Hydraulic mechanical system part progressive wear quantitative prediction method based on dynamic grid technology

Abstract

The invention discloses a quantitative prediction method for progressive wear of hydraulic mechanical system components based on a dynamic grid technology. The quantitative prediction method comprises the following steps: constructing a three-dimensional geometric model of fluid machinery; cFD numerical calculation is carried out on the basis of the three-dimensional geometric model of the fluid machine under specified boundary conditions, and an internal steady-state initial field of the fluid machine is obtained; based on the steady-state initial field in the fluid machinery, injecting sediment particles, and introducing a wear model to obtain a transient sand-containing stable flow field; on the basis of the transient sand-containing steady-state flow field, the abrasion depth is calculated according to the wall surface damage rate; calculating the difference value between the wear depth at the current moment and the wear depth at the previous moment, and obtaining the grid deformation at the current time; and according to the grid deformation at the current time, decomposition is carried out in the particle impact speed direction, the effect of changing the wall surface morphology is achieved, and the abrasion depth, the wall surface morphology change and the transient flow field change at the total time are obtained. The prediction precision of the mechanical wear depth of the fluid is improved.

Description

Technical Field

[0001] The invention belongs to the technical field of numerical simulation of hydraulic machinery wear characteristics, and in particular relates to a method for quantitatively predicting progressive wear of hydraulic machinery system components based on dynamic grid technology. Background Art

[0002] Sediment wear refers to the phenomenon or process in which sediment particles carried by the fluid impact the surface of the material at a certain speed or angle and cause material loss. In the hydraulic machinery system, the long-term transportation of sand-containing fluids by the hydropower units and the pipeline system will inevitably cause deformation of the flow wall of the hydraulic system components, peeling of component materials and other problems, thereby affecting the operating efficiency of the hydraulic machinery system. The cumulative effect of sediment wear will lead to material loss on the flow surface. The location where the wear occurs will increase the wall roughness with the material loss, causing drastic changes in the local flow state, further increasing the intensity of wear damage, and in severe cases causing failure and damage of the transportation equipment. Therefore, accurately estimating the law of erosion damage is an issue that urgently needs attention in hydraulic machinery systems that transport sand-containing fluids. Summary of the invention

[0003] In order to solve the above technical problems, the present invention proposes a quantitative prediction method for progressive wear of hydraulic machinery system components based on dynamic grid technology, so as to improve the prediction accuracy and practicality of wear depth of fluid machinery.

[0004] To achieve the above object, the present invention provides a method for quantitatively predicting progressive wear of hydraulic machinery system components based on dynamic grid technology, comprising:

[0005] S1, obtaining the two-dimensional plane three-view drawing of the hydraulic machinery system components, and constructing a fluid machinery three-dimensional geometric model for the hydraulic machinery system components;

[0006] S2. Perform CFD numerical calculations based on the three-dimensional geometric model of the fluid machinery under specified boundary conditions to obtain the initial steady-state field inside the fluid machinery;

[0007] S3, based on the initial steady-state field inside the fluid machinery, inject sediment particles, introduce the wear model, and obtain the transient sand-containing stable flow field;

[0008] S4, judging whether the flow field is full of sediment particles, if not, returning to S3, if full, proceeding to S5;

[0009] S5. Based on the transient sand-laden steady flow field, the wear depth is calculated according to the wall damage rate;

[0010] S6, calculating the difference between the wear depth at the current moment and the wear depth at the previous moment, and obtaining the mesh deformation at the current time;

[0011] S7, judging whether the wear time reaches the set time, if not, returning to S5, if reaching the set time, proceeding to S8;

[0012] S8. According to the mesh deformation at the current time, the particle impact velocity direction is used as the reference for decomposition, and the distance obtained by decomposing several vertices of each unit surface is moved to achieve the effect of wall morphology change, and obtain the wear depth, wall morphology change, and transient flow field change under the total time.

[0013] Optionally, specify boundary conditions including velocity inlet, total pressure outlet, and no-slip wall.

[0014] Optionally, the transient sand-laden stable flow field is characterized by a constant inlet and outlet pressure difference, a regular internal flow field distribution, and a balance between particle injection and particle output.

[0015] Optionally, the wear model adopts the Oka wear model.

[0016] Optionally, calculate the wear depth including:

[0017]

[0018] Where h is the wear depth; E(α) is the wear rate obtained by the Oka wear model; M d is the mass of particles impacting a single grid unit in each time step; c is the ratio of the single-step wear time to the transient calculation time step; A is the area of ​​a single grid unit surface.

[0019] Optionally, based on the mesh deformation at the current time, the decomposition is performed based on the particle impact velocity direction, including:

[0020] Get the particle impact velocity vector of the unit grid surface;

[0021] Normalize the velocity vector and project it onto the three coordinate axes to obtain the components in the three directions;

[0022] The wear depth is multiplied by the components in the three directions respectively and assigned as offset to the three components of the four nodes of the unit mesh surface.

[0023] Optionally, whether the wear time reaches the set time refers to whether the cumulative number of steps per unit wear time step reaches the total number of calculation steps.

