CN115183965A - Tunnel lining earthquake accumulated damage evaluation method suitable for vibration table test - Google Patents
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Abstract
The invention provides a tunnel lining earthquake accumulated damage evaluation method suitable for a vibrating table test according to the analysis of dynamic strain test data of a vibrating table test lining structure, considering the accumulated damage of elastoplastic deformation characteristics and combining a machine learning means, and the method comprises the following steps: 1) Designing and arranging a tunnel lining dynamic strain sensor, filling a vibration table test model, loading seismic wave test, acquiring tunnel lining dynamic strain data, and drawing a dynamic strain-time curve chart; 2) Fitting by adopting a local weighted regression algorithm to obtain a dynamic strain smooth curve; 3) Drawing a fitted local regression dynamic strain-time curve graph; 4) Extracting a local regression dynamic strain peak value and a residual dynamic strain value from a regression dynamic strain-time curve graph; 5) Calculating the plastic deformation index PEC of the tunnel lining under the action of the earthquake; 6) Drawing a PEC-seismic intensity-lining characteristic part change spectrogram, clarifying a tunnel lining cumulative damage effect, and evaluating a deformation stage of a seismic cumulative damage process.
Description
Technical Field
The invention belongs to the field of tunnel design, particularly relates to a tunnel design safety evaluation method, and more particularly relates to a tunnel lining earthquake accumulated damage evaluation method suitable for a vibration table test.
Background
In the design process of a tunnel anti-seismic structure, when the structure is complex and the existing theoretical calculation cannot be satisfactorily solved, researchers often observe the seismic reaction and the damage form of the structure by means of a vibration table model test so as to evaluate the overall anti-seismic capacity of the structure. The earthquake simulation shaking table is used as key equipment in earthquake engineering research and is mainly applied to structural earthquake resistance tests. The device can be used for simulating the earthquake environment, so that the dynamic characteristics of the engineering structure, the earthquake resistance of the inspection structure and the failure mechanism of the inspection structure under the action of earthquake force can be determined, and designers can be helped to perfect the earthquake design theory and method.
The raw data in the vibration table model test is usually recorded by various sensors (such as a dynamic strain gauge, an acceleration sensor, a displacement sensor, a dynamic soil pressure sensor and the like) arranged on the model structure. The common processing of raw data is as follows: (1) The amplitude-frequency curve is obtained by analyzing the frequency spectrum scanning, and the change conditions of the natural vibration frequency, the damping and the vibration mode of the structure can be known; (2) The acceleration peak value of the measuring point position can be obtained by the acceleration record, and the acceleration amplification factor can be obtained by dividing the acceleration peak value input by the table top; (3) Integrating the acceleration data to obtain a displacement time-course curve of the measuring point, and further obtaining a relative table displacement peak value and an interlayer displacement peak value; (4) Calculating the time when the position is possibly cracked and the deformation condition of the structure by using the strain peak value measured by the dynamic strain gauge; (5) The displacement peak value can also be solved through a displacement time-course curve recorded by a displacement sensor; (6) Solving a relative table top torsion deformation peak value and an interlayer torsion deformation peak value by utilizing an acceleration sensor arranged along the tangential direction; (7) description of experimental phenomena and crack development.
During earthquake, the lining structure mainly generates tensile and compressive damage. Two kinds of damages of different characteristic parts of the tunnel lining section have local effects, and the damage of the lining structure is related to various factors such as terrain conditions, stratum lithology, burial depth, space position and the like. The damage of the lining structure under the action of earthquake is not only related to the maximum deformation, but also related to the accumulated damage caused by the low-cycle fatigue effect generated on the lining structure by the reciprocating action of earthquake. In the process of low cycle fatigue effect, the performance of the concrete material is gradually reduced due to accumulation of plasticity and degradation of rigidity until the concrete material is completely destroyed. However, in the existing data processing process, the accumulated damage factor is not taken into consideration, so that the existing data processing process has the careless omission, and the existing theoretical calculation cannot completely research the internal mechanism of the accumulated damage.
In order to fully reflect the dynamic damage degree of the lining structure, the limitation of indexes (or corresponding internal force indexes) such as peak acceleration (speed and displacement), peak dynamic strain, peak dynamic soil pressure, frequency spectrum characteristics and the like in the traditional acceleration, dynamic strain and dynamic soil pressure analysis method is broken through. The dynamic damage problem of the lining structure is analyzed more comprehensively by considering the accumulated damage of the elastoplastic deformation characteristic according to the dynamic strain test data analysis of the lining structure tested by the vibration table based on the damage realistic state of the seismic engineering lining structure, and a more complete evaluation method is provided, so that the technical problem which needs to be solved in the field is solved urgently.
