Calculation method, device, equipment and medium for particle wall turbulent boundary layer friction

Abstract

The present application discloses a particle wall turbulent boundary layer friction calculation method, device, equipment and medium, which relates to the field of aircraft technology, including: obtaining direct numerical simulation data of particle two-phase wall turbulence; determining each sub-effect corresponding to the friction decomposition according to the direct numerical simulation data of particle two-phase wall turbulence; wherein each sub-effect corresponding to the friction decomposition includes the average vorticity near the rigid wall, the integral of the helicity tensor along the normal line of the boundary layer wall, and the integral of the particle feedback force along the curl of the boundary layer; performing MPI reduction operation and summing each sub-effect corresponding to the friction decomposition to obtain the rigid wall statistical ensemble average vortex vector component, and using the rigid wall statistical ensemble average vortex vector component and the ensemble average wall friction vector and vortex vector relationship to obtain the friction of the particle wall turbulent boundary layer. Through the above scheme, the accuracy of obtaining the particle wall turbulent boundary layer friction is improved.

Description

Technical Field

[0001] The present invention relates to the field of aircraft technology, and in particular to a particle wall turbulent boundary layer friction calculation method, device, equipment and medium. Background Art

[0002] It is urgent to develop fluid industry software independently. The research on basic research problems such as flat plate boundary layer and channel flow boundary layer is related to the optimal design of complex-shaped industrial equipment. Complex-shaped industrial equipment, such as aircraft engine turbines, is a two-phase flow problem containing particles, which contains complex vortex structures. In view of this, the development of a friction-vortex decomposition solver for particle boundary layers is crucial for understanding the relationship between friction and vortex in basic research problems such as flat plate boundary layers and channel flow boundary layers. The friction of the particle two-phase flow boundary layer is affected by two factors: one is that the particles feedback the fluid, causing disturbances to the fluid, which affects the generation of boundary layer friction; the other is the evolution and development of the vortex system attached to the boundary layer, which affects the dynamic process of the turbulent boundary layer. The turbulent dynamic process is closely related to the generation of boundary layer friction.

[0003] The traditional friction decomposition method obtains the information of each component of friction by solving the integral equation of the Navier-Stokes equation. The NS equation gives the velocity vector information of the flow field, but cannot directly give the vortex vector information. Therefore, the traditional friction decomposition method cannot reflect the evolution process of the boundary layer vortex system, and thus cannot obtain accurate particle wall turbulent boundary layer friction.

[0004] In summary, how to improve the accuracy of obtaining particle wall turbulent boundary layer friction is a problem to be solved in this field. Summary of the invention

[0005] In view of this, the purpose of the present invention is to provide a particle wall turbulent boundary layer friction calculation method, device, equipment and medium to improve the accuracy of obtaining particle wall turbulent boundary layer friction. The specific scheme is as follows:

[0006] In a first aspect, the present application discloses a method for calculating particle wall turbulent boundary layer friction resistance, comprising:

[0007] Obtain direct numerical simulation data of particle two-phase wall turbulence;

[0008] Determine the sub-effects corresponding to the friction decomposition according to the direct numerical simulation data of the particle two-phase wall turbulence; wherein the sub-effects corresponding to the friction decomposition include the average vorticity near the rigid wall, the integral of the helicity tensor along the normal line of the boundary layer wall, and the integral of the particle feedback force along the boundary layer curl;

[0009] The sub-effects corresponding to the friction decomposition are summed up by MPI reduction operation to obtain the rigid wall statistical ensemble average vortex vector component, and the rigid wall statistical ensemble average vortex vector component and the relationship between the ensemble average wall friction vector and the vortex vector are used to obtain the friction of the particle wall turbulent boundary layer.

[0010] Optionally, the direct numerical simulation data of the particle two-phase wall turbulence includes pressure, average fluid velocity, boundary layer thickness, kinematic viscosity coefficient, wall vortex vector component and feedback force of particle microclusters on the fluid.

[0011] Optionally, the determining of each sub-effect corresponding to the friction decomposition according to the direct numerical simulation data of the particle two-phase wall turbulence includes:

[0012] Calculating an average vorticity within a preset range near the rigid wall according to the average velocity of the fluid;

[0013] Obtaining Reynolds stress in different directions, and calculating the integral of the helicity tensor along the normal line of the boundary layer wall according to the Reynolds stress, the boundary layer thickness, the kinematic viscosity coefficient, the wall vortex vector component, and the average velocity of the fluid;

[0014] The feedback force of the particle micelle on the fluid is obtained, and the rotation integral of the particle feedback force along the boundary layer is calculated according to the boundary layer thickness and the feedback force of the particle micelle on the fluid.

[0015] Optionally, performing an MPI reduction operation and summing up the sub-effects corresponding to the friction decomposition includes:

[0016] The MPI reduction operation is performed to sum up the sub-effects corresponding to the friction decomposition using the rigid wall statistical ensemble average vortex vector component expression; wherein the rigid wall statistical ensemble average vortex vector component expression is:

[0017] ;

[0018] in, , , are the ensemble average vortex vector components of the rigid wall in different directions, , , are the average vorticity near the rigid wall in different directions, , are the integrals of the helicity tensor in different directions along the normal line of the boundary layer wall, , , are the integrals of the particle feedback forces along the boundary layer in different directions, i, j, k are 1, 2, 3, and represent three different directions, P is the pressure, is the kinematic viscosity coefficient, , , are the statistical ensemble average vortex vector components in different directions, , , are the average fluid velocities in different directions, , , , are the Reynolds stresses in different directions, is the substitution symbol, is the feedback force of the particle cluster on the fluid, x is the displacement variable, is the first grid away from the wall, is the boundary layer thickness, For the wall.

