A liquid rocket engine turbine pump seal-rotor design method

Abstract

To address the problem of insufficient design margin caused by the inability to obtain design boundaries in existing turbopump seal-rotor design methods, this invention discloses a liquid rocket engine turbopump seal-rotor design method comprising the following steps: Step S1, establishing a deterministic dynamic model of the seal-rotor; Step S2, setting the optimization parameters, optimization constraints, and objective function of the engine turbopump seal-rotor; Step S3, sampling the dimension and range of the uncertainty parameters to generate a sample library; Step S4, constructing a polynomial surrogate model of the seal-rotor dynamic characteristics; Step S5, determining the boundaries of the seal-rotor dynamic characteristics; Step S6, screening and optimizing the deterministic dynamic model of the seal-rotor to determine the final seal-rotor model result. This invention optimizes the seal-rotor design by combining uncertainty with rotor design, improving the reliability and safety of the rotor, and is simple, efficient, and easy to operate.

Description

Technical Field

[0001] This invention relates to a design method for a liquid rocket engine turbopump, specifically a seal-rotor design method for a liquid rocket engine turbopump. Background Technology

[0002] Liquid rocket engine turbopump seal-rotor operates in a complex and harsh mechanical and thermal environment, including high / low temperatures, high speeds, strong fluid vibration, and large axial loads. Its design and operating parameters inevitably change due to environmental influences, resulting in fluctuations in parameters such as imbalance, support parameters, material properties, sealing gaps, and even slight spalling of the impeller disc. Machining errors in its parts, installation gaps, and repeated disassembly and assembly can all alter the seal-rotor's balance, and residual imbalance can easily lead to excessive vibration. Furthermore, the harsh environment can cause nonlinear changes in the bearing axial force, leading to nonlinear vibration of the seal-rotor, further deforming the centrifugal pump impeller structure, and altering the sealing gaps of its key components. This results in unexpected fluctuations in sealing stiffness and damping, affecting the stability of the seal-rotor.

[0003] Existing liquid rocket engine turbopump seal-rotor designs are based on deterministic models, assuming that the parameters remain constant without considering parameter fluctuations. However, in actual seal-rotors, uncertainties exist at every stage of design, manufacturing, assembly, and service. Although the fluctuations of individual uncertainty parameters are small, their cumulative effect can significantly impact the dynamic response characteristics of the seal-rotor. This is especially true in reusable liquid rocket engines, where the high thrust, wide range of operating conditions, multiple starts, and long-term operation further amplify the parameter uncertainties of the turbopump seal-rotor. All these factors can lead to significant fluctuations in the dynamic characteristics of the seal-rotor within a certain range, resulting in insufficient design margins. This can cause problems such as excessive vibration and frequent failures during operation, affecting the safety and reliability of the liquid rocket engine turbopump. Summary of the Invention

[0004] The purpose of this invention is to solve the problem that existing turbopump seal-rotor designs fail to consider parameter uncertainties and thus cannot obtain design boundaries, resulting in insufficient design margins, poor safety and reliability of the designed seal-rotor due to parameter fluctuations. This invention provides a liquid rocket engine turbopump seal-rotor design method that combines uncertainty with the seal-rotor design to optimize the design of the seal-rotor, improve the reliability and safety of the seal-rotor, and is simple, efficient and easy to operate.

[0005] To achieve the above objectives, the technical solution provided by this invention is as follows:

[0006] A liquid rocket engine turbopump seal-rotor design method, characterized by the following steps:

[0007] Step S1: Based on the design specifications of the liquid rocket engine turbopump, establish an initial seal-rotor model. Based on the initial seal-rotor model, obtain a deterministic dynamic model of the seal-rotor using the finite element method.

[0008] Step S2: Based on the seal-rotor deterministic dynamics model, set the optimization parameters, optimization constraints, and objective function for the engine turbopump seal-rotor.

[0009] Step S3: Based on the physical parameters affecting the dynamic characteristics of the seal-rotor, estimate the output range of the dynamic characteristics to obtain the dimension and range of the uncertainty parameters. Sample the uncertainty parameters within the range to generate a sample library.

