Method and system for servo valve flow channel vortex suppression structure based on CFD simulation

Abstract

The invention discloses a method and system for a servo valve flow channel vortex suppression structure based on CFD simulation, and relates to the technical field of fluid simulation, and the method comprises the following steps: constructing a computational fluid dynamics simulation model of a servo valve flow channel; a multi-criterion fusion algorithm is adopted to position the spatial position of the vortex in the flow channel and quantify the damage degree of the vortex; based on vortex characteristics and Reynolds number changes, a rectification structure with gradient changes of the inclination angle, the curvature radius and the porosity of a flow guide plate in a flow channel is optimized; by taking pressure drop, flow coefficient and flow uniformity as targets, constructing an agent model through a response surface method, and performing multi-target collaborative optimization on key parameters of the vortex suppression structure in combination with a genetic algorithm; and verifying the vortex inhibition effect under the transient working condition through a dynamic grid technology. The method has the beneficial effects that multi-target balance of pressure drop, flow coefficient and uniformity is realized through a systematic optimization design method in combination with a response surface model (second-order polynomial) and a genetic algorithm, and the optimal vortex suppression effect is realized.

Description

Technical Field

[0001] The present invention relates to the technical field of fluid simulation, and in particular to a method and system for a servo valve flow channel vortex suppression structure based on CFD simulation. Background Art

[0002] As a core component of a fluid control system, the flow characteristics within the servo valve directly affect the valve's performance. The following problems often arise in traditional servo valve flow channel design:

[0003] (1) Vortex flow is easily generated inside the flow channel, resulting in increased energy loss

[0004] (2) Vortex causes flow instability, affecting the valve response characteristics

[0005] (3) Traditional design methods rely on empirical formulas and experimental verification, resulting in long development cycles and high costs.

[0006] In the existing technology, vortex suppression mainly adopts structures such as guide plates and rectifier grids, but lacks a systematic optimization design method, making it difficult to achieve the optimal vortex suppression effect. Summary of the Invention

[0007] The main purpose of the present invention is to propose a method and system for vortex suppression structure of a servo valve flow channel based on CFD simulation, aiming to solve the technical problem of vortex suppression in the servo valve flow channel.

[0008] To achieve the above objectives, the present invention proposes a method and system for a servo valve flow channel vortex suppression structure based on CFD simulation, comprising the following steps:

[0009] Construct a computational fluid dynamics simulation model of the servo valve flow path;

[0010] A multi-criteria fusion algorithm is used to locate the spatial position of vortices in the flow channel and quantify their degree of damage.

[0011] Based on the vortex characteristics and Reynolds number changes, the rectification structure of the guide plate inclination angle, curvature radius, and porosity gradient in the flow channel is optimized;

[0012] Taking pressure drop, discharge coefficient, and flow uniformity as targets, a surrogate model was constructed using the response surface methodology, and a genetic algorithm was combined to perform multi-objective collaborative optimization of the key parameters of the vortex suppression structure.

[0013] The vortex suppression effect under transient conditions is verified using dynamic grid technology.

[0014] In one embodiment, the multiple criteria include a Q criterion, a λ2 criterion, and a composite criterion:

[0015] The Q criterion is calculated by symmetric / antisymmetric decomposition of the velocity gradient tensor (tensors A, B) and the Frobenius norm;

[0016] The λ2 criterion is based on the symmetric tensor A 2 +B 2 The negative eigenvalue of determines the vortex core area;

[0017] The composite criterion is defined by the composite tensor T = αB + βA 2 +γ(AB-BA) (weights satisfy α+β+γ=1), and the identification logic is dynamically adjusted in combination with vorticity, curl and Reynolds number.

[0018] In one embodiment, the inclination angle of the guide plate is adaptively adjusted with Re (small inclination angle in laminar flow area, large inclination angle in turbulent flow area);

[0019] The curvature radius is related to Re through an error function to match the vortex scale;

[0020] The rectifier structure is based on the Darcy-Forchheimer equation and a porosity gradient distribution is designed to gradually dissipate eddy energy.

[0021] In one embodiment, the response surface method and the genetic algorithm are combined to calculate the pressure drop ΔP(x), the flow coefficient C v (x) and flow uniformity σ(x) are multi-objectives, and the optimal geometric parameter combination is automatically searched.

