CN115238441A - LS-D-Newmark earthquake landslide risk evaluation method and device and processing equipment - Google Patents
LS-D-Newmark earthquake landslide risk evaluation method and device and processing equipment Download PDFInfo
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Abstract
The application provides an LS-D-Newmark earthquake landslide risk evaluation method, device and processing equipment, which are used for adding a historical earthquake landslide density factor when a Newmark model is used for predicting earthquake landslide risk, so that the accuracy of predicting earthquake landslide risk is further improved. The method comprises the following steps: acquiring seismic landslide data of a target seismic landslide; determining the historical earthquake landslide density of the target earthquake landslide according to the earthquake landslide data; inputting earthquake landslide data into an LS-D-Newmark model, and adjusting related model parameters by using rock-soil body mechanical parameters and slope body morphological parameters to ensure that the slope has a static safety coefficient F under the action of no external power s Greater than 1; carry over historical seismic landslide density to LS-D-Newmark model, and pair F s Carrying out optimized assignment; based on optimized assigned F s Calculating the critical acceleration a of the slope c (ii) a At a c Of (2) aOn the basis, the earthquake induced slope displacement D is calculated by using the known earthquake peak acceleration value PGA n (ii) a According to D n And calculating the landslide occurrence probability P of the target landslide area.
Description
Technical Field
The application relates to the field of geological disaster engineering, in particular to an LS-D-Newmark earthquake landslide risk evaluation method, device and processing equipment.
Background
The earthquake landslide is a landslide type triggered by earthquake action or earthquake force, and refers to a geological phenomenon that a slope rock body or a soil body suddenly breaks away from a landslide region and is instable instantly due to earthquake vibration, the earthquake landslide risk is defined according to international general landslide risk assessment, the earthquake is strictly taken as a potential uncertain factor, the potential earthquake and the time-space distribution probability of inducing landslide are analyzed, and specific risk description elements comprise the position, the volume or the area of the potential earthquake landslide, the landslide type, the migration speed, the occurrence probability in a certain period and the like. Therefore, the earthquake landslide risk has a clear prediction property.
The existing model method for evaluating the earthquake landslide danger mainly comprises the following steps:
1. a comprehensive evaluation method based on statistical analysis: on the basis of statistical analysis of the correlation between the earthquake landslide and the earthquake geological background, the control effect of the earthquake geological background on landslide is disclosed, the main control factors of the earthquake landslide are excavated, and the evaluation research of the earthquake landslide risk based on multiple factors is completed by methods such as a support vector machine, information quantity and logistic regression;
2. a pseudo-static method based on an extreme balance theory: decomposing the ground vibration force acting on the slope along the sliding surface (or the direction of the maximum slope), and then calculating the ratio of the sliding force under the side slope and the anti-sliding force under the action of the seismic vibration to evaluate the landslide risk;
3. a Newmark model based on slope accumulated displacement: and predicting and evaluating the risk of earthquake-induced landslide by calculating slope displacement under the action of earthquake load.
In the existing research process of related technologies, the inventor finds that, in the currently adopted Newmark model, when earthquake landslide risk evaluation is performed through terrain gradient, rock-soil body mechanical parameters and earthquake Peak Acceleration (PGA), the prediction precision still does not remain stable, or the prediction precision is inaccurate to a certain extent.
Disclosure of Invention
The application provides an LS-D-Newmark earthquake landslide risk evaluation method, device and processing equipment, which are used for adding a historical earthquake landslide density factor when a Newmark model is used for predicting earthquake landslide risk so as to further improve the accuracy of predicting earthquake landslide risk.
In a first aspect, the application provides an LS-D-Newmark earthquake landslide risk evaluation method, which comprises the following steps:
acquiring earthquake landslide data of a target earthquake landslide;
determining the historical earthquake landslide density of the target earthquake landslide according to the earthquake landslide data;
inputting earthquake landslide data into an LS-D-Newmark model, and adjusting related model parameters by using rock-soil body mechanical parameters and slope body morphological parameters to ensure that the static safety coefficient F of the slope under the action of no external power s Greater than 1;
introducing historical earthquake landslide density into LS-D-Newmark model to add historical earthquake landslide factor, and introducing static safety factor F s Carrying out optimized assignment;
static safety factor F based on optimized assignment s Calculating the critical acceleration a of the slope c ；
Critical acceleration a on a slope c Based on the known seismic peak acceleration value PGA, calculating the earthquake-induced slope displacement D n ；
According to earthquake-induced slope displacement D n And calculating the landslide occurrence probability P of the target landslide area, and finishing the earthquake landslide risk evaluation of the target landslide area.
With reference to the first aspect of the present application, in a first possible implementation manner of the first aspect of the present application, determining a historical seismic landslide density of a target seismic landslide according to seismic landslide data includes:
and calculating the historical seismic landslide density by using a nuclear density algorithm and taking 5km as a search radius in the seismic landslide data.
With reference to the first aspect of the present application, in a second possible implementation manner of the first aspect of the present application, in a process of adjusting a model parameter, an adopted static safety factor formula is:
wherein c' is cohesion, gamma is the weight of the rock mass, t is the thickness of the potential sliding body, alpha is the inclination angle of the potential sliding surface,
for the effective internal friction angle, m is the proportion of saturated portion in the potential slip to the total slip thickness, γ w Is the groundwater gravity.
