CN114117753B - Probability earthquake side slope sliding risk analysis method and device based on vulnerability - Google Patents

Probability earthquake side slope sliding risk analysis method and device based on vulnerability Download PDF

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CN114117753B
CN114117753B CN202111330489.5A CN202111330489A CN114117753B CN 114117753 B CN114117753 B CN 114117753B CN 202111330489 A CN202111330489 A CN 202111330489A CN 114117753 B CN114117753 B CN 114117753B
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杜文琪
王伟
李典庆
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Wuhan University WHU
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Abstract

The invention provides a probability earthquake side slope sliding risk analysis method and device based on vulnerability, wherein the method comprises the following steps: step 1, selecting and determining engineering demand parameters and earthquake intensity parameters, and determining analysis precision and analysis range of the engineering demand parameters and the earthquake intensity parameters; step 2, determining a seismic risk curve of the site where the side slope is located, and selecting seismic records with consistent risk; step 3, determining statistical characteristics of rock-soil body parameters, and sampling to obtain a sample; step 4, establishing a slope numerical model, sequentially inputting seismic records for each group of samples, and performing power calculation to obtain N data pairs; step 5, obtaining a vulnerability model of each group of rock-soil parameter samples without considering uncertainty of the rock-soil parameters in different EDP sizes through vulnerability analysis according to the data pairs; step 6, obtaining a vulnerability model considering uncertainty of the rock-soil parameters through simulation; and 7, obtaining the seismic displacement risk curve considering the uncertainty of the rock-soil mass parameters according to the seismic risk curve and the vulnerability model.

Description

Probability earthquake side slope sliding risk analysis method and device based on vulnerability
Technical Field
The invention belongs to the technical field of probability seismic slope slip risk analysis, and particularly relates to a probability seismic slope slip risk analysis method and device based on vulnerability.
Background
The probability earthquake slope sliding hazard analysis can be used for predicting the sliding displacement of the slope caused by earthquake and the annual average exceeding probability, and has important guiding significance for slope earthquake-resistant design, earthquake risk assessment and the like. In order to obtain the sliding displacement of the side slope caused by the earthquake, a displacement prediction model is generally adopted. And the mean value and standard deviation of the slope displacement can be obtained rapidly through a displacement prediction model by giving the site parameters and the seismic intensity parameters. However, since the displacement prediction model is an empirical formula based on seismic wave analysis of a large number of different sites, a large error must exist in the displacement prediction result for a specific slope in a certain site. Meanwhile, when a displacement prediction model is constructed, a scholars generally calculate the slope displacement of a given seismic wave by adopting a Newmark type method. Along with the continuous progress of computer technology, various numerical simulation methods considering the static/dynamic stress-strain relation of materials are increasingly and widely applied to the calculation of slope displacement caused by earthquakes, and the calculation precision is higher than that of a Newmark type method. Therefore, obtaining the displacement caused by the earthquake by adopting a proper method is important to the risk analysis of a certain appointed slope.
In addition, uncertainty of the strength and rigidity parameters of the slope rock-soil mass is one of main factors influencing the risk of the slope displacement. At present, a learner generally adopts a logic tree method to quantify the influence of the uncertainty on the slope displacement risk, and the specific method comprises the following steps: firstly, distributing uncertainty sources and weights through a logic tree method, and calculating possible values and corresponding weights of all yield accelerations; then, calculating displacement dangerous curves corresponding to all yield acceleration values; finally, a displacement risk curve considering the uncertainty of the strength and the rigidity is obtained in a weighted average mode. However, the determination of node weights, branch numbers, etc. in the logical tree method is too dependent on the engineering experience of the analyst. Therefore, how to objectively reflect the influence of uncertainty of the slope rock-soil body parameters on the slope slip risk is a current problem to be solved urgently.
Disclosure of Invention
The invention aims to solve the problems, and aims to provide a probability earthquake side slope sliding risk analysis method and device based on vulnerability, which can objectively and reasonably reflect the influence of uncertainty of side slope rock-soil body parameters on the side slope sliding risk.
