A Coupled Analysis Method for Phase Change Sweating Cooling of Turbine Blades
By using a coupled analysis method for phase change sweating cooling of turbine blades, the problems of poor convergence and low computational efficiency in the study of phase change cooling of porous media are solved, and efficient numerical simulation and optimized design of porous media structures are realized.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Patents(China)
- Current Assignee / Owner
- NANJING UNIV OF AERONAUTICS & ASTRONAUTICS
- Filing Date
- 2023-11-13
- Publication Date
- 2026-07-17
AI Technical Summary
Numerical simulation studies of phase change sweating cooling in porous media suffer from poor convergence and low computational efficiency. In particular, the complex flow region near the phase change interface and large temperature gradient lead to unstable flow and difficulty in convergence.
A coupled analysis method for turbine blade phase change sweating cooling was adopted. Through robust numerical calculation and a parameterized porous medium structure generation method based on tunable lattice units, the phase change cooling of porous medium was decomposed into two parts. Specific settings and models in ANSYS FLUENT software were used to optimize the mesh design and monitor temperature changes to ensure convergence.
The numerical simulation convergence of phase change sweating cooling in porous media has been improved, computational efficiency has been enhanced, the design and optimization of porous media structures have been simplified, and technical support has been provided for the improvement of cooling structures.
Smart Images
Figure CN117473832B_ABST
Abstract
Description
Technical Field
[0001] This invention belongs to the technical field of blade cooling structure, specifically relating to a coupled analysis method for turbine blade phase change sweating cooling. Background Technology
[0002] The increasing demands for power and efficiency in modern advanced gas turbines have led to gradually rising turbine inlet temperatures and harsher thermal environments, making the development of high-performance turbine cooling technologies imperative. Film cooling, evaporative cooling, and thermal insulation layers are the main methods for external cooling of turbine blades. Among these, evaporative cooling, as a more effective active thermal protection cooling method for future advanced gas turbines, combines the advantages of film cooling with the characteristics of porous media materials. It uniformly disperses the cooling fluid outflow, facilitating large-area and reusable thermal protection, and separates the cooling structure from the load-bearing structure, allowing it to withstand certain impact forces. Phase change evaporative cooling refers to the endothermic phase change process that occurs when the coolant flows through a porous medium. The average particle diameter, particle structure, and porosity of the porous medium are the main factors affecting phase change evaporative cooling. To improve the cooling performance of phase change evaporative cooling in porous media, scholars both domestically and internationally have conducted a series of studies on the divergent cooling of porous media in recent years using experimental measurements and numerical calculations.
[0003] In numerical simulations, phase transitions involve multiphase flow and material phase change processes, with significant temperature and density differences at the interfaces. This results in complex flow structures and strong flow instabilities in the flow regions near these interfaces, making convergence difficult. Furthermore, the porous medium setting introduces large temperature gradients during phase transitions, further instability and affecting convergence. Inappropriate boundary conditions can also lead to convergence problems. Particularly, boundary conditions near the phase transition interface may require special handling to capture transient behavior during the phase transition. In summary, numerical simulations of divergent cooling in porous media face several convergence challenges. Therefore, a convergent, accurate, and efficient boundary condition setting method is urgently needed for numerical simulations of phase transition evaporative cooling in porous media. Summary of the Invention
[0004] To overcome the problem of convergence difficulties in numerical simulation studies of divergent cooling in porous media, and addressing the shortcomings of the numerical calculation method in ANSYS FLUENT software, this invention aims to provide a coupled analysis method for phase change sweating cooling of turbine blades. This method effectively improves the computational efficiency for studying phase change sweating cooling in porous media. Furthermore, by designing and optimizing the structure of different lattice units, porous media with corresponding required porosities can be obtained. This is of great significance for optimizing the design of cooling structures and improving cooling performance, providing a technical guarantee for the study of the sweating cooling law of porous media.
[0005] The objective of this invention is achieved through the following technical solution:
[0006] A coupled analysis method for phase change sweating cooling of turbine blades is characterized by the following two aspects: highly robust numerical calculation of phase change sweating cooling of porous media to improve the convergence of numerical simulation of phase change divergent cooling; and a parameterized porous media structure generation method based on tunable lattice units to obtain porous media with the required porosity.
