Multi-duct variable-cycle engine maneuvering and aerodynamic load prediction method and system

Abstract

The invention discloses a multi-duct variable-cycle engine maneuvering and aerodynamic load prediction method and system, and relates to the technical field of aero-engines. The method comprises the steps that typical flight actions including climbing, diving and level flight are divided based on flight tasks, a rain flow counting method is adopted to filter an original load spectrum so as to retain a key loading and unloading path, three-parameter Weibull distribution is fitted in combination with a bilinear regression method, and load distribution characteristics of typical task segments are extracted; establishing a flight dynamics equation and a lift-drag characteristic model, and verifying the prediction precision of the normal overload coefficient through Simulink simulation; and the maneuvering and aerodynamic load distribution of the multi-duct variable-cycle engine in a turbofan / turbojet mode is deduced by further combining the airfoil profile parameters of the high-sound-velocity aircraft. According to the method, the accuracy of load prediction can be remarkably improved, a reliable basis is provided for service life evaluation and optimization design of an engine structure, and the method has important engineering value.

Description

Technical Field

[0001] The present invention relates to the technical field of aeroengines, and particularly to a method and system for predicting the maneuvering and aerodynamic loads of a multi-duct variable cycle engine. Background Art

[0002] Most of the existing aeroengine load spectrum analysis methods rely on static parameters such as flight altitude and engine speed. Although this method can provide basic load information, it cannot dynamically reflect the true impact of different flight maneuvers (such as climbing, diving, and level flight) on load changes. Due to the lack of dynamic response to flight maneuvers and comprehensive consideration of flight states, traditional methods cannot effectively capture the load change characteristics of the aircraft in complex flight scenarios, resulting in low accuracy of load analysis and affecting the prediction of engine life and performance.

[0003] The current load analysis methods have the following main defects: (1) There is no systematic division of typical flight maneuvers, resulting in fragmented load analysis and unable to accurately reflect the load characteristics under different flight states; (2) When processing load data, the filtering method is prone to losing key loading and unloading path information, thus affecting the assessment of low-cycle fatigue damage; (3) The existing lift-drag characteristic model has insufficient correlation with the Reynolds number and cannot adapt to the complex aerodynamic load characteristics in high-speed flight scenarios.

[0004] These problems lead to large errors in the traditional method for predicting engine life and cannot accurately support the design optimization and performance evaluation of the engine. Therefore, there is an urgent need for a technical method that can dynamically and accurately predict engine loads, comprehensively consider the dynamic flight states of the aircraft, accurately reflect the load changes during flight, and then improve the accuracy of engine life prediction and the ability of design optimization. Summary of the Invention

[0005] The purpose of the present invention is to provide a method and system for predicting the maneuvering and aerodynamic loads of a multi-duct variable cycle engine. Based on the load prediction method of flight maneuver division, rainflow counting filtering, and three-parameter Weibull distribution fitting, combined with the flight dynamics model and high-speed airfoil extension, the accurate prediction of the maneuvering and aerodynamic loads of the multi-duct variable cycle engine is realized.

[0006] To achieve the above purpose, the present invention is realized through the following technical solutions:

[0007] A method for predicting the maneuvering and aerodynamic loads of a multi-duct variable cycle engine, comprising:

[0008] Step 1: Receive flight altitude spectrum, normal overload spectrum data, and flight Mach number data;

[0009] Step 2: Divide flight actions based on flight altitude spectrum and normal overload spectrum data. The flight actions include climbing, diving, and level flight;

[0010] Step 3: Filter the original load spectrum using the rainflow counting method, screen out the loading and unloading paths, and remove load cycles with amplitudes less than the threshold;

[0011] Step 4: Extract the load data of typical mission segments, and fit the three-parameter Weibull distribution through bilinear regression to obtain the load distribution characteristics of typical mission segments. The three-parameter Weibull distribution includes a scale parameter, a shape parameter, and a location parameter;

[0012] Step 5: Establish a flight dynamics model, and calculate the normal overload coefficient based on the six-degree-of-freedom motion equation, lift coefficient, drag coefficient, and side force coefficient;

[0013] Step 6: Combine simulation calculations to verify the calculation accuracy of the normal overload coefficient based on flight data and the aerodynamic characteristics model;

[0014] Step 7: Based on the airfoil data of high-speed aircraft, derive the maneuvering and aerodynamic load spectra of the multi-ducted variable cycle engine in turbofan and turbojet modes.

[0015] As a preferred solution of the present invention, the rules for dividing flight actions are as follows:

[0016] Measure the change in the vertical speed of the aircraft through a vertical speedometer or a barometric sensor, and calculate the rate of climb;

[0017] If the rate of climb is greater than +5 m / s, it is a climbing action;

[0018] If the rate of climb is less than -5 m / s, it is a diving action;

[0019] If the absolute value of the rate of climb is less than 5 m / s, it is a level flight action;

[0020] The flight control system obtains the rate of climb in real time and determines the current flight action.

[0021] The formula for calculating the rate of climb is:

[0022]

[0023] Where: H i is the altitude at the i-th time, and T i is the time at the i-th time.

[0024] As a preferred solution of the present invention, the filtering of the original load spectrum using the rainflow counting method includes the following steps:

[0025] For the rising section of the load spectrum, filter out the data points where the load increments between two adjacent points are positive, and delete the data points where the increments are negative;

[0026] For the descending section of the load spectrum, filter out the data points where the load increments between two adjacent points are negative, and delete the data points where the increments are positive;

[0027] The original load data points are inserted between the filtered peak and valley values to ensure the complete loading and unloading path information;

[0028] The calculation method of the threshold Δ% is:

[0029] Δ%=(G max -G min )*ω%, where: G max is the upper limit of the load amplitude range of each cycle in the original load spectrum, G min is the lower limit of the load amplitude range of each cycle in the original load spectrum, and ω is an empirical constant ranging from 8.0 to 12.5.