[0022] In one embodiment, the region with the densest vorticity in the vortex is the vortex core. The determination of the vortex core region must simultaneously meet the following requirements:

[0023]

[0024] Among them, C Q ∈[0.15,0.35];

[0025] ∈ λ =0.1·‖A‖;

[0026] k∈[0.01,0.1];

[0027] Q thresh is the Q criterion threshold, used to filter out strong rotation areas;

[0028] Turbulentkinetic energy is turbulent kinetic energy, a physical quantity that describes the energy of turbulent motion;

[0029] λ2(T) is the second eigenvalue of the tensor T;

[0030] ‖‖ represents the Frobenius norm;

[0031] W is the vorticity;

[0032] is the curl of the velocity field.

[0033] In one embodiment, the turbulent kinetic energy reflects the kinetic energy of the random pulsation of the fluid particles and is directly related to the variance of the velocity components u′, v′, and w′. The calculation formula is:

[0034]

[0035] In one embodiment, the vortex core boundary is determined by the second-order derivative extreme point + Neumann boundary condition: Core position: Solve

[0036]

[0037] H(-λ2) is the Heaviside step function, which takes the value of 1 when its parameter -λ2 is greater than 0, and 0 otherwise;

[0038] Boundary conditions:

[0039]

[0040] represents the partial derivative along the normal direction;

[0041] Indicates the boundary of the computational region.

[0042] In one embodiment, the weights of the composite criterion are α=0.6, β=0.3, and γ=0.1, and the fluid rotation characteristics are constrained by the second eigenvalue λ2(T) of the composite tensor T.

[0043] In one embodiment, the multi-objective collaborative optimization method constructs a parameter correlation matrix by quantifying the influence weights of different geometric parameter combinations on pressure drop, flow coefficient, and flow uniformity.

[0044] In one embodiment, the method comprises:

[0045] Flow field modeling module: used to build a fluid simulation model of the servo valve flow channel;

[0046] Vortex identification module: uses a multi-criteria fusion algorithm (Q criterion, λ2 criterion, composite criterion) to locate and quantify the vortex characteristics in the flow channel;

[0047] Structural design module: Based on vortex characteristics and Reynolds number changes, parametric design of guide vane inclination angle, curvature radius and porosity gradient rectification structure;

[0048] Optimization module: Response surface methodology and genetic algorithm are used to perform multi-objective optimization of vortex suppression structure parameters;

[0049] Dynamic verification module: simulates the eddy current suppression effect under transient conditions through dynamic mesh technology.

[0050] The technical solution of the present invention suppresses vortices through characteristic equations: turbulence intensity is quantified through Galileo invariants, and the characteristic values ​​are dynamically adjusted to optimize the suppression structure;

[0051] Multi-objective collaborative optimization: combining the response surface model (second-order polynomial) with the genetic algorithm to achieve a multi-objective balance among pressure drop, flow coefficient, and uniformity;

[0052] Dynamic grid verification: Dynamic grid technology is used to simulate the eddy current suppression effect under transient conditions, and the optimal vortex suppression effect is achieved through a systematic optimization design method. BRIEF DESCRIPTION OF THE DRAWINGS

[0053] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the following briefly introduces the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on the structures shown in these drawings without paying any creative work.

[0054] Figure 1 A flow chart of the method and system for the swirl suppression structure of the servo valve flow channel based on CFD simulation provided by the present invention;

[0055] Figure 2 A diagram showing simulation results of a method and system for suppressing vortex in a servo valve flow passage based on CFD simulation provided by the present invention;

[0056] The purpose, features and advantages of the present invention will be further described with reference to the accompanying drawings and in conjunction with the embodiments. DETAILED DESCRIPTION

[0057] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making any creative efforts shall fall within the scope of protection of the present invention.

[0058] It should be noted that if the embodiments of the present invention involve directional indications (such as up, down, left, right, front, back, etc.), the directional indications are only used to explain the relative position relationship, movement status, etc. between the components in a certain specific posture. If the specific posture changes, the directional indication will also change accordingly. Unless otherwise clearly specified and limited, the terms "install", "connect", and "connect" should be understood in a broad sense. For example, it can be a fixed connection, a detachable connection, or an integral connection; it can be a mechanical connection or an electrical connection; it can be a direct connection, or it can be indirectly connected through an intermediate medium, or it can be a connection between the two components. For ordinary technicians in this field, the specific meanings of the above terms in this application can be understood according to the specific circumstances.

