Method, device and apparatus for predicting combustion chamber flame tube life

Abstract

The present invention relates to the technical field of aero-engines and discloses a method for predicting the life of a combustion chamber flame liner. The method comprises: performing an ablation simulation test on the combustion chamber flame liner based on a combustion chamber computational fluid dynamics model to obtain an ablation life prediction model; performing a creep test on a flame liner simulation component based on a flame liner test load spectrum to obtain a creep life prediction model; performing a low-cycle fatigue test on the flame liner simulation component based on the flame liner test load spectrum to obtain a low-cycle fatigue life prediction model; performing a thermal shock test on the flame liner simulation component based on the flame liner test load spectrum to obtain a thermal shock life prediction model; applying different calculation weights to the ablation life prediction model, the creep life prediction model, the low-cycle fatigue life prediction model, and the thermal shock life prediction model to establish a flame liner life prediction model, and predicting the flame liner life with high accuracy using the flame liner life prediction model.

Description

Technical Field

[0001] The present invention relates to the technical field of aviation engines, and in particular to a method, a device and equipment for predicting the life of a combustion chamber flame tube. Background Art

[0002] The combustion chamber flame tube is the place where combustion is organized in aircraft engines. It is exposed to high-temperature and high-pressure gas. The gas temperature is above 2000K and the pressure exceeds 30 atmospheres. It also has to withstand high thermal stress and vibration loads. The working environment is extremely harsh. Therefore, the flame tube is one of the components with the shortest lifespan of aircraft engines.

[0003] The combustion chamber flame tube life prediction method in the related art attributes the cause of combustion chamber flame tube failure to low cycle fatigue, which is inconsistent with the actual working environment of the combustion chamber, making the combustion chamber flame tube life prediction method low in accuracy. Summary of the Invention

[0004] In view of this, the present invention provides a method, device and equipment for predicting the life of a combustion chamber flame tube, so as to solve the problem that the accuracy of the method for predicting the life of a combustion chamber flame tube is not high.

[0005] In a first aspect, the present invention provides a method for predicting the life of a combustion chamber flame tube, the method comprising: performing an ablation simulation test on the combustion chamber flame tube based on a computational fluid dynamics model of the combustion chamber to obtain an ablation life prediction model of the flame tube; performing a creep test on the flame tube simulation component based on a flame tube test load spectrum to obtain a creep life prediction model of the flame tube; performing a low cycle fatigue test on the flame tube simulation component based on the flame tube test load spectrum to obtain a low cycle fatigue life prediction model of the flame tube; performing a thermal shock test on the flame tube simulation component based on the flame tube test load spectrum to obtain a thermal shock life prediction model of the flame tube; applying different calculation weights to the ablation life prediction model, the creep life prediction model, the low cycle fatigue life prediction model and the thermal shock life prediction model to establish a flame tube life prediction model, and predicting the flame tube life through the flame tube life prediction model.

[0006] By combining numerical simulation with experimental research, low-cycle fatigue, creep, thermal shock tests on flame tube simulation parts and flame tube ablation simulation research are carried out to explore the calculation method of combustion chamber flame tube life and analyze the failure mode of flame tube under service load, which is closer to the actual working environment of combustion chamber flame tube and has higher prediction accuracy.

[0007] In an optional embodiment, an ablation simulation test is performed on the combustion chamber flame tube to obtain an ablation life prediction model of the flame tube, including: performing high-temperature ablation and particle erosion calculations based on the combustion chamber computational fluid dynamics model to obtain an ablation model; performing three-dimensional non-steady-state calculation iterations based on the ablation model, and predicting the combustion chamber flame tube life through the iterative results.

[0008] Compared with predicting the impact of substrate erosion on flame tube life through observation and testing in actual use, ablation simulation tests can obtain data faster and more conveniently, thereby improving R&D efficiency.

[0009] In an optional embodiment, high-temperature ablation and particle erosion calculations are performed based on the combustion chamber computational fluid dynamics model to obtain an ablation model, including: obtaining the heat flux density of the combustion chamber flow field based on the combustion chamber computational fluid dynamics model, integrating the heat flux density to obtain the ablation rate of the flame tube material; obtaining the erosion rate of the flame tube material through bidirectional coupling calculation of the combustion chamber flow field and particles; linearly superimposing the ablation rate and the erosion rate to obtain the ablation size of the combustion chamber flame tube, and establishing an ablation model based on the ablation size.

[0010] By simultaneously considering the transfer of mass, momentum, and energy between the flow field and particles, bidirectional coupling calculations of the flow field and particles can be realized, which can reflect the erosion effect of high-speed moving particles on the material surface.

[0011] In an optional embodiment, a creep test is performed on a flame tube simulation component based on a flame tube test load spectrum to obtain a creep life prediction model for the flame tube, including: obtaining creep damage generated by the flame tube simulation component for different service temperatures and service loads of each operating condition; linearly accumulating the creep damage to obtain total creep damage; and establishing the creep life prediction model based on the total creep damage, wherein the operating conditions include: slow-running operating condition, take-off operating condition, climb operating condition, and cruise operating condition.

[0012] In an optional embodiment, based on the flame tube test load spectrum, a low-cycle fatigue test is performed on the combustion chamber flame tube simulation component to obtain a low-cycle fatigue life prediction model of the flame tube, including: obtaining the fatigue damage generated by the flame tube simulation component for different total strain amplitudes of each working condition; linearly accumulating the fatigue damage to obtain the total fatigue damage; and establishing the low-cycle fatigue life prediction model based on the total fatigue damage.

