CN-122020759-A - Optimization method and system for dry gas seal groove type parameters

CN122020759ACN 122020759 ACN122020759 ACN 122020759ACN-122020759-A

Abstract

The invention provides a method and a system for optimizing parameters of a dry gas seal groove, which relate to the technical field of airtight structure optimization, and the method comprises the steps of determining the types and the ranges of the parameters of the groove, randomly generating parameter values and normalizing the combination to construct an initial population; the method comprises the steps of carrying out finite element simulation on each individual, obtaining air film rigidity, leakage rate and coanda data, calculating rigid-leakage ratio and coanda freezing index, constructing sensitive response index through parameter perturbation, designing self-adaptive adjustment factors decreasing with iteration, constructing first optimization index and second optimization index, selecting, crossing and freezing guide variation on the population by adopting a multi-objective genetic algorithm, carrying out iterative optimization until the preset times, and outputting individual vectors with optimal two indexes as final groove type parameters.

Inventors

YU JIASHU
AN DUO
CHENG YUE
ZHANG LANXIA
DING XUEXING
YU JIANPING

Assignees

兰州理工大学

Dates

Publication Date: 20260512
Application Date: 20260413

Claims (9)

1. The optimization method of the dry gas seal groove type parameter is characterized by comprising the following specific steps of: Step 1, determining the type and the preset range of dry gas seal groove type parameters, generating a plurality of random parameter values in the preset range of each parameter, and arranging and combining the random parameter values subjected to normalization processing of various parameters to generate a plurality of individual vectors so as to construct an initial population; Step 2, performing finite element simulation on the dry gas seal groove under each individual vector to obtain the air film rigidity, leakage rate and coanda data of the dry gas seal groove, calculating the rigid-leakage ratio, and constructing coanda freezing indexes based on the coanda data; Step 3, designing an adaptive adjustment factor which decreases with iteration times, constructing a first optimization index based on the rigid-drain ratio and the adaptive adjustment factor, and constructing a second optimization index based on the coanda freezing index and the adaptive adjustment factor; And 4, performing multi-objective genetic algorithm selection and cross operation on individual vectors in the initial population based on the first optimization index and the second optimization index, performing perturbation analysis on the crossed individual vectors to perform freezing guide variation so as to obtain an iterative population, updating the iterative population into a new initial population, iterating until the preset iteration times are reached, and selecting the individual vector with the largest rigid-drain ratio in the iterative population of the last iteration as a final dry gas seal groove type parameter.
2. The method for optimizing dry gas seal groove type parameters according to claim 1, wherein the dry gas seal groove type parameters comprise an inner radius, a groove root radius, an outer radius, a spiral angle, a groove circumferential included angle and a dam circumferential included angle.
3. The method for optimizing dry gas seal groove type parameters according to claim 2, wherein the rigid-leak ratio is a ratio of film rigidity to leak rate; selecting an annular area as an area to be analyzed in the dry gas sealing groove based on the inner radius and the groove root radius, wherein the coanda data comprise pressure gradient distribution and gas flow radial velocity distribution of the area to be analyzed; The logic for constructing the coanda freezing index is that the pressure gradient distribution and the airflow radial velocity distribution are normalized, the pressure gradient distribution in the area to be analyzed is integrated to obtain the pressure driving energy, the airflow radial velocity in the area to be analyzed is integrated to obtain the airflow radial momentum releasing energy, and the airflow radial momentum releasing energy is compared with the pressure driving energy to be used as the coanda freezing index.
4. The method for optimizing the dry gas seal groove type parameter according to claim 1, wherein the logic for constructing the sensitive response index is that the disturbance amplitude is preset, disturbance is applied to any dry gas seal groove type parameter in any body vector according to the preset disturbance amplitude within a preset range, the rigid-to-leakage ratio after the disturbance is obtained, the rigid-to-leakage ratio difference before and after the disturbance is calculated, the square of the ratio of the rigid-to-leakage ratio difference to the preset disturbance amplitude is calculated and used as the response sensitivity of the dry gas seal groove type parameter, all dry gas seal groove type parameters of the individual vector are traversed, and the response sensitivity of all dry gas seal groove type parameters is accumulated and then the root number is opened to obtain the sensitive response index of the individual vector.
