Method and device for acquiring performance parameters of engine based on air system

Abstract

The invention discloses an engine performance parameter obtaining method and device based on an air system, and the method comprises the steps: constructing a network model of an engine air system according to an engine profile map, the network model comprises a plurality of nodes and a plurality of elements, and each element / node is provided with at least one node pointing to other elements / nodes, the directed edge is used for representing the flowing direction; determining boundary conditions of an air system according to engine design requirements; determining a characteristic solving equation set of the air system according to the boundary condition and the network model; and performing iterative solution on the characteristic data of the air system based on the characteristic solution equation set to obtain the characteristic data of the air system. The building speed of the network model can be increased, and the precision of the obtained characteristic data can be improved.

Description

Technical Field

[0001] The present invention belongs to the technical field of aero-engines, and in particular relates to a method and a device for acquiring performance parameters of an engine based on an air system. Background Art

[0002] The air system of an aviation gas turbine engine is a flow network system composed of a series of pipes, holes, comb teeth, slits and other flow resistance elements on the engine parts, also known as secondary flow. Its main function is to extract a certain amount of gas from the compressor and other locations for cooling the hot end components, sealing the bearing cavity, balancing the axial force, anti-icing, etc. The characteristic data of the air system is an extremely important parameter in engine design. For example, the temperature field of the parts can be used to calculate the engine strength, and the air system can provide key heat transfer boundary conditions for the calculation of the temperature field of the parts.

[0003] However, the current methods for determining the characteristics of air systems are mostly designed only for certain components. The classification standards and calculation methods of components are not unified, which makes the construction of air systems slow, and the overall error of characteristic data is large, and the calculation accuracy is not high. Summary of the invention

[0004] The embodiments of the present invention provide a method and device for acquiring performance parameters of an engine based on an air system, which can solve the problems of low calculation accuracy and slow air system construction speed in current methods.

[0005] In a first aspect, an embodiment of the present invention provides a method for acquiring performance parameters of an engine based on an air system, the method comprising:

[0006] A network model of the engine air system is constructed according to the engine cross-sectional view, wherein the network model includes a plurality of nodes and a plurality of elements, and each element / node is provided with at least one directed edge pointing to other elements / nodes for indicating a flow direction;

[0007] Determine the boundary conditions of the air system according to the engine design requirements;

[0008] Solve the set of equations based on boundary conditions and network model to determine the characteristics of the air system;

[0009] The characteristic data of the air system are iteratively solved based on the characteristic solution equation group to obtain the characteristic data of the air system.

[0010] In a second aspect, an embodiment of the present invention provides a method for acquiring performance parameters of an engine based on an air system, including:

[0011] A model building module, the model building module is used to build a network model of the engine air system according to the engine cross-sectional view, wherein the network model includes a plurality of nodes and a plurality of elements, and each element / node is provided with at least one directed edge pointing to other elements / nodes for indicating a flow direction;

[0012] A boundary condition determination module, the boundary condition determination module is used to determine the boundary conditions of the air system according to the engine design requirements;

[0013] An equation determination module, the equation determination module is used to determine the characteristics of the air system according to the boundary conditions and the network model to solve the equation group;

[0014] The equation solving module is used to iteratively solve the characteristic data of the air system based on the characteristic solving equation group to obtain the characteristic data of the air system.

[0015] In a third aspect, an embodiment of the present invention provides an electronic device, comprising a processor and a memory, wherein the memory is used to store computer programs; the processor can be used to execute the computer program (instructions) stored in the memory to implement the method of the first aspect above.

[0016] In a fourth aspect, an embodiment of the present invention provides a computer-readable storage medium, in which a computer program is stored. When the computer program is executed, the method of the first aspect described above can be implemented.

[0017] Compared with the prior art, the embodiments of the present invention have the following beneficial effects: according to the method provided by the present invention, a one-dimensional flow network model of the air system is built instead of a three-dimensional model, which can improve the model building speed; a set of characteristic solution equations for the air system is constructed through the network model of the air system, and the characteristic data of each component and node in the air system are solved together; compared with the method of solving a single typical component and then merging the data, the coupling error of the present invention is smaller and the calculation accuracy is higher. BRIEF DESCRIPTION OF THE DRAWINGS

[0018] Figure 1 A flowchart of a method for acquiring engine performance parameters based on an air system provided by an embodiment of the present invention;

[0019] Figure 2 A schematic diagram of the structure of a network model of an air system provided by an embodiment of the present invention;

[0020] Figure 3 A schematic diagram of a solution correction process using a Newton-Raphson method provided in an embodiment of the present invention;

[0021] Figure 4A flow chart of a method for solving a characteristic equation group of an air system based on the Newton-Raphson method provided in an embodiment of the present invention;

[0022] Figure 5 A schematic structural diagram of a sealing grate tooth provided in an embodiment of the present invention;

[0023] Figure 6 A schematic diagram of the structure of a device for acquiring performance parameters of an engine without an air system provided by an embodiment of the present invention;

[0024] Figure 7 A schematic diagram of the structure of an electronic device provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0025] In the following description, specific details such as specific system structures, technologies, etc. are provided for the purpose of illustration rather than limitation, so as to provide a thorough understanding of the embodiments of the present invention. However, it should be clear to those skilled in the art that the present invention may be implemented in other embodiments without these specific details. In other cases, detailed descriptions of well-known systems, devices, circuits, and methods are omitted to prevent unnecessary details from obstructing the description of the present invention.

[0026] It should be understood that when used in the present specification and the appended claims, the term "comprising" indicates the presence of described features, integers, steps, operations, elements and / or components, but does not exclude the presence or addition of one or more other features, integers, steps, operations, elements, components and / or combinations thereof.

