A method for preparing a surface selective anti-icing structure facing an incoming flow environment

Abstract

The present invention provides a method for preparing a surface selective anti-icing structure facing an incoming flow environment; the present invention uses computational fluid dynamics methods to perform comparative screening and calculation of droplet distribution behavior and ice morphology for regionalized microstructures on complex curved surfaces, and then performs structure preparation based on laser direct writing technology, ultimately obtaining a super-hydrophobic surface with efficient anti-icing performance. The method for preparing a super-hydrophobic surface selective anti-icing structure involved in the present invention effectively saves the time and economic costs of structural screening, and can perform targeted structural design for complex surfaces, aiming to improve the anti-icing efficiency of the overall surface. In addition, the preparation method involved in the present invention is flexible and convenient, has strong environmental adaptability, and provides important technical support for the further development of anti-icing technology required in the aerospace field.

Description

Technical Field

[0001] The invention belongs to the technical field of material surface performance evaluation, and in particular relates to a method for preparing a surface selective anti-icing structure facing an incoming flow environment. Background Art

[0002] Currently, aircraft icing remains a major issue affecting flight safety. To address the issue of aircraft icing in low-temperature, high-humidity environments, researchers have proposed technologies such as electrothermal deicing, mechanical vibration deicing, and hot air deicing. However, these deicing technologies typically require additional energy and equipment, increasing the flight burden. Consequently, a range of passive deicing technologies, including superhydrophobic deicing, SLIPS deicing, and solid-state lubrication deicing, have become research hotspots. Among these, superhydrophobic deicing offers the most potential for application due to its simple material preparation and wide range of applications.

[0003] Current designs for superhydrophobic, anti-icing surfaces are typically based on static laboratory environments. The resulting superhydrophobic structures are often uniformly distributed, resulting in relatively consistent hydrophobic, anti-icing, and de-icing performance in static environments. However, for curved surfaces like wings exposed to incoming flow, droplet contact patterns vary significantly across different regions. To achieve superior anti-icing performance, selective microstructures should be designed and established tailored to the flow field and droplet contact patterns across different regions of the surface, thereby enhancing the overall anti-icing performance.

[0004] Therefore, based on computational fluid dynamics methods and laser direct writing technology, the present invention proposes a method for preparing surface selective anti-icing structures for incoming flow environments, aiming to improve the anti-icing performance of complex curved surfaces in incoming flow environments, and provide theoretical support for the development of anti-icing technology in the aerospace field. Summary of the Invention

[0005] The purpose of the present invention is to provide a method for preparing a surface selective anti-icing structure facing an incoming flow environment. The surface selective anti-icing structure facing an incoming flow environment prepared by the present invention has important guiding significance for the development of aircraft surface anti-icing and de-icing technology.

[0006] The present invention is achieved through the following technical solutions:

[0007] The present invention relates to a method for preparing a surface selective anti-icing structure facing an incoming flow environment, comprising the following steps:

[0008] Step 1: Establish a super-hydrophobic component calculation model based on Ansys ICEM software, set the length, height, and width of the calculation domain according to the characteristic length of the calculation model, place the calculation model at the geometric center of the calculation domain, and establish a curved surface component;

[0009] Step 2: Arrange a microstructure array of specific size and spacing on the surface of the curved component, divide the surface of the curved component into several areas according to morphological characteristics, divide the grid, and set a near-wall boundary layer;

[0010] Step 3: Select the incoming flow velocity and determine whether the fluid is compressible based on the Mach number of the incoming flow velocity. For compressible fluids, use a density-based solver, and for incompressible fluids, use a pressure-based solver.