In order to achieve the above object, the present invention adopts the following scheme:
< method >
The invention provides a probability earthquake side slope sliding risk analysis method based on vulnerability, which is characterized by comprising the following steps of:
step 1, acquiring historical data of a region where a side slope is located, selecting and determining engineering demand parameters EDP and earthquake intensity parameters IM according to specifications or existing researches, and determining analysis precision and range of the engineering demand parameters EDP and the earthquake intensity parameters IM; the designated precision and range should ensure that the error of the final slope sliding displacement dangerous curve is within the acceptable range of engineering or research;
step 2, determining a seismic risk curve of the site where the side slope is located, and selecting seismic records with consistent risk;
step 3, determining statistical characteristics of rock-soil body parameters, and obtaining 2 by using a central composite design method (CCD) sampling K +2K+1 groups of geotechnical parameter samples, K being the number of uncertainty parameters;
step 4, establishing a slope numerical model, sequentially inputting N seismic records for each group of rock-soil parameter samples, and performing power calculation for N times to obtain N [ EDP, IM ] data pairs;
step 5, obtaining a vulnerability model of each group of rock and soil parameter samples without considering uncertainty of the rock and soil parameters in different EDP sizes through vulnerability analysis according to the [ EDP, IM ] data pairs;
step 6, obtaining a vulnerability model considering uncertainty of rock-soil parameters through a response surface method and Monte Carlo simulation;
and 7, obtaining the seismic displacement risk curve considering the uncertainty of the rock-soil mass parameters through numerical integration according to the seismic risk curve in the step 2 and the vulnerability model in the step 6.
Preferably, the method for analyzing the probability earthquake side slope sliding risk based on vulnerability, provided by the invention, comprises the following substeps:
step 2.1, obtaining a seismic risk curve of the field through probability seismic risk analysis PSHA;
step 2.2 according to the seismic risk curve, the depolymerization result of PSHA and the shear wave velocity weighted average Vs of the rock and soil layer within the depth range of 30 meters of the field 30 And selecting seismic records with consistent risk.
Preferably, the probability earthquake side slope sliding risk analysis method based on vulnerability provided by the invention can also have the following characteristics: in step 2.2:
(1) If the vulnerability analysis method is a cloud analysis method, firstly, calculating the average moment magnitude of the depolymerized seismic event according to the depolymerization result of the PSHA
Figure GDA0004233263380000021
And average source distance>
Figure GDA0004233263380000022
Then, randomly selecting N seismic records from a seismic record database to ensure Vs of each seismic record source site and analysis site 30 Concordance (same kind of field)Earth) while ensuring that the average moment and average source distance of the N seismic records are respectively equal to +.>
Figure GDA0004233263380000023
And->
Figure GDA0004233263380000024
Consistent (relative error should be less than 10%).
(2) If the vulnerability analysis method is a multi-strip method, firstly, dividing S risk levels on a seismic risk curve; then, for a certain risk level, according to the mean value and variance of the level IM, Q seismic records are selected from a seismic record database by a method such as a Conditional Spectrometry (CS) method or a generalized conditional intensity parameter method (GCIM) method, and Vs of a source site and an analysis site of each seismic record are ensured 30 Consistent; finally, the above process is repeated for each risk level, for a total of N (n=s×q) seismic records.
Preferably, the probability earthquake side slope sliding risk analysis method based on vulnerability provided by the invention can also have the following characteristics: in step 2.2, if the vulnerability analysis method is a cloud analysis method, N should be greater than 80; if the vulnerability analysis method is a multi-band method, S should be greater than 10, Q should be greater than 30, and N should be greater than 300.
Preferably, the probability earthquake side slope sliding risk analysis method based on vulnerability provided by the invention can also have the following characteristics: step 6 further comprises the sub-steps of:
step 6.1, specifying the size of EDP, and setting the logarithm ln (eta) of the seismic median of the vulnerability model considering the uncertainty of the parameters of the rock and soil mass IM,Tot ) Obtaining undetermined coefficients of the secondary response surface function by a least square method according to the anti-seismic median value of the vulnerability model corresponding to each group of rock-soil parameter samples;
step 6.2, randomly generating 10000 groups of rock and soil parameter samples through Monte Carlo simulation, and calculating the earthquake-resistant median value of 10000 corresponding vulnerability models according to the step 6.1;
step 6.3, specifying the IM size, setting the dispersion of the vulnerability models of 10000 groups of rock-soil parameter samples to be equal to the dispersion of the vulnerability models of the average value samples in the step 5, and solving to obtain 10000 vulnerability probabilities according to the earthquake-resistant median value of the vulnerability models obtained in the step 6.2;
step 6.4, calculating 10000 expected vulnerability probability, namely taking the value of the vulnerability model considering the uncertainty of the rock-soil parameters in specifying the EDP and IM sizes;
step 6.5, repeating the step 6.3 and the step 6.4 until values in all IM ranges are taken, so as to obtain a vulnerability curve considering uncertainty of rock-soil parameters when the size of the EDP is specified;
