Bridge deck reduced scale model design method and experiment system in plateau environment

Abstract

The invention provides a bridge deck reduced scale model design method and experiment system in a plateau environment, and the design method comprises the steps: building a multi-factor coupling similarity criterion based on a similarity principle, physical parameters affecting the prototype structure performance of a bridge deck, and plateau environment parameters; determining a dynamic stress similarity ratio model based on a multi-factor coupling similarity criterion and the plateau environment parameters; based on the dynamic stress similarity ratio model and the section shape and size of the bridge deck prototype structure, performing scale design on the bridge deck prototype structure to obtain an initial scale model; and performing simulation experiment and simulation verification on the initial scale model based on a preset numerical simulation strategy and a preset plateau environment simulation strategy, and performing parameter optimization of the dynamic stress ratio similar model to design a target scale model. According to the scheme provided by the invention, experimental simulation of the bridge deck in the plateau environment can be efficiently and accurately carried out, and the experimental simulation cost is reduced.

Description

TECHNICAL FIELD

[0001] The application relates to the technical field of material scale design, in particular to a bridge deck panel scale model design method and experimental system in a plateau environment. BACKGROUND

[0002] At present, the scale experiment method for the plateau bridge has obvious defects: the traditional research mainly focuses on the reduction of geometric size, but the synergistic effect of the plateau extreme environment and the structure stress is not fully considered. The scale ratio of the environmental parameters (such as ultraviolet intensity, temperature gradient and oxygen concentration) lacks scientific definition in the existing method, which leads to a significant deviation between the model and the actual working condition; at the same time, the correlation model of the mechanical parameters and the size effect in the theoretical analysis is not perfect, and it is difficult to accurately reflect the real response of the structure under complex load. These problems make the reliability of the scale experiment result insufficient, and restrict the optimization design and performance verification of the plateau bridge deck panel.

[0003] Therefore, it is urgent to establish a systematic high-precision scale design theory to solve the problem of constructing the similarity relationship of the environment-mechanical multi-factor coupling and provide more scientific experimental support for the plateau engineering. SUMMARY

[0004] The technical problem to be solved by the application is to provide a bridge deck panel scale model design method and experimental system in a plateau environment, to restore the fatigue performance of the bridge in a real environment with high precision, and to provide high-reliability experimental support for the optimization design of the plateau engineering equipment.

[0005] To solve the above technical problems, an embodiment of the application provides a bridge deck panel scale model design method in a plateau environment, comprising:

[0006] Based on the similarity principle, the physical parameters affecting the performance of the bridge deck panel prototype structure and the plateau environment parameters, a multi-factor coupling similarity criterion is constructed;

[0007] Based on the multi-factor coupling similarity criterion and the plateau environment parameters, a dynamic stress similarity ratio model of the bridge deck panel prototype structure and its corresponding scale model under the condition of material performance attenuation is determined; the dynamic stress similarity ratio model is a coupling effect model integrating freeze-thaw damage and thermal-optical-chemical effects in a plateau extreme environment, so as to ensure the fatigue performance equivalence of the bridge deck panel prototype structure and the scale model in a plateau extreme environment; the attenuation of the material performance of the bridge deck panel prototype structure is affected by the plateau environment parameters and is represented by a preset material performance attenuation model;

[0008] Based on the dynamic stress similarity ratio model and the cross-sectional shape and size of the bridge deck panel prototype structure, the bridge deck panel prototype structure is designed in scale to obtain an initial scale model corresponding to the bridge deck panel prototype structure;

[0009] Based on the preset numerical simulation strategy and the preset highland environment simulation strategy, simulation experiments and simulation verification are performed on the initial scale model, and parameters in the dynamic stress similarity ratio model are optimized based on simulation results or simulation verification results to design the target scale model.

[0010] In one embodiment, based on the similarity principle and physical parameters affecting the performance of the bridge deck prototype structure, a multi-factor coupled similarity criterion is constructed, including:

[0011] Based on the preset Buckingham π theorem, the physical parameters and the highland environment parameters are dimensionally homogenized to obtain a corresponding group of dimensionless π numbers;

[0012] Based on the group of dimensionless π numbers, a plurality of parameter similarity ratios between the bridge deck prototype structure and its corresponding scale model parameters are determined, including a geometric similarity ratio, a stress similarity ratio, a load similarity ratio, a temperature gradient similarity ratio, an elastic modulus similarity ratio, and a freeze-thaw cycle similarity ratio, and the plurality of parameter similarity ratios constitute the multi-factor coupled similarity criterion.

[0013] In one embodiment, based on the multi-factor coupled similarity criterion and the highland environment parameters, a dynamic stress similarity ratio model of the dynamic stress similarity ratio model of the bridge deck prototype structure and its corresponding scale model under the condition of material performance degradation is determined, including:

[0014] Based on the elastic modulus similarity ratio and the geometric similarity ratio, a mechanical similarity factor is determined, which reflects the stress response relationship between the scale model and the bridge deck prototype structure under static load;

[0015] Based on the geometric similarity ratio and the preset material performance degradation model, a material performance degradation correction factor is determined, which represents the degradation rate of material strength or durability over time and environmental load unified to the same time scale to ensure dynamic similarity of performance degradation between the scale model and the bridge deck prototype structure;

[0016] Based on the temperature gradient similarity ratio and a preset degradation factor, an environmental coupling correction factor is determined, which represents the synergistic acceleration effect of temperature change, ultraviolet intensity, and oxygen concentration in the highland environment parameters on material performance degradation;

[0017] Based on the stress similarity ratio, the mechanical similarity factor, the material performance degradation correction factor, and the environmental coupling correction factor, the dynamic stress similarity ratio model is determined.

[0018] In one embodiment, determining the material performance degradation correction factor based on the geometric similarity ratio and the preset material performance degradation model includes:

[0019] In the scaled-down model, the time parameters and number of freeze-thaw cycles of the preset material property degradation model are scaled down according to the geometric similarity ratio;

[0020] Based on the results of the scaled-down adjustment, the material performance degradation term in the preset material performance degradation model is corrected to obtain the material performance degradation correction factor.

[0021] In one embodiment, the preset material performance degradation model is expressed as:

[0022] ;

[0023] in, This indicates the time t and the number of freeze-thaw cycles. The material property degradation coefficient under action; Indicates the initial performance coefficient of the material; Indicates the degradation of material properties; Indicates the oxidation rate; The constant represents the freeze-thaw damage rate; time t is used to characterize the aging degradation of material properties.

[0024] In one embodiment, the dynamic stress similarity ratio model is expressed as:

[0025] ;

[0026] in, This represents the dynamic stress similarity ratio model; This indicates the similarity ratio of the elastic modulus; This represents the geometric similarity ratio; This represents the mechanical similarity factor; Indicates the oxidation rate; This represents the freeze-thaw damage rate constant; The number of freeze-thaw cycles is represented by t; t represents time, used to characterize the aging degradation of material properties. The material's performance degradation correction factor is represented by ΔT; ΔT represents the temperature gradient of the high-altitude environment; I UV Indicates the intensity of ultraviolet radiation in a high-altitude environment; Indicates the oxygen concentration in a high-altitude environment; This represents the environmental coupling correction factor.

[0027] In one embodiment, the multi-factor coupling similarity criterion further includes boundary condition similarity, which includes consistency of external excitation borne by structure surface, consistency of load action sequence, consistency of constraint condition, and consistency of initial condition.

[0028] In one embodiment, the design method of the bridge deck panel scale model in the plateau environment further includes:

[0029] Based on a preset scale strategy, the dynamic stress similarity ratio model, and the cross-sectional size and shape of the composite layer bridge deck panel structure in the bridge deck panel prototype structure, the composite layer bridge deck panel structure in the bridge deck panel prototype structure is designed by scale; the preset scale strategy includes a stepwise thickness reduction strategy and a nanometer coating compensation strategy.

[0030] In one embodiment, based on a preset numerical simulation strategy and a preset plateau environment simulation strategy, the initial scale model is subjected to simulation experiment and simulation verification, including:

[0031] Based on a preset simulation analysis software, finite element models of the bridge deck panel prototype structure and the initial scale model are established, and multi-physical field coupling analysis of preset simulation temperature gradient, preset simulation ultraviolet intensity, preset simulation oxygen content, and preset simulation dynamic load is integrated, and by comparing stress distribution cloud maps of the finite element model corresponding to the bridge deck panel prototype structure and the finite element model corresponding to the initial scale model, simulation stress distribution deviation of the bridge deck panel prototype structure and the initial scale model is determined.