[0013] In an optional embodiment, a thermal shock test is performed on a flame tube simulation component based on a flame tube test load spectrum, including: cyclically heating the flame tube simulation component according to preset conditions until cracks appear in the flame tube simulation component; obtaining the relationship between the number of cyclic heating times of the flame tube simulation component and the crack length, and establishing the thermal shock life prediction model.

[0014] In an optional embodiment, obtaining the flame tube test load spectrum includes: obtaining the original load spectrum of the flame tube; identifying the load peak in the original load spectrum, deleting the load spectrum after reaching the load peak in the original load spectrum, and obtaining the flame tube test load spectrum, wherein the task duration of the flame tube test load spectrum is less than the task duration of the original load spectrum.

[0015] The original load spectrum of the aircraft engine was simplified and equivalent, which accelerated the test process and saved test and manpower costs.

[0016] In an optional embodiment, obtaining the computational fluid dynamics model of the combustion chamber includes: obtaining the original load spectrum of the flame tube and the three-dimensional model of the combustion chamber; obtaining the combustion chamber boundary conditions based on the original load spectrum and the three-dimensional model of the combustion chamber; performing numerical simulation on the combustion chamber boundary conditions to obtain the combustion chamber velocity field, the combustion chamber temperature field and the combustion chamber pressure field; establishing the computational fluid dynamics model of the combustion chamber based on the combustion chamber velocity field, the combustion chamber temperature field and the combustion chamber pressure field; wherein the boundary conditions include: combustion chamber inlet boundary conditions, combustion chamber outlet boundary conditions, combustion chamber wall boundary conditions and combustion chamber rotation period boundary conditions.

[0017] By precisely controlling the model parameters and starting conditions through numerical simulation, we can obtain repeatable experimental results and improve the prediction accuracy of the model.

[0018] In a second aspect, the present invention provides a device for predicting the life of a combustion chamber flame tube, the device comprising: a first prediction module, for performing an ablation simulation test on the combustion chamber flame tube based on a combustion chamber computational fluid dynamics model, to obtain an ablation life prediction model of the flame tube; a second prediction module, for performing a creep test on the flame tube simulation component based on a flame tube test load spectrum, to obtain a creep life prediction model of the flame tube; a third prediction module, for performing a low cycle fatigue test on the flame tube simulation component based on the flame tube test load spectrum, to obtain a low cycle fatigue life prediction model of the flame tube; a fourth prediction module, for performing a thermal shock test on the flame tube simulation component based on the flame tube test load spectrum, to obtain a thermal shock life prediction model of the flame tube; a life prediction module, for applying different calculation weights to the ablation life prediction model, the creep life prediction model, the low cycle fatigue life prediction model and the thermal shock life prediction model, to establish a flame tube life prediction model, and to predict the flame tube life through the flame tube life prediction model.

[0019] In a third aspect, the present invention provides a computer device comprising: a memory and a processor, the memory and the processor being communicatively connected to each other, computer instructions being stored in the memory, and the processor executing the method for predicting the life of a combustion chamber flame tube according to the first aspect or any corresponding embodiment thereof by executing the computer instructions.

[0020] By combining numerical simulation with experimental research, low-cycle fatigue, creep, thermal shock tests on flame tube simulation parts and flame tube ablation simulation research are carried out to explore the calculation method of combustion chamber flame tube life and analyze the failure mode of flame tube under service load, which is closer to the actual working environment of combustion chamber flame tube and has higher prediction accuracy. BRIEF DESCRIPTION OF THE DRAWINGS

[0021] In order to more clearly illustrate the specific embodiments of the present invention or the technical solutions in the prior art, the following briefly introduces the drawings required for use in the specific embodiments or the description of the prior art. Obviously, the drawings described below are some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0022] Figure 1 is a flow chart of a method for predicting the life of a combustion chamber flame liner according to an embodiment of the present invention;

[0023] Figure 2 is a schematic diagram of an equivalent and simplified temperature spectrum of a typical mission section of a flame tube load spectrum according to an embodiment of the present invention;

[0024] Figure 3is a flow chart of another method for predicting the life of a combustion chamber flame liner according to an embodiment of the present invention;

[0025] Figure 4 is a structural block diagram of a device for predicting the life of a combustion chamber flame liner according to an embodiment of the present invention;

[0026] Figure 5 Schematic diagram of the hardware structure of a computer device according to an embodiment of the present invention. DETAILED DESCRIPTION

[0027] To make the purpose, technical solutions, and advantages of the embodiments of the present invention more clear, the technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without making creative efforts shall fall within the scope of protection of the present invention.

[0028] With the development of the aviation industry, aircraft engines are gradually developing towards high compression ratio, high turbine inlet temperature, high thrust-to-weight ratio and longer service life. However, the increase in temperature makes the working environment of hot end components such as the combustion chamber increasingly harsh. For example, the failure problem of high-temperature parts such as the combustion chamber flame tube has become a focus of increasing attention.

[0029] Conventional methods for predicting the life of combustor liner typically use finite element analysis of the thermal loads applied to the liner to determine the thermal stress distribution. This is then used to predict the low-cycle fatigue life of the liner using empirical formulas. However, considering only the impact of thermal stress distribution on liner life is inconsistent with the actual operating environment of the combustor, resulting in low prediction accuracy. Currently, there is a lack of high-precision methods for predicting the life of combustor liner.