step 6.6 fitting the vulnerability curve in step 6.5 with a lognormal cumulative distribution curve, and solving the median eta of the vulnerability model IM,Tot And dispersion beta IM,Tot ；
Step 6.7 repeating the steps 6.1 to 6.6 until values in all EDP ranges are taken, thereby obtaining the earthquake-resistant median eta of the vulnerable model considering the uncertainty of the rock-soil body parameters in different EDP sizes IM,Tot And dispersion beta IM,Tot 。
< device >
The invention provides a probability earthquake side slope sliding risk analysis device based on vulnerability, which is characterized by comprising the following components:
a parameter determining part for obtaining the history data of the area where the slope is located, determining engineering demand parameters EDP and earthquake intensity parameters IM, and determining the analysis precision and range of the engineering demand parameters EDP and the earthquake intensity parameters IM;
a curve determination and selection part for determining a seismic risk curve of a place where the slope is located and selecting seismic records with consistent risk;
a sampling part for determining statistical characteristics of the rock-soil body parameters and obtaining 2 by sampling with a central composite design method K +2K+1 groups of geotechnical parameter samples, K being the number of uncertainty parameters;
a numerical model establishing and calculating part for establishing a slope numerical model, sequentially inputting N seismic records for each group of rock-soil parameter samples, and performing power calculation for N times to obtain N [ EDP, IM ] data pairs;
the vulnerability model preliminary acquisition part is used for acquiring a vulnerability model of which each group of rock and soil parameter samples does not consider uncertainty of the rock and soil parameters when the rock and soil parameters are different in size through vulnerability analysis according to the [ EDP, IM ] data pair;
the final obtaining part of the vulnerability model obtains the vulnerability model considering the uncertainty of the rock-soil parameters through a response surface method and Monte Carlo simulation;
the seismic displacement risk curve obtaining part is used for obtaining the seismic displacement risk curve considering the uncertainty of the rock-soil body parameters through numerical integration according to the seismic risk curve determined by the curve determination selecting part and the vulnerability model finally obtained by the vulnerability model obtaining part; and
the control part is in communication connection with the parameter determining part, the curve determining and selecting part, the sampling part, the numerical model establishing and calculating part, the vulnerability model preliminary obtaining part, the vulnerability model final obtaining part and the earthquake displacement dangerous curve obtaining part, and controls the operation of the parameter determining part, the curve determining and selecting part, the sampling part, the numerical model establishing and calculating part, the vulnerability model preliminary obtaining part, the vulnerability model final obtaining part and the earthquake displacement dangerous curve obtaining part.
Preferably, the probability earthquake side slope sliding risk analysis device based on vulnerability provided by the invention further comprises: the input display part is communicated with the parameter determining part, the curve determining and selecting part, the sampling part, the numerical model establishing and calculating part, the vulnerability model preliminary obtaining part, the vulnerability model final obtaining part, the earthquake displacement danger curve obtaining part and the control part, and displays corresponding information according to the operation instruction input by a user.
Preferably, the probability earthquake side slope sliding risk analysis device based on vulnerability provided by the invention can also have the following characteristics: the input display part can display prompt information to enable an operator to select and determine engineering demand parameters EDP and earthquake intensity parameters IM, and determine analysis precision and analysis range of the engineering demand parameters EDP and the earthquake intensity parameters IM; the input display part can also display the determined earthquake risk curve and the earthquake record with consistent risk according to the control instruction, can display the sampled rock-soil parameter samples in a list form, correspondingly display the established slope numerical model and N [ EDP, IM ] data pairs obtained by calculation, display the obtained vulnerability model, and also display the obtained earthquake displacement risk curve considering the uncertainty of the rock-soil mass parameters in a graph form.
Effects and effects of the invention
1. The method is more reasonable
The traditional probability earthquake slope sliding risk analysis method based on the displacement prediction model is high in calculation speed, low in pertinence and rough in result, and is only suitable for the preliminary analysis of the sliding risk of a large-scale and multi-slope. The method can reasonably analyze the earthquake slippage risk aiming at the concrete side slope, improves the accuracy of the side slope displacement by selecting the difference between earthquake wave salient fields with consistent risk, quantifies the earthquake resistance of the appointed side slope by the vulnerability analysis, and is suitable for the side slope needing important analysis in engineering practice.
2. Has strong applicability
The method organically links the vulnerability of the earthquake slope with the displacement risk, expands the uncertainty of the rock-soil parameters in the displacement risk analysis, has clear and easily understood concept, can be used for designating scalar intensity parameters and vector intensity parameters, and is applicable to any type of slope regardless of the depth of potential sliding belts.