5. The optimization method of the dry gas seal groove type parameter according to claim 4, wherein the logic of designing the self-adaptive adjustment factor decreasing with the iteration number is that the preset iteration number is obtained, the current iteration number is compared with the preset iteration number to obtain an iteration ratio, and the iteration ratio is processed based on a Sigmoid function to obtain the self-adaptive adjustment factor under the current iteration round.
6. The method for optimizing dry gas seal groove type parameters of claim 5, wherein the logic for constructing the first optimization index is to calculate a difference value of 1 and an adaptive adjustment factor thereof under the current iteration round for any one body vector, and then calculate a product of the difference value and a rigid-drain ratio thereof under the current iteration round as the first optimization index thereof under the current iteration round.
7. The method of claim 6 wherein the logic for constructing the second optimization index is to calculate, for any one of the body vectors, a product between an adaptive adjustment factor and a coanda freeze index for the current iteration run as the second optimization index for the current iteration run.
8. The method for optimizing dry gas seal groove type parameters according to claim 4, wherein the logic for performing freeze-induced variation comprises presetting a sensitivity response index threshold, a variation range and a response sensitivity threshold of each dry gas seal groove type parameter; if the sensitive response index of an individual vector is larger than the sensitive response index threshold, randomly generating a random number in the variation range of any dry gas seal groove type parameter of the individual vector, adding the random number to 1, and multiplying the random number by the dry gas seal groove type parameter to obtain a variation result of the dry gas seal groove type parameter; If the sensitive response index of an individual vector is not greater than the sensitive response index threshold, comparing the response sensitivity of any dry gas seal groove type parameter in the individual vector with the corresponding response sensitivity threshold one by one, calling the dry gas seal groove type parameter with the response sensitivity smaller than the corresponding response sensitivity threshold as a freezing parameter, calling the rest dry gas seal groove type parameters as non-freezing parameters, randomly generating a random number in the variation range of any non-freezing parameter, adding 1 with the random number, multiplying the random number with the dry gas seal groove type parameter, and if the variation result after variation is not in the preset range of the corresponding non-freezing parameter, re-varying to obtain the variation result of the non-freezing parameter, and selecting a random number in the preset range of the freezing parameter as the variation result of the freezing parameter.
9. A dry gas seal groove type parameter optimization system is characterized in that the system is used for realizing the dry gas seal groove type parameter optimization method according to any one of claims 1-8, and specifically comprises the following steps: the population generation module is used for determining the types and the preset ranges of the dry gas seal groove type parameters, generating a plurality of random parameter values in the preset ranges of each parameter, and arranging and combining the random parameter values subjected to normalization processing of various parameters to generate a plurality of individual vectors so as to construct an initial population; The simulation analysis module is used for carrying out finite element simulation on the dry gas seal groove under each individual vector to obtain the air film rigidity, the leakage rate and the coanda data of the dry gas seal groove, calculating the rigid-leakage ratio, and constructing coanda freezing indexes based on the coanda data; The target construction module is used for designing an adaptive adjustment factor which decreases with the iteration number, constructing a first optimization index based on the rigid-drain ratio and the adaptive adjustment factor, and constructing a second optimization index based on the coanda freezing index and the adaptive adjustment factor; The algorithm optimization module is used for carrying out multi-objective genetic algorithm selection and cross operation on individual vectors in the initial population based on the first optimization index and the second optimization index, carrying out perturbation analysis on the crossed individual vectors to carry out freezing guide variation so as to obtain an iterative population, updating the iterative population into a new initial population, carrying out iteration until the preset iteration times are reached, and selecting the individual vector with the largest rigid-drain ratio in the iterative population of the last iteration as a final dry gas seal groove type parameter.

