A method for optimizing installation scheme of large-scale impulse water turbine straight-flow nozzle

Abstract

The application discloses a large-scale impulse water turbine straight-flow nozzle installation scheme optimization method and relates to the technical field of hydraulic engineering.The method comprises the following steps: geometric modeling is performed on a target nozzle, a model is meshed according to a preset mesh quality standard, and a target nozzle grid is generated; a flow velocity analysis is performed on the nozzle grid by using operation simulation, and a flow velocity distribution is obtained; a streamline transition calculation is performed according to the flow velocity distribution, a transition flow velocity is monitored, and a target flow velocity is obtained; and periodic flow velocity optimization is performed on the nozzle grid based on the flow velocity monitoring result, and finally, an optimized nozzle installation scheme is determined. The technical problem of flow velocity instability caused by flow velocity mutation in the operation process of the existing large-scale impulse water turbine straight-flow nozzle is solved, the technical target of improving flow velocity stability is achieved by optimizing the configuration of the nozzle, and the technical effect of improving the operation reliability and efficiency of the water turbine is achieved.

Description

Technical Field

[0001] This application relates to the field of water conservancy engineering technology, and in particular to an optimization method for the installation scheme of DC nozzles of large impulse turbines. Background Technology

[0002] Large impulse turbines, as core equipment in hydropower systems, are widely used in various hydropower stations, and their operational performance directly affects power generation efficiency and the overall stability of the system. The direct-current nozzle, a crucial component of the turbine, is responsible for precisely guiding water flow to the impeller to achieve efficient conversion of water energy into mechanical energy. However, in actual operation, the velocity distribution of the direct-current nozzle is often affected by fluctuations in water flow and changes in operating conditions, leading to frequent abrupt velocity changes and subsequent velocity instability. This instability not only affects the turbine's operating efficiency but can also cause mechanical vibration and excessive wear, increasing maintenance costs. Furthermore, traditional nozzle installation methods rely heavily on experience, lacking systematic fluid dynamics analysis and real-time monitoring, making it difficult to effectively address complex flow phenomena such as flow separation. Therefore, there is an urgent need to develop more scientific and precise nozzle installation and velocity control methods to solve the technical challenges caused by velocity instability, improve the overall performance and operational reliability of the turbine, and meet the demands of modern hydropower for efficient and stable operation.

[0003] At present, there is a technical problem in the related technologies of large impulse turbine DC nozzles that causes flow velocity instability due to sudden changes in flow velocity during operation. Summary of the Invention

[0004] This application provides an optimized installation method for the DC nozzle of a large impulse turbine, which solves the technical problem of flow velocity instability caused by sudden changes in flow velocity during the operation of existing DC nozzles for large impulse turbines.

[0005] This application provides an optimized method for the installation of DC nozzles on large impulse turbines, including:

[0006] A geometric model of the target nozzle is created, and the target nozzle model is meshed based on a preset mesh quality to obtain the target nozzle mesh. Flow velocity analysis is performed on the target velocity mesh obtained from the simulation of the target nozzle mesh to obtain the target velocity distribution. A streamline transition is performed on the target nozzle mesh according to the target nozzle velocity distribution, and the transition velocity is monitored to obtain the target velocity. Based on the target velocity monitoring, the target nozzle mesh is optimized for a preset period to obtain the target installation scheme.

[0007] This application proposes an optimization method for the installation of a direct-current nozzle on a large impulse turbine. First, a geometric model of the target nozzle is created, and the model is meshed according to a preset mesh quality standard to generate the target nozzle mesh. Flow velocity analysis is performed on the nozzle mesh using operational simulation to obtain the velocity distribution. Based on the velocity distribution, streamline transition calculations are performed, and the transition velocity is monitored to obtain the target velocity. Based on the velocity monitoring results, the nozzle mesh is periodically optimized, and the optimized nozzle installation scheme is finally determined. This achieves the technical goal of improving flow velocity stability through optimized nozzle configuration, thereby enhancing the operational reliability and efficiency of the turbine. Attached Figure Description

[0008] To more clearly illustrate the technical solutions of the embodiments of the present invention, the accompanying drawings of the embodiments of the present invention will be briefly described below. Flowcharts are used in this application to illustrate the operations performed by the system according to the embodiments of the present application. It should be understood that the preceding or following operations are not necessarily performed precisely in sequence. Instead, various steps can be processed in reverse order or simultaneously as needed. Furthermore, other operations can be added to these processes, or one or more steps can be removed from these processes.

[0009] Figure 1 A flowchart illustrating an optimization method for the installation of a DC nozzle on a large impulse turbine, provided in an embodiment of this application;

[0010] Figure 2 This is a schematic diagram illustrating the process of obtaining the target velocity grid in an optimization method for the DC nozzle installation scheme of a large impact turbine provided in this application embodiment. Detailed Implementation

[0011] The above description is merely an overview of the technical solution of this application. In order to better understand the technical means of this application and to implement it in accordance with the contents of the specification, and to make the above and other objects, features and advantages of this application more obvious and understandable, specific embodiments of this application are given below.