[0027] It should also be understood that the term "and / or" used in the present description and the appended claims refers to and includes any and all possible combinations of one or more of the associated listed items.

[0028] As used in the present specification and the appended claims, the term "if" may be interpreted as "when" or "upon" or "in response to determining" or "in response to detecting", depending on the context. Similarly, the phrase "if it is determined" or "if [described condition or event] is detected" may be interpreted as meaning "upon determination" or "in response to determining" or "upon detection of [described condition or event]" or "in response to detecting [described condition or event]", depending on the context.

[0029] In addition, in the description of the present specification and the appended claims, the terms "first", "second", "third", etc. are only used to distinguish the descriptions and cannot be understood as indicating or implying relative importance.

[0030] References to "one embodiment" or "some embodiments" etc. described in the present specification mean that one or more embodiments of the present invention include specific features, structures or characteristics described in conjunction with the embodiment. Therefore, the statements "in one embodiment", "in some embodiments", "in some other embodiments", "in some other embodiments", etc. that appear in different places in this specification do not necessarily refer to the same embodiment, but mean "one or more but not all embodiments", unless otherwise specifically emphasized in other ways. The terms "including", "comprising", "having" and their variations all mean "including but not limited to", unless otherwise specifically emphasized in other ways.

[0031] The present invention is further described in detail below with reference to specific embodiments, but the embodiments of the present invention are not limited thereto.

[0032] The method for determining the characteristics of an engine air system provided in the embodiment of the present invention can be applied to electronic devices such as mobile terminals, personal notebook computers, supercomputers, etc. The embodiment of the present invention does not impose any limitation on the specific type of electronic devices.

[0033] Example 1

[0034] Figure 1 The flowchart shown is a method for obtaining engine performance parameters based on an air system according to an embodiment of the present invention. The method can be applied to the above electronic device, and the method can include steps S101-S104, and each step is described below.

[0035] S101, constructing a network model of the engine air system according to the engine cross-section diagram.

[0036] In some embodiments, the flow path of the air system is very complex. Using a three-dimensional model for analysis not only consumes computing resources but also makes it difficult to achieve the required accuracy. The flow network method is an abstract method that represents each typical component of the engine with an element and the connecting parts of each component with a node. Due to the rapidity and accuracy of the flow network method, it is widely used in the design of air systems. There are many components in the air system of an aircraft engine, and the types are relatively complex. For an entire machine's air system, it may contain hundreds or thousands of components; therefore, when using the one-dimensional fluid network method for analysis, the entire machine's air system can be decomposed into several sub-network models according to specific functions. After calculating these sub-networks, the sub-networks are then connected together to construct a network model of the entire machine's air system.

[0037] In a possible implementation, the components may be arranged according to the engine cross-sectional view, and then the connection relationship of each component and the position of the node may be determined according to the air flow path to obtain a network model of the air system.

[0038] For example, according to the design requirements of the engine, the cooling, anti-icing and other functions that the air system needs to meet can be clarified, and parameter values ​​such as the target pre-turbine temperature can be set to determine the distribution of air flow in each flow path.

[0039] For example, see Figure 2 The network model of the air system can include multiple components and nodes. Each component / node is provided with at least one directed edge pointing to other components / nodes. The direction of the directed edge can indicate the flow direction of the air; the node is the intersection of the branches of each component. The characteristic data of the air system can include the pressure and dimension of each node, the flow rate and speed of the component, etc.

[0040] In one example, the components in an engine can be divided into zero-dimensional components, one-dimensional components, and interface components. Zero-dimensional components are generally shorter components whose cumulative effects of mass and energy can be ignored, such as holes and local losses. One-dimensional components are opposite to zero-dimensional components, whose mass, energy, and cumulative effects must be considered in the calculation, such as long tubes and disk cavities. Interface components refer to the parts that connect different components, such as the hole structure composed of the opening on the disk and the rotating disk cavity.

[0041] S102, determining the boundary conditions of the air system according to the design requirements of the engine.

[0042] In one example, the boundary conditions of the air system may include inlet and outlet pressures, inlet and outlet temperatures, etc. of the air system.

[0043] For example, in actual calculations, the boundary conditions of the air system may generally include inlet total pressure and inlet temperature, and outlet static pressure. In some cases, the boundary conditions may also include inlet flow rate, inlet temperature, and outlet static pressure.

[0044] S103, determining the characteristics of the air system and solving the equation group according to the boundary conditions and the network model of the air system.

[0045] In a possible implementation, a characteristic solution equation group of the air system can be combined based on the flow equations of each element, the flow equations of each node, and the energy equations of each node, thereby converting the solution of the fluid network into the solution of the equation group.

[0046] In one example, the flow equation of a component can be used to describe the flow characteristics of the component, and its parameters include the pressure and flow rate upstream and downstream of the component. Since the pressure and mass flow rate of the component are generally functions related to time, the flow equation of the component can satisfy the following formula:

[0047] F[p1(t),p2(t),m1(t),m2(t)]=0(1.1)

[0048] Where F[·] represents the flow equation, p1(t) and p2(t) are the upstream pressure and downstream pressure of the element, respectively, and m1(t) and m2(t) are the upstream flow rate and downstream flow rate of the element, respectively.

[0049] In one example, the flow equation of the node is determined according to the mass conservation relationship of the node, which can satisfy the following formula:

[0050]

[0051] Among them, F′ n is the flow equation of node n, m i is the flow rate of element i connected to node n, and N is the total number of elements in the air system.

