Intelligent calculation method for hydraulic numerical simulation of side water inlet and outlet

Abstract

The invention discloses a side type water inlet and outlet hydraulic numerical simulation intelligent calculation method which comprises the following steps: S1, according to shape parameters of a side type water inlet and outlet, creating a parameterization construction method based on multi-level intelligent modeling; s2, intelligent positioning of a key boundary surface is completed by designing a DesignModeler geometric feature recognition algorithm; s3, constructing a water inlet and outlet distributed data transmission architecture based on a TCP / IP protocol, and realizing high-performance real-time data exchange of calculation data; s4, establishing a simulation mechanism module based on PyFluent to realize intelligent calculation of a water inlet and a water outlet and result feedback; according to the method, automatic and efficient calculation of the hydraulic characteristics of the side water inlet and outlet is realized.

Description

Technical Field

[0001] The invention relates to the technical field of water conservancy engineering, in particular to an intelligent calculation method for hydraulic numerical simulation of a side-type water inlet and outlet. Background Art

[0002] Pumped storage is a large-scale green energy storage method with mature technology and superior economy. It plays an important role in promoting my country's energy transformation and achieving carbon neutrality goals. Unlike the inlets and outlets of conventional hydropower stations, the inlets and outlets of pumped-storage power stations have complex two-way water flow characteristics. When the upper reservoir is in power generation condition, the water flows from the reservoir into the inlet and outlet (inflow), which is called the inlet. When the water flows in the tunnel under pumping condition, it diffuses from the diffusion section of the inlet and outlet and flows out to the reservoir through each diversion hole (outflow), which is called the outlet. The hydraulic characteristics of the side inlet and outlet are directly related to the operating safety and economic benefits of the pumped-storage power station, and the shape and structure of the inlet and outlet are directly related to its hydraulic characteristics. Therefore, the design specification of pumped-storage power stations puts forward the following requirements for the design of inlets and outlets:

[0003] (1) Under various operating conditions, the head loss of the side inlet and outlet should be small;

[0004] (2) Under both inflow and outflow conditions, the cross section of the trash rack should not have reverse flow velocity and the cross section velocity distribution should be relatively uniform. The velocity non-uniformity coefficient (the ratio of the maximum velocity passing the rack to the average velocity passing the rack) of the cross section of each orifice trash rack should be less than 2 and should not be greater than 1.5;

[0005] (3) Under inflow and outflow conditions, the flow distribution between orifices should be basically uniform, and the flow unevenness should be less than 10%;

[0006] (4) Under various inlet conditions, no harmful suction vortex will appear at the side inlet and outlet.

[0007] Therefore, it is of great significance to conduct in-depth research on the hydraulic characteristics of side inlets and outlets and optimize the design of side inlet and outlet structures.

[0008] The numerical simulation method is one of the methods to study the hydraulic characteristics of side inlets and outlets. It uses computers and mathematical models to solve the control equations according to the geometric shape and boundary conditions of the inlets and outlets, and obtains the hydraulic characteristic data of the inlets and outlets, providing a basis for engineering design. The advantage of numerical simulation is that it can quickly, flexibly and in detail obtain the flow field information of the inlets and outlets, but it also has the following disadvantages:

[0009] 1) Low time efficiency of pre-processing. Traditional numerical simulation methods require a lot of preparation work before simulation, including but not limited to geometric modeling, mesh generation and boundary condition setting, which will take up more time and resources and increase simulation calculation time.

[0010] 2) The effect of numerical simulation depends on the user's experience and varies from person to person. Since traditional numerical simulation methods are highly dependent on the operator's experience and judgment in terms of meshing and boundary condition setting, the simulation results are often highly subjective. Different operators may obtain different simulation results, resulting in differences between numerical simulation results and actual results.

[0011] 3) The operation complexity of the simulation process. In the traditional numerical simulation method, any modification of the inlet and outlet geometry or parameters requires re-gridding and simulation calculation, which leads to a large amount of repeated operation workload and increases the operation complexity of the simulation process. Summary of the invention

[0012] The purpose of the present invention is to overcome the above-mentioned shortcomings and provide an intelligent calculation method for hydraulic numerical simulation of side inlet and outlet, so as to realize automatic and efficient calculation of hydraulic characteristics of side inlet and outlet.

[0013] In order to solve the above technical problems, the technical solution adopted by the present invention is: a hydraulic numerical simulation intelligent calculation method for side inlet and outlet, comprising the following steps:

[0014] S1. According to the body parameters of the side inlet and outlet, a parametric construction method based on multi-level intelligent modeling is created;

[0015] S2, complete the intelligent positioning of key boundary surfaces by designing the DesignModeler geometric feature recognition algorithm;

[0016] S3, build a distributed data transmission architecture for water inlets and outlets based on TCP / IP protocol to achieve high-performance real-time data exchange of computing data;

[0017] S4. A simulation mechanism module is established based on PyFluent to realize intelligent calculation of water inlets and outlets and result feedback.

[0018] Preferably, the step S1 specifically includes the following process:

[0019] (1) Establish a precise positioning coordinate system with the end of the diversion pier as the origin to realize the spatial benchmark for integrated modeling of the entire process;

[0020] (2) According to the open channel design data, the structural characteristics of this section depend on the topographic and geological conditions and hydraulic requirements of the site; to facilitate modeling and calculation, the reservoir area is simplified into a rectangular platform, and a reverse slope section and a connecting section are set to achieve connection with the reservoir bottom; the intelligent assembly of components is realized through the advanced modeling method and Boolean operation of the Solid3d class library; and the complete open channel section geometry is constructed;

[0021] (3) Generation of vortex beam segments First, the geometric parameters of the vortex beam need to be defined, and its size is determined according to its specific position in the segment, that is, the position close to or far from the trash rack. For this purpose, an intelligent layout algorithm for vortex beams based on cumulative displacement is developed. For each vortex beam, the initial displacement vector V is calculated based on its position in the entire structure. init :

[0022]

[0023] L avb H is the length of the vortex beam section. avb is the height of the vortex beam, S or and W or is the orifice width and orifice height, i is the index of the vortex beam, indicating the horizontal layer of the vortex beam currently being processed; the horizontal position X j The calculation of is based on the cumulative length and spacing of the vortex beams; j is the index of the number of channels;

[0024]

[0025] T avb (k) is the length of the kth vortex beam, Gap is the spacing between each vortex beam; each vortex beam is moved by a translation transformation matrix, and the position of the vortex beam after movement is P new for:

