Optimization method and equipment for dock folded structural parts based on non-local homogenization modeling

Abstract

The present invention discloses a method and apparatus for optimizing dock folding structures based on nonlocal homogenization modeling. The method comprises: establishing a nonlocal heat conduction model based on a three-dimensional homogenization problem with a temperature gradient only in the x-direction; defining a nonlocal homogenization term and using the integration by parts method to convert the nonlocal homogenization term of the x-direction temperature gradient into the form of a temperature difference between two surfaces obtained using a finite element tool, thereby obtaining a simplified model under uniform temperature field conditions; obtaining a heat conduction model that takes into account the effects of width and height; and obtaining an effective thermal conductivity formula based on a metamaterial structure with infinite dimensions in three directions using a multiscale method and periodic boundary conditions, calculating the temperature distribution of the metamaterial structure, and optimizing the metamaterial structure. The method can more accurately simulate and predict the thermal performance of complex materials at the microstructural scale, particularly when considering nonlocal effects, thereby improving the accuracy and practicality of the heat transfer model.

Description

Technical Field

[0001] The present invention relates to the field of heat conduction of dock folding device structures, and in particular to a method and device for optimizing dock folding structural components based on non-local homogenization modeling. Background Art

[0002] With the development of shipbuilding and marine engineering technology, dock folding devices are located in docks. As important facilities for the manufacture, maintenance and overhaul of ships and other marine engineering equipment, dock folding devices generate a lot of heat during operation, which is mainly caused by mechanical movement and friction between metal parts. If the heat cannot be effectively dissipated, it may cause overheating of the structural parts, thereby affecting their performance and life, and may even cause safety accidents. In order to improve the heat dissipation performance of the dock folding device structural parts, filling them with complex lattice microstructures is one of the effective means. However, traditional heat transfer models often ignore the influence of the internal microstructure of the dock folding device structural parts on the macroscopic thermal performance, resulting in the inability to accurately describe key parameters such as temperature gradients. Although the existing homogenization method has solved this problem to some extent, it still fails to fully consider non-local effects, that is, the influence of changes in material properties at a small scale on macroscopic performance.

[0003] Therefore, how to conduct thermodynamic modeling of dock folding structures, accurately simulate and predict the thermal properties of complex materials at the microstructure scale, and optimize their heat transfer performance to improve the heat transfer performance is an urgent problem to be solved. Summary of the Invention

[0004] In response to the above-mentioned defects or improvement needs of the prior art, the present invention provides a method and equipment for optimizing dock folding structures based on non-local homogenization modeling, which can more accurately simulate and predict the thermal properties of complex materials at the microstructural scale, especially when considering non-local effects, thereby improving the accuracy and practicality of the heat transfer model.

[0005] To achieve the above objectives, the present invention adopts the following technical solutions.

[0006] In some embodiments, a method for optimizing a dock folding structure based on non-local homogenization modeling is provided, wherein the dock folding structure includes a metamaterial structure, and the method includes the following steps:

[0007] S1: Based on the three-dimensional homogenization problem with temperature gradient only in the x-direction, a non-local heat conduction model is established;

[0008] S2: Define the nonlocal homogenization terms, including the nonlocal homogenization term of the temperature gradient in the x-direction and the nonlocal homogenization term of the heat flux in the x-direction, and express the mathematical form of the volume homogenization operator and the temperature gradient;

[0009] S3: Using the method of integration by parts, the non-local homogenization term of the temperature gradient in the x-direction is converted into the temperature difference between the two surfaces obtained by the finite element tool, and a simplified model under the condition of uniform temperature field is obtained;

[0010] S4: Combining the nonlocal heat conduction model, the nonlocal homogenization term of the heat flux in the x-direction, and the simplified model under the uniform temperature field condition, the heat conduction model of the three-dimensional microstructure effect is obtained by considering the temperature gradient in the x-direction as well as the influence of width and height;

[0011] S5: Based on a metamaterial structure with infinite dimensions in three directions, a multi-scale method and periodic boundary conditions are used to obtain a calculation formula for the effective thermal conductivity; the three directions include the x-direction, the y-direction, and the z-direction based on an orthogonal coordinate system;

[0012] S6: calculating the temperature distribution of the metamaterial structure based on the effective thermal conductivity calculation formula, and optimizing the metamaterial structure based on the temperature distribution;

[0013] in,

[0014] The non-local heat conduction model in step S1 is:

[0015]

[0016] in, represents the nonlocal homogenization term of the temperature gradient in the x direction, is the effective thermal conductivity, represents the nonlocal homogenization term of the heat flux in the x direction;

[0017] The volume homogenization operator in the S2 step The definition is as follows:

[0018]

[0019] Wherein, L, W, and H represent the length, width, and height of the metamaterial structure, respectively. The length, width, and height directions correspond to the x-direction, y-direction, and z-direction, respectively.