[0010] Step S4: Based on the established seal-rotor deterministic dynamics model, determine the dynamic characteristics corresponding to each sample point in the sample library, and construct a polynomial surrogate model of the seal-rotor dynamic characteristics.

[0011] Step S5: Based on the polynomial surrogate model of the seal-rotor dynamic characteristics, the boundary of the seal-rotor dynamic characteristics is determined using the extremum search algorithm.

[0012] Step S6: Based on the boundary of the seal-rotor dynamic characteristics, calculate the optimization constraints and the boundary of the objective function. Within the set optimization parameter range, use an optimization algorithm to screen and optimize the seal-rotor deterministic dynamic model, determine the final seal-rotor model result, and complete the seal-rotor design of the liquid rocket engine turbopump based on the final seal-rotor model result.

[0013] Furthermore, step 1 specifically includes:

[0014] Step S1.1: Based on the design specifications of the liquid rocket engine turbopump, establish an initial seal-rotor model and make preliminary divisions of the initial seal-rotor model, namely, dividing it into disk units, support units and shaft units.

[0015] Step S1.2: Set a disk node at the center of the disk unit and add inertia at the disk node; set a support unit node at the bearing center of the support unit to introduce bearing support stiffness and damping; divide the shaft unit into shaft segments according to the shaft length, with each segment satisfying a length-to-diameter ratio of less than 1; calculate the structural parameters of the disk unit, shaft unit, and support unit using a three-dimensional solid model, and establish the mass matrix, damping matrix, stiffness matrix, and rotation matrix of the initial seal-rotor model based on the finite element method to obtain the seal-rotor deterministic dynamic model:

[0016]

[0017] In the formula, , , , These are the mass matrix, damping matrix, stiffness matrix, and rotation matrix, respectively. For sealing - rotor rotation speed , , These are the acceleration, velocity, and displacement vectors of the seal-rotor, respectively. This is the excitation force vector experienced by the sealed rotor.

[0018] Furthermore, step S2 specifically includes:

[0019] Step S2.1: Based on the deterministic dynamic model of the seal-rotor, set the optimization parameters of the engine turbopump seal-rotor. The optimization parameters include support parameters and shaft parameters, and give the optimization parameter range for each.

[0020] Step S2.2: Set optimization constraints, including critical speed constraints and disk inertia parameter constraints; the critical speed constraint sets a 20% design margin between the seal-rotor operating speed and the critical speed, and the disk inertia parameter constraint sets a 10% design margin between the seal-rotor pole rotational inertia and the diameter rotational inertia.

[0021] Among them, the isolation margin between the seal-rotor operating speed and the critical speed The expression is:

[0022]

[0023] in, For the sealing-rotor operating speed, This refers to the critical speed of the sealed rotor.

[0024] Margin of Seal-Rotor Pole Moment of Inertia and Diameter Moment of Inertia The expression is:

[0025]

[0026] In the formula, For the polar rotational inertia of the sealed rotor, The diameter and moment of inertia of the sealed rotor;

[0027] Step S2.3: Set the objective function, which is the isolation margin between the sealing-rotor operating speed and the critical speed.

[0028] Furthermore, in step S3, the specific steps for generating the sample library are as follows:

[0029] a.1, Determine the physical parameters affecting the seal-rotor dynamic characteristics. Select q uncertain parameters from these physical parameters, and give upper and lower bounds for each uncertain parameter. The sampling set of the q uncertain parameters is as follows: Transforming the interval variable between the upper and lower bounds into a standard interval variable yields the following result:

[0030]

[0031] in, This is the lower bound for the uncertainty parameter. This is the upper bound of the uncertainty parameter. The transformed standard interval variable;

[0032] a.2, According to Chebyshev's rule, the sample library is as follows:

[0033]

[0034] in , ... Let x be the discrete sampling points of x in the domain [-1, 1].