3. The uncertainty propagation mechanism is clear
The method takes the vulnerability model as a medium, firstly determines the influence of the uncertainty of the rock-soil body parameters on the vulnerability model, and then quantifies the influence of the uncertainty of the rock-soil body parameters on the displacement risk; based on the thought, the invention clearly shows the propagation path of the uncertainty of the rock-soil mass parameters, namely, the uncertainty firstly influences the earthquake displacement, further influences the vulnerability and finally transmits to the displacement danger.
In conclusion, the method is particularly suitable for reasonably analyzing the earthquake slip risk of the appointed side slope, can effectively quantify the influence of uncertainty of rock and soil parameters, and provides a new thought for analyzing the earthquake side slope slip displacement risk.
Drawings
FIG. 1 is a flow chart of a probabilistic earthquake side slope slip risk analysis method based on vulnerability according to the invention;
FIG. 2 is a graph of seismic PGA risk according to an embodiment of the present invention;
FIG. 3 is a scatter plot of seismic records in an embodiment of the invention;
FIG. 4 is a numerical model of a side slope in an embodiment of the invention;
FIG. 5 is a flow chart of a vulnerability model solving process taking into account uncertainty of rock-soil mass parameters according to the present invention;
FIG. 6 is a vulnerability curve solving process considering the uncertainty of the geotechnical parameters when Disp is 15.0cm in the embodiment of the invention; wherein, fig. 6 (a) is a frequency histogram of vulnerability probability, and fig. 6 (b) is a vulnerability graph of the frequency histogram of vulnerability probability considering uncertainty of rock-soil mass parameters;
FIG. 7 is a graph comparing vulnerability curves in an embodiment of the present invention;
FIG. 8 is a graph comparing the risk curves of sliding on a side slope in an embodiment of the present invention.
Detailed Description
The following describes in detail the specific embodiments of the probability earthquake side slope sliding risk analysis method and device based on vulnerability according to the present invention with reference to the accompanying drawings.
< example >
As shown in fig. 1, the probability earthquake side slope sliding risk analysis method based on vulnerability provided by the implementation comprises the following steps:
step 1, acquiring historical data of an area where a side slope is located, taking total displacement Disp of a slope top monitoring point as engineering demand parameter EDP and peak acceleration PGA as seismic intensity parameter IM according to European standard SYNER-G; the wider the analysis range of EDP and IM is, the higher the accuracy is, the smaller the error of the analysis result of the vulnerability and the sliding danger of the subsequent slope is, so after the calculation time is comprehensively considered, the range and the accuracy of PGA are respectively set to (0.0,5.0) g and 0.001g, and the accuracy of Disp is set to 0.1cm; in addition, SYNER-G defines a total displacement greater than 40cm as a slope destabilization failure, so the analytical range of Disp is (0.0, 40.0) cm.
Step 2, as shown in FIG. 2, utilizing a geologic featureSurvey office Web tool (https:// earthquatke. Usgs. Gov/hazards/interactive) draws a class C site (slope site) (Vs) 30 >537 m/s) seismic PGA risk curve with PGA on the abscissa and PGA on the ordinate, the annual average overrun probability lambda PGA The method comprises the steps of carrying out a first treatment on the surface of the Meanwhile, the site average moment magnitude can be known according to the depolymerization result of the Web tool
Figure GDA0004233263380000061
Average source distance->
Figure GDA0004233263380000062
Since vulnerability analysis of the embodiment will adopt cloud analysis, the site Vs is used 30 、/>
Figure GDA0004233263380000063
And->
Figure GDA0004233263380000064
For constraint, 100 seismic records are selected from the NGA-West2 database as input seismic vibrations for subsequent power calculation, and the moment and source distance of each seismic record are shown in fig. 3. Securing Vs for each seismic record source site 30 、/>
Figure GDA0004233263380000065
And->
Figure GDA0004233263380000066
Is consistent with the side slope field.
Step 3, a certain homogeneous clay slope is positioned on the C-type field in the step 2, physical and mechanical parameters of the soil body of the side slope are shown in the following table 1, wherein 3 parameters such as cohesive force, internal friction angle and initial shear modulus are random variables and obey logarithmic normal distribution; and sampling by using a central composite design method to obtain 8 bi-level factor samples, 6 axial samples and 1 central point sample, wherein the total is 15 groups of rock-soil parameter samples.