[0020] The simplified model under the uniform temperature field condition in step S3 is:

[0021]

[0022] in, ;

[0023] The thermal conductivity model of the three-dimensional microstructure effect in step S4 is:

[0024]

[0025] in, is the contribution fraction of the nonlocal phase with size-dependent effect, are the thermal conductivities in the x, y, and z directions, respectively, and k is the thermal conductivity;

[0026] The calculation formula for the effective thermal conductivity in step S5 is:

[0027]

[0028] in is the intrinsic length;

[0029] in is the intrinsic length; the effective thermal conductivity depends not only on the temperature gradient in the x direction, but also on the y and z directions;

[0030] The height variation in the z direction is chosen to calculate the size-dependent thermal conductivity, which is used to calibrate the intrinsic length. and the non-local contribution fraction .

[0031] In some embodiments, the simplified model under the uniform temperature field condition in step S3 is to use the partial integration method and set the surface and The results are derived under the condition of uniform temperature field.

[0032] In some embodiments, the non-local homogenization term of the temperature gradient in the x direction in step S3 is The calculation is evaluated by the temperature difference on the surfaces perpendicular to the x-direction at the two ends of the volume.

[0033] In some embodiments, the extrinsic length of the metamaterial structure is compared to the intrinsic length .

[0034] In some embodiments, the effective thermal conductivity in step S5 depends not only on the temperature gradient in the x-direction, but also on the width and height.

[0035] In some embodiments, the height variation in the z direction is selected in the step S5 to calculate the size-dependent thermal conductivity to calibrate the intrinsic length. and the non-local contribution fraction .

[0036] In some embodiments, a dock folding structure optimization device based on non-local homogenization modeling is further provided, wherein the dock folding structure includes a metamaterial structure, and the dock folding structure optimization device includes the following modules:

[0037] Non-local heat conduction model building module: Based on the three-dimensional homogenization problem with temperature gradient only in the x-direction, a non-local heat conduction model is established;

[0038] Non-local homogenization term definition module: defines non-local homogenization terms, including the non-local homogenization term of the x-direction temperature gradient and the non-local homogenization term of the x-direction heat flux, and expresses the mathematical form of the volume homogenization operator and the temperature gradient;

[0039] Simplified model building module under uniform temperature field conditions: Using the partial integration method, the non-local homogenization term of the temperature gradient in the x-direction is converted into the temperature difference between two surfaces obtained by the finite element tool, and a simplified model under uniform temperature field conditions is obtained;

[0040] Thermal conductivity modeling module for 3D microstructure effects: This module combines the nonlocal heat conduction model, the nonlocal homogenization term for the x-direction heat flux, and the simplified model under uniform temperature field conditions, taking into account the temperature gradient in the x-direction as well as the effects of width and height, to derive a thermal conductivity model for 3D microstructure effects.

[0041] Effective thermal conductivity calculation formula acquisition module: Based on the metamaterial structure with infinite size in three directions, the effective thermal conductivity calculation formula is obtained using a multi-scale method and periodic boundary conditions; the three directions include the x-direction, y-direction, and z-direction based on the orthogonal coordinate system;

[0042] Optimization module: calculating the temperature distribution of the metamaterial structure based on the effective thermal conductivity calculation formula, and optimizing the metamaterial structure based on the temperature distribution;

[0043] in,

[0044] The non-local heat conduction model is:

[0045]

[0046] in, represents the nonlocal homogenization term of the temperature gradient in the x direction, is the effective thermal conductivity, represents the nonlocal homogenization term of the heat flux in the x direction;

[0047] The volume homogenization operator The definition is as follows:

[0048]

[0049] Wherein, L, W, and H represent the length, width, and height of the metamaterial structure, respectively. The length, width, and height directions correspond to the x-direction, y-direction, and z-direction, respectively.

[0050] The simplified model under the uniform temperature field condition is:

[0051]

[0052] in, ;

[0053] The heat conduction model of the three-dimensional microstructure effect is:

[0054]

[0055] in, is the contribution fraction of the nonlocal phase with size-dependent effect, are the thermal conductivities in the x, y, and z directions, respectively, and k is the thermal conductivity;

[0056] The calculation formula of the effective thermal conductivity is:

[0057]

[0058] in is the intrinsic length;

[0059] in is the intrinsic length; the effective thermal conductivity depends not only on the temperature gradient in the x direction, but also on the y and z directions;

[0060] The height variation in the z direction is chosen to calculate the size-dependent thermal conductivity, which is used to calibrate the intrinsic length. and the non-local contribution fraction .