[0007] A coupled analysis method for phase change sweating cooling of turbine blades includes the following steps for highly robust numerical calculations of phase change sweating cooling in porous media:
[0008] Step 1: Model Establishment. Define the geometric characteristics of the porous media region and the computational domain of the cooling medium in the study of phase change divergent cooling in porous media. Generate the corresponding mesh file and import it into ANSYS FLUENT. To balance computational accuracy and computational load, the phase change of the porous media is calculated in two parts. The first part is a numerical simulation of the main computational domain, calculating the heat transfer on the surface of the porous media based on known data and the outlet boundary. The second part is a numerical simulation of the computational domains of the porous media and the cooling medium, calculating the phase change process of the cooling medium based on the heat transfer on the surface of the porous media and the cooling water flow rate.
[0009] Step 2: Setting up the working fluid. Considering the different working fluids involved in the sweating and cooling of porous media, three working fluids are added to the fluent database in ANSYSFLUNET: ideal gas (air), liquid water (water-liquid), and water vapor (water-vapor), and the corresponding physical property parameters are designed according to the research requirements.
[0010] Step 3: Multiphase flow setup. For model selection, use the volume of fluid model or the mixture model, which has better stability, if possible. Add the three working fluids from Step 2 to the multiphase flow setup. Set up the phase transitions for liquid water and water vapor, where the phase transition temperatures are obtained by referring to a table based on the relationship between pressure and boiling point.
[0011] Step 4: Setting up the porous media domain. A conventional k-ωSST turbulence model is used. For calculations with high mesh quality, a turbulence model with three or more equations can be selected. Check the "porous zone" setting and set the porosity and porous media material according to the material parameters required for the study. In the porous media sub-options, set the parameters for the three working media within the porous media: air, water-liquid, and water-vapor. The main parameters are Viscous Resistance and Inertial Resistance, calculated based on the physical properties of the porous media used in the experiments in the references. The values of these two parameters are basically on the same order of magnitude for the three working media.
[0012] Step 5: Calculation settings. Use the couple algorithm, which converges relatively quickly. If higher-order difference schemes fail to converge, consider switching to a first-order upwind scheme to stabilize the initial field before switching to higher-order schemes, especially since the energy equation is not easy to converge. Select the pseudo transient option; this function improves computational stability and reduces the likelihood of divergence, but convergence is slower, requiring more time steps compared to the Courrant number setting method.
[0013] Step Six: Control Settings. The parameters in the Control tab can be left at their default values. If the calculation is prone to divergence, the turbulence and energy factor values can be lowered. Set the upper and lower limits for pressure and temperature in the Limit limiter, providing values based on boundary conditions to improve calculation stability. Set the time scale factor parameter; the default value of 1 ensures convergence for most calculation examples. Under non-divergent conditions, appropriately increase this parameter to speed up convergence, while carefully monitoring the temperature and pressure fields for non-physical changes.
[0014] Step 7: Boundary and Monitoring Settings. Since the phase change in the porous medium is calculated in two parts, the heat transfer on the porous medium surface is calculated based on the known values and the outlet boundary. When adding heat, Fluent cannot add heat at the outlet boundary; it can only add volumetric source terms. During the calculation, the distribution of water-vapor is monitored. Due to the strong unsteady nature of the phase change, monitoring the temperature change on the porous medium surface can be used as a criterion for convergence.
[0015] A method for generating parameterized porous media structures based on tunable lattice units includes the following steps:
[0016] Step 1: Model the mesh region and the solid region separately. Using the structural design module built into the Magics software, scale the overall size of each lattice unit and adjust the local size as needed to obtain the porous medium lattice unit with the required porosity.
[0017] Step 2: By selecting a porous medium lattice unit with a specified porosity from the module, a porous volume is grown in a spatial array according to parameters such as size.
[0018] Step 3: Obtain the design of the porous region by finding the intersection with the design space using Boolean operations, and then obtain the model to be printed by finding the union of the porous part and the solid part using Boolean operations.
[0019] Step 4: During the calculation process, a large number of broken surface patches may be generated. When slicing, the broken surface patches may fail because a certain layer will not close. It is necessary to use the repair function in the Magics software to repair the broken surface patches so that the design model can be completely closed.
