Dam post-earthquake rapid safety assessment method and device and storage medium

Abstract

The invention relates to the technical field of dam health monitoring, in particular to a dam post-earthquake rapid safety assessment method, device and equipment and a computer storage medium. According to the dam post-earthquake rapid safety assessment method, specific values of limit state judgment conditions of preset engineering parameters are determined through nonlinear dynamic time history calculation and vulnerability analysis and research, an anti-seismic safety assessment grading index system is established, and vulnerability analysis and research are further performed, so that the dam post-earthquake rapid safety assessment method is obtained. And the probability that the dam reaches different limit states under the earthquake action of a specific strength grade is given, so that the possibility is provided for quickly judging the damage degree of the dam body after the earthquake and quickly evaluating the safety after the earthquake.

Description

Technical Field

[0001] The present invention relates to the technical field of dam health monitoring, and in particular to a method, device, equipment and computer storage medium for rapid safety assessment of a dam after an earthquake. Background Art

[0002] The basic understanding of dam seismic fortification in my country is that the dam will not be damaged by moderate earthquakes, can be repaired by large earthquakes, and will not collapse in extreme earthquakes. That is, the dam is allowed to suffer a certain degree of damage or even serious earthquake damage in extreme earthquakes, but it should be able to maintain its water storage capacity and avoid dam collapse. The safety of earth-rock dams under strong earthquakes has attracted much attention, namely the ultimate seismic resistance of earth-rock dams. The main analysis content includes how large an earthquake the earth-rock dam can withstand, the safety margin of the dam under strong earthquakes, what damage will occur to the dam under strong earthquakes, and the failure mode. Since the ultimate seismic resistance of high earth-rock dams is relatively complicated, many scholars at home and abroad have also conducted a lot of research on it. However, there is currently no unified specification or standard at home and abroad to explain the evaluation criteria for the ultimate seismic resistance of earth-rock dams. Therefore, how to establish a set of dam seismic safety evaluation grading index system to quickly conduct safety assessments on dams is currently a problem to be solved. Summary of the invention

[0003] Therefore, the technical problem to be solved by the present invention is to overcome the problem in the prior art that the safety assessment of the dam cannot be accurately performed.

[0004] In order to solve the above technical problems, the present invention provides a method for rapid safety assessment of a dam after an earthquake, comprising:

[0005] defining a failure variable according to a function of a seismic hazard random variable and a structural random variable, and dividing a random variable space according to the failure variable;

[0006] defining an earthquake vulnerability function according to a cumulative distribution probability of a probability density function of the failure variable;

[0007] Performing nonlinear dynamic time history calculation based on the observed data, and calculating estimated values ​​of parameters in the seismic vulnerability function according to the nonlinear dynamic time history calculation results, and fitting the seismic vulnerability curve;

[0008] Analyze the limit state values ​​of preset engineering demand parameters according to the nonlinear dynamic time history calculation results, and establish a dam seismic safety evaluation grading index system;

[0009] The post-earthquake state of the dam is quickly assessed based on the dam seismic safety evaluation grading index system and the earthquake vulnerability curve.

[0010] Preferably, the seismic vulnerability function is defined as:

[0011]

[0012] Among them, im is the ground motion intensity parameter, β im is the logarithmic standard deviation of the ground motion intensity parameter, μ im is the average value of the earthquake intensity parameter.

[0013] Preferably, the nonlinear dynamic time history calculation is performed based on the observed data, and the estimated values ​​of the parameters in the seismic vulnerability function are calculated according to the nonlinear dynamic time history calculation results, and the seismic vulnerability curve fitting comprises:

[0014] Using cloud analysis method to fit earthquake vulnerability curve:

[0015] A set of unscaled earthquake records that did not cause structural damage is used as observation data;

[0016] Assuming that the engineering demand parameters obey the log-normal distribution when the earthquake intensity parameters are given, the logarithms of the earthquake intensity parameters and the corresponding engineering demand parameters are taken and linearly fitted to calculate the conditional logarithmic mean of the earthquake intensity parameters and the corresponding engineering demand parameters;

[0017] Assuming that the conditional logarithmic standard deviation of the engineering demand parameter is not affected by the ground motion intensity parameter, the conditional logarithmic standard deviation of the engineering demand parameter that is globally constant is calculated;

[0018] The structural limit state is defined when the engineering demand parameters exceed a certain limit value, and the seismic vulnerability function of the structure under different limit states is calculated. Specifically, the logarithmic standard deviation and the average value of the seismic motion intensity parameters in the seismic vulnerability function are calculated according to the conditional logarithmic mean and conditional logarithmic standard deviation of the engineering demand parameters, and the seismic vulnerability curve is fitted.

[0019] Preferably, the nonlinear dynamic time history calculation is performed based on the observed data, and the estimated values ​​of the parameters in the seismic vulnerability function are calculated according to the nonlinear dynamic time history calculation results, and the seismic vulnerability curve fitting comprises:

[0020] The incremental dynamic analysis method is used to fit the earthquake vulnerability curve:

[0021] A set of earthquake records are scaled and subjected to nonlinear time history analysis until each earthquake causes structural damage;

[0022] Assuming that the seismic intensity parameters of the structure destroyed corresponding to the earthquake record obey the log-normal distribution, based on the nonlinear time history calculation results, the mean and standard deviation of the vulnerability curves of the structure under different limit states are estimated according to the moment method, and the earthquake vulnerability curve is fitted.