[0061] In some embodiments, the simplified model under the uniform temperature field condition is to use the partial integration method and set the surface and The results are derived under the condition of uniform temperature field.

[0062] In some embodiments, the non-local homogenization term The calculation is evaluated by the temperature difference on the surfaces perpendicular to the x-direction at the two ends of the volume.

[0063] In some embodiments, the extrinsic length of the metamaterial structure is compared to the intrinsic length .

[0064] In some embodiments, an electronic device is also provided, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor implements any of the above-described methods when executing the program.

[0065] In some embodiments, a computer-readable storage medium is further provided, wherein the storage medium stores a computer program, and when the computer program is executed by a processor, any of the above methods is implemented.

[0066] Compared with the prior art, the present invention has the following beneficial effects:

[0067] The non-local homogenization method for calculating the thermal conductivity of the dock folding device structural parts disclosed in the present invention can more accurately simulate and predict the thermal performance of the dock folding device structural parts filled with complex microstructures, especially when considering non-local effects, thereby improving the accuracy and practicality of the heat transfer model. BRIEF DESCRIPTION OF THE DRAWINGS

[0068] Figure 1 Schematic diagram of the overall process of a dock folding structural component optimization method based on non-local homogenization modeling according to an embodiment of the present invention.

[0069] Figure 2 This is a schematic diagram of a dock folding device according to an embodiment of the present invention.

[0070] Figure 3 This is a schematic diagram of a dock folding structure according to an embodiment of the present invention.

[0071] Figure 4 This is a schematic diagram of a dock folding structure model filled with complex microstructures according to an embodiment of the present invention.

[0072] Figure 5 This is a module schematic diagram of a dock folding structure optimization device based on non-local homogenization modeling according to an embodiment of the present invention.

[0073] Figure 6 FIG. 1 is a schematic diagram of an electronic device according to an embodiment of the present invention. DETAILED DESCRIPTION

[0074] In order to make the purpose, technical solutions and advantages of the present invention more clearly understood, the present invention will be further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present invention and are not intended to limit the present invention.

[0075] In the description of this specification, the reference terms "one embodiment", "some embodiments", "example", "specific example", or "some examples" mean that the specific features, structures, materials or characteristics described in conjunction with the embodiment or example are included in at least one embodiment or example of the present invention. In this specification, the schematic representations of the above terms do not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials or characteristics described can be combined in any one or more embodiments or examples in a suitable manner. In addition, those skilled in the art can combine and combine different embodiments or examples described in this specification and features of different embodiments or examples without contradiction.

[0076] Figure 1Schematic diagram of the overall process of a dock folding structural component optimization method based on non-local homogenization modeling according to an embodiment of the present invention. Figure 4 This is a schematic diagram of a dock folding structure model filled with complex microstructures according to an embodiment of the present invention. Figure 1 and Figure 4 In some embodiments, a method for optimizing a dock folding structure based on non-local homogenization modeling is provided, wherein the dock folding structure includes a metamaterial structure filled with a complex microstructure, and the method includes the following steps:

[0077] S1: Based on the three-dimensional homogenization problem with temperature gradient only in the x-direction, a non-local heat conduction model is established;

[0078] S2: Define the nonlocal homogenization terms, including the nonlocal homogenization term of the temperature gradient in the x-direction and the nonlocal homogenization term of the heat flux in the x-direction, and express the mathematical form of the volume homogenization operator and the temperature gradient;

[0079] S3: Using the method of integration by parts, the non-local homogenization term of the temperature gradient in the x-direction is converted into the temperature difference between the two surfaces obtained by the finite element tool, and a simplified model under the condition of uniform temperature field is obtained;

[0080] S4: Combining the nonlocal heat conduction model, the nonlocal homogenization term of the heat flux in the x-direction, and the simplified model under the uniform temperature field condition, the heat conduction model of the three-dimensional microstructure effect is obtained by considering the temperature gradient in the x-direction as well as the influence of width and height;

[0081] S5: Based on a metamaterial structure with infinite dimensions in three directions, a multi-scale method and periodic boundary conditions are used to obtain a calculation formula for the effective thermal conductivity; the three directions include the x-direction, the y-direction, and the z-direction based on an orthogonal coordinate system;

[0082] S6: calculating the temperature distribution of the metamaterial structure based on the effective thermal conductivity calculation formula, and optimizing the metamaterial structure based on the temperature distribution;

[0083] in,

[0084] The non-local heat conduction model in step S1 is:

[0085]

[0086] in, represents the nonlocal homogenization term of the temperature gradient in the x direction, is the effective thermal conductivity, represents the nonlocal homogenization term of the heat flux in the x direction;

[0087] The volume homogenization operator in the S2 step The definition is as follows:

[0088]

[0089] Wherein, L, W, and H represent the length, width, and height of the metamaterial structure, respectively. The length, width, and height directions correspond to the X, Y, and Z directions, respectively.

