Post-fire highway tunnel damage structure 3D printing model

Abstract

The utility model discloses a post-fire highway tunnel damage structure 3D printing model which is of a cylindrical structure, the cross section of the cylindrical structure comprises an outer wall and an inner wall, the outer wall comprises an upper half part of a semicircular structure, two outer side edges and an outer bottom edge, the two ends of the semicircular structure are connected to the upper ends of the two outer side edges, and the inner wall is connected to the outer bottom edge. The two ends of the outer bottom edge are connected to the lower ends of the two outer side edges, the inner wall comprises a to-be-damaged edge located on the upper half portion, two inner side edges and an inner bottom edge, the two ends of the to-be-damaged edge are connected to the upper ends of the two inner side edges, and the two ends of the inner bottom edge are connected to the lower ends of the two inner side edges. The model truly reproduces the damage condition of the post-disaster tunnel through a series of operations and a 3D printing technology, and provides reliable support for subsequent structural analysis and repair schemes.

Description

Technical Field

[0001] The utility model relates to the technical field of safety of highway tunnel structures after disasters, and more specifically, to a 3D printed model of a damaged structure of a highway tunnel after a fire. Background Art

[0002] Tunnel engineering is a critical control project on highways. The overall structural performance and safety of tunnels after fires are crucial for tunnel restoration efforts. Therefore, it is crucial to develop more accurate and efficient models for tunnel damage after fires and to use these more accurate and realistic models in model testing to accurately analyze the extent of damage to tunnel structures after disasters.

[0003] As tunnel construction continues to expand, the risk of tunnel fire accidents has also increased significantly. Since the 21st century, my country's tunnels have experienced an average of one fire every 30 kilometers per year, a remarkably high frequency. Tunnel fires not only cause serious damage to vehicles, personnel, and electromechanical equipment within, but also significantly damage the tunnel lining, significantly reducing its bearing capacity and safety performance. The high temperatures of fires can cause segmental concrete to crack and spall, exposing rebar and significantly compromising the integrity and safety of highway tunnel linings, significantly reducing the structure's bearing capacity.

[0004] Tunnel fires severely impact the safety and serviceability of structures, and repairs are costly and time-consuming. However, in practical engineering applications, research on post-fire damage in shield tunnels is relatively limited. Currently, engineers rely on advanced detection technologies and numerical simulation tools to assess the impact of fire on tunnels. However, existing tools and technologies have limitations in simulating post-fire tunnel damage and cannot fully and accurately reflect the actual situation. Developing finite element numerical models and damage model test models of damaged tunnels is fraught with difficulties. It is difficult to accurately account for the strength, stability, and durability of the lining structure and reflect the impact of fire on tunnel structural stiffness. Fire has a serious impact on tunnel damage, making research on post-fire tunnel structures crucial. Traditional test model construction methods are inefficient and lack accuracy. Existing research has significant shortcomings, particularly regarding the deformation characteristics and stiffness change functions of post-disaster highway tunnels. Existing models fail to incorporate on-site post-disaster tunnel data, making it difficult to provide strong theoretical support for post-disaster tunnel mechanical performance assessment and repair efforts.

[0005] To address these issues, this utility model proposes a 3D-printed model of a damaged highway tunnel structure after a fire. This model utilizes knowledge graph technology to obtain the deformation and local elastic modulus parameters of the tunnel lining after a disaster. Combined with on-site monitoring data, the stiffness of the damaged tunnel structure is quantified. A refined model is then constructed using 3D printing technology. Variations in the model thickness are used to simulate changes in tunnel stiffness, providing practical guidance for model testing of tunnel structures after a fire. Utility Model Content

[0006] This utility model aims to overcome at least one drawback of the existing technology by providing a 3D-printed model of damaged structures in highway tunnels after fire. This model addresses the existing issues of the inability to quantify the strength of the lining structure and the inability of tests to reflect the actual structure after a highway tunnel fire. It also overcomes the shortcomings of traditional test model production methods, thereby improving the efficiency and accuracy of post-fire tunnel structure model testing.