Disclosure of Invention
The invention aims to provide a tunnel lining earthquake accumulated damage evaluation method suitable for a shaking table test, which considers the accumulated damage of the elastoplastic deformation characteristics of a lining structure and combines a local weighted regression machine learning means, can better describe the mechanical behavior of the tunnel lining structure under the action of reciprocating load and more accurately show the damage process under the action of cyclic loads such as earthquake and the like. The safety state of the lining structure after earthquake can be evaluated quantitatively from a local part (or the whole), and a new way is provided for the fine analysis of the earthquake response process of the lining structure.
Therefore, the invention adopts the following technical scheme:
a tunnel lining earthquake accumulated damage evaluation method suitable for a shaking table test comprises the following steps:
1) Sensor layout: constructing a tunnel primary lining model for testing, designing a layout scheme of dynamic strain sensors according to the structure of the tunnel primary lining model, pasting and laying the dynamic strain sensors on the inner surface and the outer surface of a lining of the tunnel primary lining model, wherein the dynamic strain sensors on the inner surface and the outer surface are in one-to-one correspondence in position, and connecting signals of the dynamic strain sensors to an upper computer after the layout is finished; in order to improve the bonding strength of the dynamic strain sensor, glue can be adopted for bonding; in addition, in order to shorten the test period and reduce the test cost, a plurality of sensors such as an acceleration sensor, a displacement sensor, a soil movement pressure sensor or other sensors for monitoring can be arranged in a single test, and monitoring is carried out to obtain required test data;
2) And (3) seismic testing: placing the tunnel primary lining model in the step 1) on a vibration table, filling a vibration table test model according to test requirements, loading test seismic waves for testing, and transmitting data generated in the test process to an upper computer for storage by a dynamic strain sensor;
3) And (3) performing curve regression treatment: taking test data obtained by a single dynamic strain sensor, and drawing a dynamic strain-time curve chart; then, performing weighted regression calculation on the dynamic strain time course curve data through setting the window length of the data segment by adopting a local weighted regression algorithm to obtain a dynamic strain smooth value corresponding to each time point in the window length; sequentially obtaining smooth values of the dynamic strain in the other windows, and connecting the smooth values to obtain a fitted local regression dynamic strain-time curve corresponding to the test data of the dynamic strain sensor;
then test data obtained by the other dynamic strain sensors are taken, and the step 3) is repeated to obtain a fitted local regression dynamic strain-time curve of each of the other dynamic strain sensors;
the local weighted regression algorithm has the following calculation principle:
one pointxTaking the center, intercepting a section of data with specified length, performing weighted linear regression on the section of data by adopting a weight function, and recording
Is the central value of the regression line, wherein
Are the corresponding values of the fitted curve. For allnA data point can then be madenEach weighted regression line, the connecting line of the central value of each regression line is the data of the sectionLoessCurve line.
Wherein: in local weighted regression, the loss function within each data segment is as follows:
①
in the formula:h θ as a parameterθIs expressed as a vector of
；
Is the abscissa of any data point;
is composed of
The corresponding real value of the data;
is composed of
The expression of the weighted value of (c) is as follows:
②
in the formula:xfeature data for the new prediction sample; parameter(s)tThe change rate of the weight value can be artificially given in advance; then the
There are two important properties:
(1) if it is used
Then, then
(2) If it is not
Then, then
Therefore, for the distance prediction sample dataxThe weight of the near point is larger, and the distance from the predicted sample data is largerxThe far point weight is small.
Therefore, the calculation search is solved through repeated iterationJ(θ)To obtain the targeth θ Then the calculated output value at this time
I.e. the smoothed value obtained by locally weighted regression.
4) Extracting PDS and RS: respectively extracting a local regression dynamic strain peak value PDS and a residual dynamic strain value RS corresponding to each dynamic strain sensor through the fitted local regression dynamic strain-time curve graph obtained in the step 3);
5) And calculating a PEC: respectively calculating the plastic deformation index of each dynamic strain sensor according to the data acquired in the step 4)PEC：
PEC=RS/PDS③
In the formula, plastic deformation indexPEC (Plastic effect coefficient, abbreviated as PEC hereinafter)Is used to indicate the degree of plastic deformation, i.e. the degree of destructive deformation, at any point on the tunnel lining.PEC﹤1，PECThe larger the size, the larger the irrecoverable deformation degree of the tunnel lining is, and the cumulative earthquake damage effect of the tunnelSCFEThe stronger.