[0090] The simplified model under the uniform temperature field condition in step S3 is:

[0091]

[0092] in, ;

[0093] The thermal conductivity model of the three-dimensional microstructure effect in step S4 is:

[0094]

[0095] in, is the contribution fraction of the nonlocal phase with size-dependent effect, are the thermal conductivities in the x, y, and z directions, respectively, and k is the thermal conductivity;

[0096] The calculation formula for the effective thermal conductivity in step S5 is:

[0097]

[0098] in is the intrinsic length.

[0099] In some embodiments of the present invention, the execution subject for implementing the above dock folding structure optimization method may be an electronic device, such as a laptop computer, a desktop computer, or other terminal device. Of course, it may also be a host computer or a server, which may be a local or remote server.

[0100] Figure 2 This is a schematic diagram of a dock folding device according to an embodiment of the present invention. Figure 3 Schematic diagram of a dock folding structure according to an embodiment of the present invention. Figure 2 and Figure 3 The dock folding device includes a folding mechanism, a mobile hydraulic oil station, a watertight junction box, etc. The folding mechanism is mainly a mechanical device for realizing the erection and collapse of the dock pier; the mobile hydraulic oil station is used to provide folding power, electrical and manual control of the device; the watertight junction box is used to collect the status signal of the outboard watertight travel switch of the folding mechanism and transmit it to the mobile hydraulic oil station for status display and control. The folding mechanism includes a folding seat, a folding cylinder, a weight, a pulley block, an outboard watertight travel switch, etc. In some embodiments, the dock folding structure can be a folding cylinder, a pulley block ( Figure 3 shown) and other structural parts.

[0101] Specifically, the process of establishing a non-local heat conduction model is as follows:

[0102] For a three-dimensional homogenization problem with a temperature gradient only in the x-direction, the nonlocal homogenization model can be expressed as:

[0103] (1)

[0104] in, represents the nonlocal homogenization term of the temperature gradient in the x direction, is the effective thermal conductivity, Represents the nonlocal homogenization term for the heat flux in the x-direction.

[0105] Specifically, they are in the following form:

[0106] (2)

[0107] (3)

[0108] Among them, the volume homogenization operator and temperature gradients are defined as follows:

[0109] (4)

[0110] (5)

[0111] Where L, W, and H represent the length, width, and height of the metamaterial structure, respectively, with the length, width, and height directions corresponding to the x, y, and z directions, respectively. Specifically, L, W, and H are the length, width, and height of a composite structure made of a metamaterial with solid network gyroid units.

[0112] Specifically, the simplified model derivation process under uniform temperature field conditions is as follows:

[0113] Using the method of integration by parts, the nonlocal homogenization term of the temperature gradient in Eq. (3) is It can also be expressed as:

[0114] (6)

[0115] If applied on the surface and The temperature field is uniform and can be further simplified as:

[0116] (7)

[0117] in:

[0118] (8)

[0119] Specifically, the derivation process of the thermal conductivity model of the three-dimensional microstructure effect is as follows:

[0120] Through equations (1), (2), and (7), the effective thermal conductivity can be solved by the following equation:

[0121] (9)

[0122] The uniform constitutive relation for heat transfer is as follows:

[0123] (10)

[0124] where k is the thermal conductivity, is the intrinsic length is the contribution fraction of the size-dependent effect of the non-local phase. x, y, and z are the coordinate positions in the x, y, and z directions, respectively. are the coordinate positions of the points adjacent to the coordinate positions x, y, and z respectively.

[0125] Substituting formula (10) into formula (9), we can obtain:

[0126] (11)

[0127] It is able to capture three-dimensional microstructural effects. Among them:

[0128] (12)

[0129] (13)

[0130] (14)

[0131] In some embodiments, the effective thermal conductivity depends not only on the temperature gradient in the x-direction, but also on the y- and z-directions. The method based on non-local homogenization modeling proposed in this application can capture three-dimensional microstructure effects.

