CN-121980982-A - Response prediction method for ventilation supercavitation flow type in course of change of navigation depth

CN121980982ACN 121980982 ACN121980982 ACN 121980982ACN-121980982-A

Abstract

The invention discloses a response prediction method of a ventilation supercavitation flow pattern in a depth change process, which comprises the following steps of 1, constructing a mathematical model, 2, carrying out boundary condition setting and grid division on a river basin of an aircraft based on the mathematical model to obtain a numerical calculation model, 3, verifying the numerical calculation model to obtain a ventilation supercavitation numerical calculation model suitable for a depth change condition, and 4, carrying out simulation calculation on a ventilation supercavitation flow field under the depth change condition based on the supercavitation numerical calculation model to obtain a simulation result. The method for predicting the response of the ventilation supercavitation flow pattern in the navigation depth change process solves the problem that the prior art cannot predict the flow pattern change and response of cavitation bubbles in the navigation depth dynamic change process of the supercavitation aircraft.

Inventors

HUANG CHUANG
CHAI ZHIWEN
DANG JIANJUN
XU HAIYU
LI DAIJIN
LUO KAI

Assignees

西北工业大学

Dates

Publication Date: 20260505
Application Date: 20251205

Claims (10)

1. The response prediction method of the ventilation supercavitation flow type in the course of the change of the navigation depth is characterized by comprising the following steps: Step 1, constructing a mathematical model; step 2, setting boundary conditions and dividing grids of the river basin of the aircraft based on the mathematical model to obtain a numerical calculation model; step 3, verifying the numerical calculation model to obtain a ventilation supercavitation numerical calculation model suitable for the variable-depth condition; and 4, based on the super cavitation numerical calculation model, carrying out simulation calculation on the ventilation super cavitation flow field under the variable navigation depth condition to obtain a simulation result.
2. The method of claim 1, wherein the mathematical model in step 1 comprises a multiphase flow model, a turbulence model and a cavitation model.
3. The method for predicting the response of the ventilation supercavitation flow type in the process of changing the navigation depth according to claim 2, wherein the multiphase flow model is a split-phase flow model for obtaining a clear phase interface and a cavitation internal flow structure, and a basic control equation of the split-phase flow model comprises a continuity equation, a momentum equation and a volume fraction equation; the continuity equation is shown as a formula (1); (1); Wherein m is a phase, 1 and 2 respectively represent a liquid phase and a gas phase, gamma m is the volume fraction of the m-th phase, rho m is the density of the phase, v is the velocity vector of fluid infinitesimal, and t is time; the momentum equations are shown in formulas (2) and (3); (2); (3); Wherein p is static pressure, mu m is dynamic viscosity of fluid microelements, g is gravity acceleration, M is acting force of different phases, C D is a constant, rho n is gas-liquid two-phase mixed average density, A is internal phase interface area in unit volume, u α1 is alpha 1 phase velocity, and u α2 is alpha 2 phase velocity; The volume fraction equation is shown as a formula (4); (4)。
4. The method for predicting the response of the ventilation supercavitation flow type in the course of the change of the navigation depth according to claim 2, wherein the turbulence model is an SST k-omega model, and the basic equation of the SST k-omega model is shown as formulas (5) and (6); (5); (6); Wherein ρ m is density, U is speed, k is turbulence kinetic energy, μ is hydrodynamic viscosity, μ t is vortex viscosity coefficient, ω is turbulence frequency, p k is turbulence generation rate, σ ω3 , σ k3 , α 3 , β 3 and β' are model constants; The formula of the mixed function of the SST k-omega model is shown as formulas (7), (8) and (9); (7); (8); (9); Where y is the distance to the wall.
5. The method for predicting the response of a ventilation supercavitation flow pattern in a depth change process according to claim 2, wherein the cavitation model is a Singhal model, and the Singhal model is represented by formulas (10), (11) and (12) for mass transfer between phases; (10); (11); (12); Wherein, the Is the evaporation rate; Is the condensation rate, k is the local turbulence intensity, sigma is the liquid phase surface tension coefficient, F v is the vapor phase mass fraction, F g is the non-condensable gas mass fraction, p v is the bubble internal pressure, p ∞ is the far field pressure, model constants F e and F c are 0.02 and 0.01 respectively, p sat is the theoretical saturated vapor pressure, and ρ l is the far field fluid density.