[0052] For example, in the flow equation of the node, the flow to the node can be set as positive and the flow out of the node can be set as negative.

[0053] It should be understood that in the flow equation, i does not necessarily have continuous values. If node n is connected to element 1, element 2, and element 4, then i=1, 2, 4.

[0054] In one example, one of the main functions of the air system is to cool down high-temperature components and prevent ice on low-temperature components. Its cooling and heat exchange have a vital impact on the stable operation of the engine; therefore, heat exchange calculation of the air system is an indispensable link. For aircraft engines, the fluid medium used in the air cooling system and the hot gas anti-icing system is generally the high-pressure air drawn from the compressor. The cooling system needs to cool mainly the combustion chamber flame tube wall, turbine guide vanes and working blades, turbine wheel and high-temperature casing, etc. The anti-icing system needs to de-heat the engine inlet straightening cone, inlet guide vanes and compressor working blades that may be frozen. The operating temperatures of the cooling system and the anti-icing system are very different, but their air properties are similar and the basic heat exchange laws are the same, so a similar method can be used to calculate the heat exchange of the cooling system and the anti-icing system. Therefore, the energy conservation equation of each node can be obtained based on the convective heat exchange heat between the gas and the pipeline. Without considering the effect of rotation and considering the convective heat exchange between the wall and the element, the energy equation of each node is obtained according to the energy conservation equation of each node.

[0055] For example, the convective heat transfer between the gas and the pipeline can satisfy the following formula:

[0056]

[0057] Where dq is the convective heat transfer between the airflow and the pipe when it passes through a micro-element end of the pipe, h is the convective heat transfer coefficient, T w is the average temperature of the wall around the pipe, T is the temperature, u is the gas density, C p is the specific heat capacity, and A is the flow area, which is equal to the cross-sectional area of ​​the pipe here.

[0058] Exemplarily, the energy equation of a node may satisfy the following formula:

[0059]

[0060] Among them, T j is the temperature of node j, in is the set of nodes that input energy to node i′, m i′j is the flow between node i′ and node j, and out is the set of nodes that absorb energy from node i′.

[0061] Exemplarily, the characteristic solution equations of the air system may include the flow equations of the entire element, the flow equations of the node global, and the energy equations of the node global. The flow equations of each element may be combined to obtain the flow equations of the air system, and the flow equations of each node may be combined to obtain the flow equations of the air system.

[0062] For example, Figure 2 Taking the air system in the figure as an example, the flow equations in the steady state can satisfy the following formula:

[0063]

[0064] Among them, F i [·] represents the flow equation of element i, where i is a positive integer less than or equal to N, and N is the total number of elements, where N=4; p1 is the downstream pressure of element 1, and also the upstream pressure of elements 2 and 3; p2 is the downstream pressure of elements 2 and 3; p4 is the upstream pressure of element 4; m i is the flow rate of element i.

[0065] For example, Figure 2 Taking the air system in as an example, its flow equation group can satisfy the following formula:

[0066]

[0067] S104, iteratively solving characteristic data of the air system based on the characteristic solution equation group to obtain the characteristic data of the air system.

[0068] In one possible implementation, typical elements of the air system include holes, pre-swirl nozzles, local losses, channels, sealing grates, rotating disc cavities, rim seals, spoiler columns, leading edge impacts, mid-chord impacts, etc. These elements have different flow and heat transfer characteristics, and the equations generally have very strong nonlinearity, which undoubtedly increases the difficulty of air system calculations. Since the equations for solving the characteristics of the air system have strong nonlinearity and cannot be directly decomposed and solved, the characteristic data of the air system can be solved by iteration.

[0069] In one example, the system of equations may be solved based on the Newton-Raphson method to solve the characteristics of the air system.

[0070] Exemplarily, the principle of the Newton-Raphson method for solving a system of equations is to find the partial derivatives of the function with respect to each variable, solve the residual system of equations based on the partial derivatives to obtain the tangent line of the characteristic solution system of equations at the current assignment point, take the intersection of the tangent line and the coordinate axis as the correction value of the current assignment point, and repeat the above process until the correction value and the residual value of the current assignment reach the convergence criterion.

[0071] For example, see Figure 3 , Figure 3 Where X0 is the true solution of the equation, and the solution is corrected from X1 to X3 by the Newton-Raphson method. In this process, the error between the numerical solution and the true solution is constantly decreasing. Therefore, the Newton-Raphson method can continuously approach the true solution.

[0072] For example, taking the flow equation in the characteristic equation group as an example, the flow equation (i.e., formula (1.1)) can be differentiated to obtain the following Newton-Raphson iterative equation, where the left side of the equation is the differential of the variable and the right side is the residual of the equation:

[0073]

[0074] Only p1, p2, m1, and m2 here have the same meanings as p1(t), p2(t), m1(t), and m2(t) in formula (1.1), respectively.

[0075] Specifically, Figure 2 Taking the pressure of the air system in as an example, we can first set the initial values ​​of p1 and p2 respectively. The flow value is similar. Then substitute it into the above formula (1.7) to solve the residual equation group and obtain the correction amount of each characteristic data. If the residual between the correction amount and the initial value does not meet the convergence standard, the correction amount is used as a reference to re-assign the pressure value and flow value.

[0076] According to the method provided by the present invention, a one-dimensional flow network model of the air system is built instead of a three-dimensional model, which can improve the speed of model building; a set of equations for solving the characteristics of the air system is constructed through the network model of the air system, and the characteristic data of each component and node in the air system are solved together; compared with the method of solving a single typical component and then merging the data, the coupling error of the present invention is smaller and the calculation accuracy is higher.