[0030] According to an embodiment of the present invention, a method embodiment for predicting the life of a combustion chamber flame tube is provided. It should be noted that the steps shown in the flowchart of the accompanying drawings can be executed in a computer system such as a set of computer executable instructions, and although a logical order is shown in the flowchart, in some cases, the steps shown or described can be executed in an order different from that shown here.

[0031] In this embodiment, a method for predicting the life of a combustion chamber flame tube is provided, which can be used in the above-mentioned mobile terminals, such as mobile phones, tablet computers, etc. Figure 1 FIG. 1 is a flow chart of a method for predicting the life of a combustion chamber flame tube according to an embodiment of the present invention. Figure 1 As shown, the process includes the following steps:

[0032] In step S11 , based on a computational fluid dynamics (CFD) model of the combustion chamber, an ablation simulation test is performed on the flame tube of the combustion chamber to obtain an ablation life prediction model of the flame tube.

[0033] In this embodiment, the combustion chamber CFD model can be used to predict the detailed distribution of flow and temperature fields within the combustion chamber. Generally speaking, the original load spectrum data of the flame liner can be input into the combustion chamber CFD model, which then outputs the combustion chamber velocity, temperature, and pressure fields. During the ablation simulation test, the heat flux density of the flame liner can be determined using constraints. Ultimately, the resulting ablation life prediction model can be used to predict the flame liner life during the ablation simulation test.

[0034] In one embodiment, step S11 includes:

[0035] Step S111, obtaining a computational fluid dynamics model of the combustion chamber, includes:

[0036] In this embodiment, the original load spectrum of the flame tube and the three-dimensional model of the combustion chamber are obtained; based on the original load spectrum and the three-dimensional model of the combustion chamber, the combustion chamber boundary conditions are obtained; the combustion chamber boundary conditions are numerically simulated to obtain the combustion chamber velocity field, combustion chamber temperature field and combustion chamber pressure field; based on the combustion chamber velocity field, combustion chamber temperature field and combustion chamber pressure field, a combustion chamber CFD model is established; wherein the boundary conditions include: combustion chamber inlet boundary conditions, combustion chamber outlet boundary conditions, combustion chamber wall boundary conditions and combustion chamber rotation period boundary conditions.

[0037] The combustion chamber boundary conditions include: axial displacement constraint on the front end face of the combustion chamber inlet, and radial constraint release; the combustion chamber outlet end face is freely released; rotational periodic boundary conditions are applied to the cyclic symmetry surface of the combustion chamber sector; and uniform pressure is applied to the combustion chamber wall, as shown in Table 1 below. Table 1 shows the pressure loads on the inner and outer rings of the combustion chamber under different working conditions.

[0038] Table 1 Pressure loads on inner and outer rings of combustion chamber under different working conditions

[0039]

[0040] Step S112: performing an ablation simulation test on the combustion chamber flame tube to obtain an ablation life prediction model of the flame tube.

[0041] Specifically, step S112 includes:

[0042] Step S1121 , based on the combustion chamber computational fluid dynamics model, high temperature ablation and particle erosion calculations are performed to obtain an ablation model.

[0043] High-temperature ablation and particle erosion calculations can be implemented using the Euler-Lagrangian model.

[0044] Step S1121 specifically includes obtaining the heat flux density of the combustion chamber flow field based on the combustion chamber computational fluid dynamics model, integrating the heat flux density, and calculating the ablation rate of the flame tube material. Input variables for the integral calculation include parameters such as the temperature distribution, temperature gradient, heat flux density, and heat flux density gradient of the combustion chamber flow field. These parameters are called and calculated in real time using a user-defined function (UFD).

[0045] The erosion rate of the flame tube material is calculated through a bidirectional coupling calculation of the combustion chamber flow field and particles. The flow field parameters are calculated using an Euler coordinate system, while the motion of discrete particles is calculated using a Lagrangian coordinate system. This allows for the simultaneous consideration of the transfer of mass, momentum, and energy between the flow field and particles. This allows for a bidirectional coupling calculation of the flow field and particles, reflecting the erosive effect of high-speed particles on the material surface, and ultimately, the erosion rate of the flame tube material.

[0046] The ablation rate and erosion rate are linearly superimposed to obtain the ablation size of the combustion chamber flame tube. Based on the ablation size, an ablation model is established. Through data post-processing, following the linear assumption, and using the linear superposition method, the ablation size can be obtained.

[0047] Step S1122: perform three-dimensional unsteady-state calculation iteration based on the ablation model, and predict the life of the combustion chamber flame tube according to the iteration result.

[0048] The ablation model is re-performed with three-dimensional aerodynamic and thermodynamic unsteady-state calculation iterations to obtain iterative results, including: flame tube wall temperature, thermal stress and combustion chamber outlet temperature field. The failure of the combustion chamber flame tube is judged based on the iterative results, and the ablation life prediction model of the combustion chamber flame tube is obtained.

[0049] Step S12: Obtain the flame tube test load spectrum and the flame tube simulation component.

[0050] In this embodiment, the flame liner test load spectrum is a simplified version of the original flame liner load spectrum, encompassing the process of increasing load from low to high in the original load spectrum. The flame liner simulator is an equivalent simulation of an actual flame liner, closely matching the physical properties of the actual flame liner as closely as possible.