[0026]

[0027] Among them, P old is the position of the previous vortex beam, T avb To prevent the vortex beam from being too thick, H or is the orifice height; according to the above formula, each cuboid of the vortex-proof beam section is generated in sequence and stored in the entity array; a complete vortex-proof beam section is formed;

[0028] (4) Due to its irregular shape, Bezier curves of different orders are used to parameterize the diffusion section of the side inlet and outlet. A dynamic surface generation system based on multiple control points is constructed. The control points are placed at the following positions:

[0029] 1) Geometric boundary point at the inlet: defines the starting section of the diffusion section;

[0030] 2) Intermediate control points in the transition zone: define the transition shape of the cross section to ensure smooth changes in the cross section;

[0031] 3) Geometric boundary points at the outlet: define the final cross-sectional shape of the diffuser;

[0032] The points generated by Bezier curves are connected into polylines to define the surface area of ​​the three-dimensional body; a closed two-dimensional area is formed by adding vertices AddVertexAt and setting the closed state Closed = true; they are lofted along the diffusion segment guide curve using the CreateLoftedSolid method to generate a diffusion segment solid model;

[0033] (5) For water conveyance tunnels, the cross-sectional shape and layout of the water conveyance tunnel shall be comprehensively considered.

[0034] More preferably, for the water conveyance tunnel, the comprehensive consideration of the cross-sectional shape and layout of the water conveyance tunnel specifically includes the following contents:

[0035] 1) Tunnel cross-section shape: a parameterized template library integrating typical cross-sections of circular, rectangular and city gate types; the circular cross-section is defined by the radius R c Parameter control; the city gate tunnel type adopts the city gate tunnel width W cg 、Chengmen tunnel height H cg and the radius R of the arc at the top of the tunnel t Three parameters are jointly controlled; the rectangular section is controlled by the rectangular tunnel width W sq and rectangular tunnel height H sq Two parameters are determined; for the conversion between different sections, the processing scheme of the automatic complete gradient section is implemented;

[0036] 2) Layout of water conveyance tunnels: For different layout forms of plane straight tunnels, plane curved tunnels, and vertical curved tunnels, the basic geometry is generated by using the stretching and lofting technology based on the normal direction; for tunnels with curved sections, the horizontal bend radius R is determined. nh , the bending radius R of the vertical elbow n sections nv And the horizontal bending angle α of the vertical elbow n section nv , horizontal elbow bending angle α sn 、Bending angle θ of vertical elbow n sections nv , and generate the corresponding elbow geometry; after the body shape is generated, the accuracy of the geometric shape is verified through seam analysis to check whether there are gaps, overlaps or interferences between the geometry segments.

[0037] Preferably, the step S2 specifically includes the following process:

[0038] (1) Based on the normal vector: opposite element f i The normal vector N = (n x ,n y ,n z ); the judgment criteria are: |n x When |>0.95, it is classified as a lateral boundary surface; |n y When |>0.95, it is classified as a longitudinal boundary surface; |nz When |>0.95, it is classified as a horizontal boundary surface;

[0039] (2) Calculate the coordinates of the centroid of the surface element C(f i )=(C x ,C y ,C z ) and the entrance reference position P in , exit reference position P out Distance:

[0040] D in =|C(f i )-P in | (4)

[0041] D out =|C(f i )-P out | (5)

[0042] When D in <δ, it is divided into the candidate surface of the entrance area. out <δ, it is divided into the candidate surface of the exit area, where δ is the preset position threshold;

[0043] (3) Determination based on normal vector:

[0044] For candidate face element f i The normal vector N = (n x ,n y ,n z ) and the angle θ between the main flow direction V:

[0045]

[0046] Inlet boundary: cosθ>cos(1°); outlet boundary: cosθ<-cos(1°);

[0047] Symmetry plane boundary: |N×N s |>0.99, where N s is the normal vector of the symmetry surface; the remaining closed surface elements are determined to be wall boundaries;

[0048] (4) Based on boundary closure verification:

[0049] Opposite element f i The boundary curve set E = {e 1 ,e 2 ,……e m}, calculate the continuity index Cc of the boundary curve:

[0050]

[0051] Where Pi,end is the end point of the i-th curve, P i,start is the starting point of the jth curve, m is the total number of boundary curves; calculate the closure index C of the boundary curve O :

[0052]

[0053] Where ∮ds is the total length of the closed loop of the boundary curve, |e i | is the sum of the lengths of each curve segment; calculate the directional continuity index C of the boundary curve d :

[0054]

[0055] Where T i,end is the tangent vector of the end point of the i-th curve, T j,start is the tangent vector of the starting point of the jth curve; when |Cc|<ε 1 And |C O |<ε 2 And C d <ε 3 ; Determined as a valid closed boundary, where ε 1 , ε 2 , ε 3 is the preset threshold.

[0056] Preferably, in step S3, the distributed data transmission architecture of the water inlet and outlet based on the TCP / IP protocol is constructed as follows:

[0057] (1) Based on the multiple structural characteristics of the inlet and outlet, a three-layer data transmission system is constructed;

[0058] (2) Based on the characteristics of the inlet and outlet data, an intelligent compression algorithm is developed; the inlet and outlet sections use a structured data storage format to process data; the symmetric structure uses a reference point mapping method to compress data; the tunnel section uses a feature point sparse storage scheme; the compression algorithm achieves a data compression ratio greater than 5 and a restoration error less than 0.1%;

[0059] (3) Establish a task allocation mechanism for parallel computing of numerical simulations;

[0060] (4) Construct a data processing strategy guided by hydraulic characteristics.

[0061] More preferably, the constructed three-layer data transmission system specifically includes the following contents:

[0062] 1) Geometry data layer, used to transmit the geometry parameters of tunnel section, inlet and outlet section and open channel section;

[0063] 2) Grid data layer, which transmits the overall grid information of the inlet and outlet, including basic grid data and local grid encryption information;

[0064] 3) Flow field data layer, which transmits the calculated velocity field, pressure field and turbulence characteristic data.

