A method for judging the convergence of aerodynamic thermal characteristics of aircraft flow field

Abstract

The present invention discloses a method for judging the convergence of aerodynamic thermal characteristics of an aircraft flow field, which belongs to the field of aircraft thermal protection, and includes the steps of: constructing a weight function based on the correlation between flow field parameters and aerodynamic thermal characteristics, weightedly calculating the relative residual of the average of flow field thermal related parameters to judge the basic convergence of the flow field, and combining the characteristics of aircraft thermal protection, using different methods to judge the convergence of aerodynamic thermal characteristics in high heat areas and large-area low heat areas. The present invention can effectively avoid the phenomenon of inconsistency between the convergence of flow field and the convergence of aerodynamic thermal characteristics, and can reduce unnecessary redundant iterations while ensuring the accuracy requirements of aircraft thermal protection engineering.

Description

Technical Field

[0001] The present invention relates to the field of aircraft thermal protection, and more specifically, to a method for judging the convergence of aerodynamic thermal characteristics of an aircraft flow field. Background Art

[0002] When a spacecraft flies near space, if the speed is very high, the spacecraft will face strong aerodynamic heating, and the surface temperature of the spacecraft can often reach hundreds of Kelvin or even thousands of Kelvin. In order to ensure the normal operation of the internal components or systems of the spacecraft, thermal protection design is often required. Accurate prediction of the aerodynamic thermal characteristics of the spacecraft flow field is the basis of thermal protection and management of the spacecraft. With the development of high-performance computers, the numerical simulation of the aerodynamic thermal characteristics of the spacecraft flow field using computational simulation technology has attracted more and more attention. Due to its relatively low cost and relatively small application restrictions, it has become one of the main means of predicting and evaluating aerodynamic thermal characteristics. The numerical simulation of the aerodynamic thermal characteristics of the spacecraft flow field is generally achieved by iteratively solving the flow control equations. When the iterative calculation converges, the aerodynamic thermal characteristics data of concern to the user is obtained. One of the very important links is the convergence judgment of the numerical iterative calculation of the flow field. The accuracy of the aerodynamic thermal characteristics data depends to a certain extent on the effective judgment of the convergence of the numerical iteration. The convergence of numerical simulation of aircraft flow field is generally judged by flow field iteration residual (average residual and / or maximum residual): when the flow field iteration residual drops by a certain amount (or reaches a preset standard), the flow field iteration converges. Since this method can be used to judge the "time-independent" steady flow field iteration convergence, it can also be used to judge the sub-iteration convergence of unsteady flow field based on virtual time, so it is widely used.

[0003] However, this existing method is not completely suitable for numerical simulation of aerodynamic thermal characteristics of aircraft flow fields. The convergence of flow field iteration residuals usually focuses on the overall convergence characteristics of the main state parameters of the entire flow field, while the aerodynamic thermal characteristics usually focus on the heating conditions of local areas on the surface of the aircraft, such as the gradients of the main state parameters on the surface and its vicinity. Therefore, in engineering, there is often a phenomenon of inconsistency between the convergence of the flow field and the convergence of the aerodynamic thermal characteristics. "The flow field has been judged to have converged (or basically converged), but the aerodynamic thermal characteristics have not yet converged" or "The flow field as a whole has not been judged to have converged, but the aerodynamic thermal characteristics have not changed with iterations and can basically be used for thermal protection engineering." Therefore, it is necessary to develop a method for distinguishing the convergence of aerodynamic thermal characteristics of aircraft flow fields in combination with engineering needs. Summary of the invention

[0004] The purpose of the present invention is to overcome the shortcomings of the prior art and provide a method for judging the convergence of aerodynamic thermal characteristics of an aircraft flow field. Based on the correlation between flow field parameters and aerodynamic thermal characteristics, a weight function is constructed; based on the relative residual of the weighted average of the flow field thermal related parameters, the basic convergence of the flow field is judged; and in combination with the thermal protection characteristics of the aircraft, different methods are used to judge the convergence of aerodynamic thermal characteristics in high heat areas and large-area low heat areas. This method can effectively avoid the phenomenon of inconsistency between the convergence of the flow field and the convergence of the aerodynamic thermal characteristics, while ensuring the accuracy requirements of the aircraft thermal protection project, reducing unnecessary redundant iterations.

