Flow separation prediction method based on mechanical energy gradient

Abstract

The invention aims to provide a flow separation prediction method based on a mechanical energy gradient, and belongs to the field of flow separation prediction. Comprising the following steps: inputting a physical field and geometric conditions; selecting a monitoring interval; generating curve equidistant points in the interval based on the monitoring interval; generating corresponding tangent lines and angles based on the equidistant points; according to the obtained tangent line and the corresponding angle, speed conversion of the corresponding monitoring point is completed in combination with an existing physical field, and the speed conversion comprises the tangential speed and the normal speed. According to the method, curve equidistant points can be divided in the monitoring interval, the angle of the corresponding position is obtained to correct the relative speed, and a plurality of corresponding speed molded lines are generated according to the curve equidistant points, so that the relative speed molded lines are compared under the condition that uniform curve intervals are ensured, and the effectiveness and rationality of speed molded line comparison are ensured.

Description

Technical Field

[0001] The present invention relates to a flow separation prediction method, specifically a flow separation prediction method based on mechanical energy gradient. Background Technology

[0002] Flow separation is a common physical phenomenon widely found in aerospace, shipbuilding, and energy fields. Under normal conditions, when a fluid flows around the surface of an object, the combined effect of the reverse pressure gradient and viscous forces causes the fluid velocity within the boundary layer to drop to zero or even reverse, thus causing the mainstream fluid to detach from the object's surface. Furthermore, near the wall where flow separation occurs, the ratio of the flow direction mechanical energy to the normal gradient is often negative due to the occurrence of flow separation.

[0003] When flow separation occurs, this unexpected fluid flow significantly reduces the reliability and economy of fluid machinery. Flow separation increases flow resistance significantly; for example, the pressure drag formed in the separation zone of a cylinder can account for more than 70% of the total drag. Furthermore, flow separation can damage the aerodynamic performance of equipment, such as causing aircraft wing stall and reducing turbine mechanical efficiency. Simultaneously, periodic vortex shedding (such as the Karman vortex street) may induce structural resonance, and turbulent mixing in the separation zone can lead to energy dissipation and noise problems. Therefore, it is irreplaceable to develop a standardized and effective prediction method for flow separation phenomena. Summary of the Invention

[0004] The purpose of this invention is to provide a flow separation prediction method based on mechanical energy gradient that can solve the problem of insufficient accuracy in existing flow separation prediction methods.

[0005] The objective of this invention is achieved as follows: This invention provides a flow separation prediction method based on mechanical energy gradient, characterized by the following steps: (1) Input the actual physical field and geometric conditions of the calculation model; (2) Constructing the monitoring range: Based on the monitoring needs and actual characteristic locations, construct the monitoring range; (3) Selecting equidistant points based on the selected monitoring interval: Within the selected monitoring interval, equidistant points with uniform curve distances are arranged as monitoring points according to the accuracy requirements. (4) Generate the corresponding position angle based on the selected curve equidistant points: Generate the tangent line at the corresponding position based on the selected curve equidistant monitoring points, thereby obtaining the angle of each point's position; (5) Calculate the tangential and normal gradients of mechanical energy based on the data obtained in step (4) and the corresponding velocities and pressures in the original physical field; (6) Based on the mechanical energy gradient theory, determine flow separation; (7) Identify the flow separation area based on the individual judgment results of the monitoring points.

[0006] The present invention may also include: 1. In step (1), a high-precision physical field corresponding to coordinate-physical property parameters is obtained through CFD fluid simulation technology; at the same time, a geometric model matching the CFD calculation is input.

[0007] 2. In step (3), within the already calibrated monitoring range on the surface of the geometric model, different equidistant monitoring points are set according to actual needs and the actual location of features, including... in The length of the monitoring range curve already calibrated on the surface of the geometric model. The density of monitoring points is selected based on requirements and characteristic locations. This represents the number of monitoring points within the monitoring interval.

[0008] 3. In step (4), based on the data sampling points on the surface generated in step (3), the corresponding tangents are generated, and the tangent angle is obtained according to the tangent function. Then, the corresponding sine and cosine values ​​are generated according to the corresponding position angle.