[0065] More preferably, the intelligent compression algorithm specifically includes the following contents:

[0066] The intelligent compression algorithm adopts different compression strategies according to the different structural characteristics of the inlet and outlet sections. The inlet and outlet sections are divided into non-uniform grid blocks. For each grid block, its topological structure identifier and grid connection relationship are recorded, and an association mapping table between grid blocks is established. The geometric parameters in each grid block are relative to the reference value P. cer (Geometric center) differential encoding, record the difference ΔP i,j,k =P i,j,k -P cer , where P i,j,k is the geometric parameter of a point in the grid block; then, the differential value ΔP is counted to generate a Huffman coding table to further compress the data;

[0067] Symmetrical structures are compressed using the reference point mapping method; the symmetry axis or symmetry plane is identified through geometric features, and the reference point set {R p}; For each point Q in the symmetric region, only its relative position to the reference point R is stored. p The offset vector Right now

[0068] The tunnel section adopts a sparse storage scheme for feature points. According to the layout and cross-section type of the tunnel section, the key characteristic parameters of the grid distribution are extracted. For a plane straight tunnel, only the grid distribution characteristics of a standard cross-section need to be stored, including the number of circumferential grid nodes n, the number of radial grid layers m, the radial grid density ratio λ, and the axial grid division parameter k. a ; For plane curved tunnels, the bending adaptive coefficient μ is introduced during circumferential meshing to make the inner mesh appropriately denser and the outer mesh appropriately sparser; for vertical curved tunnels, due to the existence of spatial torsion, the meshing needs to additionally consider the three-dimensional torsion compensation factor γ, and store the mesh rotation matrix at the three-dimensional key torsion position; firstly, the complete mesh information including the circumferential reference points and radial stratification points is stored on the mesh nodes, and only a small number of control points are stored for the middle section, and the remaining mesh points are generated by difference; at the same time, the symmetry of the tunnel section is used to further simplify the storage of circumferential mesh points.

[0069] More preferably, establishing a task allocation mechanism for numerical simulation parallel computing specifically includes the following contents:

[0070] According to the number of grids N in each channeli With the total number of grids N total Ratio and historical calculation time T i With the total computing time T total Ratio, calculate the load factor:

[0071]

[0072] Where W i The dynamic weight coefficient is 0.3 to 0.7. The weight coefficient is adjusted to ensure that the load deviation of each computing channel is less than the preset threshold, so as to achieve the optimal allocation of computing resources.

[0073] More preferably, the data processing strategy for constructing hydraulic characteristics orientation specifically includes the following contents:

[0074] 1) Establish a key hydraulic parameter extraction module to monitor head loss, flow velocity distribution and flow distribution in real time;

[0075] 2) Set the data transmission priority P = 0.4ΔH + 0.3ΔV + 0.3ΔQ, where ΔH is the head loss change rate, ΔV is the flow velocity pulsation intensity, and ΔQ is the flow distribution deviation; adopt a priority-based block transmission method to ensure the efficient return of the calculation result data.

[0076] Preferably, step S4 specifically includes the following process:

[0077] (1) Meshing: The HydroMeshGen class is developed to automate the entire mesh generation process, and the empirical parameters and control strategies in the traditional manual meshing method are encapsulated in a programmatic manner. The transition mesh layer is automatically constructed for the boundary of the vortex beam and the adjustment section to ensure the mesh quality. A progressive mesh encryption strategy is adopted to address the non-uniform expansion characteristics of the diffusion section.

[0078] (2) Solver configuration and calculation: Develop the FlowSolver class, and automatically complete the physical model selection and boundary parameter setting through the initFlow() and setBoundary() methods;

[0079] (3) Result evaluation and optimization iteration: The HydroOptEngine class is constructed to transform the traditional trial-and-error manual optimization process into a programmed iterative optimization process. The hydraulic properties are automatically evaluated by the HydroAnalyzer class, and the geometric parameters are automatically updated by the TopoEvolver class according to the feedback criteria, thus realizing iterative closed-loop automation.

[0080] The beneficial effects of the present invention are as follows: the present invention can complete the integrated operations of rapid three-dimensional modeling, intelligent boundary recognition, precise grid division, hydraulic numerical simulation and result feedback of the side inlet and outlet of a pumped-storage power station; realize the automated and efficient calculation of the hydraulic characteristics of the side inlet and outlet; overcome the shortcomings of the traditional numerical simulation method, such as low time efficiency of pre-processing, strong subjectivity of simulation results and cumbersome operation of the simulation process. BRIEF DESCRIPTION OF THE DRAWINGS

[0081] Figure 1 It is a general side-type water inlet and outlet of a pumped storage power station;

[0082] Figure 2 This is a parametric illustration of the open channel section;

[0083] Figure 3 It is the parameterization description of the inlet and outlet sections;

[0084] Figure 4 This is a diagram of the TCP / IP protocol data transmission architecture;

[0085] Figure 5 It is a flow chart of intelligent calculation method for hydraulic numerical simulation of side inlet and outlet;

[0086] Figure 6 Generate a schematic diagram of the results for the body shape;

[0087] Figure 7 Schematic diagram of boundary conditions in the calculation area;

[0088] Figure 8 This is the mesh division result diagram;

[0089] Fig. 9 The flow velocity distribution of the side inlet and outlet trash rack cross section;

[0090] Fig.10 Flow distribution for each orifice of the side inlet and outlet;

[0091] Fig.11 This is the flow velocity field of the side inlet and outlet. DETAILED DESCRIPTION

[0092] The present invention is further described in detail below in conjunction with the accompanying drawings and specific embodiments.

[0093] A method for intelligent calculation of hydraulic numerical simulation of side inlet and outlet, comprising the following steps:

[0094] S1. According to the body parameters of the side inlet and outlet, a parametric construction method based on multi-level intelligent modeling is created;

[0095] S2. Intelligent positioning of key boundary surfaces is accomplished by designing the DesignModeler geometric feature recognition algorithm.

[0096] S3, build a distributed data transmission architecture for water inlets and outlets based on TCP / IP protocol to achieve high-performance real-time data exchange of computing data;

[0097] S4. A simulation mechanism module is established based on PyFluent to realize intelligent calculation of water inlets and outlets and result feedback.

[0098] Preferably, in step S1, the parameterized construction method of multi-level intelligent modeling is:

[0099] (1) Establish a precise positioning coordinate system with the end of the diversion pier as the origin to realize the spatial benchmark of the integrated modeling of the whole process ( Figure 1 ). The specific symbols and definitions of the parameters of each section of the inlet and outlet are listed in Table 1.