[0005] The object of the present invention is achieved through the following solutions:

[0006] A method for determining the convergence of aerodynamic thermal characteristics of an aircraft flow field comprises the following steps:

[0007] Step 1: Numerical iteration preparation;

[0008] Step 2: Flow field iterative feature extraction: During the numerical iteration process, the iterative relative residual of the flow field thermal related parameters is extracted;

[0009] Step 3: Basic convergence of flow field: Based on the correlation between flow field parameters and aerodynamic thermal characteristics, a weight function is constructed, and the average relative residual of the flow field is calculated by weighted average. Numerical iteration is performed until the average relative residual of the flow field is continuously smaller than the preset convergence standard.

[0010] Step 4: Iterative extraction of surface aerodynamic thermal characteristics: On the basis of the basic convergence of the flow field, the aerodynamic thermal characteristics distribution of the aircraft surface is extracted at each interval with a specified number of iteration steps;

[0011] Step 5: Convergence of aerodynamic thermal characteristics of the first hot zone on the surface: numerical iteration is performed until the relative differences of aerodynamic thermal characteristics of all first hot zones are continuously smaller than the preset first hot zone convergence threshold; convergence of aerodynamic thermal characteristics of the second hot zone on the surface: numerical iteration is performed until the absolute differences of aerodynamic thermal characteristics of the second hot zone on the surface are continuously smaller than the preset second hot zone convergence threshold; finally, the numerical simulation is completed to obtain the aerodynamic thermal characteristics.

[0012] Furthermore, in step 1, the numerical iteration preparation includes sub-steps: numerically discretizing the flow control equations on the aircraft flow field calculation grid, setting the initial flow field and boundary conditions, completing the numerical iteration preparation and starting the numerical iteration.

[0013] Furthermore, in step 2, the flow field thermal related parameters are specifically flow field parameters related to aerodynamic thermal characteristics on each grid element in each iteration step.

[0014] Further, in step 3, the continuously being smaller than a preset convergence standard specifically means that as the iteration proceeds, the residual is always smaller than the preset convergence standard.

[0015] Furthermore, in step 4, the number of iteration steps is selected based on the convergence of the numerical simulation of aerodynamic thermal characteristics.

[0016] Further, in step 5, the aerodynamic thermal characteristics of the first hot zone on the surface converge: numerical iteration is performed until the relative differences of the aerodynamic thermal characteristics of all the first hot zones are continuously smaller than the preset first hot zone convergence threshold; and the aerodynamic thermal characteristics of the second hot zone on the surface converge: numerical iteration is performed simultaneously until the absolute differences of the aerodynamic thermal characteristics of the second hot zone on the surface are continuously smaller than the preset second hot zone convergence threshold.

[0017] Furthermore, in step 5, the convergence of aerodynamic thermal characteristics of the first hot zone on the surface is first executed: numerical iteration is performed until the relative differences of aerodynamic thermal characteristics of all first hot zones are continuously smaller than a preset first hot zone convergence threshold; and then the convergence of aerodynamic thermal characteristics of the second hot zone on the surface is executed: numerical iteration is performed until the absolute differences of aerodynamic thermal characteristics of the second hot zone on the surface are continuously smaller than a preset second hot zone convergence threshold, and the two are performed simultaneously.

[0018] Furthermore, the first heat zone is a high heat zone, and the second heat zone is a low heat zone; wherein the high heat zone and the low heat zone are both empirically set.

[0019] Furthermore, in step 5, completing the numerical simulation and obtaining the aerodynamic thermal characteristics specifically includes the sub-steps of: terminating the numerical iteration, outputting or calculating various iteration curves, flow field parameter distributions and aerodynamic thermal characteristics data for use in aircraft thermal protection design and evaluation.

[0020] Furthermore, the selection range of the specified number of iteration steps is between 1000 and 10000.

[0021] The beneficial effects of the present invention include:

[0022] When extracting iterative features of the flow field, the present invention mainly targets the heat-related parameters of the flow field and focuses on their correlation with aerodynamic thermal characteristics, which can effectively avoid unnecessary calculations and analyses.

[0023] The present invention adopts iterative relative residual when extracting iterative features of the flow field, which can effectively avoid the masking of tiny iterative fluctuations, thereby improving the accuracy of iterative feature extraction.