[0132] Specifically, the derivation process of the effective thermal conductivity calculation formula is as follows:

[0133] In some embodiments, the metamaterial structure is a composite structure, including a porous titanium structure and a titanium-aluminum composite structure. For the porous titanium structure, the filler material is air. For the titanium-aluminum composite structure, the filler material is aluminum. For an infinite metamaterial structure with infinite cells in all three directions, the intrinsic length is much smaller than the extrinsic length (infinity). In some embodiments, the extrinsic length of the metamaterial structure is much smaller than the intrinsic length. That is, the nonlocal contribution can be neglected. In this case, , the size-independent thermal conductivity k can be calibrated. To obtain the size-independent thermal conductivity, we simulate a unit cell with periodic boundary conditions in all three directions. This approach is called a multiscale method. Let's set a temperature difference of 0.1K on the two surfaces of a unit cell. Combining the multiscale method with material properties, the size-independent effective thermal conductivity k is k=9.4062W / (m∙K) for the porous titanium structure and k=81.0510W / (m∙K) for the titanium-aluminum composite structure. Because the size-independent thermal conductivity k is calibrated based on the multiscale method, where infinity is achieved through the use of periodic boundary conditions, the size-independent thermal conductivity k is size-independent and therefore cannot capture size-dependent heat transfer phenomena.

[0134] Integrate equations (13) and (14), and Can be easily determined as:

[0135] (15)

[0136] (16)

[0137] According to formula (7), the can be rewritten as:

[0138] (17)

[0139] Substituting equations (15) and (16) into equation (11), we get:

[0140] (18)

[0141] In some embodiments, the effective thermal conductivity depends not only on the temperature gradient in the x-direction, but also on the width and height. In some embodiments, the height variation in the z-direction is selected to obtain a size-dependent thermal conductivity to calibrate the intrinsic length and the non-local contribution fraction In some embodiments, the composite structure is Figure 4 As shown. It has infinite length L and fixed width The height H can be obtained from Change to , in order to characterize size-dependent heat transfer phenomena. In some embodiments, Although the temperature gradient varies only in the x-direction, the nonlocal heat flux in the x-direction varies in all three directions.

[0142] Results verification: The effective thermal conductivity of porous titanium structures predicted by the non-local method, multi-scale method, parallel model and high-fidelity finite element method of this application were compared and verified. Highly size-dependent. Because the parallel model cannot account for microstructural effects, while the multiscale method ignores size-dependent effects, both methods fail to capture the highly size-dependent thermal conductivity predicted by the high-fidelity finite element method. For porous titanium structures, the parallel model's error ranges from 44.1% to 44.9% because it considers a constant temperature gradient and ignores microstructural effects. Compared to the parallel model, the multiscale method achieves higher accuracy. The multiscale method can account for microstructural effects but ignores size-dependent effects characterized by intrinsic length. The error range for the multiscale method is reduced to between 7.2% and 1.4%. Unlike the microstructure-free parallel model and the size-independent multiscale method, the proposed microstructure-enhanced nonlocal model incorporates both microstructural and size-dependent effects. Therefore, the nonlocal homogenized thermal conductivity can capture highly size-dependent heat transfer behavior and agrees well with the results evaluated by the high-fidelity finite element method.

[0143] Figure 5 This is a schematic diagram of a module of a dock folding structure optimization device based on non-local homogenization modeling according to an embodiment of the present invention. Figure 5 In some embodiments of the present application, a device for optimizing a dock folding structure based on non-local homogenization modeling is further provided. The dock folding structure includes a metamaterial structure. The device for optimizing the dock folding structure includes the following modules:

[0144] Non-local heat conduction model building module: Based on the three-dimensional homogenization problem with temperature gradient only in the x-direction, a non-local heat conduction model is established;

[0145] Non-local homogenization term definition module: defines non-local homogenization terms, including the non-local homogenization term of the x-direction temperature gradient and the non-local homogenization term of the x-direction heat flux, and expresses the mathematical form of the volume homogenization operator and the temperature gradient;

[0146] Simplified model building module under uniform temperature field conditions: Using the partial integration method, the non-local homogenization term of the temperature gradient in the x-direction is converted into the temperature difference between two surfaces obtained by the finite element tool, and a simplified model under uniform temperature field conditions is obtained;

[0147] Thermal conductivity modeling module for 3D microstructure effects: This module combines the nonlocal heat conduction model, the nonlocal homogenization term for the x-direction heat flux, and the simplified model under uniform temperature field conditions, taking into account the temperature gradient in the x-direction as well as the effects of width and height, to derive a thermal conductivity model for 3D microstructure effects.