[0100] Table 1 Parametric characteristics of side inlet / outlet

[0101]

[0102]

[0103] (2) According to the open channel design data, the structural characteristics of this section mainly depend on the topographic and geological conditions and hydraulic requirements of the site. To facilitate modeling and calculation, the reservoir area is simplified into a rectangular platform, and a reverse slope section and a connecting section are set to achieve connection with the reservoir bottom. The intelligent assembly of components is realized through the advanced modeling method and Boolean operation of the Solid3d class library; the complete open channel section geometry is constructed. The open channel section parameter settings are as follows: Figure 2 shown.

[0104] (3) Generation of vortex beam segments First, the geometric parameters of the vortex beams must be defined, and their dimensions must be determined based on their specific positions in the segments (close to or far from the trash rack). For this purpose, an intelligent placement algorithm for vortex beams based on cumulative displacement was developed. For each vortex beam, the initial displacement vector V is calculated based on its position in the entire structure. init :

[0105]

[0106] L avb H is the length of the vortex beam section. avb is the height of the vortex beam, S or and W or is the orifice width and orifice height, i is the index of the vortex beam, indicating the horizontal layer of the vortex beam currently being processed. The meaning of the parameters is shown in Table 1. Horizontal position X j The calculation of is based on the cumulative length and spacing of the vortex beams. j is the index of the number of channels.

[0107]

[0108] T avb (k) is the length of the kth vortex beam, and Gap is the spacing between each vortex beam. Each vortex beam is moved by a translation transformation matrix, and the position of the vortex beam after movement is P new for:

[0109]

[0110] Among them, P old is the position of the previous vortex beam, T avb To prevent the vortex beam from being too thick, H or is the orifice height. According to the above formula, each cuboid of the vortex beam section is generated in turn and stored in the entity array to form a complete vortex beam section.

[0111] (4) Due to its irregular shape, Bezier curves of different orders are used to parameterize the diffusion section of the side inlet and outlet. A dynamic surface generation system based on multiple control points is constructed. Figure 3 The control points are shown in red in (c). The control points are placed at the following positions:

[0112] 1) Geometric boundary point at the entrance: defines the starting section of the diffusion section.

[0113] 2) Intermediate control points in the transition zone: define the transition shape of the section to ensure smooth changes in the cross section.

[0114] 3) Geometric boundary points at the outlet: define the final cross-sectional shape of the diffuser.

[0115] The points generated by Bezier curves are connected into polylines to define the surface area of ​​the three-dimensional body. By adding vertices (AddVertexAt) and setting the closed state (Closed = true), a closed two-dimensional area is formed. They are lofted along the diffusion segment guide curve using the CreateLoftedSolid method to generate a diffusion segment solid model.

[0116] (5) For water conveyance tunnels, the cross-sectional shape and layout of the water conveyance tunnel shall be comprehensively considered.

[0117] 1) Tunnel cross-section shape: a parameterized template library integrating typical cross-sections such as circular, rectangular and city gate. c Parameter control; the city gate tunnel type adopts the city gate tunnel width W cg 、Chengmen tunnel height H cg and the radius R of the arc at the top of the tunnel t Three parameters are jointly controlled; the rectangular section is controlled by the rectangular tunnel width W sq and rectangular tunnel height H sqTwo parameters are determined. For the conversion between different sections, the processing scheme of the automatic complete gradient segment is provided.

[0118] 2) Layout of water conveyance tunnel: For different layout forms such as plane straight tunnel, plane curved tunnel, vertical curved tunnel, etc., the basic geometry is generated by stretching and lofting technology based on the normal direction. For tunnels with curved sections, the horizontal bend radius R is determined. nh , the bending radius R of the vertical elbow n sections nv And the horizontal bending angle α of the vertical elbow n section nv , horizontal elbow bending angle α sn 、Bending angle θ of vertical elbow n sections nv , and generate the corresponding elbow geometry. After the body shape is generated, the accuracy of the geometry is verified through seam analysis to check whether there are gaps, overlaps or interferences between the various geometry segments.

[0119] Preferably, in step S2, the DesignModeler geometric feature recognition algorithm is as follows:

[0120] (1) Based on the normal vector: opposite element f i The normal vector N = (n x ,n y ,n z ). The judgment criteria are: |n x When |>0.95, it is classified as a lateral boundary surface; |n y When |>0.95, it is classified as a longitudinal boundary surface; |n z When |>0.95, it is classified as a horizontal boundary surface.

[0121] (2) Calculate the coordinates of the centroid of the surface element C(f i )=(C x ,C y ,C z ) and the entrance reference position P in , exit reference position P out Distance:

[0122] D in =|C(f i )-P in | (4)

[0123] D out =|C(f i )-P out | (5)

[0124] When D in <δ, it is divided into the candidate surface of the entrance area. out <δ, it is divided into the candidate surface of the exit area, where δ is the preset position threshold.

[0125] (3) Determination based on normal vector:

[0126] For candidate face element f i The normal vector N = (n x ,n y ,n z ) and the angle θ between the main flow direction V:

[0127]

[0128] Inlet boundary: cosθ>cos(1°); outlet boundary: cosθ<-cos(1°).

[0129] Symmetry plane boundary: |N×N s |>0.99, where N s is the normal vector of the symmetry surface. The remaining closed surface elements are determined to be wall boundaries.

[0130] (4) Based on boundary closure verification:

[0131] Opposite element f i The boundary curve set E = {e 1 ,e 2 ,……e m}, calculate the continuity index Cc of the boundary curve:

[0132]

[0133] Where P i,end is the end point of the i-th curve, P i,start is the starting point of the jth curve, and m is the total number of boundary curves. Calculate the closure index C of the boundary curve O :

[0134]

[0135] Where ∮ds is the total length of the closed loop of the boundary curve, |e i | is the sum of the lengths of each curve segment. Calculate the directional continuity index C of the boundary curve d :

[0136]

[0137] Where T i,end is the tangent vector of the end point of the i-th curve, T j,start is the tangent vector of the starting point of the jth curve. When |Cc|<ε 1 And |C O |<ε 2 And C d <ε 3 . It is determined to be a valid closed boundary, where ε 1, ε 2 , ε 3 is the preset threshold.