[0024] When calculating the average relative residual of the flow field of the present invention, the differences in the effects of different regions of the flow field on the thermal characteristics of the aircraft surface, the differences in the action mechanism and composition of the aerodynamic thermal characteristics are taken into account in the weight function, which can effectively avoid the phenomenon of inconsistency between the convergence of the flow field and the convergence of the aerodynamic thermal characteristics.

[0025] When judging the convergence of aerodynamic thermal characteristics, the present invention adopts different convergence judgment methods in high-heat areas and large-area low-heat areas, fully considering the characteristics of aircraft aerodynamic thermal protection, which can not only ensure the calculation accuracy required by thermal protection engineering, but also reduce unnecessary redundant iterations.

[0026] The method proposed in the present invention has good universality. Applicable fluids include but are not limited to the Earth's atmosphere, Martian gas, high-temperature combustion gas or pyrolysis gas, etc.; applicable gas models include but are not limited to complete gas model, equilibrium gas model, high-temperature chemical non-equilibrium gas model, thermodynamic non-equilibrium gas model, thermochemical non-equilibrium gas model; applicable grids include but are not limited to one-dimensional / two-dimensional / three-dimensional structured grids, unstructured grids, Cartesian grids and hybrid grids, etc.; applicable aircraft include but are not limited to subsonic, transonic, supersonic and hypersonic aircraft. BRIEF DESCRIPTION OF THE DRAWINGS

[0027] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative labor.

[0028] Figure 1 is the weighted average residual convergence curve of the flow field;

[0029] Figure 2 Heat flow distribution in the high-heat area of ​​the head;

[0030] Figure 3 To calculate the characteristic heat flux and compare it with the flight test results. DETAILED DESCRIPTION

[0031] All features disclosed in all embodiments in this specification, or steps in all methods or processes implicitly disclosed, except for mutually exclusive features and / or steps, can be combined and / or expanded or replaced in any manner.

[0032] The specific implementation process and physical basis of the present invention are described below, and the present invention includes but is not limited to the following implementation modes:

[0033] The present invention provides a method for determining the convergence of aerodynamic thermal characteristics of an aircraft flow field, comprising the following steps:

[0034] Step 1: Preparation for numerical iteration: On the aircraft flow field calculation grid, numerically discretize the flow control equations, set the initial flow field and boundary conditions, complete the preparation for numerical iteration and start the numerical iteration.

[0035] In a further embodiment, step 1 is described in detail as follows:

[0036] The basic principles and implementation methods of computational grid generation, discretization of flow control equations on grid elements, setting of initial flow field and boundary conditions, iterative solution of flow control equations, etc. are introduced in detail in many public documents. The present invention can be directly applied and can be well applicable.

[0037] Here, only examples are given for brief description, and the present invention is applicable to these disclosed methods, but is not limited thereto:

[0038] Numerical iteration to solve the flow control equations is a common method for numerical simulation of aircraft flow fields. Here, we take the three-dimensional complete gas viscous flow control Navier-Stokes (NS) equations commonly used in engineering as an example to briefly introduce them. The dimensionless conservation integral form can be written as:

[0039] ;

[0040] Among them, Q is the conserved quantity vector, t is time, F and Fv are the convection flux and diffusion flux respectively, is the source term, is the grid integration area, is the Reynolds number, dV is the volume integral differential element, and ds is the area integral differential element.

[0041] The numerical iterative solution of the flow control equation is usually performed on the discretized flow field grid elements. According to the different shapes of the aircraft and the flight conditions, the space near the aircraft is divided into continuous space elements (or area elements) according to a certain density. This is the flow field grid and its grid elements, which are the basis of numerical simulation of the aircraft flow field. There are many types of flow field grids, which can generally be divided into structured grids, unstructured grids, Cartesian grids, nested grids or hybrid grids of the above grids. There are also many methods for generating flow field grids, which can be generated by professional grid software (such as Gridgen, PointWise, Gridstar, etc.), or by direct algebra or geometric generation methods. These grid types and generation methods can be obtained through public channels, and the present invention can be well applied.

[0042] The spatial discretization of the flow control equations may adopt but is not limited to Reo, AUSM, HLLE, TVD, Vanleer, Steger-Warming and other formats; the time discretization may adopt but is not limited to LU-SGS, ADI, RK, SSOR and other formats. These formats can be obtained through public channels and will not be elaborated in detail in the present invention.