[0035] Furthermore, step S4 specifically includes:

[0036] Step S4.1: Select the deterministic dynamic characteristics corresponding to N sample points from the seal-rotor deterministic dynamic model sample library to obtain the set of deterministic dynamic characteristic vectors corresponding to the N sample points. :

[0037]

[0038] in, This is the deterministic dynamic characteristic vector corresponding to the first sample point. This is the deterministic dynamic characteristic vector corresponding to the second sample point. This is the deterministic dynamic characteristic vector corresponding to the Nth sample point;

[0039] Step S4.2, construct the polynomial proxy model:

[0040] ;

[0041] in, The transformation matrix is ​​composed of the substitution values ​​of the basis vectors at each sample point. is the basis vector.

[0042] Furthermore, in step S5, the maximum / minimum search algorithm is an optimization iterative algorithm, a simulated annealing algorithm, a global search algorithm, or a scan algorithm; the boundary of the seal-rotor dynamic characteristics is:

[0043] .

[0044] Furthermore, step S6 specifically includes:

[0045] Step S6.1: Based on the seal-rotor dynamic characteristic boundary U, calculate the boundary of the seal-rotor operating speed and critical speed isolation margin. And the boundary between the seal-rotor pole moment of inertia and the diameter moment of inertia margin. ;

[0046] Step S6.2: Eliminate design parameters that do not meet the optimization constraints within the boundary range. Within the range of design parameters that meet the optimization constraints, use an optimization algorithm to search for the maximum objective function. Output the final seal-rotor model result based on the maximum objective function. Complete the seal-rotor design of the liquid rocket engine turbopump based on the final seal-rotor model result.

[0047] Furthermore, step S6.2 specifically includes:

[0048] Step S6.2.1, based on the minimum value of the isolation margin between the seal-rotor operating speed and the critical speed. and the minimum value of the polar moment of inertia and the diameter moment of inertia margin. Select the support parameters and shaft parameters that meet the optimization constraints;

[0049] Step S6.2.2: Use an optimization algorithm to search for the maximum objective function. The optimal support parameters and shaft parameters of the seal-rotor are determined, and the final seal-rotor model results are output. Based on the final seal-rotor model results, the seal-rotor design of the liquid rocket engine turbopump is completed.

[0050] Furthermore, in step S6.2.2, the optimization algorithm is simulated annealing, gradient descent, or genetic algorithm.

[0051] Compared with the prior art, the present invention has the following beneficial technical effects:

[0052] 1. The liquid rocket engine turbopump seal-rotor design method of the present invention addresses the changes in the seal-rotor dynamic characteristics caused by uncertain parameters by establishing an interval polynomial surrogate model. It combines uncertainty with the seal-rotor design, using the upper and lower boundaries of the obtained optimization constraints and the values ​​of the objective function within the boundary range as the verification objects. This overcomes the shortcomings of existing technologies that cannot obtain design boundaries due to the lack of consideration of uncertain parameters. It can not only effectively avoid the vibration amplitude from exceeding the standard, but also reserve sufficient safety margin, thus better ensuring the reliability and safety of the seal-rotor.

[0053] 2. The liquid rocket engine turbopump seal-rotor design method of the present invention can flexibly select uncertainty parameters according to actual needs, which can be a single action or multiple combined actions. It is simple, practical and easy to operate. The design method sets optimization constraints and eliminates sample points that do not meet the constraints during the optimization process, ensuring the reliability of the output rotor model, avoiding unnecessary calculations and improving optimization efficiency.

[0054] 3. The liquid rocket engine turbopump seal-rotor design method of the present invention calls the pre-written seal-rotor dynamic equation solving program for solving, which can make use of the original deterministic seal-rotor related program, reduce the workload, and further improve work efficiency; at the same time, it can take into account the dynamic stiffness of the rolling bearing, the additional stiffness and damping brought by the seal, which can truly reflect the dynamic characteristics of the actual seal-rotor and reduce modeling errors.