[0148] Effective thermal conductivity calculation formula acquisition module: Based on the metamaterial structure with infinite size in three directions, the effective thermal conductivity calculation formula is obtained using a multi-scale method and periodic boundary conditions; the three directions include the x-direction, y-direction, and z-direction based on the orthogonal coordinate system;

[0149] Optimization module: calculating the temperature distribution of the metamaterial structure based on the effective thermal conductivity calculation formula, and optimizing the metamaterial structure based on the temperature distribution;

[0150] in,

[0151] The non-local heat conduction model is:

[0152]

[0153] in, represents the nonlocal homogenization term of the temperature gradient in the x direction, is the effective thermal conductivity, represents the nonlocal homogenization term of the heat flux in the x direction;

[0154] The volume homogenization operator The definition is as follows:

[0155]

[0156] Wherein, L, W, and H represent the length, width, and height of the metamaterial structure, respectively. The length, width, and height directions correspond to the x-direction, y-direction, and z-direction, respectively.

[0157] The simplified model under the uniform temperature field condition is:

[0158]

[0159] in, ;

[0160] The heat conduction model of the three-dimensional microstructure effect is:

[0161]

[0162] in, is the contribution fraction of the nonlocal phase with size-dependent effect, are the thermal conductivities in the x, y, and z directions, respectively, and k is the thermal conductivity;

[0163] The calculation formula of the effective thermal conductivity is:

[0164]

[0165] in is the intrinsic length.

[0166] In some embodiments, the simplified model under the uniform temperature field condition is to use the partial integration method and set the surface and The results are derived under the condition of uniform temperature field.

[0167] In some embodiments, the non-local homogenization term The calculation is evaluated by the temperature difference on the surfaces perpendicular to the x-direction at the two ends of the volume.

[0168] In some embodiments, the extrinsic length of the metamaterial structure is compared to the intrinsic length .

[0169] In some embodiments, the above-mentioned dock folding structure optimization device based on non-local homogenization modeling corresponds to the above-mentioned dock folding structure optimization method, and each module has the function of implementing the above-mentioned dock folding structure optimization method based on non-local homogenization modeling.

[0170] Figure 6 Schematic diagram of an electronic device according to an embodiment of the present invention. Figure 6 In some embodiments, an electronic device is also provided, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor implements any of the above-described methods when executing the program.

[0171] At the hardware level, the electronic device includes a processor, an internal bus, a network interface, a memory, and a non-volatile memory, and may also include other hardware required for the business. The processor reads the corresponding computer program from the non-volatile memory into the memory and then runs it to achieve the above Figure 1 The aforementioned method for optimizing dock folding structures based on non-local homogenization modeling. Of course, in addition to software implementations, this specification does not exclude other implementations, such as logic devices or a combination of hardware and software. In other words, the execution of the following processing flow is not limited to individual logic units but can also be hardware or logic devices. It is understandable that simply by programming the method flow in a hardware description language and programming it into an integrated circuit, a hardware circuit that implements the logical method flow can be obtained.

[0172] The above method can be implemented by a controller in any appropriate manner. For example, the controller can take the form of a microprocessor or processor and a computer-readable medium storing computer-readable program code (such as software or firmware) executable by the (micro)processor, logic gates, switches, application-specific integrated circuits (ASICs), programmable logic controllers, and embedded microcontrollers. Examples of controllers include, but are not limited to, microcontrollers. The memory controller can also be implemented as part of the control logic of the memory. It is understood that in addition to implementing the controller in a purely computer-readable program code manner, it is entirely possible to implement the same function in the form of logic gates, switches, application-specific integrated circuits, programmable logic controllers, and embedded microcontrollers by logically programming the method steps. Therefore, such a controller can be considered a hardware component, and the devices included therein for implementing various functions can also be considered as structures within the hardware component. Or even, the devices for implementing various functions can be considered as both software modules that implement the method and structures within the hardware component.

[0173] The systems, devices, modules, or units in the above embodiments may be implemented by computer chips or entities, or by products having certain functions. A typical implementation device is a computer. Specifically, the computer may be, for example, a personal computer, a laptop computer, a cellular phone, a camera phone, a smartphone, a personal digital assistant, a game console, a tablet computer, a wearable device, or a combination of any of these devices.

[0174] For the convenience of description, the above devices are described as being divided into various modules according to their functions. Of course, when implementing this specification, the functions of each module can be implemented in the same or multiple software and / or hardware.