[0059] In addition, if there are descriptions of "first", "second", etc. in the embodiments of the present invention, the descriptions of "first", "second", etc. are only for descriptive purposes and cannot be understood as indicating or implying their relative importance or implicitly indicating the number of the indicated technical features. Thus, the features defined as "first" or "second" can explicitly or implicitly include at least one of the features. Moreover, the terms "comprise", "include" or any other variations thereof are intended to cover non-exclusive inclusion, so that a process, method, article or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, article or device. Without further restrictions, an element defined by the sentence "comprises a..." does not exclude the presence of other identical elements in the process, method, article or device including the elements. In addition, if "and / or" or "and / or" appears in the full text, its meaning includes three parallel solutions. Taking "A and / or B" as an example, it includes solution A, solution B, or solutions that satisfy both A and B. In addition, the technical solutions between the various embodiments can be combined with each other, but they must be based on the fact that ordinary technicians in this field can implement them. When the combination of technical solutions is mutually contradictory or cannot be implemented, it should be deemed that such a combination of technical solutions does not exist and is not within the scope of protection required by the present invention.

[0060] The present invention proposes a method and system for swirl suppression of a servo valve flow channel based on CFD simulation, comprising the following steps:

[0061] Construct a computational fluid dynamics simulation model of the servo valve flow path;

[0062] A multi-criteria fusion algorithm is used to locate the spatial position of vortices in the flow channel and quantify their degree of damage.

[0063] Based on the vortex characteristics and Reynolds number changes, the rectification structure of the guide plate inclination angle, curvature radius, and porosity gradient in the flow channel is optimized;

[0064] Taking pressure drop, discharge coefficient, and flow uniformity as targets, a surrogate model was constructed using the response surface methodology, and a genetic algorithm was combined to perform multi-objective collaborative optimization of the key parameters of the vortex suppression structure.

[0065] The vortex suppression effect under transient conditions is verified using dynamic grid technology.

[0066] It is more efficient to find vortices in the flow channel through composite criteria; by using the structural parameters in the flow channel as the optimization guide, based on the vortex characteristics and Reynolds number changes, with pressure drop, flow coefficient, and flow uniformity as the goals, an algorithm is used to screen excellent vortex suppression structures, and finally dynamic grid technology is used to verify the optimization effect, realizing a full-link process from identifying vortices to optimizing vortices and finally selecting the best, to achieve the best vortex suppression effect.

[0067] Specifically, the present invention provides a systematic solution on a simulation path for eliminating vortices in a flow channel.

[0068] In one embodiment, the multiple criteria include a Q criterion, a λ2 criterion, and a composite criterion:

[0069] The Q criterion is calculated by symmetric / antisymmetric decomposition of the velocity gradient tensor (tensors A, B) and the Frobenius norm;

[0070] The λ2 criterion is based on the symmetric tensor A 2 +B 2 The negative eigenvalue of determines the vortex core area;

[0071] The composite criterion is defined by the composite tensor T = αB + βA 2 +γ(AB-BA) (weights satisfy α+β+γ=1), and the identification logic is dynamically adjusted in combination with vorticity, curl and Reynolds number.

[0072] In one embodiment, the inclination angle of the guide plate is adaptively adjusted with Re (small inclination angle in laminar flow area, large inclination angle in turbulent flow area);

[0073] The curvature radius is related to Re through an error function to match the vortex scale;

[0074] The rectifier structure is based on the Darcy-Forchheimer equation and a porosity gradient distribution is designed to gradually dissipate eddy energy.

[0075] In one embodiment, the response surface method and the genetic algorithm are combined to calculate the pressure drop ΔP(x), the flow coefficient C v (x) and flow uniformity σ(x) are multi-objectives, and the optimal geometric parameter combination is automatically searched.

[0076] In one embodiment, the region with the densest vorticity in the vortex is the vortex core. The determination of the vortex core region must simultaneously meet the following requirements:

[0077]

[0078] Among them, C Q ∈[0.15,0.35];

[0079]

[0080] Tanh(x) characteristics: x=0, tanh(x)=0; x=∞, tanh(x)=1.

[0081] When Re≈8000, C Q =0.2 (transition zone);

[0082] When Re=∞, C Q =0.25 (fully developed turbulence region);

[0083] The ΔRe least squares method was used to fit the experimental data to obtain 2000

[0084]

[0085] In a typical servo valve flow channel (Re∈[2000,15000], the ratio is measured in the range of [0.15,0.35].