[0009] 4. In step (5), based on the data obtained in step (4), the velocity in the absolute coordinates of the original physical field is transformed using sine and cosine functions according to the angle of the corresponding position. The specific velocity transformation formula is as follows: in , This represents the flow direction and velocity perpendicular to the flow in the original grid data, i.e., in absolute coordinates. , These represent the tangential and normal velocities at the corresponding positions after coordinate transformation. For the angles within the corresponding interval; The formula for calculating mechanical energy is: in, This represents the static pressure at the corresponding location. This represents the fluid density at the corresponding location. This represents the absolute velocity of the fluid at the corresponding location. The corrected formula is: where is the gravitational potential energy of the fluid at the corresponding location. .

[0010] 5. Step (6) specifically involves calculating the K value for each point from step (5), where the formula for the dimensionless parameter K is: in, As mechanical energy, These represent the gradients of mechanical energy in the normal and tangential directions, respectively; a negative K value indicates flow separation, which can be used to determine whether flow separation occurs and where it occurs.

[0011] The advantages of this invention are: 1. By processing the original physical and geometric fields, this invention can obtain the tangential and normal mechanical energy gradients at different locations. This allows for the optimization of the discrimination parameter, i.e., mechanical energy, by combining the physical and geometric fields, making the flow separation prediction and discrimination method more reasonable and the discrimination parameter more accurate. 2. This invention links the mechanical energy gradient with flow separation by calculating the tangential and normal mechanical energy gradients, thereby optimizing the method of flow separation judgment and prediction and avoiding the error caused by judging flow separation through velocity flow field. Attached Figure Description

[0012] Figure 1 This is a flowchart of the present invention; Figure 2 This is a schematic diagram of the present invention. Detailed Implementation

[0013] The invention will now be described in more detail with reference to the accompanying drawings: Combination Figure 1-2 The present invention provides a flow separation prediction method based on mechanical energy gradient, comprising the following steps: (1) Input the actual physical field and geometric conditions of the calculation model; (2) Constructing the monitoring range: Based on the monitoring needs and actual characteristic locations, construct the monitoring range; (3) Selecting equidistant points based on the selected monitoring interval: Within the selected monitoring interval, equidistant points with uniform curve distances are arranged as monitoring points according to the accuracy requirements. (4) Generate the corresponding position angle based on the selected curve equidistant points: Generate the tangent line at the corresponding position based on the selected curve equidistant monitoring points, thereby obtaining the angle of each point's position; (5) Calculate the tangential and normal gradients of mechanical energy based on the data obtained in step (4) and the corresponding velocities and pressures in the original physical field; (6) Based on the mechanical energy gradient theory, determine flow separation; (7) Identify the flow separation area based on the individual discrimination results of the monitoring points; In step (1), a high-precision physical field with a one-to-one correspondence between coordinates and physical property parameters is obtained through traditional CFD fluid simulation technology; at the same time, a geometric model that matches the CFD calculation is input.

[0014] In step (3), a monitoring interval is constructed; based on monitoring requirements and actual feature locations, a monitoring range is constructed: within the already marked monitoring range on the surface of the geometric model, different equidistant monitoring points are set according to actual requirements and actual feature locations, including... in The length of the monitoring range curve already calibrated on the surface of the geometric model. The density of monitoring points is selected based on requirements and characteristic locations. This represents the number of monitoring points within the monitoring interval.

[0015] In step (4), based on the data sampling points on the surface generated in step (3), the corresponding tangents are generated, and the tangent angle is obtained according to the tangent function. Then, the corresponding sine and cosine values ​​are generated according to the corresponding position angle.

[0016] In step (5), based on the data obtained in step (4), the velocity in the absolute coordinates of the original physical field is transformed using sine and cosine functions according to the angle of the corresponding position. The specific velocity transformation formula is as follows: in , This represents the flow direction and velocity perpendicular to the flow in the original grid data, i.e., in absolute coordinates. , These represent the tangential and normal velocities at the corresponding positions after coordinate transformation. For the angles within the corresponding interval; The specific formula for calculating mechanical energy is as follows: in, This represents the static pressure at the corresponding location. This represents the fluid density at the corresponding location. This represents the absolute velocity of the fluid at the corresponding location. This represents the gravitational potential energy of the fluid at the corresponding location. For air, the gravitational potential energy can be considered constant, so this term can be ignored. The corrected formula is: Step (6) specifically involves calculating the K values ​​for each point obtained in step (5): The formula for the dimensionless parameter K is: in, As mechanical energy, These represent the gradients of mechanical energy in the normal and tangential directions, respectively. A negative K value indicates that flow separation has occurred, which allows us to determine and predict whether flow separation has occurred and where it will occur.