[0032] Local full-size model pieces of the bridge deck panel prototype structure and scale model test pieces corresponding to the local full-size model pieces are constructed, and fatigue loading experiments are carried out on the local full-size model pieces and the scale model test pieces in a simulation cabin of a low-temperature and low-pressure corrosion environment, and fatigue crack propagation lengths of the local full-size model pieces and the scale model test pieces are monitored through a preset strain gauge array in the simulation cabin, and simulation stress deviation of the local full-size model pieces and the scale model test pieces is determined.

[0033] Embodiments of the present application also provide an experimental system of a bridge deck panel scale model in a plateau environment, wherein the bridge deck panel scale model is designed by the design method of the bridge deck panel scale model in a plateau environment described in the above embodiments, and the experimental system includes:

[0034] A simulation cabin, which includes a foldable experimental box body and a sensor assembly, the sensor assembly being arranged in the foldable experimental box body; the simulation cabin is used to provide a place for fatigue loading experiment and simulate a plateau environment for the scale model according to experimental conditions required by the fatigue loading experiment; the sensor assembly is used to monitor real-time state data in the simulation cabin in real time; and

[0035] A central control module is in communication with the simulation cabin and an upper computer, and a multi-altitude environment parameter library and a dynamic parameter conversion model are stored in the central control module; the dynamic parameter conversion model determines a target altitude and a target working condition corresponding to the target altitude in the multi-altitude environment parameter library according to the fatigue loading experiment requirement, and dynamically scales the target working condition to obtain an experimental working condition required by the fatigue loading experiment.

[0036] The above scheme of the present application at least has the following beneficial effects:

[0037] 1. A non-linear dynamic stress similarity ratio model is established by coupling multi-factor similarity criteria and plateau environment parameters, temperature gradient, oxygen concentration, ultraviolet intensity and other parameters in the plateau environment are deeply coupled with the performance degradation law of the bridge deck slab material, and the stress distribution and fatigue crack propagation characteristics of the scale model under extreme conditions such as ultraviolet radiation, low temperature and low pressure are kept dynamically consistent with the prototype.

[0038] 2. A ladder type bridge deck slab composite layer scaling strategy and a nano coating compensation strategy are used to ensure the threshold of corrosion resistance while accurately matching the fatigue damage equivalence, breaking through the bottleneck that the corrosion function and the bearing performance are difficult to coordinate in the traditional scale model.

[0039] 3. The initial scale model is verified by combining the numerical simulation of multi-physical field coupling and the bidirectional verification mechanism of plateau environment simulation experiment, realizing the double checking of structure response under complex boundary conditions and dynamic load, and significantly improving the prediction accuracy of the scale model in the plateau special environment.

[0040] 4. The experiment system is constructed, and a multi-altitude environment database and a dynamic parameter conversion model are integrated in the experiment system to support the accurate reproduction of environmental conditions at different altitude gradients, effectively reducing the difficulty of experimental parameter calibration, and providing high-reliability experimental support for the optimization design of plateau engineering equipment.

[0041] It should be understood that the implementation of any embodiment of the present application does not mean that multiple or all of the above beneficial effects are simultaneously possessed or achieved. BRIEF DESCRIPTION OF DRAWINGS

[0042] In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings needed to be used in the embodiments or prior art description will be briefly introduced below. Obviously, the drawings in the following description are only exemplary, and those skilled in the art can also obtain other implementation drawings according to the provided drawings without creating any creative labor.

[0043] The structures, proportions, sizes, etc. shown in the specification are merely used to cooperate with the content disclosed in the specification for understanding and reading by those skilled in the art, and are not used to limit the conditions that can be implemented by the application, so they do not have technical substantive significance. Any modification of the structure, change of the proportional relationship or adjustment of the size, without affecting the effect that can be produced by the application and the purpose that can be achieved, should still fall within the scope of the technical content disclosed by the application.

[0044] Figure 1 The high-altitude environment bridge deck panel reduced-scale model design method flowchart provided by the embodiment of the application;

[0045] Figure 2 The composite bridge deck panel ladder-type thickness reduction schematic diagram provided by an optional embodiment of the application;

[0046] Figure 3 The composite bridge deck panel coated with a nano coating schematic diagram provided by an optional embodiment of the application;

[0047] Figure 4 The prototype structure stress distribution nephogram provided by an optional embodiment of the application;

[0048] Figure 5 The reduced-scale model stress distribution nephogram provided by an optional embodiment of the application;

[0049] Figure 6 The stress analysis diagram of the key part of the node top plate weld toe in the prototype structure provided by an optional embodiment of the application;

[0050] Figure 7 The stress analysis diagram of the key part of the node top plate weld toe in the reduced-scale model provided by an optional embodiment of the application;

[0051] Figure 8 The fatigue crack propagation length and cycle number relationship diagram of the local full-scale model piece and the corresponding reduced-scale model test piece provided by an optional embodiment of the application;

[0052] Figure 9 The crack propagation length and stress intensity factor ΔK1 relationship diagram of the local full-scale model piece and the corresponding reduced-scale model test piece provided by an optional embodiment of the application;

[0053] Figure 10 The reduced-scale model design flowchart provided by an optional embodiment of the application;

[0054] Figure 11 The folding experimental box three-dimensional structure schematic diagram in the experimental system provided by the embodiment of the application;

[0055] Figure 12is a schematic view of the folded folding experimental box provided by an optional embodiment of the present application;

[0056] Figure 13 is a schematic view of the unfolded folding experimental box provided by an optional embodiment of the present application;

[0057] Figure 14 is a schematic block diagram of a computing device provided by an embodiment of the present application.

[0058] BRIEF DESCRIPTION OF DRAWINGS A, nano coating; B, stainless steel layer; C, weathering steel layer;

[0059] 1, folding experimental box; 11, first telescopic part; 12, second telescopic part; 13, connecting end part; 14, observation window; 15, loading notch; 16, box end part; 17, box tail part; 2, liquid nitrogen storage; 3, oxygen generator; 4, turbulence generator; 5, loading device; 6, external device support skeleton; 7, rubber skin. DETAILED DESCRIPTION

[0060] Exemplary embodiments of the present disclosure will be described in greater detail below with reference to the accompanying drawings. While exemplary embodiments of the present disclosure are shown in the drawings, it is understood that the present disclosure can be embodied in various forms without being limited by the embodiments set forth herein. Rather, these embodiments are provided so that the present disclosure can be thoroughly understood and fully conveyed to those skilled in the art.

[0061] It should be understood that the terms "comprise / comprising", "consist / consisting" or any other variant thereof are intended to cover non-exclusive inclusions, such that a product, device, process or method that includes a list of elements does not only include those elements, but can also include other elements not expressly listed or inherent to such product, device, process or method. Without more limitations, the elements defined by the phrase "comprise / comprising", "consist / consisting" do not exclude the presence of additional identical elements in the product, device, process or method that includes the elements.

[0062] In addition, the terms "first", "second" are only for descriptive purposes and cannot be understood as indicating or implying relative importance or implicitly indicating the number of indicated technical features. Therefore, the features defined with "first", "second" can explicitly or implicitly include one or more of the features. In the description of the present application, the meaning of "a plurality of" is two or more, unless otherwise specifically limited.

[0063] As Figure 1 shown, an embodiment of the present application proposes a bridge deck panel scale model design method in plateau environment, which can include:

[0064] Step 11, based on similar principles, physical parameters affecting the performance of the bridge deck prototype structure and plateau environmental parameters, a multi-factor coupling similarity criterion is constructed;

[0065] Step 12, based on the multi-factor coupling similarity criterion and the plateau environmental parameters, a dynamic stress similarity ratio model of the bridge deck prototype structure and its corresponding scale model under the condition of material performance degradation is determined; the dynamic stress similarity ratio model is a coupling effect model integrating freeze-thaw damage and thermal-optical-chemical effects under extreme plateau environments, to ensure the fatigue performance equivalence of the bridge deck prototype structure and the scale model under extreme plateau environments; the degradation of the material performance of the bridge deck prototype structure is affected by the plateau environmental parameters and is represented by a pre-set material performance degradation model;

[0066] Step 13, based on the dynamic stress similarity ratio model and the cross-sectional shape and size of the bridge deck prototype structure, the bridge deck prototype structure is scaled down to obtain an initial scale model corresponding to the bridge deck prototype structure;

[0067] Step 14, based on the pre-set numerical simulation strategy and the pre-set plateau environment simulation strategy, the initial scale model is simulated and verified, and based on the simulation results or the verification results, the parameters in the dynamic stress similarity ratio model are optimized to design the target scale model.