[0011] Step 4: Select the turbulence model in Ansys Fluent software, set the corresponding boundary conditions, and perform grid-independence verification and reliability verification;

[0012] Step 5: Set the incoming flow velocity, incoming flow temperature, wall temperature, and surface contact angle according to the actual working conditions, perform flow field calculations, and read the calculation results into Ansys Fluent Icing software;

[0013] Step 6: Set up the Particles module and Icing module in Ansys Fluent Icing software to calculate the distribution behavior of incoming droplets and the icing morphology in a low-temperature environment, and obtain the droplet collection coefficient and icing quality parameters in different areas of the surface;

[0014] Step 7: Based on this, select microstructures with different geometric parameters and repeat the process from Step 2 to Step 6 multiple times, and compare the droplet collection coefficient and ice quality parameters for the same segmented area to obtain the optimal microstructure parameters for each area;

[0015] Step 8, based on the structural parameters obtained in step 7 and laser direct writing technology, the laser wavelength, laser power, exposure time, scanning speed, and path parameters are adjusted to prepare a microstructure component on the surface of the substrate material;

[0016] Step 9: The microstructure component obtained in step 8 is subjected to surface fluorination modification to obtain the final super-hydrophobic surface selective anti-icing structure.

[0017] Preferably, in step 1, the curved surface component includes a scaled airfoil, a flat plate, or a complex curved surface.

[0018] Preferably, in step 1, the length of the calculation domain is more than 20 times the characteristic length of the calculation model, and the width and height are both more than 5 times the characteristic length of the calculation model.

[0019] Preferably, in step 2, the microstructure array includes: a square column array, a cylindrical array, a pyramid array, a spherical array, and a wedge array.

[0020] Preferably, in step 2, the height of the microstructure array is 20 μm to 200 μm, the side length / diameter is 20 μm to 100 μm, and the spacing is 0 μm to 100 μm.

[0021] Preferably, in step 2, the number of the regions is 5-10.

[0022] Preferably, in step 2, the near-wall boundary layer is 10 layers, the expansion coefficient is 1.2, and the initial boundary layer height is y, as shown in the following formula (1):

[0023]

[0024] Among them, y + is the dimensionless height from the bottom wall, U τ is the tangential velocity controlled by the wall shear stress, U τ It is expressed as shown in formula (2):

[0025]

[0026] τ ω It is expressed as shown in formula (3):

[0027]

[0028] In formula (3), τ ω is the wall shear stress, ρ is the air density, U ∞ is the incoming flow velocity. + It is 0.8-1.2.

[0029] Preferably, in step 3, the standard for distinguishing the fluid is: a fluid with an incoming Mach number higher than 0.3 is determined to be a compressible fluid, and a fluid with a Mach number lower than 0.3 is determined to be an incompressible fluid.

[0030] Preferably, in step 4, the turbulence model is Spalart-Allmaras (SA), k-ε, k-ω, Transition SST, Reynolds stress (RSM) and Detached eddy simulation (DES), etc.

[0031] Preferably, in step 4, the calculation result is considered reliable if the difference between the calculation result and the test result is within 10%.

[0032] Preferably, in step 6, the LWC of the incoming droplet distribution behavior is 0.00015 kg / m 3 ~0.001kg / m 3The droplet diameter of the incoming droplet distribution behavior is 10μm to 100μm. In the Particles distribution module, keep the Monodispersed option to capture the droplet trajectory with a single droplet. To ensure that the droplet velocity is consistent with the incoming flow velocity, disable the Droplet velocity vector option. Set the ice type to Glaze, Rime, etc.

[0033] Preferably, in step 7, the number of repetitions is determined by the optional type of microstructure and the range of geometric parameters, and is generally not more than 10 times.

[0034] Preferably, in step 8, the matrix material is but not limited to metal, composite material, etc.

[0035] Preferably, in step 9, the fluorination modification method includes but is not limited to spraying, ion plating, chemical dipping, etc.

[0036] The present invention has the following advantages:

[0037] (1) The method for preparing a surface selective anti-icing structure facing an incoming flow environment involved in the present invention realizes the prediction of droplet contact form and freezing behavior on surfaces of different microstructures in a low-temperature incoming flow environment through computational fluid dynamics, effectively saving the time and economic costs of structural design screening.

[0038] (2) The method for preparing a surface selective anti-icing structure facing an incoming flow environment involved in the present invention can perform targeted structural design based on the specific flow field characteristics of a complex surface, effectively improving the overall anti-icing performance of the surface.