[0017] The overall process is as follows: First, input the actual physical field and geometric conditions of the calculation model. Based on actual needs, select the monitoring interval. Based on the selected monitoring interval, select the curve equidistant points, i.e., the data acquisition points. Based on the selected curve equidistant points, generate the tangent lines at the corresponding positions to obtain the corresponding position angles. Based on the obtained position angles and the corresponding velocities and pressures in the original physical field, calculate the mechanical energy tangential and normal gradients. Then, calculate and use the K value to identify the flow separation region, and finally complete the flow separation prediction based on the mechanical energy gradient.

Claims

1. A flow separation prediction method based on mechanical energy gradient, characterized by: Includes the following steps: (1) Input the actual physical field and geometric conditions of the calculation model; (2) Constructing the monitoring range: Based on the monitoring needs and actual characteristic locations, construct the monitoring range; (3) Selecting equidistant points based on the selected monitoring interval: Within the selected monitoring interval, equidistant points with uniform curve distances are arranged as monitoring points according to the accuracy requirements. (4) Generate the corresponding position angle based on the selected curve equidistant points: Generate the tangent line at the corresponding position based on the selected curve equidistant monitoring points, thereby obtaining the angle of each point's position; (5) Calculate the tangential and normal gradients of mechanical energy based on the data obtained in step (4) and the corresponding velocities and pressures in the original physical field; (6) Based on the mechanical energy gradient theory, determine flow separation; (7) Identify the flow separation area based on the individual judgment results of the monitoring points.

2. The flow separation prediction method based on mechanical energy gradient according to claim 1, characterized in that: In step (1), a high-precision physical field corresponding to coordinates and physical property parameters is obtained through CFD fluid simulation technology; at the same time, a geometric model matching the CFD calculation is input.

3. The flow separation prediction method based on mechanical energy gradient according to claim 1, characterized in that: In step (3), within the calibrated monitoring range on the surface of the geometric model, different equidistant monitoring points are set according to actual needs and the actual location of features, including... in The length of the monitoring range curve already calibrated on the surface of the geometric model. The density of monitoring points is selected based on requirements and characteristic locations. This represents the number of monitoring points within the monitoring interval.

4. The flow separation prediction method based on mechanical energy gradient according to claim 1, characterized in that: In step (4), based on the data sampling points on the surface generated in step (3), the corresponding tangents are generated, and the tangent angle is obtained according to the tangent function. Then, the corresponding sine and cosine values ​​are generated according to the corresponding position angle.

5. The flow separation prediction method based on mechanical energy gradient according to claim 1, characterized in that: In step (5), based on the data obtained in step (4), the velocity in the absolute coordinates of the original physical field is transformed using sine and cosine functions according to the angle of the corresponding position. The specific velocity transformation formula is as follows: in , This represents the flow direction and velocity perpendicular to the flow in the original grid data, i.e., in absolute coordinates. , These represent the tangential and normal velocities at the corresponding positions after coordinate transformation. For the angles within the corresponding interval; The formula for calculating mechanical energy is: in, This represents the static pressure at the corresponding location. This represents the fluid density at the corresponding location. This represents the absolute velocity of the fluid at the corresponding location. The corrected formula is: where is the gravitational potential energy of the fluid at the corresponding location. 。 6. The flow separation prediction method based on mechanical energy gradient according to claim 1, characterized in that: Step (6) specifically involves calculating the K value for each point obtained in step (5), where the formula for the dimensionless parameter K is: in, As mechanical energy, These represent the gradients of mechanical energy in the normal and tangential directions, respectively; a negative K value indicates flow separation, which can be used to determine whether flow separation occurs and where it occurs.

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