[0077] Example 2

[0078] Figure 4 The flowchart of a method for solving a characteristic equation group of an air system based on the Newton-Raphson method provided by an embodiment of the present invention is shown. As an example but not a limitation, the method may include S401-S404, and each step is described below.

[0079] S401, substituting the kth set of characteristic data into the characteristic solving equation group of the air system to obtain the kth characteristic solving equation group.

[0080] Exemplarily, the kth group of characteristic data may include the kth mass, kth flow rate and kth temperature of each component in the air system, and the kth mass, kth flow rate and kth temperature of each node.

[0081] S402, taking partial derivatives of the characteristic data in the k-th characteristic solution equation group to obtain a residual equation group, and solving the residual equation group to correct the characteristic data to obtain a correction amount of the k-th group of characteristic data (i.e., the k+1-th group of characteristic data), thereby obtaining a residual value of the k-th group of characteristic data.

[0082] In one example, since the change of physical properties in the air system will affect the values ​​of pressure and flow, the characteristic solution equations of the air system are highly nonlinear, and the coefficients will keep changing. Therefore, based on the steady-state approximation method, the k+1th flow and pressure of each node and each element can be solved according to the kth characteristic solution equations; and then the k+1th temperature of each node and each element can be solved according to the k+1th flow and pressure of each node and each element.

[0083] For example, in order to ensure the stability of the calculation, the time step for transient solution based on the steady-state approximation method must satisfy the following formula:

[0084]

[0085] Where Δt is the time step, ν is the CFL number, Δx is the grid size, and c is the wave speed.

[0086] Similarly, in order to ensure the stability of transient solutions, the solution process can adopt the method of constant grid size and variable time step. Before the calculation of each transient time step begins, each component can be traversed to calculate the maximum time step that satisfies the calculation stability of all components, and this can be used as the size of the time advancement step.

[0087] S403, determining whether the residual value of the kth group of characteristic data meets the convergence standard.

[0088] In one example, if the residual value of the kth set of characteristic data does not meet the convergence criterion, k may be set to k+1, and iteration may continue according to the k+1th set of characteristic data.

[0089] Exemplarily, it is possible to determine whether the kth group of characteristic data meets the convergence criteria by judging whether the absolute value of the residual value is less than or equal to the convergence threshold, that is, by the following formula (1.9):

[0090]

[0091] in, is the kth flow rate of element i, for The correction amount (i.e. the k+1th flow rate of element i), is the kth pressure of element i, for The correction amount, 10 -3 is the convergence threshold.

[0092] Specifically, formula (1.9) shows that when the difference between the k+1th assignment and the kth assignment of the mass flow / pressure of each element is less than 0.001 times its kth assignment, the convergence state is reached.

[0093] For example, due to the strong nonlinearity of the equations to be solved for the characteristics of the air system, the convergence factor is generally set relatively small, so convergence under steady-state conditions often requires dozens of iterations or more.

[0094] It should be understood that 10 -3 This is only an example of a convergence threshold. Users can select appropriate convergence criteria according to different working conditions to achieve a balance between solution accuracy and computing resources.

[0095] In another example, if the residual value of the kth group of characteristic data meets the convergence criterion, step S404 may be performed to output the kth group of characteristic data as characteristic data of the air system.

[0096] S404: Output the kth group of characteristic data as characteristic data of the air system.

[0097] Solving a system of equations with strong nonlinear characteristics based on the Newton-Raphson method can reduce the computational complexity.

[0098] For the above step S402, the k+1th flow rate, pressure and temperature of different types of components may be determined specifically by the methods shown in the following embodiments 3 to 5.

[0099] Example 3

[0100] In some embodiments, the length of the zero-dimensional element is generally very short, and the cumulative effect of energy and mass in its flow process can be ignored. Therefore, the k+1th mass flow rate can be calculated based on the steady-state formula using the aerodynamic parameters of the inlet and outlet of the element in the kth set of characteristic data.

[0101] As an example, a hole is a zero-dimensional element, and its flow rate is proportional to the flow coefficient, which is affected by parameters such as hole geometry and rotation. Therefore, the k+1th mass flow rate of the hole can be determined based on the first flow solution model with the flow coefficient involved in the calculation. Since the gas flows through the hole for a very short time, the heat transfer characteristics of the hole are generally not considered.

[0102] In a possible implementation, the first flow solution model may satisfy the following formula:

[0103]

[0104] Where m is the flow rate, C d is the pore flow coefficient, γ is the specific heat ratio, A is the flow area, here is the pore flow area, R is the gas constant, T1 * is the total inlet temperature, p1 * is the total inlet pressure, p2 * is the outlet static pressure.

[0105] For example, Figure 2 Taking element 2 in the figure as an example, the kth pressure of node 1 can be taken as p1 * , the kth pressure p2 of node 2 * , the kth temperature of element 2 is taken as T1 * Substituting into the above formula (1.10), we get the k+1th flow rate of element 2.

[0106] For example, the flow velocity in the hole cannot exceed the speed of sound. After the ratio of the outlet static pressure to the inlet total pressure reaches a critical value, reducing the outlet static pressure cannot increase the flow through the hole. This situation is called "blockage". According to the blockage characteristics of the hole, the hole can play a role in limiting the flow.

[0107] In one example, the flow coefficient of a hole is not necessarily a constant. The flow coefficient of a hole generally depends on factors such as the pressure ratio, the hole aspect ratio, and the chamfer. In addition, the flow coefficient of a rotating hole is also related to the ratio of the tangential velocity of the hole to the axial velocity of the airflow in the hole. Therefore, when calculating the flow of a rotating hole, the hole flow coefficient needs to be corrected.