[0030] As a preferred embodiment of the present invention, the steps of fitting the three-parameter Weibull distribution by the double linear regression method are as follows:

[0031] Define the parameters of the regression model: is the shape parameter, which indicates the shape of the load distribution; is the location parameter, which indicates the location offset of the distribution; is the scale parameter, which indicates the scale of load distribution;

[0032] The linear regression equation is fitted by the least squares method, and the following formulas are established:

[0033]

[0034] in: and is the functional relationship used to calculate the regression parameters;

[0035] The regression parameters are optimized by iterative method, and each iteration is updated using the following formula:

[0036]

[0037] Where: f(β) is the objective function, f′(β) is the derivative of the objective function with respect to β, (n) It is n The parameter value of the iteration;

[0038] During the iteration process, a dynamic step size adjustment strategy is adopted to adjust the step size according to the change between the current error and the previous error; if the error changes too quickly, the step size is reduced; if the error changes slowly, the step size is increased;

[0039] The accuracy calculation formula is as follows:

[0040]

[0041] Where: and respectively represent the parameter values of the current and the previous iteration; when the accuracy reaches the preset threshold, the iteration stops;

[0042] Analyze the flight data and divide it into peak-type task segments and load-maintaining task segments based on the rotor speed spectrum; apply the three-parameter Weibull distribution to the peak-type task segments, fit their peak and valley values, and output a distribution characteristic table containing the scale parameter, shape parameter, and location parameter; apply the exponential distribution to the load-maintaining task segments, fit their load-maintaining time, and output a distribution characteristic table containing the scale parameter, shape parameter, and location parameter.

[0043] As a preferred embodiment of the present invention, the establishment of the flight dynamics model includes the following steps:

[0044] Calculate the lift coefficient C L 、drag coefficient C D 、side force coefficient C Z , and the calculation formulas are as follows:

[0045]

[0046] Where: ρ is the atmospheric density, v is the aircraft speed, S is the wing area, L is the lift, D is the drag, and Z is the side force; calculate the Reynolds number Re, and the calculation formula is:

[0047]

[0048] Where: v is the flight speed, ρ and μ are respectively the velocity of the fluid, the density of the fluid, and the dynamic viscosity, and l is the chord length of the wing;

[0049] Based on the calculated lift coefficient, drag coefficient, and side force coefficient, calculate the motion response of the aircraft, including the translational and rotational motions of the aircraft, and calculate the normal overload coefficient;

[0050] According to the flight data and the aerodynamic characteristic model, calculate the normal overload coefficient and verify it to ensure the calculation accuracy;

[0051] Output the normal overload coefficient, fuel consumption rate, and engine thrust data as the input of the prediction model.

[0052] Establishment of the aircraft kinematic equation:

[0053] As a preferred embodiment of the present invention, the steps for verifying the normal overload coefficient include:

[0054] Based on flight data and aerodynamic characteristics models, the calculation accuracy of the normal load coefficient is verified through simulation calculations;

[0055] By comparing the calculated values with the measured values, the root mean square error was ensured not to exceed 0.05.

[0056] As a preferred embodiment of the present invention, the method comprises:

[0057] Calculate the Reynolds number based on the flight altitude and Mach number;

[0058] Based on the lift-drag characteristics data of NASA a315-Ⅱ airfoil, the lift coefficient, drag coefficient and side force coefficient at the current angle of attack and Reynolds number are obtained through two-dimensional interpolation.

[0059] Combined with the flight dynamics equations, the normal overload spectrum and rotor speed spectrum in turbofan mode and turbojet mode are calculated.

[0060] A prediction system for a multi-bypass variable cycle engine maneuvering and aerodynamic load prediction method, comprising:

[0061] Data acquisition module, used to obtain flight altitude spectrum, normal overload spectrum, fuel consumption rate and engine thrust data;

[0062] Action classification module, used to classify climbing, diving, and level flight actions according to the climbing rate threshold, and mark them with different colors;

[0063] A filtering processing module is used to perform rain flow counting filtering, select valid load cycles and eliminate irrelevant cycle data;

[0064] The distribution fitting module is used to solve the Weibull distribution parameters using the bilinear regression method to generate the load distribution of the typical task segment;

[0065] Dynamic modeling module, used to integrate the six-degree-of-freedom motion equations with the lift-drag characteristic model and output the normal overload coefficient;

[0066] The extended application module is used to adapt the airfoil parameters of hypersonic aircraft and generate the maneuvering and aerodynamic load spectra of multi-bypass variable cycle engines.

[0067] As a preferred solution of the present invention, the dynamic modeling module is implemented through a simulation platform, and the input parameters include angle of attack, sideslip angle, bank angle, pitch angle, engine thrust and flight Mach number.

[0068] As a preferred solution of the present invention, the extended application module includes:

[0069] Airfoil database, used to store lift and drag characteristic data of hypersonic aircraft airfoils at different Reynolds numbers;

[0070] An interpolation calculation unit for dynamically calling database data according to current flight parameters;

[0071] A load spectrum generation unit for outputting the normal overload spectrum and rotor speed spectrum in the turbofan mode and turbojet mode.

[0072] Compared with the prior art, the beneficial effects of the present invention are as follows: Through the dynamic flight action division based on the flight altitude spectrum and normal overload spectrum data, the present invention adopts a climb rate threshold of ±5 m / s and color coding, combined with the rain flow counting method for filtering, retains the key loading and unloading paths, and accurately screens out the effective load cycles, solving the problem of insufficient load prediction accuracy in the prior art. At the same time, the three-parameter Weibull distribution is iteratively solved by the bilinear regression method to effectively fit the load data and accurately describe the load distribution characteristics under different flight actions. To further improve the prediction accuracy, the present invention establishes a six-degree-of-freedom flight dynamics model corrected by the Reynolds number, and verifies the calculation accuracy of the normal overload coefficient through simulation, ensuring that the root mean square error RMSE is less than 0.05. This model can adapt to high Mach number flight scenarios, generates the maneuvering and aerodynamic load spectra of a multi-ducted variable cycle engine in the turbofan / turbojet mode based on the lift-drag characteristic data of the NASA a315-II airfoil. Description of the Drawings

[0073] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the following will briefly introduce the drawings required for the description of the embodiments. Obviously, the following drawings are only some embodiments of the present invention. For those of ordinary skill in the art, other drawings can be obtained based on these drawings without creative efforts.

