A reliability assessment platform and method for underwater shield tunnel waterproofing systems

Abstract

The present invention provides a reliability assessment platform and method for underwater shield tunnel waterproofing systems, relating to the technical field of shield tunnel evaluation. The method divides the outer surface of an underwater shield tunnel into N equal-sized regions, collects water samples with unknown centers at each location, and performs laboratory testing to obtain inorganic and organic data. A biocorrosion coefficient is generated based on the inorganic and organic data. Property data for the waterproofing material of the underwater shield tunnel waterproofing layer is obtained, and a waterproofing coefficient is generated based on the property data. A waterproofing system reliability assessment coefficient is generated based on the minimum value of the waterproofing coefficient and the biocorrosion coefficient of all regions. The reliability assessment of the tunnel waterproofing system is then completed based on the waterproofing system reliability assessment coefficient. This method considers the impact of microorganisms on the waterproofing system, making the waterproofing system reliability assessment more accurate.

Description

Technical Field

[0001] The present invention relates to the technical field of shield tunnel evaluation, and in particular to a reliability evaluation platform and evaluation method for an underwater shield tunnel waterproofing system. Background Art

[0002] In modern urban infrastructure construction, underwater shield tunnels, as crucial transportation corridors, face numerous environmental challenges, particularly water permeability and biocorrosion. These factors can lead to corrosion and damage to tunnel structures, seriously threatening their safety and service life. Existing waterproofing systems rely heavily on empirical experience and static testing, lacking dynamic, real-time assessment methods for tunnel waterproofing performance. Furthermore, traditional assessment methods often overlook the impact of biological factors in water samples on waterproofing materials, failing to fully reflect the actual reliability of the waterproofing system.

[0003] In the prior art, publication number CN118862439A discloses a reliability evaluation method and system for underwater large-diameter shield tunnel waterproofing systems. This method determines shield tunnel waterproofing system reliability evaluation indicators and an evaluation system; divides shield tunnel waterproofing system reliability evaluation grade standards; and based on the shield tunnel waterproofing system reliability evaluation system, uses an improved hierarchical analysis method to calculate the subjective weight of each evaluation indicator and an improved CRITIC method to calculate the objective weight of each evaluation indicator. The subjective and objective weights are then comprehensively calculated based on game theory to obtain a combined weight. Finally, a cloud model is introduced into the shield tunnel waterproofing system reliability evaluation system and evaluation grade standards to obtain the shield tunnel waterproofing system reliability evaluation grade. This method, based on the combined weighting method and cloud model, constructs a full-lifecycle shield tunnel waterproofing reliability evaluation model, addressing the ambiguity and randomness issues inherent in the full-lifecycle shield tunnel waterproofing reliability evaluation process. However, this existing technology still has shortcomings. For the evaluation of the waterproof reliability of shield tunnels, the evaluation of the waterproof layer is an important part, and the surrounding microorganisms in the waterproof layer have a huge impact on the waterproof ability of the waterproof layer. The existing technology does not take this into account, resulting in inaccurate evaluation results of the shield tunnel waterproof reliability.

[0004] The above information disclosed in this Background section is only for enhancement of understanding of the background of the present disclosure and therefore it may contain information that does not form the prior art that is already known to a person of ordinary skill in the art. Summary of the Invention

[0005] The purpose of the present invention is to provide a coal mine supervision method and system based on video images to solve the problems raised in the above background technology.

[0006] To achieve the above object, the present invention provides the following technical solutions:

[0007] A reliability assessment platform for underwater shield tunnel waterproofing systems, specifically comprising:

[0008] The data acquisition module is used to divide the external surface of the underwater shield tunnel into N areas of equal area, collect water samples from the center of each area, and test the water samples in the laboratory to obtain inorganic and organic data;

[0009] The biological evaluation module is used to calculate the hydrogen sulfide metabolism evaluation coefficient based on inorganic data and generate the sulfate-reducing bacteria biological interference coefficient based on organic data; and to generate the biocorrosion coefficient based on the hydrogen sulfide metabolism evaluation coefficient and the sulfate-reducing bacteria interference coefficient;

[0010] The material evaluation module is used to obtain the property data of the waterproof material of the underwater shield tunnel waterproof layer, generate the waterproof coefficient of the waterproof layer based on the property data of the waterproof material of the underwater shield tunnel waterproof layer, and generate the reliability evaluation coefficient of the waterproof system based on the minimum value of the waterproof coefficient of the waterproof layer and the biocorrosion coefficient of all areas;

[0011] The comprehensive evaluation module is used to complete the reliability evaluation of the tunnel waterproofing system based on the waterproofing system reliability evaluation coefficient.