[0019] Optionally, the process of obtaining the expression of the component of the vortex vector averaged by the rigid wall statistical ensemble includes:

[0020] Constructing an initial particle two-phase flow vortex dynamics conservation equation according to an incompressible particle flow control equation and a vortex vector expression, and transforming the initial particle two-phase flow vortex dynamics conservation equation into a non-conservative form of the vortex dynamics equation;

[0021] Removing redundant terms and unsteady terms in the non-conservative form of the eddy dynamics equation to obtain the eddy dynamics conservation equation of the target particle two-phase flow;

[0022] Integrating the viscous dissipation term in the eddy dynamics conservation equation of the target particle two-phase flow to obtain an integral expression of the viscous dissipation term of the boundary layer, and transforming the integral expression of the viscous dissipation term of the boundary layer to obtain an integral expression of the viscous dissipation term;

[0023] Based on the integral expression of the viscous dissipation term, the relationship between the rigid wall vortex vector and the grid vortex vector is converted to obtain the rigid wall vortex vector expression, and based on the Reynolds average operation formula, the rigid wall vortex vector expression is converted to obtain the rigid wall statistical ensemble average vortex vector component expression.

[0024] Optionally, the process of obtaining the relationship between the ensemble average wall friction vector and the vortex vector includes:

[0025] The wall shear stress vector definition formula is transformed based on the vortex vector definition formula to obtain the wall shear stress vector determinant, and the wall shear stress vector determinant is converted into a wall shear stress vector component expression based on the wall shear stress vector component formula;

[0026] The wall shear stress vector component expression is transformed to obtain the relationship between the ensemble average wall friction vector and the vortex vector.

[0027] Optionally, the relationship between the ensemble average wall friction vector and the vortex vector is:

[0028] ;

[0029] ;

[0030] in, is the friction vector of the ensemble average particle wall turbulent boundary layer, , They are The friction vector of the ensemble average particle wall turbulent boundary layer in the direction, represents the dynamic viscosity coefficient, represents the fluid density, T is the transpose, , , are the statistical ensemble average vortex vector components of the rigid wall in different directions.

[0031] In a second aspect, the present application discloses a particle wall turbulent boundary layer friction calculation device, comprising:

[0032] A data acquisition module, used to obtain direct numerical simulation data of particle two-phase wall turbulence;

[0033] A friction decomposition module is used to determine each sub-effect corresponding to the friction decomposition according to the direct numerical simulation data of the particle two-phase wall turbulence; wherein each sub-effect corresponding to the friction decomposition includes the average vorticity near the rigid wall, the integral of the helicity tensor along the normal line of the boundary layer wall, and the integral of the particle feedback force along the curl of the boundary layer;

[0034] The friction acquisition module is used to perform MPI reduction operations and sum up the sub-effects corresponding to the friction decomposition to obtain the statistical ensemble average vortex vector component of the rigid wall, and use the statistical ensemble average vortex vector component of the rigid wall and the relationship between the ensemble average wall friction vector and the vortex vector to obtain the friction of the particle wall turbulent boundary layer.

[0035] In a third aspect, the present application discloses an electronic device, comprising:

[0036] Memory, used to store computer programs;

[0037] The processor is used to execute the computer program to implement the steps of the particle wall turbulent boundary layer friction calculation method disclosed above.

[0038] In a fourth aspect, the present application discloses a computer-readable storage medium for storing a computer program; wherein, when the computer program is executed by a processor, the steps of the particle wall turbulent boundary layer friction calculation method disclosed above are implemented.

[0039] The beneficial effects of the present application are as follows: the present application determines the various sub-effects corresponding to the friction decomposition based on the direct numerical simulation data of particle two-phase wall turbulence, that is, determines the average vorticity near the rigid wall, the integral of the helicity tensor along the normal of the boundary layer wall, and the integral of the particle feedback force along the curl of the boundary layer, and performs MPI reduction operation and sums the average vorticity near the rigid wall, the integral of the helicity tensor along the normal of the boundary layer wall, and the integral of the particle feedback force along the curl of the boundary layer to obtain the rigid wall statistical ensemble average vortex vector component, and then uses the rigid wall statistical ensemble average vortex vector component and the ensemble average wall friction vector and vortex vector relationship to obtain the friction of the particle wall turbulent boundary layer. Because the existence of the vortex vector will cause the fluid micro-clusters to produce rotational motion near the wall to increase the wall friction between the fluid and the wall, the present application combines the average vorticity near the rigid wall and the rigid wall statistical ensemble average vortex vector component to obtain the friction of the particle wall turbulent boundary layer, and more comprehensively considers the friction generation factors, thereby improving the accuracy of obtaining the friction of the particle wall turbulent boundary layer. BRIEF DESCRIPTION OF THE DRAWINGS

[0040] In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on the provided drawings without paying creative work.

[0041] Figure 1 A flow chart of a particle wall turbulent boundary layer friction calculation method disclosed in the present application;

[0042] Figure 2 A specific control body zoom schematic diagram disclosed in this application;

[0043] Figure 3 A schematic diagram of a specific wall shear stress vector disclosed in this application;

[0044] Figure 4 A schematic diagram of a specific particle wall turbulent boundary layer friction decomposition disclosed in the present application;

[0045] Figure 5 This is a schematic diagram of the structure of a particle wall turbulent boundary layer friction calculation device disclosed in this application;

[0046] Figure 6 This is a structural diagram of an electronic device disclosed in this application. DETAILED DESCRIPTION

[0047] The following will be combined with the drawings in the embodiments of the present application to clearly and completely describe the technical solutions in the embodiments of the present application. 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 creative work are within the scope of protection of the present invention.

