Adhesion prediction method considering temperature influence
By establishing an adhesion prediction model that takes temperature into account and dynamically updating the adhesion force field, the problem that existing models cannot accurately predict adhesion force under extreme temperatures is solved, thereby improving the photoelectric conversion efficiency of photovoltaic systems.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- CHINA POWER TECH INC
- Filing Date
- 2025-12-31
- Publication Date
- 2026-05-08
AI Technical Summary
Existing adhesion prediction models fail to effectively consider the influence of temperature on the adhesion process, resulting in an inability to accurately predict the interface contact state and adhesion force under extreme temperature conditions, which makes it difficult to meet the actual needs of deep space exploration photovoltaic systems.
A computational model including a rigid sphere and a deformable substrate is established, and an adhesion force field and a temperature field are applied. The adhesion force field is dynamically updated through the computational model, and a quantitative correlation between thermal strain and adhesion performance is established, including adhesion force, pull-off force, friction force and normal force. A full-process model is constructed to adapt to extreme temperature environments.
It enables accurate adhesion prediction under extreme temperature conditions, shortens the R&D cycle, reduces trial and error costs, and improves the photoelectric conversion efficiency of photovoltaic systems.
Smart Images
Figure CN121997645A_ABST
Abstract
Description
Technical Field
[0001] This invention belongs to the field of adhesion technology, and in particular relates to an adhesion prediction method that takes into account the influence of temperature. Background Technology
[0002] When the contact scale reaches the micrometer or nanometer level, adhesion becomes the dominant factor in interfacial interactions. This effect is particularly prominent in photovoltaic systems for deep space exploration missions such as lunar and Mars exploration, and has become a key issue affecting system reliability and performance. For example, the deposition and adhesion of Martian dust on the surface of solar panels caused a significant decrease in the performance of the Opportunity rover's solar panels. Although it is speculated that Martian winds can remove some dust, the risk of adhesion cannot be fundamentally eliminated. The accumulation of dust on the solar panel wings can reduce the cell conversion efficiency, and in severe cases, it can cause local shading of photovoltaic modules, generate hot spot effects and lead to local high temperatures, ultimately causing irreversible damage to the photovoltaic system. This demonstrates the importance of predicting adhesion at micro / nano-scale contact surfaces for photovoltaic systems and deep space exploration projects.
[0003] Existing adhesion prediction models suffer from a core flaw: they fail to consider the impact of temperature on the adhesion process. In lunar and Mars exploration missions, the lunar environment ranges from -143℃ to 117℃, while the average Martian environment ranges from -125℃ to 35℃. Extreme temperatures significantly alter the mechanical properties and thermal deformation states of materials: at low temperatures, materials tend to harden and become brittle, while at high temperatures they may soften or thermally degrade. Furthermore, the thermal stress induced by temperature changes (generated by the resistance to thermal expansion and contraction of materials) directly affects the interfacial contact state and the magnitude of the adhesion force. This complex influence of temperature on adhesion performance means that existing models lacking temperature field considerations cannot accurately predict adhesion behavior under extreme conditions, making it difficult to meet the practical needs of engineering scenarios such as deep space exploration photovoltaic systems. Therefore, there is an urgent need to propose an adhesion prediction method that considers temperature effects. Summary of the Invention
[0004] To address the aforementioned technical problems, this invention provides an adhesion prediction method that considers the effects of temperature, which is particularly suitable for adhesion prediction considering the effects of temperature at the micrometer or nanometer scale.
[0005] The technical solution adopted in this invention is: to provide an adhesion prediction method that considers the influence of temperature, comprising the following steps:
[0006] Step 1: Establish a computational model including a rigid sphere and a deformable substrate, and apply an adhesion force field and a temperature field at the contact interface between the rigid sphere and the deformable substrate.
[0007] Step 2: Set the boundary conditions of the calculation model, constrain the bottom edge degree of freedom of the deformable base, and drive the rigid sphere to complete the contact and friction process with the deformable base using a displacement control method;
[0008] Step 3: Run the calculation model to calculate the differential point force at the contact interface, and integrate to obtain temperature-related adhesion performance data. Based on the calculated force signal and stress state, determine the interface contact state and dynamically update the adhesion force field. The temperature-related adhesion performance data includes adhesion force, pull-off force, friction force, and normal force.