[0108] For example, the orifice flow coefficient C′ of the rotating orifice is d The following formula can be satisfied:

[0109]

[0110] Among them, C d1 is the flow coefficient when passing through a stationary hole under the same conditions, u″ is the circumferential speed of the hole rotation, and v is the speed when passing through a stationary hole under the same conditions.

[0111] Optionally, in the air system, in order to reduce the loss of the hole and increase the flow coefficient of the hole, a chamfer may be added to the hole.

[0112] As an example, local loss is one of the most common elements in air systems and is also a typical zero-dimensional element. It is generally used to abstractly simulate the pressure loss of gas flowing through a complex geometry. Local loss includes three types of loss elements: sudden expansion, sudden contraction, and given pressure loss coefficient.

[0113] For local loss elements, the total pressure drop at the inlet and outlet is proportional to the square of the velocity. Therefore, the k+1th pressure data of the local loss element should satisfy the following pressure loss constraints:

[0114]

[0115] Among them, ξ is the element loss coefficient, ρ is the average gas density, and v′ is the gas flow velocity.

[0116] In a possible implementation, the loss coefficient of the local loss element has a certain relationship with the geometry and flow conditions of the element.

[0117] In one example, taking the sudden expansion element as an example, its loss coefficient can satisfy the following formula:

[0118]

[0119] in, A1 is the element inlet area, and A2 is the element outlet area.

[0120] In another example, taking a sudden expansion element as an example, its loss coefficient can satisfy the following formula:

[0121]

[0122] Example 4

[0123] In some embodiments, since the one-dimensional element is long, it needs to be segmented in the flow direction to simulate the accumulation effect occurring inside it.

[0124] In one possible implementation, the continuity equation, momentum equation and energy equation of the transient pipe flow can be determined based on the control equation of the flow in the transient compressible pipe, and then the three equations are solved based on the Lax-Windloff method to obtain the fluid flow characteristic parameters of the element. Finally, the kth flow rate, kth pressure and kth temperature of the element are substituted into the solution model determined according to the fluid flow characteristic parameters of the element to obtain the k+1th flow rate, pressure and temperature of the element.

[0125] In one example, the governing equation for the flow in a transient compressible tube can satisfy the following formula:

[0126]

[0127] Where W is the fluid flow characteristic parameter, x is the flow direction, t is the time, F″ is the mass flow, momentum flow or energy flow, and C is the source term, which can include the change of flow area, the influence of friction and heat transfer.

[0128] Exemplarily, the continuity equation of transient pipe flow may satisfy the following formula:

[0129]

[0130] Among them, ρ is density, p is static pressure, A is flow area, u′ is gas velocity, and k is adiabatic index.

[0131] Exemplarily, the momentum equation of transient pipe flow may satisfy the following formula:

[0132]

[0133] Exemplarily, the momentum equation of transient pipe flow may satisfy the following formula:

[0134]

[0135] Where f′ is the friction term and q is the heat flow per unit area per unit time.

[0136] In one example, the characteristic linear method can generally be used to solve the fluid flow characteristic parameters of transient compressible perfusion. However, in practical applications, the characteristic linear method has high requirements for the steady-state initial field and is not stable enough over time. Therefore, the two-step Lax-Wendlov method can be used to solve the continuity equation, momentum equation, and energy equation of transient pipe flow.

[0137] Exemplarily, the fluid flow characteristic parameters obtained based on the two-step Lax-Wendlov method can satisfy the following formula:

[0138]

[0139] Where n is the number of time steps, and j is the number of the grid nodes in the tube. The n+1th time step is later than the nth time step. Represents the intermediate value between the n+1th time step and the nth time step.

[0140] As an example, a sealing grate is a typical one-dimensional component. Sealing grate is a commonly used sealing structure in air systems and is widely used in various types of aircraft engines and gas turbines. Sealing grate is used to reduce pressure and seal gas, and its sealing characteristics have a vital impact on the performance of the engine. Figure 5 The sealing grate teeth can be divided into three types according to the tooth shape: straight teeth, helical teeth and step teeth.

[0141] In a possible implementation, the actual flow rate solution model obtained by the sealing grate teeth according to the fluid flow characteristic parameters can satisfy the following formula:

[0142] m=m id C d KK1 (1.21)

[0143] in:

[0144]

[0145] Among them, m id is the ideal flow rate of the sealing grate teeth, S is the tooth pitch, C' is the tooth top clearance, and N' is the number of teeth of the sealing grate teeth.

[0146] In one example, the sealing grate is sealed by momentum dissipation. When the airflow passes through the sealing grate, part of the pressure head is converted into kinetic energy and enters the small cavity between the sealing grate at a very high speed. Since the kinetic energy dissipation is relatively large when the gas flows at high speed, the gas pressure is reduced, and the sealing effect is finally achieved. Therefore, when the gas passes through the sealing grate, there will be a relatively large pressure drop at the inlet and outlet. The pressure loss of the sealing grate can satisfy the following formula:

[0147]

[0148] in, b is the empirical coefficient, which is generally 1.2 for straight teeth, 0.9 for helical teeth, and 0.7 for step teeth. A is the flow area, which is the flow area of ​​the sealing grate teeth here; m is the flow rate of the sealing grate teeth.

[0149] As another example, film holes are another typical one-dimensional element. Film holes are important elements used in blade film cooling, which are used to cool the surface of turbine blades. Film cooling is a thermal protection measure that uses a nozzle on the wall of a turbine blade to eject a stream of cold air to block the mainstream high-temperature combustion gas from damaging the wall. The flow characteristics of the film hole play a key role in the heat dissipation of the blade.