[0074] Among them:

[0075] Figure 1 is the method flow chart of the embodiment of the present invention;

[0076] Figure 2 is the flight action division result diagram in the embodiment of the present invention;

[0077] Figure 3 is the coordinate axis diagram of the multi-ducted variable cycle engine aircraft in the embodiment of the present invention;

[0078] Figure 4 is the comparison diagram of the rain flow counting cumulative probability of the maneuvering load prediction spectrum of the third-generation aircraft in the embodiment of the present invention;

[0079] Figure 5 is the normal overload spectrum diagram of the climb action of the multi-ducted variable cycle engine in the turbofan mode in the embodiment of the present invention;

[0080] Figure 6It is the normal overload spectrum diagram of the climbing action in the turbojet mode of the multi-ducted variable cycle engine in the embodiment of the present invention;

[0081] Figure 7 It is the rotational speed spectrum diagram of the climbing action in the turbofan mode of the multi-ducted variable cycle engine in the embodiment of the present invention;

[0082] Figure 8 It is the rotational speed spectrum diagram of the climbing action in the turbojet mode of the multi-ducted variable cycle engine in the embodiment of the present invention. Detailed implementation manners

[0083] To make the objectives, technical solutions and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings of the embodiments of the present invention. Obviously, the described embodiments are some but not all of the embodiments of the present invention. All other embodiments obtained by those of ordinary skill in the art based on the described embodiments of the present invention belong to the scope of protection of the present invention.

[0084] Embodiment 1

[0085] As Figure 1 shown, it is an embodiment of the present invention, and this embodiment provides a method for predicting the maneuver and aerodynamic load of a multi-ducted variable cycle engine, including:

[0086] Step 1: Receive the flight altitude spectrum, normal overload spectrum data and flight Mach number data;

[0087] Step 2: Divide the flight actions based on the flight altitude spectrum and the normal overload spectrum data, and the flight actions include climbing, diving and level flight;

[0088] Specifically, the rules for dividing the flight actions are as follows:

[0089] Measure the change in the vertical speed of the aircraft through a vertical speedometer or a barometric sensor, and calculate the rate of climb;

[0090] If the rate of climb is greater than +5 m / s, it is a climbing action;

[0091] If the rate of climb is less than -5 m / s, it is a diving action;

[0092] If the absolute value of the rate of climb is less than 5 m / s, it is a level flight action;

[0093] The flight control system obtains the rate of climb in real time and determines the current flight action.

[0094] In this embodiment, as Figure 2 shown, for the division of flight actions, input the flight altitude spectrum, flight Mach number, and normal overload spectrum, and dynamically divide the actions according to the change rate of the flight altitude. The formula for calculating the rate of climb is:

[0095]

[0096] Wherein: H i is the height at the i-th time, and T i is the time at the i-th time.

[0097] The three action division rules are shown in Table 1:

[0098] Table 1 Typical flight action division principles

[0099]

[0100] Use MATLAB software to model and divide the flight data, and divide the flight actions using the colors in Table 1. As Figure 2 shown, it is the flight action division result of a flight profile.

[0101] As Figure 3 shown, Oxyz is the aircraft body coordinate system, the origin is the center of gravity position of the aircraft, and Ox q y q z q is the airflow coordinate system, and Ox b y b z b is the semi-body coordinate system.

[0102] Based on the working process analysis results, use MATLAB software to perform component-level modeling of the multi-ducted variable cycle engine based on the aerodynamic thermodynamics configuration model to form component-level modeling data;

[0103] Load spectrum filtering and distribution fitting, using the rainflow counting method for filtering, with the filtering target being to remove small-amplitude load cycles (which contribute little to low-cycle fatigue damage) and retain the key loading and unloading paths.

[0104] In this embodiment, as Figure 4 shown, the low-cycle fatigue damage suffered by the aeroengine during service is formed due to the repeated changes of the throttle, including three types: 0-maximum-0 cycle, idle-maximum-idle cycle, and cruise-maximum-cruise cycle. Perform rainflow counting statistics on the predicted normal overload spectrum and the actual normal overload spectrum to further verify that the low-cycle fatigue of the predicted spectrum and the actual spectrum is damage-equivalent, thus indicating that the lift-drag characteristic model in this paper can accurately predict the normal overload under flight actions and provides a calculation method for analyzing the maneuvering loads of the multi-ducted variable cycle engine.

[0105] Step 3: Filter the original load spectrum using the rainflow counting method, screen out the loading and unloading paths, and remove the load cycles with amplitudes less than the threshold;

[0106] The method of filtering the original load spectrum by using the rain flow counting method comprises the following steps:

[0107] For the rising section of the load spectrum, filter out the data points where the load increments between two adjacent points are positive, and delete the data points where the increments are negative;

[0108] For the descending section of the load spectrum, filter out the data points where the load increments between two adjacent points are negative, and delete the data points where the increments are positive;

[0109] The original load data points are inserted between the filtered peak and valley values to ensure the complete loading and unloading path information;

[0110] The calculation method of the threshold Δ% is:

[0111] Δ%=(G max -G min ) * ω%, where: G max is the upper limit of the load amplitude range of each cycle in the original load spectrum, G min is the lower limit of the load amplitude range for each cycle in the original load spectrum, ω is an empirical constant. For aircraft engines, the recommended value range is 8.0 to 12.5. In this paper, ω is taken as 10.

[0112] Step 4: Extract the load data of the typical task segment and fit the three-parameter Weibull distribution using the bilinear regression method to obtain the load distribution characteristics of the typical task segment. The three-parameter Weibull distribution includes a scale parameter, a shape parameter, and a position parameter.