[0009] Step 4: Repeat Step 3 with thermal strain as a variable to obtain temperature-related adhesion performance data under different thermal strain conditions, and establish a quantitative correlation between thermal strain and temperature-related adhesion performance data.
[0010] Furthermore, the adhesion force Through equations The calculation yielded, where The adhesion force per unit area, For the contact area, For discrete numbers, The direction vector of the adhesive force per unit contact area.
[0011] Furthermore, the adhesion force per unit area Through equations The calculation yielded, where For surface distance, To balance the spacing, The adhesive work, This represents relative displacement.
[0012] Furthermore, based on the aforementioned thermal strain Through equations The temperature-dependent stress was calculated. ,in This is the temperature-dependent elastic modulus. For temperature-dependent total strain, The change in temperature This is the temperature-dependent coefficient of thermal expansion.
[0013] Furthermore, the frictional force is the integral of the shear stress along the friction path, and the tangential component of the temperature-related stress is the shear stress.
[0014] Furthermore, the normal force is the integral result of the normal component of the temperature-related stress over the contact area.
[0015] Furthermore, the interface contact state is determined by the equation Make a judgment when The current stress state indicates that the yield limit has not been reached, and the material remains elastic; when The time indicates that the current stress state exceeds the yield limit, the interface contact state is in a state of plastic deformation, and the adhesion force field needs to be updated; wherein, For Mises equivalent stress, For the deviatoric stress tensor, This is the temperature-dependent yield stress.
[0016] Furthermore, the temperature-dependent yield stress Through equations The calculation yielded, where The initial yield stress is temperature-dependent. This refers to the temperature-dependent hardening index. For hardening modulus, This is the equivalent plastic strain.
[0017] Furthermore, when the interface contact state results in plastic deformation, the evolution equation of the equivalent plastic strain is: ,in For the equivalent plastic strain increment, This is the shear modulus.
[0018] Furthermore, the equivalent plastic strain increment Through equations Calculation, where For the plastic strain increment tensor.
[0019] The advantages and positive effects of this invention are as follows: By adopting the above technical solution, a complete process of "modeling, calculation, iteration, and correlation" is constructed, filling the gap in the temperature field of existing models and adapting to adhesion prediction under extreme temperature environments; a quantitative correlation between thermal strain and adhesion performance is established, which helps to shorten the R&D cycle, reduce trial and error costs, and improve the photoelectric conversion efficiency of photovoltaic systems; and the influence of thermal expansion coefficient on interface adhesion force and pull-off force is predicted, making up for the lack of temperature field in existing prediction methods. Attached Figure Description
[0020] Figure 1 This is a schematic flowchart of an adhesion prediction method considering the influence of temperature according to an embodiment of the present invention.
[0021] Figure 2 This is a schematic diagram of the principle structure of a computational model according to an embodiment of the present invention;
[0022] Figure 3 This is a schematic diagram of the effect of thermal strain on adhesion force according to an embodiment of the present invention;
[0023] Figure 4 This is a schematic diagram of the effect curve of thermal strain on peeling force according to an embodiment of the present invention;
[0024] Figure 5 This is a schematic diagram of the effect curve of thermal strain on friction force according to an embodiment of the present invention;
[0025] Figure 6 This is a schematic diagram of the effect curve of thermal strain on shear stress according to an embodiment of the present invention;
[0026] In the diagram: 1-rigid sphere; 2-deformable substrate; 3-contact interface. Detailed Implementation
[0027] The present disclosure will now be described more fully with reference to the accompanying drawings, which illustrate exemplary embodiments of the present disclosure. The technical solutions of the embodiments of the present disclosure will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present disclosure, and not all embodiments. All other embodiments obtained by those skilled in the art based on the embodiments of the present disclosure without creative effort are within the scope of protection of the present disclosure.
[0028] like Figures 1-2 As shown, the present invention provides an adhesion prediction method that considers the influence of temperature, comprising the following steps:
[0029] S100 Step 1: Establish a computational model including a rigid sphere 1 and a deformable substrate 2, and apply an adhesion force field and a temperature field at the contact interface 3 between the rigid sphere 1 and the deformable substrate 2.
[0030] S200 Step 2: Set the boundary conditions of the calculation model, constrain the bottom edge degree of freedom of the deformable base 2, and drive the rigid sphere 1 to complete the contact and friction process with the deformable base 2 using displacement control.