[0020] The advantage of this grid division method is that the calculation is relatively simple and the computational requirements are relatively low.
[0021] In this invention, the coupled analysis method involves first performing mainstream calculations to obtain the thermal boundary conditions of the porous medium, then applying the thermal boundary conditions to the fluid and solid domains of the porous medium, without considering the mainstream, and performing a second calculation to finally obtain the phase change characteristics within the porous medium and the cooling effect distribution on the gas-fuel side surface of the porous medium.
[0022] The beneficial effects of this invention are:
[0023] This method improves the convergence of numerical simulation studies on phase change divergent cooling, significantly increasing the research efficiency. Furthermore, the parameterized porous media structure generation method based on tunable lattice units offers relatively convenient computation and reduces computer requirements. Most importantly, it enables the design and fabrication of porous media structures with specified structures and porosities, greatly facilitating experimental research on the phase change cooling mechanism of porous media and the optimized design of porous media structures.
[0024] This invention is of great significance for the optimized design of cooling structures and the improvement of cooling performance, and provides technical support for the study of the sweating cooling law of porous media. Attached Figure Description
[0025] Figure 1 This is a flowchart illustrating the feasibility study of a highly robust numerical calculation method for phase change sweating cooling of porous media according to the present invention.
[0026] Figure 2 This is a schematic diagram of the model structure of the porous medium phase change sweating cooling example of the present invention.
[0027] Figure 3 This is a specific example of a feasibility study on a highly robust numerical calculation method for phase change sweating cooling of porous media, as described in this invention, to monitor temperature trends in the monitoring area.
[0028] Figure 4 This is a schematic diagram of the convergence standard curve of temperature change on the porous medium surface of the present invention.
[0029] Figure 5 This is a schematic diagram of a self-designed lattice unit in an example of the present invention.
[0030] Figure 6 This is a schematic diagram of a porous dielectric structure grown from a self-designed lattice unit in an example of the present invention. Detailed Implementation
[0031] The specific embodiments of the present invention will be further described in detail below with reference to the accompanying drawings, and the technical solutions in the embodiments of the present invention will be clearly and completely described. Obviously, the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative effort are within the scope of protection of the present invention.
[0032] See Figure 1 The diagram shown is a flowchart illustrating the feasibility study of a highly robust numerical calculation method for phase change sweating cooling of porous media. The schematic diagram of the combined model structure for the phase change sweating cooling example of porous media is shown below. Figure 2 As shown, this includes the porous medium region and the cooling medium computational domain (the porous medium is 80mm*40mm*10mm, and the cooling medium is 80mm*40mm*15mm). A specific example of a feasibility study on a highly robust numerical calculation method for phase change sweating cooling of porous media is shown below, illustrating the temperature trend of the monitored area. Figure 3 As shown in the diagram. A schematic diagram of the convergence standard curve of temperature change on the porous medium surface is shown below. Figure 4 As shown.
[0033] This embodiment provides a specific case study on the practical application of a robust numerical calculation method for phase change sweating cooling of porous media. The method includes the following steps:
[0034] Step 1: Model Establishment. Define the geometric characteristics of the porous media region and the computational domain of the cooling medium in the study of phase change divergent cooling in porous media (the porous media is 80mm*40mm*10mm, and the cooling medium is 80mm*40mm*15mm). Figure 2 As shown, the generated mesh file is then imported into ANSYS FLUENT. To balance computational accuracy and computational load, the phase transition of the porous medium is calculated in two parts. The first part is a numerical simulation of the main computational domain, calculating the heat transfer on the surface of the porous medium based on known parameters and the outlet boundary. The second part is a numerical simulation of the computational domain of the porous medium and the cooling medium, calculating the phase transition process of the cooling medium based on the heat transfer on the surface of the porous medium and the cooling water flow rate.
[0035] Step Two: Setting up the working fluid. Considering the different working fluids involved in the sweating and cooling of porous media, add two other working fluids besides the ideal gas (air) to the fluent database in ANSYS FLUENT: liquid water and water vapor. Design the corresponding physical property parameters according to the research requirements. It is worth noting that the density and viscosity settings need to be adjusted to improve simulation accuracy.