[0012] Furthermore, the inorganic data include sulfate ion concentration, dissolved oxygen concentration, activation energy of the reaction of sulfate-reducing bacteria to produce hydrogen sulfide, and water sample temperature in the water sample;

[0013] The organic data includes the concentration of hydroxyl groups in organic matter, the comprehensive growth rate of sulfate-reducing bacteria, and the gene abundance of sulfate-reducing bacteria. The specific logic for obtaining the comprehensive growth rate of sulfate-reducing bacteria is as follows:

[0014] SRB were cultured in a water sample for one day. The day was divided into 24 measurement time periods at equal intervals. The growth rate of SRB in each measurement time period was obtained, and the average was used as the comprehensive growth rate of SRB. The calculation formula is as follows:

[0015]

[0016] in, is the comprehensive growth rate of sulfate-reducing bacteria, For the The number of sulfate-reducing bacteria at the end of each measurement period, For the The number of sulfate-reducing bacteria at the starting point of each measurement period, is the duration of the measurement period;

[0017] The abundance of sulfate-reducing bacteria genes was obtained by qPCR experiments on sulfate-reducing bacteria in water samples.

[0018] Furthermore, the specific logic for generating the biocorrosion coefficient is as follows: calculating the hydrogen sulfide metabolism evaluation coefficient based on inorganic data, generating the sulfate-reducing bacteria biological interference coefficient based on organic data; generating the biocorrosion coefficient based on the hydrogen sulfide metabolism evaluation coefficient and the sulfate-reducing bacteria interference coefficient;

[0019] The specific logic of the hydrogen sulfide metabolic evaluation coefficient is as follows: Based on the sulfate ion concentration, dissolved oxygen concentration, the activation energy of the sulfate-reducing bacteria metabolism reaction to produce hydrogen sulfide, and the water sample temperature, the specific formula for the hydrogen sulfide metabolic evaluation coefficient is as follows:

[0020]

[0021] in, is the hydrogen sulfide metabolism assessment coefficient, is the sulfate ion concentration, is the dissolved oxygen concentration, is the activation energy of the sulfate-reducing bacteria metabolism to produce hydrogen sulfide, is the gas constant, is the water sample temperature;

[0022] The specific logic for generating the sulfate-reducing bacteria biointerference coefficient is as follows: the hydroxyl concentration in organic matter, the comprehensive growth rate of sulfate-reducing bacteria, and the gene abundance of sulfate-reducing bacteria are analyzed to generate the sulfate-reducing bacteria biointerference coefficient. The specific formula for generating the sulfate-reducing bacteria biointerference coefficient is:

[0023]

[0024] in, To generate the sulfate-reducing bacteria biointerference coefficient, is the concentration of hydroxyl groups in organic matter, is the comprehensive growth rate of sulfate-reducing bacteria, is the abundance of sulfate-reducing bacteria genes;

[0025] The specific formula used to generate the biocorrosion coefficient is;

[0026]

[0027] in, is the biocorrosion coefficient.

[0028] Furthermore, the property data of the waterproof material of the underwater shield tunnel waterproof layer include the waterproof material permeability coefficient, elastic modulus, tensile strength, Poisson's ratio and waterproof layer thickness;

[0029] The permeability coefficient of the waterproof material is obtained through a water-filled permeability test, the elastic modulus and Poisson's ratio are obtained through a standard tensile test, and the tensile strength is obtained through a tensile testing machine.

[0030] Furthermore, the specific logic for generating the reliability evaluation coefficient of the waterproof layer system is as follows: obtaining the property data of the waterproof material of the underwater shield tunnel waterproof layer, generating the waterproof coefficient of the waterproof layer based on the property data of the waterproof material of the underwater shield tunnel waterproof layer, and generating the reliability evaluation coefficient of the waterproof layer system based on the minimum value of the waterproof coefficient of the waterproof layer and the biocorrosion coefficient of all areas; the specific formula for generating the waterproof coefficient of the waterproof layer is:

[0031]

[0032] in, is the waterproof coefficient of the waterproof layer, is the permeability coefficient of the waterproof material, is the elastic modulus of the waterproof material, is the tensile strength of the waterproof material, For the compressive strength of waterproof materials, is the Poisson's ratio of the waterproof material, is the thickness of the waterproof layer;

[0033] The specific formula for generating the reliability assessment coefficient of the waterproof layer system is:

[0034]

[0035] in, To generate the reliability evaluation coefficient of the waterproof system, is the minimum value of the biocorrosion coefficient of all areas.

