CN114722650A - Tunnel structure residual life prediction method based on lining degradation - Google Patents

Tunnel structure residual life prediction method based on lining degradation Download PDF

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CN114722650A
CN114722650A CN202210070829.3A CN202210070829A CN114722650A CN 114722650 A CN114722650 A CN 114722650A CN 202210070829 A CN202210070829 A CN 202210070829A CN 114722650 A CN114722650 A CN 114722650A
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lining
tunnel
concrete
tunnel lining
time
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缪林昌
刘栗昊
王霆
钱振东
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Southeast University
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    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F30/00—Computer-aided design [CAD]
    • G06F30/20—Design optimisation, verification or simulation
    • G06F30/23—Design optimisation, verification or simulation using finite element methods [FEM] or finite difference methods [FDM]
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F30/00—Computer-aided design [CAD]
    • G06F30/10—Geometric CAD
    • G06F30/13—Architectural design, e.g. computer-aided architectural design [CAAD] related to design of buildings, bridges, landscapes, production plants or roads
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F2119/00—Details relating to the type or aim of the analysis or the optimisation
    • G06F2119/04—Ageing analysis or optimisation against ageing
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F2119/00—Details relating to the type or aim of the analysis or the optimisation
    • G06F2119/08—Thermal analysis or thermal optimisation
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F2119/00—Details relating to the type or aim of the analysis or the optimisation
    • G06F2119/14—Force analysis or force optimisation, e.g. static or dynamic forces

Abstract

The invention discloses a method for predicting the residual life of a tunnel structure based on lining degradation, which comprises the following steps: step 1, establishing a tunnel lining concrete strength deterioration model; step 2, determining the carbonization depth of the lining concrete and the development rule of the elastic modulus of the concrete according to actual measurement of engineering, and establishing a carbonization depth prediction model; step 3, establishing a tunnel lining finite element calculation model according to the actual condition of the tunnel, and extracting the stress condition of the tunnel lining; step 4, obtaining a tunnel lining safety coefficient time-varying formula; and 5, establishing a tunnel lining residual life prediction method. The tunnel lining safety evaluation and prediction method considers the influences of tunnel lining carbonization and tunnel lining strength deterioration on tunnel lining safety, is combined with highway tunnel design specifications and engineering practice, can reflect the tunnel lining safety more truly according to the calculation result, and can predict and evaluate the residual life of the tunnel lining more accurately.