[0113] The three-parameter Weibull distribution is fitted by the bilinear regression method, and the steps are as follows:

[0114] Define the parameters of the regression model: is the shape parameter, which indicates the shape of the load distribution; is the location parameter, which indicates the location offset of the distribution; is the scale parameter, which indicates the scale of load distribution;

[0115] The linear regression equation is fitted by the least squares method, and the following formulas are established:

[0116]

[0117] in: and is the functional relationship used to calculate the regression parameters;

[0118] The regression parameters are optimized by iterative method, and each iteration is updated using the following formula:

[0119]

[0120] Where: f(β) is the objective function, f′(β) is the derivative of the objective function with respect to β, (n) It is n The parameter value of the iteration;

[0121] During the iteration process, a dynamic step size adjustment strategy is adopted to adjust the step size according to the change between the current error and the previous error; if the error changes too quickly, the step size is reduced; if the error changes slowly, the step size is increased;

[0122] The accuracy calculation formula is as follows:

[0123]

[0124] in: and Represent the parameter values of the current and previous iterations respectively; when the accuracy reaches the preset threshold, the iteration stops;

[0125] The flight data is analyzed and divided into peak-type mission segments and load-holding mission segments based on the rotor speed spectrum. The three-parameter Weibull distribution is applied to the peak-type mission segments to fit their peak and valley values, and a distribution characteristic table containing scale parameters, shape parameters, and position parameters is output. The exponential distribution is applied to the load-holding mission segments to fit their load-holding time, and a distribution characteristic table containing scale parameters, shape parameters, and position parameters is output.

[0126] Using the three-parameter Weibull distribution fitting, its mathematical form is:

[0127]

[0128] Among them: η is the scale parameter, β is the shape parameter, and γ is the location parameter;

[0129] Aircraft kinematic equations are established: Figure 2 As shown, Oxyz is the aircraft body coordinate system, the origin is the center of gravity of the aircraft, Ox q y q z q is the airflow coordinate system, Ox b y b z b is the half-body coordinate system.

[0130] When an aircraft is performing a flight mission, there is both relative motion of particles and involved motion of rigid bodies. The six-degree-of-freedom equation is:

[0131]

[0132] By analyzing the force on the aircraft and considering the engine thrust and the aerodynamic characteristics of the aircraft, the above formula can be rewritten as:

[0133]

[0134] Among them, V x , V y and V z are the velocity components of the aircraft in each direction, ω x , ω y and ω z are the angular velocity components of the aircraft in each direction, I x , I y and I z are the moment of inertia components of the aircraft, I xy is the product of inertia, m is the mass of the aircraft, P is the engine thrust, D is the drag of the aircraft in the airflow coordinate system, L is the lift in the airflow coordinate system, Z is the side force in the airflow coordinate system, M x , M y and M z are the moment components generated by aerodynamic forces in each direction. α is the angle of attack of the aircraft, β is the sideslip angle of the aircraft, γ is the bank angle of the aircraft, θ is the pitch angle of the aircraft, is the angle between the projection of the engine thrust line on the aircraft's symmetry plane and the body coordinate axis Ox. When the thrust line is obliquely upward it is positive.

[0135] In the formula:

[0136]

[0137] During the flight of the aircraft, its mass m also changes with time. Q is the fuel consumption rate (kg / s):

[0138]

[0139] The mass m integrated with respect to time t gives:

[0140]

[0141] Among them, m t＝0 is the mass of the aircraft at takeoff. The lift-drag characteristic equation is:

[0142]

[0143] Among them, ρ is the atmospheric density, v is the aircraft speed, S is the wing area, C L and C D are the lift coefficient and drag coefficient, which are related to the wing. C Zis the side force coefficient. In fact, the side force has nothing to do with the area of the wing. The wing area is introduced to obtain the same expressions as those for lift and drag.

[0144] Therefore, according to the flight dynamics equations under different flight maneuvers, by inputting the required flight parameters, the lift coefficient C of this type of aircraft can be calculated. L , the drag coefficient C D and the side force coefficient C Z can be obtained, and the influencing factors of the lift-drag characteristics can be determined. Then, according to the operating conditions required by the multi-ducted variable cycle engine, the lift-drag characteristics of the wing that conform to the multi-ducted variable cycle engine model can be selected. Furthermore, the maneuvering load relationship of this model during the execution of flight missions can be analyzed.

[0145] Step 5: Establish a flight dynamics model. Based on the six-degree-of-freedom motion equations, lift coefficient, drag coefficient, and side force coefficient, calculate the normal overload coefficient;

[0146] Specifically, the establishment of the flight dynamics model includes the following steps:

[0147] Calculate the lift coefficient C L , the drag coefficient C D , the side force coefficient C Z , and the calculation formulas are as follows:

[0148]

[0149] where: ρ is the atmospheric density, v is the aircraft speed, S is the wing area, L is the lift, D is the drag, and Z is the side force; ]>

[0150] Calculate the Reynolds number Re, and the calculation formula is:

[0151]

[0152] where: v is the flight speed, ρ and μ are the velocity of the fluid, the density of the fluid, and the dynamic viscosity respectively, and l is the chord length of the wing;

[0153] Based on the calculated lift coefficient, drag coefficient, and side force coefficient, combined with the six-degree-of-freedom motion equations, calculate the motion response of the aircraft, including the translational and rotational motions of the aircraft, and calculate the normal overload coefficient;

[0154] According to the flight data and the aerodynamic characteristics model, calculate the normal overload coefficient and verify it to ensure the calculation accuracy;

[0155] Output the normal overload coefficient, fuel consumption rate, and engine thrust data as the input of the prediction model.

[0156] Step 6: Combine simulation calculations, and verify the calculation accuracy of the normal overload coefficient based on flight data and the aerodynamic characteristics model;

[0157] Step 7: Based on the airfoil data of the high Mach number aircraft, derive the maneuvering and aerodynamic load spectra of the multi-ducted variable cycle engine in the turbofan and turbojet modes.