[0031] S300 Step 3: Run the calculation model and set the movement distance required for the adhesion process. Calculate the differential point force of the contact interface 3 and integrate to obtain temperature-related adhesion performance data. Based on the calculated force signal and stress state, determine the interface contact state and dynamically update the adhesion force field. Temperature-related adhesion performance data includes adhesion force, pull-off force (peeling force), friction force and normal force.
[0032] S400 Step 4: Repeat Step 3 with thermal strain as a variable to obtain temperature-related adhesion performance data under different thermal strain conditions, and establish a quantitative correlation between thermal strain and temperature-related adhesion performance data.
[0033] Specifically, step three is repeated using thermal strain as a variable to obtain temperature-related adhesion performance data under different thermal strain conditions, such as... Figure 3 As shown, the effect of temperature on the adhesion process is obtained, where This represents the rate at which Young's modulus decreases with temperature. The coefficient of linear expansion is 1 / 3. The change in temperature As a dimensionless expression for the sliding distance, changes in adhesive force reveal that temperature has a significant impact on the adhesion process. For example... Figure 4 As shown, temperature has a significant effect on pull-off force, increasing with thermal strain. As the pull-off force continues to increase, it also shows a significant upward trend. Under these conditions, with From 2.5×10 -4 Increased to 17.5 × 10 -4 The pull-off force increased from 0.65 to 0.697. Under the condition of r=20%, as... Increased from 2.5 to 17.5 × 10 -4 The pull-off force increased from 0.687 to 0.715. For example... Figure 5 As shown, the effect of temperature on adhesive friction is obtained. With increasing thermal strain, the friction during sliding shows a significant decreasing trend. Compared to changes in adhesive work, the effect of temperature on the friction process is more significant. Figure 6 As shown, the change in shear stress during the friction process is obtained. The shear stress, expressed as a dimensionless value for the center distance, shows a significant decreasing trend with increasing thermal strain compared to 25℃. This indirectly explains the phenomenon that frictional force decreases with increasing thermal strain. From 2.5×10 -4 Increased to 17.5 × 10 -4 The shear stress decreased by 41.01%. The integral of the shear stress along the friction path is the frictional force, so the trend of frictional force and shear stress is consistent. When r = 10%, as... From 2.5×10 -4 Increased to 17.5 × 10 -4 The frictional force decreased by 17.2%. When r=20%, the frictional force decreased by 38.6%, demonstrating the significant impact of temperature changes on shear stress and frictional force. =2.5×10 -4 When r doubles, the frictional force decreases by 2.7%. =7.5×10 -4 When r doubles, the frictional force decreases by 9.2%. =17.5×10 -4 When r increases by a factor of 1, the frictional force decreases by 27.9%. This establishes a quantitative correlation between thermal strain and temperature-dependent adhesion performance data.
[0034] Using the above methods, a complete process of "modeling, calculation, iteration, and correlation" is constructed to fill the gap in the temperature field of existing models and adapt to adhesion prediction under extreme temperature environments; it realizes the systematic acquisition of core performance data such as adhesion force and pull-off force, providing direct guidance for the anti-adhesion design of photovoltaic systems; and it establishes a quantitative correlation between thermal strain and adhesion performance, helping to shorten the R&D cycle, reduce trial and error costs, and improve the photoelectric conversion efficiency of photovoltaic systems.
[0035] In one embodiment, adhesion force Through equations The calculation yielded, where The adhesion force per unit area, For the contact area, For discrete numbers, This is the direction vector of the adhesive force per unit contact area.
[0036] Specifically, the integral form of adhesion force calculation is as follows: As shown, to facilitate the computational model, the release region is divided into a finite number of tiny interconnected elements. The finite element discretization form of the adhesion force is as shown in the equation. As shown, Contact area The differential form of the adhesive force is the pull-off force, which reaches its maximum value when the rigid sphere separates from the substrate.
[0037] In one embodiment, the adhesion force per unit area Through equations The calculation yielded, where For surface distance, To balance the spacing, Adhesion work, This represents relative displacement.