[0036] Step 3: Multiphase flow setup. For model selection, use the volume of fluid model or the mixture model, which has better stability, if possible. Add the three working fluids from Step 2 to the multiphase flow setup. Set up the phase transitions for liquid water and water vapor, where the phase transition temperatures are obtained by referring to a table based on the relationship between pressure and boiling point.
[0037] Step 4: Setting up the porous media domain. A conventional k-ωSST turbulence model is used. For calculations with high mesh quality, a turbulence model with three or more equations can be selected. Check the "porous zone" setting and set the porosity and porous media material according to the material parameters required for the study. In the porous media sub-options, set the parameters for the three working media within the porous media: air, water-liquid, and water-vapor. The main parameters are Viscous Resistance and Inertial Resistance, calculated based on the physical properties of the porous media used in the experiments in the references. The values of these two parameters are basically on the same order of magnitude for the three working media.
[0038] Step 5: Calculation settings. Use the couple algorithm, which converges relatively quickly. If higher-order difference schemes fail to converge, consider switching to a first-order upwind scheme to stabilize the initial field before switching to higher-order schemes, especially since the energy equation is not easy to converge. Select the pseudo transient option; this function improves computational stability and reduces the likelihood of divergence, but convergence is slower, requiring more time steps compared to the Courrant number setting method.
[0039] Step Six: Control Settings. The parameters in the Control tab can be left at their default values. If the calculation is prone to divergence, the turbulence and energy factor values can be lowered. Set the upper and lower limits for pressure and temperature in the Limit limiter, providing values based on boundary conditions to improve calculation stability. Set the time scale factor parameter; the default value of 1 ensures convergence for most calculation examples. Under non-divergent conditions, appropriately increase this parameter to speed up convergence, while carefully monitoring the temperature and pressure fields for non-physical changes.
[0040] Step 7: Boundary and Monitoring Settings. Since the phase change of the porous medium is calculated in two parts, each part is calculated separately. Based on the known heat transfer on the porous medium surface calculated from the outlet boundary, the heat transfer cannot be added at the Fluent outlet boundary; it can only be added as a volumetric source term. During the calculation, the distribution of the water-vapor is monitored as follows: Figure 3 As shown, due to the strong unsteady characteristics of phase transitions, monitoring the temperature change on the surface of porous media can be used as a criterion for convergence, such as... Figure 4 As shown, Figure 4 The vertical axis represents the temperature change on the surface of the porous medium, and the horizontal axis represents the number of convergence steps.
[0041] This embodiment provides a specific example of the practical application of a parameterized porous media structure generation method based on tunable lattice units, and presents the porous media structure designed and generated according to the actual process. The method includes the following steps:
[0042] Step 1: Model the mesh region and the solid region separately. Using the built-in structure design module in the Magic software, a new custom lattice was designed with a body diagonals with rounded nodes as a reference. The overall size of each lattice unit was scaled up and its local dimensions adjusted as needed to obtain the porous medium lattice unit with the required porosity. Figure 5 This is a schematic diagram of a self-designed lattice unit in an example of the present invention. Figure 6 This is a schematic diagram of a porous dielectric structure grown from a self-designed lattice unit in an example of the present invention.
[0043] Step 2: By selecting a porous medium lattice unit with a specified porosity from the module, a porous volume is grown in a spatial array according to parameters such as size.
[0044] Step 3: Obtain the design of the porous region by finding the intersection with the design space using Boolean operations, and then obtain the model to be printed by finding the union of the porous part and the solid part using Boolean operations.
[0045] Step 4: During the calculation process, a large number of broken surface patches may be generated. When slicing, the broken surface patches may fail because a certain layer will not close. It is necessary to use the repair function in the Magics software to repair the broken surface patches so that the design model can be completely closed.
[0046] This invention presents a coupled analysis method for phase change divergent cooling of turbine blades. The coupled analysis method involves first calculating the mainstream to obtain the thermal boundary conditions of the porous medium. Then, these thermal boundary conditions are applied to the fluid and solid domains of the porous medium. Ignoring the mainstream, a second calculation is performed to finally obtain the phase change characteristics within the porous medium and the cooling effect distribution on the combustion-side surface. This significantly improves the convergence of numerical simulations for phase change divergent cooling in porous media, thereby increasing the research efficiency. Furthermore, the parameterized porous medium structure generation method based on tunable lattice units provides abundant model resources for the study of phase change divergent cooling in different porous media.