[0086] ∈ λ =0.1·‖a‖;

[0087] k∈[0.01,0.1];

[0088] Q thresh is the Q criterion threshold, used to filter out strong rotation areas;

[0089] Turbulent kinetic energy is a physical quantity that describes the energy of turbulent motion.

[0090] λ2(T) is the second eigenvalue of the tensor T;

[0091] ‖‖ represents the Frobenius norm;

[0092] W is the vorticity;

[0093] is the curl of the velocity field.

[0094] In one embodiment, the turbulent kinetic energy reflects the kinetic energy of the random pulsation of the fluid particles and is directly related to the variance of the velocity components u′, v′, and w′. The calculation formula is:

[0095]

[0096] In one embodiment, the vortex core boundary is determined by the second-order derivative extreme point + Neumann boundary condition: Core position: Solve

[0097]

[0098] H(-λ2) is the Heaviside step function, which takes the value of 1 when its parameter -λ2 is greater than 0, and 0 otherwise;

[0099] Boundary conditions:

[0100]

[0101] represents the partial derivative along the normal direction;

[0102] Indicates the boundary of the computational region.

[0103] In one embodiment, the weights of the composite criterion are α=0.6, β=0.3, and γ=0.1, and the fluid rotation characteristics are constrained by the second eigenvalue λ2(T) of the composite tensor T.

[0104] In one embodiment, the multi-objective collaborative optimization method constructs a parameter correlation matrix by quantifying the influence weights of different geometric parameter combinations on pressure drop, flow coefficient, and flow uniformity.

[0105] In one embodiment, the method comprises:

[0106] Flow field modeling module: used to build a fluid simulation model of the servo valve flow channel;

[0107] Vortex identification module: uses a multi-criteria fusion algorithm (Q criterion, λ2 criterion, composite criterion) to locate and quantify the vortex characteristics in the flow channel;

[0108] Structural design module: Based on vortex characteristics and Reynolds number changes, parametric design of guide vane inclination angle, curvature radius and porosity gradient rectification structure;

[0109] Optimization module: Response surface methodology and genetic algorithm are used to perform multi-objective optimization of vortex suppression structure parameters;

[0110] Dynamic verification module: simulates the eddy current suppression effect under transient conditions through dynamic mesh technology.

[0111] The following describes the contents involved in the above embodiment in conjunction with a preferred embodiment:

[0112] 1. Vortex identification and quantification method: (Multi-criteria fusion identification algorithm: to achieve accurate positioning of vortexes and quantify the degree of damage, providing data support for subsequent optimization)

[0113] 1.1 Basic vortex identification method

[0114] The vortex identification methods are all based on the eigenvalue of the velocity gradient tensor.

[0115]

[0116] is the Laplace operator;

[0117] (u, v, w): Represents the components of the velocity vector in the direction of V. That is, u is the component of the velocity in the x direction;

[0118] v is the component of velocity in the y direction;

[0119] w is the component of velocity in the z direction.

[0120] u, v, w are the same as u, v, ω.

[0121] Its characteristic equation is:

[0122]

[0123] The above formula is rewritten using the three Galilean invariants P, Q, and R of the characteristic equation, where P is the pressure;

[0124] Q represents flow;

[0125] R represents the radius of curvature;

[0126] It can be written as:

[0127] (λ-P)(λ-Q)(λ-R)=0

[0128] λ 3 +Pλ 2 +Qλ+R=0

[0129] in,

[0130] P=-(λ1+λ2+λ3)

[0131] Q=λ1λ2+λ2λ3+λ3λ1

[0132] R=λ1λ2λ3

[0133] Among them, λ1, λ2, and λ3 are respectively expressed as The three eigenvalues ​​of .

[0134] The Galilean invariance property is not derived by formula, but is a hypothetical law. The Galilean transformation describes the conversion relationship between different inertial reference frames. For example, when observing the same physical process from a stationary reference frame to a uniformly moving reference frame, the physical laws should remain unchanged.

[0135] Here, the invariance of P, Q, and R is represented. P, the pressure, is a scalar quantity that remains constant across inertial reference frames; R, the radius of curvature, is a geometric quantity that is also independent of the choice of reference frame; and Q, the flow rate, can also be invariant if defined relative to a boundary or control surface. Therefore, P, Q, and R can, in a sense, be chosen as Galilean invariants, useful for constructing physical models that hold true across different inertial reference frames. This is primarily intended to eliminate the effects of reference frame motion on vortex core identification and is suitable for dynamic conditions.