[0068] In this embodiment, based on the similarity principle, a multi-factor coupling similarity criterion is constructed to accurately identify and quantify all key physical parameters affecting the performance of the bridge deck and the plateau environmental parameters. At the same time, methods such as dimensional analysis can be used to ensure that the behavior of the scale model and the bridge deck prototype structure in these physical parameters is comparable, thereby ensuring the accuracy of the subsequent design of the scale model and the experiment based on the scale model. Due to the unique nature of the plateau environment, which is characterized by extreme and variable conditions such as significant temperature gradient, high-intensity ultraviolet radiation, low oxygen concentration, and frequent freeze-thaw cycles, these factors have a nonlinear impact on material performance (such as elastic modulus and oxidation rate). Based on the multi-factor coupling similarity criterion, the nonlinear relationship between the physical parameters of the prototype structure and the plateau environmental parameters is derived to establish a dynamic stress similarity ratio model considering the material performance degradation of the prototype structure, to simultaneously couple multiple factors such as plateau environment, external load, and size effect, thereby truly and accurately reflecting the impact of the plateau environment on the material performance of the bridge deck prototype structure of the original bridge, to ensure the dynamic consistency of the scale model in simulating the aging process of the prototype structure, and thereby ensuring the accuracy of the fatigue loading experiment of the scale model;

[0069] Further, based on the determined dynamic stress similarity ratio model and the cross-sectional shape and size of the bridge deck plate operation structure, the prototype structure is designed in scale; in the scale design process, the size of the model and other design parameters should be designed in accordance with the dynamic stress similarity ratio model, so that the scale model can accurately simulate the complex response of the prototype structure in the plateau environment;

[0070] Further, to ensure that the dynamic response of the scale model in the plateau extreme environment is highly consistent with the prototype structure, the feasibility of the designed original scale model is verified by preset numerical simulation and plateau environment simulation experiment, which can realize double checking of the structure response under complex environment and dynamic load on the one hand, and can also adjust the parameters in the dynamic stress similarity ratio model in time according to the verification result on the other hand; when double verification is carried out, the stress deviation of the prototype structure and the original scale model can be compared respectively, if the stress deviation of the double verification is within the set threshold range, it is considered that the current original scale model meets the design requirements, then the original scale model is determined as the target scale model for subsequent fatigue loading experiment; otherwise, steps 11 to 13 are repeated to optimize the parameters in the dynamic stress similarity ratio model, and the original scale model is designed and double verified based on the optimized dynamic stress similarity ratio model in turn until the target scale model meeting the requirements is obtained.

[0071] Based on the dynamic stress similarity ratio model coupled with the plateau environment parameters and the physical parameters, the scale model corresponding to the bridge deck plate prototype structure is designed to restore the fatigue performance of the bridge in the real environment size with high precision, solve the difficulty of constructing the similarity relationship of the existing environment-mechanical multi-factor coupling, and provide more scientific and reliable experimental support for the plateau engineering; at the same time, the complex behavior in the real plateau environment is accurately simulated on the smaller scale model, which reduces the demand for full-size field experiment which is expensive, time-consuming and complex logistics, provides a more reliable and economical durability evaluation method for key infrastructure projects in high-altitude areas, thereby improving the infrastructure resilience while effectively reducing the long-term operation risk and maintenance cost.

[0072] In an optional embodiment of the present application, the above step 11 can include:

[0073] Step 111, based on the preset Buckingham pi theorem, the physical parameters and the plateau environment parameters are dimensionally homogeneous, to obtain the corresponding dimensionless pi number group;

[0074] In step 112, based on the dimensionless pi number group, a plurality of parameter similarity ratios between the bridge deck prototype structure and its corresponding scale model are determined, including geometric similarity ratio, stress similarity ratio, load similarity ratio, temperature gradient similarity ratio, elastic modulus similarity ratio, and freeze-thaw cycle similarity ratio, and the plurality of parameter similarity ratios constitute a multi-factor coupling similarity criterion.

[0075] In this embodiment, first, the key physical parameters and highland environment parameters are dimensionally homogenized to make the bridge deck prototype structure and the scale model comparable in multiple parameters;

[0076] Here, the physical parameters can include the geometric dimensions of the bridge deck prototype structure (such as length L, thickness d1, cross-sectional joint size d2, etc.), material parameters (such as elastic modulus E, thermal expansion coefficient α, density ρ, yield strength σy, and material oxidation rate k(T), etc.), mechanical parameters (such as stress σ, load P, strain ε, etc.), and the highland environment parameters can include temperature gradient ΔT, ultraviolet intensity I UV , oxygen concentration W O2 , and the number of freeze-thaw cycles N f under highland environment;

[0077] Here, dimension analysis can be performed by pre-setting the platinum Buckingham π theorem to obtain a plurality of dimensionless pi number groups, each of which represents the physical similarity relationship between the scale model and the prototype structure;

[0078] Through dimensionally homogenized processing, the plurality of dimensionless pi number groups obtained can be expressed as:

[0079] represents stress-load geometric similarity to ensure that the proportional relationship of stress and load under the influence of geometric size in the scale model remains consistent with the prototype structure;

[0080] represents material stiffness matching to ensure that the product of material elastic modulus and geometric size is proportional to the load and remains consistent between the model and the prototype;

[0081] represents thermal gradient and thermal expansion coupling similarity, which captures the complex interaction between temperature change, structure size, and material thermal expansion coefficient;

[0082] similarity of environmental factors (such as oxygen concentration or corrosion rate) ensures that environmental degradation processes such as oxidation and corrosion are properly simulated in the scale model; where D is the oxygen diffusion coefficient (dimension L 2 T -1 );

[0083] This represents the similarity between the number of freeze-thaw cycles and material damage, ensuring accurate reproduction of cumulative damage from freeze-thaw cycles in cold, high-altitude environments; where B is the material damage coefficient (dimension L). 2 T -1 );

[0084] This indicates the coupling between ultraviolet intensity and material performance degradation, taking into account the photoaging effect caused by high-intensity ultraviolet radiation in plateau regions.

[0085] Furthermore, based on multiple dimensionless π number groups, several parameter similarity ratios between the scaled-down model and the prototype structure can be defined, as follows (where lowercase p represents the parameters of the original structure, and m represents the parameters of the scaled-down model):

[0086] Geometric similarity ratio λ L =L p / L m This similarity ratio represents the reduction ratio of all linear dimensions of the scaled model relative to the prototype, in order to maintain an accurate reproduction of the geometry;

[0087] Stress similarity ratio λ σ =σ p / σ m =1, this similarity ratio means that the internal stress distribution of the scaled model under appropriately scaled loads must be completely consistent with the prototype structure;

[0088] Temperature gradient similarity ratio λ ΔT =ΔT p / ΔT m =1 / λ L This similarity ratio takes into account the consistency of the coefficient of thermal expansion, which means that in a smaller scaled-down model, a larger temperature gradient needs to be applied to produce an equivalent thermal strain.

[0089] freeze-thaw cycle similarity ratio This similarity ratio specifies how the number of freeze-thaw cycles in the scaled-down model is adjusted to simulate the equivalent damage accumulation effect in the prototype structure, where λ B λ represents a parameter indicating the material's resistance to freeze-thaw damage, reflecting the relative difference in resistance between the prototype structure material and the scaled-down model material. B >1 indicates that the prototype structure material is more durable (deteriorates more slowly), so the scaled-down model needs more iterations. Increase); λ B <1 indicates that the prototype material is more susceptible to damage (damages faster), so the scaled-down model requires fewer cycles. Decrease); λ B =1 indicates that the materials have completely identical freeze-thaw properties, so the material item does not affect scaling;

[0090] Load similarity ratio λP = P p / P m = λ L 2 , which indicates that the load applied on the model should be scaled by the square of the geometric dimension, which is consistent with the scaling law of area, ensuring the accurate simulation of pressure or distributed load.