[0012] To make the objectives, technical solutions, and advantages of this application clearer, the following detailed description of this application will be provided in conjunction with the accompanying drawings. The described embodiments should not be considered as limitations on this application. All other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.

[0013] In the following description, references to "some embodiments" describe a subset of all possible embodiments. However, it is understood that "some embodiments" can be the same or different subsets of all possible embodiments and can be combined with each other without conflict. The terms "first" and "second" are used merely to distinguish similar objects and do not represent a specific ordering of objects. The terms "comprising" and "having," and any variations thereof, are intended to cover non-exclusive inclusion. For example, a process, method, system, product, or server that includes a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or modules not explicitly listed or inherent to these processes, methods, products, or devices. Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this application belongs. The terminology used herein is for the purpose of describing embodiments of this application only.

[0014] This application provides an optimized method for the installation of DC nozzles on large impulse turbines, such as... Figure 1 As shown, the method includes:

[0015] Step S100: Geometric modeling of the target nozzle is performed. The target nozzle model is meshed based on a preset mesh quality to obtain the target nozzle mesh. Specifically, based on the actual structure and size parameters of the target nozzle, a three-dimensional geometric model is created using professional 3D modeling software such as CATIA to ensure that the model accurately and completely represents details such as the nozzle's inlet contour, outlet shape, main body length, curvature, and internal cavity features. Information such as the flow velocity range and flow properties of the fluid inside the nozzle is extracted, and a preset flow type is used to determine the preset mesh quality. For laminar flow, a relatively sparse mesh with refined meshes at the wall is used; for turbulent flow, a finer mesh with good orthogonal smoothness is required. Then, tools such as ANSYS_Meshing are used to generate hexahedral elements using structured meshing for regular parts such as the inlet section, and tetrahedral elements using unstructured meshing for complex regions such as curved transition sections. Key areas such as the throat and near the wall are locally refined to finally obtain the target nozzle mesh.

[0016] In one possible implementation, a geometric model of the target nozzle is performed, and the target nozzle model is meshed based on a preset mesh quality to obtain the target nozzle mesh. Step S100 further includes step S110, extracting fluid velocity and fluid flow properties, and presetting the flow type. Specifically, key information related to the fluid inside the target nozzle is extracted, among which fluid velocity and fluid flow properties are particularly important. Fluid velocity information is obtained through various means, such as referring to experimental data of similar nozzle systems in the past, theoretical calculations, or using preliminary fluid simulation software to perform simple flow field predictions, determining the possible velocity range of the fluid at different locations in the nozzle, such as higher velocity at the inlet, and corresponding changes in velocity in the gradually expanding or contracting sections inside the nozzle. At the same time, the fluid flow properties are analyzed to determine whether it is laminar or turbulent. Laminar flow is characterized by parallel flow between fluid layers without interference, and usually occurs when the flow velocity is low, the pipe diameter is small, and the fluid viscosity is high; while turbulent flow is characterized by irregular vortex motion and strong mixing phenomena inside the fluid, and mostly occurs when the flow velocity is high, the pipe diameter is large, or the fluid viscosity is low. Based on this information on flow velocity and flow properties, the flow type is precisely preset. For example, if the flow velocity is low and analysis shows that it is more likely to be laminar flow, then it is preset to laminar flow; if the flow velocity is high and there are obvious signs of turbulence, then it is preset to turbulence.

[0017] Step S120: Configure the mesh quality based on the flow type to obtain the preset mesh quality. Specifically, after determining the flow type, configure the mesh quality to obtain the preset mesh quality. For the preset laminar flow, since laminar flow is relatively stable, the mesh can be relatively sparse. However, to accurately simulate the flow characteristics of the boundary layer, special treatment is necessary near the nozzle wall. Using boundary layer meshing technology, multiple layers of gradually refined meshes are generated near the wall, which can accurately capture the velocity gradient changes of the fluid at the wall. In regions far from the wall, the mesh cell size can be appropriately increased to improve computational efficiency while ensuring computational accuracy. For example, in the axial direction of the nozzle, the mesh cell length in regions far from the wall is set to several times the mesh cell length near the wall. For the preset turbulent flow, due to the complexity and randomness of turbulence, a finer mesh is needed to capture its vortex structure and drastic velocity changes. Reducing the mesh cell size improves the orthogonality and smoothness of the mesh, ensuring that the mesh can accurately reflect various characteristics of turbulence. For example, in the turbulent core region, the size of the mesh cells should be small enough to capture the details of the vortices, and the angle between adjacent mesh cells should be as close to a right angle as possible to ensure the accuracy and stability of the calculation. By configuring the mesh quality for different flow types, a preset mesh quality suitable for the fluid analysis of the target nozzle is finally determined, providing an important quality standard for subsequent mesh generation.