[0136] The Q criterion is to use Q>0. The specific calculation can be obtained by decomposition:

[0137]

[0138] Q can be written as:

[0139]

[0140] |||| represents the Frobenius norm.

[0141] λ2 criterion:

[0142]

[0143] Where P represents pressure and ρ is density. 2 +B 2 When there are two negative eigenvalues, the pressure is minimized in the plane defined by the eigenvectors corresponding to these two negative eigenvalues. Assuming the eigenvalue subscripts are arranged in descending order, λ1>λ2>λ3, then there are two eigenvalues, equivalent to λ2<0, hence the name λ2 method. The location of the vortex is the region where λ2<0.

[0144] Vorticity W: the curl of the velocity field

[0145]

[0146] 1.2 Unified derivation of composite criteria

[0147] Tensor Invariants Refactoring: Defining Composite Tensors

[0148] T=αB+βA 2 +γ(AB-BA)

[0149] The weight coefficient satisfies α+β+γ=1 (the preferred range in the patent is α=0.6, β=0.3, γ=0.1)

[0150] Composite feature conditions:

[0151] 1.2.1 The vortex core region must meet the following requirements:

[0152] These three conditions work together to identify and judge vortex structures or specific flow characteristics in the fluid. Specifically:

[0153] The first condition determines whether the vortex strength is large enough by comparing Q with its threshold;

[0154] The second condition determines whether the fluid deformation or rotation characteristics meet the requirements by limiting the characteristic value λ2(T);

[0155] The third condition determines whether the degree of fluid rotation is significant by comparing the curl of the velocity field with the vortex strength.

[0156]

[0157] Among them, C Q =0.25,∈ λ =0.1·‖A‖, κ∈[0.01,0.1];

[0158] Q thresh is the Q criterion threshold, used to filter out strong rotation areas;

[0159] Turbulent kinetic energy is a physical quantity that describes the energy of turbulent motion. It reflects the kinetic energy of the random pulsation of fluid particles and is directly related to the variance of the velocity components u′, v′, and w′. The calculation formula is:

[0160]

[0161] The larger the value, the more intense the turbulent pulsation.

[0162] λ2(T) is the second eigenvalue of the tensor T.

[0163] 1.2.2 Accurate determination of vortex core boundary: Identify and locate vortex structures in the fluid. Specifically, it determines the position and intensity of the vortex through the second-order derivative extreme point location method combined with the Neumann boundary condition.

[0164] Locating the second-order derivative extreme points: By solving the points where the second-order derivative is equal to zero, the core position of the vortex structure can be found. These points usually correspond to the vortex center or the place where the vortex intensity is the greatest.

[0165]

[0166] H(-λ2) is the Heaviside step function, which takes the value of 1 when its parameter -λ2 is greater than 0, and 0 otherwise.

[0167] Combined with the Neumann boundary condition: ensure that the rate of change of the vortex intensity (along the normal direction) on the boundary of the calculation area is zero, prevent the vortex structure from showing discontinuous or abnormal changes at the boundary, and ensure the rationality and stability of the calculation results.

[0168]

[0169] represents the partial derivative along the normal direction;

[0170] Indicates the boundary of the computational region.

[0171] 1.3 Theoretical basis of dynamic parameters:

[0172] 1.3.1 Reynolds number adaptive threshold:

[0173] Based on the local equilibrium assumption of turbulence: In turbulent flows, the local equilibrium assumption states that, within a certain range, the generation, transmission, and dissipation of turbulent energy are in a state of dynamic equilibrium. Therefore, changes in the Reynolds number can reflect changes in turbulence intensity.

[0174]

[0175] Q thresh (Re) represents the adaptive threshold value that changes with the Reynolds number Re;

[0176] Q ∞ is the high Reynolds number limit, which is 0.2;

[0177] Re: Reynolds number, a dimensionless number for fluid flow, used to determine the flow state (laminar or turbulent);

[0178] Re c : Critical Reynolds number. When the Reynolds number reaches this value, the flow begins to transition from laminar flow to turbulent flow. The value is 3000.

[0179] The formula adaptively adjusts the threshold Q by the Reynolds number Re thresh , which reflects the law of how turbulence intensity changes with Reynolds number. In practical applications, corresponding thresholds can be calculated based on different Reynolds numbers to identify and analyze turbulent structures.