TABLE 1 physical and mechanical parameters of clay layers
Figure GDA0004233263380000067
Figure GDA0004233263380000071
Step 4, establishing a soil slope numerical model in finite difference software FLAC, wherein the slope height and the slope ratio of the soil slope are respectively 10m and 1:1.5 as shown in FIG. 4; and for each group of rock and soil parameter samples, 100 seismic records are sequentially input, 100 power calculations are carried out, and 100 [ Disp, PGA ] data pairs are obtained.
Step 5, according to 100 [ Disp, PGA ] corresponding to each group of rock and soil parameter samples]Data pairs, and obtaining an earthquake-resistant median eta of vulnerability models of each group of rock and soil parameter samples with different Disp sizes without considering uncertainty of rock and soil parameters through a cloud analysis method IM,RTR And dispersion beta IM,RTR :
Figure GDA0004233263380000072
In the formula, P [ Disp|PGA]The probability is vulnerability probability, which indicates the probability that the slope displacement is larger than the designated Disp given PGA; Φ () represents the cumulative function of the standard normal distribution. Taking the center point sample (average sample) as an example, η is when Disp is 1.0, 5.0 and 15.0cm IM,RTR 0.147, 0.334 and 0.525g, beta IM,RTR Both 0.211.
Step 6, obtaining a vulnerability model considering uncertainty of parameters of a rock-soil body through a response surface method and Monte Carlo simulation, wherein a solving flow is shown in fig. 5, and the specific substeps are as follows:
step 6.1, designating the size of Disp, and setting the logarithm ln (eta) of the seismic median of the vulnerability model considering the uncertainty of the rock-soil parameters IM,Tot ) Obtaining undetermined coefficients of the secondary response surface function by a least square method according to the anti-seismic median value of the vulnerability model corresponding to each group of rock-soil parameter samples; taking disp=15.0 cm as an example, the vulnerability model is the logarithm of the median earthquake resistance
Figure GDA0004233263380000073
The following quadratic polynomial predictions can be used:
Figure GDA0004233263380000074
in xi k For the position of the random variable in the standard normal space, k is equal to 1, 2 and 3, which in turn correspond to cohesion, internal friction angle and initial shear modulus.
Step 6.2, randomly generating 10000 groups of rock and soil parameter samples through Monte Carlo simulation, and solving the earthquake-resistant median value of 10000 vulnerability models according to the step 6.1.
Step 6.3, the size of the PGA is specified, and the dispersion of the vulnerability models of 10000 groups of rock and soil parameter samples is equal to the dispersion of the vulnerability models of the average value samples in the step 5, namely beta IM,Tot Always equal to 0.211, and according to the earthquake-resistant median value of the vulnerability model obtained in the step 6.2, 10000 vulnerability probabilities are obtained by solving; taking pga=0.600 g as an example, the frequency histogram of 10000 vulnerability probabilities at this time is shown in fig. 6 (a).
Step 6.4 calculates 10000 vulnerability probability expectation, namely when considering uncertainty of rock and soil parameters, the probability that the displacement of a slope top monitoring point is larger than 15.0cm is 0.610 given pga=0.600 g, as shown in fig. 6 (a).
Step 6.5 repeating steps 6.3 and 6.4 until all possible values of PGA in the range of (0.0,5.0) g are taken, thereby obtaining a vulnerability curve considering uncertainty of parameters of the rock-soil mass when disp=15.0 cm, see fig. 6 (b).
Step 6.6 fitting the vulnerability curve in step 6.5 with a lognormal cumulative distribution curve, thereby solving the median earthquake resistance η of the vulnerability model considering the uncertainty of the geotechnical parameters when disp=15.0 cm is obtained IM,Tot =0.508 g and dispersion β IM,Tot ＝0.259。
And 6.7, repeating the steps 6.1 to 6.6 until all possible values of the Disp within the range of (0.0, 40.0) cm are taken, so as to obtain the earthquake-resistant median value and the dispersion of the vulnerable model which take the uncertainty of the rock-soil body parameters into consideration when different Disp sizes are obtained.
FIG. 7 compares vulnerability curves before and after considering the uncertainty of the rock-soil mass parameters when Disp is 1.0cm, 5.0cm and 15.0cm, respectively, with Tot and RTR indicating the consideration and non-consideration of the rock-soil mass parameter uncertainty, respectively. It can be seen that, considering the uncertainty of the rock-soil mass parameters, all vulnerability curves become more dwarf and fatter, and the dispersion is increased; meanwhile, the earthquake-resistant median value is also deviated to different degrees.