[0007] The technical solution adopted by the present invention is a 3D printed model of a damaged structure of a highway tunnel after a fire, which is a cylindrical structure. The cross-section of the cylindrical structure includes an outer wall and an inner wall. The outer wall includes the upper half of a semicircular structure, two outer sides and an outer bottom side. The two ends of the semicircular structure are respectively connected to the upper ends of the two outer sides, and the two ends of the outer bottom side are respectively connected to the lower ends of the two outer sides. The inner wall includes a simulated damaged side located in the upper half, two inner sides and an inner bottom side. The two ends of the simulated damaged side are respectively connected to the upper ends of the two inner sides, and the two ends of the inner bottom side are respectively connected to the lower ends of the two inner sides.

[0008] The damage of a highway tunnel after a fire in reality is simulated by using the simulated damaged edge, and subsequent tests are conducted on the 3D printed model to calculate whether the highway tunnel needs to be reinforced and repaired after the fire.

[0009] In order to reduce the computational complexity of damage simulation, multiple fan-shaped depressions are present on the simulated damaged edge. The fan-shaped depressions are distributed at intervals on the left and top of the simulated damaged edge. Using fan-shaped depressions to replace complex damage and restore the real situation as much as possible also reduces the computational complexity. The distribution of fan-shaped depressions is simulated according to the real situation.

[0010] In order to simulate the burning of the inner wall of a highway tunnel during a fire in most real situations, stepped depressions are distributed at both ends of the simulated damaged edge.

[0011] In order to simulate the damage distribution of highway tunnels in real conditions, the fan-shaped depressions of the damage on the 3D printed model are more distributed on the left side than on the right side.

[0012] Since in most real situations a highway tunnel will collapse if the extent of damage exceeds 3 / 4 of the wall thickness, the depth of the fan-shaped depression does not exceed 3 / 4 of the wall thickness of the outer wall and the inner wall.

[0013] Since most highway tunnels in reality are semicircular, the designed damage edge is approximately semicircular.

[0014] In order to simulate the conditions of a highway tunnel in real life and improve the stability of the model, the wall thickness of the simulated damaged edge and the semicircular structure is smaller than that of the inner and outer walls.

[0015] The portion where the outer bottom edge is connected to the two outer sides is arc-shaped, and the portion where the inner bottom edge is connected to the two inner sides is arc-shaped.

[0016] In order to further reduce the amount of calculation, the simulation process of the non-damaged surface is simplified as much as possible, and the distance between the inner bottom edge and the outer bottom edge is equal to the distance between the inner side edge and the outer side edge.

[0017] In reality, the damage caused by fire to highway tunnels is mostly localized damage, and the degree of damage is far less than the localized damage. Therefore, the depth of the designed depression is about 1 / 2 of the width.

[0018] Compared with the prior art, the present invention has the following advantages and technical achievements:

[0019] This technological innovation significantly improves the efficiency and accuracy of post-disaster tunnel structure assessment and repair through a series of key steps. First, by leveraging knowledge graphs and field data analysis, damage information from tunnel structures can be systematically organized and extracted, providing foundational data for subsequent work. Based on damage reports and similarity criteria, a 3D-printed damaged structure model with varying stiffness was developed, effectively simulating actual damage conditions.

[0020] Finite Element Analysis (FEA) modeling and analysis verified and optimized the accuracy of the 3D printed model. Model parameters were adjusted through multiple iterations to ensure it matched the actual tunnel damage. Leveraging advanced 3D printing technology, an optimized complex structural model was produced, accurately reproducing the details and complexity of the tunnel damage.

[0021] Subsequently, the 3D printed model was subjected to mechanical property testing and calibration to verify its mechanical response under different loads, ensuring that the model met expectations in terms of mechanical properties and geometric accuracy. Ultimately, the optimized 3D printed model provided guidance for post-disaster tunnel structure damage model testing, providing quantifiable guidance for modeling damaged structures. BRIEF DESCRIPTION OF THE DRAWINGS

[0022] The accompanying drawings of this utility model are for illustrative purposes only and are not to be construed as limiting the present invention. To more clearly illustrate the technical solutions of the embodiments of the present utility model, the following briefly describes the drawings required for describing the embodiments. Obviously, the drawings described below represent only some embodiments of the present utility model. Persons skilled in the art can, without inventive effort, derive other drawings from these drawings.