[0180] 1.3.2 Vortex strength weight factor: defines the vortex strength contribution, combines the effects of vorticity, Q criterion and Reynolds number, and can comprehensively evaluate the vortex strength contribution of a certain point in the fluid.

[0181]

[0182] 2. Parametric suppression structure design:

[0183] By parametrically defining parameters such as the inclination angle θ, the curvature radius R (ratio of the channel height R / H), and the vortex evolution under different Reynolds numbers, the channel structure is optimized.

[0184] 2.1 According to the boundary layer theory, the relationship between the characteristic length scale of the vortex near the wall and Re is:

[0185]

[0186] σ v is the characteristic length of the vortex core, D h is the hydraulic diameter, C1 is the empirical coefficient, which is set to 0.5, ρ is the fluid density, μ is the fluid dynamic viscosity, and u is the average flow velocity.

[0187] 2.2 Effect of guide plate inclination angle on flow separation:

[0188]

[0189] ΔRe is the turbulence transition range; θ0 is the reference angle; Δθ is the adjustment amplitude.

[0190] When Re <Re c When Re>Re c When the flow is diverted, a large inclination angle (≈60°) enhances the diversion effect.

[0191] 2.3 Empirical relationship between curvature radius and vortex intensity:

[0192]

[0193] When Re is 8000, erf(0)=0,

[0194] C2 directly corresponds to the ratio of the curvature radius to the hydraulic diameter when the Reynolds number is 8000, which is the benchmark reference point of the model and is approximately 0.15.

[0195]

[0196] This formula ensures that:

[0197] Low Re (Re<5000): small curvature (R / D h ≈0.1) enhanced eddy dissipation;

[0198] High Re (Re>10000): large curvature (R / D h ≈0.3) to reduce secondary flow losses.

[0199] 2.4 A rectifier structure with a porosity gradient change is set at the sudden change point of the flow channel to gradually dissipate the eddy energy.

[0200] Based on the Darcy-Forchheimer equation, the flow field governing equation is modified as follows:

[0201]

[0202] Where: ε is the porosity; V is the fluid velocity; ρ is the fluid density; P is the pressure; represents the velocity tensor; μ is the fluid dynamic viscosity; α(ε) is the shape factor related to the void fraction; β(ε) is the inertia factor related to the porosity; dp is the particle diameter; T is the viscous stress tensor.

[0203] Definition of eddy energy density Its dissipation rate is:

[0204]

[0205] C d is a constant related to dielectric properties, C f is the turbulence characteristic constant.

[0206] Optimal porosity distribution: To make the eddy energy decay exponentially along the flow channel E v (x) = E v0 e -λx , and we get:

[0207]

[0208] ε(x) is the porosity at position x; ε0 is the porosity at the initial position; ε L is the porosity at the end of the flow channel; L is the total length of the flow channel; and x is the distance along the flow channel.

[0209] In order to achieve a smooth transition, the aperture changes according to a quadratic law:

[0210]

[0211] d p (x) Aperture diameter at position x.

[0212] 3 Intelligent optimization process:

[0213] Combining the response surface method (RSM) with the genetic algorithm (NSGA-II), the pressure drop ΔP(x), the flow coefficient C v (x) and flow uniformity σ(x) are multi-objectives, and the optimal geometric parameter combination is automatically searched.

[0214] Multi-objective function definition:

[0215]

[0216] f1(x) aims to reduce the pressure drop, f2(x) improves the flow performance, and f3(x) increases the uniformity of the velocity distribution.

[0217] Constructing a response surface model (second-order polynomial)

[0218]

[0219] Indicates the predicted target response value, which is the above ΔP(x), C v (x), σ(x);

[0220] β0, β i , β ii , β ij , represents the response value of the model;

[0221] x i are geometric parameters (inclination angle θ, curvature radius R (ratio to channel height R / H), porosity ε).

[0222] With the goal of minimizing ΔP and σ and maximizing Cv, the NSGA-II algorithm is run to obtain the Pareto frontier.

[0223] Pareto frontier analysis:

[0224]

[0225] The TOPSIS method is used to select the comprehensive optimal solution from the Pareto solution set.

[0226] 1) Standardized Pareto frontier data

[0227] Normalize the target values ​​of the Pareto solution set: Normalize the evaluation matrix X of the mth solution and nth target.