[0055] 4. The liquid rocket engine turbopump seal-rotor design method of the present invention has the advantage of establishing a polynomial surrogate model not only in solving multi-source uncertain parameter interval dynamics problems, but also in being applicable to single-dimensional or two-dimensional interval uncertain problems. In particular, when the dimension is larger or the order is higher, the established polynomial surrogate model can save a lot of computational costs and can be reused in liquid rocket engines. Attached Figure Description

[0056] Figure 1 This is a schematic flowchart of an embodiment of the liquid rocket engine turbopump seal-rotor design method of the present invention;

[0057] Figure 2 This is a schematic diagram of the seal-rotor model division in an embodiment of the liquid rocket engine turbopump seal-rotor design method of the present invention;

[0058] Figure 3 This is a schematic diagram of the seal-rotor dynamic response curve of a turbopump under design conditions that do not consider uncertainties;

[0059] Figure 4This is a schematic diagram of the dynamic response curve of a turbine pump seal-rotor under the influence of uncertain parameter fluctuations without considering design uncertainties.

[0060] Figure 5 This is a schematic diagram of the dynamic response curve of the seal-rotor under the influence of uncertain parameter fluctuations in an embodiment of the liquid rocket engine turbopump seal-rotor design method of the present invention. Detailed Implementation

[0061] To make the objectives, advantages, and features of the present invention clearer, the present invention will be further described in detail below with reference to the accompanying drawings and specific embodiments. Those skilled in the art should understand that these embodiments are merely used to explain the technical principles of the present invention and are not intended to limit the scope of protection of the present invention.

[0062] like Figure 1 As shown, this embodiment provides a liquid rocket engine turbopump seal-rotor design method, specifically including the following steps:

[0063] Step S1: Establish a deterministic dynamic model of the seal-rotor system.

[0064] like Figure 2 As shown, for the initial design of the seal-rotor, the seal-rotor model is divided into disk elements, support elements, and shaft elements. The disk nodes are located at the center of gravity of the disk, and inertia is added at the nodes. The support element nodes are located at the bearing centers. The cyan stepped shaft in the figure represents the shaft element, which is appropriately divided according to the shaft length, with each segment having a length-to-diameter ratio less than 1. The yellow-marked locations in the figure represent disk elements: distributed at axial positions of 0.0 m, 0.12 m, 0.22 m, 0.32 m, 0.42 m, and 0.55 m, etc.; disk nodes are set at the center of each disk element, and the mass and moment of inertia calculated from the 3D solid model are added. The red-marked locations represent support elements: distributed at axial positions of 0.10 m, 0.18 m, 0.38 m, and 0.50 m, etc.; support nodes are set at the bearing centers of each support element to introduce bearing support stiffness and damping. The stiffness and damping generated by fluid excitation at the seal are added to the corresponding nodes.

[0065] The structural parameters of the disk element, shaft element, and support element are calculated using a three-dimensional solid model. Based on the finite element method, the mass matrix, damping matrix, stiffness matrix, and rotation matrix of the initial seal-rotor model are established, resulting in a deterministic dynamic model of the seal-rotor.

[0066] The deterministic finite element model of the seal-rotor system can be expressed by the following dynamic equations:

[0067]

[0068] In the formula, M, C, K, and G are the mass matrix, damping matrix, stiffness matrix, and rotation matrix, respectively (which are known axioms), and Ω is the seal-rotor rotational speed. , , These are the acceleration, velocity, and displacement vectors of the seal-rotor, respectively. This is the excitation force vector of the sealed-rotor system.

[0069] Since the dynamic stiffness of a rolling bearing is related to the axial force and rotational speed, the dynamic stiffness of the bearing is solved based on a five-degree-of-freedom quasi-static ball bearing model. The expression for the bearing stiffness is:

[0070]

[0071] In the formula, Fx and Fy are the radial forces applied to the bearing, Fz is the axial force applied to the bearing, Mx and My are the torques, δx, δy, and δz are the relative displacements of the inner and outer rings in the x, y, and z directions, θx and θy are the relative rotation angles of the inner and outer rings in the x and y directions, and the elements on the main diagonal are the radial stiffness, axial stiffness, and angular stiffness in the x and y directions, respectively.

[0072] K b By adding it to each bearing node, the stiffness matrix K can be obtained.