[0048] It is urgent to develop fluid industry software independently. The research on basic research problems such as flat plate boundary layer and channel flow boundary layer is related to the optimal design of complex-shaped industrial equipment. Complex-shaped industrial equipment, such as aircraft engine turbines, is a two-phase flow problem containing particles, which contains complex vortex structures. In view of this, the development of a friction-vortex decomposition solver for particle boundary layers is crucial for understanding the relationship between friction and vortex in basic research problems such as flat plate boundary layers and channel flow boundary layers. The friction of the particle two-phase flow boundary layer is affected by two factors: one is that the particles feedback the fluid, causing disturbances to the fluid, which affects the generation of boundary layer friction; the other is the evolution and development of the vortex system attached to the boundary layer, which affects the dynamic process of the turbulent boundary layer. The turbulent dynamic process is closely related to the generation of boundary layer friction.

[0049] The traditional friction decomposition method obtains the information of each component of friction by solving the integral equation of the Navier-Stokes equation. The NS equation gives the velocity vector information of the flow field, but cannot directly give the vortex vector information. Therefore, the traditional friction decomposition method cannot reflect the evolution process of the boundary layer vortex system, and thus cannot obtain accurate particle wall turbulent boundary layer friction.

[0050] To this end, the present application provides a particle wall turbulent boundary layer friction calculation scheme to improve the accuracy of obtaining the particle wall turbulent boundary layer friction.

[0051] See also Figure 1 As shown, the embodiment of the present application discloses a method for calculating the friction resistance of a particle wall turbulent boundary layer, including:

[0052] Step S11: Obtaining direct numerical simulation data of particle two-phase wall turbulence.

[0053] In this embodiment, the particle two-phase wall turbulence direct numerical simulation data includes pressure, average fluid velocity, boundary layer thickness, kinematic viscosity coefficient, wall vortex vector component and particle micro-group feedback force on the fluid. For example, the particle two-phase wall turbulence solver is used to generate the particle two-phase wall turbulence direct numerical simulation data, which specifically includes pressure P, average fluid velocity, boundary layer thickness, kinematic viscosity coefficient, wall vortex vector component and particle micro-group feedback force on the fluid. , kinematic viscosity coefficient , wall vortex vector component and particle micro-cluster feedback force on the fluid .

[0054] Step S12: determining the various sub-effects corresponding to the friction decomposition according to the direct numerical simulation data of the particle two-phase wall turbulence; wherein the various sub-effects corresponding to the friction decomposition include the average vorticity near the rigid wall, the integral of the helicity tensor along the normal of the boundary layer wall, and the integral of the particle feedback force along the curl of the boundary layer.

[0055] In this embodiment, the determination of each sub-effect corresponding to the friction decomposition based on the direct numerical simulation data of the particle two-phase wall turbulence includes: calculating the average vorticity within a preset range near the rigid wall according to the average velocity of the fluid; obtaining the Reynolds stress in different directions, and calculating the integral of the helicity tensor along the normal line of the boundary layer wall according to the Reynolds stress, the boundary layer thickness, the kinematic viscosity coefficient, the wall vortex vector component, and the average velocity of the fluid; obtaining the feedback force of the particle micro-cluster on the fluid, and calculating the integral of the particle feedback force along the boundary layer curl according to the boundary layer thickness and the feedback force of the particle micro-cluster on the fluid. The specific process is as follows:

[0056] 1) Calculate the average vorticity within a preset range near the rigid wall based on the average fluid velocity, that is, the first grid from the wall 1) Obtain the vortex vector components on the surface; 2) Obtain the Reynolds stress in different directions , , , , and according to the Reynolds stress, boundary layer thickness , kinematic viscosity coefficient , statistical ensemble average vortex vector component , , , average fluid velocity , , Calculate the integral of the helicity tensor along the normal of the boundary layer wall , ; 3) Boundary layer thickness , the feedback force of particle clusters on fluid Calculate the particle feedback force along the boundary layer curl integral , , .

[0057] Step S13: Perform MPI reduction operations on the sub-effects corresponding to the friction decomposition and sum them up to obtain the statistical ensemble average vortex vector component of the rigid wall, and use the statistical ensemble average vortex vector component of the rigid wall and the relationship between the ensemble average wall friction vector and the vortex vector to obtain the friction of the particle wall turbulent boundary layer.

[0058] In this embodiment, the summing up of the sub-effects corresponding to the friction decomposition by performing an MPI reduction operation includes: summing up the sub-effects corresponding to the friction decomposition by performing an MPI reduction operation using an expression of an average vortex vector component of a rigid wall statistical ensemble; wherein the expression of an average vortex vector component of a rigid wall statistical ensemble is:

[0059] ;

[0060] in, , , are the ensemble average vortex vector components of the rigid wall in different directions, , , are the average vorticity near the rigid wall in different directions, , are the integrals of the helicity tensor in different directions along the normal line of the boundary layer wall, , , are the integrals of the particle feedback forces along the boundary layer in different directions, i, j, k are 1, 2, 3, and represent three different directions, P is the pressure, is the kinematic viscosity coefficient, , , are the statistical ensemble average vortex vector components in different directions, , , are the average fluid velocities in different directions, , , , are the Reynolds stress, is the substitution symbol, is the feedback force of the particle cluster on the fluid, x is the displacement variable, is the first grid away from the wall, is the boundary layer thickness, For the wall.