[0043] The initial flow field can be generated by flight incoming flow, or other flight state results can be reused; boundary condition settings can include but are not limited to incoming flow conditions and wall condition setting methods. The above methods can be obtained through public channels, and the present invention will not be described in detail. The focus of the present invention is to construct a method for determining the convergence of aerodynamic thermal characteristics of an aircraft flow field based on the numerical iteration process and characteristics.

[0044] Step 2: Flow field iterative feature extraction: During the numerical iteration process, extract the iterative relative residual of the "flow field parameters related to aerodynamic thermal characteristics (hereinafter referred to as flow field thermal related parameters)" on each grid element at each iteration step , where n represents the nth iteration step, i represents the i-th spatial grid element, and s represents the s-th flow field parameter related to the aerodynamic thermal characteristics.

[0045] The selection of "flow field thermal related parameters" focuses on their correlation with aerodynamic thermal characteristics, and is closely related to the calculation model used in numerical simulation. There are many options, and the present invention includes these options but is not limited to them. For example: when simulating the aerodynamic thermal characteristics of a complete gas, the flow field thermal related parameters may include but are not limited to gas temperature, thermal conductivity coefficient, etc.; when simulating the aerodynamic thermal characteristics of a chemically non-equilibrium gas, the flow field thermal related parameters may include but are not limited to gas temperature, thermal conductivity coefficient, gas components (or chemical enthalpy of a mixed gas), component diffusion coefficient, etc.; when simulating the aerodynamic thermal characteristics of a thermochemically non-equilibrium gas, the flow field thermal related parameters may include but are not limited to gas translational temperature, vibrational temperature, electron temperature, thermal conductivity coefficient, gas components (or chemical enthalpy of a mixed gas), component diffusion coefficient, etc.

[0046] There are many ways to calculate the iterative relative residual of the "flow field thermal related parameters", one of which is taken as an example here. The present invention includes this method but is not limited to it:

[0047]

[0048] Among them, max is a function, which means taking the maximum value in the brackets. and are the n-step and n-1-step iteration values ​​of the ith grid element and the s-th flow field thermal related parameters, respectively; is a small positive number artificially set for the sth flow field thermal related parameter to prevent the denominator of the above formula from being zero and causing calculation failure. The value of The present invention includes the following settings but is not limited to ,here It is the minimum value of the range of the thermal related parameters of the sth flow field.

[0049] In a further embodiment, step 2 is described in detail as follows:

[0050] There are many types and expressions of residuals of numerical iteration. From the parameter classification, there are: residuals of conserved variables (such as momentum residuals, energy residuals, etc.), residuals of original variables (such as pressure, temperature, density, velocity, etc.) and residuals of aerodynamic characteristics calculated based on flow field parameter distribution (such as lift coefficient residuals, drag coefficient residuals, pitch moment residuals, etc.); from the perspective of dimensions, there are: dimensionless relative residuals and dimensioned absolute residuals; from the perspective of statistics, there are: average residuals (such as arithmetic mean residuals, geometric mean residuals, etc.), extreme value residuals (such as maximum residuals, etc.).

[0051] When extracting iterative features of the flow field, the present invention mainly targets "flow field thermal related parameters" and focuses on their correlation with aerodynamic thermal characteristics, thereby effectively avoiding unnecessary calculations and analyses. The selection of "flow field thermal related parameters" must match the engineering requirements of aerodynamic thermal characteristics and the calculation model used in numerical simulation. Different calculation models and different engineering requirements of aerodynamic thermal characteristics may consider different "flow field thermal related parameters", and the present invention is compatible with these models or requirements.

[0052] Since the absolute values ​​of "flow field thermal related parameters" on different flow field micro-elements may have order of magnitude differences, if the dimensioned absolute residual is directly used, the small iterative fluctuations may be concealed during weighted calculation. The iterative relative residual is used during feature extraction in the present invention to characterize the iterative changes of "flow field thermal related parameters" on different flow field micro-elements relative to themselves, which can effectively avoid the small iterative fluctuations from being concealed, thereby improving the accuracy of iterative feature extraction.