[0138] Preferably, in step S3, the distributed data transmission architecture of the water inlet and outlet is:

[0139] (1) Based on the multiple structural characteristics of the inlet and outlet, a three-layer data transmission system is constructed, including:

[0140] 1) Geometry data layer, used to transmit the geometry parameters of tunnel section, inlet and outlet section and open channel section;

[0141] 2) Grid data layer, which transmits the overall grid information of the inlet and outlet, including basic grid data and local grid encryption information;

[0142] 3) Flow field data layer, which transmits the calculated velocity field, pressure field and turbulence characteristic data;

[0143] (2) Based on the characteristics of the inlet and outlet data, an intelligent compression algorithm is developed: the inlet and outlet sections use a structured data storage format to process data; the symmetric structure uses a reference point mapping method to compress data; and the tunnel section uses a feature point sparse storage scheme. This compression algorithm achieves a data compression ratio greater than 5 and a restoration error less than 0.1%.

[0144] The intelligent compression algorithm adopts different compression strategies according to the different structural characteristics of the inlet and outlet sections. The inlet and outlet sections are divided into non-uniform grid blocks. For each grid block, its topological structure identifier and grid connection relationship are recorded, and an association mapping table between grid blocks is established. The geometric parameters in each grid block are relative to the reference value P cer (Geometric center) differential encoding, record the difference ΔP i,j,k =P i,j,k -P cer , where P i,j,k is the geometric parameter of a point in the grid block. Then, the differential value ΔP is counted to generate a Huffman coding table to further compress the data.

[0145] Symmetrical structures are compressed using the reference point mapping method. The symmetry axis or symmetry plane is identified through geometric features, and the reference point set {R p For each point Q in the symmetric region, only its relative position to the reference point R is stored. p The offset vector Right now

[0146] The tunnel section adopts a sparse storage scheme for feature points. According to the layout and cross-section type of the tunnel section, the key characteristic parameters of the grid distribution are extracted. For a plane straight tunnel, only the grid distribution characteristics of a standard cross-section need to be stored, including the number of circumferential grid nodes (n), the number of radial grid layers (m), the radial grid density ratio (λ), and the axial grid division parameter (k a ); For plane curved tunnels, the bending adaptive coefficient (μ) is introduced in the circumferential meshing to make the inner mesh appropriately denser and the outer mesh appropriately sparser; For vertical curved tunnels, due to the existence of spatial torsion, the meshing needs to additionally consider the three-dimensional torsion compensation factor (γ), and the mesh rotation matrix is ​​stored at the three-dimensional key torsion position. First, the complete mesh information including the circumferential reference points and radial stratification points is stored on the mesh nodes, and only a small number of control points are stored for the middle section, and the remaining mesh points are generated by difference; At the same time, the symmetry of the tunnel section is used to further simplify the storage of circumferential mesh points.

[0147] (3) Establish a task allocation mechanism for parallel computing of numerical simulations, including the task allocation based on the number of grids N in each channel. i With the total number of grids N total Ratio and historical calculation time T i With the total computing time T total Ratio, calculate the load factor:

[0148]

[0149] Where W i The dynamic weight coefficient is 0.3 to 0.7. By adjusting the weight coefficient, the load deviation of each computing channel is ensured to be less than the preset threshold, so as to achieve the optimal allocation of computing resources.

[0150] (4) Constructing a hydraulic characteristics-oriented data processing strategy,

[0151] 1) Establish a key hydraulic parameter extraction module to monitor head loss, flow velocity distribution and flow distribution in real time;

[0152] 2) Set the data transmission priority P = 0.4ΔH + 0.3ΔV + 0.3ΔQ, where ΔH is the head loss change rate, ΔV is the flow velocity pulsation intensity, and ΔQ is the flow distribution deviation; adopt a priority-based block transmission method to ensure the efficient return of the calculation result data.

[0153] Preferably, in step S5, numerical simulation is performed on the hydraulic characteristics of the side inlet and outlet, and the simulation mechanism module construction scheme based on PyFluent is:

[0154] (1) Meshing: The HydroMeshGen class is developed to automate the entire mesh generation process, and the empirical parameters and control strategies in the traditional manual meshing method are encapsulated in a programmatic manner. The transition mesh layer is automatically constructed for the boundary of the vortex beam and the adjustment section to ensure the mesh quality. In view of the non-uniform expansion characteristics of the diffusion section, a progressive mesh encryption strategy is adopted.

[0155] (2) Solver configuration and calculation: Develop the FlowSolver class, which automatically completes the physical model selection and boundary parameter setting through methods such as initFlow() and setBoundary(). Automatic configuration greatly reduces human intervention and improves calculation efficiency.

[0156] (3) Result evaluation and optimization iteration: The HydroOptEngine class is constructed to transform the traditional trial-and-error manual optimization process into a programmed iterative optimization process. The HydroAnalyzer class is used to automatically evaluate the hydraulic properties, and the TopoEvolver class is used to automatically update the geometric parameters according to the feedback criteria, thus achieving iterative closed-loop automation.

[0157] Embodiment 1:

[0158] like Figure 5 As shown, the present invention provides an intelligent calculation method for hydraulic numerical simulation of side inlet and outlet, which specifically includes the following steps:

[0159] (1) Taking the side inlet and outlet of a pumped storage power station as an example, the specific implementation method is as follows: Figure 1-3 In this embodiment, the body parameters of the side-type water inlet and outlet are listed in Table 2.

[0160] Table 2 Body shape parameter results (unit: m; °)

[0161]

[0162] According to the parametric modeling rules, points, lines, surfaces and bodies are created in VS according to the design requirements and geometric parameters, and the sub-components of the inlet / outlet are established respectively, and the sub-components are assembled. The detailed body generation results are as follows Figure 6 shown.

[0163] (2) The DesignModeler geometric feature recognition algorithm is used to identify the symmetry planes, inlet / outlet sections, and wall features of the three-dimensional body. The corresponding boundary conditions are automatically set for the three-dimensional body, including symmetry boundary conditions, reservoir boundary conditions, and tunnel boundary conditions. Figure 5 shown.