Description

Tunnel structure residual life prediction method based on lining degradation
Technical Field
The invention belongs to the field of safety evaluation and prediction of tunnel structures in tunnel engineering, and particularly relates to a residual life prediction evaluation method of a tunnel structure based on lining degradation.
Background
Due to the construction difficulty and the construction cost of the tunnel engineering, the design service life of the tunnel engineering exceeds 100 years. In the whole stage after the tunnel lining is constructed, the tunnel lining faces long-term environmental tests, and in the service life cycle of the tunnel, surrounding rock creep and failure of primary lining can cause the pressure born by the secondary lining to be larger and larger. The lining concrete is very easy to deteriorate due to the influence of the environment, because the temperature difference exists inside and outside the concrete in the process of pouring the concrete of the tunnel, and then the concrete is hardened, shrinkage cracks are easily generated, and the cracks provide convenience for the carbonization of the concrete. Carbonization of concrete is a chemical attack to which concrete is subjected from the environment. CO in air2The gas permeates into the concrete and reacts with the alkaline substance to form carbonate and water, so that the alkalinity of the concrete is reduced, namely the concrete is carbonized and also called neutralized, and the chemical reaction is Ca (OH)2+CO2＝CaCO3+H2And (O). The cement generates a large amount of calcium hydroxide in the hydration process, so that the gaps of the concrete are filled with saturated calcium hydroxide solution, and the alkaline medium has good protection effect on the reinforcing steel bars, so that indissolvable Fe is generated on the surfaces of the reinforcing steel bars 2O3And Fe3O4And is referred to as a passivation film (alkaline oxide film). The alkalinity of the concrete is reduced after carbonization, and when the carbonization exceeds the protective layer of the concrete, the concrete loses the protective effect on the reinforcing steel bars under the condition of the presence of water and air, and the reinforcing steel bars begin to rust. The lining concrete is corroded and carbonized, so that cracks are generated, and the effective thickness of the tunnel lining is obviously reduced. Therefore, the influence of these phenomena on the long-term performance and safety of the tunnel needs to be fully considered in the evaluation of the whole life cycle of the tunnel lining.
At present, most of researches on the prediction of the service life of a tunnel lining structure are based on an indoor concrete rapid carbonization test, and meanwhile, a steel bar corrosion criterion and a concrete cracking criterion are combined to be used as a judgment basis, so that a series of research results are obtained, including the prediction of the service life of the lining structure controlled by a crack limit value and the prediction of the service life of the lining structure controlled by a bearing capacity limit value, and the safety of the lining structure can be evaluated and the residual service life can be predicted. Sunfu et al, in the text of "prediction research on durability life of tunnel lining structure" (report on underground space and engineering, 2006,2(3):3.), proposed a method for determining the final life of a lining structure by respectively taking crack limit values and bearing capacity as standards for measuring the end of the life of the tunnel structure, predicting the structure life under different criteria, and comparing the structure life with the standard. In the 'prediction of durability life of tunnel lining structure and prevention and control measures' of Liujun forest and the like, crack limit values, carbonization criteria and bearing capacity criteria are respectively used as standards for measuring the end of the life of the tunnel structure.
Limitations of the above existing models and methods: firstly, the highway tunnel lining structure is under the action of strong ground stress, and the influence of stress is not considered in predicting the lining life. Secondly, the influence of structural stress change on prediction caused by tunnel lining defects is ignored in the existing method. Thirdly, the existing method does not consider the dynamic reduction of the bearing capacity of the lining caused by the increase of the operating life of the lining, and the prediction deviation is larger.
Disclosure of Invention
In order to overcome the defects of the prior art, the invention provides a method for predicting the residual life of a tunnel structure based on lining degradation, which comprehensively considers the influence of tunnel lining carbonization on the effective thickness of a tunnel, increases the influence of the operating life of the tunnel on the bearing capacity of lining concrete, influences of the stress of the tunnel lining on the safety, and can reflect the safety of the tunnel lining more truly according to the calculation result.
In order to achieve the above object, the technical scheme of the invention is as follows:
a tunnel safety and residual life prediction method based on lining degradation is characterized in that the concrete strength parameter measured on site is utilized to infer the concrete carbonization depth of the tunnel wall in the monitoring point area range, and intelligent evaluation is carried out on the performance state of the tunnel concrete structure. The method comprises the following steps:
Step 1, establishing a tunnel lining concrete strength degradation model.
According to the concrete corrosion law in the existing corrosive ion environment, a lining thickness simplified time-varying model in the service environment is provided, the lining deterioration thickness is further linked with the lining elastic modulus and strength, and the time-varying model with the exponential decay of the lining tensile strength and the compressive strength along with time is provided as follows:
Figure BDA0003482075180000021
wherein, t0Constructing time for supporting; ra0The initial compressive strength of the concrete; ra(t) is lining time-varying compressive strength; rl0The initial tensile strength of the concrete; rl(t) is lining time-varying tensile strength; beta is a constant and represents a lining degradation coefficient, and is selected according to the concrete grade.
And 2, determining a development rule of the carbonization depth of the lining concrete according to actual measurement of engineering and establishing a carbonization depth prediction model.
Combining a basic carbonization depth prediction model and field carbonization depth actual measurement data, the carbonization depth prediction model of the corresponding engineering is provided as follows:
Figure BDA0003482075180000022
wherein, KmcEngineering carbonization coefficients, and fitting according to the actual measurement result; k is a radical ofco2The influence coefficient of the concentration of the carbon dioxide,
Figure BDA0003482075180000023
t is the annual average temperature (. degree. C.) of the environment; RH is ambient annual average relative humidity (%); f. ofcuThe concrete cube compressive strength (MPa); m is cAnd (4) actually measuring the strength of the tunnel concrete.
And 3, establishing a tunnel lining finite element calculation model according to the actual condition of the tunnel, and extracting the stress condition of the tunnel lining.
Establishing a finite element model in finite element software according to conditions such as tunnel burial depth, tunnel lining design data, tunnel lining actual detection results, surrounding rock strength and the like, calculating, and extracting the distribution of bending moment M and axial force N of the key section of the tunnel lining in post-processing.
And 4, obtaining a tunnel lining safety coefficient time-varying formula.
And (3) substituting the tunnel lining concrete strength degradation model and the lining concrete carbonization depth prediction model obtained in the steps 1 and 2 into a lining safety coefficient calculation formula specified in road tunnel design specification JTG 3370.1-2018 by using the bending moment M and the axial force N of the tunnel lining section obtained in the step 3 to obtain a safety coefficient time-varying formula as follows:
Figure BDA0003482075180000031
wherein the content of the first and second substances,
Figure BDA0003482075180000032
is the concrete stability factor; n is axial force (kN); m is a bending moment (kN.m); alpha is alphaXIs the eccentricity influence coefficient over time:
Figure BDA0003482075180000033
e0eccentricity of axial force, e0＝M/N；
b is the width (m) of the section of the tunnel lining; h is the thickness (m) of the section of the tunnel lining.
And 5, establishing a tunnel lining residual life prediction method.
And when the safety coefficient obtained in the step 4 is lower than 2.4, the lining safety service life is ended, and the time of putting into operation is subtracted from the ending time, so that the residual service life of the lining can be predicted.
Has the beneficial effects that: compared with the prior art, the invention has the following characteristics:
(1) according to the method, the concrete strength parameter measured on site is used for presuming the concrete carbonization depth of the tunnel wall in the monitoring point area range, and the performance state of the tunnel concrete structure is intelligently evaluated. The calculation result can reflect the safety of the tunnel lining more truly.
(2) The invention considers the influence of tunnel lining carbonization on the effective thickness of the tunnel, the influence of the increase of the tunnel operation age on the bearing capacity of lining concrete, the influence of the stress of the tunnel lining on the safety and other three factors, considers the measured data of the operated tunnel, and uses the measured data as a correction coefficient, thereby more accurately predicting the service life of the tunnel. The method reduces the cost for long-term operation of the tunnel engineering, ensures the safety of the tunnel engineering, and has good economic benefit and social benefit.
Drawings
FIG. 1 is a flowchart of a method for predicting the remaining life of a tunnel structure based on lining degradation according to the present invention;
FIG. 2 is a graph showing the deterioration tendency of the structural strength of the tunnel lining in example 1;
fig. 3 is a graph showing the development prediction of the carbonization depth of the tunnel lining structure in example 1;
fig. 4 is a time-varying graph of the safety coefficient of the tunnel lining structure in example 1.
Detailed Description
The present invention will be described in detail below with reference to the accompanying drawings and specific embodiments.
Example 1