[0051] Specifically, step S12 includes:

[0052] Step S121, obtaining a flame tube test load spectrum, including: obtaining an original load spectrum of the flame tube; identifying a load peak in the original load spectrum, deleting the load spectrum after reaching the load peak in the original load spectrum, and obtaining a flame tube test load spectrum, wherein the task duration of the flame tube test load spectrum is less than the task duration of the original load spectrum.

[0053] Specifically, based on the original load spectrum of the flame tube, the flame tube creep test load spectrum, the flame tube low cycle fatigue test load spectrum and the flame tube thermal shock test load spectrum can be obtained.

[0054] Figure 2 This is an equivalent simplification of the temperature spectrum of the typical task section of the flame tube load spectrum provided by the embodiment of the present invention. Figure 2 As shown in the figure, assuming that the task duration of a typical task segment in the original temperature load spectrum is t1, the temperature load spectrum corresponding to t1 is as follows: Figure 2 As shown in the figure, after deleting the small temperature load of the typical task section, the test load spectrum is obtained as follows: Figure 2 As shown in the curve in the trapezoidal box, the task duration of the task segment in the test load spectrum is t2, as shown in Figure 2 As shown, t2 is much smaller than t1.

[0055] In this way, the small loads of the original load spectrum of the flame tube are deleted to obtain the flame tube test load spectrum; the flame tube load spectrum can be simplified and the original load spectrum can be equivalently accelerated, which reduces the consumption of human and material resources in the test stage to a certain extent.

[0056] Step S122, obtaining a flame tube simulation component, includes:

[0057] In step S1221, the flame tube simulation member adopts the same material as the flame tube, and adopts the same material grade and hot and cold process as the flame tube; in this way, the flame tube simulation member and the flame tube have the same fatigue performance.

[0058] Step S1222: The geometric shape of the stress concentration portion of the flame tube simulation part is similar or approximate to that of the flame tube, so that the stress distribution of the flame tube simulation part and the stress concentration portion of the flame tube are close or similar.

[0059] Step S1223, the design temperature of the flame tube simulation is equal to the original flame tube test temperature, the design temperature of the flame tube simulation is equal to the original flame tube working temperature, the temperature value of the stress analysis and life calculation of the flame tube simulation is equal to the flame tube assessment point test temperature, and the temperature value of the stress analysis and life calculation of the flame tube simulation is equal to the flame tube assessment point working temperature.

[0060] Step S13: Based on the flame tube test load spectrum, a creep test is performed on the flame tube simulation component to obtain a creep life prediction model of the flame tube.

[0061] In this embodiment, the flame tube creep test load spectrum is obtained by equivalently deleting the original flame tube load spectrum. Creep testing of a flame tube simulation can be performed to test the plastic deformation of the flame tube simulation under a single stress or under a combined stress.

[0062] In one embodiment, step S13 includes:

[0063] Step S131 : obtaining creep damage generated by the flame tube simulation component for different service temperatures and service loads of each working condition.

[0064] The creep damage of the flame tube simulation component is calculated by fitting the thermal strength parameter comprehensive curve equation through the creep durability performance data of the high-temperature alloy material, and then the creep life trb of the flame tube simulation component under the current working conditions is evaluated.

[0065] The creep rupture performance data of high-temperature alloy materials are fitted with the comprehensive curve equation of thermal strength parameters as shown below

[0066] lg(σ)=a0+a1×P+a2×P 2 +a3×P 3

[0067] in, P=lg(t rb )+b×T, a0, a1, a2, a3 and b are the coefficients of the comprehensive curve equation of thermal intensity parameters, T is Fahrenheit temperature, θ is Celsius temperature, and σ is the service load.

[0068] Under the conditions of known service load and service temperature, the creep life trb of the flame tube simulation under the current working conditions can be obtained by fitting the thermal strength parameter comprehensive curve equation according to the creep rupture performance data of the high-temperature alloy material.

[0069] Step S132: linearly accumulate the creep damage to obtain the total creep damage; based on the total creep damage, establish a creep life prediction model, wherein the flame tube test load spectrum conditions include: slow running condition, take-off condition, climb condition and cruise condition.

[0070] Total creep damage d creep It is calculated by the following formula.

[0071]

[0072] Among them, D i is the creep damage of the simulated component corresponding to the working condition in stage i, t i is the loading time under the i-th stage condition, trb i is the creep life of the flame tube simulation component under the i-th stage working condition.

[0073] Step S15 , performing a low cycle fatigue test on the flame tube simulation component based on the flame tube test load spectrum, and obtaining a low cycle fatigue life prediction model of the flame tube.

[0074] In this embodiment, the original load spectrum of the flame tube is equivalently deleted to obtain the low-cycle fatigue test load spectrum of the flame tube. A low-cycle fatigue test is performed on the flame tube simulation in strain control mode, and data used for fatigue calculation is collected to determine the lifespan of the flame tube simulation that can withstand cyclic fatigue.

[0075] In one embodiment, step S15 includes:

[0076] Step S151 : obtaining fatigue damage generated by the flame tube simulation component for different total strain amplitudes of each working condition.