[0053] Step 3: Basic convergence of flow field: During the numerical iteration process, a weight function is constructed based on the correlation between flow field parameters and aerodynamic thermal characteristics. , the weighted average calculation is used to obtain the average relative residual of the flow field at the nth iteration ; Numerical iteration to Continuously less than the preset convergence standard When , the flow field basically converges; here “continuously smaller than the preset convergence standard” means that as the iteration proceeds, the residual is always smaller than the preset convergence standard.

[0054] Weight function It is mainly constructed based on the correlation between flow field parameters and aerodynamic thermal characteristics, and is used to characterize the comprehensive influence of the sth flow field thermal related parameters of the i-th grid microelement on the aerodynamic thermal characteristics. There are many construction methods, and the present invention includes the following methods but is not limited to them:

[0055]

[0056] in, is the shortest distance from the ith grid element to the surface of the aircraft; Characterize the characteristic scale of the flow field that affects the aerodynamic thermal characteristics. Since the aerodynamic thermal characteristics are mainly affected by the distribution of the wall boundary layer parameters, Taken as the characteristic thickness of the boundary layer; is the influencing factor of the sth flow field thermal-related parameter on the aerodynamic thermal characteristics, which is determined by the calculation model used in the numerical simulation and the aerodynamic thermal characteristics required by the engineering.

[0057] Convergence criteria It can be set in combination with specific numerical simulation working conditions. There are many setting methods. The present invention provides one of them but is not limited to this: .here is the magnitude of the average relative residual decrease, it is recommended ; is the average relative residual of the flow field in the first step iteration, that is .

[0058] In a further embodiment, step 3 is described in detail as follows:

[0059] The influence of different flow field areas on the thermal characteristics of the aircraft surface is different, which is related to many factors such as the type of flow, the distance to the surface, the upstream and downstream relationship, etc., but generally speaking, there is the following rule: the aerodynamic thermal characteristics of the aircraft surface are mainly affected by the distribution of the wall boundary layer parameters, and the closer to the aircraft surface, the more significant the influence; in the area far from the wall boundary layer, the change of flow field parameters has a relatively small impact on the surface thermal characteristics, and the farther away from the aircraft surface, the smaller the impact. Therefore, the construction of the weight function can take into account the characteristic that "the closer the grid element is to the wall, the greater its influence weight". The example method of the present invention uses to express this feature.

[0060] The mechanism and composition of the aerodynamic thermal characteristics of aircraft vary from one project to another and from one simulation method to another. For example, for conditions with relatively low flight speeds, if a full gas numerical simulation of the aerodynamic thermal characteristics of an aircraft is used, the thermal conduction mechanism of temperature is mainly considered; while for conditions with relatively high flight speeds, if a high-temperature non-equilibrium gas is used to simulate the aerodynamic thermal characteristics of an aircraft, in addition to the thermal conduction mechanism of temperature, chemical reaction endothermic / heat-proof mechanisms may also need to be considered. Different mechanisms have different strengths, and the degree of influence of their flow field thermal-related parameters on the aerodynamic thermal characteristics is also different. Therefore, the weight function can be set in combination with the calculation model used in the numerical simulation and the composition of the aerodynamic thermal characteristics required by the project. The weight function used in the example method of the present invention is to express this feature.

[0061] Different calculation methods, grids and flight conditions have different reduction ranges of numerical iteration residuals. For example, in complex flight conditions, when the calculation format has low dissipation and the grid quality is poor, the numerical iteration residual may only drop by 2 to 3 orders of magnitude; while in simple conditions, when the calculation format has high dissipation and the grid quality is good, the numerical iteration residual may drop by more than 10 orders of magnitude. Since step 3 is only a judgment of the basic convergence of the flow field, usually when the residual drops by 2 to 6 orders of magnitude, the main flow field structures are basically formed or basically stable, so the convergence standard of the present invention is Recommended when setting .

[0062] Step 4: Iterative extraction of surface aerodynamic thermal characteristics: On the basis of the basic convergence of the flow field, continue numerical iteration, specify the number of iteration steps D at each interval, and extract the aerodynamic thermal characteristics of the aircraft surface calculated from the flow field parameter distribution. Distribution, where n represents the nth iteration and j represents the jth surface mesh element.