[0039] (3) The method for preparing a surface selective anti-icing structure facing an incoming flow environment involved in the present invention can be flexibly applied to a variety of complex curved surface components, and the preparation process is simple and convenient, and has wide applicability.

[0040] (4) The method for preparing the surface selective anti-icing structure facing the incoming flow environment involved in the present invention provides theoretical guidance for the further development of the anti-icing technology required in the aerospace field. BRIEF DESCRIPTION OF THE DRAWINGS

[0041] Figure 1 This is a flow chart of the method for preparing a surface selective anti-icing structure facing an incoming flow environment involved in the present invention;

[0042] Figure 2 Schematic diagram of the calculation structure model established in Example 1;

[0043] Figure 3This is a graph showing the droplet collection coefficient and ice mass of the structural region in Example 1;

[0044] Figure 4 This is a microstructure diagram prepared in Example 1;

[0045] Figure 5 This is the contact angle diagram of the microstructure surface after fluorination modification in Example 1. DETAILED DESCRIPTION

[0046] The present invention will be described in detail below with reference to specific embodiments. It should be noted that the following embodiments are only for further explanation of the present invention, but the protection scope of the present invention is not limited to the following embodiments.

[0047] Example 1

[0048] This embodiment relates to a method for preparing a surface selective anti-icing structure facing an incoming flow environment, such as Figure 1 The specific steps are as follows:

[0049] Step 1: Based on Ansys ICEM software, a NACA 0012 airfoil calculation model with a chord length of 100 mm is established. The length, width, and height of the calculation domain model are set to 2000 mm, 600 mm, and 600 mm respectively according to the characteristic length of the airfoil, and the airfoil calculation model is placed at the geometric center of the calculation domain.

[0050] Step 2: Then, a wedge array structure perpendicular to the surface is set on the airfoil surface, with the structure height set to 50 μm, the bottom side length to 80 μm, and the structure spacing to 0 μm. Figure 2 As shown in the figure, the surface is divided into 6 regions according to the airfoil characteristics, namely region 1, region 2, region 3, region 4, region 5, and region 6 from left to right; the number of wall boundary layers is set to 10, the expansion coefficient is 1.2, and the initial boundary layer height is 1×10 -6 m, and then the computational grid is obtained after unstructured processing;

[0051] The formula is as follows:

[0052] The initial boundary layer height is y, which is expressed by the following equation (1):

[0053]

[0054] Among them, y + is the dimensionless height from the bottom wall, U τ is the tangential velocity controlled by the wall shear stress, U τ It is expressed as shown in formula (2):

[0055]

[0056] τ ω It is expressed as shown in formula (3):

[0057]

[0058] In formula (3), τ ω is the wall shear stress, ρ is the air density, U ∞ is the incoming flow velocity. + Keep it at 1.

[0059] Step 3: Select the incoming flow velocity as 70 m / s, which is lower than Mach 0.3 and is an incompressible fluid, and choose the pressure-based solver.

[0060] Step 4: Select the Transition SST turbulence model in Ansys Fluent software, set the corresponding boundary conditions, and perform grid-independence verification and reliability verification to ensure that the relative error is within 10%.

[0061] Step 5: Set the flow velocity to 70 m / s, the flow temperature to 253.15 K, the wall temperature to 264.54 K, and the surface contact angle to 150°. Perform flow field calculations and import the results into Ansys Fluent Icing software.

[0062] Step 6: In the Particles module of Ansys Fluent Icing, set the wall temperature to 265.54K again. In the Droplet module, set the liquid water content (LWC) to 0.00055kg / m 3 , the droplet diameter is 20 μm, keep the monodispersed state in the Particles distribution module, cancel the Droplet velocity vector option, and calculate the droplet distribution behavior of the incoming flow in a low temperature environment; then, in the Ice accretion conditions, determine the ice type as Glaze, select the freezing time as 60 seconds, start the calculation, and finally obtain the local droplet collection coefficient and ice mass curve on the structure surface, as shown in Figure 3 As shown in the figure, (a) shows the curve of distance and local droplet collection coefficient of the structure, and (b) shows the curve of distance and local ice mass on the structure surface. As can be seen from the figure, the droplet collection coefficient and ice mass on the structure surface gradually decrease along the incoming flow direction.