[0038] Specifically, the adhesion between a rigid sphere and a deformable substrate can be represented by the relationship between the adhesive force between the interfaces and the relative displacement of the interfaces. The adhesive force between the interfaces varies with the relative distance between the interacting interfaces. This functional relationship is based on the Lennard-Jones (LJ) potential function and the continuity rule, which proposes a unit-area adhesive force model for the sliding process. The LJ potential function can be used to solve micro / nanoscale adhesion and adhesive friction problems. The main components of the LJ potential function are short-range repulsion terms and long-range van der Waals attraction terms. The expression for the LJ potential function is as follows: ,in To minimize potential, The distance between atoms. The zero potential energy distance. Based on the Derjaguin approximation and the LJ potential function, the interaction relationship between the adhesive force per unit area and the distance (relative displacement) is as follows: As shown.
[0039] In one embodiment, thermal stress (temperature-dependent stress) is generated by the expansion or contraction of the material due to temperature changes, based on thermal strain. Through equations Calculated temperature-dependent stress ,in This is the temperature-dependent elastic modulus. For temperature-dependent total strain, The change in temperature The coefficient of thermal expansion is the temperature-dependent coefficient. These represent the initial elastic modulus, initial total strain, and initial coefficient of thermal expansion, respectively. , , These are the temperature-related correction functions for the corresponding physical quantities.
[0040] In one embodiment, the frictional force is the integral of the shear stress along the friction path, and the tangential component of the temperature-dependent stress is the shear stress.
[0041] In one embodiment, the normal force is the integral of the normal component of the temperature-dependent stress over the contact area.
[0042] In one embodiment, the interface contact state is determined by an equation. Make a judgment when The current stress state indicates that the yield limit has not been reached, and the material remains elastic; when The time indicates that the current stress state exceeds the yield limit, the interface contact state is in a state of plastic deformation, and the adhesion force field needs to be updated; wherein, For Mises equivalent stress, For the deviatoric stress tensor, This is the temperature-dependent yield stress.
[0043] In one embodiment, temperature-dependent yield stress Through equations The calculation yielded, where The initial yield stress is temperature-dependent. This refers to the temperature-dependent hardening index. For hardening modulus, This is the equivalent plastic strain.
[0044] In one embodiment, when the interface contact state is one of plastic deformation, the evolution equation of the equivalent plastic strain is: ,in For the equivalent plastic strain increment, This is the shear modulus.
[0045] In one embodiment, the equivalent plastic strain increment Through equations Calculation, where For the plastic strain increment tensor.
[0046] Based on embodiments of this disclosure, this disclosure also provides an electronic device, a readable storage medium, and a computer program product.
[0047] An electronic device includes at least one processor; and a memory communicatively connected to the at least one processor; wherein the memory stores instructions executable by the at least one processor, the instructions being executed by the at least one processor to enable the at least one processor to perform the adhesion prediction method considering the effects of temperature provided in this disclosure.
[0048] Electronic devices are intended to represent various forms of digital computers, such as laptop computers, desktop computers, workstations, personal digital assistants, servers, blade servers, mainframe computers, and other suitable computers. Electronic devices can also represent various forms of mobile devices, such as personal digital processors, cellular phones, smartphones, wearable devices, and other similar computing devices. The components shown herein, their connections and relationships, and their functions are merely illustrative and are not intended to limit the implementation of the present disclosure described and / or claimed herein.
[0049] A non-transitory computer-readable storage medium storing computer instructions, wherein the computer instructions are used to cause a computer to execute the adhesion prediction method considering the effects of temperature provided in this disclosure.
[0050] The various embodiments of this disclosure can be implemented in digital electronic circuit systems, integrated circuit systems, field-programmable gate arrays (FPGAs), application-specific integrated circuits (ASICs), application-specific standard products (ASSPs), systems-on-a-chip (SoCs), complex programmable logic devices (CPLDs), computer hardware, firmware, software, and / or combinations thereof. These various embodiments may include implementations in one or more computer programs that can be executed and / or interpreted on a programmable system including at least one programmable processor, which may be a dedicated or general-purpose programmable processor, capable of receiving data and instructions from a storage system, at least one input device, and at least one output device, and transmitting data and instructions to the storage system, the at least one input device, and the at least one output device.
[0051] A computer program product includes a computer program / instructions that are executed by a processor to provide an adhesion prediction method that takes into account the effects of temperature.