[0018] Step S200: Based on the target velocity grid obtained from the simulation of the target nozzle grid, velocity analysis is performed to obtain the target velocity distribution. Specifically, the target nozzle grid model is imported using computational fluid dynamics software such as ANSYS_Fluent. Inlet velocity, pressure, and temperature, outlet pressure or flow rate, and boundary conditions such as wall roughness and no-slip are set according to the actual working conditions of the nozzle. The Navier-Stokes equations are solved to obtain the target velocity grid. Abrupt change thresholds are determined based on nozzle design requirements and actual operating conditions. Target abrupt change grids with velocity changes exceeding the threshold are identified by scanning the target velocity grid data. These grids are often located at nozzle structural changes and may affect performance. Streamlines, velocity vectors, and pressure changes are analyzed on the target abrupt change grids to verify flow separation. Simultaneously, target pressure grids are identified based on pressure gradient thresholds. Pressure gradient trend analysis is performed on the target pressure grids in conjunction with neighboring grids. Target abrupt change grids and target pressure grids that satisfy flow separation or pressure gradient anomalies are added to the target velocity distribution, providing a basis for nozzle optimization.

[0019] In one possible implementation, such as Figure 2 As shown, based on the target velocity grid obtained from the simulation of the target nozzle grid, velocity analysis is performed to obtain the target velocity distribution. Step S200 further includes step S210, extracting the target inlet, target outlet, and target wall from the target nozzle grid. Specifically, for the target nozzle grid, the target inlet, target outlet, and target wall are precisely extracted. The target inlet is the starting point where the fluid enters the nozzle, and its shape and size have a crucial impact on the flow rate, velocity, and flow pattern of the fluid flowing into the nozzle. For example, if the inlet is circular, its diameter will directly determine the initial fluid flux entering the nozzle; if it is rectangular, the ratio of length to width will affect the velocity distribution of the fluid at the inlet. The target outlet is the part where the fluid flows out of the nozzle. The shape and area of ​​the outlet determine the velocity and pressure changes when the fluid flows out. For example, a contracting outlet will accelerate the fluid, while an expanding outlet may decelerate the fluid and reduce the pressure. The target wall is the boundary that forms the internal cavity of the nozzle. Its surface characteristics, such as roughness and temperature, will affect the viscous resistance and heat transfer process of the fluid, thereby affecting the fluid flow state inside the entire nozzle.

[0020] Step S220: Configure inlet boundary conditions for the target inlet, configure outlet boundary conditions for the target outlet, and configure wall conditions for the target wall to complete the boundary condition configuration. Specifically, after successfully extracting the target inlet, target outlet, and target wall, boundary condition configuration is performed. For the target inlet, the inlet boundary conditions are configured based on the fluid inflow situation in the actual working scenario of the nozzle. If the nozzle is connected to a pipeline system with a stable pressure source, a corresponding pressure value is set at the inlet; if the flow rate into the nozzle is known, the flow rate value can be used as the inlet boundary condition; it can also be configured based on the actual measured or estimated inlet velocity, while considering physical parameters such as fluid temperature and density to ensure that the inlet boundary conditions accurately reflect the actual fluid inflow characteristics. For the target outlet, the outlet boundary conditions are configured based on the external environment at the nozzle outlet end or the requirements of subsequent connected equipment. For example, if the nozzle outlet is open to the atmosphere, it can be set to ambient pressure; if it is connected to another cavity with lower pressure, a corresponding pressure difference condition is set; or the outlet boundary conditions are determined based on the expected outlet velocity or flow rate. For the target wall, wall conditions are configured based on the actual physical properties of the wall. If the wall surface is relatively smooth, set a low roughness value; if the wall surface has some heat dissipation or heating, it is necessary to set corresponding wall surface temperature or heat flux conditions; usually, the wall surface is set to no-slip condition, that is, the fluid velocity at the wall surface is zero, to simulate the actual interaction between the fluid and the wall surface. By precisely configuring the boundary conditions of the target inlet, target outlet, and target wall surface, the boundary condition settings of the entire target nozzle mesh are completed.

[0021] Step S230: Perform a simulation on the target nozzle mesh based on boundary conditions to obtain the target velocity mesh. Specifically, after configuring the boundary conditions, perform a simulation on the target nozzle mesh using professional computational fluid dynamics (CFD) software. Import the target nozzle mesh model with configured boundary conditions into a CFD software platform such as ANSYS_Fluent or CFX. The software will calculate the velocity information at each mesh node within the nozzle by numerically solving the governing equations of fluid flow, such as the Navier-Stokes equations, based on the set boundary conditions and the geometry of the nozzle mesh. During the simulation, the software will use appropriate numerical calculation methods, such as the finite volume method and the finite difference method, to discretize the governing equations and iteratively solve them, gradually approximating the actual flow field solution. After a certain amount of computation time and number of iterations, the velocity distribution of the fluid at various locations within the entire nozzle is obtained. The velocity information is presented in the form of mesh node data, thus obtaining the target velocity mesh. The target velocity grid can intuitively reflect the velocity field characteristics of the fluid inside the nozzle under set boundary conditions, providing a basic data source for further analysis of the fluid flow characteristics inside the nozzle, such as the uniformity of velocity distribution and the existence of flow separation, so as to evaluate and optimize the performance of the nozzle.