[0063] Step 7. On this basis, select microstructure arrays with structure heights of 20 μm, 30 μm, 40 μm, 60 μm, and 70 μm, respectively, and repeat the process from steps 2 to 6 five times. Compare the droplet collection coefficient and ice quality parameters for the same segmented area to obtain the optimal microstructure parameters for each area.

[0064] Step 8: Based on the structural parameters obtained in step 7, the laser wavelength, laser power, exposure time, scanning speed, path and other parameters are adjusted based on the laser direct writing technology to prepare the microstructure on the surface of the aluminum alloy substrate. The surface morphology of the structure is clear and smooth without obvious defects, meeting the design requirements, such as Figure 4 shown.

[0065] In step 9, the microstructure component obtained in step 8 is fluorinated by chemical impregnation to obtain a final super-hydrophobic surface with a surface contact angle of up to 167°, showing excellent super-hydrophobic properties. Figure 5 shown.

[0066] Example 2

[0067] This embodiment relates to a method for preparing a surface selective anti-icing structure facing an incoming flow environment, comprising the following steps:

[0068] Step 1: Based on Ansys ICEM software, a NACA 0012 airfoil calculation model with a chord length of 100 mm is established. The length, width, and height of the calculation domain model are set to 2000 mm, 600 mm, and 600 mm respectively according to the characteristic length of the airfoil, and the airfoil calculation model is placed at the geometric center of the calculation domain.

[0069] Step 2: Then, a cylindrical array structure perpendicular to the airfoil surface is set, with a structure height of 70 μm, a diameter of 40 μm, and a structure spacing of 40 μm. The surface is divided into five regions based on the airfoil characteristics, the number of wall boundary layers is set to 10, the expansion coefficient is 1.2, and the initial boundary layer height is 5×10 -7 m, and then the computational grid is obtained after unstructured processing.

[0070] In step 3, the incoming flow velocity is selected as 150 m / s, which is higher than Mach 0.3, and the fluid is compressible. The density-based solver is selected.

[0071] Step 4: Select the k-ε turbulence model in Ansys Fluent software, set the corresponding boundary conditions, and perform grid-independence verification and reliability verification to ensure that the relative error is within 10%.

[0072] In step 5, set the flow velocity to 150 m / s, the flow temperature to 253.15 K, the wall temperature to 264.54 K, and the surface contact angle to 155°. Flow field calculations were performed and the results were imported into Ansys Fluent Icing software.

[0073] Step 6: In the Particles module of Ansys Fluent Icing, set the wall temperature to 265.54K again. In the Droplet module, set the liquid water content (LWC) to 0.00075kg / m 3 , the droplet diameter is 40μm, the particle distribution module is kept monodispersed, and the droplet velocity vector option is cancelled to calculate the incoming droplet distribution behavior in a low-temperature environment; then, in the ice accretion conditions, the ice type is determined to be glaze, the freezing time is selected as 120s, and the calculation is started to finally obtain the droplet collection coefficient and ice mass on the structure surface.

[0074] Step 7. On this basis, select microstructure arrays with structure heights of 30 μm, 50 μm, 90 μm, 110 μm, 130 μm, 150 μm, and 170 μm, and repeat the process from steps 2 to 6 7 times. Compare the droplet collection coefficient and ice quality parameters for the same segmented area to obtain the optimal microstructure parameters for each area.

[0075] Step 8: Based on the structural parameters obtained in step 7 and laser direct writing technology, the laser wavelength, laser power, exposure time, scanning speed, path and other parameters are adjusted to prepare a microstructure on the surface of the stainless steel substrate.

[0076] Step 9: The microstructure component obtained in step 8 is subjected to fluorination modification by spraying to obtain a final super-hydrophobic surface.