[0023] Figure 1 This is a structural diagram of a 3D printed model of a damaged structure in a highway tunnel after a fire in the utility model.

[0024] Figure 2 This is the initial structural diagram of a 3D printed model of a damaged structure in a highway tunnel after a fire in this utility model.

[0025] Figure 3 This is an analytical structural diagram of a 3D printed model of a damaged structure in a highway tunnel after a fire in this utility model.

[0026] Figure 4 The present invention provides a flow chart for producing a 3D printed model of a damaged structure in a highway tunnel after a fire.

[0027] Figure 5 This is a schematic diagram of a damage report generated based on the index map and field data in the present invention.

[0028] Figure 6 Schematic diagram of the 3D printed model based on damage reports and similarity criteria.

[0029] Figure 7 This is a schematic diagram of the process of establishing a 3D printing model of tunnel structure damage in the present invention.

[0030] Figure 8 Schematic diagram of iterative optimization of the 3D printing model in FEA finite element simulation in this utility model. DETAILED DESCRIPTION

[0031] The following will be combined with the accompanying drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the embodiments described are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative efforts are within the scope of protection of the present invention.

[0032] like Figure 1As shown, the 3D printed model of the damaged structure of a highway tunnel after a fire provided by the present invention is a cylindrical structure, and its cross section consists of an outer wall and an inner wall. The upper half of the outer wall is a semicircular structure, and the lower half consists of two outer sides and an outer bottom side. The two ends of the semicircular structure are respectively connected to the upper ends of the two outer sides, and the two ends of the outer bottom side are respectively connected to the lower ends of the two outer sides, and the connected edges are arc-shaped. The upper half of the inner wall is a simulated damaged edge that is approximately semicircular, and the lower half consists of two inner sides and an inner bottom side. The two ends of the simulated damaged edge are connected to the upper ends of the two inner sides, and the two ends of the inner bottom side are connected to the lower end of the inner side, and the connected edges are arc-shaped. The shape of the simulated damage is approximately fan-shaped, which is used to simulate damage such as cracks and depressions in reality. This can reduce the difficulty of simulation and the amount of calculation required for simulating damage. To conform to actual conditions, the wall thickness of the simulated damage edge and the semicircular structure is less than that of the inner and outer walls. The depth of the fan-shaped depression does not exceed 3 / 4 of the thickness of the outer and inner walls. The fan-shaped depressions are spaced at intervals on the left and top of the simulated damage edge and are distributed in a stepped manner at both ends of the simulated damage edge. The distribution is uneven, which is more consistent with the actual highway tunnel after fire. The distance between the inner bottom edge and the outer bottom edge is equal to the distance between the inner and outer sides, which can reduce the amount of calculation required for the non-simulated damage surface.

[0033] like Figure 2 As shown, the initial model of the 3D printing model provided by the present invention simulates a highway tunnel before the fire, including the inner wall and the outer wall. The upper half of the inner wall and the outer wall are both semicircular structures. The upper half of the inner wall is not damaged, and the lower half is Figure 1 The model shown is the same as the one shown, and the 3D printing model is built through the subsequent steps.

[0034] like Figure 3 As shown, the lower half of the analysis model of the 3D printing model provided by the present invention is Figure 1 The model shown is the same. The upper part consists of a semicircular outer wall (not marked in the figure), an initial structural surface, and an uneven structural damage surface. The structural damage surface is located between the initial structural surface and the outer wall. The initial structural surface is marked in yellow, and the structural damage surface is marked in green. The structural damage surface is marked based on the situation of a highway tunnel after a fire in real life. There are depressions and cracks distributed on the structural damage surface, which are used to analyze important parameters such as the degree of damage and location.