After each seismic wave loading, the data signal of the dynamic strain sensor cannot return to the data zero point by itself. That is, the tunnel lining model is considered to have an unrecoverable internal damage deformation, i.e., residual strainRS(Residual Strain, hereinafter abbreviated to abbreviationRS) And accords with the basic theoretical cognitive range of elastoplasticity mechanics of the concrete plasticity damage model. Damage index in reference structure inelastic damage performance evaluation methodD I The basic idea of (2) providing the plastic deformation index of the tunnel lining under the action of earthquakePEC(Plastic effect coeffient, hereinafter abbreviated as abbreviationPEC）。PECAt any point on different characteristic parts of the lining structureRSAnd peak value of dynamic strainPDS(Peak Dynamic string, abbreviated asPDS) Is measured in the measurement. The basic principle is as follows:
as shown in FIG. 2, the concrete specimen has a damaged real state under uniaxial tension, and the real state contains many microcracks and micro-cavities. If the concrete member is assumed to be under a tensile force ofTCross sectional area ofAWhen there is Cauchy stress
。
As shown in FIG. 3, the concrete specimen is in the damage-free hypothetical state under the uniaxial tension stress state if the cross-sectional area of the concrete member
Is thatAThe residual effective area of the microcracks and the micro-cavities is reduced, and the effective stress tensor is obtained
The expression is as follows:
introduction of Damage parameters
⑤
Wherein:
indicating micro-cracks in concrete membersAnd cross-sectional area of micro-cavern damage;
Aa cross-sectional area representing a damaged state of a real concrete member;
according to the injury parameter concept of the formula (5),
microcrack and microvoid damage, i.e., residual strain as referred to in equation (3)RS，ANamely the dynamic strain peak mentioned in equation (3)PDSDefining the plastic deformation index of the tunnel lining under the action of earthquakePEC。
6) Drawing a PEC change spectrogram: using the position of the dynamic strain sensor as a horizontal axis, the seismic intensity as a vertical axis and the plastic deformation indexPECIs a vertical shaft; respectively drawing a PEC-seismic intensity-lining characteristic part change spectrogram of the dynamic strain sensor on the inner surface of the tunnel lining and a PEC-seismic intensity-lining characteristic part change spectrogram of the dynamic strain sensor on the outer surface of the tunnel lining; and evaluating the deformation stage of the tunnel lining earthquake cumulative damage process through the PEC change spectrogram.
The invention breaks through the limitations of indexes (or corresponding internal force indexes) such as peak acceleration (speed, displacement), peak dynamic strain, peak dynamic soil pressure, frequency spectrum characteristics and the like in the traditional acceleration, dynamic strain and dynamic soil pressure analysis method, and innovatively provides a tunnel lining earthquake accumulated damage (PEC) evaluation method suitable for a vibration table test based on the practical damage state of the lining structure of the seismic engineering according to the dynamic strain test data analysis of the vibration table test lining structure and the combination of machine learning means and the accumulated damage of the elastoplastic deformation characteristic. By accurately extracting the local regression dynamic strain peak value and the residual dynamic strain value and based on the concrete elastoplasticity damage basic principle, the earthquake-action tunnel lining plastic deformation index PEC is provided, and the tunnel lining earthquake accumulated damage can be quantitatively evaluated.
Drawings
FIG. 1 is a block flow diagram of a cumulative damage assessment method of the present invention;
FIG. 2 shows the real state of damage of a concrete specimen under uniaxial tension stress;
FIG. 3 is a non-damage hypothetical state of a concrete specimen under uniaxial tension stress;
FIG. 4 is a three-dimensional view of the arrangement of the transducers of the vibrating table model in embodiment 1;
FIG. 5 is a sectional view of a dynamic strain sensor arrangement in a tunnel lining model in embodiment 1;
FIG. 6 is a graph of dynamic strain versus time and a dynamic strain smoothing curve in example 1;
FIG. 7 is a PEC-seismic intensity-lining feature change spectrum of a dynamic strain sensor on the inner surface of a tunnel lining in example 1;
FIG. 8 is a PEC-seismic intensity-lining feature variation spectrum of a dynamic strain sensor for the outer surface of a tunnel lining in example 1;
FIG. 9 is a three-dimensional view of the arrangement of the transducers of the vibrating table model in embodiment 2;
FIG. 10 is a sectional view of the arrangement of dynamic strain sensors of the tunnel lining model in example 2;
FIG. 11 is a graph of the dynamic strain versus time and a dynamic strain smoothing curve in example 2;
FIG. 12 is a PEC-seismic intensity-lining feature change spectrum of a dynamic strain sensor on the inner surface of a tunnel lining in example 2;
figure 13 is a PEC-seismic intensity-lining feature change spectrum of the tunnel lining outer surface dynamic strain sensor of example 2.