[0063] The selection of the specified iteration step number D must be selected in combination with the specific convergence of the numerical simulation of aerodynamic thermal characteristics. The present invention provides a parameter recommended range of D but is not limited thereto: D=1000~10000;

[0064] In a further embodiment, step 4 is described in detail as follows:

[0065] There are differences in the aerodynamic thermal characteristic parameters that are of interest in different working conditions or projects, and common ones include surface heat flux, heat transfer coefficient, Stanton number, etc. The present invention can target one of the parameters or multiple parameters and their combinations.

[0066] There are many factors that affect the convergence of aerodynamic thermal characteristics of aircraft flow fields, including grids, numerical formats, simulation conditions, model complexity, etc. Its convergence is relatively slow, and usually requires thousands or even hundreds of thousands of iterations to converge. Since the calculation of aerodynamic thermal characteristics requires additional computational overhead, and the changes in aerodynamic thermal characteristics are generally slow after the flow field has basically converged, extracting the surface aerodynamic thermal characteristics at certain intervals of iteration can not only reduce the computational overhead, but also relatively clearly obtain the changing trend of aerodynamic thermal characteristics within a longer iteration interval.

[0067] Step 5: Convergence of aerodynamic thermal characteristics in high heat area on the surface: During the numerical iteration process, for each high heat area, when the relative difference of aerodynamic thermal characteristics at intervals of D iteration steps is continuously less than When , the aerodynamic thermal characteristics of the high heat flow area converge; numerical iteration is performed until the aerodynamic thermal characteristics of all high heat areas converge; here It is the preset high-heat zone convergence threshold, which is determined by the accuracy requirement of the surface aerodynamic thermal characteristics prediction; “continuously less than” means that as the iteration proceeds, it is always less than the preset convergence threshold.

[0068] There are many methods for identifying the high heat area on the aircraft surface. These methods can be used alone or in combination. The present invention provides two methods but is not limited to them:

[0069] (1) Surface aerodynamic thermal characteristics Greater than The area is a high-heat area. It is the preset high heat zone threshold, which is determined by the specific heat protection engineering design;

[0070] (2) Based on the aerodynamic heating characteristics, directly specify the high heat area, such as the head high heat area, the leading edge high heat area of ​​the flight wing / rudder, the leading edge high heat area of ​​the platform, the inlet lip high heat area, the windward convex surface high heat area, etc.

[0071] For each high-heat zone, the relative difference of the aerodynamic thermal characteristics at intervals of D iteration steps can be calculated using a variety of methods, which can be used alone or in combination. The present invention provides three of the methods but is not limited thereto:

[0072] (1) Peak method:

[0073]

[0074] (2) Area-weighted average method:

[0075]

[0076] (3) Extended area-weighted average method:

[0077]

[0078] here , , are the relative differences of the peak value, area-weighted average, and extended area-weighted average of the aerodynamic thermal characteristics in the high-heat zone, is the area of ​​the jth surface element; and Take the maximum values ​​of the corresponding parameters in the high-heat area of ​​the nth step and the nDth step respectively; and The corresponding parameters in the high-heat area of ​​the nth step and the nDth step are accumulated respectively; To accumulate the corresponding parameters of the union area of ​​the high heat areas of the nth step and the nDth step.

[0079] In a further embodiment, step 5 is described in detail as follows:

[0080] The higher the temperature or heat flow, the greater the cost of heat protection. The high heat zone is the focus and difficulty of the aircraft thermal protection system design, and its prediction accuracy directly determines the redundancy range of the aerodynamic thermal protection system. Since the peak value, mean value and relative error range of the surface aerodynamic thermal characteristics are usually concerned when designing the redundancy of the aerodynamic thermal protection system, the present invention focuses on the numerical convergence of the relative difference of the peak value / mean value of the aerodynamic thermal characteristics in the high heat zone.

[0081] The aerodynamic thermal characteristics of large-area low-heat areas on the surface converge: During the numerical iteration process, for large-area low-heat areas, the absolute difference of the aerodynamic thermal characteristics of the numerical iteration interval D iteration steps is continuously less than , its aerodynamic thermal characteristics converge; here It is the preset low heat zone convergence threshold, which is determined by the thermal protection engineering requirements; “continuously less than” means that as the iteration proceeds, it is always less than the preset convergence threshold; the large area low heat zone is the surface area of ​​the aircraft excluding the high heat zone.