[0150] In a possible implementation, the flow solution model of the air film hole is similar to that of the hole based on the flow characteristic parameters of the fluid, and the details can be seen in the above formula (1.10); the only difference between the two is the calculation of the flow coefficient.

[0151] In one example, the flow coefficient of the air film hole may satisfy the following formula, which specifically depends on the blowing ratio of the air film hole:

[0152]

[0153] in:

[0154] Re=m′2d / μA

[0155] Among them, Re is the Reynolds number of the air film hole flow, m′2 is the input flow rate of the air film hole, d is the equivalent diameter of the air film hole, h is the height of the air film hole channel, μ is the dynamic viscosity of the air film hole, and A is the flow area, which is the air film hole area here.

[0156] Exemplarily, the blowing ratio M of the air film hole may satisfy the following formula:

[0157] M=ρ2u2 / ρ m u m (1.24)

[0158] Among them, ρ2 is the average density of the secondary flow, u2 is the average velocity of the secondary flow, ρ m is the mainstream average density, u m is the mainstream average flow velocity.

[0159] For example, the air film holes, like general hole elements, have the characteristic of "clogging".

[0160] As another example, the channel element is another typical one-dimensional element. Channel elements are generally used to simulate the cooling channel inside the turbine blade, which has both flow and heat transfer characteristics. The cross-section of the channel can be rectangular, circular or irregular. The radial straight-through internal flow channel of the blade is the simplest and most effective cooling method inside the blade. The cooling air inside the blade flows directly through the inner cavity of the guide vane in the radial direction, and absorbs heat through the convection heat exchange between the cold air and the blade wall to achieve the purpose of reducing the surface temperature of the blade. Under the condition of a certain amount of cooling air, due to the relatively low convection heat transfer coefficient of this method, the cooling effect is also relatively limited. When the cold air usage is 2%, the blade temperature can generally be reduced by 80 to 140 degrees Celsius. For a general straight-through inner cavity, the calculation can be approximated using the pipe formula of circular, rectangular and other shapes according to the shape of the cavity cross-section.

[0161] For example, the heat transfer coefficient is the key to heat transfer calculation. The heat transfer coefficient of a smooth channel depends on the friction coefficient and the Nusselt number of the channel; the heat transfer coefficient of a non-smooth channel (such as a ribbed channel) mainly depends on its roughness function.

[0162] In a possible implementation, the friction coefficient and Nusselt number of the smooth channel can satisfy the following formulas:

[0163]

[0164] Where L is the channel length and D is the channel hydraulic diameter.

[0165] Nu=(f / 2)RePr / [1.07+12.7(f / 2) 1 / 2 (Pr 2 / 3 -1)] (1.26)

[0166] Among them, Pr is the Prandtl number, which is generally taken as 0.7.

[0167] In another possible implementation, in actual use, in order to improve the heat transfer coefficient of the cooling channel in the blade and thus enhance the heat transfer inside the blade, ribs are usually added to the cooling channel in the blade. In a static ribbed channel, the heat transfer performance mainly depends on the channel width-to-height ratio, the fin structure, and the Reynolds number of the airflow. For a ribbed channel, its roughness function can satisfy the following formula:

[0168]

[0169] Among them, f is the friction coefficient, W is the width of the fins in the channel, e′ is the height of the fins in the channel, D is the hydraulic diameter of the channel, and H is the height of the channel.

[0170] Exemplarily, the heat transfer roughness function G of the ribbed channel may satisfy the following formula:

[0171]

[0172] Wherein, St is the average Stent number of the cold air on the ribbed side wall.

[0173] Example 5

[0174] In some embodiments, the interface element may include complex elements such as a rotating disc cavity. The volume of the interface element is relatively large, and the volume response in a transient state is relatively obvious.

[0175] As an example, a rotating disk cavity is a typical interface element. The disk cavity is generally composed of a chamber composed of two wheels. Its geometry is relatively complex and irregular. Because it involves high-speed rotation, its flow and heat transfer are the most complex, and it presents different characteristics with different geometric conditions and boundaries. According to its rotation form, the disk cavity can generally be divided into a rotating-static system disk cavity and a rotating-rotating system disk cavity. The rotating-static system represents a chamber composed of a rotating and a stationary wheel, and the rotating-rotating system represents a chamber composed of two rotating wheels.

[0176] For example, if the rotation effect in the disc cavity is considered, the radial velocity in the disc cavity is ignored, the volume of the chamber is constant, and the inlets and outlets of the rotating disc cavity are regarded as holes, the mass conservation equation and energy conservation equation of the rotating disc cavity can be obtained based on the cavity's flushing and deflation theory. The flow rate solution formula can be obtained by analyzing these two equations. The average density and pressure in the next time step in the cavity can be obtained by solving the pressure equation and the ideal gas state equation based on the rotating disc cavity.

[0177] In a possible implementation, the mass conservation equation and energy conservation equation of the rotating disk cavity may satisfy the following formulas respectively:

[0178]

[0179] Where V is the volume of the rotating disk cavity, M is the number of external inflow boundaries, and m o,r is the mass flow rate of the substance entering the system through the external inflow boundary r, N″ is the number of internal outflow boundaries, m i,s is the mass flow rate of the substance flowing out of the system through the internal outflow boundary s.

[0180] Where e is the internal energy of the gas, h o,r is the mass entering the system through the external inflow boundary r, h i,s is the mass flowing out of the system through the internal outflow boundary s, Q htc is the convective heat transfer energy, Q wind is the wind resistance temperature rise energy.