[0061] In this embodiment, the process of obtaining the expression of the average vortex vector component of the rigid wall statistical ensemble includes: constructing the initial particle two-phase flow vortex dynamics conservation equation according to the incompressible particle flow control equation and the vortex vector expression, and transforming the initial particle two-phase flow vortex dynamics conservation equation into the non-conservation form of the vortex dynamics equation; removing the redundant terms and unsteady terms in the non-conservation form of the vortex dynamics equation to obtain the target particle two-phase flow vortex dynamics conservation equation; integrating the viscous dissipation term in the target particle two-phase flow vortex dynamics conservation equation to obtain the boundary layer viscous dissipation term integral expression, and converting the boundary layer viscous dissipation term integral expression to obtain the viscous dissipation term integral expression; based on the viscous dissipation term integral expression, converting the relationship between the rigid wall vortex vector and the grid vortex vector to obtain the rigid wall vortex vector expression, and converting the rigid wall vortex vector expression based on the Reynolds average operation formula to obtain the rigid wall statistical ensemble average vortex vector component expression. Among them, the process of obtaining the rigid wall statistical ensemble average vortex vector component expression is specifically as follows:

[0062] 1) According to the incompressible particle flow control equation and the vortex vector expression, the initial particle two-phase flow vortex dynamics conservation equation is constructed, and the initial particle two-phase flow vortex dynamics conservation equation is transformed into the non-conservative form of the vortex dynamics equation; among which, the incompressible particle flow control equation is specifically:

[0063] ;

[0064] ;

[0065] In the formula, represents the fluid density, , represents the displacement variable, i, j, k are 1, 2, 3, and represent three different directions, t represents time, , represents the velocity vector of fluid particles in different directions, represents the feedback force of the particle cluster on the fluid i direction, P represents the fluid pressure, is the kinematic viscosity coefficient;

[0066] The expression of vortex vector is as follows:

[0067] ;

[0068] In the formula, represents the component of the vortex vector in the i direction, represents the substitution symbol, represents the velocity vector of the fluid cluster in the k direction, represents the displacement variable;

[0069] The conservation equation of eddy dynamics of initial particle two-phase flow is as follows:

[0070] ;

[0071] In the formula, , represents the component of the vortex vector in the i and j directions, represents the displacement variable, t represents the time, , represents the velocity vector of fluid particles in different directions, is the kinematic viscosity coefficient, represents the substitution symbol, is the feedback force of particle cluster on the fluid in k direction;

[0072] Furthermore, before converting to a non-conservative form, the initial particle two-phase flow eddy dynamics conservation equation can be converted to the following form:

[0073] ;

[0074] In the formula, represents the divergence of the velocity vector, represents the divergence of the vortex vector field, t represents time, is the feedback force of the particle cluster on the fluid in the k direction, , represents the displacement variable, is the kinematic viscosity coefficient, , , represents the velocity vector of fluid particles in different directions, , represents the component of the vortex vector in the i and j directions, Represents a substitution symbol;

[0075] According to the vortex dynamics theory, for incompressible flow, , It is small enough to be ignored, so the non-conservative form of the vortex dynamics equation is derived. The non-conservative form of the vortex dynamics equation is as follows:

[0076] ;

[0077] In the formula, , represents the component of the vortex vector in the i and j directions, , represents the velocity vector of fluid particles in different directions, represents the displacement variable, t represents the time, is the feedback force of the particle cluster on the fluid in the k direction, represents the substitution symbol, is the kinematic viscosity coefficient.

[0078] 2) Remove the redundant terms in the non-conservative form of the eddy dynamics equation and take a small control volume in the boundary layer of the granular two-phase flow, such as Figure 2 A specific control volume scaling diagram is shown, assuming that in the control volume middle, and Viscous dissipation of vorticity in the direction ,and The direction can be ignored, so the following formula can be obtained:

[0079] ;

[0080] Furthermore, we remove the unsteady terms and assume that the flow is periodic, because we are interested in the statistical ensemble average. The stretching term of the vorticity is moved to the left, thereby obtaining the conservation equation of the vortex dynamics of the target particle two-phase flow, which is as follows:

[0081] ;

[0082] In the formula, , , represents the components of the vortex vector in different directions, , represents the displacement variable, , , represents the fluid velocity in different directions, is the feedback force of the particle cluster on the fluid in the k direction, , , represents the substitution symbol, is the kinematic viscosity coefficient.

[0083] 3) For the target particle two-phase flow eddy dynamics conservation equation, the boundary layer is along the wall normal direction The viscous dissipation term is integrated, and the vorticity gradient It is very small in the inviscid region, so the integral expression of the boundary layer viscous dissipation term is obtained as follows:

[0084] ;

[0085] In the formula, , , represents the components of the vortex vector in different directions, , represents the displacement variable, For the wall, , , represents the vortex vector component on the wall, , , Indicates the distance from the first grid to the wall The vortex vector component on is the boundary layer thickness.