[0164] (3) Based on the TCP / IP protocol distributed data transmission architecture, Socket programming and multi-threaded concurrent technology are used to achieve high-performance real-time data exchange of parameter data. TCP / IP protocol data transmission architecture Figure 4 The specific communication process is as follows:

[0165] 1) A three-layer data transmission system was constructed: the geometric data layer is responsible for transmitting the geometric parameters of the tunnel section, the inlet and outlet section, and the open channel section; the grid data layer transmits the overall grid information including the basic grid data and local encryption information; the flow field data layer transmits the calculated velocity field, pressure field, and turbulence characteristic quantity data. 2) An intelligent compression algorithm was developed based on the inlet and outlet data characteristics: the inlet and outlet sections record the topological identifiers and connection relationships, and establish an association mapping table. The differential encoding based on the geometric center combined with Huffman compression can achieve data reduction (the compression rate of key parameters is increased by 62%); the number of mapping points is extracted from the extended surface of the longitudinal symmetry axis of the standard section of the side inlet and outlet (the number of mapping points is reduced from 5120 to 60); the tunnel section extracts the key parameters of the section. This embodiment has spatial torsion, and the three-dimensional torsion compensation factor (γ=0.005) needs to be considered additionally. The complete grid information including circumferential reference points and radial stratification points is stored, and only a small number of control points are stored for the middle section, and the remaining grid points are generated by differential (the number of feature points is reduced from 1200 to 27). 3) Calculate the load factor, where the initial value of α is 0.5, and the dynamic adjustment range is 0.3 to 0.7 based on historical calculation data. By adjusting the weight coefficient, the load deviation of the four calculation channels is controlled within 8.5%.

[0166] (4) Intelligent calculation of the hydraulic characteristics of the side inlet and outlet. According to the three-dimensional shape and boundary conditions of the side inlet and outlet, the three-dimensional shape of the inlet and outlet is automatically meshed, such as Figure 8 According to this engineering feature, the built-in code automatically completes the settings of physical model parameters, material properties, solver, initial conditions, time step, number of iterations, convergence criteria, and post-processing parameters.

[0167] Using the PyFluent interface, the simulation parameters are automatically set according to the mesh model and boundary conditions of the inlet and outlet. Under the inflow condition of this project, the flow velocity is 2.95m / s, the boundary condition is the solid no-slip condition, and the turbulence model is the Realizable k-ε model; under the outflow condition, the flow velocity is 2.63m / s, the boundary condition is the solid no-slip condition, and the turbulence model is the RSM model. And based on the results of numerical simulation. Generate the corresponding hydraulic index key information and automatically draw graphics.

[0168] (6) In this embodiment, the generated numerical simulation intelligent calculation results are as follows:

[0169] 1. Head loss

[0170] Table 3 shows the head loss at the inlet and outlet of the pumping and power generation conditions. Under the pumping condition, the head loss is 0.76m, and the head loss coefficient is 0.34; under the power generation condition, the head loss is 0.30m, and the head loss coefficient is 0.23.

[0171] Table 3 Inlet and outlet head loss and head loss coefficient (pumping conditions)

[0172]

[0173] 2. Inlet and outlet flow velocity distribution

[0174] Fig. 9 The flow velocity distribution of the trash rack cross section at the inlet and outlet under pumping conditions. The average flow velocity of the trash rack cross section is 0.62~0.74m / s, the maximum flow velocity is 1.08m / s, and the velocity non-uniformity coefficient of each orifice (the ratio of the maximum flow velocity through the rack to the average flow velocity through the rack) is 1.05~1.47.

[0175] 3. Flow distribution of each orifice

[0176] The flow distribution of each orifice at the inlet and outlet is 22.90% to 27.24% (the ideal flow distribution is 25%), and the unevenness of the flow at each orifice is 7.57% to 8.96%. The results are as follows Fig.10 shown.

[0177] 4. Flow pattern near the inlet and outlet

[0178] Fig.11 It is the velocity field of the inlet and outlet. It can be seen from the figure that the water flow under the pumping condition (outflow) does not deviate at the beginning of the diffusion section, the mainstream is located in the middle of the orifice, there is no reverse flow velocity in the trash rack section, and the water surface near the inlet and outlet is stable.

[0179] Embodiment 2

[0180] This embodiment verifies the effectiveness and superiority of the method of the present invention through a comparative test with the traditional manual method. A side inlet and outlet of a pumped storage power station project is selected for comparative study.

[0181] 1. Multi-condition adaptability analysis

[0182] In the water level range of 270.67m-315.00m, 10 typical working conditions were selected for performance verification:

[0183] Table 4 Performance comparison under different working conditions

[0184]

[0185] 2. Computational efficiency and resource consumption analysis

[0186] Table 5 Comparison of computing resource utilization

[0187] Evaluation Dimensions Conventional manual method Method of the present invention Optimization level Single working condition calculation time (h) 24±4 2±0.5 91.6% shorter CPU usage (%) 85 62 27.1% reduction Memory usage (GB) 32 24 Save 25.0% Number of manual interventions (times / operating condition) 15-20 2-3 85.0% reduction

[0188] 3. Mesh quality and computational stability

[0189] Table 6 Comparison of grid characteristics and calculation accuracy

[0190] Grid Parameters Conventional manual method Method of the present invention Improved results Minimum orthogonal quality 0.55±0.03 0.62±0.02 12.7% improvement Maximum skewness 0.86±0.04 0.78±0.02 9.3% reduction Grid sensitivity (%) 2.8 1.2 57.1% reduction Y+ value range 30-120 30-80 More reasonable

[0191] 4. Boundary layer treatment effect

[0192] Table 7 Boundary layer characteristics comparison

[0193] Characteristics parameters Conventional manual method Method of the present invention Degree of improvement Velocity gradient near the wall (1 / s) 286 235 17.8% reduction Boundary layer thickness uniformity 0.82 0.91 11.0% increase Turbulence intensity fluctuation (%) ±8.5 ±4.2 50.6% reduction

[0194] Through the comparison of the above systematic experimental data, it can be seen that the advantages are significant in the following aspects:

[0195] (1) Adaptability to multiple working conditions: Under different water levels and flow conditions, the method of the present invention shows an efficiency improvement of 13.6%-17.1%, and has stronger adaptability. At the same time, this method can complete hydraulic analysis under various tunnel types such as single slope, plane turn, vertical turn, etc. (2) Computational efficiency: The design cycle is shortened from the traditional 24 hours to 2 hours, and the utilization rate of computing resources is significantly optimized; at the same time, this method is also applicable to various tunnel types such as single slope, plane turn, vertical turn, etc., and can achieve similar efficiency improvements. (3) Mesh quality: All indicators of mesh quality are better than traditional methods, ensuring the reliability of calculation results; (4) Boundary layer treatment: The flow characteristics near the wall are significantly improved, the turbulence intensity fluctuation is reduced by 50.6%, and the boundary layer thickness distribution is more uniform.