[0228]

[0229] 2) Weighted normalization matrix

[0230] v ij =w j ·r ij

[0231] w j is the weight vector, and the weight is adjusted dynamically according to the working conditions

[0232]

[0233] 3) Determine the ideal solution and negative ideal solution

[0234] Ideal solution A + ={minv i1 ,maxv i2 ,minv i3}

[0235] Negative ideal solution A - ={maxv i1 ,maxv i2 ,maxv i3}

[0236] 4) Calculate distance and proximity

[0237]

[0238] Select closeness C i The largest solution is regarded as the optimal solution.

[0239] Dynamic mesh simulation verification: For the transient working conditions of the servo valve spool movement, dynamic mesh technology is used to simulate the suppression effect of the suppression structure on transient vortexes.

[0240] like Figure 2 As shown in FIG, based on the comparison of different vortex identification methods, the identification effect of the traditional single criterion (Q / λ2) and the composite criterion of the present invention is compared, and the missed detection rate of the vortex is reduced by about 62%.

[0241] The following are some explanations of terms:

[0242] Laplace operator: Laplace operator (Laplacian) is an important second-order differential operator in mathematics and physics, which is used to describe the smoothness or "uniformity" of a function in space.

[0243] Galileo invariant: Galileo invariant is a physical quantity that describes fluid motion and is not affected by the observer's uniform motion state (that is, the quantity that remains unchanged under Galileo transformation).

[0244] Turbulent kinetic energy: Turbulent kinetic energy (TKE) is the core parameter in fluid mechanics that describes the energy of turbulent motion. It is defined as half of the sum of the square root of the square of the pulsating velocity components of the fluid particles.

[0245] Pareto frontier: It is a core concept in the field of multi-objective optimization, which refers to the boundary or surface formed by the set of all optimal trade-off solutions between multiple conflicting objectives.

[0246] TOPSIS method: sort the solutions by calculating their comprehensive distance from the ideal optimal solution (positive ideal solution) and the ideal worst solution (negative ideal solution), and select the solution that is closest to the optimal solution and farthest from the worst solution.

[0247] It should be understood that the references to "one embodiment" or "one example" throughout the specification mean that the specific features, structures, or characteristics associated with the example are included in at least one example of the present invention. Therefore, the phrases "in one embodiment" or "in one example" appearing throughout the specification do not necessarily refer to the same example. In addition, these specific features, structures, or characteristics may be combined in any suitable manner in one or more examples. Those skilled in the art should also be aware that the examples described in the specification are all optional examples, and the actions and modules involved are not necessarily required for the present invention.

[0248] In various embodiments of the present invention, it should be understood that the size of the serial numbers of the above-mentioned processes does not necessarily mean the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of the present invention.

[0249] The flow charts and block diagrams in the accompanying drawings of the present invention illustrate the possible implementation architecture, functions and operations of the systems, methods and computer program products according to various embodiments of the present application. In this regard, each box in the flow chart or block diagram can represent a module, program segment or a part of code, and the module, program segment or a part of code contains one or more executable instructions for realizing the specified logical function. It should also be noted that in some alternative implementation schemes, the functions marked in the box can also occur in a different order than those marked in the accompanying drawings. For example, two boxes represented in succession can actually be executed substantially in parallel, and they can sometimes be executed in the opposite order, which is determined based on the functions involved. It should be noted that each box in the block diagram and / or flow chart, and the combination of the boxes in the block diagram and / or flow chart can be implemented by a dedicated hardware-based system that performs the specified function or operation, or can be implemented by a combination of dedicated hardware and computer instructions.

[0250] The above description is merely an exemplary embodiment of the present invention and does not limit the patent scope of the present invention. Any equivalent structural transformation made by utilizing the contents of the present invention's description and drawings under the technical concept of the present invention, or directly / indirectly applied in other related technical fields, is included in the patent protection scope of the present invention.

Claims

1. A method for swirl suppression structure of a servo valve flow channel based on CFD simulation, characterized in that: The following steps are involved: Construct a computational fluid dynamics simulation model of the servo valve flow path; A multi-criteria fusion algorithm is used to locate the spatial position of vortices in the flow channel and quantify their degree of damage. Based on the vortex characteristics and Reynolds number changes, the rectification structure of the guide plate inclination angle, curvature radius, and porosity gradient in the flow channel is optimized; Taking pressure drop, discharge coefficient, and flow uniformity as targets, a surrogate model was constructed using the response surface methodology, and a genetic algorithm was combined to perform multi-objective collaborative optimization of the key parameters of the vortex suppression structure. The vortex suppression effect under transient conditions is verified using dynamic grid technology.