[0035] like Figure 5 As shown, the 3D printing model of the damaged structure of a highway tunnel after a fire provided by the present invention includes:

[0036] Step S101: retrieve the elastic modulus function of the post-disaster tunnel lining structure damage through the knowledge graph, and further determine the stiffness of the structural lining based on the function, and obtain the tunnel structure damage report in combination with on-site data analysis; Step S102: based on the damage report and similarity criteria, reflect the change in tunnel structure stiffness by changing the lining thickness of the model tunnel, use computer-aided design software CAD to establish a preliminary 3D printing model, and introduce the thermodynamic and mechanical properties of the tunnel material; Step S103: optimize the preliminary established 3D printing model, and verify the model accuracy through FEA modeling analysis based on the model. To ensure accuracy, the model parameters are adjusted through multiple iterations. In step S104, the optimized 3D model is input into the 3D printer, and PLA material is selected to ensure the strength and durability of the printed model. The printing parameters are monitored and adjusted in real time during the printing process to ensure the quality and accuracy of the model. In step S105, various mechanical property tests are performed on the printed 3D model, and the model is calibrated according to the test results to ensure that it can accurately reflect the damage of the actual tunnel. In step S106, the proposed 3D printed model is used to guide the production of a model for the post-fire tunnel model test, and the impact of the fire on the tunnel structure is analyzed.

[0037] The utility model provides an accurate and efficient 3D printing model of the damaged structure of a highway tunnel after a fire, which can truly reflect the damage situation of the tunnel after the disaster and provide guidance for the model making of the post-disaster tunnel structure model test.

[0038] In step S101, Figure 6 As shown in the figure, first, data nodes such as the elastic modulus of the damaged structure, damage type, damage degree, and damage location are constructed, and relationships between the nodes are established to comprehensively describe and analyze the tunnel damage situation. By integrating historical case and existing case data into a unified knowledge base, an efficient knowledge graph database retrieval system is formed. Laser scanning and high-precision photography are used to generate high-precision three-dimensional point cloud data and detailed surface image information, thereby fully capturing the current status of the tunnel lining structure and analyzing and processing the acquired field data. Then, the field data is fused and analyzed with the knowledge graph data, and the damage elastic modulus function is retrieved to determine the structural stiffness. A detailed damage report is generated, which includes the damage location, damage type, and damage degree, providing a scientific basis and data support for the post-disaster tunnel model test parameters.

[0039] In step S102, Figure 7As shown, first, tunnel-related parameters, including damage location, type, extent, lining thickness, and material properties, are input based on the damage report and similarity criteria. These parameters serve as the foundational data for model optimization. Using similarity criteria, various parameters of the model tunnel, particularly changes in lining thickness, are adjusted and optimized to accurately reflect changes in tunnel structural stiffness. After parameter optimization is complete, a preliminary 3D-printed model is created based on the optimized parameters using computer-aided design (CAD) software. During the 3D modeling process, the thermodynamic and mechanical properties of the tunnel material, including strength, elastic modulus, and thermal expansion coefficient, are comprehensively considered to ensure that the 3D-printed model accurately reflects the physical properties of the actual tunnel. The resulting 3D-printed model more accurately reflects the damage to the tunnel structure, ensuring model accuracy.

[0040] In particular, in step S22, the thickness of the model lining is changed to simulate the stiffness change of the post-disaster model due to damage, such as Figure 7 As shown, through a comprehensive analysis of knowledge graphs and field data, detailed damage reports for the tunnel were retrieved to determine the location, type, and extent of the damage. This generated a post-disaster site map, equating a section of the tunnel to a damaged curved beam. Based on local equivalence, the local damage was processed into a curved beam model with varying thickness. During this process, special attention was paid to the impact of thickness variations at each damage location on the overall stiffness of the tunnel. All damage details within the section were superimposed, and the thickness variations at each damage point were accurately simulated, ultimately creating a refined 3D printed model. This model not only accurately reflects the actual damage to the tunnel lining but also intuitively demonstrates the impact of damage on the tunnel's structural stiffness. During the modeling process, CAD software ensured that every detail was accurately reflected, providing a highly realistic physical model for post-disaster tunnel restoration.