[0022] In one possible implementation, flow velocity analysis is performed on the target velocity grid obtained from the operational simulation of the target nozzle grid to obtain the target velocity distribution. Step S200 further includes step S240, which identifies the velocity of the target velocity grid based on abrupt change thresholds and extracts the target abrupt change grids. Specifically, it is necessary to determine the abrupt change threshold. The setting of the abrupt change threshold is not arbitrary; it depends on an in-depth analysis of the normal velocity variation range of the fluid within the target nozzle and a precise grasp of the velocity stability requirements. The threshold can be determined through theoretical analysis, statistical analysis of experimental data from similar nozzle systems in the past, or preliminary numerical simulation experiments. For example, if a large amount of experimental data shows that the fluctuation range of the fluid velocity within the target nozzle under normal operating conditions is usually between ±2 m / s, then in order to more sensitively capture abnormal velocity changes that may affect nozzle performance, the abrupt change threshold can be set to 3 m / s. After determining the abrupt change threshold, a detailed velocity identification is performed on the target velocity grid. Since the target velocity grid contains velocity information at various locations within the nozzle, each node is examined individually to check the difference between its velocity value and that of its neighboring nodes. When the difference between the velocity at a node and that of its neighboring nodes exceeds a mutation threshold, the grid region containing that node is marked as a potential mutation region. Through this point-by-point scanning and comparison method, all grid regions that meet the criteria are extracted, and these regions together constitute the target mutation grid. Target mutation grids are often concentrated in areas where the internal structure of the nozzle undergoes significant changes, such as the nozzle throat, where the cross-sectional area decreases sharply and the fluid velocity increases rapidly, making it prone to velocity mutations; and also in the bends of the nozzle, where the velocity distribution changes due to centrifugal force when the fluid turns, which may also lead to mutations.

[0023] Step S250: If flow separation verification and identification of the target abrupt change grid yields a separation result, the target abrupt change grid is added to the target velocity distribution. Specifically, after extracting the target abrupt change grid, flow separation verification and identification are performed on it. This requires the comprehensive application of multiple fluid dynamics analysis methods and tools. Starting with the streamline morphology of the flow field, observe whether abnormal phenomena such as backflow, vortices, or sudden interruptions of streamlines occur in the target abrupt change grid region. For example, in normal fluid flow, streamlines should be smooth, continuous, and gradually change along the mainstream direction. If streamlines begin to bend and form closed vortex rings in the target abrupt change grid region, this is an important sign of flow separation. At the same time, analyze the velocity vector distribution. In the region where flow separation occurs, the direction and magnitude of the velocity vector will change drastically, and a significant velocity component will appear perpendicular to the mainstream direction. In addition, pressure distribution is also one of the key factors in judging flow separation. Near the flow separation point, the pressure will locally decrease, forming a low-pressure area, causing fluid to flow from the high-pressure area to the low-pressure area, thereby disrupting the original mainstream morphology. By comprehensively analyzing the streamlines, velocity vectors, and pressure distribution of the target abrupt change grid region, if flow separation is confirmed in that region (i.e., a separation result is obtained), the target abrupt change grid is added to the target velocity distribution. The aim is to more accurately depict the overall velocity distribution within the nozzle, especially in areas with abnormal flow states. This allows for targeted optimization and adjustment of the nozzle structure or operating parameters, improving the stability and uniformity of the fluid velocity within the nozzle, and ultimately enhancing the overall efficiency and performance of the nozzle system.

[0024] In one possible implementation, if the target abrupt change grid is verified and a separation result is obtained through flow separation verification, and the target abrupt change grid is added to the target velocity distribution, step S250 further includes step S251, which involves pressure identification of the target abrupt change grid based on a pressure gradient threshold to obtain a target pressure grid. Specifically, the pressure gradient threshold is determined. Determining the threshold requires comprehensive analysis of various factors, including the design specifications of the target nozzle, operating conditions, and fluid characteristics. For example, for high-pressure nozzle systems, the internal pressure gradient variation range is large, and the pressure gradient threshold may be set accordingly higher; while for low-pressure, precision nozzle systems, the pressure gradient threshold needs to be set more precisely. A suitable pressure gradient threshold is determined through theoretical calculations, experimental data references, or preliminary simulation analysis. Pressure identification is then performed on the target abrupt change grid. Since the target abrupt change grid is a region with flow anomalies previously screened based on velocity abrupt changes, the pressure difference between each grid node and its adjacent nodes is calculated within these regions using computational fluid dynamics software or related algorithms. The pressure difference is compared with a set pressure gradient threshold. When the pressure difference exceeds the threshold, the grid region containing that node is identified as a pressure anomaly region. These pressure anomaly regions collectively constitute the target pressure grid. The target pressure grid is typically located in areas of the nozzle where flow velocity changes drastically and the structure is complex, such as the transition region between the nozzle throat and bends. Due to the rapid changes in geometry, the fluid pressure changes in these areas are also complex, easily generating pressure gradients that do not conform to normal flow patterns.