[0077] Based on the Manson-Coffin formula, the relationship between strain and fatigue life is established, and then the low cycle fatigue life tpl of the flame tube simulation under the current working conditions is evaluated. The Manson-Coffin formula is as follows

[0078]

[0079] Where ε is the total strain amplitude, ε e is the elastic strain amplitude, ε p is the plastic strain amplitude, δ′ f is the fatigue strength coefficient, ε′ f is the fatigue continuation coefficient, d is the fatigue strength index, c is the fatigue continuation index, and E is the Young's modulus.

[0080] Step S152: linearly accumulate the fatigue damage to obtain the total fatigue damage; and establish a low-cycle fatigue life prediction model based on the total fatigue damage.

[0081] Total fatigue damage D fat It is calculated by the following formula.

[0082]

[0083] Among them, N i is the fatigue damage of the simulated component corresponding to the working condition in stage i, n i is the loading time under the i-th stage condition, tpl i is the fatigue life of the flame tube simulation component under the i-th stage working condition.

[0084] Low-cycle fatigue testing was performed on the flame tube simulation, and the fatigue load peak was determined based on the maximum thermal stress of the flame tube. Using a scanning electron microscope (SEM) and XRD diffractometer, the microstructure of the flame tube simulation that had not undergone low-cycle fatigue testing was analyzed to obtain the original microstructure of the flame tube simulation. At the same time, the original microstructure of one flame tube simulation after fatigue testing under each low-cycle fatigue test spectrum was observed, which allowed the damage mechanism of the flame tube material under low-cycle fatigue loads to be explored. In this way, by comparing the test life of the flame tube simulation under the original load spectrum and the test load spectrum, the damage equivalence of the flame tube test load spectrum can be verified.

[0085] Step S17: Based on the flame tube test load spectrum, a thermal shock test is performed on the flame tube simulation component to obtain a thermal shock life prediction model for the flame tube.

[0086] In this embodiment, the flame tube thermal shock test load spectrum is obtained by equivalently deleting the original flame tube load spectrum. A thermal shock test is performed on the flame tube simulation to evaluate the adaptability of the flame tube simulation to rapid changes in ambient temperature.

[0087] In one embodiment, step S17 includes:

[0088] Step S171: Cyclic heating is performed on the flame tube simulation according to preset conditions until cracks appear in the flame tube simulation. The relationship between the number of cyclic heating cycles and the crack length of the flame tube simulation is obtained, and a thermal shock life prediction model is established. The preset conditions limit the ambient temperature of the flame tube simulation.

[0089] Use a resistance wire high-temperature furnace to heat the flame tube simulation to the preset temperature and keep it warm for 30 seconds. Then quickly insert it into distilled water at room temperature, cool it for 30 seconds, then take out the flame tube simulation and put it into the high-temperature furnace again to heat it, starting the next heating cycle, and repeating the cycle.

[0090] The thermal shock test temperature is consistent with the thermal shock test temperature cycle of the flame tube material, and thermal fatigue tests are carried out on the flame tube simulation parts under several different thermal fatigue temperature cycles. During the test, after cracks appear on the flame tube simulation parts, the flame tube simulation parts are removed every 100 thermal shock cycles, and the relationship between the crack length of the flame tube simulation parts and the number of thermal shock cycles is recorded to obtain the thermal shock life prediction model of the flame tube.

[0091] Using SEM and XRD diffractometers, the microstructure of the flame tube simulation before thermal shock testing was analyzed to obtain the original microstructure of the flame tube simulation. Microstructure analysis was also performed on one flame tube simulation after each temperature cycle thermal shock test. This allowed the damage mechanism of the flame tube simulation under temperature load cycles to be determined, revealing the failure mode of the flame tube simulation under thermal shock testing.

[0092] Step S19 : Applying different calculation weights to the ablation life prediction model, the creep life prediction model, the low-cycle fatigue life prediction model, and the thermal shock life prediction model to establish a flame liner life prediction model. The flame liner life prediction model is used to predict the flame liner life. The calculation weights are determined based on corresponding experiments.

[0093] Specifically, the calculation weight of the ablation prediction model is determined according to the ablation simulation test; the calculation weight of the creep life prediction model is determined according to the creep test; the calculation weight of the low cycle fatigue life prediction model is determined according to the low cycle fatigue test; and the calculation weight of the thermal shock life prediction model is determined according to the thermal shock test.

[0094] Total damage D under temperature-stress combined service load total =∑D C , where D C is the damage under each temperature-stress combination service load cycle, D C =D fat +D creep , when the total damage D total When the accumulation reaches 1, the flame tube material will fail and the flame tube life will be shortened.

[0095] Furthermore, a flame tube simulation was tested according to the flame tube low-cycle fatigue test load spectrum. During the test, thermocouples were installed on the outer wall of the flame tube simulation to obtain accurate wall temperature. The crack propagation and ablation patterns inside the flame tube were monitored for a preset period of time, and the flame tube ablation behavior under real gas operating conditions was obtained. This can be used to modify the flame tube ablation life prediction model.

[0096] The method for predicting the life of a combustion chamber flame tube provided in this embodiment adopts a method that combines numerical simulation and experimental research. By conducting low-cycle fatigue, creep, thermal shock tests on flame tube simulation parts and flame tube ablation simulation research, etc., it explores the calculation method of the combustion chamber flame tube life and analyzes the failure mode of the flame tube under service load. It is closer to the actual working environment of the combustion chamber flame tube and has a higher prediction accuracy.