[0023] Preferably, the nonlinear dynamic time history calculation is performed based on the observed data, and the estimated values ​​of the parameters in the seismic vulnerability function are calculated according to the nonlinear dynamic time history calculation results, and the seismic vulnerability curve fitting comprises:

[0024] The multi-band analysis method is used to fit the earthquake vulnerability curve:

[0025] A nonlinear time history analysis is performed using a set of scaled earthquake records containing earthquakes that cause structural damage.

[0026] Assuming that whether each earthquake record causes structural damage is independent of other earthquake records, the probability of the structure reaching different limit states is calculated through binomial distribution, and the mean and standard deviation of the seismic intensity parameters in the seismic vulnerability function under different limit state conditions of the structure are calculated using the maximum likelihood estimation method to fit the seismic vulnerability curve.

[0027] Preferably, the earthquake intensity parameters include single spectral acceleration and joint spectral acceleration.

[0028] Preferably, analyzing the limit state values ​​of preset engineering demand parameters according to the nonlinear dynamic time history calculation results to establish a dam seismic safety evaluation grading index system includes:

[0029] Analyze the limit state value of the percentage decrease of the first-order natural frequency of the dam body after the earthquake based on the nonlinear time history calculation results;

[0030] When the percentage of the first-order natural frequency drop of the dam body after the earthquake is greater than the first limit state value, it is determined that the downstream beam of the arch dam begins to be damaged and the dam body enters a nonlinear working state;

[0031] When the percentage decrease of the first-order natural frequency of the dam body after the earthquake is greater than the second limit state value, it is determined that the dam body has suffered moderate damage, and the middle part of the downstream face beam has cracked and extended into the dam body;

[0032] When the percentage decrease of the first-order natural frequency of the dam body after the earthquake is greater than the second limit state value, it is judged that the arch dam is severely damaged and cracked, has reached the limit of its seismic resistance, and is about to be destroyed.

[0033] The present invention also provides a device for rapid safety assessment of a dam after an earthquake, comprising:

[0034] A failure variable calculation module, used to define failure variables according to the function of seismic hazard random variables and structural random variables, and divide the random variable space according to the failure variables;

[0035] An earthquake vulnerability function calculation module, used for defining an earthquake vulnerability function according to a cumulative distribution probability of a probability density function of the failure variable;

[0036] An earthquake vulnerability curve fitting module is used to perform nonlinear dynamic time history calculation based on the observed data, and calculate the estimated values ​​of the parameters in the earthquake vulnerability function according to the nonlinear dynamic time history calculation results, so as to fit the earthquake vulnerability curve;

[0037] A hierarchical index system establishment module is used to analyze the limit state values ​​of preset engineering demand parameters according to the nonlinear dynamic time history calculation results and establish a hierarchical index system for dam seismic safety evaluation;

[0038] The safety assessment module is used to quickly assess the post-earthquake status of the dam based on the dam seismic safety assessment grading index system and the earthquake vulnerability curve.

[0039] The present invention also provides a dam post-earthquake rapid safety assessment device, comprising:

[0040] Memory for storing computer programs;

[0041] A processor is used to implement the steps of the above-mentioned method for rapid safety assessment of a dam after an earthquake when executing the computer program.

[0042] The present invention also provides a computer-readable storage medium, on which a computer program is stored. When the computer program is executed by a processor, the steps of the above-mentioned method for rapid post-earthquake safety assessment of a dam are implemented.

[0043] The above technical solution of the present invention has the following advantages compared with the prior art:

[0044] The method for rapid post-earthquake safety assessment of a dam described in the present invention determines the specific values ​​of the limit state judgment conditions of preset engineering parameters through dynamic time history calculation and vulnerability analysis research, and establishes a grading index system for earthquake-resistant safety assessment, thereby making it possible to quickly determine the degree of damage to the dam body after an earthquake and conduct rapid post-earthquake safety assessment. BRIEF DESCRIPTION OF THE DRAWINGS

[0045] In order to make the content of the present invention more clearly understood, the present invention is further described in detail below according to specific embodiments of the present invention in conjunction with the accompanying drawings, wherein:

[0046] Figure 1 It is a flow chart of the implementation of a method for rapid safety assessment of a dam after an earthquake provided by the present invention;

[0047] Figure 2 It is the schematic diagram of CLA analysis data and linear fitting;

[0048] Figure 3 It is a schematic diagram of the IDA curve and the seismic vulnerability curve based on IDA fitting;

[0049] Figure 4Schematic diagram of MSA analysis data and earthquake vulnerability curve. DETAILED DESCRIPTION

[0050] The core of the present invention is to provide a method, device, equipment and computer storage medium for rapid safety assessment of dams after earthquakes, which can effectively conduct rapid safety assessment of dams after earthquakes.

[0051] In order to enable those skilled in the art to better understand the scheme of the present invention, the present invention is further described in detail below in conjunction with the accompanying drawings and specific implementation methods. Obviously, the described embodiments are only part of the embodiments of the present invention, rather than all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative work are within the scope of protection of the present invention.