[0036] Furthermore, the specific logic of the waterproof system reliability evaluation coefficient for evaluating the reliability of an underwater shield tunnel waterproof system is as follows: a waterproof system reliability evaluation threshold is preset, the waterproof system reliability evaluation coefficient is compared with the waterproof system reliability evaluation threshold, and the reliability evaluation coefficient of the waterproof system is used to evaluate the reliability of the waterproof system. Defined as a reliable waterproof system Defined as a reliable early warning system for waterproofing It is defined as an unreliable waterproofing system;

[0037] in, To generate the reliability evaluation coefficient of the waterproof system, Reliable assessment of threshold values ​​for waterproofing systems.

[0038] The present invention further provides a method for evaluating the reliability of an underwater shield tunnel waterproofing system. The method is used in the aforementioned underwater shield tunnel waterproofing system reliability evaluation platform and specifically comprises:

[0039] Step 1: Divide the outer surface of the underwater shield tunnel into N regions of equal area, collect water samples from the center of each region, and test the water samples in the laboratory to obtain inorganic and organic data;

[0040] Step 2: Calculate the hydrogen sulfide metabolism evaluation coefficient based on the inorganic data, generate the sulfate-reducing bacteria biological interference coefficient based on the organic data; generate the biocorrosion coefficient based on the hydrogen sulfide metabolism evaluation coefficient and the sulfate-reducing bacteria interference coefficient;

[0041] Step 3: Obtain the property data of the waterproof material of the underwater shield tunnel waterproof layer, generate the waterproof coefficient of the waterproof layer based on the property data of the waterproof material of the underwater shield tunnel waterproof layer, and generate the waterproof system reliability assessment coefficient based on the minimum value of the waterproof coefficient of the waterproof layer and the biocorrosion coefficient of all areas;

[0042] Step 4: Complete the reliability assessment of the tunnel waterproofing system based on the waterproofing system reliability assessment coefficient.

[0043] Compared with the prior art, the present invention has the following beneficial effects:

[0044] The present invention generates a biocorrosion coefficient based on inorganic and organic data from the external surface of an underwater shield tunnel. The biocorrosion coefficient indicates the corrosion rate or potential severity of corrosion caused by microbial activity. The inclusion of this coefficient can more accurately assess the reliability of waterproofing systems. BRIEF DESCRIPTION OF THE DRAWINGS

[0045] Figure 1 It is a schematic diagram of the overall platform structure of the present invention.

[0046] Figure 2 Schematic diagram of the overall method of the present invention. DETAILED DESCRIPTION

[0047] In order to make the objectives, technical solutions and advantages of the present invention more clearly understood, the present invention is further described in detail below with reference to specific embodiments.

[0048] It should be noted that, unless otherwise defined, the technical or scientific terms used in the present invention should have the usual meanings understood by people with ordinary skills in the field to which the present invention belongs. The "first", "second" and similar words used in the present invention do not indicate any order, quantity or importance, but are only used to distinguish different components. "Include" or "comprise" and similar words mean that the elements or objects appearing before the word include the elements or objects listed after the word and their equivalents, without excluding other elements or objects. "Connect" or "connected" and similar words are not limited to physical or mechanical connections, but may include electrical connections, whether direct or indirect. "Up", "down", "left", "right" and the like are only used to indicate relative position relationships. When the absolute position of the object being described changes, the relative position relationship may also change accordingly.

[0049] Example:

[0050] See also Figure 1 , the present invention provides a technical solution:

[0051] A reliability assessment platform for underwater shield tunnel waterproofing systems, specifically comprising:

[0052] The data acquisition module is used to divide the external surface of the underwater shield tunnel into N areas of equal area, collect water samples from the center of each area, and test the water samples in the laboratory to obtain inorganic and organic data;

[0053] The inorganic data include sulfate ion concentration, dissolved oxygen concentration, activation energy of the reaction of sulfate-reducing bacteria to produce hydrogen sulfide, and water sample temperature in the water sample;

[0054] The organic data includes the hydroxyl concentration in organic matter, the comprehensive growth rate of sulfate-reducing bacteria, and the gene abundance of sulfate-reducing bacteria; the inorganic and organic data are all normalized to the maximum and minimum values. The specific logic for obtaining the comprehensive growth rate of sulfate-reducing bacteria is as follows:

[0055] SRB were cultured in a water sample for one day. The day was divided into 24 measurement time periods at equal intervals. The growth rate of SRB in each measurement time period was obtained, and the average was used as the comprehensive growth rate of SRB. The calculation formula is as follows:

[0056]

[0057] in, is the comprehensive growth rate of sulfate-reducing bacteria, For the The number of sulfate-reducing bacteria at the end of each measurement period, For the The number of sulfate-reducing bacteria at the starting point of each measurement period, is the duration of the measurement period;

[0058] The abundance of sulfate-reducing bacteria genes was obtained by qPCR experiments on sulfate-reducing bacteria in water samples.