[0097] Figure 3 FIG. 1 is a flow chart of another method for predicting the life of a combustion chamber flame tube according to an embodiment of the present invention. Figure 3 As shown in the figure, the life prediction process of the flame tube of the aircraft engine combustion chamber includes:

[0098] Step S31: The combustion chamber boundary conditions are obtained using the original aircraft engine load spectrum and the three-dimensional combustion chamber model. These boundary conditions specifically include the inlet boundary condition, the combustion chamber outlet boundary condition, the combustion chamber wall boundary condition, and the combustion chamber rotation period boundary condition. Based on these boundary conditions, a combustion chamber CFD model and a flame tube ablation model are obtained.

[0099] Step S32: load spectrum research based on the low cycle fatigue test of the full envelope flame tube.

[0100] Step S32.1, finite element analysis of the flame tube stress field.

[0101] Step S32.2: flame tube low cycle fatigue test load spectrum.

[0102] Step S33: creep, low cycle fatigue and thermal shock test research of the flame tube simulation component.

[0103] Step S33.1, flame tube simulation component design.

[0104] Step S33.2: creep test of flame tube simulation component.

[0105] Step S33.3: low cycle fatigue test of the flame tube simulation component.

[0106] Step S33.4, thermal shock test of the flame tube simulation component.

[0107] Step S34, flame tube life calculation and research.

[0108] Step S34.1, study the flame tube material life prediction model under temperature-stress combined characteristic load.

[0109] Step S34.2, experimental study on flame tube material life under temperature-stress combined characteristic load.

[0110] Step S34.3, flame tube life calculation method.

[0111] Step S35: Durability test of the combustion chamber test piece. Please refer to the above text for details, which will not be repeated here.

[0112] This embodiment also provides a device for predicting the life of a combustion chamber flame tube. This device is used to implement the above-mentioned embodiments and preferred embodiments, and details already described will not be repeated. As used below, the term "module" may refer to a combination of software and / or hardware that implements a predetermined function. Although the devices described in the following embodiments are preferably implemented in software, implementation using hardware, or a combination of software and hardware, is also possible and contemplated.

[0113] This embodiment provides a device for predicting the life of a combustion chamber flame tube, such as Figure 4 As shown, including:

[0114] The first prediction module 21 is used to perform an ablation simulation test on the combustion chamber flame tube based on the combustion chamber computational fluid dynamics model to obtain an ablation life prediction model of the flame tube. Please refer to step S11 for details and will not be repeated here.

[0115] Specifically, the first prediction module 21 includes:

[0116] The modeling unit is used to obtain the computational fluid dynamics model of the combustion chamber.

[0117] The first test unit is used to perform an ablation simulation test on the combustion chamber flame tube to obtain an ablation life prediction model of the flame tube.

[0118] The second prediction module 22 is used to perform a creep test on the flame tube simulation component based on the flame tube test load spectrum to obtain a creep life prediction model for the flame tube. Please refer to step S13 for details, which will not be repeated here.

[0119] Specifically, the second prediction module 22 includes:

[0120] The first creep unit is used to obtain the creep damage caused by the flame tube simulation component for different service temperatures and service loads of each working condition.

[0121] The second creep unit is used to linearly accumulate creep damage to obtain total creep damage; based on the total creep damage, a creep life prediction model is established, wherein the flame tube test load spectrum conditions include: slow running condition, take-off condition, climb condition and cruise condition.

[0122] The third prediction module 23 is used to perform a low-cycle fatigue test on the flame tube simulation based on the flame tube test load spectrum to obtain a low-cycle fatigue life prediction model for the flame tube. Please refer to step S15 for details and will not be repeated here.

[0123] Specifically, the third prediction module 23 includes:

[0124] The first fatigue unit is used to obtain the fatigue damage caused by the flame tube simulation component for different total strain amplitudes of each working condition.

[0125] The second fatigue unit is used to linearly accumulate fatigue damage to obtain total fatigue damage; based on the total fatigue damage, a low-cycle fatigue life prediction model is established.

[0126] The fourth prediction module 24 is used to perform a thermal shock test on the flame tube simulation component based on the flame tube test load spectrum to obtain a thermal shock life prediction model for the flame tube. Please refer to step S17 for details and will not be repeated here.

[0127] Specifically, the fourth prediction module 24 includes:

[0128] The first thermal shock unit is used to cyclically heat the flame tube simulation component according to preset conditions until cracks appear on the flame tube simulation component; obtain the relationship between the number of cyclic heating times of the flame tube simulation component and the crack length, and establish a thermal shock life prediction model.

[0129] Life prediction module 25 is used to apply different calculation weights to the ablation life prediction model, creep life prediction model, low-cycle fatigue life prediction model, and thermal shock life prediction model to establish a flame tube life prediction model. The flame tube life prediction model is used to predict the flame tube life. For details, please refer to step S19 and will not be repeated here.

[0130] By combining numerical simulation with experimental research, low-cycle fatigue, creep, thermal shock tests on flame tube simulation parts and flame tube ablation simulation research are carried out to explore the calculation method of combustion chamber flame tube life and analyze the failure mode of flame tube under service load, which is closer to the actual working environment of combustion chamber flame tube and has higher prediction accuracy.

[0131] The further functional description of each of the above modules and units is the same as that of the above corresponding embodiments and will not be repeated here.

[0132] The device for predicting the life of the combustion chamber flame tube in this embodiment is presented in the form of a functional unit, where the unit refers to an ASIC (Application Specific Integrated Circuit) circuit, a processor and memory that executes one or more software or fixed programs, and / or other devices that can provide the above functions.