[0091] In this embodiment, the stress similarity ratio (λ σ ) is set to 1, i.e. the scaled-down model is required to have the same stress distribution as the prototype structure, to ensure that the stress state and fatigue performance of the scaled-down model are directly comparable to those of the prototype structure, without the need for a complex stress scaling factor.

[0092] In an optional embodiment of the present application, the above step 12 can include:

[0093] Step 121, determining a mechanical similarity factor based on the elastic modulus similarity ratio and the geometric similarity ratio, the mechanical similarity factor reflecting the stress response relationship between the scaled-down model and the bridge deck prototype structure under static load, which constitutes the basic mechanical scaling basis; the mechanical similarity factor can be expressed as: ; wherein, represents the elastic modulus similarity ratio;

[0094] Step 122, determining a material performance decay correction factor based on the geometric similarity ratio and a preset material performance decay model, the material performance decay correction factor representing the decay rate of material strength or durability over time and environmental load unified to the same time scale, to ensure dynamic similarity of performance decay between the scaled-down model and the bridge deck prototype structure;

[0095] Specifically, it can include:

[0096] Step 1221, in the scaled-down model, the time parameter and the number of freeze-thaw cycles of the preset material performance decay model are scaled and adjusted according to the geometric similarity ratio, to ensure that the scaled-down model can accurately reflect the long-term aging process of the prototype structure;

[0097] Step 1222, based on the results of the scaled-down adjustment, the material performance decay term in the preset material performance decay model is corrected to obtain the material performance decay correction factor.

[0098] Here, the material performance decay term is corrected to unify the decay rates of the prototype structure and the model to the same "aging" time scale. By dividing the number of freeze-thaw cycles by the square of the geometric similarity ratio λL², it is ensured that the cumulative damage and performance degradation of the material in the fatigue loading experiment are consistent with the performance dynamics of the prototype under the same service time or cycle number, which is crucial for accurately predicting the long-term durability of the prototype structure from the accelerated experimental results.

[0099] Here, the pre-defined material property degradation model is expressed as:

[0100] ;

[0101] in, This indicates the time t and the number of freeze-thaw cycles. The material property degradation coefficient under action; Indicates the initial performance coefficient of the material; Indicates the degradation of material properties; Indicates the oxidation rate; The freeze-thaw damage rate constant is represented (which can be calibrated through freeze-thaw cycle experiments); time t is used to characterize the aging degradation of material properties.

[0102] Due to the time similarity ratio λ t =λ L 2 Therefore, the material property degradation term can be corrected to the following material property degradation correction factor: This correction dynamically adjusts the aging rate of the scaled-down model to ensure that its performance degradation is consistent with the prototype structure under the same time or number of cycles, so that accelerated experiments can truly reflect the changes in material properties under actual service conditions.

[0103] Step 123: Based on the temperature gradient similarity ratio and the preset attenuation factor, determine the environmental coupling correction factor. The environmental coupling correction factor represents the synergistic accelerating effect of temperature change, ultraviolet intensity and oxygen concentration in the plateau environment on the attenuation of material performance.

[0104] In this embodiment, an environmental coupling factor is first introduced based on the temperature gradient similarity ratio and the oxygen content similarity ratio to incorporate environmental changes such as temperature, oxygen concentration, and ultraviolet radiation into the scaled-down model. This quantifies the additional impact of these environmental factors on material performance degradation, thereby ensuring the accuracy of fatigue loading experiments. Preferably, the environmental coupling factor can be expressed as... Where ΔTm and ΔTp represent the temperature gradients of the scaled-down model and the prototype structure, respectively, and the temperature gradient ratio is... It reflects the relative difference in temperature fluctuation between the scaled-down model and the prototype structure. Due to the huge diurnal temperature difference in the plateau region, significant thermal stress will be caused, which will accelerate fatigue damage. The temperature gradient ratio can effectively capture the influence of thermal stress. and The oxygen concentrations for the prototype structure and the scaled-down model are respectively. The influence of the low-oxygen environment at high altitude on the oxidation and corrosion rate of materials was considered in order to simulate specific corrosion effects; This represents the ultraviolet intensity of the scaled model, and the ultraviolet intensity term... The accelerated effect of high-intensity ultraviolet radiation in plateau area on the photo-aging process of materials (e.g. coating) is quantified; both γ and β represent preset attenuation factors, both of which can be empirical parameters calibrated through accelerated corrosion experiments, reflecting the specific contribution and interaction intensity of different environmental factors on the aging rate of materials, so that the scale model can accurately simulate the response of the real material.

[0105] Further, the environmental coupling factor can be modified by a multiplication term (i.e. environmental coupling modification factor) to quantify the additional impact of environmental differences on material aging, ensuring that the fatigue loading experiment can reproduce the complex effects of multi-factor coupling in the real plateau environment. When the actual environmental temperature or ultraviolet intensity is greater than the target environment, then f>0, resulting in a decrease in the stress similarity ratio λ σ , indicating that the performance of the scale model deteriorates faster than the prototype structure; if the environmental conditions are consistent, then f=0, in which case the environmental coupling modification factor degenerates to 1, i.e. only the inherent attenuation effect of the material is considered (attenuation following the material performance attenuation model).

[0106] In step 124, a dynamic stress similarity ratio model is determined based on the stress similarity ratio, the mechanical similarity factor, the material performance attenuation modification factor, and the environmental coupling modification factor.

[0107] Here, the dynamic stress similarity ratio model can be expressed as:

[0108] ;

[0109] wherein λ represents the dynamic stress similarity ratio, which is consistent with λ ; σ represents the elastic modulus similarity ratio; represents the geometric similarity ratio; represents the mechanical similarity factor; represents the oxidation rate; represents the freeze-thaw damage rate constant; represents the number of freeze-thaw cycles; t represents time, used to represent the time-dependent decay of material performance; represents the material performance attenuation modification factor; ΔT represents the temperature gradient of the plateau environment; I UV represents the ultraviolet intensity of the plateau environment; represents the oxygen concentration of the plateau environment; represents the environmental coupling modification factor.

[0110] ​By coupling the mechanical similarity factor, the material performance attenuation correction factor and the environmental coupling correction factor through the dynamic stress similarity ratio model, the traditional static scale design is converted into the dynamic scale design (dynamic attenuation of material performance and dynamic environmental coupling correction factor), so as to capture the environmental change to the degradation mechanism of material performance and influence, ensure the fatigue performance equivalence of the scale model in the plateau extreme environment and the prototype structure, and further improve the accuracy and reliability of the long-term performance prediction of the bridge deck plate structure under the actual service condition.

[0111] In an optional embodiment of the application, the multi-factor coupling similarity criterion can also include a dynamic similarity principle; when designing the scale model, the dynamic problem is considered, such as the existence of earthquakes and frequency vibration problems, and since the modal parameter similarity relationship (modal frequency ratio, modal stiffness ratio and modal mass ratio) of the scale model and the prototype structure is the core theoretical basis for ensuring the consistency of the dynamic response of the scale model and the prototype structure, the design of the scale model should also follow the dynamic similarity principle, and the derivation process is based on Newton's second law, dimensional analysis and similarity principle, and specifically as follows:

[0112] Modal frequency ratio: ;

[0113] Modal stiffness ratio: ;

[0114] Modal mass ratio: ;

[0115] (1) From the above, the geometric scale ratio is λ L =L p / L m , the stiffness scale ratio is , and the mass scale ratio is , so the frequency ratio is derived as: , and the modal frequency ratio is: ;

[0116] (2) The stiffness is defined as K, which is the force required for unit displacement, and is related to the material elastic modulus E and the geometric size. The modal stiffness ratio is: For the beam structure inside the bridge, the bending stiffness is , wherein the moment of inertia is , so ; if the materials are the same , then , and the scale relationship of the stiffness matrix is determined by geometric similarity, and the overall stiffness scale ratio is λ L .

[0117] (3) The mass is defined as M = ρ·V, wherein the volume V ∝ L 3 , and if the material densities are the same (ρ p = ρ m, Then the mass scale ratio is equal to the modal mass ratio: The inertia force: The acceleration of the scaled model needs to be scaled to maintain dynamic similarity.