[0158] The steps for verifying the normal overload coefficient include:

[0159] Based on flight data and the aerodynamic characteristics model, verify the calculation accuracy of the normal overload coefficient through simulation calculations;

[0160] By comparing the calculated value with the measured value, ensure that the root mean square error does not exceed 0.05.

[0161] The method includes:

[0162] Calculate the Reynolds number according to the flight altitude and Mach number;

[0163] Based on the lift-drag characteristics data of the NASA a315-II airfoil, obtain the lift coefficient, drag coefficient, and side force coefficient at the current angle of attack and Reynolds number through two-dimensional interpolation;

[0164] Combine the flight dynamics equations to calculate the normal overload spectrum and rotor speed spectrum in the turbofan mode and the turbojet mode.

[0165] As Figure 5 、 Figure 6 shown, since the flight altitude and Mach number of the high Mach number aircraft are different from those of the third-generation aircraft, calculate the Reynolds number Re at each point of each action according to the flight process parameters of the high Mach number aircraft, and the lift coefficient C L 、drag coefficient C D and side force coefficient C Z are obtained through two-dimensional interpolation of the wing angle of attack and Reynolds number of the high Mach number aircraft's airfoil characteristics, and then the corresponding forces are obtained through the calculation formulas of lift, drag, and side force. Finally, the normal overload n y calculation formula is used to obtain the normal overload of the multi-ducted variable cycle engine and the maneuvering load spectrum of the multi-ducted variable cycle engine.

[0166] As Figure 7 、 Figure 8As shown, the three-rotor speed can be derived from the existing fuel flow rates in each combustion chamber. However, the fuel quantity at each moment in the different mission segments of a multi-bypass variable cycle engine is unknown. Therefore, thrust is used as the input quantity, and the speed spectrum of the three rotors is derived from the performance model. The speed spectrum is filtered after rain flow counting and can be basically divided into two types: peak mission segments and load-holding mission segments, as shown in the figure. Peak mission segments can be viewed as triangular waves, with the peak value, valley value, and mission segment duration defining the mission segment. Load-holding mission segments can be viewed as trapezoidal waves, with the peak value, valley value, mission segment duration, and load-holding time defining the mission segment.

[0167] Example 2

[0168] Another embodiment of the present invention provides a multi-bypass variable cycle engine maneuvering and aerodynamic load prediction system, comprising:

[0169] Data acquisition module, used to obtain flight altitude spectrum, normal overload spectrum, fuel consumption rate and engine thrust data;

[0170] Action classification module, used to classify climbing, diving, and level flight actions according to the climbing rate threshold, and mark them with different colors;

[0171] A filtering processing module is used to perform rain flow counting filtering, select valid load cycles and eliminate irrelevant cycle data;

[0172] The distribution fitting module is used to solve the Weibull distribution parameters using the bilinear regression method to generate the load distribution of the typical task segment;

[0173] Dynamic modeling module, used to integrate the six-degree-of-freedom motion equations with the lift-drag characteristic model and output the normal overload coefficient;

[0174] The extended application module is used to adapt the airfoil parameters of hypersonic aircraft and generate the maneuvering and aerodynamic load spectra of multi-bypass variable cycle engines.

[0175] Furthermore, the dynamic modeling module is implemented through a simulation platform, and the input parameters include angle of attack, sideslip angle, bank angle, pitch angle, engine thrust and flight Mach number.

[0176] Furthermore, the extended application module includes:

[0177] Airfoil database, used to store lift and drag characteristic data of hypersonic aircraft airfoils at different Reynolds numbers;

[0178] Interpolation calculation unit, used to dynamically call database data according to current flight parameters;

[0179] The load spectrum generation unit is used to output the normal overload spectrum and rotor speed spectrum in turbofan mode and turbojet mode.

[0180] Example 3

[0181] In this paper, the original flight dynamics are simplified as follows:

[0182] (1) After classifying typical flight maneuvers, only the dynamics under this flight maneuver are considered, and the superposition of maneuvers is not considered.

[0183] (2) For typical flight maneuvers, only the relative motion of the mass point is considered, and the rigid body motion of the aircraft is not considered;

[0184] Analysis of the climbing maneuver: Climbing is one of the classic maneuvers of an aircraft. After the aircraft takes off, the engine thrust increases, the aircraft speed increases, and the lift generated by the wings also increases accordingly, causing the aircraft to gradually leave the ground. As the altitude increases, the air dynamic pressure decreases, and the lift of the aircraft will also decrease accordingly. To maintain the lift required for climbing, the angle of attack and thrust are usually adjusted for control.

[0185] According to the flight dynamics equations mentioned above, the climbing maneuver is simplified. Since the rotation process of the aircraft is not considered, only the linear motion of the aircraft is considered; and since the nozzle of the third-generation aircraft is not a vector nozzle and the angle cannot be adjusted, the angle between the engine thrust and the aircraft body coordinate axis Ox The nozzle angle does not change, and the climbing equation is as shown in Equation 3.21:

[0186]

[0187] In this paper, 50 cross-section data of third-generation aircraft are selected, and maneuvers are classified according to the flight maneuver classification criteria in Table 3.1. For the extracted climbing section, dynamic analysis of the climbing data is carried out, and a Simulink module is built. The input quantities are shown in Table 2:

[0188] Table 2 Input quantities of the flight dynamics Simulink module for the climbing section

[0189]

[0190] Input the angle of attack YJ of the aircraft, the sideslip angle CHJ of the aircraft, the bank angle QXJ of the aircraft, the pitch angle FYJ of the aircraft, the acceleration in the x direction ax , the acceleration ay in the y direction, the acceleration in the z direction az and the fuel consumption rate Q. The engine thrust P can be used to calculate the lift L, drag D, and side force Z through the flight dynamics equations of climbing. The input altitude H can be used to calculate the air density ρ and airspeed at the current altitude through the atmospheric model v , the input flight Mach number Ma and wing area S at this time. According to the lift-drag characteristic equation, the lift coefficient C L , the drag coefficient C D and the side force coefficient C Z;

[0191] Analysis of level flight motion: The level flight of an aircraft is a basic flight attitude. In this state, the altitude of the aircraft remains basically unchanged, and the lift generated by the wings is basically equal to the gravity of the aircraft, with slightly small fluctuations possible. The pilot can control the speed and direction of the aircraft by adjusting the throttle and control surfaces. During level flight, the engine of the aircraft provides thrust to make the aircraft fly forward. The level flight motion is an important stage in the flight profile, which provides the basis for other flight motions such as climbing, diving, and turning.