[0133] The embodiment of the present invention also provides a computer device having the above Figure 4 The device shown is used to predict the life of the combustion chamber flame tube.

[0134] See also Figure 5 , Figure 5 is a structural diagram of a computer device provided by an optional embodiment of the present invention, such as Figure 5 As shown, the computer device includes: one or more processors 10, memory 20, and interfaces for connecting various components, including high-speed interfaces and low-speed interfaces. Various components utilize different buses to communicate with each other and can be installed on a common mainboard or installed in other ways as needed. The processor can process the instructions executed in the computer device, including instructions stored in the memory or on the memory to display the graphical information of the GUI on an external input / output device (such as, a display device coupled to the interface). In some optional embodiments, if necessary, multiple processors and / or multiple buses can be used together with multiple memories and multiple memories. Equally, multiple computer devices can be connected, and each device provides part of the necessary operations (for example, as a server array, a group of blade servers, or a multi-processor system). Figure 5 A processor 10 is taken as an example.

[0135] The processor 10 may be a central processing unit, a network processor, or a combination thereof. The processor 10 may further include a hardware chip. The hardware chip may be an application-specific integrated circuit, a programmable logic device, or a combination thereof. The programmable logic device may be a complex programmable logic device, a field programmable gate array, a general purpose array logic, or any combination thereof.

[0136] The memory 20 stores instructions that can be executed by at least one processor 10, so that the at least one processor 10 executes the method shown in the above embodiment.

[0137] The memory 20 may include a program storage area and a data storage area, wherein the program storage area may store an operating system and application programs required for at least one function; the data storage area may store data created based on the use of the computer device, etc. In addition, the memory 20 may include a high-speed random access memory, and may also include a non-transient memory, such as at least one disk storage device, a flash memory device, or other non-transient solid-state storage device. In some optional embodiments, the memory 20 may optionally include a memory remotely located relative to the processor 10, and these remote memories may be connected to the computer device via a network. Examples of the above-mentioned network include, but are not limited to, the Internet, an intranet, a local area network, a mobile communication network, and combinations thereof.

[0138] The memory 20 may include a volatile memory, such as a random access memory; the memory may also include a non-volatile memory, such as a flash memory, a hard disk or a solid-state drive; the memory 20 may also include a combination of the above types of memory.

[0139] The computer device also includes an input device 30 and an output device 40. The processor 10, the memory 20, the input device 30 and the output device 20 can be connected via a bus or other means. Figure 5 The bus connection is taken as an example.

[0140] The input device 30 can receive input digital or character information and generate key signal input related to user settings and function control of the computer device, such as a touch screen, a keypad, a mouse, a trackpad, a touch pad, an indicator stick, one or more mouse buttons, a trackball, a joystick, etc. The output device 40 can include a display device, an auxiliary lighting device (e.g., an LED), and a tactile feedback device (e.g., a vibration motor). The above-mentioned display device includes but is not limited to a liquid crystal display, a light emitting diode, a display, and a plasma display. In some optional embodiments, the display device can be a touch screen.

[0141] The embodiment of the present invention also provides a computer-readable storage medium. The above-mentioned method according to the embodiment of the present invention can be implemented in hardware, firmware, or implemented as a computer code that can be recorded in a storage medium, or implemented as a computer code that is originally stored in a remote storage medium or a non-temporary machine-readable storage medium and downloaded through a network and will be stored in a local storage medium, so that the method described herein can be stored in such software processing on a storage medium using a general-purpose computer, a dedicated processor, or programmable or dedicated hardware. Among them, the storage medium can be a magnetic disk, an optical disk, a read-only storage memory, a random access memory, a flash memory, a hard disk or a solid-state drive, etc.; further, the storage medium can also include a combination of the above-mentioned types of memory. It can be understood that a computer, a processor, a microprocessor controller or programmable hardware includes a storage component that can store or receive software or computer code. When the software or computer code is accessed and executed by a computer, a processor or hardware, the method shown in the above embodiment is implemented.

[0142] A portion of the present invention may be applied as a computer program product, such as a computer program instruction, which, when executed by a computer, can call or provide the method and / or technical solution according to the present invention through the operation of the computer. Those skilled in the art should understand that the form in which the computer program instruction exists in a computer-readable medium includes, but is not limited to, a source file, an executable file, an installation package file, etc. Accordingly, the way in which the computer program instruction is executed by the computer includes, but is not limited to: the computer directly executes the instruction, or the computer compiles the instruction and then executes the corresponding compiled program, or the computer reads and executes the instruction, or the computer reads and installs the instruction and then executes the corresponding installed program. Here, the computer-readable medium may be any available computer-readable storage medium or communication medium that can be accessed by the computer.

[0143] Although the embodiments of the present invention have been described with reference to the accompanying drawings, those skilled in the art may make various modifications and variations without departing from the spirit and scope of the present invention. Such modifications and variations are all within the scope defined by the appended claims.