6. The method for predicting response of ventilation supercavitation flow type in the course of changing the depth of a sea according to claim 2, wherein the specific process of step 2 is as follows: Step 2.1, setting a calculation domain scale, namely determining the axial total length of the calculation domain as 5 times of the length of the aircraft, determining the distance from the calculation domain inlet to the cavitation device at the head of the aircraft as 1 time of the length of the aircraft, and determining the distance from the calculation domain outlet to the tail jet outlet as 3 times of the length of the aircraft; step 2.2, setting a computing domain boundary condition, wherein the computing domain inlet boundary is set to be a speed inlet of 100m/s, the computing domain outlet boundary is set to be a pressure outlet of 0.2MPa, and the computing domain periphery is freely in and out; And 2.3, carrying out structured grid division on a calculation domain to obtain a numerical calculation model, wherein the grid scale in a cavitation encryption area of the calculation domain is not more than 0.5mm, the grid layer number of the cavitation encryption area of the calculation domain is not less than 70 layers, and more than 60% of grids of the calculation domain are concentrated in a ventilation super cavitation and tail jet flow influence area.
7. The method for predicting response of ventilation supercavitation flow pattern in course of change of navigation depth according to claim 2, wherein the verification in step 3 includes verification of free navigation supercavitation test on model lake of large-size ventilation supercavitation underwater vehicle and verification of independence of grid; The verification of the free navigation supercavitation test on the large-size ventilation supercavitation underwater vehicle model lake is specifically that the supercavitation size of the ventilation supercavitation flow type in the free navigation state obtained in the free navigation supercavitation test on the large-size ventilation supercavitation underwater vehicle model lake is compared with the supercavitation size obtained by numerical calculation, and the supercavitation size error is not more than 2.1%, which indicates that the numerical calculation model meets the requirement; The grid independence verification is specifically that the number of grids is not less than 364 ten thousand, so that the calculation accuracy is met, the waste of calculation resources is avoided, and the grid independence verification is met.
8. The method for predicting the response of the ventilation supercavitation flow field in the process of changing the depth of a sea according to claim 2, wherein the simulation calculation of the ventilation supercavitation flow field under the condition of changing the depth of a sea in step 4 specifically comprises the simulation calculation under the condition of lowering the depth of a sea step and the simulation calculation under the condition of increasing the depth of a sea step.
9. The method for predicting the response of the ventilation supercavitation flow type in the process of changing the depth of a ship according to claim 8, wherein the simulation calculation under the condition of lowering the depth of the ship is that the method of changing the environmental pressure step is adopted, the step change is carried out to 0.15MPa on the basis of stable cavitation corresponding to the environmental pressure of 0.2MPa, the characteristic scale of supercavitation and the change characteristic of the pressure in the cavitation are analyzed, the cavitation flow type under the same working condition is compared and the change of the cavitation flow type and the response characteristic are explored; For a cavitation device with a fixed size, when the cavitation number is small and the influence of gravity is not counted, the characteristic scale of the supercavitation is determined by the cavitation number, and the cavitation number is defined as shown in a formula (13): (13); wherein P ∞ is far-field static pressure, P c is cavitation internal gas static pressure, and U is incoming flow speed.
10. The method for predicting the response of the ventilation supercavitation flow pattern in the process of changing the navigation depth according to claim 8 is characterized by comprising the steps of performing simulation calculation on the ventilation supercavitation flow pattern during the increase of the navigation depth step according to a ventilation supercavitation numerical calculation model to obtain the ventilation supercavitation flow field, analyzing the ventilation supercavitation flow field to obtain the radius and half length of the ventilation supercavitation under the increase of the navigation depth step, analyzing the ventilation supercavitation flow variation and comparing the ventilation supercavitation flow variation with a constant navigation depth, and analyzing the flow pattern difference reason.