[0192] The level flight motion is simplified to an angle of attack α = 0 and a pitch angle θ = 0, and the angle between the engine thrust and the body coordinate axis Ox Therefore, the flight dynamics equation for the level flight motion is:

[0193]

[0194] According to the previous division of flight motions, a dynamic analysis of the level flight data was carried out, and a Simulink module was built. The input quantities are shown in Table 3:

[0195] Table 3 Input quantities of the flight dynamics Simulink module for the level flight segment

[0196]

[0197] Input the sideslip angle CHJ of the aircraft, the bank angle QXJ of the aircraft, the acceleration in the x direction ax , the acceleration ay in the y direction, the acceleration az in the z direction, the engine thrust P, and the fuel consumption rate Q of the aircraft. The lift L, drag D, and side force Z can be calculated. Input the altitude H, flight Mach number Ma, and wing area S. According to the atmospheric model and the lift-drag characteristic equation, the lift coefficient C L , drag coefficient C D , and side force coefficient C Z ;

[0198] Analysis of dive motion: The dive motion of an aircraft is a common flight maneuver, usually used to increase speed or perform aerobatics. During the dive, the aircraft descends at an angle close to vertical, increasing the speed by reducing the lift. The dive can be divided into several stages: First is the acceleration stage, where the pilot pushes the control stick forward to lower the nose and make the aircraft enter the dive state; then is the high-speed stage, where the aircraft moves forward at an extremely high speed; finally is the pull-up stage, where the pilot gradually raises the nose to make the aircraft return to the normal flight attitude.

[0199] The dive motion is simplified in the same way as the climb motion. The flight dynamics equation for the dive motion is:

[0200]

[0201] The input quantity is consistent with the climbing motion, and the lift coefficient C L , drag coefficient C D and side force coefficient C Z ;

[0202] Verification of lift-to-drag characteristic model: The influencing factors of maneuvering load include altitude H, Mach number Ma, thrust P, flight actions, etc. The maneuvering load of the aircraft is mainly the normal overload coefficient n y , and the normal overload coefficient refers to the ratio of all the resultant forces N y in the y direction except gravity to the gravity G in the body coordinate system Oxyz, that is:

[0203]

[0204] According to the flight dynamics equation, n y under typical flight actions can be obtained as shown in Table 4:

[0205] Table 4 Normal overload n under different flight actions y Calculation formula

[0206]

[0207] The input parameters include: altitude H, Mach number Ma, angle of attack α , pitch angle θ, sideslip angle β, bank angle γ, fuel consumption rate Q, and thrust P, as shown in Table 3.2:

[0208] Table 3.2 Normal overload n y Input quantity of the Simulink module for calculation

[0209]

[0210] Lift coefficient C L and drag coefficient C D are calculated through the angle of attack α and altitude H. At altitude H and Mach number Ma, according to the atmospheric model and lift and drag calculation formulas, the lift L, drag D, and side force Z can be calculated. According to the table, a Simulink module can be built to calculate the normal overload coefficient n under flight actions y .

[0211] From the perspective of mathematical statistics, the error between the measured value and the predicted value of the normal overload can be achieved through various statistical methods, including standard deviation, variance, mean square error, mean difference, Z-test, T-test, etc. In this paper, the root mean square error (RMSE) test is selected. On the one hand, by calculating the square root of the mean of the squares of the differences between the predicted value and the actual value, it can comprehensively consider the magnitude and direction of all prediction errors, avoiding the problem of positive and negative errors canceling each other out; on the other hand, RMSE gives a higher penalty to larger errors, such as squaring larger errors, so it can more accurately measure the performance of the model in prediction, especially when the prediction errors are large. Therefore, using the root mean square error analysis can prove the accuracy of the lift-drag characteristic model of the third-generation aircraft. The root mean square error RMSE between the measured value and the predicted value of the normal overload of the third-generation aircraft is as follows:

[0212]

[0213] To ensure the rationality of the statistics, this paper conducts a root mean square error analysis on all climbing, level flight, and diving maneuvers of 20 profiles of the third-generation aircraft. The measured errors and predicted errors of different flight maneuvers are shown in Table 5, and the maximum error does not exceed 0.05, proving that this lift-drag characteristic relationship can calculate the normal overload of the third-generation aircraft relatively accurately.

[0214] Table 5 Root Mean Square Error of Normal Overload Calculation under Different Flight Maneuvers

[0215]

[0216] The low-cycle fatigue damage suffered by an aeroengine during service is formed due to the repeated changes of the throttle, including three types: 0-maximum-0 cycle, idle-maximum-idle cycle, and cruise-maximum-cruise cycle. Conducting rainflow counting statistics on the predicted normal overload spectrum and the actual normal overload spectrum, as shown in the figure, further verifies that the low-cycle fatigue of the predicted spectrum and the actual spectrum is damage-equivalent, thus indicating that the lift-drag characteristic model of this method can accurately predict the normal overload under flight maneuvers, providing a calculation method for analyzing the maneuvering loads of a multi-ducted variable cycle engine;

[0217] Maneuvering and Aerodynamic Loads of a Multi-ducted Variable Cycle Engine: Since the flight altitude and Mach number of a high-supersonic aircraft are different from those of a third-generation aircraft, calculate the Reynolds number Re of each point of each maneuver according to the flight process parameters of the high-supersonic aircraft, lift coefficient C L , drag coefficient C D and side force coefficient C Z Obtained through the airfoil characteristics of the high-supersonic aircraft by two-dimensional interpolation of the wing angle of attack and Reynolds number, and then obtain the corresponding forces through the calculation formulas of lift, drag, and side force. Finally, through the normal overload n yThe normal overload of the multi-ducted variable cycle engine obtained by the calculation formula. The maneuvering load spectrum of the multi-ducted variable cycle engine is shown in the figure.