Detailed Description
The invention is further illustrated by the following specific embodiments in conjunction with the attached drawing figures:
example 1
Earthquake accumulated damage of tunnel transverse main sliding surface space power coupling systemPECEvaluation of
(1) In the case, a vibration table test method is adopted to research the dynamic response of a tunnel structure traversing a main sliding surface under the action of an earthquake, the layout schemes of tunnel lining dynamic strain sensors and the like are designed, the dynamic strain sensors are arranged according to the design schemes, 502 glue is used for adhering the dynamic strain sensors to the inner surface and the outer surface of a tunnel lining model, and the design of the vibration table test model and the layout of sensor elements are shown in figures 4 and 5.
(2) And (3) filling a vibrating table test model according to the sensor layout scheme in the step (1), loading seismic wave test, and acquiring dynamic strain monitoring data of the tunnel lining characteristic part tested by the vibrating table.
(3) And (3) taking test data obtained by a single dynamic strain sensor, drawing a dynamic strain-time curve graph, and fitting by adopting a local weighted regression algorithm through a formula (1) to obtain a dynamic strain smooth curve. And repeating the steps, and sequentially obtaining the fitted local regression dynamic strain-time curves corresponding to the test data of the rest dynamic strain sensors.
(4) Accurately extracting the local regression dynamic strain peak value (max _ count) of each characteristic part of the tunnel lining by fitting a local regression dynamic strain-time curve graphPDS|) And residual dynamic strain value (max $)RS|) As shown in fig. 6.
(5) Accurately extracting a local regression dynamic strain peak value and a residual dynamic strain value, and calculating the plastic deformation index of the tunnel lining under the action of the earthquake through a formula (3)PEC. Respectively drawing a PEC-seismic intensity-lining characteristic part change spectrogram of the tunnel lining inner surface dynamic strain sensor (shown in figure 7) and a PEC-seismic intensity-lining characteristic part change spectrogram of the tunnel lining outer surface dynamic strain sensor (shown in figure 8).
As shown in FIGS. 7 and 8, in the 0.05-0.15 g stage,PECthe slow increase indicates that the plastic deformation of the tunnel lining is small and in the elastic deformation phase. In the stage of 0.15-0.3 g,PECthe plastic deformation degree of the tunnel lining is gradually increased by a certain degree, and the tunnel lining begins to enter the elastoplasticity stage.PECThe plastic deformation of the tunnel lining is increased greatly at the stage of 0.3-0.6 g, which indicates that the plastic deformation of the tunnel lining is increased rapidly and the tunnel lining begins to enter the plastic deformation stage.PECThe deformation stage of the tunnel lining structure is fully considered, so that the dynamic damage of the tunnel lining under the earthquake excitation has obvious cumulative effect. On the basis of fully considering the plastic deformation characteristic of the tunnel lining, the cumulative seismic effect of the tunnel lining mainly comprises the following three stages: progressive destructive effect (slow deformation) stage (<0.15 g), an initial effect (elastoplastic deformation) stage (0.15-0.3 g), and a plastic effect (plastic deformation) stage (0.3-0.6 g).
Example 2
Earthquake accumulated damage of tunnel transverse traction section sliding surface space power coupling systemPECEvaluation of
(1) In the case, a vibration table test method is adopted to research the dynamic response of a tunnel structure traversing a traction section slip surface under the action of an earthquake, the layout schemes of tunnel lining dynamic strain sensors and the like are designed, the dynamic strain sensors are arranged according to the design schemes, 502 glue is used for adhering the dynamic strain sensors to the inner surface and the outer surface of a tunnel lining model, and the design of the vibration table test model and the layout of sensor elements are shown in fig. 9 and 10.
(2) Filling a vibration table test model according to the sensor layout scheme in the step (1), loading seismic wave test, and obtaining dynamic strain monitoring data of the tunnel lining characteristic part tested by the vibration table.