[0175] Those skilled in the art will appreciate that the embodiments of the present application can be provided as methods, systems, or computer program products. Therefore, this specification can adopt the form of a complete hardware embodiment, a complete software embodiment, or an embodiment in combination with software and hardware. Moreover, the application can adopt the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to magnetic disk storage, CD-ROM, optical storage, etc.) that contain computer-usable program code.

[0176] The present application is described with reference to the flowcharts and / or block diagrams of the methods, devices (systems), and computer program products according to the embodiments of the present specification. It should be understood that each process and / or box in the flowchart and / or block diagram, as well as the combination of the processes and / or boxes in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 a process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0177] In some embodiments, a computer-readable storage medium is further provided, wherein the storage medium stores a computer program, and when the computer program is executed by a processor, any of the above methods is implemented.

[0178] In some embodiments, these computer program instructions may also be stored in a computer-readable memory capable of directing a computer or other programmable data processing device to operate in a specific manner, so that the instructions stored in the computer-readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 a process or multiple processes and / or boxes Figure 1 The function specified in one or more boxes.

[0179] In some embodiments, these computer program instructions may also be loaded onto a computer or other programmable data processing device so that a series of operating steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing instructions for implementing the process described in the flow. Figure 1 a process or multiple processes and / or boxes Figure 1 A step that specifies a function in one or more boxes.

[0180] In some embodiments, a computing device includes one or more processors (CPUs), input / output interfaces, network interfaces, and memory.

[0181] In some embodiments, memory may include non-permanent storage in a computer-readable medium, in the form of random access memory (RAM) and / or non-volatile memory, such as read-only memory (ROM) or flash RAM. Memory is an example of a computer-readable medium.

[0182] In some embodiments, computer-readable media include permanent and non-permanent, removable and non-removable media that can be implemented by any method or technology to store information. The information can be computer-readable instructions, data structures, program modules or other data. Examples of computer storage media include, but are not limited to, phase change memory (PRAM), static random access memory (SRAM), dynamic random access memory (DRAM), other types of random access memory (RAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), flash memory or other memory technology, compact disc read-only memory (CD-ROM), digital versatile disc (DVD) or other optical storage, magnetic cassettes, magnetic tape, magnetic disk storage or other magnetic storage devices or any other non-transmission medium that can be used to store information that can be accessed by a computing device.

[0183] It will be easily understood by those skilled in the art that the above description is merely a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of the present invention should be included in the scope of protection of the present invention.

Claims

1. A dock folding structural component optimization method based on non-local homogenization modeling, characterized in that: The dock folding structure comprises a metamaterial structure, and the method comprises the following steps: S1: Based on the three-dimensional homogenization problem with temperature gradient only in the X direction, a non-local heat conduction model is established; S2: Define the nonlocal homogenization terms, including the nonlocal homogenization term of the temperature gradient in the X direction and the nonlocal homogenization term of the heat flux in the X direction, and express the mathematical form of the volume homogenization operator and the temperature gradient; S3: Using the method of integration by parts, the non-local homogenization term of the temperature gradient in the X direction is converted into the temperature difference between the two surfaces obtained by the finite element tool, and a simplified model under the condition of uniform temperature field is obtained; S4: Combining the nonlocal heat conduction model, the nonlocal homogenization term of the heat flux in the X direction, and the simplified model under the uniform temperature field condition, the heat conduction model of the three-dimensional microstructure effect is obtained by considering the temperature gradient in the X direction and the influence of width and height; S5: Based on a metamaterial structure with infinite size in three directions, a multi-scale method and periodic boundary conditions are used to obtain a calculation formula for the effective thermal conductivity; the three directions include the x-direction, the y-direction, and the z-direction based on an orthogonal coordinate system; S6: calculating the temperature distribution of the metamaterial structure based on the effective thermal conductivity calculation formula, and optimizing the metamaterial structure based on the temperature distribution; in, The non-local heat conduction model in step S1 is: ； in, represents the nonlocal homogenization term of the temperature gradient in the x direction, is the effective thermal conductivity, represents the nonlocal homogenization term of the heat flux in the x direction; The volume homogenization operator in the S2 step The definition is as follows: ； Wherein, L, W, and H represent the length, width, and height of the metamaterial structure, respectively. The length, width, and height directions correspond to the x-direction, y-direction, and z-direction, respectively. The simplified model under the uniform temperature field condition in step S3 is: ； in, ; The thermal conductivity model of the three-dimensional microstructure effect in step S4 is: ； in, is the contribution fraction of the nonlocal phase with size-dependent effect, They are Thermal conductivity in the x-, y-, and z-directions, k is the thermal conductivity; The calculation formula for the effective thermal conductivity in step S5 is: ； in is the intrinsic length; The effective thermal conductivity depends not only on the temperature gradient in the x-direction, but also on the y- and z-directions; In the step S5, the height variation in the z direction is selected to calculate the size-dependent thermal conductivity, which is used to calibrate the intrinsic length. and the non-local contribution fraction .