[0082] For a large area of ​​low heat zone, the absolute difference of aerodynamic thermal characteristics at intervals of D iteration steps can be calculated by a variety of methods, which can be used alone or in combination. The present invention provides three of the methods but is not limited thereto:

[0083] (1) Maximum method:

[0084]

[0085] (2) Area-weighted average method:

[0086]

[0087] (3) Extended area-weighted average method:

[0088]

[0089] here , They are the maximum value, area-weighted average, and extended area-weighted average of the absolute difference of aerodynamic thermal characteristics in the low-heat zone, respectively. is the area of ​​the jth surface element; To take the maximum value of the corresponding parameter in the union area of ​​the low heat area of ​​the nth step and the nDth step; and The corresponding parameters in the low-heat area of ​​the nth step and the nDth step are accumulated respectively; To accumulate the corresponding parameters in the union area of ​​the low-heat areas of the nth step and the nDth step.

[0090] In a further embodiment, the details are as follows:

[0091] In low-heat areas, the difficulty of thermal protection design is relatively low, and the engineering accuracy requirements are relatively low. We often focus on whether the local aerodynamic thermal characteristics are within the tolerance range of a certain type of thermal protection material. For example, in areas with low surface heat flux, assuming that the heat flux predicted by the aerodynamic thermal characteristics of the flow field is 100W / m 2 With 0.1W / m 2 Although the values ​​of the two span three orders of magnitude and the relative difference reaches 1000 times, they may not have practical significance for aircraft thermal protection engineering design, because conventional thermal protection materials can easily achieve thermal protection in this heat flow range. Therefore, when judging the convergence of aerodynamic thermal characteristics in a large area of ​​low heat area on the surface, the present invention uses the absolute difference of aerodynamic thermal characteristics and combines it with the requirements of thermal protection engineering to reduce meaningless redundant calculations.

[0092] After completing the numerical simulation, the aerodynamic thermal characteristics are obtained. After the numerical iteration is terminated, various iterative curves and the distribution of various flow field parameters are obtained. Based on the parameter distribution of the flow field, the aerodynamic thermal characteristics data that can be used for the thermal protection design of the aircraft are calculated.

[0093] Application effect example description:

[0094] Here, the numerical simulation of the aerodynamic thermal environment of a super Electre blunt cone is taken as an example to illustrate the application effect of the present invention. The present invention can be used in this working condition, but is not limited to this working condition.

[0095] The Electre blunt cone is about 2m long, with a head radius of 0.175m and a body semi-cone angle of The numerical simulation conditions are as follows: Mach number 13.0, speed 4230m / s, incoming gas density 0.0006944kg / m3, incoming gas pressure 53Pa, incoming gas temperature 265K, flight angle of attack 20 degrees, and surface catalytic conditions using non-catalytic (NCW) and fully catalytic conditions (FCW).

[0096] Figure 1 The weighted average residual convergence curve of the flow field is given. It can be seen that when the iteration steps are about 8000, the flow field basically converges (here the average relative residual decreases by an order of magnitude of d=3). Figure 2 and Figure 3 The heat flow cloud diagram and characteristic heat flow line diagram calculated by the present invention are given respectively, where FCW is the simulation result of the catalytic wall, NCW is the non-catalytic simulation result, and Flight data is the flight test measurement result. It can be seen that the heat flow distribution of the head is smooth, without abnormal fluctuations, which conforms to the heat flow distribution law of the stagnation point area of ​​the ball head; the characteristic heat flow is in good agreement with the test. The above results all illustrate the effectiveness of the calculation convergence judgment of the present invention.

[0097] The above description is only the technical principle and preferred embodiment used in the present invention. It will be understood by those skilled in the art that the present invention is not limited to the specific embodiments described herein. It is possible for those skilled in the art to make various obvious changes, adjustments and substitutions without departing from the scope of protection of the present invention. Therefore, although the present invention has been described in more detail through the above embodiments, the present invention is not limited to the above embodiments, and may also include more other equivalent embodiments without departing from the principles and concepts of the present invention, and the scope of the present invention is determined by the scope of the appended claims.