[0118] In an optional embodiment of the present application, the multi-factor coupling similarity criterion can also include boundary condition similarity, which includes consistency of external excitation on the structure surface, consistency of load action sequence, consistency of constraint conditions, and consistency of initial conditions.

[0119] In this embodiment, when designing the scaled model, boundary condition similarity should also be followed to ensure that the behavior of the scaled model is equivalent to that of the prototype structure;

[0120] Here, the consistency of external excitation is the core to ensure the consistency of the dynamic response of the scaled model and the prototype structure. Preferably, the high-altitude low-pressure wind field can be simulated by a virtual boundary medium technology, combined with the dynamic excitation effect of freeze-thaw cycles, directly acting on the boundary layer of the scaled model (also the boundary layer of the prototype structure of the bridge deck slab, such as the bearing area of the bridge deck slab), to reproduce the wind-induced vibration and frost heaving effect of the prototype structure surface in the real environment. The scaled adjustment of the external excitation parameters (amplitude, frequency) can be linked through the optimization of the boundary contact stiffness to avoid stress concentration or local damage accumulation deviation caused by excitation distortion.

[0121] The consistency of the load action sequence directly affects the fatigue damage evolution of the boundary area. During the scaled model experiment, the loading time sequence of the prototype structure fatigue load spectrum is strictly followed, and the two-way verification of multi-stage loading experiment and numerical simulation is carried out to ensure that the crack propagation path of the boundary layer (such as the composite interface) of the scaled model is consistent with that of the prototype structure.

[0122] The consistency of the constraint conditions requires that the scaled model and the prototype structure be strictly consistent in terms of constraint types (such as fixed hinged, sliding support), contact stiffness (interface bonding force), and load action sequence (fatigue load spectrum), to avoid stress distribution distortion caused by boundary constraint differences.

[0123] The consistency of the initial conditions requires that the scaled model and the prototype be strictly consistent in terms of initial damage state (such as micro-crack distribution, residual stress field) and manufacturing process parameters, to avoid fatigue crack propagation and life prediction deviation caused by initial defect differences.

[0124] In an optional embodiment of the present application, it can also include:

[0125] ​Step 21, based on the preset scaling strategy, the dynamic stress similarity ratio model, and the cross-sectional size and shape of the composite deck structure in the bridge deck prototype structure, the composite deck structure in the bridge deck prototype structure is scaled down; the preset scaling strategy includes a stepped thickness reduction strategy and a nano-coating compensation strategy.

[0126] In this embodiment, particular attention is paid to the composite bridge deck prototype structure in the highland environment (such as the composite bridge deck prototype structure can be composed of 316L stainless steel and Q420qNH weathering steel), and when designing the scaled structure corresponding to the composite bridge deck prototype structure, the scaling of the composite layer of the composite bridge deck prototype structure needs to consider the corrosion resistance (stainless steel layer) and fatigue performance (weathering steel layer). Taking the thickness of the stainless steel layer in the composite bridge deck prototype structure as 3mm and the thickness of the weathering steel layer as 16mm as an example, the above process is described:

[0127] The main design logic is as follows:

[0128] Functional layering principle: since the core function of the stainless steel layer (3mm) is corrosion prevention, the minimum effective corrosion prevention thickness (≥1mm) needs to be ensured after scaling down to avoid corrosion prevention failure due to excessive thinning; the core function of the weathering steel layer (16mm) is load bearing and fatigue resistance, and the scaled-down structure needs to meet the dynamic similarity (stiffness, mass ratio) while retaining the fatigue crack propagation characteristics.

[0129] Stepped thickness reduction strategy: set the geometric scaling ratio λ L : according to the size requirements of the scaling model (such as λ L =4), the weathering steel thickness is reduced to 16 / λ L =4mm in proportion, and the stainless steel layer is reduced in steps (as shown in Figure 2 ), while considering the optimization of the step boundary, the stress gradient of the bridge deck is determined by the finite element analysis model to avoid local stress concentration caused by sudden thickness changes;

[0130] For the high stress area of the stainless steel layer (such as the midspan of the bridge deck): the thickness is kept at 1mm (minimum functional thickness) to prioritize the minimum functional corrosion prevention thickness and ensure the corrosion resistance of the structure at the most vulnerable part;

[0131] For the low stress area of the stainless steel layer (such as the end): reduce to 0.75mm ( λ L =4) in proportion, supplemented by nano-coating to compensate for the corrosion resistance, to make up for the decrease in corrosion resistance caused by the reduction in thickness, as shown in Figure 3 .

[0132] For the anti-corrosion nano coating, a biomimetic nano composite coating (such as ZnO / TiO2 nanoparticles + epoxy resin) is used to enhance the thin layer anti-corrosion ability, and the corrosion rate can be reduced by an order of magnitude, which can well compensate for the decay of the anti-corrosion performance of the stainless steel layer when the thickness changes.

[0133] Considering the fatigue equivalent of weathering steel, the pre-strain treatment is used to simulate the fatigue damage of the prototype structure, and the crack propagation rate of the scaled model of weathering steel needs to satisfy the relationship =λ L 2 Through the design of the stepwise thickness reduction strategy and the nano coating compensation strategy, the problem of synergistic optimization of corrosion resistance and fatigue performance in the scaled model of the highland composite bridge deck is solved. It should be understood that the above preset scaling strategy can not be limited to bridge decks, and can be applied to low-temperature simulation scenarios of composite panels and related corrosion-resistant steel structures, such as composite panel materials, steel columns, steel beams, etc.

[0134] In an optional embodiment of the present application, the above step 14 can include:

[0135] Step 141, based on the preset simulation analysis software, establish the finite element model of the bridge deck prototype structure and the initial scaled model, and integrate the multi-physical field coupling analysis of the preset simulation temperature gradient, the preset simulation ultraviolet intensity, the preset simulation oxygen content and the preset simulation dynamic load, and determine the simulation stress distribution deviation of the bridge deck prototype structure and the initial scaled model by comparing the stress distribution cloud diagram of the corresponding finite element model of the bridge deck prototype structure and the corresponding finite element model of the initial scaled model.

[0136] Step 142, construct a local full-scale model piece of the bridge deck prototype structure and a scaled model test piece corresponding to the local full-scale model piece, and carry out fatigue loading experiments on the local full-scale model piece and the scaled model test piece in a low-temperature and low-pressure corrosion environment simulation cabin, and monitor the fatigue crack propagation length of the local full-scale model piece and the fatigue crack propagation length of the scaled model test piece through a preset strain array in the simulation cabin, to determine the simulation stress deviation of the local full-scale model piece and the scaled model test piece.

[0137] When performing the preset numerical simulation strategy for simulation experiments, the finite element model of the prototype structure and the scaled model can be established through ABAQUS simulation software; taking the geometric similarity ratio λ L =4 as an example, the numerical simulation integrates the plateau day and night temperature difference ΔT=60°C, the ultraviolet accelerated corrosion model (IUV=200W / m²), and the dynamic load spectrum scaled by λ P =λ L ² scaling amplitude.

[0138] For example, Figure 4 and Figure 5The figures show the stress distribution cloud maps of the full-scale and scaled-down models of the prototype structure under vehicle load simulation. As can be seen from the figures, the maximum stress values ​​and local stress distributions of the two models show a high degree of consistency. Figure 6 and Figure 7 The figures show the stress analysis results of the full-scale and scaled-down models of the prototype structure at their respective node positions (key parts of the weld toe on the top plate of the node) under vehicle load. As can be seen from the figures, stress is concentrated at the node positions. However, the full-scale and scaled-down models of the prototype structure have a high degree of consistency in stress distribution, and the difference between their maximum stresses does not exceed 15%. In engineering, the consistency between the two can be considered to be good.

[0139] Combining the stress distribution cloud map and the stress analysis diagram of the key parts of the weld toe on the top plate of the node, it is confirmed that the stress distribution consistency between the scaled model and the full-scale model corresponding to the prototype structure reaches more than 90%. At this point, the scaled model can be confirmed as having passed verification. Otherwise, based on the simulation data, the environmental coupling factor f(ΔT, I) is inverted. UV W O2 Furthermore, the dynamic stress similarity model was optimized. Through theoretical analysis and simulation, the consistency between the mechanical behavior of the scaled model and the prototype structure in the extreme environment of the plateau can be preliminarily confirmed, providing guidance and parameter optimization basis for subsequent physical experiments.