Description

Optimization method and system for dry gas seal groove type parameters Technical Field The invention relates to the technical field of airtight structure optimization, in particular to a method and a system for optimizing dry gas seal groove type parameters. Background In the technical field of dry gas sealing, the formation and stability of a gas film between sealing end faces are key for determining sealing performance. Particularly under the condition of hydrogen medium, the gas film shows remarkable coanda effect (namely coanda effect) at the micron scale due to low hydrogen density and high viscosity, so that the gas does not flow in a turbulent flow or laminar flow state in the traditional sense, but is in a boundary layer unseparated state for a long time, and the gas film is tightly adsorbed on the sealing end face. The physical characteristics enable the flow behavior between the sealing end faces to be more complex, the traditional groove type design method based on the conventional flow state assumption is difficult to accurately describe the actual flow state of the air film, and the design and optimization of the sealing structure are lack of pertinence. The existing spiral groove design depends on a simplified flow model, the influence of the coanda effect on the stability of the air film cannot be fully considered, and the performance advantage of dry gas sealing in a low-density and high-viscosity gas medium is difficult to fully develop. The above information disclosed in the background section is only for enhancement of understanding of the background of the disclosure and therefore it may include information that does not form the prior art that is already known to a person of ordinary skill in the art. Disclosure of Invention The invention aims to provide a method and a system for optimizing parameters of a dry gas seal groove, which are used for solving the problems in the background technology. In order to achieve the above purpose, the present invention provides the following technical solutions: the optimization method of the dry gas seal groove type parameter comprises the following specific steps: step 1, determining the type and the preset range of dry gas seal groove type parameters, generating a plurality of random parameter values in the preset range of each parameter, and arranging and combining the random parameter values subjected to normalization processing of various parameters to generate a plurality of individual vectors so as to construct an initial population; Step 2, performing finite element simulation on the dry gas seal groove under each individual vector to obtain the air film rigidity, leakage rate and coanda data of the dry gas seal groove, calculating the rigid-leakage ratio, and constructing coanda freezing indexes based on the coanda data; Step 3, designing an adaptive adjustment factor which decreases with iteration times, constructing a first optimization index based on the rigid-drain ratio and the adaptive adjustment factor, and constructing a second optimization index based on the coanda freezing index and the adaptive adjustment factor; And 4, carrying out multi-objective genetic algorithm selection and cross operation on individual vectors in the initial population based on the first optimization index and the second optimization index, carrying out perturbation analysis on the crossed individual vectors to carry out freezing guide variation so as to obtain an iterative population, updating the iterative population into a new initial population, carrying out iteration until the preset iteration times are reached, and selecting the individual vector with the largest rigid-drain ratio in the iterative population of the last iteration as a final dry gas seal groove type parameter. Further, the dry gas seal groove type parameters comprise an inner radius, a groove root radius, an outer radius, a spiral angle, a groove area circumferential included angle and a dam area circumferential included angle. Further, the rigid-leak ratio is the ratio of the air film rigidity to the leak rate; selecting an annular area as an area to be analyzed in the dry gas sealing groove based on the inner radius and the groove root radius, wherein the coanda data comprise pressure gradient distribution and gas flow radial velocity distribution of the area to be analyzed; The logic for constructing the coanda freezing index is that the pressure gradient distribution and the airflow radial velocity distribution are normalized, the pressure gradient distribution in the area to be analyzed is integrated to obtain the pressure driving energy, the airflow radial velocity in the area to be analyzed is integrated to obtain the airflow radial momentum releasing energy, and the airflow radial momentum releasing energy is compared with the pressure driving energy to be used as the coanda freezing index. Further, the disturbance amplitude is preset, disturbance is applied to any dry gas sea