Step 7, solving a displacement risk curve through the following integral according to the earthquake risk curve and the vulnerability model:
Figure GDA0004233263380000081
wherein lambda is Disp The annual average override probability for Disp. Fig. 8 compares displacement risk curves before and after considering the uncertainty of the rock-soil mass parameters, and Tot and RTR represent the consideration and non-consideration of the rock-soil mass parameter uncertainty, respectively. It can be seen that, considering uncertainty in the parameters of the rock and soil mass, the risk of small sliding displacements induced by earthquakes is slightly reduced, for example, the probability of sliding displacement exceeding 1.0cm per year is reduced by 1.27 x 10 -2 Decrease by 1.23 x 10 -2 Reduced by about 3.2%; the risk of earthquake-induced large sliding displacements is significantly increased, for example, the probability of sliding displacement exceeding 15.0cm per year is increased from 1.41×10 -3 Reduced by 1.84 x 10 -3 Raised by about 30.3%.
The example shows that the probability earthquake side slope sliding risk analysis method based on vulnerability can more reasonably analyze the earthquake sliding risk of a certain appointed side slope; meanwhile, the method can take the vulnerability model as a medium to consider the influence of the uncertainty of the rock-soil body parameters on the danger of the earthquake slope, and clearly demonstrate the propagation process of the uncertainty.
Further, the embodiment also provides a probability seismic slope slip risk analysis device capable of automatically realizing the method, which comprises a parameter determination part, a curve determination and selection part, a sampling part, a numerical model establishment calculation part, a vulnerability model preliminary acquisition part, a vulnerability model final acquisition part, a seismic displacement risk curve acquisition part, an input display part and a control part.
The parameter determining part executes the content described in the step 1, acquires the history data of the region where the side slope is located, determines the engineering demand parameter EDP and the seismic intensity parameter IM, and determines the analysis precision and the analysis range thereof.
The curve determination and selection part executes the description of the step 2, determines the seismic risk curve of the site where the slope is located, and selects seismic records with consistent risk.
The sampling part executes the content described in the step 3, determines the statistical characteristics of the rock-soil body parameters, and samples and obtains 2 by using a central composite design method K +2K+1 groups of geotechnical parameter samples, K is the number of uncertainty parameters.
The numerical model establishment calculation part executes the content described in the step 4, establishes a slope numerical model, sequentially inputs N seismic records for each group of rock-soil parameter samples, performs N times of power calculation, and obtains N [ EDP, IM ] data pairs;
the vulnerability model preliminary obtaining part executes the content described in the step 5, and obtains a vulnerability model of each group of rock and soil parameter samples without considering uncertainty of the rock and soil parameters in different EDP sizes through vulnerability analysis according to the [ EDP, IM ] data pair;
the vulnerability model final obtaining part executes the content described in the step 6, and obtains the vulnerability model considering the uncertainty of the rock-soil parameters through a response surface method and Monte Carlo simulation.
The seismic displacement risk curve obtaining part executes the content described in the step 7, and the seismic displacement risk curve considering the uncertainty of the rock-soil body parameter is obtained through numerical integration according to the seismic risk curve determined by the curve determination selecting part and the vulnerability model finally obtained by the vulnerability model obtaining part.
The input display part is communicated with the parameter determining part, the curve determining and selecting part, the sampling part, the numerical model establishing and calculating part, the vulnerability model preliminary obtaining part, the vulnerability model final obtaining part, the earthquake displacement danger curve obtaining part and the control part, and displays corresponding information according to the operation instruction input by a user. The input display part can display prompt information to enable an operator to select and determine engineering demand parameters EDP and earthquake intensity parameters IM, and determine analysis precision and analysis range of the engineering demand parameters EDP and the earthquake intensity parameters IM; the input display part can also display the determined earthquake risk curve and the earthquake record with consistent risk according to the control instruction, can display the sampled rock-soil parameter samples in a list form, correspondingly display the established slope numerical model and N [ EDP, IM ] data pairs obtained by calculation, display the obtained vulnerability model, and also display the obtained earthquake displacement risk curve considering the uncertainty of the rock-soil mass parameters in a graph form.
The control part is communicated with the parameter determining part, the curve determining and selecting part, the sampling part, the numerical model establishing and calculating part, the vulnerability model preliminary obtaining part, the vulnerability model final obtaining part, the earthquake displacement danger curve obtaining part and the input display part, and controls the operation of the parameter determining part, the curve determining and selecting part, the sampling part, the numerical model establishing and calculating part, the vulnerability model preliminary obtaining part, the vulnerability model final obtaining part, the earthquake displacement danger curve obtaining part and the input display part.