[0052] Please refer to Figure 1 , Figure 1 This is a flowchart of a method for rapid post-earthquake safety assessment of a dam provided by the present invention; the specific operation steps are as follows:

[0053] S101: defining a failure variable according to a function of a seismic hazard random variable and a structural random variable, and dividing a random variable space according to the failure variable;

[0054] S102: defining an earthquake vulnerability function according to the cumulative distribution probability of the probability density function of the failure variable;

[0055] S103: performing nonlinear dynamic time history calculation based on the observed data, and calculating estimated values ​​of parameters in the seismic vulnerability function according to the nonlinear dynamic time history calculation results, and fitting the seismic vulnerability curve;

[0056] Among them, the nonlinear dynamic time-history calculation needs to take into account the opening and closing behavior of transverse joints, the plastic damage mechanism of concrete, the heterogeneity and elastic-plastic behavior of bedrock, the radiation damping effect of infinite foundation, and the fluid-solid coupling of reservoir water-dam body-foundation.

[0057] S104: Analyze the limit state values ​​of preset engineering demand parameters according to the nonlinear dynamic time history calculation results, and establish a dam seismic safety evaluation grading index system;

[0058] S105: Rapidly assessing the post-earthquake status of the dam based on the dam seismic safety evaluation grading index system and the earthquake vulnerability curve.

[0059] Based on the above embodiments, this embodiment describes step S101 in detail:

[0060] The seismic vulnerability of a structure indicates the probability of a certain expected level of damage (or reaching a predefined limit state) under an earthquake of a given intensity. Its mathematical description is as follows:

[0061] F(im)=P[LS|IM=im] Equation 1

[0062] Where F(im) is the seismic vulnerability probability of the structure; LS is a certain performance level of the structure; IM represents the seismic intensity parameter; im is the possible value of IM; P[LS|IM=im] represents the conditional probability that the structure is at a certain performance level LS when the local vibration intensity parameter IM=im.

[0063] Taking structural failure as an example, whether the structure fails can be determined by the failure indicator g i To represent, i = 1, 2, 3, ..., N represents N different failure modes:

[0064] g i =g i (x1,x2,…,x n ; y1,y2,…,y m ) Formula 2

[0065] Where g i It is defined as a random variable of earthquake hazard (x1, x2, …, x n ) and structural random variables (y1,y2,…,y m ), which can be stress, displacement, etc. The seismic hazard random variable can be a seismic scene parameter or a component of a seismic record, etc. The structural random variable can be a structural dimension, material strength, etc. In order to simplify the analysis, only one failure mode is considered. According to the traditional structural reliability analysis method, when the failure variable reaches the corresponding limit state surface, the structure fails:

[0066] g(x1,x2,…,x n ; y1,y2,…,y m )=0Formula 3

[0067] The random variable space is thus divided by this surface into a safe region (g≤0) and a failure region (g>0). It is assumed that failure always occurs when the failure variable g is equal to the same value. This means that all so-called identical structures with the same structural parameters and load conditions will fail at the same failure variable g. However, the so-called identical structure is only defined at a level that can be measured by technology. Unmeasurable differences in random parameters will lead to measurable changes in the values ​​of failure variables corresponding to structural failures. This is the so-called intrinsic uncertainty of the failure variable. Sometimes, for different reasons, we ignore some seismic hazard random variables or do not consider the variability of certain structural random variables (which we can measure), which leads to greater uncertainty in the failure variable. This additional uncertainty is called external uncertainty. After considering these uncertainties, the random variable space is divided into three regions:

[0068] (1) Safe Zone

[0069] g(x1,x2,…,x n ; y1,y2,…,y m )≤g min Formula 4

[0070] (2) Possible failure area

[0071] g min <g(x1,x2,…,x n ; y1,y2,…,y m ) <g max Formula 5

[0072] (3) Failure zone

[0073] g(x1,x2,…,x n ; y1,y2,…,y m )≥g max Formula 6

[0074] Based on the above embodiments, this embodiment describes step S102 in detail:

[0075] We define the probability density function of the failure variable g as f(g), then the probability of structural failure vulnerability is its cumulative distribution probability:

[0076]

[0077] Under the premise of the above formula, the problem of converting the vulnerability function into the probability density function f(g) of the failure variable is solved. The concept of entropy (H) in information theory is introduced, which represents the measure of uncertainty. For the one-dimensional probability density function f(x), the calculation formula of entropy is:

[0078]

[0079] Where l is a constant, which has no effect on the entropy relationship, but only changes the starting point of the entropy estimate, and can be taken as 1. When little is known about the random variable x, and only its range of values ​​is known, the entropy corresponding to the uniform distribution is the largest; if the range of the variable x is unlimited, and its mean μ and standard deviation β are known, the entropy corresponding to the normal distribution is larger than that of other distribution forms:

[0080]

[0081] It is very important to ensure that the entropy is maximized. When a non-normal distribution also has the same mean and standard deviation, its entropy is less than the normal distribution, which means that the distribution uses information that is not included in the known conditions. The correctness of this information is unknown and it is likely to be proven wrong after more information about the random variable is supplemented. Therefore, the principle of maximum entropy should be strictly followed to avoid excessive inference. In earthquake vulnerability calculations, the seismic intensity parameters are usually greater than 0, so the lognormal distribution should be used as the probability density function:

[0082]

[0083] Here μ is the mean of the random variable x and β is its logarithmic standard deviation.