[0196] In summary, this intelligent calculation method for hydraulic numerical simulation can better simulate the hydraulic characteristics of side inlets and outlets, and can provide an effective tool and reference for the hydraulic calculation of the inlets and outlets of pumped storage power stations.

[0197] The above embodiments are only preferred technical solutions of the present invention and should not be regarded as limiting the present invention. The protection scope of the present invention shall be the technical solutions recorded in the claims, including equivalent replacement solutions of the technical features in the technical solutions recorded in the claims. That is, equivalent replacement improvements within this scope are also within the protection scope of the present invention.

Claims

1. An intelligent calculation method for hydraulic numerical simulation of side inlet and outlet, characterized by: The following steps are involved: S1. According to the body parameters of the side inlet and outlet, a parametric construction method based on multi-level intelligent modeling is created; S2, complete the intelligent positioning of key boundary surfaces by designing the DesignModeler geometric feature recognition algorithm; S3, build a distributed data transmission architecture for water inlets and outlets based on TCP / IP protocol to achieve high-performance real-time data exchange of computing data; S4. A simulation mechanism module is established based on PyFluent to realize intelligent calculation of water inlets and outlets and result feedback.

2. The intelligent calculation method for hydraulic numerical simulation of side inlet and outlet according to claim 1 is characterized by: The step S1 specifically The process includes: (1) Establish a precise positioning coordinate system with the end of the diversion pier as the origin to realize the spatial benchmark for integrated modeling of the entire process; (2) According to the open channel design data, the structural characteristics of this section depend on the topographic and geological conditions and hydraulic requirements of the site; to facilitate modeling and calculation, the reservoir area is simplified into a rectangular platform, and a reverse slope section and a connecting section are set to achieve connection with the reservoir bottom; the intelligent assembly of components is realized through the advanced modeling method and Boolean operation of the Solid3d class library; and the complete open channel section geometry is constructed; (3) Generation of vortex beam segments First, the geometric parameters of the vortex beam need to be defined, and its size is determined according to its specific position in the segment, that is, the position close to or far from the trash rack. For this purpose, an intelligent layout algorithm for vortex beams based on cumulative displacement is developed. For each vortex beam, the initial displacement vector V is calculated based on its position in the entire structure. init : L avb H is the length of the vortex beam section. avb is the height of the vortex beam, S or and W or is the orifice width and orifice height, i is the index of the vortex beam, indicating the horizontal layer of the vortex beam currently being processed; the horizontal position X j The calculation of is based on the cumulative length and spacing of the vortex beams; j is the index of the number of channels; T avb (k) is the length of the kth vortex beam, Gap is the spacing between each vortex beam; each vortex beam is moved by a translation transformation matrix, and the position of the vortex beam after movement is P new for: Among them, P old is the position of the previous vortex beam, T avb To prevent the vortex beam from being too thick, H or is the orifice height; according to the above formula, each cuboid of the vortex-proof beam section is generated in sequence and stored in the entity array; a complete vortex-proof beam section is formed; (4) Due to its irregular shape, Bezier curves of different orders are used to parameterize the diffusion section of the side inlet and outlet. A dynamic surface generation system based on multiple control points is constructed. The control points are placed at the following positions: 1) Geometric boundary point at the inlet: defines the starting section of the diffusion section; 2) Intermediate control points in the transition zone: define the transition shape of the cross section to ensure smooth changes in the cross section; 3) Geometric boundary points at the outlet: define the final cross-sectional shape of the diffuser; The points generated by Bezier curves are connected into polylines to define the surface area of ​​the three-dimensional body; a closed two-dimensional area is formed by adding vertices AddVertexAt and setting the closed state Closed = true; they are lofted along the diffusion segment guide curve using the CreateLoftedSolid method to generate a diffusion segment solid model; (5) For water conveyance tunnels, the cross-sectional shape and layout type of the water conveyance tunnel shall be comprehensively considered.

3. The intelligent calculation method for hydraulic numerical simulation of side inlet and outlet according to claim 2 is characterized by: For the water conveyance tunnel, the cross-sectional shape and layout of the water conveyance tunnel shall be comprehensively considered, including the following contents: 1) Tunnel cross-section shape: a parameterized template library integrating typical cross-sections of circular, rectangular and city gate types; the circular cross-section is defined by the radius R c Parameter control; the city gate tunnel type adopts the city gate tunnel width W cg 、Chengmen tunnel height H cg and the radius R of the arc at the top of the tunnel t The three parameters are controlled jointly; the rectangular section is controlled by the rectangular tunnel width W sq and rectangular tunnel height H sq Two parameters are determined; for the conversion between different sections, the processing scheme of the automatic complete gradient section is provided; 2) Layout of water conveyance tunnels: For different layout forms of plane straight tunnels, plane curved tunnels, and vertical curved tunnels, the basic geometry is generated by using the stretching and lofting technology based on the normal direction; for tunnels with curved sections, the horizontal bend radius R is determined. nh , the bending radius R of the vertical elbow n sections nv And the horizontal bending angle α of the vertical elbow n section nv , horizontal elbow bending angle α sn 、Bending angle θ of vertical elbow n sections nv , and generate the corresponding elbow geometry; after the body shape is generated, the accuracy of the geometric shape is verified through seam analysis to check whether there are gaps, overlaps or interferences between the geometry segments.

4. The intelligent calculation method for hydraulic numerical simulation of side inlet and outlet according to claim 1 is characterized by: The step S2 specifically includes the following process: (1) Based on the normal vector: opposite element f i The normal vector N = (n x ,n y ,n z ); the judgment criteria are: |n x When |>0.95, it is classified as a lateral boundary surface; |n y When |>0.95, it is classified as a longitudinal boundary surface; |n z When |>0.95, it is classified as a horizontal boundary surface; (2) Calculate the coordinates of the centroid of the surface element C(f i )=(C x ,C y ,C z ) and the entrance reference position P in , exit reference position P out Distance: D in =|C(f i )-P in | (4) D out =|C(f i )-P out | (5) When D in <δ, it is divided into the candidate surface of the entrance area. out <δ, it is divided into the candidate surface of the exit area, where δ is the preset position threshold; (3) Determination based on normal vector: For candidate face element f i The normal vector N = (n x ,n y ,n z ) and the angle θ between the main flow direction V: Inlet boundary: cosθ>cos(1°); outlet boundary: cosθ<-cos(1°); Symmetry plane boundary: |N×N s |>0.99, where N s is the normal vector of the symmetry surface; the remaining closed surface elements are determined to be wall boundaries; (4) Based on boundary closure verification: Opposite element f i The boundary curve set E = {e1, e2, ... e m }, calculate the continuity index Cc of the boundary curve: Where P i,end is the end point of the i-th curve, P i,start is the starting point of the jth curve, m is the total number of boundary curves; calculate the closure index C of the boundary curve O : Where ∮ds is the total length of the closed loop of the boundary curve, |e i | is the sum of the lengths of each curve segment; calculate the directional continuity index C of the boundary curve d : Where T i,end is the tangent vector of the end point of the i-th curve, T j,start is the tangent vector of the starting point of the jth curve; when |Cc|<ε1 and |C O |<ε2 and C d <ε3; it is determined to be a valid closed boundary, where ε1, ε2, and ε3 are preset thresholds.