[0059] The biological evaluation module is used to calculate the hydrogen sulfide metabolism evaluation coefficient based on inorganic data and generate the sulfate-reducing bacteria biological interference coefficient based on organic data; and to generate the biocorrosion coefficient based on the hydrogen sulfide metabolism evaluation coefficient and the sulfate-reducing bacteria interference coefficient;

[0060] The specific logic for generating the biocorrosion coefficient is as follows: calculate the hydrogen sulfide metabolism evaluation coefficient based on inorganic data, generate the sulfate-reducing bacteria biological interference coefficient based on organic data; generate the biocorrosion coefficient based on the hydrogen sulfide metabolism evaluation coefficient and the sulfate-reducing bacteria interference coefficient;

[0061] The specific logic of the hydrogen sulfide metabolic evaluation coefficient is as follows: Based on the sulfate ion concentration, dissolved oxygen concentration, the activation energy of the sulfate-reducing bacteria metabolism reaction to produce hydrogen sulfide, and the water sample temperature, the specific formula for the hydrogen sulfide metabolic evaluation coefficient is as follows:

[0062]

[0063] in, is the hydrogen sulfide metabolism assessment coefficient, is the sulfate ion concentration, is the dissolved oxygen concentration, is the activation energy of the sulfate-reducing bacteria metabolism to produce hydrogen sulfide, is the gas constant, =water sample temperature; hydrogen sulfide is a highly corrosive substance, especially in underwater environments. When sulfate-reducing bacteria metabolize sulfate (SO₄²⁻) in an anoxic environment, they produce hydrogen sulfide. The presence of hydrogen sulfide not only directly causes chemical corrosion to waterproofing materials but also degrades their physical properties. The hydrogen sulfide metabolism assessment coefficient indicates the ability of sulfate-reducing bacteria to metabolize hydrogen sulfide. A higher coefficient indicates a higher potential for hydrogen sulfide production and a higher corrosion risk. Higher sulfate ion concentrations indicate a greater metabolic potential for sulfate-reducing bacteria, which in turn affects hydrogen sulfide production. Changes in dissolved oxygen concentration can affect microbial metabolic pathways. Low oxygen levels increase the metabolic activity of sulfate-reducing bacteria, leading to increased hydrogen sulfide production. Higher activation energy for the hydrogen sulfide production reaction requires more energy and is less likely to occur. Therefore, activation energy has a significant impact on the rate of hydrogen sulfide production. Temperature influences the reaction rate; generally, higher temperatures increase the reaction rate, making temperature an important factor in assessing metabolic capacity.

[0064] in, Based on the Arrhenius equation, the temperature sensitivity of sulfate-reducing bacteria (SRB) reduction reactions is positively correlated with the hydrogen sulfide metabolism coefficient. Dissolved oxygen is a key factor influencing the activity of SRB. SRB are anaerobic microorganisms, and high concentrations of dissolved oxygen inhibit their activity, reducing H2S production. Therefore, dissolved oxygen concentration is negatively correlated with H2S production capacity and serves as the denominator in the equation.

[0065] The specific logic for generating the sulfate-reducing bacteria biointerference coefficient is: the sulfate-reducing bacteria biointerference coefficient is generated by analyzing the hydroxyl groups in the organic matter, the comprehensive growth rate of sulfate-reducing bacteria, and the gene abundance of sulfate-reducing bacteria. The specific formula for generating the sulfate-reducing bacteria biointerference coefficient is:

[0066]

[0067] in, To generate the sulfate-reducing bacteria biointerference coefficient, is the concentration of hydroxyl groups in organic matter, is the comprehensive growth rate of sulfate-reducing bacteria, The SRB biointerference coefficient (SRI) represents the gene abundance of sulfate-reducing bacteria (SRBs). The SRI biointerference coefficient (SRI) reflects the impact of SRB on the environment or materials by measuring the concentration of hydroxyl groups in organic matter, the gene abundance of SRBs, and the overall growth rate. The SRI biointerference coefficient (SRI) indicates the potential impact of SRB on the environment or materials. A higher SRI indicates a more significant SRI interference effect, leading to severe corrosion. SRBs require hydroxyl groups in organic matter as a primary energy source for hydrogen sulfide metabolism. A higher hydroxyl concentration in organic matter means more energy is available to the microorganisms, driving their growth and metabolic activity and increasing the biointerference effect. Gene abundance reflects the number and activity of SRB in the environment. A higher gene abundance generally indicates a greater presence of SRB, which enhances their impact on materials. The SRI biointerference coefficient (SRI) represents the growth rate of SRB under specific environmental conditions. A faster growth rate indicates more active microbial metabolic activity and a greater potential to produce corrosive substances (such as hydrogen sulfide).