The above embodiments are merely illustrative of the technical solutions of the present invention. The method and apparatus for analyzing the risk of sliding on a probabilistic earthquake slope based on vulnerability according to the present invention are not limited to the above embodiments, but the scope of the invention is defined by the claims. Any modifications, additions or equivalent substitutions made by those skilled in the art based on this embodiment are within the scope of the invention as claimed in the claims.

Claims (8)

1. The probability earthquake side slope sliding risk analysis method based on the vulnerability is characterized by comprising the following steps of:
step 1, acquiring historical data of an area where a side slope is located, and determining engineering demand parametersEDPAnd seismic intensity parametersIMAnd determining their analytical accuracy and range;
step 2, determining a seismic risk curve of the site where the side slope is located, and selecting seismic records with consistent risk;
step 3, determining statistical characteristics of the rock-soil body parameters, and sampling by using a central composite design method to obtain
Figure QLYQS_1
The rock-soil parameter samples are assembled,Kthe number of uncertainty parameters;
step 4, establishing a slope numerical model, and inputting each group of rock-soil parameter samples in sequenceNRecording the strip earthquake, and performingNSecondary power calculation to obtainNPersonal [ EDP, IM ]]A data pair;
step 5, obtaining a vulnerability model of each group of rock and soil parameter samples without considering uncertainty of the rock and soil parameters in different EDP sizes through vulnerability analysis according to the [ EDP, IM ] data pairs;
step 6, obtaining a vulnerability model considering uncertainty of rock-soil parameters through a response surface method and Monte Carlo simulation;
and 7, obtaining the seismic displacement risk curve considering the uncertainty of the rock-soil mass parameters through numerical integration according to the seismic risk curve in the step 2 and the vulnerability model in the step 6.
2. The vulnerability-based probabilistic seismic side slope slip risk analysis method of claim 1, characterized by:
wherein step 2 further comprises the sub-steps of:
step 2.1, obtaining a seismic risk curve of the field through probability seismic risk analysis PSHA;
step 2.2, according to the seismic risk curve, the depolymerization result of PSHA and the shear wave velocity weighted average Vs of the rock and soil layer within the depth range of 30 meters of the field 30 Seismic records are selected that are consistent in risk.
3. The vulnerability-based probabilistic seismic side slope slip risk analysis method according to claim 2, characterized in that:
wherein, in step 2.2:
(1) If the vulnerability analysis method is cloud analysisThe method comprises calculating average moment magnitude of depolymerized seismic event according to depolymerization result of PSHA
Figure QLYQS_2
And average source distance>
Figure QLYQS_3
The method comprises the steps of carrying out a first treatment on the surface of the Then randomly selecting from the seismic record databaseNA plurality of seismic records, each of which is ensured to be from a source site and a Vs of an analysis site 30 Consistent while ensuringNThe average moment and average source distance of the bar seismic records are respectively equal to +.>
Figure QLYQS_4
And->
Figure QLYQS_5
Consistent;
(2) If the vulnerability analysis method is a multi-band method, first, the seismic risk curve is dividedSA risk level; then, for a certain risk level, selecting from the seismic record database by a conditional spectrometry or a generalized conditional intensity parameter method according to the mean and variance of IM of the levelQA plurality of seismic records, each seismic record being secured at the same time as Vs at the source site and analysis site 30 Consistent; finally, the above process is repeated for each risk level, for a total of choicesNA strip of seismic records is recorded,
Figure QLYQS_6
。
4. the vulnerability-based probabilistic seismic side slope slip risk analysis method of claim 3, wherein:
wherein, in the step 2.2, if the vulnerability analysis method is a cloud analysis method,Nshould be greater than 80; if the vulnerability analysis method is a multi-band method,Sit should be greater than 10 and should be greater than,Qshould be greater than 30.