[0084] In earthquake vulnerability analysis, the failure variable g is considered to obey the mean μ R , with a standard deviation of β R To simplify the analysis, β R Usually considered to be a constant, but only μ R It has uncertainty and follows a log-normal distribution with a mean of μ U , with a standard deviation of β U :

[0085]

[0086] where f R is the probability density function of the failure variable g when only the uncertainty of the mean is considered in earthquake vulnerability analysis, f U μ R The probability density function of the failure variable g is obtained as follows:

[0087] f C (g,μ U ,β R ,β U ) = f R (g,μ R ,β R )×f U (μ R ,μ U ,β U ) Formula 13

[0088] where f C is the probability density function of the failure variable g, which contains all possible factors that may affect the failure variable, including accidental uncertainty R and epistemic uncertainty U caused by cognitive errors. Based on the above formula, the seismic vulnerability function is:

[0089]

[0090] where β C is the log standard deviation of the joint distribution:

[0091]

[0092] However, in the actual analysis process, β U It is difficult to obtain μ, which is mostly due to the lack of data. R is a certain value, then the earthquake vulnerability function is:

[0093]

[0094] For concrete dams, the fragility function in Equation 14 is defined as:

[0095]

[0096] Where im is the ground motion intensity parameter value, β im is the logarithmic standard deviation of the ground motion intensity parameter, μ im is the average value of the seismic intensity parameter. When epistemic uncertainty is considered in earthquake vulnerability analysis, β im represents the standard deviation of the coupling of aleatoric uncertainty and epistemic uncertainty, i.e., β C For β C In the early stage, researchers gave β through expert opinions and data analysis. U and β R , β can be directly given when data is very scarce C As computing power increases, β U and β R They can be obtained separately through structural dynamic analysis, and then combined through formula 17 to calculate β C (Although this approach will bring some errors), or directly calculate β through Monte Carlo random simulation and other calculation methods C The value of β U and β R Treated separately.

[0097] Based on the above embodiments, this embodiment describes step S103 in detail:

[0098] In earthquake vulnerability analysis, the parameter values ​​(mean μ and logarithmic standard deviation β) of the earthquake vulnerability function can be estimated based on the calculation results (or observation data). These parameter values, like the observation data, depend on the dynamic response analysis method used. This invention introduces three commonly used earthquake vulnerability curve fitting methods in detail.

[0099] (1) Cloud analysis method

[0100] CLA uses a set of unscaled earthquake records for calculations, and is usually used in conjunction with probabilistic seismic demand analysis to explore the correlation between the engineering demand parameter EDP and the ground motion intensity parameter IM. CLA is generally not used for seismic vulnerability analysis of structural damage. It is usually assumed that EDP follows a log-normal distribution when IM is given:

[0101] EDP|IM~LN(μ EDP|IM ,β EDP|IM ) Formula 18

[0102] where μ EDP|IM and β EDP|IM are the conditional log mean and conditional log standard deviation of EDP under a given IM, respectively.

[0103] Through a large number of probabilistic seismic demand analyses, Cornell found that when IM = im, the conditional logarithmic mean μ of EDP is EDP|IM It is linearly related to the logarithm of IM, ln(im):

[0104] μ EDP|IM＝im =Bln(im)+ln(A) Formula 19

[0105] Or the conditional median of EDP is related to IM in a power function:

[0106]

[0107] in is the conditional median value of EDP given IM.

[0108] Therefore, the logarithms of IM and the corresponding EDP in CLA were taken and linear fitting was performed, as shown in Figure 2 As shown, the coefficients A and B in formula 20 can be obtained to find the logarithmic mean μ of EDP corresponding to IM = im. EDP|IM .

[0109] At the same time, CLA further assumes that the conditional logarithmic standard deviation in Equation 18 does not change with the change of IM, that is, it remains constant globally. The conditional logarithmic standard deviation is calculated by the following formula:

[0110]

[0111] where n is the number of earthquake records in CLA.

[0112] Based on the above results, if the EDP exceeds a certain limit value to define the limit state of the structure in CLA, the corresponding fragility function is:

[0113]

[0114] Substituting equation 19 into equation 22 and further rearranging it, we obtain:

[0115]

[0116] make:

[0117]

[0118] where μ im For the demand level edp Figure 2 The IM value corresponding to the fitted straight line in the figure is the conditional median value of EDP. When it is equal to the given demand level edp, it corresponds to The earthquake intensity IM. Then the earthquake vulnerability function corresponding to this limit state is:

[0119]

[0120] The parameters of the seismic vulnerability function are calculated according to Equations 24 and 25.

[0121] Obviously, the CLA method can conveniently calculate the seismic vulnerability function, thanks to several important assumptions in the CLA method, namely, when the IM is given, the EDP is log-normally distributed, the EDP and IM are linearly related on a logarithmic scale, and the logarithmic standard deviation remains constant.