[0068] The formula uses the fourth power of one third ( ) is to reflect the nonlinear effect of gene abundance on biotic perturbation capacity. Higher gene abundance generally indicates higher bacterial populations and greater metabolic potential, but this relationship may not be completely linear, so the effect was adjusted by the power of one-third and one-fourth. 、 and They are all linearly positively correlated with the biological interference coefficient of sulfate-reducing bacteria, so the relationship between them and the biological interference coefficient of sulfate-reducing bacteria is expressed by the method of continuous product.

[0069] The specific formula used to generate the biocorrosion coefficient is;

[0070]

[0071] in, The biocorrosion coefficient (BCC) indicates the corrosion rate or potential severity of corrosion caused by microbial activity. A higher BCC indicates a greater corrosion risk and can lead to faster failure of waterproofing materials. The BCC assesses the risk of microbial corrosion by integrating hydrogen sulfide production capacity and the biointerference effect of sulfate-reducing bacteria (SRB). By monitoring and analyzing these parameters, it is possible to effectively predict and prevent potential biocorrosion issues in various engineering environments and implement appropriate protective measures. The H2S metabolism assessment coefficient (H2S) reflects the ability of SRB to produce H2S in underwater or soil environments. As H2S is a highly corrosive gas, this coefficient is crucial for understanding the impact of biocorrosion. A higher H2S metabolism assessment coefficient generally indicates a faster H2S production rate, which may lead to more severe corrosion. The SRB biointerference coefficient (SRI) indicates the impact of SRB on the environment or substrate. This coefficient is related to the concentration of organic matter, the genetic abundance of SRB, and the overall growth rate. Higher values ​​indicate higher SRB activity in the environment, leading to a stronger interference effect and potentially accelerating corrosion.

[0072] Two factors, hydrogen sulfide generation capacity and the biointerference coefficient, act synergistically to determine the risk of biocorrosion. A high hydrogen sulfide generation capacity combined with a high biointerference coefficient typically significantly increases the severity of corrosion. Multiplying these two parameters comprehensively accounts for the metabolic activity of sulfate-reducing bacteria and their influence in the environment.

[0073] The material evaluation module is used to obtain the property data of the waterproof material of the underwater shield tunnel waterproof layer, generate the waterproof coefficient of the waterproof layer based on the property data of the waterproof material of the underwater shield tunnel waterproof layer, and generate the reliability evaluation coefficient of the waterproof system based on the minimum value of the waterproof coefficient of the waterproof layer and the biocorrosion coefficient of all areas;

[0074] The property data of the waterproof material of the underwater shield tunnel waterproof layer include the waterproof material permeability coefficient, elastic modulus, tensile strength, Poisson's ratio and waterproof layer thickness;

[0075] The permeability coefficient of the waterproof material is obtained through a water-filled permeability test, the elastic modulus and Poisson's ratio are obtained through a standard tensile test, and the tensile strength is obtained through a tensile testing machine.

[0076] The specific logic for generating the reliability evaluation coefficient of the waterproof layer system is as follows: obtaining the property data of the waterproof material of the underwater shield tunnel waterproof layer, generating the waterproof coefficient of the waterproof layer based on the property data of the waterproof material of the underwater shield tunnel waterproof layer, and generating the reliability evaluation coefficient of the waterproof layer system based on the minimum value of the waterproof coefficient of the waterproof layer and the biocorrosion coefficient of all areas; the specific formula for generating the waterproof coefficient of the waterproof layer is:

[0077]

[0078] in, is the waterproof coefficient of the waterproof layer, is the permeability coefficient of the waterproof material, is the elastic modulus of the waterproof material, is the tensile strength of the waterproof material, For the compressive strength of waterproof materials, is the Poisson's ratio of the waterproof material, The waterproofing coefficient of a waterproof layer indicates the waterproofing performance of the waterproofing material. A larger value indicates better waterproofing. The material's permeability coefficient reflects the material's ability to penetrate water. A lower permeability coefficient indicates better waterproofing. The Poisson's ratio of a waterproof material indicates the ratio of lateral to longitudinal strain when the material is subjected to tension or compression. Poisson's ratio negatively impacts the material's deformation properties. The elastic modulus of a waterproof material reflects the material's ability to deform under stress. A higher elastic modulus indicates greater rigidity and greater resistance to deformation. The compressive strength of a waterproof material indicates the maximum stress it can withstand under compression. A thicker waterproof layer generally provides better waterproofing. The waterproofing coefficient of a waterproof layer evaluates the material's waterproofing capabilities using its physical and mechanical properties (such as permeability coefficient, elastic modulus, Poisson's ratio, tensile strength, and compressive strength). A high waterproofing coefficient value indicates that the waterproof layer effectively prevents water from penetrating, thereby protecting the internal structure.