Referring to fig. 1, a method for predicting the remaining life of a tunnel structure based on lining degradation includes the following steps:
1) and establishing a tunnel lining concrete strength deterioration model.
According to the concrete corrosion rule in the existing corrosive ion environment, a lining thickness simplified time-varying model in the service environment is provided, the lining deterioration thickness is further linked with the lining elastic modulus and strength, and the time-varying model with the lining tensile strength and the compressive strength exponentially decaying along with time is provided as follows:
Figure BDA0003482075180000041
wherein, t0Constructing time for supporting; ra0The initial compressive strength of the concrete; rl0The initial tensile strength of the concrete; beta is constant and represents the deterioration coefficient of lining, in this case, beta is 0.001a-1。
And calculating to obtain a lining structure compressive strength deterioration trend chart as shown in figure 2.
2) And according to actual measurement of engineering, determining a development rule of the carbonization depth of the lining concrete and establishing a carbonization depth prediction model.
Combining a basic carbonization depth prediction model and field carbonization depth actual measurement data, the carbonization depth prediction model of the corresponding engineering is provided as follows:
Figure BDA0003482075180000042
wherein, KmcEngineering carbonization coefficients, and fitting according to the actual measurement result; k is a radical ofco2The influence coefficient of the concentration of the carbon dioxide,
Figure BDA0003482075180000043
t is the annual average temperature (. degree. C.) of the environment; RH is ambient annual average relative humidity (%); f. ofcuThe concrete cube compressive strength (MPa); m iscAnd (5) actually measuring the strength of the tunnel concrete.
The measured data are shown in Table 1, and a chart of the development prediction of the carbonization depth is obtained as shown in FIG. 3.
Table 1 engineering parameter values
Figure BDA0003482075180000044
3) Establishing a finite element model in finite element software according to conditions such as tunnel burial depth, tunnel lining design data, tunnel lining actual detection results, surrounding rock strength and the like, dividing grids, setting materials and boundary conditions, and setting a grid division diagram as shown in FIG. 4.
After submitting calculation and finishing, the bending moment M and the axial force N of the tunnel lining key section can be extracted in the finite element software post-processing.
4) And obtaining a tunnel lining safety coefficient time-varying formula.
And (3) substituting the tunnel lining concrete strength degradation model and the lining concrete carbonization depth prediction model obtained in the steps 1 and 2 into a lining safety coefficient calculation formula specified in road tunnel design specification JTG 3370.1-2018 by using the bending moment M and the axial force N of the tunnel lining section obtained in the step 3 to obtain a safety coefficient time-varying formula as follows:
Figure BDA0003482075180000045
Wherein, the first and the second end of the pipe are connected with each other,
Figure BDA0003482075180000046
is the concrete stability factor; n is axial force (kN); m is a bending moment (kN.m); alpha is alphaXIs the eccentricity influence coefficient over time:
Figure BDA0003482075180000051
e0eccentricity of axial force, e0＝M/N；
b is the width (m) of the section of the tunnel lining; h is the thickness (m) of the section of the tunnel lining.
Preferably, Φ is 1, b is 1, and h is 0.5.
The time-varying safety factor of the most dangerous part of the tunnel lining can be obtained by the above formula, as shown in fig. 4.
5) And establishing a method for predicting the residual life of the tunnel lining.
The lowest limit of lining safety factor is regulated to be 2.4 in road tunnel design specification JTG 3370.1-2018, and when the time-varying safety factor of a tunnel lining structure is lower than 2.4, the lining safety service life is ended, namely the predicted service life of the lining.
Based on the time-varying safety factor formula in step 4 and the curve of FIG. 4To obtain the predicted service life T when the lining safety coefficient is lower than 2.4S。
Using predicted lifetime TSMinus the time T taken into operationTAnd the residual service life T of the lining can be predicted.
In this example TS＝72a，TTThe remaining service life T is 61a, 11 a.
The remaining service life is still long, so the daily maintenance is only needed.
The method considers the influence of tunnel lining carbonization on the effective thickness of the tunnel, the influence of the increase of the operating life of the tunnel on the bearing capacity of lining concrete, the influence of the stress of the tunnel lining on the safety and other three factors, and takes the existing measured data of the tunnel as a correction coefficient, thereby more accurately predicting the service life of the tunnel. The method reduces the cost for long-term operation of the tunnel engineering, ensures the safety of the tunnel engineering, and has good economic benefit and social benefit.
It should be noted that the above-mentioned embodiments are only preferred embodiments of the present invention, and are not intended to limit the scope of the present invention, and all equivalent substitutions or substitutions made on the above-mentioned embodiments are included in the scope of the present invention.