[0024] Optionally, CFD numerical calculations are performed using a scale-adaptive simulation model.

[0025] Technical effect of the present invention: The present invention discloses a method for quantitatively predicting the progressive wear of hydraulic machinery system components based on dynamic mesh technology, constructing a three-dimensional geometric model of the fluid domain of the fluid machinery; based on the three-dimensional geometric model, using the wear model to obtain the wear rate of the flow wall; based on the dynamic mesh technology, calculating the wear deformation under different wear durations under transient conditions; finally obtaining the wear depth under different wear times. The present invention can greatly improve the prediction accuracy of the wear depth of fluid machinery, and has strong practicality and generalizability. The present invention not only focuses on the qualitative description of the elbow erosion phenomenon, but also emphasizes the progressive erosion characteristics of the elbow through quantitative analysis, providing technical support for the accurate understanding of the degree of elbow erosion. The research is helpful to formulate effective maintenance strategies and thus extend the service life of the pipeline system. BRIEF DESCRIPTION OF THE DRAWINGS

[0026] The drawings constituting a part of the present application are used to provide a further understanding of the present application. The illustrative embodiments and descriptions of the present application are used to explain the present application and do not constitute an improper limitation on the present application. In the drawings:

[0027] Figure 1 It is a flow chart of a method for quantitatively predicting progressive wear of hydraulic machinery system components based on dynamic grid technology according to an embodiment of the present invention;

[0028] Figure 2 It is a schematic diagram of a geometric model of an embodiment of the present invention;

[0029] Figure 3 A schematic diagram of the grid division of the computational domain according to an embodiment of the present invention;

[0030] Figure 4 This is a schematic diagram comparing the wear depth predicted by the embodiment of the present invention with the experimental value;

[0031] Figure 5 This is a schematic diagram of the change in the morphology of the flow wall surface of the embodiment of the present invention after every 10 hours for 10-50 hours. DETAILED DESCRIPTION

[0032] It should be noted that, in the absence of conflict, the embodiments and features in the embodiments of the present application can be combined with each other. The present application will be described in detail below with reference to the accompanying drawings and in combination with the embodiments.

[0033] It should be noted that the steps shown in the flowcharts of the accompanying drawings can be executed in a computer system such as a set of computer executable instructions, and that, although a logical order is shown in the flowcharts, in some cases, the steps shown or described can be executed in an order different from that shown here.

[0034] like Figure 1As shown, this embodiment provides a method for quantitatively predicting progressive wear of hydraulic machinery system components based on dynamic grid technology, including:

[0035] Step 1: Model the flow channel based on existing data. The geometric model of this embodiment is a 90° elbow. Figure 2 As shown, the geometric dimensions are indicated in the figure.

[0036] Step 2: Perform hexahedral core meshing on the three-dimensional fluid domain model established in step 1 to ensure the simulation accuracy of the mainstream and ensure that the mesh near the flow wall can be deformed and reconstructed. At the same time, the mesh of the elbow is encrypted. Figure 3 shown.

[0037] Step 3: The three-dimensional fluid domain model established in step 1 is subjected to the specified boundary conditions (velocity inlet, V in =45.72m / s; total pressure outlet, P out =0Pa) to carry out CFD numerical simulation calculation to obtain a good steady-state initial flow field.

[0038] Step 4, using the flow field obtained in step 3 as the initial condition, perform transient CFD numerical simulation calculation to obtain a stable transient flow field (the inlet and outlet pressure difference is basically stable).

[0039] Step 5: Based on the stable transient flow field obtained in step 3, add sediment particles (the sediment particle information is as follows: particle size dp = 150 μm, the inlet velocity is kept the same as the boundary condition in step 2, V in =45.72m / s, sediment particle flow rate Q s =2.0810 -4 kg / s), taking into account the erosion and accumulation effect, the added mass force and the pressure gradient force, the stable transient flow field containing sand is finally obtained.

[0040] Step 6: After obtaining the wear rate of the flow wall, calculate the wear depth using the following formula:

[0041]

[0042] Where, h is the wear depth, unit is m; E(α) is the wall wear rate. Taking the Oka model as an example, the unit of E(α) is m3 / kg, which means the volume of the wall lost per unit particle mass; M d Under transient conditions, the unit is kg, which represents the mass of particles impacting the wall at each time; A is the area of ​​the grid unit; c is the time coefficient, which is defined as the ratio of a single-step wear time to the transient time step, and the purpose is to balance the scale difference between the wear time and the transient time step.

[0043] Step 7: Use the following formula to calculate the difference between the wear depth of the current time step and the previous time step:

[0044] Δh=h t -h t-1 ;

[0045] Where Δh is the wear depth at the current moment, in m, h t It represents the total wear depth up to this moment, h t-1 It represents the sum of the wear depth up to the last moment. Δh is taken as the mesh deformation at the current moment.

[0046] Step 8: Decompose the mesh deformation at the current moment based on the velocity vector of the particle impacting the wall, and move the four vertices of each unit surface by the decomposed distance to achieve the effect of changing the wall morphology. The progressive wear characteristics are obtained by step-by-step saving. Figure 4 The comparison between the predicted value of this method and the experimental value is shown, and the agreement with the experimental situation is high, which illustrates the feasibility of this method.