[0047] The above description is merely a preferred embodiment of the present invention and is not intended to limit the invention. Various modifications and variations can be made to the present invention by those skilled in the art. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the scope of protection of the present invention.
Claims
1. A coupled analysis method for phase change sweating cooling of turbine blades, characterized in that, This includes the following two aspects: robust numerical calculations for phase change sweating cooling in porous media, improving the convergence of numerical simulations of phase change sweating cooling; and a parameterized porous media structure generation method based on tunable lattice units to obtain porous media with the required porosity. The robust numerical calculations for phase change sweating cooling in porous media include the following steps: Step 1: Model Establishment. Define the geometric characteristics of the porous media region and the computational domain of the cooling medium in the porous media phase change sweating cooling study. Generate the corresponding mesh file and import it into ANSYS FLUENT. To balance computational accuracy and computational load, the porous media phase change is calculated in two parts. The first part is a numerical simulation of the main computational domain, calculating the heat transfer on the porous media surface based on the known inlet and outlet boundaries. The second part is a numerical simulation of the computational domains of the porous media and the cooling medium, calculating the phase change process of the cooling medium based on the heat transfer on the porous media surface and the cooling water flow rate. Step 2: Setting up the working fluid. Considering the different working fluids involved in the sweating and cooling of porous media, three working fluids are added to the fluent database in ANSYS FLUENT: ideal gas, liquid water, and water vapor. The corresponding physical property parameters are designed according to the research requirements. Step 3: Multiphase flow setup. For model selection, the volume of fluid model and the mixture model, which has better stability, are used. The three working fluids from Step 2 above are added to the multiphase flow setup. The phase transition of liquid water and water vapor is set, and the phase transition temperature is obtained by looking up a table based on the relationship between pressure and boiling point. Step 4: Setting up the porous media domain. A conventional k-ω SST turbulence model is used. For calculations with high mesh quality, a turbulence model with three or more equations is selected. The porous zone setting is checked. According to the material parameters required for the study, the porosity and porous media material are set. In the porous media sub-option, the parameters for the three working fluids in the porous media, namely ideal gas, liquid water and water vapor, are set as Viscous Resistance and Inertial Resistance respectively. Step 5: Calculation settings. Use the couple algorithm, which converges faster. If the higher-order difference scheme fails to converge, switch to the first-order upwind scheme to calculate the initial field stability before switching back to the higher-order scheme. Check the pseudo transient option to improve calculation stability and reduce the likelihood of divergence. Step 6: Control settings. The parameters in the Control tab can be left at their default values. If the calculation is prone to divergence, lower the factor values for turbulence and energy. Set the upper and lower limits for pressure and temperature in the Limit limiter, and give the values according to the boundary conditions to improve the stability of the calculation. Set the time scale factor parameter. The default value of 1 ensures the convergence of the calculation examples, and at the same time monitors whether non-physical solutions appear in the temperature and pressure fields. Step 7: Boundary and monitoring settings. Since the phase change of the porous medium is calculated in two parts, the heat transfer on the surface of the porous medium is calculated based on the known inlet and outlet boundaries. When adding heat, the outlet boundary of Fluent cannot add heat, so a volume source term is added in the form of a source term. During the calculation, the distribution of water-vapor is monitored, and the temperature change on the surface of the porous medium is used as the criterion for convergence.
2. The method for coupled analysis of turbine blade phase change sweating cooling according to claim 1, characterized in that: A method for generating parameterized porous media structures based on tunable lattice units includes the following steps: Step 1: Model the mesh region and the solid region separately. Using the structural design module built into the Magics software, scale the overall size of each lattice unit and adjust the local size as required to obtain the porous medium lattice unit with the required porosity. Step 2: By selecting porous medium lattice units with a specified porosity from the module and growing porous volumes in a spatial array according to size parameters; Step 3: Obtain the design of the porous region by finding the intersection with the design space using Boolean operations, and then use Boolean operations to find the union of the porous part and the solid part to obtain the model to be printed; Step 4: If a large number of broken surface patches are generated during the calculation process, the slicing will fail because a certain layer will not close when slicing the broken surface patches. Use the repair function in the Magics software to repair the broken surface patches so that the design model can be completely closed.