(3) And (3) taking test data obtained by a single dynamic strain sensor, drawing a dynamic strain-time curve graph, and fitting by adopting a local weighted regression algorithm through a formula (1) to obtain a dynamic strain smooth curve. And repeating the steps, and sequentially obtaining the fitted local regression dynamic strain-time curves corresponding to the test data of the rest dynamic strain sensors.
(4) By fitting the local regression dynamic strain-time curve graph, the local regression dynamic strain peak value (max & lty & gt) of each characteristic part of the tunnel lining is accurately extractedPDS|) And residual dynamic strain value (max $)RS|) As shown in fig. 11.
(5) Accurately extracting a local regression dynamic strain peak value and a residual dynamic strain value, and calculating the plastic deformation index of the tunnel lining under the action of the earthquake through a formula (3)PEC. Respectively drawing a PEC-seismic intensity-lining characteristic part change spectrogram of the tunnel lining inner surface dynamic strain sensor (shown in figure 12) and a PEC-seismic intensity-lining characteristic part change spectrogram of the tunnel lining outer surface dynamic strain sensor (shown in figure 13).
As shown in FIGS. 12 and 13, in the 0.05-0.15 g stage,PECthe approximately linear increase indicates that the plastic deformation of the tunnel lining is small and is basically in the elastic deformation stage. In the stage of 0.15-0.3 g,PEChas a certain degree of increase, which indicates the plastic deformation degree of the tunnel liningGradually increasing and beginning to enter the elastic-plastic deformation stage.PECThe plastic deformation of the tunnel lining is greatly increased in the 0.3-0.4 g stage, which indicates that the plastic deformation of the tunnel lining is rapidly increased, and the tunnel lining begins to enter the plastic deformation stage.PECThe deformation stage of the tunnel lining structure is fully considered, so that the dynamic damage of the tunnel lining under the seismic excitation has obvious cumulative effect. On the basis of fully considering the plastic deformation characteristic of the tunnel lining, the accumulated seismic effect of the tunnel lining mainly comprises three stages of an elastic deformation stage: (<0.15 g), an elastoplastic deformation stage (0.15-0.3 g), and a plastic deformation stage (0.3-0.4 g).
Claims (1)
1. A tunnel lining earthquake accumulated damage evaluation method suitable for a shaking table test is characterized by comprising the following steps:
1) Sensor layout: constructing a tunnel primary lining model for testing, designing a layout scheme of dynamic strain sensors according to the structure of the tunnel primary lining model, pasting and laying the dynamic strain sensors on the inner surface and the outer surface of a lining of the tunnel primary lining model, wherein the dynamic strain sensors on the inner surface and the outer surface are in one-to-one correspondence in position, and connecting signals of the dynamic strain sensors to an upper computer after the layout is finished;
2) And (3) seismic testing: placing the tunnel primary lining model obtained in the step 1) on a vibration table, and filling a vibration table test model according to test requirements; loading test seismic waves for testing, and acquiring data generated in the test process by a dynamic strain sensor and transmitting the data to an upper computer for storage;
3) And (3) curve regression treatment: test data obtained by a single dynamic strain sensor is taken, and a dynamic strain-time curve graph is drawn; then, a local weighted regression algorithm is adopted, the dynamic strain-time curve graph is calculated to obtain a complete dynamic strain smooth curve, and a fitting local regression dynamic strain-time curve graph is drawn;
then test data obtained by the other dynamic strain sensors are taken, and a fitted local regression dynamic strain-time curve graph corresponding to the test data of the other dynamic strain sensors is obtained in sequence;
4) Extracting PDS and RS: respectively extracting a local regression dynamic strain peak value PDS and a residual dynamic strain value RS corresponding to each dynamic strain sensor through the fitted local regression dynamic strain-time curve graph obtained in the step 3);
5) And calculating a PEC: respectively calculating the plastic deformation index of each dynamic strain sensor according to the data obtained in the step 4)PEC：
PEC=RS/PDS
6) Drawing a PEC change spectrogram: using the position of the dynamic strain sensor as a horizontal axis, the seismic intensity as a vertical axis and the plastic deformation indexPECIs a vertical shaft; respectively drawing a PEC-seismic intensity-lining characteristic part change spectrogram of a dynamic strain sensor on the inner surface of the tunnel lining and a PEC-seismic intensity-lining characteristic part change spectrogram of a dynamic strain sensor on the outer surface of the tunnel lining; and evaluating the deformation stage of the tunnel lining earthquake cumulative damage process through the PEC change spectrogram.
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