[0086] 4) The vortex vector component on the rigid wall and the vortex vector component on the first grid away from the wall and the boundary layer along the wall normal direction The viscous dissipation integral on The relationship is as follows:

[0087] ;

[0088] In the formula, , , represents the vortex vector component on the wall, , , Indicates the distance from the first grid to the wall The vortex vector component on , , Represents the components of the vortex vector in different directions;

[0089] The integral of the viscous dissipation term is , according to the above relationship, the integral expression of the boundary layer viscous dissipation term is transformed to obtain the integral expression of the viscous dissipation term, which is as follows:

[0090] ;

[0091] In the formula, , , represents the components of the vortex vector in different directions, , , represents the fluid velocity in different directions, , represents the displacement variable, is the kinematic viscosity coefficient, is the feedback force of the particle cluster on the fluid in the k direction, , , represents the substitution symbol, is the boundary layer thickness.

[0092] 5) , and based on the integral expression of the viscous dissipation term, the relationship between the rigid wall vortex vector and the grid vortex vector is transformed to obtain the rigid wall vortex vector expression:

[0093] ;

[0094] In the formula, , , represents the components of the vortex vector in different directions, , , represents the fluid velocity in different directions, , represents the displacement variable, is the kinematic viscosity coefficient, is the feedback force of the particle cluster on the fluid in the k direction, , , represents the substitution symbol, is the boundary layer thickness, is the first grid away from the wall.

[0095] 6) The Reynolds average calculation formula is as follows:

[0096] ;

[0097] In the formula, represents any function, express The statistical mean of express The pulsation value;

[0098] To make the formula more concise, let the symbol , , Respectively , , , , , Respectively , , , and then the rigid wall vortex vector expression is transformed based on the Reynolds average operation formula to obtain the rigid wall statistical ensemble average vortex vector component expression.

[0099] In this embodiment, the process of obtaining the relationship between the ensemble average wall friction vector and the vortex vector includes: transforming the wall shear stress vector definition formula based on the vortex vector definition formula to obtain the wall shear stress vector determinant, and transforming the wall shear stress vector determinant into the wall shear stress vector component expression based on the wall shear stress vector component formula; transforming the wall shear stress vector component expression to obtain the relationship between the ensemble average wall friction vector and the vortex vector. The process of obtaining the relationship between the ensemble average wall friction vector and the vortex vector is specifically as follows:

[0100] 1) According to the vortex dynamics theory, the wall shear stress vector definition formula defines the wall shear stress vector , the wall shear stress vector is defined as follows:

[0101] ;

[0102] In the formula, represents the dynamic viscosity coefficient, represents the vortex vector, represents the wall normal vector;

[0103] The definition of vortex vector is as follows:

[0104] ;

[0105] In the formula, are the normal vectors in three directions on the surface of the microelement, , , They represent the vortex vector components on the wall, respectively, and T is the transpose;

[0106] Furthermore, the wall shear stress vector definition is transformed based on the vortex vector definition to obtain the wall shear stress vector determinant, as follows:

[0107] ;

[0108] In the formula, the values ​​of i, j, and k are 1, 2, and 3, representing three different directions. are the normal vectors in three directions on the surface of the microelement, , , denote the vortex vector components on the wall, represents the dynamic viscosity coefficient, represents the wall shear stress vector;

[0109] According to the Einstein tensor form, the actual direction of the wall shear stress vector is opposite to the direction of the cross product, for example Figure 3A specific schematic diagram of the wall shear stress vector is shown in FIG. 1 , in which the Einstein tensor is expressed as follows:

[0110] ;

[0111] In the formula, represents the substitution symbol, represents the dynamic viscosity coefficient, represents the normal vector in the j direction, represents the vortex vector component on the wall, The Einstein tensor form of the wall shear stress vector;

[0112] Based on the wall shear stress vector component formula, the wall shear stress vector determinant is converted into the wall shear stress vector component expression, where the wall shear stress vector component formula is as follows:

[0113] ;

[0114] In the formula, represents the wall shear stress vector, and represents the components of the wall shear stress vector, T is the transpose;

[0115] The expressions of the wall shear stress vector components are as follows:

[0116] ;

[0117] In the formula, are the normal vectors in three directions on the surface of the microelement, , , denote the vortex vector components on the wall, represents the dynamic viscosity coefficient, and represents the component of the wall shear stress vector.

[0118] 2) The expressions of the wall shear stress vector components are transformed to obtain the relationship between the ensemble average wall friction vector and the vortex vector, which can reflect the functional relationship between the ensemble average wall friction vector and the ensemble average vortex vector component at the wall.

[0119] In this embodiment, the relationship between the ensemble average wall friction vector and the vortex vector is:

[0120] ;

[0121] in, is the friction vector of the ensemble average particle wall turbulent boundary layer, , They are The friction vector of the ensemble average particle wall turbulent boundary layer in the direction, represents the dynamic viscosity coefficient, T is the transpose, , , are the statistical ensemble average vortex vector components of the rigid wall in different directions.

[0122] For example Figure 4 The figure shows a specific schematic diagram of friction decomposition of particle-wall turbulent boundary layer. Combining the incompressible particle two-phase flow equation and vortex dynamics theory, the theoretical equation of friction decomposition of point force particle two-phase flow based on vortex dynamics is derived, namely, the expression of the statistical ensemble average vortex vector component of the rigid wall and the relationship between the ensemble average wall friction vector and the vortex vector, which provides a new perspective for friction decomposition. On the other hand, the helicity part also theoretically proves that the generation mechanism of wall turbulence surface friction is a three-dimensional event, which is related to all directions. , , The helicity part is closely related to the vorticity vector component on the surface. According to the expression of the average vortex vector component of the rigid wall statistical ensemble and the relationship between the ensemble average wall friction vector and the vortex vector, it can be determined that the helicity part includes the average scale component and the pulsating scale component. The pulsating scale component is exactly the influence of turbulence on the average friction of the wall. The expression of the helicity part shows that the contribution of turbulence to the surface friction is multi-scale, both on the average scale and the pulsating scale.