[0025] Step S252: Analyze the pressure gradient trend based on the target pressure grid and its neighboring grids to obtain the target pressure trend. Specifically, after obtaining the target pressure grid, analyze the pressure gradient trend using the neighboring grids. The neighboring grids refer to the grid regions spatially adjacent to the target pressure grid. During the analysis, the target pressure grid is the core, and the direction and magnitude of pressure changes in the surrounding grids are observed. For example, from the nozzle inlet to the outlet, under normal flow conditions, the pressure should gradually decrease. However, if the pressure first decreases and then increases in the target pressure grid and its neighboring grid regions, or if the rate of pressure decrease is abnormally slow or rapid, it indicates an abnormal pressure gradient trend. By fitting and differencing the pressure data from multiple neighboring grids, a pressure gradient change curve is plotted, thereby determining the target pressure trend. The trend visually reflects the direction of pressure change within the target pressure grid region and is an important basis for judging whether the fluid flow in that region is stable and meets the nozzle design expectations.

[0026] Step S253: If the target pressure trend does not meet the gradient fallback threshold, the target pressure grid is added to the target velocity distribution. Specifically, it is determined whether the target pressure trend meets the gradient fallback threshold. The gradient fallback threshold is also set based on the ideal working state of the nozzle and the principles of fluid mechanics. If the pressure trend shows a smooth characteristic, gradually decreasing towards the nozzle exit direction with a change within a preset range, then it is considered to meet the gradient fallback threshold, indicating that the pressure change in this area conforms to normal flow patterns; conversely, if the pressure trend fluctuates, stagnates, or even changes in the opposite direction, and exceeds the range allowed by the gradient fallback threshold, then it is determined that the gradient fallback threshold is not met. The target pressure grid is added to the target velocity distribution. Because abnormal pressure in a region can affect the velocity distribution of the fluid, leading to unstable velocity or adverse phenomena such as local vortices. Adding it to the target velocity distribution can more comprehensively and accurately reflect the actual flow state of the fluid in the nozzle, providing a more detailed basis for subsequent optimization of the nozzle structure and adjustment of working parameters, so as to improve the fluid flow characteristics in the nozzle and improve the working efficiency and performance of the nozzle.

[0027] Step S300: Based on the target nozzle velocity distribution, streamline the target nozzle grid for transition, and monitor the transition velocity to obtain the target velocity. Specifically, based on the target nozzle velocity distribution, solve relevant equations using numerical calculation methods such as finite difference or finite volume to determine the streamline direction and curvature during the transition from regions of drastic velocity change to stable conditions, and calculate the preliminary shape and size parameters of the progressive channel. Collect transition section configuration length, diameter, and velocity samples over a preset time period, and use machine learning algorithms such as regression to train and construct a transition section configuration model. Input the mutation threshold into the model to calculate a suitable transition section configuration length and diameter, and optimize the progressive channel to obtain the transition channel. After the transition channel is constructed, monitor the target velocity feedback based on its length and diameter parameters to obtain the iterative velocity. By assigning values ​​and iteratively adjusting the parameter combination, determine the optimized velocity as the target velocity to improve the efficiency and performance of the nozzle system.

[0028] In one possible implementation, the streamline transition of the target nozzle mesh is performed based on the target nozzle velocity distribution, and the target velocity is obtained by monitoring the transition velocity. Step S300 further includes step S310, calculating the streamlined progressive transition section of the target nozzle mesh based on the target velocity distribution to obtain a progressive channel. Specifically, the streamlined progressive transition section of the target nozzle mesh is calculated based on the target velocity distribution. The target velocity distribution shows the magnitude and trend of the fluid velocity at different locations within the nozzle, which is an important basis for calculating the streamlined progressive transition section. In-depth analysis of the velocity distribution data identifies regions with significant velocity changes, such as the nozzle throat, where the velocity typically increases rapidly; and regions with relatively stable velocity, such as the nozzle exit section. For the junctions of regions with different velocity characteristics, relevant principles and numerical calculation methods of computational fluid dynamics, such as the finite volume method, are used to determine how the streamlines progressively transition between different velocity regions. By solving and iteratively calculating the fluid motion equations, and considering the fluid's viscosity, inertia, and the constraint effect of the nozzle geometry on the fluid, the tortuous path of streamlines from the high-velocity region to the low-velocity region, the changes in streamline density, and the acceleration or deceleration patterns of the fluid during the transition are gradually determined. Based on this, the channel shape and dimensions that can achieve this gradual streamline transition are calculated, thus obtaining the gradual channel. The design of the gradual channel aims to enable the fluid to smoothly transition through different velocity regions, reducing adverse phenomena such as energy loss, vortex formation, and flow separation caused by sudden changes in velocity, thereby improving the overall efficiency and stability of the fluid flow within the nozzle.

