to provide experimental basis for the conversion of Karman vortex frequencies. The measurement results from the physical installation model closely approximate the actual machine, ensuring data accuracy and verifying the accuracy of simulation results. Non-contact measurement does not interfere with the flow field, guaranteeing accuracy and providing solid experimental support for frequency conversion, vibration damping assessment, and guide vane optimization, thus enhancing the reliability of the solution.

[0033] In an optional embodiment of the present invention, in step S3, the Karman vortex frequency f of the prototype turbine is calculated through the following steps. p : S31. The incoming flow velocity of the water turbine is calculated using the following formula (1). V : V= Q / S' =Q / πD'bks =Q / k 1 D 2 (1) Q This represents the flow rate of the turbine passing through the double-row blade section at this time. S’ The area of ​​the water flow channel at the vortex separation point of the double-row blade grating; D’ The diameter of the distribution circle at the vortex separation point on the guide vane; b This refers to the guide vane height. k S This is a correction factor that adjusts the area of ​​the flow channel occupied by the guide vane at the vortex separation point. πD' B' The calculated area is actually larger than the channel area, so it needs to be corrected. k S =a / (L+a) , 0<kS<1 ; a For the opening degree of the guide vanes; L is the characteristic length of the blunt body, and in a double-row cascade, it is the distance between the vortex separation points on both sides of the guide vane; Let the coefficient k 1 =k S πbD' / D 2 ; D The diameter of the rotor is a fixed value. The following formula (2) is obtained: V=Q / k 1 D 2 (2); S32. The flow rate of the water turbine is calculated using the following formula (3): Q= nφD 3 π 2 / 240 (3) in, n This refers to the turbine speed; φ The turbine flow coefficient is positively correlated with the opening of the movable guide vanes. Let the coefficient k 2 =π 2 / 240, resulting in the following formula (4). Q=k 2 nφD 3 (4); S33. Substituting formulas (2) and (4) into formula (5) yields formula (6): f = S t V / L (5) f = St ( k 2 nφD) / (k 3 k 1 D) (6) in, f The frequency of turbine detachment; S t For Struhar numbers; V The velocity of the incoming flow to the water turbine; L is the characteristic length of the blunt body, and in a double-row cascade, it is the distance between the vortex separation points on both sides of the guide vane; S34. Formula (6) yields the following formula (7): f / n = St ( k 2 φ ) / ( k 3 k 1) Let the coefficient K=St k 2 / ( k 3 k 1), thus obtaining the following formula (8): f / n = Kφ (8); The coefficient K is a dimensionless number. As can be seen from formula (8), the main factor determining the Karman vortex shedding frequency is the flow coefficient. φThe guide vane opening and distribution circle diameter of the actual turbine and the model strictly adhere to the law of geometric similarity, while the flow coefficient... φ The flow coefficient is positively correlated with the opening of the movable guide vanes. When the opening of the movable guide vanes of the turbine model and the prototype turbine are the same, the flow coefficient of the turbine model and the prototype turbine is positively correlated. φ They are equal; therefore, the Karman vortex shedding frequency of the actual machine can be calculated by the following formula (9). f p : f p = n p f m / n m (9) Where: f p The Karman vortex frequency of the prototype turbine; f m The Karman vortex frequency of the turbine model; n p The rotational speed of the prototype water turbine; n m This represents the rotational speed of the water turbine model.

[0034] In this invention, the Karman vortex frequency conversion from the model to the prototype turbine is derived, establishing a scientific frequency conversion relationship between the model and the prototype. The correlation between frequency and guide vane opening and flow coefficient is clarified, enabling accurate calculation of the actual turbine frequency from the model frequency. This method quickly obtains reliable Karman vortex frequencies of the actual turbine without requiring costly CFD calculations or experiments, significantly reducing calculation and testing costs. It provides accurate data for subsequent vibration damping assessment and guide vane optimization, ensuring scientific conversion results and efficient and feasible engineering applications.

[0035] In an optional embodiment of the present invention, step S4 includes the following steps: S41. Obtain the natural frequencies of the actual machine structure through modal calculation. f ; S42, the natural frequency f Frequency of Karman vortex shedding from the actual machine f p Compare, if the inherent frequency f Karman vortex shedding frequency on the actual machine f p If the value is within -10% to +10%, the risk of turbine vibration is relatively high. S43. For high-risk turbines, modify the guide vane design, reconstruct a scaled-down turbine model, and calculate the Karman vortex shedding frequency until the Karman vortex shedding frequency differs significantly from the structure's natural frequency, thus meeting the vibration avoidance requirements.