[0073] Based on the assumption of small, centripetal perturbations, and using different eddy frequencies as input conditions, CFD quasi-steady-state numerical simulations were employed to obtain the radial force Fr and tangential force Ft excited by the sealing fluid at each eddy frequency. With the eddy frequency as the independent variable and Fr and Ft as dependent variables, the damping coefficient can be obtained through least-squares fitting. The functional equations for the sealing radial force, tangential force, and eddy frequency are obtained as follows:

[0074]

[0075] In the formula, F r F t ω represents the radial and tangential forces of the seal, ω represents the eddy frequency, K and k represent the direct and cross stiffness of the seal, respectively, C and c represent the direct and cross damping of the seal, respectively, M and m represent the direct and cross inertia coefficients, respectively, and e represents the static eccentricity of the seal.

[0076] The static eccentricity of the seal is generally taken as 10% of the seal radius clearance, and the whirl frequency is taken as ±Ω, ±0.5Ω, and 0, where Ω is the rotational angular velocity of the seal-rotor, "+" indicates whirl in the same direction as the rotation of the seal-rotor, and "-" indicates whirl in the opposite direction.

[0077] Step S2: Set optimization parameters, optimization constraints, and objective function.

[0078] The selection of optimization parameters mainly includes three categories: support parameters, disk parameters, and shaft parameters. Support parameters include the stiffness and position of the fulcrum; disk parameters include the disk's position, mass, polar moment of inertia, and diametrical moment of inertia; shaft parameters include the shaft's length and inner and outer diameters. Generally, disk parameters are related to the performance and efficiency of the turbine pump and should not be modified. Support and shaft parameters are the focus of optimization. Based on actual needs, the support and shaft parameters to be optimized are set, and the optimization range is given.

[0079] Optimization constraints can include critical speed constraints and disk inertia parameter constraints. In this embodiment, the optimization constraints are set to a 20% margin between the operating speed and the critical speed of the sealed rotor, and a 10% margin between the pole moment of inertia and the diameter moment of inertia of the sealed rotor. The expression for the isolation margin between the operating speed and the critical speed of the sealed rotor is:

[0080]

[0081] In the formula, For the sealing-rotor operating speed, This refers to the critical speed of the sealed rotor.

[0082] The expressions for the pole moment of inertia and diameter moment of inertia margin of the sealed rotor are:

[0083]

[0084] In the formula, For the polar rotational inertia of the sealed rotor, The diameter and moment of inertia of the sealed rotor.

[0085] The objective function can be set as needed. In this embodiment, the objective function is set to the isolation margin between the working speed and the critical speed of the sealed rotor. Similarly, the shaft strain energy distribution and vibration amplitude can also be used for calculation.

[0086] Step S3: Given the dimension and range of the uncertainty parameters, sample all uncertainty parameters to generate a sample library.

[0087] Identify the physical parameters affecting the seal-rotor dynamics, such as unbalance, support parameters, material properties, seal clearance, slight disc spalling, and bearing axial force. In some cases, due to limitations in practical conditions and economic costs, it is difficult to obtain sufficient probabilistic information for these parameters. In contrast, interval quantization is much easier for determining the range of variable values, providing a more accurate estimate of the dynamic characteristic output range while saving significant costs. Based on specific needs, a subset of physical parameters is selected for analysis. Assuming q uncertainties are selected, including unbalance, bearing axial force, and additional seal stiffness, and given upper and lower bounds for each uncertainty parameter, the set of q uncertainties is as follows: Transforming an interval variable into a standard interval variable yields the following result:

[0088]

[0089] In the formula, This is the lower bound for the uncertainty parameter. This is the upper bound of the uncertainty parameter. These are standard interval variables after transformation and do not have actual physical meaning. During numerical calculations, an inverse transformation can be performed to map them to actual seal-rotor physical parameters.

[0090] Establishing a polynomial proxy set: Given a polynomial order n, generally n≥4, the sample library spanned by the roots of an (n+1)th order Chebyshev polynomial can be represented as:

[0091]

[0092] in , ... These are discrete sampling points selected according to Chebyshev's rule on the domain [-1,1] of x;

[0093] The sample vector for each dimension of the variable can be calculated using the following formula:

[0094]

[0095] The sample library contains If there are 1 sample points, Then all sample points in the sample library All will be used, if Then randomly select from the sample library 1 sample point.