[0079] Thickness directly impacts the barrier effectiveness of a waterproof layer. Generally, the thicker the layer, the more difficult it is for water to penetrate. Therefore, thickness, as part of a product, can enhance the waterproofing coefficient. Elastic modulus and compressive strength are important indicators of a material's ability to resist deformation and withstand pressure. Since they contribute equally to waterproofing performance, their sum and multiplication by the thickness of the waterproofing layer form the numerator. Low permeability is a key characteristic of waterproofing materials. The lower the permeability coefficient, the greater the overall waterproofing coefficient (KFW), indicating better waterproofing performance. The Poisson's ratio reflects the ratio of lateral to axial strain during material deformation. A high Poisson's ratio can lead to adverse deformation, which is affected by water penetration. Therefore, the permeability coefficient and the Poisson's ratio of the waterproofing material are multiplied together and used as the denominator to reflect their synergistic negative impact on waterproofing performance.

[0080] The specific formula for generating the reliability assessment coefficient of the waterproof layer system is:

[0081]

[0082] in, To generate the reliability evaluation coefficient of the waterproof system, The minimum biocorrosion coefficient for all areas. The waterproofing system reliability assessment coefficient is calculated by ratioing the minimum biocorrosion coefficient to the waterproofing layer's waterproofing coefficient, yielding the overall reliability of the waterproofing system under microbial influence. A high waterproofing system reliability assessment coefficient indicates that the waterproofing system can maintain its waterproofing effectiveness even in the face of biocorrosion. The biocorrosion coefficient reflects the potential threat posed by microorganisms to the waterproofing layer. A higher biocorrosion coefficient requires a stronger waterproofing layer to resist such attack. The minimum biocorrosion coefficient is determined by monitoring and assessing the activity levels of hydrogen sulfide and sulfate-reducing bacteria. This value reflects the potential risk of microbial corrosion in the environment. A higher biocorrosion coefficient requires a stronger waterproofing layer to resist such attack. The reliability of the waterproofing system requires an assessment of the least reliable locations. If the waterproofing system is reliable even at the lowest biocorrosion coefficient, the overall reliability of the waterproofing system is undoubtedly sufficient.

[0083] The comprehensive evaluation module is used to complete the reliability evaluation of the tunnel waterproofing system based on the waterproofing system reliability evaluation coefficient.

[0084] The specific logic of evaluating the reliability of an underwater shield tunnel waterproofing system based on the water system reliability assessment coefficient is as follows: preset a waterproofing system reliability assessment threshold, compare the waterproofing system reliability assessment coefficient with the waterproofing system reliability assessment threshold, and Defined as a reliable waterproof system Defined as a reliable early warning system for waterproofing It is defined as an unreliable waterproofing system;

[0085] in, To generate the reliability evaluation coefficient of the waterproof system, Reliable assessment of threshold values ​​for waterproofing systems.

[0086] The present invention further provides a method for evaluating the reliability of an underwater shield tunnel waterproofing system. The method is used in the aforementioned underwater shield tunnel waterproofing system reliability evaluation platform and specifically comprises:

[0087] Step 1: Divide the outer surface of the underwater shield tunnel into N regions of equal area, collect water samples from the center of each region, and test the water samples in the laboratory to obtain inorganic and organic data;

[0088] Step 2: Calculate the hydrogen sulfide metabolism evaluation coefficient based on the inorganic data, generate the sulfate-reducing bacteria biological interference coefficient based on the organic data; generate the biocorrosion coefficient based on the hydrogen sulfide metabolism evaluation coefficient and the sulfate-reducing bacteria interference coefficient;

[0089] Step 3: Obtain the property data of the waterproof material of the underwater shield tunnel waterproof layer, generate the waterproof coefficient of the waterproof layer based on the property data of the waterproof material of the underwater shield tunnel waterproof layer, and generate the waterproof system reliability assessment coefficient based on the minimum value of the waterproof coefficient of the waterproof layer and the biocorrosion coefficient of all areas;

[0090] Step 4: Complete the reliability assessment of the tunnel waterproofing system based on the waterproofing system reliability assessment coefficient.