[0036] In this invention, the natural frequencies of the actual turbine structure are obtained through modal calculations and compared with the Karman vortex shedding frequencies to determine whether they fall within the ±10% resonance risk range. For high-risk solutions, the guide vane design is modified and recalculated iteratively. A clear vibration avoidance judgment standard and closed-loop optimization process are established to proactively identify resonance hazards during the design phase and optimize the guide vanes. This allows for rapid identification of vibration risks, preventing resonance failures after the actual turbine is manufactured. Iterative optimization of the model effectively offsets frequency ranges, improving the structural safety and operational stability of the turbine, reducing subsequent rectification costs, and ensuring the compliance and reliability of the guide vane design.

[0037] Application Example 1 In this application example, during the hydraulic research and development of a hydroelectric turbine unit, a set of high-performance double-row blade cascades was designed. However, it is necessary to determine the frequency of Karman vortex shedding so as to avoid this frequency during the structural design process.

[0038] Conventional methods include: 1. Calculating using empirical formulas, but this has inaccuracy issues. 2. Establishing a geometric model of the actual machine size and performing CFD calculations to obtain the Karman vortex shedding frequency. However, the actual machine size is large, the computational load is large, and it consumes a lot of resources.

[0039] Using this method, the Karman vortex shedding frequency can be obtained from CFD calculations at the model scale or in model tests, and then mapped to the actual machine to guide structural design. It has the advantages of saving resources and having a short cycle time.

[0040] Therefore, in this application example, the turbine guide vane is optimized using the guide vane optimization method based on Karman vortex conversion from model to prototype turbine guide vane according to this application.

[0041] In this application example, guide vane optimization is performed on the water turbine based on Karman vortex conversion from the model to the prototype water turbine guide vanes.

[0042] In this application example, the schematic diagram of the three-dimensional CFD flow field simulation model is as follows: Figure 2 As shown.

[0043] In this application example, the turbine is a mixed-flow turbine, and the parameters of the mixed-flow turbine scheme and the three-dimensional CFD flow field simulation model are shown in Table 1.

[0044] Table 1. Parameters of the mixed-flow turbine scheme and the three-dimensional CFD flow field simulation model in Application Example 1

[0045] Based on the above parameters, a three-dimensional CFD calculation model of the entire flow channel is established. The calculation unit is 65 r / min, and the rotation speed is n = n11 * sqrt(H) / D = 65 * sqrt(30) / 0.336525 = 974.75 r / min (usually this rotation speed is in the range of 0-2000 r / min). In this application example, the Karman vortex shedding frequencies were calculated to be 70.5 Hz, 75.9 Hz, and 81.3 Hz when the turbine guide vane openings were 16°, 17°, and 18°, respectively, using a three-dimensional CFD flow field simulation model. Meanwhile, through structural modal analysis, the natural frequency of the turbine guide vane structure was found to be 81.53Hz. At this time, the Karman vortex shedding at an 18° opening is very close to the natural frequency of the guide vane structure, which is 81.53Hz. It is determined that Karman vortex resonance is likely to occur under this condition, and the guide vane structure design needs to be modified.

[0046] If the calculated Karman vortex shedding frequency is too close to the natural frequency of the actual aircraft structure, the guide vane profile is modified to change the Karman vortex shedding frequency, or the actual aircraft structure is modified to change the natural frequency of the structure, so as to ensure that there is a significant difference between the two.

[0047] The mechanism design of the guide vane needs to be modified (such as thickening the guide vane connecting rod). At this time, the recalculated natural frequency is 102.7Hz, which is 26% different from 81.3Hz (usually it should be greater than 20%). At this time, it can be considered that the Karman vortex resonance is no longer likely to occur under this working condition. The guide vane development and mechanism design of this scheme can be safely used in engineering practice.

[0048] Application Example 2 In this application example, the turbine is a pump-turbine. Compared to application example 1, this application example obtains the Karman vortex frequency f of the turbine model by constructing a scaled-down physical installation model. m ; In this application example, the parameters of the water pump turbine and the solid installation model are shown in Table 2; the schematic diagram of the solid installation model is shown below. Figure 3 As shown.

[0049] Table 2 Parameters of the pump-turbine and solid installation model in Application Example 2

[0050] In this application example, the values ​​of 12°, 12.5°, 14°, and n in the table above are used. 11 =59.35r / min, set the speed as n=59.35*sqrt(30) / 0.52136=623.51r / min, and conduct detailed tests on the above three working conditions. The Karman vortex shedding frequencies are 113.8Hz, 115.8Hz and 128.7Hz respectively.