[0047] Step 9, repeat steps 5 to 8, and make a judgment in step 7 to determine whether the wear time reaches the total wear time. If it has reached, then jump out of the calculation to obtain the progressive wear characteristics of the flow wall under the total wear time. If it has not reached, then repeat steps 5 to 8. Figure 5 The figure shows the comparison between the wall morphology of the elbow after 50 hours of wear and the wall morphology before wear. The blue arrow indicates the flow direction. The left picture shows the change in geometric shape after 10 hours of wear, and the right picture is a partial enlargement of the change in the middle of the outer morphology of the elbow after every 10 hours of wear.

[0048] The present invention discloses a quantitative prediction method for progressive wear of hydraulic machinery system components based on dynamic grid technology, constructing a three-dimensional geometric model of the fluid domain of the fluid machinery; based on the three-dimensional geometric model, using the wear model to obtain the wear rate of the flow wall; based on the dynamic grid technology, calculating the wear deformation under different wear durations under transient conditions; finally obtaining the wear depth under different wear times. The present invention can greatly improve the prediction accuracy of the wear depth of fluid machinery, and has strong practicality and generalizability. The present invention not only focuses on the qualitative description of the elbow erosion phenomenon, but also emphasizes the progressive erosion characteristics of the elbow through quantitative analysis, providing technical support for the accurate cognition of the elbow erosion degree. The research is helpful to formulate effective maintenance strategies and thus extend the service life of the pipeline system.

[0049] The above are only preferred specific implementations of the present application, but the protection scope of the present application is not limited thereto. Any changes or substitutions that can be easily thought of by a person skilled in the art within the technical scope disclosed in the present application should be included in the protection scope of the present application. Therefore, the protection scope of the present application should be based on the protection scope of the claims.

Claims

1. A quantitative prediction method for progressive wear of hydraulic machinery system components based on dynamic grid technology, characterized in that: include: S1. Construct a three-dimensional geometric model of fluid machinery; S2. Perform CFD numerical calculations based on the three-dimensional geometric model of the fluid machinery under specified boundary conditions to obtain the initial steady-state field inside the fluid machinery; S3, based on the initial steady-state field inside the fluid machinery, inject sediment particles, introduce the wear model, and obtain the transient sand-containing stable flow field; S4, judging whether the flow field is full of sediment particles, if not, returning to S3, if full, proceeding to S5; S5. Based on the transient sand-laden steady flow field, the wear depth is calculated according to the wall damage rate; S6, calculating the difference between the wear depth at the current moment and the wear depth at the previous moment, and obtaining the mesh deformation at the current time; S7, judging whether the wear time reaches the set time, if not, returning to S5, if reaching the set time, proceeding to S8; S8. According to the mesh deformation at the current time, the particle impact velocity direction is used as the reference for decomposition, and the distance obtained by decomposing several vertices of each unit surface is moved to achieve the effect of wall morphology change, and obtain the wear depth, wall morphology change, and transient flow field change under the total time.

2. The method for quantitatively predicting progressive wear of hydraulic machinery system components based on dynamic grid technology according to claim 1, characterized in that: The specified boundary conditions include velocity inlet, total pressure outlet, and no-slip wall.

3. The method for quantitatively predicting progressive wear of hydraulic machinery system components based on dynamic grid technology according to claim 1, characterized in that: The characteristics of the transient sand-laden stable flow field are that the inlet and outlet pressure difference remains constant, the internal flow field distribution conforms to the law, and the particle injection and particle output remain balanced.

4. The method for quantitatively predicting progressive wear of hydraulic machinery system components based on dynamic grid technology according to claim 1, characterized in that: The wear model adopts the Oka wear model.

5. The method for quantitatively predicting progressive wear of hydraulic machinery system components based on dynamic grid technology according to claim 1, characterized in that: Calculation of wear depth includes: Where h is the wear depth; E(α) is the wear rate obtained by the Oka wear model; M d is the mass of particles impacting a single grid unit in each time step; c is the ratio of the single-step wear time to the transient calculation time step; A is the area of ​​a single grid unit surface.

6. The method for quantitatively predicting progressive wear of hydraulic machinery system components based on dynamic grid technology according to claim 1, characterized in that: According to the mesh deformation at the current time, the decomposition based on the particle impact velocity direction includes: Get the particle impact velocity vector of the unit grid surface; Normalize the velocity vector and project it onto the three coordinate axes to obtain the components in the three directions; The wear depth is multiplied by the components in the three directions respectively and assigned as offset to the three components of the four nodes of the unit mesh surface.

7. The method for quantitatively predicting progressive wear of hydraulic machinery system components based on dynamic grid technology according to claim 1, characterized in that: Whether the wear time reaches the set time refers to whether the cumulative number of steps per unit wear time step reaches the total number of calculation steps.

8. The method for quantitatively predicting progressive wear of hydraulic machinery system components based on dynamic grid technology as claimed in claim 1, characterized in that: CFD numerical calculation adopts a scale-adaptive simulation model.

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