[0029] Step S320: Configure the parameters of the progressive channel based on the transition section configuration model to obtain the transition channel. Specifically, after obtaining the progressive channel, configure its parameters based on the transition section configuration model to obtain the transition channel. Constructing the transition section configuration model requires the prior collection of a large amount of relevant data, including samples of transition section configuration length, transition section configuration diameter, and transition section flow velocity within a preset time period. The sample data can originate from data accumulated from previous experimental tests on similar nozzles, or from valid data obtained through multiple numerical simulations. Using abundant data samples, machine learning or data fitting methods are employed to construct the transition section configuration model. For example, regression analysis algorithms are used to model the relationship between transition section configuration length, diameter, and flow velocity, determining the optimal combination of length and diameter for the transition section under different flow velocity conditions. After constructing the transition section configuration model, a specific mutation threshold is input into the model. The mutation threshold is determined during the previous analysis of the target flow velocity distribution and is a key indicator used to measure whether flow velocity changes are abnormal. Based on the mutation threshold, the transition section configuration model calculates the suitable transition section configuration length and diameter parameters for the current progressive channel according to its internal algorithm and data relationships. Then, based on the calculated parameters, the progressive channel is precisely configured, adjusting its length, diameter, and internal geometric details to obtain the transition channel. The transition channel is more optimized in structure and size, better adapting to changes in fluid velocity within the nozzle, further improving the stability and efficiency of fluid flow.

[0030] Step S330: Monitor the transition velocity of the transition channel to obtain the target velocity. Specifically, after the transition channel is constructed, its transition velocity is monitored to obtain the target velocity. During the monitoring process, the structural parameters of the transition channel are fully utilized, namely, the configuration length and diameter of the transition section are used for feedback monitoring of the target velocity. Since the length and diameter of the transition channel directly affect the magnitude and distribution of the fluid velocity within it, by changing these parameters and monitoring the velocity changes in real time, the velocity response law under different parameter combinations can be explored. For example, gradually increasing the length of the transition channel and observing how the velocity gradually decreases; or decreasing the diameter of the transition channel and analyzing the increase in velocity. In this process, a series of iterative velocity data are obtained. Based on the iterative velocity data, the transition channel is iteratively assigned values, that is, the length and diameter parameters of the transition channel are continuously adjusted, and then the velocity changes are monitored again. Through multiple such iterative operations, the optimal velocity state is gradually approached. Finally, the optimized velocity obtained in this iterative optimization process is determined as the target velocity. This target flow velocity is obtained by comprehensively considering factors such as the flow velocity distribution, streamline transition, and optimization of transition channel parameters within the nozzle. It can maximize the stability and uniformity of the fluid flow velocity within the nozzle, reduce energy loss and equipment wear caused by flow velocity fluctuations, and thus significantly improve the working performance and operating efficiency of the entire nozzle system.

[0031] In one possible implementation, the progressive channel is parameter-configured based on a transition section configuration model to obtain a transition channel. Step S320 further includes step S321, which involves supervised training based on transition section configuration length samples, transition section configuration diameter samples, and transition section flow velocity samples over a preset time period to obtain the transition section configuration model. Specifically, transition section configuration length samples, transition section configuration diameter samples, and transition section flow velocity samples are collected within a preset time period. The source of the sample data is crucial, and it is obtained through experimental testing on a large number of nozzles of the same type or similar operating conditions. During the experiment, the configuration length, diameter, and corresponding flow velocity data of the transition section of different nozzles are accurately measured during operation. For example, for a series of nozzles of different specifications but similar uses, tests are conducted under different pressure, flow rate, and other operating conditions, and the actual length and diameter of the transition section of each nozzle, as well as the flow velocity value measured under the parameters, are recorded. At the same time, rigorously validated numerical simulation data can also be used as supplementary samples. After organizing the rich and diverse sample data, a supervised learning algorithm is used for training. For example, by employing algorithms such as linear regression and neural networks, using the transition section configuration length and diameter as input features and the transition section flow velocity as the output label, and continuously adjusting the model's parameters, the model can accurately learn the intrinsic relationship between the transition section configuration length, diameter, and flow velocity, thereby obtaining a transition section configuration model. The model can predict the corresponding flow velocity based on given transition section length and diameter information, or conversely, calculate the appropriate transition section length and diameter based on the desired flow velocity.