[0096] Step S4: Based on the seal-rotor deterministic dynamics model, determine the dynamic characteristics corresponding to each sample point in the sample library, and construct a polynomial surrogate model of the seal-rotor dynamic characteristics.

[0097] The deterministic dynamic characteristics at the selected N sample points, obtained from the seal-rotor deterministic dynamic model, are as follows: .in, To select a set of deterministic dynamic characteristic vectors corresponding to N sample points, This is the deterministic dynamic characteristic vector corresponding to the first sample point. This is the deterministic dynamic characteristic vector corresponding to the second sample point. This is the deterministic dynamic characteristic vector corresponding to the Nth sample point.

[0098] The polynomial proxy model with the highest order of n is constructed as follows:

[0099]

[0100] in, The transformation matrix, composed of the substitution values ​​of the basis vectors at each sample point, is expressed as:

[0101]

[0102] The basis vectors X are arranged in ascending order from 0 to n according to their overall order and variable order, as expressed in the following expression:

[0103]

[0104] The established polynomial surrogate model has advantages not only in solving multi-source uncertain parameter interval dynamics problems, but also in single-dimensional or two-dimensional interval uncertain problems, where all sample points in the sample library will be used. Especially when the dimension is large or the order is high, the established polynomial surrogate model can save a significant amount of computational cost.

[0105] Step S5: Based on the polynomial surrogate model of the seal-rotor dynamics characteristics, use the maximum / minimum search algorithm to determine the boundary of the seal-rotor dynamics characteristics.

[0106] Based on the established polynomial surrogate model of the seal-rotor dynamics, the maximum / minimum value can be found through optimization iteration, simulated annealing algorithm, global search, or sweep method. The boundary expression of the seal-rotor dynamics is then obtained as follows:

[0107] .

[0108] Step S6: Based on the boundary of the seal-rotor dynamic characteristics, calculate the objective function. Within the range of the optimization parameters, use an optimization algorithm to screen and optimize the seal-rotor model to determine the final seal-rotor model result.

[0109] Specifically, in this embodiment, the objective function is the isolation margin. Based on the seal-rotor dynamic characteristic boundary U, the boundary between the seal-rotor operating speed and the critical speed isolation margin is calculated. Calculate the boundary margins for the polar and diametrical moments of inertia of the sealed rotor. The minimum value of the isolation margin between the operating speed and the critical speed. Minimum values ​​of polar moment of inertia and diameter moment of inertia margin The algorithm determines whether the selected design parameters within the optimization parameter range meet the optimization constraints set in this embodiment: "a 20% design margin is set between the operating speed and critical speed of the seal-rotor, and a 10% design margin is set between the pole moment of inertia and the diameter moment of inertia of the seal-rotor." Design parameters that do not meet the optimization constraints are then removed. Simulated annealing, gradient descent, or genetic algorithms are used to search for the maximum objective function. The final seal-rotor model result is output.

[0110] like Figure 3 As shown, the operating speed of the turbine pump seal-rotor is 17800 r / min. Without considering uncertainties, the first-order critical speed of the turbine pump seal-rotor is 21533 r / min. The isolation margin between the operating speed and the critical speed is 21.0%, meeting the requirement of "setting a 20% design margin between the operating speed and the critical speed of the seal-rotor." However, under the influence of fluctuations in uncertain parameters, such as... Figure 4 As shown, the original single-peak resonant frequency evolved into a high-amplitude resonant band, meaning that within a frequency range near the original critical speed, the vibration of the seal-rotor could be significant. Furthermore, the maximum amplitude value is no longer at the frequency position under the original deterministic condition, indicating a frequency shift. The deterministic curve is always contained within the interval solution range, suggesting that the deterministic solution can be considered a special case of the interval solution. After considering the uncertainty parameters, the minimum interval boundary value of the first-order critical speed of the turbine pump seal-rotor without considering uncertainties is 20815 r / min. At this point, the isolation margin between the operating speed and the critical speed is 16.9%, which does not meet the requirement of "setting a 20% design margin between the operating speed and the critical speed of the seal-rotor." This indicates that fluctuations in the uncertainty parameters led to insufficient original design margins, affecting the safety and reliability of the seal-rotor.