[0091] The above formulas are all dimensionless and numerical calculations. The formulas are obtained by collecting a large amount of data and performing software simulation to obtain the most recent real situation. The preset parameters in the formulas are set by technicians in this field according to actual conditions.

[0092] The above embodiments can be implemented in whole or in part by software, hardware, firmware, or any other combination thereof. When implemented using software, the above embodiments can be implemented in whole or in part in the form of a computer program product. Those skilled in the art will appreciate that the units and algorithm steps of each example described in conjunction with the embodiments disclosed herein can be implemented by electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are performed by hardware or software depends on the specific application and design constraints of the technical solution.

[0093] The units described as separate components may or may not be physically separate, and the components shown as units may or may not be physical units, and may be located in one place or distributed across multiple network units. Some or all of these units may be selected to achieve the purpose of this embodiment as needed.

[0094] The above is only a specific implementation method of the present application, but the scope of protection of the present application is not limited thereto. Any technician familiar with this technical field can easily think of changes or replacements within the technical scope disclosed in this application, which should be covered by the scope of protection of the present application.

Claims

1. A reliability assessment platform for underwater shield tunnel waterproofing systems, characterized in that: Specifically include: The data acquisition module is used to divide the external surface of the underwater shield tunnel into N areas of equal area, collect water samples from the center of each area, and test the water samples in the laboratory to obtain inorganic and organic data; The biological evaluation module is used to calculate the hydrogen sulfide metabolism evaluation coefficient based on inorganic data and generate the sulfate-reducing bacteria biological interference coefficient based on organic data; and to generate the biocorrosion coefficient based on the hydrogen sulfide metabolism evaluation coefficient and the sulfate-reducing bacteria interference coefficient; The material evaluation module is used to obtain the property data of the waterproof material of the underwater shield tunnel waterproof layer, generate the waterproof coefficient of the waterproof layer based on the property data of the waterproof material of the underwater shield tunnel waterproof layer, and generate the reliability evaluation coefficient of the waterproof system based on the minimum value of the waterproof coefficient of the waterproof layer and the biocorrosion coefficient of all areas; Comprehensive evaluation module, used to complete the reliability assessment of the tunnel waterproofing system based on the waterproofing system reliability assessment coefficient; Based on the sulfate ion concentration, dissolved oxygen concentration, activation energy of the sulfate-reducing bacteria metabolism to produce hydrogen sulfide, and water sample temperature, the specific formula for generating the hydrogen sulfide metabolism evaluation coefficient is as follows: in, is the hydrogen sulfide metabolism assessment coefficient, is the sulfate ion concentration, is the dissolved oxygen concentration, is the activation energy of the sulfate-reducing bacteria metabolism to produce hydrogen sulfide, is the gas constant, is the water sample temperature; The hydroxyl concentration in organic matter, the comprehensive growth rate of sulfate-reducing bacteria, and the gene abundance of sulfate-reducing bacteria were analyzed to generate the sulfate-reducing bacteria biological interference coefficient. The specific formula for generating the sulfate-reducing bacteria biological interference coefficient is: in, To generate the sulfate-reducing bacteria biointerference coefficient, is the concentration of hydroxyl groups in organic matter, is the comprehensive growth rate of sulfate-reducing bacteria, is the abundance of sulfate-reducing bacteria genes; The specific formula used to generate the biocorrosion coefficient is; in, is the biocorrosion coefficient.

2. The underwater shield tunnel waterproofing system reliability assessment platform according to claim 1, characterized in that: The inorganic data include sulfate ion concentration, dissolved oxygen concentration, activation energy of the reaction of sulfate-reducing bacteria to produce hydrogen sulfide, and water sample temperature in the water sample; The organic data includes the hydroxyl concentration in the organic matter, the comprehensive growth rate of sulfate-reducing bacteria, and the gene abundance of sulfate-reducing bacteria. The specific logic for obtaining the comprehensive growth rate of sulfate-reducing bacteria is as follows: sulfate-reducing bacteria are cultured in a water sample environment for one day, and the day is divided into 24 measurement time periods at equal intervals. The growth rate of sulfate-reducing bacteria in each measurement time period is obtained, and the average of the values ​​is used as the comprehensive growth rate of sulfate-reducing bacteria. The calculation formula is as follows: in, is the comprehensive growth rate of sulfate-reducing bacteria, For the The number of sulfate-reducing bacteria at the end of each measurement period, For the The number of sulfate-reducing bacteria at the starting point of each measurement period, is the duration of the measurement period; The abundance of sulfate-reducing bacteria genes was obtained by qPCR experiments on sulfate-reducing bacteria in water samples.