Claims (6)

1. A method for predicting the residual life of a tunnel structure based on lining degradation is characterized by comprising the following steps:
step 1, establishing a tunnel lining concrete strength degradation model according to a concrete corrosion rule in an existing corrosive ion environment;
step 2, determining a development rule of the carbonization depth of the lining concrete and establishing a carbonization depth prediction model according to actual measurement of engineering;
step 3, establishing a tunnel lining finite element calculation model according to the actual condition of the tunnel, and extracting the stress condition of the tunnel lining;
step 4, obtaining a tunnel lining safety coefficient time-varying formula;
and 5, establishing a tunnel lining residual life prediction method.
2. The method for predicting the residual life of the tunnel structure based on the lining deterioration according to claim 1, wherein the tunnel lining concrete strength deterioration model in the step 1 is specifically:
Figure FDA0003482075170000011
wherein, t0Constructing time for supporting; ra0The initial compressive strength of the concrete; ra(t) is lining time-varying compressive strength; r l0The initial tensile strength of the concrete; rl(t) is lining time-varying tensile strength; beta is a constant and represents a lining degradation coefficient, and is selected according to the concrete grade.
3. The method for predicting the residual life of the tunnel structure based on the lining deterioration according to claim 1, wherein the carbonization depth prediction model in the step 2 is as follows:
Figure FDA0003482075170000012
wherein, KmcEngineering carbonization coefficients, and fitting according to the actual measurement result; k is a radical ofco2The influence coefficient of the concentration of the carbon dioxide,
Figure FDA0003482075170000013
t is the annual average temperature (. degree. C.) of the environment; RH is ambient annual average relative humidity (%); f. ofcuThe concrete cube compressive strength (MPa); m iscAnd (4) actually measuring the strength of the tunnel concrete.
4. The method for predicting the remaining life of a tunnel structure based on lining deterioration as claimed in claim 1, wherein the establishment of the tunnel lining model and the extraction of the stress condition in step 3 require the establishment of a finite element model in finite element software according to the tunnel burial depth, the tunnel lining design data, the actual detection result of the tunnel lining and the surrounding rock strength, and calculation, and the extraction of the bending moment M and the axial force N distribution of the key section of the tunnel lining in the post-processing.
5. The method for predicting the residual life of the tunnel structure based on lining degradation according to claim 1, wherein the tunnel lining safety factor time-varying formula in the step 4 is as follows:
Figure FDA0003482075170000014
Wherein, the first and the second end of the pipe are connected with each other,
Figure FDA0003482075170000015
is the concrete stability factor; n is axial force (kN); m is a bending moment (kN.m); h is the thickness (m) of the tunnel lining interface; ra(t) is lining time-varying compressive strength; alpha is alphaXIs the eccentricity influence coefficient over time:
Figure FDA0003482075170000021
e0eccentricity of axial force, e0＝M/N；
b is the width (m) of the section of the tunnel lining; h is the thickness (m) of the tunnel lining interface.
6. The method for predicting the residual life of the tunnel structure based on the lining deterioration according to claim 1, wherein the method for predicting the residual life of the tunnel structure in the step 5 comprises the following steps:
and when the time-varying safety coefficient of the tunnel lining structure is lower than 2.4, the safe service life of the lining is ended, and the service life is the predicted service life of the lining. Using predicted lifetime TSMinus the time T taken into operationTAnd the residual service life T of the lining can be predicted.
CN202210070829.3A 2022-01-21 2022-01-21 Tunnel structure residual life prediction method based on lining degradation Pending CN114722650A (en)

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Cited By (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN115859444A (en) * 2022-12-21 2023-03-28 交通运输部公路科学研究所 Method for predicting road tunnel collapse

Cited By (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN115859444A (en) * 2022-12-21 2023-03-28 交通运输部公路科学研究所 Method for predicting road tunnel collapse
CN115859444B (en) * 2022-12-21 2023-06-16 交通运输部公路科学研究所 Highway tunnel collapse prediction method

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