[0181] Exemplarily, the energy conservation equation of the rotating disk cavity can also be expressed as:

[0182] C p Δt=hA(T w -T a )+Mω(1.31)

[0183] Where M is the torque and h is the convective heat transfer coefficient.

[0184] In one example, the flow rate of the rotating disc cavity is calculated in the same manner as the hole, and the details can be found in the above formula (1.10).

[0185] For example, the hole flow coefficient of the rotating disk cavity can be obtained by interpolation according to factors such as the aspect ratio, pressure ratio and rotation speed of the rotating disk cavity.

[0186] In one example, the pressure equation for the rotating disk cavity may satisfy the following formula:

[0187]

[0188]

[0189] Exemplarily, the flow pressure loss of the rotating disc cavity may satisfy the following formula:

[0190]

[0191] in, is the relative total pressure at the inlet, is the relative total pressure at the outlet, SPR is the pressure change caused by rotation, and K is the proportionality coefficient.

[0192] in:

[0193]

[0194] Among them, V t is the tangential velocity.

[0195] In a possible implementation, the heat transfer coefficient of the rotating disk cavity also mainly depends on the friction coefficient and the Nusselt number.

[0196] In one example, the friction coefficient of the rotating disk cavity may satisfy the following formula:

[0197]

[0198] Where k is the average roughness.

[0199] Exemplarily, the torque τ on the rotating disk cavity surface may satisfy the following formula:

[0200]

[0201] Where r is the radius of the disk cavity, ω d is the angular velocity of the wheel, ω a is the gas rotation angular velocity, C τ is the torque coefficient.

[0202] In one example, the heat transfer of the disk cavity takes into account the convective heat transfer and the temperature rise caused by wind resistance on the gas, and its Nusselt number can satisfy the following formula:

[0203]

[0204] Among them, Nu lam is the laminar Nusselt number, Nu tur is the turbulent Nusselt number, and j is the proportional coefficient of laminar flow.

[0205] Exemplarily, the energy conservation equation of the rotating disk cavity may satisfy the following formula:

[0206] C p Δt=hA(T w -T a )+Mω(1.37)

[0207] Where M is the torque and h is the convective heat transfer coefficient.

[0208] Example 6

[0209] Figure 6 The structure diagram of a performance parameter acquisition device of an engine based on an air system provided by an embodiment of the present invention is shown. As an example but not limitation, the device 600 may include a model building module 610, a boundary condition determination module 620, an equation determination module 630, and an equation solving module 640.

[0210] Exemplarily, the model building module is used to build a network model of the engine air system based on the engine cross-section diagram, wherein the network model includes multiple nodes and multiple elements, and each element / node is provided with at least one directed edge pointing to other elements / nodes for indicating the flow direction; the boundary condition determination module is used to determine the boundary conditions of the air system according to the engine design requirements; the equation determination module is used to determine the characteristic solution equation group of the air system according to the boundary conditions and the network model; the equation solving module is used to iteratively solve the characteristic data of the air system based on the characteristic solution equation group to obtain the characteristic data of the air system.

[0211] According to the device provided by the present invention, a one-dimensional flow network model of the air system is built instead of a three-dimensional model, which can improve the speed of model building; a set of equations for solving the characteristics of the air system is constructed through the network model of the air system, and the characteristic data of each component and node in the air system are solved together; compared with the method of solving a single typical component and then merging the data, the coupling error of the present invention is smaller and the calculation accuracy is higher.

[0212] Example 7

[0213] Figure 7 FIG. 1 is a schematic diagram of the structure of an electronic device provided by an embodiment of the present invention. Figure 7 The electronic device 700 shown may include: at least one processor 710 ( Figure 7 Only one processor is shown in the figure), a memory 720, and a computer program 730 stored in the memory 720 and executable on the at least one processor 710, wherein the processor 710 implements the steps of any of the above-mentioned method embodiments when executing the computer program 730.

[0214] The electronic device 700 may be a processing device such as a robot that can implement the above method. The embodiment of the present invention does not impose any limitation on the specific type of the electronic device.

[0215] Those skilled in the art will understand that Figure 7 The electronic device 700 is merely an example and does not constitute a limitation on the electronic device. The electronic device 700 may include more or fewer components than shown in the figure, or may combine certain components, or may include different components. For example, the electronic device 700 may also include an input and output interface.

[0216] The processor 710 may be a central processing unit (CPU), or other general-purpose processors, digital signal processors (DSP), application-specific integrated circuits (ASTC), field programmable gate arrays (FPGA) or other programmable logic devices, discrete gates or transistor logic devices, discrete hardware components, etc. A general-purpose processor may be a microprocessor or any conventional processor, etc.

[0217] The memory 720 may be an internal storage unit in some embodiments, such as a hard disk or a memory. The memory 720 may also be an external storage device in other embodiments, such as a plug-in hard disk, a smart memory card (SmartMemory Card, SMC), a secure digital (Secure Digital, SD) card, a flash card (Flash Card), etc. Further, the memory 720 may also include both an internal storage unit and an external storage device. The memory 720 is used to store an operating system, an application program, a boot loader (Boot Loader), data, and other programs, such as the program code of the computer program, etc. The memory 720 may also be used to temporarily store data that has been output or is to be output.

[0218] It should be understood that the order of execution of the steps in the above embodiment does not necessarily mean the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiment of the present invention.