[0122] (2) Incremental dynamic analysis method

[0123] Because the IDA method has clear concepts and simple operations, it is currently widely used. Taking the limit state of structural damage as an example, IDA scales n earthquake records proportionally until they all cause structural damage. Figure 3 As shown in Figure 2, this process will produce a set of IM values ​​corresponding to the beginning of damage for each earthquake record, denoted as IM C The probability of structural damage at a given IM level can then be estimated as the damage level IM C The percentage of records below a given IM:

[0124] P[C|IM=im]=P[IM C ≤im] Formula 27

[0125] Where C represents the limit state of structural damage, IM C represents the IM corresponding to the structure just being damaged, which is assumed to be an uncertainty variable that follows a log-normal distribution with a mean of And the standard deviation is Then the seismic vulnerability curve of structural damage can be expressed by the following lognormal cumulative distribution function:

[0126]

[0127] The IM corresponding to each earthquake record is obtained by IDA calculation C The parameters in Equation 28 are estimated by moment method, and the seismic vulnerability curve is fitted as follows: Figure 3 As shown:

[0128]

[0129] (3) Multi-band analysis

[0130] MSA generally performs structural analysis at discrete IM levels and uses different earthquake records at each IM level. The MSA method is more common when conditional spectra or other methods are used to select earthquake records representing specific IM levels. Taking the structural failure limit state as an example, MSA does not require that all earthquake records be calculated until the structure fails. The EDP-IM data obtained by the analysis is as follows: Figure 4 Since different earthquake records are used at each IM level, even if the expected failure probability increases with increasing IM, this may not be strictly true in practice.

[0131] For the data in MSA, since the damage intensity value of each earthquake cannot be given, the estimation method in IDA cannot be used. However, the proportion of structural damage under each IM can be obtained, so the maximum likelihood estimation method can be used to fit the earthquake vulnerability curve. At each intensity level IM = im i Place, n i There are x earthquake records in total i earthquake records lead to structural damage. Assuming that whether each earthquake record leads to damage is independent of other earthquake records, the probability of this happening is given by the binomial distribution:

[0132]

[0133] where p i When the earthquake intensity level IM = im i The probability of structural damage.

[0134] For multiple levels of earthquake intensity, multiply the probabilities corresponding to each level of earthquake intensity to obtain the probability of the event corresponding to the entire data set:

[0135]

[0136] Where m is the number of intensity levels considered. Substituting Equation 28 into Equation 32 yields:

[0137]

[0138] By solving the maximum value of the likelihood function in equation 33, we can obtain the estimated values ​​of the parameters in the earthquake vulnerability function and obtain the earthquake vulnerability curve, as shown in Figure 4 As shown. The MSA method does not require that each earthquake record be calculated to the point of structural damage, which makes it applicable to unscaled earthquake records, that is, there can be only one earthquake for each intensity level. In addition, MSA assumes that each observation is independent and the overall probability is the multiplication of the probability at each level. If the same earthquake record is used for structural analysis of multiple intensity levels, this assumption may not be strict, but in fact, analysis has shown that even with IDA data (using the same earthquake record at all IM levels), the MSA method can obtain effective earthquake vulnerability curves. In summary, the MSA method has strict restrictions on the selection of earthquake records, ensuring that the selected earthquake records can represent the specified intensity level, and there is no doubt that may be caused by over-scaling of earthquake records in IDA. Therefore, under the premise of ensuring that various uncertainties are fully considered, the earthquake vulnerability analysis results obtained by the MSA method are more reliable.

[0139] Based on the above embodiments, we analyze the earthquake intensity parameter (IM):

[0140] (1) Definition and classification of IM

[0141] The earthquake vulnerability curve represents the probability of different degrees of structural damage under different earthquake intensity levels. The earthquake intensity parameter IM is a measure of earthquake intensity, which can represent the strength of the earthquake to a certain extent. The selection of IM is very important for earthquake vulnerability analysis. Only when the selected IM can well represent the strength of the earthquake, the earthquake vulnerability curve will have a relatively high reliability.

[0142] In addition to the commonly used PGA and S a In addition to (T1), many researchers have proposed a large number of IMs in their research results. This paper classifies these IMs according to the current research results, selects some representative IMs for statistics, and can be roughly divided into the following three groups.

[0143] Group 1: scalar IMs related to earthquake records but not to response spectra, as shown in Table 1.

[0144] Table 1 IM statistics of earthquake intensity parameters (Group 1)

[0145]

[0146]

[0147] Group 2: scalar IMs that are related to the response spectrum and have nothing to do with structural properties, as shown in Table 2.

[0148] Table 2 IM statistics of earthquake intensity parameters (Group 2)

[0149]

[0150] Group 3: Scalar IMs related to structural characteristics and response spectra, as shown in Table 3.

[0151] Table 3 IM statistics of earthquake intensity parameters (Group 3)

[0152]

[0153]

[0154] (2) Optimal IM for arch dams

[0155] The above embodiment introduces the process of solving the vulnerability curve using the CLA method, which involves the linear fitting of IM and EDP on a logarithmic scale, and the correlation between IM and EDP is determined by the degree of the fitting.