5. The intelligent calculation method for hydraulic numerical simulation of side inlet and outlet according to claim 1 is characterized by: In step S3, the distributed data transmission architecture of the water inlet and outlet based on the TCP / IP protocol is constructed as follows: (1) Based on the multiple structural characteristics of the inlet and outlet, a three-layer data transmission system is constructed; (2) Develop an intelligent compression algorithm based on the characteristics of inlet and outlet data; The inlet and outlet sections use structured data storage format to process data; the symmetrical structure uses reference point mapping method to compress data; the tunnel section uses feature point sparse storage scheme; the compression algorithm achieves a data compression ratio greater than 5 and a restoration error less than 0.1%; (3) Establish a task allocation mechanism for parallel computing of numerical simulations; (4) Construct a data processing strategy guided by hydraulic characteristics.

6. The intelligent calculation method for hydraulic numerical simulation of side inlet and outlet according to claim 5, characterized in that: The three-layer data transmission system constructed specifically includes the following contents: 1) Geometry data layer, used to transmit the geometry parameters of tunnel section, inlet and outlet section and open channel section; 2) Grid data layer, which transmits the overall grid information of the inlet and outlet, including basic grid data and local grid encryption information; 3) Flow field data layer, which transmits the calculated velocity field, pressure field and turbulence characteristic data.

7. The intelligent calculation method for hydraulic numerical simulation of side inlet and outlet according to claim 5 is characterized by: The intelligent compression algorithm specifically includes the following: The intelligent compression algorithm adopts different compression strategies according to the different structural characteristics of the inlet and outlet sections. The inlet and outlet sections are divided into non-uniform grid blocks. For each grid block, its topological structure identifier and grid connection relationship are recorded, and an association mapping table between grid blocks is established. The geometric parameters in each grid block are relative to the reference value P. cer (Geometric center) differential encoding, record the difference ΔP i,j,k =P i,j,k -P cer , where P i,j,k is the geometric parameter of a point in the grid block; then, the differential value ΔP is counted to generate a Huffman coding table to further compress the data; Symmetrical structures are compressed using the reference point mapping method; the symmetry axis or symmetry plane is identified through geometric features, and the reference point set {R p }; For each point Q in the symmetric region, only its relative position to the reference point R is stored. p The offset vector Right now The tunnel section adopts a sparse storage scheme for feature points. According to the layout and cross-sectional type of the tunnel section, the key characteristic parameters of the grid distribution are extracted. For a plane straight tunnel, only the grid distribution characteristics of a standard cross-section need to be stored, including the number of circumferential grid nodes n, the number of radial grid layers m, the radial grid density ratio λ, and the axial grid division parameter k. a ; For plane curved tunnels, the bending adaptive coefficient μ is introduced during circumferential meshing to make the inner mesh appropriately denser and the outer mesh appropriately sparser; for vertical curved tunnels, due to the existence of spatial torsion, the meshing needs to additionally consider the three-dimensional torsion compensation factor γ, and store the mesh rotation matrix at the three-dimensional key torsion position; firstly, the complete mesh information including the circumferential reference points and radial stratification points is stored on the mesh nodes, and only a small number of control points are stored for the middle section, and the remaining mesh points are generated by difference; at the same time, the symmetry of the tunnel section is used to further simplify the storage of circumferential mesh points.

8. The intelligent calculation method for hydraulic numerical simulation of side inlet and outlet according to claim 5, characterized in that: The task allocation mechanism for establishing numerical simulation parallel computing specifically includes the following contents: According to the number of grids N in each channel i With the total number of grids N total Ratio and historical calculation time T i With the total computing time T total Ratio, calculate the load factor: Where W i The dynamic weight coefficient is 0.3 to 0.

7. The weight coefficient is adjusted to ensure that the load deviation of each computing channel is less than the preset threshold, so as to achieve the optimal allocation of computing resources.

9. The intelligent calculation method for hydraulic numerical simulation of side inlet and outlet according to claim 5, characterized in that: The data processing strategy for building hydraulic characteristics orientation specifically includes the following contents: 1) Establish a key hydraulic parameter extraction module to monitor head loss, flow velocity distribution and flow distribution in real time; 2) Set the data transmission priority P = 0.4ΔH + 0.3ΔV + 0.3ΔQ, where ΔH is the head loss change rate, ΔV is the flow velocity pulsation intensity, and ΔQ is the flow distribution deviation; adopt a priority-based block transmission method to ensure the efficient return of the calculation result data.

10. The intelligent calculation method for hydraulic numerical simulation of side inlet and outlet according to claim 1, characterized in that: The step S4 specifically includes the following process: (1) Meshing: The HydroMeshGen class is developed to automate the entire mesh generation process, and the empirical parameters and control strategies in the traditional manual meshing method are encapsulated in a programmatic manner. The transition mesh layer is automatically constructed for the boundary of the vortex beam and the adjustment section to ensure the mesh quality. A progressive mesh encryption strategy is adopted to address the non-uniform expansion characteristics of the diffusion section. (2) Solver configuration and calculation: Develop the FlowSolver class, and automatically complete the physical model selection and boundary parameter setting through the initFlow() and setBoundary() methods; (3) Result evaluation and optimization iteration: The HydroOptEngine class is constructed to transform the traditional trial-and-error manual optimization process into a programmed iterative optimization process. The hydraulic properties are automatically evaluated by the HydroAnalyzer class, and the geometric parameters are automatically updated by the TopoEvolver class according to the feedback criteria, thus realizing iterative closed-loop automation.

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