[0051] The natural frequency of the guide vane structure was calculated to be 108.7 Hz.

[0052] At this time, the Karman vortex shedding frequency under the 12° guide vane opening condition is 113.8Hz, which is very close to the natural frequency of the guide vane structure, 108.7Hz. It is judged that Karman vortex resonance is likely to occur under this condition.

[0053] The guide vane profile was modified, the model was reworked, and tests were conducted. The Karman vortex shedding frequencies under three operating conditions were obtained as 132.1Hz, 139.7Hz, and 152.4Hz. The Karman vortex shedding frequency closest to the natural frequency of 108.7Hz was 132.1Hz, a difference of 21.53%, which is greater than 20%. Therefore, the modification of the guide vane can be considered reasonable, avoiding the natural frequency of the guide vane structure and significantly reducing the risk of resonance. This developed turbine and its corresponding structural design can be used in practical engineering applications.

[0054] It is understood that the present invention has been described through some embodiments, and those skilled in the art will recognize that various changes or equivalent substitutions can be made to these features and embodiments without departing from the spirit and scope of the invention. Furthermore, under the teachings of the present invention, these features and embodiments can be modified to adapt to specific situations and materials without departing from the spirit and scope of the invention. Therefore, the present invention is not limited to the specific embodiments disclosed herein, and all embodiments falling within the scope of the claims of this application are within the protection scope of the present invention.

Claims

1. A guide vane optimization method based on Karman vortex conversion from model to prototype turbine guide vanes, characterized in that: Includes the following steps: S1. Based on the prototype turbine design scheme, construct a scaled-down turbine model; S2. The Karman vortex frequency f of the turbine model is obtained through simulation. m ; S3, Karman vortex frequency f obtained through the turbine model m The Karman vortex frequency f of the prototype turbine was calculated. p ; S4. The Karman vortex frequency f of the prototype turbine p Determine whether the prototype turbine meets the vibration damping requirements. If not, optimize the guide vanes and repeat steps S1-S4 until the vibration damping requirements are met. S5, End.

2. The guide vane optimization method based on Karman vortex conversion from model to prototype turbine guide vane as described in claim 1, characterized in that: In step S1, the runner size of the turbine model is greater than or equal to 0.25m.

3. The guide vane optimization method based on Karman vortex conversion from model to prototype turbine guide vane as described in claim 1, characterized in that: In step S1, the turbine model is a three-dimensional CFD flow field simulation model.

4. The guide vane optimization method based on Karman vortex conversion from model to prototype turbine guide vanes as described in claim 3, characterized in that: In step S1, constructing the three-dimensional CFD flow field simulation model includes the following steps: S11. Construct a geometric model based on the dimensions of the model turbine; S12. Mesh the geometric model; S13. Establish a three-dimensional CFD flow field simulation model based on the geometric model after mesh generation.

5. The guide vane optimization method based on Karman vortex conversion from model to prototype turbine guide vane as described in claim 3, characterized in that: Step S2 includes the following steps: S21. Set the operating parameters in the three-dimensional CFD flow field simulation model. The operating parameters include flow rate and rotational speed. S22. Based on the three-dimensional CFD flow field simulation model, CFD simulation calculations were performed to obtain the Karman vortex shedding frequency of the double-row cascade. f m and the location of the separation point.

6. The guide vane optimization method based on Karman vortex conversion from model to prototype turbine guide vane as described in claim 5, characterized in that: In step S21, setting the flow rate includes: constructing geometric models with different active guide vane openings, dividing the geometric models into meshes, selecting the geometric model with the required flow rate corresponding to the active guide vane opening to establish a three-dimensional CFD flow field simulation model for CFD simulation calculation.

7. The guide vane optimization method based on Karman vortex conversion from model to prototype turbine guide vane as described in claim 5, characterized in that: In step S21, setting the rotational speed includes: calculating the model turbine rotational speed based on the unit rotational speed of an existing turbine when a Karman vortex occurs using the following formula: n 11 = (n*D) / sqrt(H); Where, n 11 n is the unit speed at which the existing turbine generates the Karman vortex; D is the turbine speed of the model; H is the runner diameter of the model turbine; and H is the head of the model turbine, which is a fixed value.

8. The guide vane optimization method based on Karman vortex conversion from model to prototype turbine guide vane according to claim 1, characterized in that: In step S1, the turbine model is a physical installation model.