[0041] In step S103, Figure 8 As shown, finite element analysis (FEA) is first used to establish an initial model. This initial model is based on the refined 3D printing model established in S22, determining key parameters such as the model's geometry, material properties, and boundary conditions. By analyzing the initial results, adjustments to the model thickness begin. This adjustment process requires comprehensive consideration of the complexity of actual tunnel damage and the feasibility of 3D printing technology to ensure that each adjustment is close to the actual situation. The optimized model is then subjected to FEA analysis again, and the new results are compared with the previous results to assess whether the adjusted model is closer to the actual situation. If the new model results meet expectations, the optimized model thickness and other adjustment parameters are recorded for use in subsequent steps. If the results still do not meet expectations, further adjustments to the model thickness are made.

[0042] This process typically requires multiple iterations, each leading to finer adjustments and more accurate analysis. Each iteration of modeling and analysis provides valuable data and experience for optimizing the final model. Through repeated iterations, the model's accuracy and reliability gradually improve, ultimately enabling it to accurately reproduce actual tunnel damage.

[0043] In step S104, the model parameters optimized through finite element analysis (FEA) are first imported into the CAD software to generate a high-precision model. Next, the processed CAD model is converted into an STL file format and uploaded to the 3D printer's control software for final preparations before printing. During the printing process, various 3D printer parameters, including print speed, layer thickness, and print temperature, are strictly controlled. Furthermore, to further improve model accuracy, necessary post-processing steps are performed after printing, including support structure removal, surface polishing, and coating treatment, ensuring that every detail of the model is as close to reality as possible.

[0044] In step S105, the 3D printed model undergoes mechanical property testing and calibration to ensure that it accurately reflects the complex damage conditions and mechanical properties of an actual tunnel. First, the model undergoes a series of detailed mechanical property tests, including compression, tension, and bending tests. During the compression test, the model is placed in a compression testing machine, where vertical loads are gradually applied to record deformation and bearing capacity under different loads. The model's compressive performance under axial load is evaluated to ensure that it simulates the behavior of a tunnel under geological pressure. During the tensile test, the model is stretched to fracture using a tensile testing machine. The stress-strain curve of the model during the stretching process is recorded to determine the model's tensile strength and ductility, ensuring that its performance under tension is consistent with actual conditions. During the bending test, a bending load is applied using a bending tester, and the model's response at different bending angles is recorded to evaluate the model's bending resistance, particularly its ability to withstand bending stresses of the tunnel structure. During each test, high-precision sensors and a data acquisition system record mechanical property data, including key parameters such as load, displacement, stress, and strain, to ensure the accuracy and integrity of the test data.

[0045] Next, the model parameters were adjusted and calibrated based on the results of the mechanical properties tests. First, the test results were analyzed in detail, and the model's material constitutive parameters, such as elastic modulus, yield strength, and Poisson's ratio, were adjusted to more accurately reflect the actual material properties. Geometric optimization was equally important. Based on geometric deformation and localized failures observed during the experiments, the model's geometry was optimized, such as by adding local reinforcements and adjusting thicknesses, to improve the model's stability and accuracy under load, ensuring that it more closely resembled the load patterns of an actual tunnel. The adjusted parameters and optimized geometry were then re-imported into the finite element analysis (FEA) software for a new simulation analysis to verify the performance of the adjusted and optimized model in a virtual environment and ensure that it accurately reproduced the actual conditions. Compression, tension, and bending tests were then conducted using the adjusted and optimized model, and new mechanical property data was recorded to confirm that the adjusted model performed as expected in the actual mechanical properties tests. The final test results were then compared in detail with the expected results to assess the consistency of the model's mechanical properties and geometric accuracy, ensuring that all mechanical performance indicators and geometric accuracy met the design requirements and accurately reflected the tunnel's damage and mechanical characteristics. All test data and simulation results are comprehensively analyzed to confirm whether the model's performance across various metrics meets expectations. If so, the final model parameters and design are recorded. If not, adjustments and optimizations are continued until all requirements are met. Through these refined steps, the final 3D printed model fully and accurately reflects the tunnel's complex damage conditions and mechanical properties, providing a scientific basis for tunnel project evaluation and maintenance.

[0046] In step S106, the optimized 3D printed model obtained in S105 is used to guide the production of a test model of the post-disaster damaged tunnel. The specific process is as follows:

[0047] First, based on the detailed data of the optimized 3D printing model, the parameters of the printing material were adjusted to ensure that the material used could truly reproduce the damage characteristics of the tunnel after the fire. This included selecting a suitable printing material and adjusting its density, elastic modulus, and thermal properties to match the changes in the tunnel structure after the fire.