[0156] There are four main indicators to judge the correlation between IM and EDP, namely, Efficiency, Practicality, Proficiency and Sufficiency. EDP|IM It reflects the correlation strength between IM and EDP and the uncertainty of the probabilistic seismic demand model PSDM. EDP|IM The smaller the value, the higher the effectiveness of IM. To improve this effectiveness, more information needs to be included in IM. This is why spectral acceleration has been proven to be more effective than PGA, because spectral acceleration contains information such as structural self-vibration characteristics and damping. Practicality is represented by B value, which represents the slope of linear regression. The larger the B value, the higher the practicality. The smaller the ln(IM) range corresponding to the same ln(EDP) range, the higher the sensitivity of EDP to IM. Proficiency is expressed by β im It represents the standard deviation of the seismic vulnerability curve, β im The smaller the value, the higher the proficiency, which means that the uncertainty of seismic vulnerability curve caused by adopting a specific IM is smaller. Sometimes, the validity and practicality cannot get consistent judgment results, then β imA combination of the two criteria can be considered. Sufficiency means that the IM is conditionally statistically independent of the ground motion characteristics, usually magnitude M and epicentral distance R. Sufficiency requires that M and R have no systematic effect on the seismic demand model PSDM for a given IM, which means that the traditional application of the full probability theory in PSDA is appropriate for IM.

[0157] According to the above criteria, the optimal IM for arch dams is studied. For the IM obtained directly from earthquakes and not related to the response spectrum, the optimal IM is a RMS , followed by I A , the commonly used PGA is not sufficient, and its calculation results may be affected by the magnitude M or the epicenter distance R. For IMs based on response spectrum calculation but not related to structural characteristics, VSI is the optimal IM, and the other IMs are not sufficient. For spectral acceleration IMs related to structures, the commonly used S a (T1) shows a high correlation with the structural response, while considering the high-order spectral acceleration Class IM shows higher effectiveness, practicality and proficiency as the number of spectral accelerations N increases. a (T1) and is the optimal IM for arch dams.

[0158] Based on the above embodiments, this embodiment analyzes the engineering demand parameters:

[0159] In the selection of IM, an important criterion is that it is required to be able to predict the structural response well, and the structural response is measured by EDP. The importance of EDP lies in that it is generally needed to judge the performance level of the structure in vulnerability analysis, such as judging whether the structure has been damaged and dividing the limit state, so as to lay the foundation for calculating the earthquake vulnerability curve. Due to the complexity of the failure mode of high arch dams and the lack of actual earthquake damage data, there is currently no consensus on the definition of its performance level and the selection of EDP. Commonly used EDPs include the maximum displacement upstream of the top arch, the opening of the transverse joint, and the volume ratio of the dam body damage. This section proposes to use the percentage of the first-order frequency decrease of the dam body after the earthquake as a new EDP, and the expression of this EDP is:

[0160]

[0161] where d F represents the percentage of the first-order natural frequency decrease of the dam body after the earthquake, f 1,d It represents the first-order natural frequency of the dam body after the earthquake, and f1 represents the initial first-order natural frequency of the dam body.

[0162] Studies have shown that: FThere is a strong linear relationship between the volume ratio of the dam body damage and the dam body damage. This linear relationship is not obvious when the dam body damage is small, but it is very significant when the dam body enters the nonlinear working state. F In particular, it has a strong correlation with dam cracking. F It is also related to the maximum displacement of the dam crest Δ u and Δ d There is a correlation, Δ u and Δ d With the F When the dam enters the nonlinear working state, the increase rate slows down, and Δ u and Δ d Show different randomness F Growth rate, when the dam damage becomes more serious, Δ u and Δ d Noticeable differences in size begin to appear.

[0163] Based on the above embodiments, this embodiment describes step S104 in detail:

[0164] Based on the nonlinear time history calculation results, we analyze the limit state value of the percentage decrease of the 1st order natural frequency of the dam body after the earthquake;

[0165] When the percentage of the first-order natural frequency drop of the dam body after the earthquake is greater than the first limit state value, it is determined that the downstream beam of the arch dam begins to be damaged and the dam body enters a nonlinear working state;

[0166] When the percentage decrease of the first-order natural frequency of the dam body after the earthquake is greater than the second limit state value, it is determined that the dam body has suffered moderate damage, and the middle part of the downstream face beam has cracked and extended into the dam body;

[0167] When the percentage decrease of the first-order natural frequency of the dam body after the earthquake is greater than the second limit state value, it is judged that the arch dam is severely damaged and cracked, has reached the limit of its earthquake resistance, and is about to be destroyed.

[0168] In one embodiment, 1) LS1: with d F >2.5% is considered as a limit state, the downstream beam of the arch dam begins to be damaged and the dam body enters a nonlinear working state; (2) LS2: d F >10% is the second limit state, which means that the dam body is moderately damaged, typically manifested as cracks in the middle of the downstream beam extending into the dam body; (3) LS3: d F >30% is the limit state LS3, which means that the arch dam is severely damaged and cracked, has reached the limit of its seismic resistance, and is about to be destroyed.