[0140] In the actual physical simulation experiment, a full-scale model of the bridge deck prototype structure (1:1 composite interface) and a corresponding scaled-down model specimen (such as a scaled-down CT specimen) were first constructed. Fatigue loading experiments were carried out in a low-temperature, low-pressure corrosion environment simulation chamber (-40°C, oxygen concentration 15%) and at room temperature (20°C). The stability of the full-scale model and the corresponding scaled-down model specimen was monitored using strain gauge arrays and digital image correlation (DIC) technology. The deviation between the dynamic response of the scaled-down model specimen and the theoretical prediction was analyzed. Simultaneously, data on the evolution of crack propagation length on the full-scale model and the corresponding scaled-down model specimen with the number of cycles were collected, and the results were obtained as follows: Figure 8 The diagram shows the relationships between various parameters, where SW-1 represents the curve corresponding to a full-scale model specimen at low temperature, SW-2 represents the curve corresponding to a scaled-down model specimen at low temperature, DW-1 represents the curve corresponding to a full-scale model specimen at room temperature (20°C), and DW-2 represents the curve corresponding to a scaled-down model specimen at room temperature (20°C). Furthermore, based on fatigue data (crack propagation length) at different temperatures, the correlation between crack propagation length and stress intensity factor ΔK1 at different temperatures can be inverted (e.g.,...). Figure 9It can be seen from the figure that the low-temperature and low-pressure corrosive environment greatly improves the fatigue performance of the structure. By substituting the fatigue properties of the material into the finite element model based on the fatigue data at different temperatures obtained through actual physical experiments, the fatigue condition of the overall model can be simulated and calculated more accurately, and the accuracy of the numerical simulation results can also be verified. By obtaining the material performance degradation and fatigue crack propagation data in the real environment, and correcting and improving the environmental coupling factor and the corresponding coefficient of the dynamic stress similarity ratio model of the corresponding scale model, the precise matching of the theory and the actual working condition is ensured.

[0141] As Figure 10 shown, the design method of the bridge deck panel scale model in the plateau environment provided by the above-embodiment of the present application has the following specific process in the specific implementation:

[0142] First, the plateau environment parameters are coupled with the geometric and dynamic similarity criteria, and the design is performed through the composite layer dynamic scaling strategy, dynamic analysis, and comprehensive dynamic stress similarity ratio model. Among them, the environmental parameter coupling needs to consider the freeze-thaw degradation and the oxidation rate of the material layer attribute and perform environmental parameter dynamic correction, then consider the temperature, ultraviolet, oxygen concentration and other environmental coupling parameters, and finally perform similarity ratio correction to obtain the dynamic stress similarity ratio model.

[0143] Further, the finite element scale model is established based on the dynamic stress similarity ratio model, and the related coefficients of the bridge deck panel prototype structure and the initial scale model are verified by numerical simulation. At the same time, through the low-temperature fatigue tensile experiment of the local full-scale model of the bridge deck panel and the corresponding scale model, the low-temperature fatigue properties of the material and the fatigue performance difference of the scale deck panel are determined.

[0144] Further, the key parameters are verified based on numerical simulation and local experiment, if the deviation is out of limit, the similarity ratio coefficient is corrected and the dynamic stress similarity ratio model is optimized circularly, and the target scale model is designed based on the corrected dynamic stress similarity ratio model, otherwise the scale model experiment is started.

[0145] As Figure 11 to Figure 13As shown, the embodiment of the present application also provides an experimental system of a bridge deck panel scale model in a plateau environment, the bridge deck panel scale model being designed by the above-mentioned design method of a bridge deck panel scale model in a plateau environment, the experimental system comprising a simulation cabin and a central control module. The simulation cabin comprises a foldable experimental box body 1 and a sensor assembly, and the sensor assembly is arranged in the foldable experimental box body 1. The simulation cabin is used to provide a place for fatigue loading experiment and simulate a plateau environment for the scale model according to the experimental conditions required by the fatigue loading experiment. The sensor assembly is used to monitor real-time state data in the simulation cabin in real time. The central control module is in communication connection with the simulation cabin and an upper computer. The central control module stores a multi-altitude environment parameter library and a dynamic parameter conversion model. The dynamic parameter conversion model determines a target altitude and a target working condition corresponding to the target altitude in the multi-altitude environment parameter library according to the fatigue loading experiment requirement, and dynamically scales the target working condition to obtain the experimental condition required by the fatigue loading experiment.

[0146] Preferably, the foldable experimental box body 1 is internally provided with platform modules for placing scale model test pieces. An RFID chip (storing platform module ID, functional parameters and historical data) can be embedded in each platform module. The central control module can automatically identify the combination state of the platform modules through near field communication and call pre-stored assembly logic (such as a loading unit preferentially docking a cross-region).

[0147] The foldable experimental box body 1 is externally provided with a plurality of external devices such as a liquid nitrogen storage device 2, an oxygen generator 3, a turbulent flow generator 4 and a loading device 5. The plurality of external devices are detachably connected to the outside of the foldable experimental box body 1 through an external device support framework 6. Here, the specific structure of the external device support framework 6 is not limited, and it is only required to be matched with the structural design of the foldable experimental box body 1 and to be able to bear the weight and size of different devices.

[0148] The liquid nitrogen storage 2, the oxygen generator 3, the turbulent flow generator 4 and the loading device 5 are in communication with the foldable experimental box 1. Among them, the liquid nitrogen storage 2 delivers liquid nitrogen into the foldable experimental box 1 to ensure the stability of the low-temperature environment during the experiment, the oxygen generator 3 delivers the prepared oxygen into the foldable experimental box 1 to simulate the high-oxygen or low-oxygen conditions in the plateau environment, the turbulent flow generator 4 generates turbulent flow to simulate the air flow disturbance in the natural environment, thereby reducing the possibility of boundary layer separation, thereby reducing the resistance and improving the accuracy of the experiment, and the loading device 5 can apply load to the model structure test piece outside the foldable experimental box 1; since the space occupied by the larger model structure test piece inside can be larger, applying load outside can be more in line with the assembly convenience, and at the same time, a load with larger tonnage and excitation effect can be applied. Preferably, the liquid nitrogen storage 2, the oxygen generator 3, the turbulent flow generator 4 and the loading device 5 can be respectively connected in communication with the central control module through the control units arranged respectively, during the experiment, the environment and state parameters in the box are monitored in real time through the sensor assembly arranged in the box, and are fed back to the central control module, so as to adjust the strength and frequency of the movement of each device in time, thereby ensuring the accuracy of the experiment simulation.

[0149] Here, the foldable experimental box 1 adopts a pull-out frame (the unfolded size is 6m x 3m x 2.5m, and the volume is reduced to 1 / 3 after folding), which can realize rapid deployment. The pull-out frame includes a plurality of foldable telescopic parts (to realize rapid assembly). In order to ensure the air tightness of the foldable experimental box 1, after the connection and locking of the plurality of foldable telescopic parts, a sealing and pressurizing device is arranged inside the connecting sealing strip of the adjacent two foldable telescopic parts, the air tightness is stabilized by providing pressure inside, the foldable experimental box 1 is unfolded, and the air tightness connecting strip is arranged in each step telescopic part, so as to ensure that the device is developed, and the whole device is isolated from the external gas. A foldable rubber skin 7 is arranged on the outer layer of the unfolded box, the rubber skin 7 has strong activity and waterproof sealing capacity, which can prevent the box structure from being exposed outside, and also can isolate the exchange of gas between the inner and outer layers.

[0150] Here, the number of foldable telescopic parts can be set according to actual needs. In a realizable example, as shown in FIG. 2, the foldable experimental box 1 includes a plurality of foldable telescopic parts, and the number of foldable telescopic parts is 4. Figure 13As shown, two folding telescopic parts are provided, namely, the first telescopic part 11 and the second telescopic part 12, and the box end 16 and the box tail 17 of the folding experimental box body 1 are respectively connected with the first telescopic part 11 and the second telescopic part 12 in a telescopic manner, wherein the connecting end 13 of the folding experimental box body 1 is arranged between the first telescopic part 11 and the second telescopic part 12 and is tightly connected with the first telescopic part 11 and the second telescopic part 12 respectively. A sliding mechanism is arranged in the first telescopic part 11 and the second telescopic part 12, and after telescopic expansion, the box can be pressurized by a sealing pressurizing device (such as an electromagnetic connecting part) to pressurize the air-tight connecting strip at the connection, and at the same time, the sliding mechanism is compressed, so as to realize the effect of rapid assembly of air tightness.