Description

Response prediction method for ventilation supercavitation flow type in course of change of navigation depth Technical Field The invention belongs to the technical field of cavitation flow type prediction of supercavitation aircrafts, and particularly relates to a response prediction method of ventilation supercavitation flow type in a navigation depth change process. Background The supercavitation aircraft generates the covering cavitation bubbles by introducing non-condensing gas, so that the resistance of the aircraft is obviously reduced, the speed bottleneck of the traditional underwater weapon is broken through, and the supercavitation aircraft is widely focused by students at home and abroad. Supercavitation aircraft hydrodynamic forces differ from fully wetted aircraft by virtue of the position and motion coupling relationship of the aircraft to cavitation flow patterns. The supercavitation aircraft has the adjustment of the navigation depth in the actual working process, and the response of the motion of the aircraft is inconsistent with the response of the cavitation due to the cavitation delay effect, so that the supercavitation form and the relative position of the cavitation are difficult to determine, and the navigation control and trajectory prediction of the supercavitation aircraft face challenges. According to the published literature, when the navigation depth changes, factors such as free surface effect, hydrostatic pressure and the like have a great influence on cavitation flow patterns, and the development of cavitation is delayed, and the response characteristic of the process leads to cavitation hydrodynamic nonlinear enhancement, so that cavitation navigation stability is further influenced. The current research is mainly focused on the influence of the navigation depth of the steady working condition on the supercavitation, and the research on the flow pattern change characteristic and response characteristic of the cavitation in the dynamic change process of the navigation depth is fresh. Disclosure of Invention The invention aims to provide a response prediction method for ventilation supercavitation flow patterns in the process of changing the navigation depth, and solves the problem that the prior art cannot predict flow pattern change and response of cavitation bubbles in the process of dynamically changing the navigation depth of a supercavitation aircraft. The invention adopts the technical scheme that the method for predicting the response of the ventilation supercavitation flow type in the course of the change of the navigation depth comprises the following steps: Step 1, constructing a mathematical model; step 2, setting boundary conditions and dividing grids of the river basin of the aircraft based on the mathematical model to obtain a numerical calculation model; step 3, verifying the numerical calculation model to obtain a ventilation supercavitation numerical calculation model suitable for the variable-depth condition; and 4, based on the super cavitation numerical calculation model, carrying out simulation calculation on the ventilation super cavitation flow field under the variable navigation depth condition to obtain a simulation result. The invention is also characterized in that: The digital model in the step 1 comprises a multiphase flow model, a turbulence model and a cavitation model. The multiphase flow model is selected from a split-phase flow model for obtaining a clear phase interface and a cavitation internal flow structure, wherein a basic control equation of the split-phase flow model comprises a continuity equation, a momentum equation and a volume fraction equation; The continuity equation is shown as a formula (1); (1); Wherein m is a phase, 1 and 2 respectively represent a liquid phase and a gas phase, gamma m is the volume fraction of the m-th phase, rho m is the density of the phase, v is the velocity vector of fluid infinitesimal, and t is time; The momentum equations are shown in formulas (2) and (3); (2); (3); Wherein p is static pressure, mu m is dynamic viscosity of fluid microelements, g is gravity acceleration, M is acting force of different phases, C D is a constant, rho n is gas-liquid two-phase mixed average density, A is internal phase interface area in unit volume, u α1 is alpha 1 phase velocity, and u α2 is alpha 2 phase velocity; the volume fraction equation is shown as formula (4); (4)。 the turbulence model adopts SSTk-omega model, and the basic equation of SSTk-omega model is shown in formulas (5) and (6); (5); (6); Wherein ρ m is density, U is speed, k is turbulence kinetic energy, μ is hydrodynamic viscosity, μ t is vortex viscosity coefficient, ω is turbulence frequency, p k is turbulence generation rate, σ ω3,σk3,α3,β3 and β' are model constants; The mixing function formula of SSTk-omega model is shown in formulas (7), (8) and (9); (7); (8); (9); Where y is the distance to the wall. The cavitation model adopts a Singhal model,