[0219] Those skilled in the art can clearly understand that for the convenience and simplicity of description, only the division of the above-mentioned functional units and modules is used as an example for illustration. In practical applications, the above-mentioned function allocation can be completed by different functional units and modules as needed, that is, the internal structure of the device can be divided into different functional units or modules to complete all or part of the functions described above. The functional units and modules in the embodiment can be integrated into a processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The above-mentioned integrated unit can be implemented in the form of hardware or in the form of software functional units. In addition, the specific names of the functional units and modules are only for the convenience of distinguishing each other, and are not used to limit the scope of protection of the present invention. The specific working process of the units and modules in the above-mentioned system can refer to the corresponding process in the aforementioned method embodiment, which will not be repeated here.

[0220] An embodiment of the present invention further provides a computer-readable storage medium, wherein the computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the steps in the above-mentioned method embodiments can be implemented.

[0221] An embodiment of the present invention provides a computer program product. When the computer program product runs on an electronic device, the electronic device can implement the steps in the above-mentioned method embodiments when executing the computer program product.

[0222] If the integrated unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the present invention implements all or part of the processes in the above-mentioned embodiment method, which can be completed by instructing the relevant hardware through a computer program. The computer program can be stored in a computer-readable storage medium. When the computer program is executed by the processor, the steps of the above-mentioned various method embodiments can be implemented. Among them, the computer program includes computer program code, and the computer program code can be in source code form, object code form, executable file or some intermediate form. The computer-readable medium can at least include: any entity or device that can carry the computer program code to the camera / terminal device, recording medium, computer memory, read-only memory (ROM, Read-Only Memory), random access memory (RAM, RandomAccess Memory), electric carrier signal, telecommunication signal and software distribution medium. For example, a USB flash drive, a mobile hard disk, a magnetic disk or an optical disk. In some jurisdictions, according to legislation and patent practice, computer-readable media cannot be electric carrier signals and telecommunication signals.

[0223] In the above embodiments, the description of each embodiment has its own emphasis. For parts that are not described or recorded in detail in a certain embodiment, reference can be made to the relevant descriptions of other embodiments.

[0224] Those skilled in the art will appreciate that the units and algorithm steps of each example described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. Professional and technical personnel can use different methods to implement the described functions for each specific application, but such implementation should not be considered to be beyond the scope of the present invention.

Claims

1. A method for obtaining performance parameters of an engine based on an air system, characterized in that: include: Constructing a network model of the engine air system according to the engine cross-sectional view, wherein the network model includes a plurality of nodes and a plurality of elements, and each element / node is provided with at least one directed edge pointing to other elements / nodes for indicating a flow direction; Determining boundary conditions of the air system according to engine design requirements; Determine the characteristics of the air system and solve a set of equations according to the boundary conditions and the network model; The characteristic data of the air system is iteratively solved based on the characteristic solving equation group to obtain the characteristic data of the air system.

2. The method according to claim 1, characterized in that The types of the elements include zero-dimensional elements, one-dimensional elements and interface elements. The mass accumulation effect and energy accumulation effect of the zero-dimensional elements are negligible, while the mass accumulation effect and energy accumulation effect of the one-dimensional elements are not negligible. The interface elements are used to connect different elements.

3. The method according to claim 1, characterized in that The characteristic data of the air system includes one or more of the following: pressure of a node, flow rate of a node, temperature of a node, pressure of an element, flow rate of an element, and temperature of an element.

4. The method according to claim 3, characterized in that The boundary conditions include the inlet total pressure of the air system, the inlet temperature of the air system and the outlet static pressure of the air system; or, the boundary conditions include the inlet flow rate of the air system, the inlet temperature of the air system and the outlet static pressure of the air system.

5. The method according to claim 3, characterized in that: The characteristic solving equation group includes the flow equation group of the element, the flow equation group of the node and the energy equation group of the node.

6. The method according to claim 3, characterized in that The iteratively solving the characteristic data of the air system based on the characteristic solving equation group to obtain the characteristic data of the air system includes: Substituting the kth set of characteristic data of the air system into the characteristic equation group of the air system to obtain the kth characteristic equation group; Taking partial derivatives of the characteristic equations in the k-th characteristic equation group to obtain the k-th residual equation group; Correcting the kth set of characteristic data according to the kth residual equation group to obtain the k+1th set of characteristic data of the air system; Determining whether a convergence criterion is met according to a residual value between the kth group of characteristic data and the k+1th group of characteristic data; If the residual value meets the convergence criterion, the kth set of characteristic data is output as the characteristic data of the air system.

7. The method according to claim 6, characterized in that The step of correcting the kth set of characteristic data according to the kth residual equation group to obtain the k+1th set of characteristic data of the air system includes: Based on the kth residual equation group, the kth flow rate / pressure of the element and / or node is corrected to obtain the k+1th flow rate / pressure of the element / node; The k+1th temperature of the element / node is determined according to the k+1th flow rate / pressure of the element / node.

8. A performance parameter acquisition device for an engine based on an air system, characterized in that: include: A model building module, the model building module is used to build a network model of the engine air system according to the engine cross-sectional view, wherein the network model includes a plurality of nodes and a plurality of elements, and each element / node is provided with at least one directed edge pointing to other elements / nodes for indicating a flow direction; A boundary condition determination module, the boundary condition determination module is used to determine the boundary conditions of the air system according to engine design requirements; an equation determination module, the equation determination module being used to determine the characteristics of the air system and solve a set of equations according to the boundary conditions and the network model; An equation solving module is used to iteratively solve the characteristic data of the air system based on the characteristic solving equation group to obtain the characteristic data of the air system.

9. An electronic device comprising a memory, a processor and a computer program stored in the memory, characterized in that: When the processor executes the computer program, the method according to any one of claims 1 to 7 is implemented.

10. A computer-readable storage medium storing a computer program, characterized in that: When the computer program is executed by the electronic device, the method according to any one of claims 1 to 7 is implemented.

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