[0169] Therefore, in practical applications, d FIt can be used for real-time health monitoring of the dam body. With the help of environmental excitation and other means, the natural frequency information of the dam body can be obtained in real time, and compared with the data before the earthquake, thus making it possible to quickly determine the degree of damage to the dam body after the earthquake and conduct a rapid safety assessment after the earthquake.

[0170] The embodiment of the present invention also provides a device for rapid safety assessment of a dam after an earthquake; the specific device may include:

[0171] A failure variable calculation module, used to define failure variables according to the function of seismic hazard random variables and structural random variables, and divide the random variable space according to the failure variables;

[0172] An earthquake vulnerability function calculation module, used for defining an earthquake vulnerability function according to a cumulative distribution probability of a probability density function of the failure variable;

[0173] An earthquake vulnerability curve fitting module is used to perform nonlinear dynamic time history calculation based on the observed data, and calculate the estimated values ​​of the parameters in the earthquake vulnerability function according to the nonlinear dynamic time history calculation results, so as to fit the earthquake vulnerability curve;

[0174] A hierarchical index system establishment module is used to analyze the limit state values ​​of preset engineering demand parameters according to the nonlinear dynamic time history calculation results and establish a hierarchical index system for dam seismic safety evaluation;

[0175] The safety assessment module is used to quickly assess the post-earthquake status of the dam based on the dam seismic safety assessment grading index system and the earthquake vulnerability curve.

[0176] The dam post-earthquake rapid safety assessment device of this embodiment is used to implement the aforementioned dam post-earthquake rapid safety assessment method. Therefore, the specific implementation method of the dam post-earthquake rapid safety assessment device can be seen in the embodiment part of the dam post-earthquake rapid safety assessment method above. For example, the failure variable calculation module, the earthquake vulnerability function calculation module, the earthquake vulnerability curve fitting module, the graded index system establishment module, and the safety assessment module are respectively used to implement steps S101, S102, S103, S104 and S105 in the above-mentioned dam post-earthquake rapid safety assessment method. Therefore, its specific implementation method can refer to the description of the corresponding various parts of the embodiment, which will not be repeated here.

[0177] A specific embodiment of the present invention further provides a device for rapid safety assessment of a dam after an earthquake, comprising: a memory for storing a computer program; and a processor for implementing the steps of the above-mentioned method for rapid safety assessment of a dam after an earthquake when executing the computer program.

[0178] A specific embodiment of the present invention further provides a computer-readable storage medium, on which a computer program is stored. When the computer program is executed by a processor, the steps of the above-mentioned method for rapid post-earthquake safety assessment of a dam are implemented.

[0179] Those skilled in the art will appreciate that the embodiments of the present application may be provided as methods, systems, or computer program products. Therefore, the present application may adopt the form of a complete hardware embodiment, a complete software embodiment, or an embodiment in combination with software and hardware. Moreover, the present application may adopt the form of a computer program product implemented in one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) that include computer-usable program code.

[0180] The present application is described with reference to the flowcharts and / or block diagrams of the methods, devices (systems), and computer program products according to the embodiments of the present application. It should be understood that each process and / or box in the flowchart and / or block diagram, as well as the combination of the processes and / or boxes in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to generate a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 A process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0181] These computer program instructions may also be stored in a computer-readable memory capable of directing a computer or other programmable data processing device to operate in a specific manner, so that the instructions stored in the computer-readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 A process or multiple processes and / or boxes Figure 1 A function specified in one or more boxes.

[0182] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operating steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing instructions for implementing the process. Figure 1 A process or multiple processes and / or boxes Figure 1 The steps for the functions specified in one or more boxes.

[0183] Obviously, the above embodiments are merely examples for the purpose of clear explanation and are not intended to limit the implementation methods. For those skilled in the art, other different forms of changes or modifications can be made based on the above description. It is not necessary and impossible to list all the implementation methods here. The obvious changes or modifications derived therefrom are still within the scope of protection of the present invention.

Claims

1. A method for rapid safety assessment of a dam after an earthquake, characterized in that: include: defining a failure variable according to a function of a seismic hazard random variable and a structural random variable, and dividing a random variable space according to the failure variable; defining an earthquake vulnerability function according to a cumulative distribution probability of a probability density function of the failure variable; Performing nonlinear dynamic time history calculation based on the observed data, and calculating estimated values ​​of parameters in the seismic vulnerability function according to the nonlinear dynamic time history calculation results, and fitting the seismic vulnerability curve; Analyze the limit state values ​​of preset engineering demand parameters according to the nonlinear dynamic time history calculation results, and establish a dam seismic safety evaluation grading index system; The post-earthquake state of the dam is quickly assessed based on the dam seismic safety evaluation grading index system and the earthquake vulnerability curve.

2. The method for rapid post-earthquake safety assessment of a dam according to claim 1, characterized in that: The seismic vulnerability function is defined as: Among them, im is the ground motion intensity parameter, β im is the logarithmic standard deviation of the ground motion intensity parameter, μ im is the average value of the earthquake intensity parameter.