9. The guide vane optimization method based on Karman vortex conversion from model to prototype turbine guide vane as described in claim 8, characterized in that: In step S1, constructing a scaled-down water turbine model specifically involves: machining the model water turbine according to its dimensions and installing it on a water turbine model test bench.

10. The guide vane optimization method based on Karman vortex conversion from model to prototype turbine guide vane according to claim 9, characterized in that: Step S2 includes the following steps: S201. According to the test conditions, adjust the model turbine to the corresponding guide vane opening, set the motor to the corresponding speed, and start the test; S202. During the test, when the aperture is increased to the point where Karman vortices occur, the test personnel use non-contact measuring instruments to measure the location of the Karman vortex separation point and the vortex shedding frequency of the double-row blade cascade. f m .

11. The guide vane optimization method based on Karman vortex conversion from model to prototype turbine guide vane according to claim 1, characterized in that: In step S3, the Karman vortex frequency f of the prototype turbine is calculated through the following steps. p : S31. The incoming flow velocity of the water turbine is calculated using the following formula (1). V : V = Q / S' = Q / πD'bks = Q / k 1 D 2 （1） Q This represents the flow rate of the turbine passing through the double-row blade section at this time. S’ The area of ​​the water flow channel at the vortex separation point of the double-row blade grating; D’ The diameter of the distribution circle at the vortex separation point on the guide vane; b This refers to the guide vane height. k S This is a correction factor that adjusts the area of ​​the flow channel occupied by the guide vane at the vortex separation point. πD' B' The calculated area is actually larger than the channel area, so it needs to be corrected. k S =a / (L+a) , 0 < kS < 1 ; a For the opening degree of the guide vanes; L is the characteristic length of the blunt body, and in a double-row cascade, it is the distance between the vortex separation points on both sides of the guide vane; Let the coefficient k 1 =k S πbD' / D 2 ; D The diameter of the rotor is a fixed value. The following formula (2) is obtained: V=Q / k 1 D 2 （2）； S32. The flow rate of the water turbine is calculated using the following formula (3): Q= nφD 3 π 2 / 240 （3） in, n This refers to the turbine speed; φ The turbine flow coefficient is positively correlated with the opening of the movable guide vanes. Let the coefficient k 2 =π 2 / 240, resulting in the following formula (4). Q=k 2 nφD 3 （4）； S33. Substituting formulas (2) and (4) into formula (5) yields formula (6): f = S t V / L （5） f = St ( k 2 nφD) / (k 3 k 1 D) （6） in, f The frequency of turbine detachment; S t For Struhar numbers; V The incoming flow velocity to the water turbine; L is the characteristic length of the blunt body, and in a double-row cascade, it is the distance between the vortex separation points on both sides of the guide vane; S34. Formula (6) yields the following formula (7): f / n = St ( k 2 φ ) / ( k 3 k 1) Let the coefficient K=St k 2 / ( k 3 k 1), thus obtaining the following formula (8): f / n = Kφ （8）； The coefficient K is a dimensionless number. As can be seen from formula (8), the main factor determining the Karman vortex shedding frequency is the flow coefficient. φ The guide vane opening and distribution circle diameter of the actual turbine and the model strictly adhere to the law of geometric similarity, while the flow coefficient... φ The flow coefficient is positively correlated with the opening of the movable guide vanes. When the opening of the movable guide vanes of the turbine model and the prototype turbine are the same, the flow coefficient of the turbine model and the prototype turbine is positively correlated. φ They are equal; therefore, the Karman vortex shedding frequency of the actual machine can be calculated by the following formula (9). f p : f p = n p f m / n m （9） Where: f p The Karman vortex frequency of the prototype turbine; f m The Karman vortex frequency of the turbine model; n p The rotational speed of the prototype water turbine; n m This represents the rotational speed of the water turbine model.

12. The guide vane optimization method based on Karman vortex conversion from model to prototype turbine guide vane according to claim 1, characterized in that: Step S4 includes the following steps: S41. Obtain the natural frequencies of the actual machine structure through modal calculation. f ; S42, the natural frequency f Frequency of Karman vortex shedding from the actual machine f p Compare, if the inherent frequency f Karman vortex shedding frequency on the actual machine f p If the value is within -10% to +10%, the risk of turbine vibration is relatively high. S43. For high-risk turbines, modify the guide vane design, reconstruct a scaled-down turbine model, and calculate the Karman vortex shedding frequency until the Karman vortex shedding frequency differs significantly from the structure's natural frequency, thus meeting the vibration avoidance requirements.

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