[0151] Preferably, an observation window 14 and a loading slot 15 are arranged on the box, and the observation window 14 can be arranged on the second telescopic part 12. The observation window 14 can be used to detect the docking deviation of the platform module in real time through a visual positioning system (integrated in a DIC camera), so as to timely drive the internal loading position through a servo motor. The loading device 5 applies a load to the model structure specimen through the loading slot 15; preferably, a flexible sealing layer is arranged at the lower part of the loading slot 15 to prevent gas leakage during loading.

[0152] Here, the multi-altitude environment parameter library covers key parameter databases such as extreme temperature (3000m, 4500m, 5500m, etc.), low air pressure, and high-intensity ultraviolet radiation at different altitude gradients, and supports continuous plateau environment simulation from temperate plains to alpine mountains; here, an arbitrary altitude target curve can be dynamically generated through an interpolation algorithm, which provides a precise benchmark for fatigue loading experiments of scale models. During the fatigue loading experiment, the dynamic parameter conversion model extracts corresponding parameters from the multi-altitude environment parameter library according to the experimental requirements, so as to ensure that the environmental parameters of the experiment simulation are consistent with the real environment of the plateau.

[0153] The dynamic parameter conversion model is a bridge that combines the environmental parameters in the multi-altitude environment parameter library with the geometric, material, and mechanical characteristics of the scale model, and is used to determine the specific values of the environmental parameters in the experiment. Here, the dynamic parameter conversion model can be based on the analysis of the actual parameter characteristics of the prototype environment according to the geographical location, and the physical quantity dynamic scaling relationship is constructed by combining the scale ratio, so as to realize the cross-scale equivalent mapping of complex environmental parameters such as temperature and humidity, and ensure the mechanical and chemical behavior consistency of the scale model and the prototype structure environment.

[0154] During the experiment, considering the self-regulation and rapid assembly characteristics of the experimental system, the structure of the experimental box in the experimental system is designed, the folding module is designed, the transportation volume is reduced by 1 / 3, and the external equipment support skeleton 6 is matched. The large external equipment can be detachably installed outside the folding experimental box 1. The folding experimental box 1 can be quickly assembled by considering the sealing performance and the activity performance. After the tail of the box is fixed, the end of the box is stretched, the first and second stretching parts 11 and 12 of the folding experimental box 1 are pulled out and unfolded, and after being completely unfolded, the built-in magnetic attraction device starts to apply pressure to the sealing strip. In order to ensure the sealing performance of the connecting part, the folding rubber skin 7 is arranged outside the box, which can well wrap the outside of the structure and isolate the external environment.

[0155] The specific process of the fatigue loading experiment of the experimental system designed above is as follows:

[0156] Step 31, according to the experimental requirements, the target altitude and experimental conditions are determined.

[0157] Step 32, the dynamic parameter conversion model extracts the environmental parameters such as temperature, air pressure and oxygen concentration at this altitude from the multi-altitude environmental parameter library.

[0158] Step 33, the dynamic parameter conversion model combines the geometric, material and mechanical characteristics of the scale model to dynamically scale the extracted environmental parameters to obtain the required environmental parameters for the experiment.

[0159] Step 34, the multifunctional environmental cabin adjusts the temperature, air pressure, oxygen concentration and other environmental parameters in the cabin according to the environmental parameters sent by the dynamic parameter conversion model, and provides the corresponding experimental environment for the scale model.

[0160] Step 35, during the experiment, the multifunctional environmental cabin monitors the environmental parameters in the cabin in real time and feeds back the data to the dynamic parameter conversion model.

[0161] Step 36, the dynamic parameter conversion model judges whether the environmental parameters need to be adjusted according to the real-time feedback data, and sends the adjusted parameters to the multifunctional environmental cabin to realize closed-loop control of the environmental parameters.

[0162] Through the modular design and intelligent control of the experimental system, the experimental efficiency and convenience can be significantly improved, and high-reliability experimental support is provided for the optimization design of plateau engineering equipment; at the same time, through the joint action of the simulation cabin, the multi-altitude environmental parameter library and the dynamic parameter conversion model in the experimental system, accurate and dynamic plateau environment simulation is provided for the scale model, ensuring the accuracy and reliability of the experiment.

[0163] Figure 14A block diagram of a computing device that is capable of implementing various embodiments of the present disclosure is shown, which can be used to perform Figure 1 or Figure 10 at least one operation. As shown in Figure 14 , the electronic device 400 includes a computing unit 401 that can perform various appropriate actions and processes in accordance with a computer program stored in a read-only memory (ROM) 402 or a computer program loaded into a random access memory (RAM) 403 from a storage unit 408. In the RAM 403, various programs and data required for device operations can also be stored. The computing unit 401, the ROM 402, and the RAM 403 are connected to each other through a bus 404. An input / output (I / O) interface 405 is also connected to the bus 404.

[0164] Various components in the electronic device are connected to the I / O interface 405, including: an input unit 406, such as a keyboard, a mouse, etc.; an output unit 407, such as various types of displays, a speaker, etc.; a storage unit 408, such as a magnetic disk, an optical disk, etc.; and a communication unit 409, such as a network card, a modem, a wireless communication transceiver, etc. The communication unit 409 allows the device to exchange information / data with other devices through a computer network, such as the Internet, and / or various telecommunication networks.

[0165] The computing unit 401 can be various general-purpose and / or special-purpose processing components with processing and computing capabilities. Some examples of the computing unit 401 include, but are not limited to, a central processing unit (CPU), a graphics processing unit (GPU), various specialized artificial intelligence (AI) computing chips, various computing units running machine learning model algorithms, a digital signal processor (DSP), and any appropriate processor, controller, microcontroller, etc. The computing unit 401 performs various methods and processes described above, such as the methods of various embodiments of the present disclosure. For example, in some embodiments, the methods of various embodiments of the present disclosure can be implemented as a computer software program that is tangibly embodied in a machine-readable medium, such as the storage unit 408. In some embodiments, part or all of the computer program can be loaded and / or installed onto the device via the ROM 402 and / or the communication unit 409. When the computer program is loaded into the RAM 403 and executed by the computing unit 401, one or more steps of the methods of various embodiments of the present disclosure described above can be performed. Alternatively, in other embodiments, the computing unit 401 can be configured to perform the methods of various embodiments of the present disclosure by any other appropriate means, such as by means of firmware.

[0166] Various embodiments of the systems and techniques described above herein 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), payload-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.

[0167] 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.

[0168] 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.

[0169] To provide for interaction with a user, the systems and techniques described here can be implemented on a computer having a display device (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor) for displaying information to the user and a keyboard and a pointing device (e.g., a mouse or a trackball) by which the user can provide input to the computer. Other kinds of devices can be used to provide for interaction with a user as well; for example, feedback provided to the user can be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user can be received in any form, including acoustic, speech, or tactile input.

[0170] The systems and techniques described here can be implemented in a computing system that includes a back end component (e.g., as a data server), or that includes a middleware component (e.g., an application server), or that includes a front end component (e.g., a user computer having a graphical user interface or a Web browser through which a user can interact with an implementation of the systems and techniques described here), or any combination of such back end, middleware, or front end components. The components of the system can be interconnected by any form or medium of digital data communication (e.g., a communication network). Examples of communication networks include a local area network (LAN), a wide area network (WAN), and the Internet.

[0171] The computer system can include clients and servers. A client and server are generally remote from each other and typically interact through a communication network. The relationship of client and server arises by virtue of computer programs running on the respective computers and having a client-server relationship to each other. A server can be a cloud server, also known as cloud computing server or cloud host, which is a host product in the cloud computing service system, to solve the defects of large management difficulty and weak business scalability in traditional physical host and VPS service ("Virtual Private Server", or simply "VPS"). The server can also be a server of a distributed system, or a server combined with a blockchain.

[0172] It should be understood that various forms of flow shown above can be used, with steps reordered, added, or removed. For example, the steps recited in the present disclosure can be performed in parallel, in series, or in a different order, without limitation herein, as long as the desired results of the technical solutions of the present disclosure can be achieved.