Claims

1. A method for determining the convergence of aerodynamic thermal characteristics of an aircraft flow field, characterized in that: The following steps are involved: Step 1: Numerical iteration preparation; Step 2: Flow field iterative feature extraction: During the numerical iteration process, the iterative relative residual of the flow field thermal related parameters is extracted; Step 3: Basic convergence of flow field: Based on the correlation between flow field parameters and aerodynamic thermal characteristics, a weight function is constructed, and the average relative residual of the flow field is calculated by weighted average. Numerical iteration is performed until the average relative residual of the flow field is continuously smaller than the preset convergence standard. Step 4: Iterative extraction of surface aerodynamic thermal characteristics: On the basis of the basic convergence of the flow field, the aerodynamic thermal characteristics distribution of the aircraft surface is extracted at each interval with a specified number of iteration steps; Step 5: Convergence of aerodynamic thermal characteristics of the first hot zone on the surface: numerical iteration is performed until the relative differences of aerodynamic thermal characteristics of all first hot zones are continuously smaller than the preset first hot zone convergence threshold; convergence of aerodynamic thermal characteristics of the second hot zone on the surface: numerical iteration is performed until the absolute differences of aerodynamic thermal characteristics of the second hot zone on the surface are continuously smaller than the preset second hot zone convergence threshold; finally, the numerical simulation is completed to obtain the aerodynamic thermal characteristics.

2. The method for determining the convergence of aerodynamic thermal characteristics of an aircraft flow field according to claim 1, characterized in that: In step 1, the numerical iteration preparation includes sub-steps: numerically discretizing the flow control equations on the aircraft flow field calculation grid, setting the initial flow field and boundary conditions, completing the numerical iteration preparation and starting the numerical iteration.

3. The method for determining the convergence of aerodynamic thermal characteristics of an aircraft flow field according to claim 1, characterized in that: In step 2, the flow field thermal related parameters are specifically flow field parameters related to aerodynamic thermal characteristics on each grid element in each iteration step.

4. The method for determining the convergence of aerodynamic thermal characteristics of an aircraft flow field according to claim 1, characterized in that: In step 3, the continuously smaller than the preset convergence standard specifically means that as the iteration proceeds, the residual is always smaller than the preset convergence standard.

5. The method for determining the convergence of aerodynamic thermal characteristics of an aircraft flow field according to claim 1, characterized in that: In step 4, the number of iteration steps is selected based on the convergence of the numerical simulation of the aerodynamic thermal characteristics.

6. The method for determining the convergence of aerodynamic thermal characteristics of an aircraft flow field according to claim 1, characterized in that: In step 5, the aerodynamic thermal characteristics of the first hot zone on the surface converge: numerical iteration is performed until the relative differences of the aerodynamic thermal characteristics of all the first hot zones are continuously smaller than the preset first hot zone convergence threshold; and the aerodynamic thermal characteristics of the second hot zone on the surface converge: numerical iteration is performed simultaneously until the absolute differences of the aerodynamic thermal characteristics of the second hot zone on the surface are continuously smaller than the preset second hot zone convergence threshold.

7. The method for determining the convergence of aerodynamic thermal characteristics of an aircraft flow field according to claim 1, characterized in that: In step 5, the convergence of aerodynamic thermal characteristics of the first hot zone on the surface is first performed: numerical iteration is performed until the relative differences of aerodynamic thermal characteristics of all first hot zones are continuously smaller than the preset first hot zone convergence threshold; and then the convergence of aerodynamic thermal characteristics of the second hot zone on the surface is performed: numerical iteration is performed until the absolute differences of aerodynamic thermal characteristics of the second hot zone on the surface are continuously smaller than the preset second hot zone convergence threshold at the same time.

8. The method for determining the convergence of aerodynamic thermal characteristics of an aircraft flow field according to any one of claims 6 or 7, characterized in that: The first heat zone is a high heat zone, and the second heat zone is a low heat zone; wherein, the high heat zone and the low heat zone are both set based on experience.

9. The method for determining the convergence of aerodynamic thermal characteristics of an aircraft flow field according to claim 1, characterized in that: In step 5, the completion of the numerical simulation to obtain the aerodynamic thermal characteristics specifically includes the sub-steps of: terminating the numerical iteration, outputting or calculating various iteration curves, flow field parameter distributions and aerodynamic thermal characteristics data for use in aircraft thermal protection design and evaluation.

10. The method for determining the convergence of aerodynamic thermal characteristics of an aircraft flow field according to claim 5, characterized in that: The selection range of the specified number of iteration steps is between 1000 and 10000.

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