[0048] Next, the 3D printer's speed and other printing conditions, such as temperature and layer thickness, are controlled to achieve highly accurate model production. This process requires meticulous adjustment of machine settings to ensure the printed model exhibits a high degree of geometric accuracy and surface finish, accurately reflecting the damage state of the actual tunnel. To further improve the model's accuracy and durability, necessary post-processing is performed after printing, including surface polishing, coating, and structural reinforcement. This eliminates errors and defects in the printing process and enhances the model's stability and strength.

[0049] Finally, the adjusted and post-processed test model will be used for actual post-disaster damage assessment. Through detailed inspection and testing of the model, performance data such as deformation, stress response, and failure mode will be recorded under simulated post-disaster conditions. This data will be used to verify and optimize the post-fire tunnel structural design and provide a scientific basis for actual repairs. This process ensures that the test model is not only highly accurate but also truly reproduces the post-disaster tunnel damage, providing reliable support for subsequent structural analysis and repair plans.

[0050] The preferred embodiments of the present invention disclosed above are intended only to illustrate the present invention. These preferred embodiments do not exhaustively describe all details, nor do they limit the present invention to specific embodiments. Obviously, many modifications and variations are possible based on the contents of this specification. These embodiments are selected and described in detail herein to better explain the principles and practical applications of the present invention, thereby enabling those skilled in the art to better understand and utilize the present invention. The present invention is limited only by the claims and their full scope and equivalents.

Claims

1. A 3D printed model of a damaged structure in a highway tunnel after a fire, comprising a cylindrical structure, wherein the cross section of the cylindrical structure comprises an outer wall and an inner wall, wherein the outer wall comprises an upper half of a semicircular structure, two outer sides, and an outer bottom side, wherein the two ends of the semicircular structure are respectively connected to the upper ends of the two outer sides, and the two ends of the outer bottom side are respectively connected to the lower ends of the two outer sides, characterized in that: The inner wall includes a simulated broken edge located in the upper half, two inner side edges and an inner bottom edge, the two ends of the simulated broken edge are respectively connected to the upper ends of the two inner side edges, and the two ends of the inner bottom edge are respectively connected to the lower ends of the two inner side edges.

2. A 3D printed model of a damaged structure of a highway tunnel after a fire according to claim 1, characterized in that: There are multiple fan-shaped depressions on the simulated damaged edge, and the fan-shaped depressions are distributed at intervals on the left side and the top of the simulated damaged edge.

3. The 3D printed model of a damaged structure of a highway tunnel after a fire according to claim 2, characterized in that: Both ends of the simulated damaged edge are provided with stepped depressions.

4. The 3D printed model of a damaged structure of a highway tunnel after a fire according to claim 2, characterized in that: The fan-shaped depressions are distributed more on the left side than on the right side.

5. The 3D printed model of a damaged structure of a highway tunnel after a fire according to claim 4, characterized in that: The depth of the fan-shaped recess does not exceed ¾ of the thickness of the outer wall and the inner wall.

6. A 3D printed model of a damaged structure of a highway tunnel after a fire according to any one of claims 2 to 5, characterized in that: The simulated breaking edge is approximately a semicircle.

7. The 3D printed model of a damaged structure of a highway tunnel after a fire according to claim 6, characterized in that: The wall thickness of the simulated broken edge and the semicircular structure is smaller than the wall thickness of the inner wall and the outer wall.

8. The 3D printed model of a damaged structure of a highway tunnel after a fire according to claim 7, characterized in that: The portion where the outer bottom edge is connected to the two outer sides is arc-shaped, and the portion where the inner bottom edge is connected to the two inner sides is arc-shaped.

9. The 3D printed model of a damaged structure of a highway tunnel after a fire according to claim 8, characterized in that: The distance between the inner bottom edge and the outer bottom edge is equal to the distance between the inner side edge and the outer side edge.

10. The 3D printed model of damaged structure of a highway tunnel after fire according to claim 9, characterized in that: The depth of the fan-shaped recess is approximately 1 / 2 of its width.

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