[0052] The program code used to implement the methods of this disclosure may be written in any combination of one or more programming languages. This program code may be provided to a processor or controller of a general-purpose computer, special-purpose computer, or other programmable data processing apparatus, such that when executed by the processor or controller, the program code causes the functions / operations specified in the flowcharts and / or block diagrams to be implemented. The program code may be executed entirely on a machine, partially on a machine, as a standalone software package partially on a machine and partially on a remote machine, or entirely on a remote machine or server.
[0053] In the context of this disclosure, a machine-readable medium can be a tangible medium that may contain or store a program for use by or in conjunction with an instruction execution system, apparatus, or device. A machine-readable medium can be a machine-readable signal medium or a machine-readable storage medium. A machine-readable medium can be, but is not limited to, electronic, magnetic, optical, electromagnetic, infrared, or semiconductor systems, apparatus, or devices, or any suitable combination of the foregoing. More specific examples of machine-readable storage media include electrical connections based on one or more wires, portable computer disks, hard disks, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fiber, portable compact disk read-only memory (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination of the foregoing.
[0054] The embodiments of the present invention have been described in detail above, but the content described is only a preferred embodiment of the present invention and should not be considered as limiting the scope of the present invention. All equivalent changes and improvements made within the scope of the present invention should still fall within the patent coverage of the present invention.
Claims
1. An adhesion prediction method considering the effect of temperature, characterized in that, Includes the following steps: Step 1: Establish a computational model including a rigid sphere and a deformable substrate, and apply an adhesion force field and a temperature field at the contact interface between the rigid sphere and the deformable substrate. Step 2: Set the boundary conditions of the calculation model, constrain the bottom edge degree of freedom of the deformable base, and drive the rigid sphere to complete the contact and friction process with the deformable base using a displacement control method; Step 3: Run the calculation model to calculate the differential point force at the contact interface, and integrate to obtain temperature-related adhesion performance data. Based on the calculated force signal and stress state, determine the interface contact state and dynamically update the adhesion force field. The temperature-related adhesion performance data includes adhesion force, pull-off force, friction force, and normal force. Step 4: Repeat Step 3 with thermal strain as a variable to obtain temperature-related adhesion performance data under different thermal strain conditions, and establish a quantitative correlation between thermal strain and temperature-related adhesion performance data.
2. The adhesion prediction method considering temperature effects according to claim 1, characterized in that: The adhesion force Through equations The calculation yielded, where The adhesion force per unit area, For the contact area, For discrete numbers, The direction vector of the adhesive force per unit contact area.
3. The adhesion prediction method considering temperature effects according to claim 2, characterized in that: The unit area adhesion force Through equations The calculation yielded, where For surface distance, To balance the spacing, The adhesive work, This represents relative displacement.
4. The adhesion prediction method considering temperature effects according to claim 1, characterized in that: According to the thermal strain Through equations The temperature-dependent stress was calculated. ,in This is the temperature-dependent elastic modulus. For temperature-dependent total strain, The change in temperature This is the temperature-dependent coefficient of thermal expansion.
5. The adhesion prediction method considering temperature effects according to claim 4, characterized in that: The frictional force is the integral of the shear stress along the friction path, and the tangential component of the temperature-related stress is the shear stress.
6. The adhesion prediction method considering temperature effects according to claim 4, characterized in that: The normal force is the integral of the normal component of the temperature-dependent stress over the contact area.
7. The adhesion prediction method considering temperature effects according to claim 1, characterized in that: The interface contact state is expressed by the equation Make a judgment when The current stress state indicates that the yield limit has not been reached, and the material remains elastic; when The time indicates that the current stress state exceeds the yield limit, the interface contact state is in a state of plastic deformation, and the adhesion force field needs to be updated; wherein, For Mises equivalent stress, For the deviatoric stress tensor, This is the temperature-dependent yield stress.
8. The adhesion prediction method considering temperature effects according to claim 7, characterized in that: The temperature-dependent yield stress Through equations The calculation yielded, where The initial yield stress is temperature-dependent. This is the temperature-dependent hardening index. For hardening modulus, This is the equivalent plastic strain.
9. The adhesion prediction method considering temperature effects according to claim 8, characterized in that: When the interface contact state is one of plastic deformation, the evolution equation of the equivalent plastic strain is: ,in For the equivalent plastic strain increment, This is the shear modulus.
10. The adhesion prediction method considering temperature effects according to claim 9, characterized in that: The equivalent plastic strain increment Through equations Calculation, where For the plastic strain increment tensor.