[0032] Step S322: The mutation threshold is input into the transition section configuration model for parameter configuration. Based on the obtained transition section configuration length and diameter, a progressive channel configuration is performed to obtain the transition channel. Specifically, after obtaining the transition section configuration model, the mutation threshold is input into the model for parameter configuration. The mutation threshold is a key indicator previously determined during the target nozzle flow velocity analysis, reflecting the sensitivity to flow velocity changes within the nozzle and the requirements for flow velocity stability. When the mutation threshold is input into the transition section configuration model, the model calculates a suitable transition section configuration length and diameter based on its internally learned relationships and algorithms. For example, if the mutation threshold is set low, reflecting a higher requirement for flow velocity stability, the model will calculate a longer transition section configuration length and a smaller transition section configuration diameter, allowing for a smoother flow velocity change during the transition process; conversely, if the mutation threshold is high, the length and diameter of the transition section will be adjusted accordingly. A progressive channel configuration is performed based on the obtained transition section configuration length and diameter. Based on the calculated length and diameter parameters, the geometry of the transition channel is constructed, determining details such as the curvature of its internal surfaces and the expansion or contraction ratio of the channel. For example, if the transition section is long, the flow velocity will gradually change over a longer distance when constructing the progressive channel; if the transition section has a small diameter, the cross-section of the channel will also be reduced accordingly to achieve precise control of the fluid velocity. In this way, a transition channel is finally obtained, which can effectively guide the fluid to smoothly transition from one velocity region to another, reducing energy loss and flow instability caused by sudden changes in flow velocity, and improving the fluid transmission efficiency and stability of the entire nozzle system.

[0033] In one possible implementation, a mutation threshold is input into the transition section configuration model for parameter configuration. A progressive channel configuration is performed based on the obtained transition section configuration length and diameter to obtain the transition channel. Step S322 further includes step S3221, where feedback monitoring of the target flow velocity is performed based on the transition section configuration length and diameter to obtain an iterative flow velocity. Specifically, feedback monitoring of the target flow velocity is carried out based on the determined transition section configuration length and diameter. Since the transition section configuration length and diameter have a fundamental impact on the fluid flow velocity within the transition channel, under specific transition section configuration lengths and diameters, multiple flow velocity monitoring points are set within the transition channel, and high-precision flow velocity measurement instruments, such as laser Doppler velocimeters (LDV) or hot-wire anemometers, are used to collect real-time flow velocity data at different locations. The monitoring points are distributed at key parts of the transition channel, such as the inlet, middle section, and near the outlet, to comprehensively understand the changes in fluid flow velocity within the transition channel. The collected velocity data were processed and analyzed to obtain the velocity distribution under the current transition section configuration length and diameter, thereby determining the overall iterative velocity. The iterative velocity reflects the actual flow characteristics of the fluid under this set of transition section parameters and provides a basis for subsequent parameter adjustments.

[0034] Step S3222: The transition channel is iteratively assigned values ​​based on the iterative flow rate, and the obtained optimized flow rate is taken as the target flow rate. Specifically, after obtaining the iterative flow rate, the transition channel is iteratively assigned values ​​based on the data. Specifically, based on the difference between the iterative flow rate and the expected target flow rate, the two key parameters, the configuration length and diameter of the transition section, are adjusted. If the iterative flow rate is higher than the expected target flow rate, it may be necessary to appropriately increase the configuration length of the transition section to give the fluid a longer path within the channel to slow down, or to decrease the configuration diameter of the transition section to increase the flow resistance of the fluid and thus reduce the flow rate; conversely, if the iterative flow rate is lower than the expected target flow rate, the configuration length of the transition section can be shortened or the configuration diameter of the transition section can be increased. After adjusting the parameters, the flow rate in the transition channel is monitored again using a flow rate monitoring device to obtain a new iterative flow rate. This process is repeated, continuously adjusting the configuration length and diameter of the transition section and monitoring the flow rate changes, forming an iterative cycle. As the number of iterations increases, the parameters of the transition channel are gradually optimized, and the iterative flow rate gets closer and closer to the expected optimal flow rate state. When the iterative flow rate meets the preset convergence conditions, such as the change in flow rate being less than a certain set value or reaching a predetermined number of iterations, the optimized flow rate obtained at this point is taken as the target flow rate. The target flow rate is obtained after multiple iterations of optimization and ensures that the fluid flows in the transition channel at the most stable and compliant flow rate, thereby improving the working efficiency and performance of the entire nozzle system and reducing problems such as energy loss, vibration, and adverse effects on the nozzle structure caused by unstable flow rates.