[0123] The beneficial effect of the present application is that the present application determines the various sub-effects corresponding to the friction decomposition based on the direct numerical simulation data of particle two-phase wall turbulence, that is, determines the average vorticity near the rigid wall, the integral of the helicity tensor along the normal of the boundary layer wall, and the integral of the particle feedback force along the curl of the boundary layer, and performs MPI reduction operation and sums the average vorticity near the rigid wall, the integral of the helicity tensor along the normal of the boundary layer wall, and the integral of the particle feedback force along the curl of the boundary layer to obtain the rigid wall statistical ensemble average vortex vector component, and then uses the rigid wall statistical ensemble average vortex vector component and the ensemble average wall friction vector and vortex vector relationship to obtain the friction of the particle wall turbulent boundary layer. Because the existence of the vortex vector will cause the fluid micro-clusters to produce rotational motion near the wall to increase the wall friction between the fluid and the wall, the present application combines the average vorticity near the rigid wall and the rigid wall statistical ensemble average vortex vector component to obtain the friction of the particle wall turbulent boundary layer, and more comprehensively considers the friction generation factors, thereby improving the accuracy of obtaining the friction of the particle wall turbulent boundary layer.

[0124] See also Figure 5 As shown, the embodiment of the present application discloses a particle wall turbulent boundary layer friction calculation device, comprising:

[0125] A data acquisition module 11 is used to acquire direct numerical simulation data of particle two-phase wall turbulence;

[0126] The friction decomposition module 12 is used to determine the sub-effects corresponding to the friction decomposition according to the direct numerical simulation data of the particle two-phase wall turbulence; wherein the sub-effects corresponding to the friction decomposition include the average vorticity near the rigid wall, the integral of the helicity tensor along the normal line of the boundary layer wall, and the integral of the particle feedback force along the boundary layer curl;

[0127] The friction acquisition module 13 is used to perform MPI reduction operations and sum up the sub-effects corresponding to the friction decomposition to obtain the statistical ensemble average vortex vector component of the rigid wall, and use the statistical ensemble average vortex vector component of the rigid wall and the relationship between the ensemble average wall friction vector and the vortex vector to obtain the friction of the particle wall turbulent boundary layer.

[0128] The beneficial effects of the present application are as follows: the present application determines the various sub-effects corresponding to the friction decomposition based on the direct numerical simulation data of particle two-phase wall turbulence, that is, determines the average vorticity near the rigid wall, the integral of the helicity tensor along the normal of the boundary layer wall, and the integral of the particle feedback force along the curl of the boundary layer, and performs MPI reduction operation and sums the average vorticity near the rigid wall, the integral of the helicity tensor along the normal of the boundary layer wall, and the integral of the particle feedback force along the curl of the boundary layer to obtain the rigid wall statistical ensemble average vortex vector component, and then uses the rigid wall statistical ensemble average vortex vector component and the ensemble average wall friction vector and vortex vector relationship to obtain the friction of the particle wall turbulent boundary layer. Because the existence of the vortex vector will cause the fluid micro-clusters to produce rotational motion near the wall to increase the wall friction between the fluid and the wall, the present application combines the average vorticity near the rigid wall and the rigid wall statistical ensemble average vortex vector component to obtain the friction of the particle wall turbulent boundary layer, and more comprehensively considers the friction generation factors, thereby improving the accuracy of obtaining the friction of the particle wall turbulent boundary layer.

[0129] Furthermore, an embodiment of the present application also provides an electronic device. Figure 6 This is a structural diagram of an electronic device 20 according to an exemplary embodiment. The content in the diagram cannot be considered as any limitation on the scope of use of the present application.

[0130] Figure 6 A schematic diagram of the structure of an electronic device provided in an embodiment of the present application. Specifically, it may include: at least one processor 21, at least one memory 22, a power supply 23, a communication interface 24, an input / output interface 25, and a communication bus 26. The memory 22 is used to store a computer program, which is loaded and executed by the processor 21 to implement the relevant steps in the particle wall turbulent boundary layer friction calculation method performed by the electronic device disclosed in any of the aforementioned embodiments.

[0131] In this embodiment, the power supply 23 is used to provide working voltage for each hardware device on the electronic device; the communication interface 24 can create a data transmission channel between the electronic device and the external device, and the communication protocol it follows is any communication protocol that can be applied to the technical solution of the present application, and is not specifically limited here; the input and output interface 25 is used to obtain external input data or output data to the outside world, and its specific interface type can be selected according to specific application needs and is not specifically limited here.

[0132] Among them, the processor 21 may include one or more processing cores, such as a 4-core processor, an 8-core processor, etc. The processor 21 can be implemented in at least one hardware form of DSP (Digital Signal Processing), FPGA (Field-Programmable Gate Array), and PLA (Programmable Logic Array). The processor 21 may also include a main processor and a coprocessor. The main processor is a processor for processing data in the awake state, also known as a CPU (Central Processing Unit); the coprocessor is a low-power processor for processing data in the standby state. In some embodiments, the processor 21 may be integrated with a GPU (Graphics Processing Unit), which is responsible for rendering and drawing the content to be displayed on the display screen. In some embodiments, the processor 21 may also include an AI (Artificial Intelligence) processor, which is used to process computing operations related to machine learning.