Claims

1. A method for predicting the life of a combustion chamber flame liner, characterized in that: The method comprises: The heat flux density of the combustion chamber flow field is obtained based on a computational fluid dynamics model of the combustion chamber, and the heat flux density is integrated to obtain the ablation rate of the flame tube material; the erosion rate of the flame tube material is obtained through a two-way coupling calculation of the combustion chamber flow field and particles; the ablation rate and the erosion rate are linearly superimposed to obtain the ablation size of the combustion chamber flame tube, and an ablation model is established based on the ablation size; a three-dimensional unsteady-state calculation iteration is performed based on the ablation model, and the life of the combustion chamber flame tube is predicted based on the iterative results; Based on the flame tube test load spectrum, creep tests were conducted on flame tube simulation components to obtain a creep life prediction model for the flame tube. Based on the flame tube test load spectrum, a low cycle fatigue test is performed on the flame tube simulation component to obtain a low cycle fatigue life prediction model of the flame tube; Based on the flame tube test load spectrum, a thermal shock test is performed on the flame tube simulation component to obtain a thermal shock life prediction model for the flame tube, including: cyclically heating the flame tube simulation component according to preset conditions until cracks are generated in the flame tube simulation component; obtaining a relationship between the number of cyclic heating times of the flame tube simulation component and the crack length, and establishing the thermal shock life prediction model, wherein the preset conditions are limitations on the ambient temperature conditions of the flame tube simulation component; Different calculation weights are applied to the ablation model, the creep life prediction model, the low cycle fatigue life prediction model and the thermal shock life prediction model to establish a flame tube life prediction model, and the flame tube life is predicted using the flame tube life prediction model.

2. The method according to claim 1, characterized in that Based on the flame tube test load spectrum, a creep test was conducted on the flame tube simulation component to obtain the creep life prediction model of the flame tube, including: For different service temperatures and service loads of each working condition, obtaining creep damage generated by the flame tube simulation component; Linearly accumulating the creep damage to obtain total creep damage; Based on the total creep damage, the creep life prediction model is established, wherein the operating conditions include: idling operating condition, take-off operating condition, climbing operating condition and cruising operating condition.

3. The method according to claim 1, characterized in that Based on the flame tube test load spectrum, a low-cycle fatigue test was conducted on the combustion chamber flame tube simulation component to obtain a low-cycle fatigue life prediction model for the flame tube, including: For different total strain amplitudes of each working condition, obtaining fatigue damage generated by the flame tube simulation component; Linearly accumulating the fatigue damage to obtain total fatigue damage; Based on the total fatigue damage, the low cycle fatigue life prediction model is established.

4. The method according to claim 1, wherein The acquisition of the flame tube test load spectrum includes: Get the original load spectrum of the flame tube; A load peak in the original load spectrum is identified, and load spectra after the load peak is reached in the original load spectrum are deleted to obtain the flame tube test load spectrum, wherein the mission duration of the flame tube test load spectrum is less than the mission duration of the original load spectrum.

5. The method according to claim 1, wherein Obtaining the combustion chamber computational fluid dynamics model, including: Obtain the original load spectrum of the flame tube and the three-dimensional model of the combustion chamber; Obtaining combustion chamber boundary conditions based on the original load spectrum and the combustion chamber three-dimensional model; Numerical simulation is performed on the combustion chamber boundary conditions to obtain the combustion chamber velocity field, the combustion chamber temperature field and the combustion chamber pressure field; Establishing a computational fluid dynamics model of the combustion chamber based on the combustion chamber velocity field, the combustion chamber temperature field, and the combustion chamber pressure field; The boundary conditions include: combustion chamber inlet boundary conditions, combustion chamber outlet boundary conditions, combustion chamber wall boundary conditions and combustion chamber rotation period boundary conditions.

6. A device for predicting the life of a combustion chamber flame tube, characterized in that: The device comprises: The first prediction module is configured to obtain a heat flux density of a combustion chamber flow field based on a combustion chamber computational fluid dynamics model, perform integral calculation on the heat flux density to obtain an ablation rate of a flame tube material; obtain an erosion rate of the flame tube material through a bidirectional coupling calculation of the combustion chamber flow field and particles; linearly superpose the ablation rate and the erosion rate to obtain an ablation size of the combustion chamber flame tube, and establish an ablation model based on the ablation size; perform three-dimensional unsteady-state calculation iteration based on the ablation model, and predict the life of the combustion chamber flame tube based on the iterative results; The second prediction module is used to perform a creep test on the flame tube simulation component based on the flame tube test load spectrum to obtain a creep life prediction model for the flame tube; A third prediction module is configured to perform a low cycle fatigue test on the flame tube simulation component based on the flame tube test load spectrum to obtain a low cycle fatigue life prediction model for the flame tube; The fourth prediction module is used to perform a thermal shock test on the flame tube simulation component based on the flame tube test load spectrum to obtain a thermal shock life prediction model for the flame tube, including: cyclically heating the flame tube simulation component according to preset conditions until cracks are generated in the flame tube simulation component; obtaining a relationship between the number of cyclic heating times of the flame tube simulation component and the crack length, and establishing the thermal shock life prediction model, wherein the preset conditions are limitations on the ambient temperature conditions of the flame tube simulation component; The life prediction module is used to apply different calculation weights to the ablation model, the creep life prediction model, the low cycle fatigue life prediction model and the thermal shock life prediction model, establish a flame tube life prediction model, and predict the flame tube life through the flame tube life prediction model.

7. A computer device, characterized in that: include: A memory and a processor, wherein the memory and the processor are communicatively connected to each other, the memory stores computer instructions, and the processor executes the method for predicting the life of a combustion chamber flame tube according to any one of claims 1 to 5 by executing the computer instructions.

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