[0035] Step S400: Based on the target flow velocity, the flow velocity of the target nozzle grid is optimized for a preset period to obtain the target installation scheme. Specifically, based on the target flow velocity, a high-precision sensor network is used to set monitoring points at key locations on the nozzle grid within a preset period to acquire flow velocity data in real time and set the flow velocity deviation range. Simultaneously, an adjustment plan is formulated for parameters including nozzle throat diameter, expansion section angle, inlet shape, fluid pressure, and temperature. Then, iterative optimization is performed according to the plan. After each parameter adjustment, the new flow velocity data is compared with the target flow velocity to evaluate the effect. Taking into account the interaction of multiple parameters, multiple iterations are performed to approximate the optimal combination. Finally, when the nozzle flow velocity stabilizes near the target flow velocity and meets the requirements, the installation scheme corresponding to this nozzle parameter combination is the target installation scheme. Applying this scheme can improve the power generation efficiency of the turbine and reduce energy loss, thereby achieving efficient and stable system operation.

[0036] This application embodiment employs geometric modeling of the target nozzle and meshing the model according to a preset mesh quality standard to generate the target nozzle mesh. Flow velocity analysis is performed on the nozzle mesh using simulation to obtain the velocity distribution. Streamline transition calculations are performed based on the velocity distribution, and the transition velocity is monitored to obtain the target velocity. Based on the velocity monitoring results, the nozzle mesh is periodically optimized, and the optimized nozzle installation scheme is finally determined. This achieves the technical goal of improving velocity stability through optimized nozzle configuration, thereby enhancing the operational reliability and efficiency of the turbine.

[0037] The specific embodiments described above do not constitute a limitation on the scope of protection of this application. Those skilled in the art should understand that various modifications, combinations, and substitutions can be made according to design requirements and other factors. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of this application should be included within the scope of protection of this application. In some cases, the actions or steps described in this application can be performed in a different order than that shown in the embodiments and still achieve the desired results. Furthermore, the processes depicted in the accompanying drawings do not necessarily require a specific or sequential order to achieve the desired results. In some embodiments, multitasking and parallel processing are also possible or may be advantageous.

Claims

1. An optimized method for installing the DC nozzle of a large impulse turbine, characterized in that, include: Perform geometric modeling of the target nozzle, and mesh the target nozzle model based on the preset mesh quality to obtain the target nozzle mesh; Based on the operational simulation of the target nozzle mesh, the target velocity mesh is obtained through velocity analysis to obtain the target velocity distribution; Based on the target nozzle velocity distribution, streamline the transition of the target nozzle grid, and monitor the transition velocity to obtain the target velocity, including: Based on the target velocity distribution, a streamlined progressive transition section is calculated for the target nozzle mesh to obtain a progressive channel; The progressive channel is configured with parameters based on the transition segment configuration model to obtain the transition channel, including: Supervised training is performed based on transition segment configuration length samples, transition segment configuration diameter samples, and transition segment flow velocity samples within a preset time period to obtain the transition segment configuration model; The mutation threshold is input into the transition segment configuration model for parameter configuration. Based on the obtained transition segment configuration length and transition segment configuration diameter, a progressive channel configuration is performed to obtain the transition channel. Obtaining a transition channel also includes: Feedback monitoring of the target flow velocity is performed based on the configuration length and diameter of the transition section to obtain the iterative flow velocity; The transition channel is iteratively assigned a value based on the iterative flow rate, and the obtained optimized flow rate is taken as the target flow rate. Monitor the transition flow velocity in the transition channel to obtain the target flow velocity; Based on the target flow velocity monitoring, the flow velocity of the target nozzle grid is optimized for a preset period to obtain the target installation scheme.

2. The method for optimizing the installation scheme of the DC nozzle of a large impulse turbine as described in claim 1, characterized in that, To obtain the preset mesh quality, including: Extract fluid velocity and fluid flow properties, and preset the flow type; Configure the mesh quality based on the flow type and obtain the preset mesh quality.

3. The method for optimizing the installation scheme of the DC nozzle of a large impulse turbine as described in claim 1, characterized in that, Obtain the target flow velocity mesh, including: Extract the target inlet, target outlet, and target wall from the target nozzle mesh; Configure inlet boundary conditions for the target inlet, configure outlet boundary conditions for the target outlet, and configure wall conditions for the target wall to complete the boundary condition configuration; The target nozzle mesh is simulated based on boundary conditions to obtain the target velocity mesh.

4. The method for optimizing the installation scheme of the DC nozzle of a large impulse turbine as described in claim 1, characterized in that, Obtaining the target velocity distribution includes: Based on the mutation threshold, the target flow velocity grid is identified, and the target mutation grid is extracted. If the target mutation grid is verified and a separation result is obtained by performing flow separation verification on the target mutation grid, the target mutation grid is added to the target velocity distribution.

5. The method for optimizing the installation scheme of the DC nozzle of a large impulse turbine as described in claim 4, characterized in that, Obtaining the target velocity distribution also includes: The target mutation grid is identified based on the pressure gradient threshold to obtain the target pressure grid; Based on the target pressure grid and the target neighboring grid, pressure gradient trend analysis is performed to obtain the target pressure trend; If the target pressure trend is determined not to meet the gradient fallback threshold, then the target pressure grid is added to the target velocity distribution.

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