[0111] However, the turbine pump seal-rotor designed using the method of this invention takes into account the impact of uncertain parameter fluctuations from the initial design stage, such as... Figure 5As shown, the minimum value of the first critical speed range of the turbine pump seal-rotor is 22048 r / min, and the isolation margin between the operating speed and the critical speed is 23.9%. Even under the influence of uncertain parameter fluctuations, it still meets the requirement of "setting a 20% design margin between the operating speed and the critical speed of the seal-rotor". This solves the problem in the prior art that the design boundary cannot be obtained due to the lack of consideration of uncertain parameters, resulting in insufficient design margin. It can reserve sufficient safety margin and better ensure the safety and reliability of the seal-rotor.

[0112] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, and are not intended to limit them. Although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some or all of the technical features therein. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of the present invention.

Claims

1. A liquid rocket engine turbopump seal-rotor design method, characterized in that, Includes the following steps: Step S1: Based on the design specifications of the liquid rocket engine turbopump, establish an initial seal-rotor model. Based on the initial seal-rotor model, obtain a deterministic dynamic model of the seal-rotor using the finite element method. Step S2: Based on the seal-rotor deterministic dynamics model, set the optimization parameters, optimization constraints, and objective function for the engine turbopump seal-rotor. Step S3: Based on the physical parameters affecting the dynamic characteristics of the seal-rotor, estimate the output range of the dynamic characteristics to obtain the dimension and range of the uncertainty parameters. Sample the uncertainty parameters within the range to generate a sample library. Step S4: Based on the established seal-rotor deterministic dynamics model, determine the dynamic characteristics corresponding to each sample point in the sample library, and construct a polynomial surrogate model of the seal-rotor dynamic characteristics. Step S5: Based on the polynomial surrogate model of the seal-rotor dynamic characteristics, the boundary of the seal-rotor dynamic characteristics is determined using the extremum search algorithm. Step S6: Based on the boundary of the seal-rotor dynamic characteristics, calculate the optimization constraints and the boundary of the objective function. Within the set optimization parameter range, use an optimization algorithm to screen and optimize the seal-rotor deterministic dynamic model, determine the final seal-rotor model result, and complete the seal-rotor design of the liquid rocket engine turbopump based on the final seal-rotor model result.

2. The liquid rocket engine turbopump seal-rotor design method according to claim 1, characterized in that, Step 1 is as follows: Step S1.1: Based on the design specifications of the liquid rocket engine turbopump, establish an initial seal-rotor model and make preliminary divisions of the initial seal-rotor model, namely, dividing it into disk units, support units and shaft units. Step S1.2: Set a disk node at the center of the disk unit and add inertia at the disk node; set a support unit node at the bearing center of the support unit to introduce bearing support stiffness and damping; divide the shaft unit into shaft segments according to the shaft length, with each segment satisfying a length-to-diameter ratio of less than 1; calculate the structural parameters of the disk unit, shaft unit, and support unit using a three-dimensional solid model, and establish the mass matrix, damping matrix, stiffness matrix, and rotation matrix of the initial seal-rotor model based on the finite element method to obtain the seal-rotor deterministic dynamic model: ； In the formula, , , , These are the mass matrix, damping matrix, stiffness matrix, and rotation matrix, respectively. For sealing - rotor rotation speed , , These are the acceleration, velocity, and displacement vectors of the seal-rotor, respectively. This is the excitation force vector experienced by the sealed rotor.