[0218] In order to compile the maneuvering load spectrum of the multi-ducted variable cycle engine, it is necessary to perform distribution fitting on the maneuvering loads in the climbing, level flight, and diving mission segments of the multi-ducted variable cycle engine. According to the maneuvering load distribution characteristic fitting method, the normal overload n under different flight maneuvers can be obtained. y Taking the climbing segment as an example, the fitting results are shown in Table 6:

[0219] Table 6 Fitting of the maneuvering load mission segment in the climbing segment of the variable cycle engine

[0220]

[0221] During the service process of the multi-ducted variable cycle engine, it is mainly affected by aerodynamic loads (such as turbine inlet temperature, rotor speed) and maneuvering loads (such as normal overload coefficient, lateral overload coefficient, axial overload coefficient). Here, the distribution of the aerodynamic loads of the multi-ducted variable cycle engine is mainly analyzed.

[0222] According to the performance model of the multi-ducted variable cycle engine, the three-rotor speeds can be obtained through the existing fuel flow rates of each combustion chamber. However, the fuel quantity at each moment in different mission segments of the multi-ducted variable cycle engine is unknown. Therefore, the thrust is used as the input quantity, and the speed spectrum of the three rotors is obtained through the performance model.

[0223] After the speed spectrum is filtered by rainflow counting, it can basically be divided into two types: the peak type mission segment and the hold type mission segment, as shown in the figure. The peak type mission segment can be regarded as a triangular wave, and this mission segment is determined by the peak value, valley value, and mission segment duration. The hold type mission segment can be regarded as a trapezoidal wave, and the hold type mission segment is determined by the peak value, valley value, mission segment duration, and hold time.

[0224] The peak and valley values of these two mission segments can be fitted by the three-parameter Weibull distribution, and the double linear regression method is used to solve the fitting. The durations of the two mission segments follow an exponential distribution, and the hold time of the hold type mission segment follows an exponential distribution. The fitting distribution results are shown in Table 7:

[0225] Table 7 Fitting of the aerodynamic load mission segment in the climbing segment of the variable cycle engine

[0226]

[0227] In summary, by establishing a set of common working equations for a multi-ducted variable cycle engine and combining component-level modeling with an efficient iterative solution method, the present invention can comprehensively analyze the maneuvering and aerodynamic loads of a multi-ducted variable cycle engine. It not only solves the problems of insufficient analysis accuracy, difficulty in capturing dynamic characteristics, and low computational efficiency in the prior art, but also provides an important theoretical basis for the reliability design and optimization of multi-ducted variable cycle engines. The present invention is applicable to the design and development of a new generation of multi-ducted variable cycle engines, has significant technological progressiveness and engineering practical value, and is of great significance for promoting the development of technologies in the field of aeroengines.

[0228] In the description of this specification, the description with reference to terms such as "one embodiment", "some embodiments", "example", "specific example", or "some examples" means that the specific features, structures, materials, or characteristics described in connection with the embodiment or example are included in at least one embodiment or example of the present application. Moreover, the specific features, structures, materials, or characteristics described can be combined in a suitable manner in any one or more embodiments or examples. In addition, without contradiction, those skilled in the art can combine and combine the different embodiments or examples described in this specification and the features of different embodiments or examples.

[0229] Any process or method description shown in the flowchart or described in other ways herein can be understood as representing a module, segment, or part of code including one or more executable instructions for implementing a specific logical function or process. And the scope of the preferred embodiments of the present application includes additional implementations, where the functions can be executed in a substantially simultaneous manner or in the reverse order according to the involved functions, rather than in the order shown or discussed.

[0230] As mentioned above, the above are only the specific embodiments of the present application, but the protection scope of the present application is not limited thereto. Any person skilled in the art can easily think of various changes or substitutions within the technical scope disclosed in the present application, and these should all be covered by the protection scope of the present application. Therefore, the protection scope of the present application should be subject to the protection scope of the claims.

Claims

1. A method for predicting the maneuvering and aerodynamic loads of a multi-ducted variable cycle engine, characterized in that, include: Step 1: Receive flight altitude spectrum, normal overload spectrum data and flight Mach number data; Step 2: Classify flight actions based on the flight altitude spectrum and normal overload spectrum data, wherein the flight actions include climbing, diving, and level flight; Step 3: Use the rain flow counting method to filter the original load spectrum, screen out the loading and unloading paths, and remove the load cycles with amplitudes less than the threshold; Step 4: Extract the load data of the typical task segment and fit the three-parameter Weibull distribution using the bilinear regression method to obtain the load distribution characteristics of the typical task segment. The three-parameter Weibull distribution includes a scale parameter, a shape parameter, and a position parameter. Step 5: Establish a flight dynamics model and calculate the normal load coefficient based on the six-degree-of-freedom motion equation, lift coefficient, drag coefficient, and side force coefficient; Step 6: Verify the calculation accuracy of the normal load coefficient based on simulation calculations, flight data, and aerodynamic characteristics models. Step 7: Based on the airfoil data of the hypersonic aircraft, derive the maneuverability and aerodynamic load spectrum of the multi-bypass variable cycle engine in turbofan and turbojet modes.

2. The method for predicting the maneuvering and aerodynamic loads of a multi-ducted variable cycle engine according to claim 1, wherein The rules for dividing the flight actions are as follows: The vertical speed change of the aircraft is measured by a vertical speed meter or air pressure sensor to calculate the ascent and descent rate; If the rate of ascent and descent is greater than +5m / s, it is a climbing action; If the rate of ascent and descent is less than -5m / s, it is a dive; If the absolute value of the climbing rate is less than 5m / s, it is a level flight action; The flight control system obtains the ascent and descent rate in real time and determines the current flight action.