3. The method for rapid post-earthquake safety assessment of a dam according to claim 2, characterized in that: The nonlinear dynamic time history calculation is performed based on the observed data, and the estimated values ​​of the parameters in the seismic vulnerability function are calculated according to the nonlinear dynamic time history calculation results. The seismic vulnerability curve fitting includes: Using cloud analysis method to fit earthquake vulnerability curve: A set of unscaled earthquake records that did not cause structural damage is used as observation data; Assuming that the engineering demand parameters obey the log-normal distribution when the earthquake intensity parameters are given, the logarithms of the earthquake intensity parameters and the corresponding engineering demand parameters are taken and linearly fitted to calculate the conditional logarithmic mean of the earthquake intensity parameters and the corresponding engineering demand parameters; Assuming that the conditional logarithmic standard deviation of the engineering demand parameter is not affected by the ground motion intensity parameter, the conditional logarithmic standard deviation of the engineering demand parameter that is globally constant is calculated; The structural limit state is defined when the engineering demand parameters exceed a certain limit value, and the seismic vulnerability function of the structure under different limit states is calculated. Specifically, the logarithmic standard deviation and the average value of the seismic motion intensity parameters in the seismic vulnerability function are calculated according to the conditional logarithmic mean and conditional logarithmic standard deviation of the engineering demand parameters, and the seismic vulnerability curve is fitted.

4. The method for rapid post-earthquake safety assessment of a dam according to claim 2, characterized in that: The nonlinear dynamic time history calculation is performed based on the observed data, and the estimated values ​​of the parameters in the seismic vulnerability function are calculated according to the nonlinear dynamic time history calculation results. The seismic vulnerability curve fitting includes: The incremental dynamic analysis method is used to fit the earthquake vulnerability curve: A set of earthquake records are scaled and subjected to nonlinear time history analysis until each earthquake causes structural damage; Assuming that the seismic intensity parameters corresponding to the structural damage of the earthquake record obey the log-normal distribution, Based on the nonlinear time history calculation results, the mean and standard deviation of the vulnerability curves under different limit states of the structure are estimated according to the moment method, and the seismic vulnerability curve is fitted.

5. The method for rapid post-earthquake safety assessment of a dam according to claim 4, characterized in that: The nonlinear dynamic time history calculation is performed based on the observed data, and the estimated values ​​of the parameters in the seismic vulnerability function are calculated according to the nonlinear dynamic time history calculation results. The seismic vulnerability curve fitting includes: The multi-band analysis method is used to fit the earthquake vulnerability curve: A nonlinear time history analysis is performed using a set of scaled earthquake records containing earthquakes that cause structural damage. Assuming that whether each earthquake record causes structural damage is independent of other earthquake records, the probability of the structure reaching different limit states is calculated through binomial distribution, and the mean and standard deviation of the seismic intensity parameters in the seismic vulnerability function under different limit state conditions of the structure are calculated using the maximum likelihood estimation method to fit the seismic vulnerability curve.

6. The method for rapid post-earthquake safety assessment of a dam according to any one of claims 2 to 5, characterized in that: The earthquake intensity parameters include single spectral acceleration and joint spectral acceleration.

7. The method for rapid post-earthquake safety assessment of a dam according to claim 1, characterized in that: The analyzing the limit state values ​​of preset engineering demand parameters according to the nonlinear dynamic time history calculation results and establishing a dam seismic safety evaluation grading index system comprises: Analyze the limit state value of the percentage decrease of the first-order natural frequency of the dam body after the earthquake based on the nonlinear time history calculation results; When the percentage of the first-order natural frequency drop of the dam body after the earthquake is greater than the first limit state value, it is determined that the downstream beam of the arch dam begins to be damaged and the dam body enters a nonlinear working state; When the percentage decrease of the first-order natural frequency of the dam body after the earthquake is greater than the second limit state value, it is determined that the dam body has suffered moderate damage, and the middle part of the downstream face beam has cracked and extended into the dam body; When the percentage decrease of the first-order natural frequency of the dam body after the earthquake is greater than the second limit state value, it is judged that the arch dam is severely damaged and cracked, has reached the limit of its seismic resistance, and is about to be destroyed.

8. A rapid safety assessment device for a dam after an earthquake, characterized in that: include: A failure variable calculation module, used to define failure variables according to the function of seismic hazard random variables and structural random variables, and divide the random variable space according to the failure variables; An earthquake vulnerability function calculation module, used for defining an earthquake vulnerability function according to a cumulative distribution probability of a probability density function of the failure variable; The seismic vulnerability curve fitting module is used to perform nonlinear dynamic time history calculation based on the observed data, and calculate the estimated values ​​of the parameters in the seismic vulnerability function according to the nonlinear dynamic time history calculation results. Fitting earthquake vulnerability curves; A hierarchical index system establishment module is used to analyze the limit state values ​​of preset engineering demand parameters according to the nonlinear dynamic time history calculation results and establish a hierarchical index system for dam seismic safety evaluation; The safety assessment module is used to quickly assess the post-earthquake status of the dam based on the dam seismic safety assessment grading index system and the earthquake vulnerability curve.

9. A rapid safety assessment device for dams after earthquake, characterized in that: include: Memory for storing computer programs; A processor is used to implement the steps of a method for rapid post-earthquake safety assessment of a dam as claimed in any one of claims 1 to 7 when executing the computer program.

10. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the steps of a method for rapid post-earthquake safety assessment of a dam are implemented as described in any one of claims 1 to 7.

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