2. The dock folding structure optimization method according to claim 1, characterized in that: The simplified model under the uniform temperature field condition in step S3 is based on the partial integration method and the surface and The results are derived under the condition of uniform temperature field.

3. The dock folding structure optimization method according to claim 2, characterized in that: The nonlocal homogenization term in the S3 step The calculation is evaluated by the temperature difference on the surfaces perpendicular to the x-direction at the two ends of the volume.

4. The dock folding structure optimization method according to claim 3, characterized in that: The external length of the metamaterial structure compared to the intrinsic length .

5. A dock folding structural component optimization device based on non-local homogenization modeling, characterized in that: The dock folding structure comprises a metamaterial structure, and the dock folding structure optimization device comprises the following modules: Non-local heat conduction model building module: Based on the three-dimensional homogenization problem with temperature gradient only in the x-direction, a non-local heat conduction model is established; Non-local homogenization term definition module: defines non-local homogenization terms, including the non-local homogenization term of the x-direction temperature gradient and the non-local homogenization term of the x-direction heat flux, and expresses the mathematical form of the volume homogenization operator and the temperature gradient; Simplified model building module under uniform temperature field conditions: Using the partial integration method, the non-local homogenization term of the temperature gradient in the x-direction is converted into the temperature difference between two surfaces obtained by the finite element tool, and a simplified model under uniform temperature field conditions is obtained; Thermal conductivity modeling module for 3D microstructure effects: This module combines the nonlocal heat conduction model, the nonlocal homogenization term for the x-direction heat flux, and the simplified model under uniform temperature field conditions, taking into account the temperature gradient in the x-direction as well as the effects of width and height, to derive a thermal conductivity model for 3D microstructure effects. Effective thermal conductivity calculation formula acquisition module: Based on the metamaterial structure with infinite size in three directions, the effective thermal conductivity calculation formula is obtained using a multi-scale method and periodic boundary conditions; the three directions include the x-direction, y-direction, and z-direction based on the orthogonal coordinate system; Optimization module: calculating the temperature distribution of the metamaterial structure based on the effective thermal conductivity calculation formula, and optimizing the metamaterial structure based on the temperature distribution; in, The non-local heat conduction model is: ； in, represents the nonlocal homogenization term of the temperature gradient in the x direction, is the effective thermal conductivity, represents the nonlocal homogenization term of the heat flux in the x direction; The volume homogenization operator The definition is as follows: ； Wherein, L, W, and H represent the length, width, and height of the metamaterial structure, respectively. The length, width, and height directions correspond to the x-direction, y-direction, and z-direction, respectively. The simplified model under the uniform temperature field condition is: ； in, ; The heat conduction model of the three-dimensional microstructure effect is: ； in, is the contribution fraction of the nonlocal phase with size-dependent effect, are the thermal conductivities in the x, y, and z directions, respectively, and k is the thermal conductivity; The calculation formula of the effective thermal conductivity is: ； in is the intrinsic length; the effective thermal conductivity depends not only on the temperature gradient in the x direction, but also on the y and z directions; The height variation in the z direction is selected to calculate the size-dependent thermal conductivity, which is used to calibrate the intrinsic length and the non-local contribution fraction .

6. The dock folding structure optimization device based on non-local homogenization modeling according to claim 5 is characterized in that: The simplified model under the uniform temperature field condition is based on the partial integration method and the surface and The results are derived under the condition of uniform temperature field.

7. The dock folding structure optimization device based on non-local homogenization modeling according to claim 6 is characterized in that: The nonlocal homogenization term The calculation is evaluated by the temperature difference on the surfaces perpendicular to the x-direction at the two ends of the volume.

8. The dock folding structure optimization device based on non-local homogenization modeling according to claim 7 is characterized in that: The external length of the metamaterial structure compared to the intrinsic length .

9. An electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein: When the processor executes the program, the method according to any one of claims 1 to 4 is implemented.

10. A computer-readable storage medium, characterized in that The storage medium stores a computer program, and when the computer program is executed by a processor, the method according to any one of claims 1 to 4 is implemented.

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