3. The method for predicting the maneuvering and aerodynamic loads of a multi-ducted variable cycle engine according to claim 1, wherein, The method of filtering the original load spectrum by using the rain flow counting method comprises the following steps: For the rising section of the load spectrum, filter out the data points where the load increments between two adjacent points are positive, and delete the data points where the increments are negative; For the descending section of the load spectrum, filter out the data points where the load increments between two adjacent points are negative, and delete the data points where the increments are positive; The original load data points are inserted between the filtered peak and valley values to ensure the complete loading and unloading path information; The calculation method of the threshold Δ% is: Δ%=(G max - G min )*ω%, where: G max is the upper limit of the load amplitude range for each cycle in the original load spectrum, G min is the lower limit of the load amplitude range for each cycle in the original load spectrum, and ω is an empirical constant with a value range of 8.0 to 12.

5.

4. The method for predicting the maneuvering and aerodynamic loads of a multi-duct variable cycle engine according to claim 1, wherein, The three-parameter Weibull distribution is fitted by the bilinear regression method, and the steps are as follows: Define the parameters of the regression model: is the shape parameter, representing the shape of the load distribution; is the location parameter, representing the location offset of the distribution; is the scale parameter, representing the scale of the load distribution; The linear regression equation is fitted by the least squares method, and the following formulas are established: Wherein: and are functional relationships for calculating regression parameters; The regression parameters are optimized by iterative method, and each iteration is updated using the following formula: where: f(β) is the objective function, f′(β) is the derivative of the objective function with respect to β, and β (n) is the n parameter value at the During the iteration process, a dynamic step size adjustment strategy is adopted to adjust the step size according to the change between the current error and the previous error; if the error changes too quickly, the step size is reduced; if the error changes slowly, the step size is increased; The accuracy calculation formula is as follows: Wherein: and represent the parameter values of the current and the previous iteration respectively; when the precision reaches the preset threshold, the iteration stops; The flight data is analyzed and divided into peak-type mission segments and load-holding mission segments based on the rotor speed spectrum. The three-parameter Weibull distribution is applied to the peak-type mission segments to fit their peak and valley values, and a distribution characteristic table containing scale parameters, shape parameters, and position parameters is output. The exponential distribution is applied to the load-holding mission segments to fit their load-holding time, and a distribution characteristic table containing scale parameters, shape parameters, and position parameters is output.

5. The method for predicting the maneuvering and aerodynamic loads of a multi-ducted variable cycle engine according to claim 1, wherein The flight dynamics model is established, comprising the following steps: Calculate the lift coefficient C L , the drag coefficient C D , and the side force coefficient C Z , and the calculation formula is as follows: where: ρ is the atmospheric density, v is the aircraft speed, S is the wing area, L is the lift, D is the drag, and Z is the side force; Calculate the Reynolds number Re, the calculation formula is: Where: v is the flight speed, ρ and μ are the velocity, density and dynamic viscosity of the fluid respectively, and l is the chord length of the wing; based on the calculated lift coefficient, drag coefficient and side force coefficient, the motion response of the aircraft is calculated by combining the six-degree-of-freedom motion equation, including the translational and rotational motions of the aircraft, and the normal overload coefficient is calculated. According to the flight data and the aerodynamic characteristic model, calculate the normal overload coefficient and verify it to ensure the calculation accuracy. Output the normal overload coefficient, fuel consumption rate, and engine thrust data as the input of the prediction model.

6. The method for predicting the maneuvering and aerodynamic loads of a multi-ducted variable cycle engine according to claim 1, wherein The steps for verifying the normal overload coefficient include: Based on the flight data and the aerodynamic characteristic model, verify the calculation accuracy of the normal overload coefficient through simulation calculation. By comparing the calculated value with the measured value, ensure that the root mean square error does not exceed 0.

05.

7. The method for predicting the maneuvering and aerodynamic loads of a multi-ducted variable cycle engine according to claim 1, characterized in that The method includes: Calculate the Reynolds number according to the flight altitude and Mach number. Based on the lift-drag characteristic data of the NASA a315-II airfoil, obtain the lift coefficient, drag coefficient and side force coefficient at the current angle of attack and Reynolds number through two-dimensional interpolation. Combined with the flight dynamics equation, calculate the normal overload spectrum and rotor speed spectrum in the turbofan mode and turbojet mode.

8. A prediction system for a multi-ducted variable cycle engine maneuvering and aerodynamic load prediction method according to any one of claims 1-7, characterized in that, Include: A data acquisition module for obtaining the flight altitude spectrum, normal overload spectrum, fuel consumption rate and engine thrust data. An action division module for dividing the climb, dive and level flight actions according to the climb rate threshold and marking them with different colors for distinction. A filtering processing module for performing rainflow counting method filtering, selecting effective load cycles and removing irrelevant cycle data; a distribution fitting module for solving the Weibull distribution parameters by using the bilinear regression method and generating the load distribution of the typical mission segment. A dynamics modeling module for integrating the six-degree-of-freedom motion equation and the lift-drag characteristic model and outputting the normal overload coefficient. An extended application module for adapting the airfoil parameters of high-speed aircraft and generating the maneuver and aerodynamic load spectra of multi-ducted variable cycle engines.

9. The multi-ducted variable cycle engine maneuvering and aerodynamic load prediction system according to claim 8, wherein The dynamics modeling module is implemented through a simulation platform, and the input parameters include the angle of attack, sideslip angle, bank angle, pitch angle, engine thrust and flight Mach number.

10. The multi-ducted variable cycle engine maneuvering and aerodynamic load prediction system according to claim 8, characterized in that, The extended application module includes: An airfoil database for storing the lift-drag characteristic data of high-speed aircraft airfoils at different Reynolds numbers. An interpolation calculation unit for dynamically calling the database data according to the current flight parameters. A load spectrum generation unit for outputting the normal overload spectrum and rotor speed spectrum in the turbofan mode and turbojet mode.

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