[0077] Example 3

[0078] This embodiment relates to a method for preparing a surface selective anti-icing structure facing an incoming flow environment, comprising the following steps:

[0079] Step 1: Based on Ansys ICEM software, a computational model of the complex curved surface of the engine lip with a diameter of 80 mm is established. The length, width, and height of the computational domain model are set to 1600 mm, 400 mm, and 400 mm, respectively, according to the characteristic length, and the computational model is placed at the geometric center of the computational domain.

[0080] Step 2: Then, a spherical array structure perpendicular to the surface is set on the curved surface, with a structure height of 50 μm, a diameter of 50 μm, and a structure spacing of 10 μm. The surface is divided into 10 regions based on the airfoil characteristics, the number of wall boundary layers is set to 10, the expansion coefficient is 1.2, and the initial boundary layer height is 1×10 -6 m, and then the computational grid is obtained after unstructured processing.

[0081] Step 3: Select the incoming flow velocity as 50 m / s, which is lower than Mach 0.3, for an incompressible fluid, and choose the pressure-based solver.

[0082] Step 4: Select the k-ω turbulence model in Ansys Fluent software, set the corresponding boundary conditions, and perform grid-independence verification and reliability verification to ensure that the relative error is within 10%.

[0083] Step 5: Set the flow velocity to 50 m / s, the flow temperature to 265.67 K, the wall temperature to 280.93 K, and the surface contact angle to 160°. Perform flow field calculations and import the results into Ansys Fluent Icing software.

[0084] Step 6: In the Particles module of Ansys Fluent Icing, set the wall temperature to 280.93 K again. In the Droplet module, set the liquid water content (LWC) to 0.00045 kg / m 3 , the droplet diameter is 20μm, the particle distribution module is kept monodispersed, and the droplet velocity vector option is cancelled to calculate the incoming droplet distribution behavior in a low temperature environment; then the ice type is determined to be rime in the ice accretion conditions, and the freezing time is selected as 360s. The calculation starts and finally the droplet collection coefficient and ice mass on the structure surface are obtained.

[0085] Step 7. On this basis, select microstructure arrays with structural spacing of 20μm, 30μm, 40μm, 50μm, 60μm, 70μm, 80μm, and 90μm, and repeat the process from step 2 to step 6 8 times. Compare the droplet collection coefficient and ice quality parameters for the same segmented area to obtain the optimal microstructure parameters for each area.

[0086] In step 8, according to the structural parameters obtained in step 7, based on the laser direct writing technology, the laser wavelength, laser power, exposure time, scanning speed, path and other parameters are adjusted to prepare the microstructure on the surface of the carbon fiber composite material matrix material.

[0087] Step 9: The microstructure component obtained in step 8 is fluorinated by ion plating to obtain a final super-hydrophobic surface.

[0088] The present invention uses computational fluid dynamics methods to perform comparative screening and calculation of droplet distribution behavior and ice morphology for regionalized microstructures on complex curved surfaces, and then performs structural preparation based on laser direct writing technology, ultimately obtaining a superhydrophobic surface with efficient anti-icing performance. The surface selective anti-icing structure design and preparation method involved in the present invention effectively saves the time cost and economic cost of structural design screening, and can perform targeted structural design for complex surfaces, aiming to improve the anti-icing efficiency of the overall surface. In addition, the structural design and preparation method proposed in the present invention are flexible and convenient, and have strong environmental adaptability, providing important technical support for the further development of anti-icing technology required in the aerospace field. It is worth noting that the present invention focuses on proposing a design and preparation method for an anti-icing structure, and is not limited to the incoming flow environment or the matrix material.

[0089] The above describes the specific embodiments of the present invention. It should be understood that the present invention is not limited to the above specific embodiments, and those skilled in the art may make various variations or modifications within the scope of the claims, which do not affect the essence of the present invention.