[0133] In addition, the memory 22, as a carrier for storing resources, can be a read-only memory, a random access memory, a disk or an optical disk, etc. The resources stored thereon include an operating system 221, a computer program 222 and data 223, etc. The storage method can be temporary storage or permanent storage.

[0134] Among them, the operating system 221 is used to manage and control the hardware devices and computer programs 222 on the electronic device to realize the operation and processing of the massive data 223 in the memory 22 by the processor 21, which can be Windows, Unix, Linux, etc. In addition to including a computer program that can be used to complete the particle wall turbulent boundary layer friction calculation method performed by the electronic device disclosed in any of the aforementioned embodiments, the computer program 222 can also further include a computer program that can be used to complete other specific tasks. In addition to data transmitted from an external device received by the electronic device, the data 223 can also include data collected by its own input and output interface 25.

[0135] Furthermore, the present application also discloses a computer-readable storage medium for storing a computer program; wherein, when the computer program is executed by a processor, the above-disclosed particle wall turbulent boundary layer friction calculation method is implemented. The specific steps of the method can refer to the corresponding contents disclosed in the above-disclosed embodiments, and will not be repeated here.

[0136] In this specification, each embodiment is described in a progressive manner, and each embodiment focuses on the differences from other embodiments. The same or similar parts between the embodiments can be referred to each other. For the device disclosed in the embodiment, since it corresponds to the method disclosed in the embodiment, the description is relatively simple, and the relevant parts can be referred to the method part.

[0137] Professionals may further appreciate that the units and algorithm steps of each example described in conjunction with the embodiments disclosed herein can be implemented with electronic hardware, computer software, or a combination of the two. In order to clearly illustrate the interchangeability of hardware and software, the composition and steps of each example have been generally described in terms of function in the above description. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. Professional and technical personnel may use different methods to implement the described functions for each specific application, but such implementation should not be considered to be beyond the scope of this application. The steps of the method or algorithm described in conjunction with the embodiments disclosed herein can be implemented directly with hardware, a software module executed by a processor, or a combination of the two. The software module can be placed in a random access memory (RAM), memory, read-only memory (ROM), electrically programmable EPROM (Erasable Programmable Read Only Memory), electrically erasable programmable EEPROM (Electrically Erasable Programmable read only memory), register, hard disk, removable disk, CD-ROM (Compact Disc Read-Only Memory), or any other form of storage medium known in the technical field.

[0138] Finally, it should be noted that, in this article, relational terms such as first and second, etc. are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Moreover, the terms "include", "comprise" or any other variants 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. In the absence of further restrictions, the elements defined by the sentence "comprise a ..." do not exclude the presence of other identical elements in the process, method, article or device including the elements.

[0139] The above is a detailed introduction to the particle wall turbulent boundary layer friction calculation method, device, equipment and medium provided by the present invention. Specific examples are used in this article to illustrate the principles and implementation methods of the present invention. The description of the above embodiments is only used to help understand the method of the present invention and its core idea; at the same time, for general technical personnel in this field, according to the idea of ​​the present invention, there will be changes in the specific implementation method and application scope. In summary, the content of this specification should not be understood as a limitation on the present invention.

Claims

1. A particle wall turbulent boundary layer friction calculation method, characterized in that: include: Acquire direct numerical simulation data of particle two-phase wall turbulence; wherein the direct numerical simulation data of particle two-phase wall turbulence includes pressure, average velocity of fluid, thickness of boundary layer, kinematic viscosity coefficient, wall vortex vector component and feedback force of particle micro-clusters on fluid; Determine the sub-effects corresponding to the friction decomposition according to the direct numerical simulation data of the particle two-phase wall turbulence; wherein the sub-effects corresponding to the friction decomposition include the average vorticity near the rigid wall, the integral of the helicity tensor along the normal line of the boundary layer wall, and the integral of the particle feedback force along the boundary layer curl; Performing MPI reduction operations on the sub-effects corresponding to the friction decomposition and summing them up to obtain a rigid wall statistical ensemble average vortex vector component, and using the rigid wall statistical ensemble average vortex vector component and a relationship between the ensemble average wall friction vector and the vortex vector to obtain the friction of the particle wall turbulent boundary layer; The determining of each sub-effect corresponding to the friction decomposition according to the direct numerical simulation data of the particle two-phase wall turbulence comprises: Calculate the average vorticity within a preset range near the rigid wall according to the average velocity of the fluid; obtain the Reynolds stress in different directions, and calculate the integral of the helicity tensor along the normal line of the boundary layer wall according to the Reynolds stress, the boundary layer thickness, the kinematic viscosity coefficient, the wall vortex vector component, and the average velocity of the fluid; obtain the feedback force of the particle micro-cluster on the fluid, and calculate the curl integral of the particle feedback force along the boundary layer according to the boundary layer thickness and the feedback force of the particle micro-cluster on the fluid; The summing up of the sub-effects corresponding to the friction decomposition by performing MPI reduction operations includes: The MPI reduction operation is performed to sum up the sub-effects corresponding to the friction decomposition using the rigid wall statistical ensemble average vortex vector component expression; wherein the rigid wall statistical ensemble average vortex vector component expression is: ； in, , , are the ensemble average vortex vector components of the rigid wall in different directions, , , are the average vorticity near the rigid wall in different directions, , are the integrals of the helicity tensor in different directions along the normal line of the boundary layer wall, , , are the integrals of the particle feedback forces along the boundary layer in different directions, i, j, k are 1, 2, 3, and represent three different directions, P is the pressure, is the kinematic viscosity coefficient, , , are the statistical ensemble average vortex vector components in different directions, , , are the average fluid velocities in different directions, , , , are the Reynolds stresses in different directions, is the substitution symbol, is the feedback force of the particle cluster on the fluid, x is the displacement variable, is the first grid away from the wall, is the boundary layer thickness, For the wall.