3. The underwater shield tunnel waterproofing system reliability assessment platform according to claim 1, characterized in that: The property data of the waterproof material of the underwater shield tunnel waterproof layer include the waterproof material permeability coefficient, elastic modulus, tensile strength, Poisson's ratio and waterproof layer thickness; The permeability coefficient of the waterproof material is obtained through a water-filled permeability test, the elastic modulus and Poisson's ratio are obtained through a standard tensile test, and the tensile strength is obtained through a tensile testing machine.

4. The underwater shield tunnel waterproofing system reliability assessment platform according to claim 3, characterized in that: The specific logic for generating the reliability evaluation coefficient of the waterproof layer system is as follows: obtaining the property data of the waterproof material of the underwater shield tunnel waterproof layer, generating the waterproof coefficient of the waterproof layer based on the property data of the waterproof material of the underwater shield tunnel waterproof layer, and generating the reliability evaluation coefficient of the waterproof layer system based on the minimum value of the waterproof coefficient of the waterproof layer and the biocorrosion coefficient of all areas; the specific formula for generating the waterproof coefficient of the waterproof layer is: in, is the waterproof coefficient of the waterproof layer, is the permeability coefficient of the waterproof material, is the elastic modulus of the waterproof material, is the tensile strength of the waterproof material, For the compressive strength of waterproof materials, is the Poisson's ratio of the waterproof material, is the thickness of the waterproof layer; The specific formula for generating the reliability assessment coefficient of the waterproof layer system is: in, To generate the reliability evaluation coefficient of the waterproof system, is the minimum value of the biocorrosion coefficient of all areas.

5. The underwater shield tunnel waterproofing system reliability assessment platform according to claim 4, characterized in that: The specific logic for evaluating the reliability of an underwater shield tunnel waterproofing system using the waterproofing system reliability evaluation coefficient is as follows: preset a waterproofing system reliability evaluation threshold, compare the waterproofing system reliability evaluation coefficient with the waterproofing system reliability evaluation threshold, and Defined as a reliable waterproof system Defined as a reliable early warning system for waterproofing It is defined as an unreliable waterproofing system; in, To generate the reliability evaluation coefficient of the waterproof system, Reliable assessment of threshold values ​​for waterproofing systems.

6. A reliability assessment method for an underwater shield tunnel waterproofing system, characterized by: The method is used to implement the underwater shield tunnel waterproofing system reliability assessment platform according to any one of claims 1 to 5, specifically comprising: Step 1: Divide the outer surface of the underwater shield tunnel into N regions of equal area, collect water samples from the center of each region, and test the water samples in the laboratory to obtain inorganic and organic data; Step 2: Calculate the hydrogen sulfide metabolism evaluation coefficient based on the inorganic data, generate the sulfate-reducing bacteria biological interference coefficient based on the organic data; generate the biocorrosion coefficient based on the hydrogen sulfide metabolism evaluation coefficient and the sulfate-reducing bacteria interference coefficient; Step 3: Obtain the data of waterproof material properties of underwater shield tunnel waterproof layer, generate waterproof coefficient of waterproof layer according to the data of waterproof material properties of underwater shield tunnel waterproof layer, and calculate the minimum value of waterproof coefficient of waterproof layer and biocorrosion coefficient of all areas. Generate waterproof system reliability assessment coefficient; Step 4: Complete the reliability assessment of the tunnel waterproofing system based on the waterproofing system reliability assessment coefficient; Based on the sulfate ion concentration, dissolved oxygen concentration, activation energy of the sulfate-reducing bacteria metabolism to produce hydrogen sulfide, and water sample temperature, the specific formula for generating the hydrogen sulfide metabolism evaluation coefficient is as follows: in, is the hydrogen sulfide metabolism assessment coefficient, is the sulfate ion concentration, is the dissolved oxygen concentration, is the activation energy of the sulfate-reducing bacteria metabolism to produce hydrogen sulfide, is the gas constant, is the water sample temperature; The hydroxyl concentration in organic matter, the comprehensive growth rate of sulfate-reducing bacteria, and the gene abundance of sulfate-reducing bacteria were analyzed to generate the sulfate-reducing bacteria biological interference coefficient. The specific formula for generating the sulfate-reducing bacteria biological interference coefficient is: in, To generate the sulfate-reducing bacteria biointerference coefficient, is the concentration of hydroxyl groups in organic matter, is the comprehensive growth rate of sulfate-reducing bacteria, is the abundance of sulfate-reducing bacteria genes; The specific formula used to generate the biocorrosion coefficient is; in, is the biocorrosion coefficient.

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