3. The liquid rocket engine turbopump seal-rotor design method according to claim 2, characterized in that, Step S2 specifically involves: Step S2.1: Based on the deterministic dynamic model of the seal-rotor, set the optimization parameters of the engine turbopump seal-rotor. The optimization parameters include support parameters and shaft parameters, and give the optimization parameter range for each. Step S2.2: Set optimization constraints, including critical speed constraints and disk inertia parameter constraints; the critical speed constraint sets a 20% design margin between the seal-rotor operating speed and the critical speed, and the disk inertia parameter constraint sets a 10% design margin between the seal-rotor pole rotational inertia and the diameter rotational inertia. Among them, the isolation margin between the seal-rotor operating speed and the critical speed The expression is: ； in, For the sealing-rotor operating speed, This refers to the critical speed of the sealed rotor. Margin of Seal-Rotor Pole Moment of Inertia and Diameter Moment of Inertia The expression is: ； In the formula, For the polar rotational inertia of the sealed rotor, The diameter and moment of inertia of the sealed rotor; Step S2.3: Set the objective function, which is the isolation margin between the sealing-rotor operating speed and the critical speed.

4. The liquid rocket engine turbopump seal-rotor design method according to claim 3, characterized in that: In step S3, the specific steps for generating the sample library are as follows: a.1, Determine the physical parameters affecting the seal-rotor dynamic characteristics. Select q uncertain parameters from these physical parameters, and give upper and lower bounds for each uncertain parameter. The sampling set of the q uncertain parameters is as follows: Transforming the interval variable between the upper and lower bounds into a standard interval variable yields the following result: ； in, This is the lower bound for the uncertainty parameter. This is the upper bound of the uncertainty parameter. The transformed standard interval variable; a.2, According to Chebyshev's rule, the sample library is as follows: ； in , ... Let x be the discrete sampling points of x in the domain [-1, 1].

5. The liquid rocket engine turbopump seal-rotor design method according to claim 4, characterized in that: Step S4 is as follows: Step S4.1: Select the deterministic dynamic characteristics corresponding to N sample points from the seal-rotor deterministic dynamic model sample library to obtain the set of deterministic dynamic characteristic vectors corresponding to the N sample points. : ； in, This is the deterministic dynamic characteristic vector corresponding to the first sample point. This is the deterministic dynamic characteristic vector corresponding to the second sample point. This is the deterministic dynamic characteristic vector corresponding to the Nth sample point; Step S4.2, construct the polynomial proxy model: ； in, The transformation matrix is ​​composed of the substitution values ​​of the basis vectors at each sample point. is the basis vector.

6. The liquid rocket engine turbopump seal-rotor design method according to claim 5, characterized in that: In step S5, the maximum / minimum search algorithm is an optimization iterative algorithm, a simulated annealing algorithm, a global search algorithm, or a scanning algorithm; the boundary of the seal-rotor dynamic characteristics is: 。 7. The liquid rocket engine turbopump seal-rotor design method according to claim 6, characterized in that: Step S6 is as follows: Step S6.1: Based on the seal-rotor dynamic characteristic boundary U, calculate the boundary of the seal-rotor operating speed and critical speed isolation margin. And the boundary between the seal-rotor pole moment of inertia and the diameter moment of inertia margin. ; Step S6.2: Eliminate design parameters that do not meet the optimization constraints within the boundary range. Within the range of design parameters that meet the optimization constraints, use an optimization algorithm to search for the maximum objective function. Output the final seal-rotor model result based on the maximum objective function. Complete the seal-rotor design of the liquid rocket engine turbopump based on the final seal-rotor model result.

8. The liquid rocket engine turbopump seal-rotor design method according to claim 7, characterized in that, Step S6.2 specifically includes: Step S6.2.1, based on the minimum value of the isolation margin between the seal-rotor operating speed and the critical speed. and the minimum value of the polar moment of inertia and the diameter moment of inertia margin. Select the support parameters and shaft parameters that meet the optimization constraints; Step S6.2.2: Use an optimization algorithm to search for the maximum objective function. The optimal support parameters and shaft parameters of the seal-rotor are determined, and the final seal-rotor model results are output. Based on the final seal-rotor model results, the seal-rotor design of the liquid rocket engine turbopump is completed.

9. The liquid rocket engine turbopump seal-rotor design method according to claim 8, characterized in that: In step S6.2.2, the optimization algorithm is simulated annealing, gradient descent, or genetic algorithm.

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