2. The particle wall turbulent boundary layer friction calculation method according to claim 1 is characterized in that: The process of obtaining the expression of the average vortex vector component of the rigid wall statistical ensemble includes: Constructing an initial particle two-phase flow vortex dynamics conservation equation according to an incompressible particle flow control equation and a vortex vector expression, and transforming the initial particle two-phase flow vortex dynamics conservation equation into a non-conservative form of the vortex dynamics equation; Removing redundant terms and unsteady terms in the non-conservative form of the eddy dynamics equation to obtain the eddy dynamics conservation equation of the target particle two-phase flow; Integrating the viscous dissipation term in the eddy dynamics conservation equation of the target particle two-phase flow to obtain an integral expression of the viscous dissipation term of the boundary layer, and transforming the integral expression of the viscous dissipation term of the boundary layer to obtain an integral expression of the viscous dissipation term; Based on the integral expression of the viscous dissipation term, the relationship between the rigid wall vortex vector and the grid vortex vector is converted to obtain the rigid wall vortex vector expression, and based on the Reynolds average operation formula, the rigid wall vortex vector expression is converted to obtain the rigid wall statistical ensemble average vortex vector component expression.

3. The particle wall turbulent boundary layer friction calculation method according to claim 1 is characterized in that: The process of obtaining the relationship between the ensemble average wall friction vector and the vortex vector includes: The wall shear stress vector definition formula is transformed based on the vortex vector definition formula to obtain the wall shear stress vector determinant, and the wall shear stress vector determinant is converted into a wall shear stress vector component expression based on the wall shear stress vector component formula; The wall shear stress vector component expression is transformed to obtain the relationship between the ensemble average wall friction vector and the vortex vector.

4. The particle wall turbulent boundary layer friction calculation method according to claim 3 is characterized in that: The relationship between the ensemble average wall friction vector and the vortex vector is: ； ； in, is the friction vector of the ensemble average particle wall turbulent boundary layer, , They are The friction vector of the ensemble average particle wall turbulent boundary layer in the direction, represents the dynamic viscosity coefficient, represents the fluid density, T is the transpose, , , are the statistical ensemble average vortex vectors of the rigid wall in different directions.

5. A particle wall turbulent boundary layer friction calculation device, characterized in that: include: A data acquisition module is used to acquire direct numerical simulation data of particle two-phase wall turbulence; wherein the direct numerical simulation data of particle two-phase wall turbulence includes pressure, average velocity of fluid, thickness of boundary layer, kinematic viscosity coefficient, wall vortex vector component and feedback force of particle micro-clusters on fluid; A friction decomposition module is used to determine each sub-effect corresponding to the friction decomposition according to the direct numerical simulation data of the particle two-phase wall turbulence; wherein each sub-effect corresponding to the friction decomposition includes the average vorticity near the rigid wall, the integral of the helicity tensor along the normal line of the boundary layer wall, and the integral of the particle feedback force along the curl of the boundary layer; A friction acquisition module is used to perform an MPI reduction operation and sum each sub-effect corresponding to the friction decomposition to obtain a rigid wall statistical ensemble average vortex vector component, and obtain the friction of the particle wall turbulent boundary layer by using the rigid wall statistical ensemble average vortex vector component and the relationship between the ensemble average wall friction vector and the vortex vector; The friction decomposition module is specifically used for: Calculate the average vorticity within a preset range near the rigid wall according to the average velocity of the fluid; obtain the Reynolds stress in different directions, and calculate the integral of the helicity tensor along the normal line of the boundary layer wall according to the Reynolds stress, the boundary layer thickness, the kinematic viscosity coefficient, the wall vortex vector component, and the average velocity of the fluid; obtain the feedback force of the particle micro-cluster on the fluid, and calculate the curl integral of the particle feedback force along the boundary layer according to the boundary layer thickness and the feedback force of the particle micro-cluster on the fluid; The friction resistance acquisition module is specifically used for: The MPI reduction operation is performed to sum up the sub-effects corresponding to the friction decomposition using the rigid wall statistical ensemble average vortex vector component expression; wherein the rigid wall statistical ensemble average vortex vector component expression is: ； in, , , are the ensemble average vortex vector components of the rigid wall in different directions, , , are the average vorticity near the rigid wall in different directions, , are the integrals of the helicity tensor in different directions along the normal line of the boundary layer wall, , , are the integrals of the particle feedback forces along the boundary layer in different directions, i, j, k are 1, 2, 3, and represent three different directions, P is the pressure, is the kinematic viscosity coefficient, , , are the statistical ensemble average vortex vector components in different directions, , , are the average fluid velocities in different directions, , , , are the Reynolds stresses in different directions, is the substitution symbol, is the feedback force of the particle cluster on the fluid, x is the displacement variable, is the first grid away from the wall, is the boundary layer thickness, For the wall.

6. An electronic device, characterized in that: include: Memory, used to store computer programs; A processor is used to execute the computer program to implement the steps of the particle wall turbulent boundary layer friction calculation method as described in any one of claims 1 to 4.

7. A computer-readable storage medium, characterized in that: Used to store computer programs; wherein, when the computer program is executed by a processor, the steps of the particle wall turbulent boundary layer friction calculation method as described in any one of claims 1 to 4 are implemented.

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