2. The method for swirl suppression structure of a servo valve flow channel based on CFD simulation according to claim 1, characterized in that: The multiple criteria include Q criterion, λ2 criterion and composite criterion: The Q criterion is calculated by symmetric / antisymmetric decomposition of the velocity gradient tensor (tensors A, B) and the Frobenius norm; The λ2 criterion is based on the symmetric tensor A 2 +B 2 The negative eigenvalue of determines the vortex core area; The composite criterion is defined by the composite tensor T = αB + βA 2 +γ(AB-BA) (weights satisfy α+β+γ=1), and the identification logic is dynamically adjusted in combination with vorticity, curl and Reynolds number.

3. The method for swirl suppression structure of a servo valve flow passage based on CFD simulation according to claim 1, characterized in that: The inclination angle of the guide plate is adaptively adjusted with Re (small inclination angle in laminar flow area, large inclination angle in turbulent flow area); The curvature radius is related to Re through an error function to match the vortex scale; The rectifier structure is based on the Darcy-Forchheimer equation and a porosity gradient distribution is designed to gradually dissipate eddy energy.

4. The method for swirl suppression structure of a servo valve flow passage based on CFD simulation according to claim 1, characterized in that: Combining response surface method and genetic algorithm, the pressure drop ΔP(x), flow coefficient C v (x) and flow uniformity σ(x) are multi-objectives, and the optimal geometric parameter combination is automatically searched.

5. The method for swirl suppression structure of a servo valve flow passage based on CFD simulation according to claim 1, characterized in that: The area with the densest vorticity in the vortex is the vortex core. The determination of the vortex core area must meet the following requirements: Among them, C Q ∈[0.15,0.35]; ∈ λ ＝0.1·‖A‖； κ∈[0.01,0.1]; Q thresh is the Q criterion threshold, used to filter out strong rotation areas; Turbulent kinetic energy is a physical quantity that describes the energy of turbulent motion. λ2(T) is the second eigenvalue of the tensor T; ‖‖ represents the Frobenius norm; W is the vorticity; is the curl of the velocity field.

6. The method for swirl suppression structure of a servo valve flow passage based on CFD simulation according to claim 5, characterized in that: Turbulent kinetic energy reflects the kinetic energy of random pulsation of fluid particles and is directly related to the variance of velocity components u′, v′, and w′. The calculation formula is:

7. The method for swirl suppression structure of a servo valve flow passage based on CFD simulation according to claim 5, characterized in that: The vortex core boundary is determined by the second-order derivative extreme point + Neumann boundary condition: Core position: Solve H(-λ2) is the Heaviside step function, which takes the value of 1 when its parameter -λ2 is greater than 0, and 0 otherwise; Boundary conditions: represents the partial derivative along the normal direction; Indicates the boundary of the computational region.

8. The method for swirl suppression structure of a servo valve flow passage based on CFD simulation according to claim 2, characterized in that: The weight values ​​of the composite criterion are α=0.6, β=0.3, γ=0.1, and the fluid rotation characteristics are constrained by the second eigenvalue λ2(T) of the composite tensor T.

9. The method for swirl suppression structure of a servo valve flow passage based on CFD simulation according to claim 2, characterized in that: The multi-objective collaborative optimization method constructs a parameter correlation matrix by quantifying the influence weights of different geometric parameter combinations on pressure drop, flow coefficient and flow uniformity.

10. A system of swirl suppression structure of servo valve flow channel based on CFD simulation, characterized by: include: Flow field modeling module: used to build a fluid simulation model of the servo valve flow channel; Vortex identification module: uses a multi-criteria fusion algorithm (Q criterion, λ2 criterion, composite criterion) to locate and quantify the vortex characteristics in the flow channel; Structural design module: Based on vortex characteristics and Reynolds number changes, parametric design of guide vane inclination angle, curvature radius and porosity gradient rectification structure; Optimization module: Response surface methodology and genetic algorithm are used to perform multi-objective optimization of vortex suppression structure parameters; Dynamic verification module: simulates the eddy current suppression effect under transient conditions through dynamic mesh technology.

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