Claims

1. A method for preparing a surface selective anti-icing structure facing an incoming flow environment, characterized in that: The following steps are involved: Step 1: Establish a super-hydrophobic component calculation model based on Ansys ICEM software, set the length, height, and width of the calculation domain according to the characteristic length of the calculation model, place the calculation model at the geometric center of the calculation domain, and establish a curved surface component; Step 2: Arrange a microstructure array of specific size and spacing on the surface of the curved component, divide the surface of the curved component into several regions according to its morphological characteristics, divide the grid, set the near-wall boundary layer, and obtain the computational grid; Step 3: Select the incoming flow velocity and determine whether the fluid is compressible based on the Mach number of the incoming flow velocity. For compressible fluids, use a density-based solver, and for incompressible fluids, use a pressure-based solver. Step 4: Select the turbulence model in Ansys Fluent software, set the corresponding boundary conditions, and perform grid-independence verification and reliability verification; Step 5: Set the incoming flow velocity, incoming flow temperature, wall temperature, and surface contact angle according to the actual working conditions, perform flow field calculations, and read the calculation results into Ansys Fluent Icing software; Step 6: Set up the particle flow module and icing module in Ansys Fluent Icing software to calculate the incoming flow droplet distribution behavior and ice morphology in a low-temperature environment, and obtain the droplet collection coefficient and ice quality parameters in different areas of the surface; Step 7: Based on this, select microstructures with different geometric parameters and repeat the process from Step 2 to Step 6 multiple times, and compare the droplet collection coefficient and ice quality parameters for the same segmented area to obtain the optimal microstructure parameters for each area; Step 8, based on the structural parameters obtained in step 7 and laser direct writing technology, the laser wavelength, laser power, exposure time, scanning speed, and path parameters are adjusted to prepare a microstructure component on the surface of the substrate material; Step 9: The microstructure component obtained in step 8 is subjected to surface fluorination modification to obtain the final super-hydrophobic surface selective anti-icing structure.

2. The method for preparing a surface selective anti-icing structure facing an incoming flow environment according to claim 1, characterized in that: In step 1, the curved surface component includes a scaled airfoil, a flat plate, and a complex curved surface.

3. The method for preparing a surface selective anti-icing structure facing an incoming flow environment according to claim 1, characterized in that: In step 1, the length of the calculation domain is more than 20 times the characteristic length of the calculation model, and the width and height are both more than 5 times the characteristic length of the calculation model.

4. The method for preparing a surface selective anti-icing structure facing an incoming flow environment according to claim 1, characterized in that: In step 2, the microstructure array includes: a square column array, a cylindrical array, a pyramid array, a spherical array, and a wedge array.

5. The method for preparing a surface selective anti-icing structure facing an incoming flow environment according to claim 1, characterized in that: In step 2, the height of the microstructure array is 20 μm to 200 μm, the side length / diameter is 20 μm to 100 μm, and the spacing is 0 μm to 100 μm.

6. The method for preparing a surface selective anti-icing structure facing an incoming flow environment according to claim 1, characterized in that: In step 2, the number of the regions is 5-10.

7. The method for preparing a surface selective anti-icing structure facing an incoming flow environment according to claim 1, characterized in that: In step 2, the near-wall boundary layer is 10 layers, the expansion coefficient is 1.2, and the initial boundary layer height is y, as shown in the following formula (1): Among them, y + is the dimensionless height from the bottom wall, U τ is the tangential velocity controlled by the wall shear stress, U τ It is expressed as shown in formula (2): τ ω It is expressed as shown in formula (3): In formula (3), τ ω is the wall shear stress, ρ is the air density, U ∞ is the incoming flow velocity.

8. The method for preparing a surface selective anti-icing structure facing an incoming flow environment according to claim 1, characterized in that: In step 3, the standard for distinguishing the fluid is: a fluid with an incoming Mach number higher than 0.3 is determined to be a compressible fluid, and a fluid with a Mach number lower than 0.3 is determined to be an incompressible fluid.

9. The method for preparing a surface selective anti-icing structure facing an incoming flow environment according to claim 1, wherein: In step 4, the turbulence models are Spalart-Allmaras, k-ε, k-ω, Transition SST, Reynoldsstress, and Detached eddy simulation.

10. The method for preparing a surface selective anti-icing structure facing an incoming flow environment according to claim 1, wherein: In step 6, the LWC of the incoming droplet distribution behavior is 0.00015 kg / m 3 ~0.001kg / m 3 The droplet diameter of the incoming droplet distribution behavior is 10μm to 100μm.

Images