[0173] The above detailed description does not limit the scope of the disclosure. Various modifications, combinations, sub-combinations and alternatives can be made to the detailed description. Any modification, equivalent replacement and improvement etc. made within the spirit and principle of the disclosure shall be included in the scope of the disclosure.

Claims

1. A method for designing a scaled-down model of a bridge deck in a high-altitude environment, characterized in that, include: Based on the principle of similarity, physical parameters affecting the performance of the bridge deck prototype structure, and plateau environmental parameters, a multi-factor coupled similarity criterion is constructed. Based on the multi-factor coupling similarity criterion and the plateau environment parameters, a dynamic stress similarity ratio model is determined between the bridge deck prototype structure and its corresponding scaled-down model under material performance degradation conditions. The dynamic stress similarity ratio model is an integrated model of freeze-thaw damage and thermo-optical-chemical coupling effects under extreme plateau conditions to ensure the equivalence of fatigue performance between the bridge deck prototype structure and the scaled-down model under extreme plateau conditions. The degradation of the material performance of the bridge deck prototype structure is affected by the plateau environment parameters and is represented by a preset material performance degradation model. Based on the dynamic stress similarity ratio model and the cross-sectional shape and size of the bridge deck prototype structure, the bridge deck prototype structure is scaled down to obtain an initial scaled model corresponding to the bridge deck prototype structure. The initial scaled model is simulated and verified based on a preset numerical simulation strategy and a preset plateau environment simulation strategy. The parameters in the dynamic stress similarity ratio model are then optimized based on the simulation results or the simulation verification results in order to design the target scaled model.

2. The method for designing a scaled-down model of a bridge deck in a plateau environment according to claim 1, characterized in that, Based on the principle of similarity and the physical parameters affecting the performance of the bridge deck prototype structure, a multi-factor coupled similarity criterion is constructed, including: The physical parameters and the plateau environment parameters are homogenized in dimension based on the pre-set Buckingham π theorem to obtain the corresponding dimensionless π number group. Based on the dimensionless π number group, multiple parameter similarity ratios are determined between the prototype structure of the bridge deck and its corresponding scaled-down model. These multiple parameter similarity ratios include geometric similarity ratio, stress similarity ratio, load similarity ratio, temperature gradient similarity ratio, elastic modulus similarity ratio, and freeze-thaw cycle similarity ratio. Furthermore, these multiple parameter similarity ratios constitute the multi-factor coupled similarity criterion.

3. The method for designing a scaled-down model of a bridge deck in a plateau environment according to claim 2, characterized in that, Based on the multi-factor coupling similarity criterion and the plateau environment parameters, the dynamic stress similarity ratio model of the bridge deck prototype structure and its corresponding scaled-down model under material performance degradation is determined. The dynamic stress similarity ratio model includes: Based on the elastic modulus similarity ratio and the geometric similarity ratio, a mechanical similarity factor is determined, which reflects the stress response relationship between the scaled-down model and the bridge deck prototype structure under static load. Based on the geometric similarity ratio and the preset material performance degradation model, a material performance degradation correction factor is determined. The material performance degradation correction factor represents unifying the rate of decay of material strength or durability with time and environmental load to the same time scale, so as to ensure that the scaled model and the bridge deck prototype structure have similar dynamic performance degradation. Based on the temperature gradient similarity ratio and the preset attenuation factor, an environmental coupling correction factor is determined. The environmental coupling correction factor represents the synergistic accelerating effect of temperature change, ultraviolet intensity and oxygen concentration in plateau environmental parameters on the attenuation of material performance. The dynamic stress similarity ratio model is determined based on the stress similarity ratio, the mechanical similarity factor, the material property degradation correction factor, and the environmental coupling correction factor.

4. The method for designing a scaled-down model of a bridge deck in a plateau environment according to claim 3, characterized in that, Based on the geometric similarity ratio and the preset material performance degradation model, the material performance degradation correction factor is determined, including: In the scaled-down model, the time parameters and number of freeze-thaw cycles of the preset material property degradation model are scaled down according to the geometric similarity ratio; Based on the results of the scaled-down adjustment, the material performance degradation term in the preset material performance degradation model is corrected to obtain the material performance degradation correction factor.

5. The method for designing a scaled-down model of a bridge deck in a plateau environment according to claim 3, characterized in that, The preset material performance degradation model is expressed as follows: ； in, This indicates the time t and the number of freeze-thaw cycles. The material property degradation coefficient under action; Indicates the initial performance coefficient of the material; Indicates the degradation of material properties; Indicates the oxidation rate; The constant represents the freeze-thaw damage rate; time t is used to characterize the aging degradation of material properties.

6. The method for designing a scaled-down model of a bridge deck in a plateau environment according to claim 3, characterized in that, The dynamic stress similarity ratio model is expressed as follows: ； in, This represents the dynamic stress similarity ratio model; This indicates the similarity ratio of the elastic modulus; This represents the geometric similarity ratio; This represents the mechanical similarity factor; Indicates the oxidation rate; This represents the freeze-thaw damage rate constant; The number of freeze-thaw cycles is represented by t; t represents time, used to characterize the aging degradation of material properties. The material's performance degradation correction factor is represented by ΔT; ΔT represents the temperature gradient of the high-altitude environment; I UV Indicates the intensity of ultraviolet radiation in a high-altitude environment; Indicates the oxygen concentration in a high-altitude environment; This represents the environmental coupling correction factor.

7. The method for designing a scaled-down model of a bridge deck in a plateau environment according to claim 1, characterized in that, The multi-factor coupling similarity criterion also includes boundary condition similarity, which includes the consistency of external excitations borne by the structural surface, the consistency of load application sequence, the consistency of constraint conditions, and the consistency of initial conditions.

8. The method for designing a scaled-down model of a bridge deck in a plateau environment according to claim 1, characterized in that, Also includes: Based on the preset scaling strategy, the dynamic stress similarity ratio model, and the cross-sectional dimensions and shape of the composite layer bridge deck structure in the bridge deck prototype structure, the composite layer bridge deck structure in the bridge deck prototype structure is scaled down; the preset scaling strategy includes a stepped thickness reduction strategy and a nano-coating compensation strategy.

9. The method for designing a scaled-down model of a bridge deck in a plateau environment according to claim 1, characterized in that, The initial scaled model was simulated and verified based on a preset numerical simulation strategy and a preset plateau environment simulation strategy, including: Finite element models of the bridge deck prototype structure and the initial scaled model are established based on preset simulation analysis software. Multi-physics field coupling analysis of preset simulation temperature gradient, preset simulation ultraviolet intensity, preset simulation oxygen content and preset simulation dynamic load is integrated. By comparing the stress distribution cloud maps of the finite element models corresponding to the bridge deck prototype structure and the initial scaled model, the simulation stress distribution deviation between the bridge deck prototype structure and the initial scaled model is determined. A partial full-scale model of the bridge deck prototype structure and a corresponding scaled-down model specimen were constructed. Fatigue loading experiments were conducted on the partial full-scale model and the scaled-down model specimen in a low-temperature, low-pressure corrosion environment simulation chamber. The fatigue crack propagation length of the partial full-scale model and the scaled-down model specimen were monitored by a preset strain gauge array in the simulation chamber to determine the simulated stress deviation between the partial full-scale model and the scaled-down model specimen.

10. An experimental system for a scaled-down model of a bridge deck in a high-altitude environment, characterized in that, The scaled-down bridge deck model is designed using the scaled-down bridge deck model design method for high-altitude environments as described in any one of claims 1-9. The experimental system includes: The simulation chamber includes a foldable experimental enclosure and sensor components, the sensor components being housed within the foldable experimental enclosure. The simulation chamber provides a testing environment and simulates a high-altitude environment for the scaled-down model, based on the experimental conditions required for fatigue loading experiments. The sensor components are used to monitor real-time status data within the simulation chamber. The central control module is communicatively connected to the simulation chamber and the host computer. The central control module stores a multi-altitude environmental parameter library and a dynamic parameter conversion model. The dynamic parameter conversion model determines the target altitude and the target working condition corresponding to the target altitude from the multi-altitude environmental parameter library according to the fatigue loading test requirements, and dynamically scales the target working condition to obtain the experimental working condition required for the fatigue loading test.

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