5. The vulnerability-based probabilistic seismic side slope slip risk analysis method of claim 1, characterized by:
wherein step 6 further comprises the sub-steps of:
step 6.1, designating the size of EDP, and setting the logarithm of the anti-seismic median of the vulnerability model considering the uncertainty of the rock-soil body parameters
Figure QLYQS_7
Obtaining undetermined coefficients of the secondary response surface function by a least square method according to the anti-seismic median value of the vulnerability model corresponding to each group of rock-soil parameter samples;
step 6.2, randomly generating 10000 groups of rock and soil parameter samples through Monte Carlo simulation, and calculating the earthquake-resistant median value of 10000 vulnerability models according to the step 6.1;
step 6.3, designating the size of IM, setting the dispersion of the vulnerability models of 10000 groups of rock-soil parameter samples to be equal to the dispersion of the vulnerability models of the average value samples in step 5, and solving to obtain 10000 vulnerability probabilities according to the earthquake-resistant median value of the vulnerability models obtained in step 6.2;
step 6.4, calculating 10000 expectations of vulnerability probability, namely taking the vulnerability model of uncertainty of rock-soil parameters into consideration into account to take the value of the vulnerability model when the EDP and IM sizes are appointed;
step 6.5, repeating the step 6.3 and the step 6.4 until values in all IM ranges are taken, so as to obtain a vulnerability curve considering uncertainty of the rock-soil parameters when the size of the EDP is specified;
step 6.6, fitting the vulnerability curve in the step 6.5 with a lognormal cumulative distribution curve, and solving the earthquake-resistant median of the vulnerability model
Figure QLYQS_8
And deviation->
Figure QLYQS_9
；
Step 6.7, repeating steps 6.1 to 6.6 until values within all EDP ranges are taken, thereby obtaining noEarthquake-resistant median value of vulnerable model considering uncertainty of rock-soil mass parameters at same EDP size
Figure QLYQS_10
And deviation->
Figure QLYQS_11
。
6. Probability earthquake side slope slip risk analysis device based on vulnerability, characterized by comprising:
a parameter determination part for obtaining the history data of the area where the slope is located and determining the engineering demand parametersEDPAnd seismic intensity parametersIMAnd determining their analytical accuracy and range;
a curve determination and selection part for determining a seismic risk curve of a place where the slope is located and selecting seismic records with consistent risk;
a sampling part for determining statistical characteristics of the rock-soil body parameters and sampling by using a central composite design method to obtain
Figure QLYQS_12
The rock-soil parameter samples are assembled,Kthe number of uncertainty parameters;
a numerical model establishment and calculation part for establishing a slope numerical model, wherein for each group of rock-soil parameter samples, the numerical model establishment and calculation part sequentially inputsNRecording the strip earthquake, and performingNSecondary power calculation to obtainNPersonal [ EDP, IM ]]A data pair;
the vulnerability model preliminary acquisition part is used for acquiring a vulnerability model of which each group of rock and soil parameter samples does not consider uncertainty of the rock and soil parameters when the rock and soil parameters are different in size through vulnerability analysis according to the [ EDP, IM ] data pair;
the final obtaining part of the vulnerability model obtains the vulnerability model considering the uncertainty of the rock-soil parameters through a response surface method and Monte Carlo simulation;
the seismic displacement risk curve obtaining part is used for obtaining a seismic displacement risk curve considering the uncertainty of the rock-soil mass parameters through numerical integration according to the seismic risk curve determined by the curve determination selecting part and the vulnerability model obtained by the vulnerability model final obtaining part; and
and the control part is in communication connection with the parameter determining part, the curve determining and selecting part, the sampling part, the numerical model establishing and calculating part, the vulnerability model preliminary obtaining part, the vulnerability model final obtaining part and the earthquake displacement dangerous curve obtaining part and controls the operation of the parameter determining part, the curve determining and selecting part, the sampling part, the numerical model establishing and calculating part and the vulnerability model final obtaining part.
7. The vulnerability-based probabilistic seismic side slope slip risk analysis device of claim 6, further comprising:
the input display part is in communication connection with the parameter determination part, the curve determination selection part, the sampling part, the numerical model establishment calculation part, the vulnerability model preliminary acquisition part, the vulnerability model final acquisition part, the earthquake displacement dangerous curve acquisition part and the control part, and displays corresponding information according to operation instructions input by a user.
8. The vulnerability-based probabilistic seismic side slope slip risk analysis apparatus according to claim 7, wherein:
wherein the input display part can display prompt information to enable an operator to select and determine engineering demand parametersEDPAnd seismic intensity parametersIMAnd determining their analytical accuracy and range; the input display part can also display the determined earthquake risk curve and the earthquake record with the same risk according to the control instruction, can display the sampled rock and soil parameter sample in a list form, and can display the established slope numerical model and the calculated rock and soil parameter sampleNPersonal [ EDP, IM ]]And correspondingly displaying the data pairs, displaying the obtained vulnerability model, and displaying the obtained seismic displacement risk curve considering the uncertainty of the rock-soil mass parameters in a graph form.
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