With reference to the first aspect of the present application, in a third possible implementation manner of the first aspect of the present application, the static safety factor F is calculated s In the optimization assignment process, the adopted static safety factor optimization assignment formula is as follows:
with reference to the first aspect of the present application, in a fourth possible implementation manner of the first aspect of the present application, the slope critical acceleration a is calculated c In the process, the formula of the slope critical acceleration is as follows:
where g is the gravitational acceleration and α is the potential slip plane inclination.
With reference to the first aspect of the present application, in a fifth possible implementation manner of the first aspect of the present application, the earthquake-induced slope displacement D is calculated n In the process of (1), adoptThe formula of the earthquake-induced slope displacement is as follows:
with reference to the first aspect of the present application, in a sixth possible implementation manner of the first aspect of the present application, in the process of calculating the landslide occurrence probability P of the target landslide area, an adopted landslide occurrence probability calculation formula is as follows:
P＝0.335[1-exp(-0.048D n 1.565 )]。
in a second aspect, the application provides an LS-D-Newmark earthquake landslide risk evaluation device, which includes:
the acquisition unit is used for acquiring seismic landslide data of the target seismic landslide;
the determining unit is used for determining the historical earthquake landslide density of the target earthquake landslide according to the earthquake landslide data;
the adjusting unit is used for inputting the earthquake landslide data into the LS-D-Newmark model and adjusting relevant model parameters by utilizing rock-soil body mechanical parameters and slope body dynamic parameters so as to ensure that the static safety coefficient F of the slope under the action of no external power s Greater than 1;
an optimization unit for substituting historical earthquake landslide density into the LS-D-Newmark model to add a historical earthquake landslide factor and for a static safety factor F s Carrying out optimized assignment;
a calculation unit for optimizing the assigned static safety factor F s Calculating the critical acceleration a of the slope c ；
A calculation unit for the critical acceleration a on the slope c Based on the known seismic peak acceleration value PGA, calculating the earthquake-induced slope displacement D n ；
A computing unit for further inducing a slope displacement D according to the earthquake n And calculating the landslide occurrence probability P of the target landslide area, and finishing the earthquake landslide risk evaluation of the target landslide area.
With reference to the second aspect of the present application, in a first possible implementation manner of the second aspect of the present application, the determining unit is specifically configured to:
and calculating historical seismic landslide density by using a kernel density algorithm and taking 5km as a search radius in the seismic landslide data.
With reference to the second aspect of the present application, in a second possible implementation manner of the second aspect of the present application, in the process of adjusting the model parameters, a static safety factor formula is adopted as follows:
wherein c' is cohesive force, gamma is the weight of the rock mass, t is the thickness of the potential sliding body, alpha is the inclination angle of the potential sliding surface,
for effective internal friction angle, m is the proportion of saturated portion in the potential slide to the total slide thickness, γ w Is the groundwater gravity.
With reference to the second aspect of the present application, in a third possible implementation manner of the second aspect of the present application, the static safety factor F is set s In the optimization assignment process, the adopted static safety factor optimization assignment formula is as follows:
with reference to the second aspect of the present application, in a fourth possible implementation manner of the second aspect of the present application, the slope critical acceleration a is calculated c In the process, the formula of the slope critical acceleration is as follows:
where g is the gravitational acceleration and α is the potential slip plane inclination.
With reference to the second aspect of the present application, in a fifth possible implementation manner of the second aspect of the present application, the earthquake-induced slope displacement D is calculated n In the process, the formula of the earthquake-induced slope displacement is as follows:
with reference to the second aspect of the present application, in a sixth possible implementation manner of the second aspect of the present application, in the process of calculating the landslide occurrence probability P of the target landslide area, an adopted landslide occurrence probability calculation formula is as follows:
P＝0.335[1-exp(-0.048D n 1.565 )]。
in a third aspect, the present application provides a processing device, which includes a processor and a memory, where the memory stores a computer program, and the processor executes the method provided by the first aspect of the present application or any one of the possible implementation manners of the first aspect of the present application when calling the computer program in the memory.
In a fourth aspect, the present application provides a computer-readable storage medium storing a plurality of instructions, which are suitable for being loaded by a processor to perform the method provided by the first aspect of the present application or any one of the possible implementation manners of the first aspect of the present application.
From the above, the present application has the following advantageous effects:
aiming at predicting the earthquake landslide danger, the method optimizes a Newmark model, configures an LS-D-Newmark model on the basis of the Newmark model, determines the historical earthquake landslide density of the target earthquake landslide according to the earthquake landslide data after acquiring the earthquake landslide data of the target earthquake landslide, inputs the earthquake landslide data into the LS-D-Newmark model, and adjusts related model parameters by using rock-soil body mechanical parameters and slope body dynamic parameters, so that the static safety coefficient F of the slope under the action of no external power is realized s If the static safety factor is larger than 1, then historical earthquake landslide density is brought into the LS-D-Newmark model to add historical earthquake landslide factors, and the static safety factor F is set s Carrying out optimized assignment, wherein the optimized assignment is based on the static safety factor F s Calculating the critical acceleration a of the slope c Then at the critical acceleration a of the slope c On the basis, the known earthquake peak acceleration value PGA is utilized to calculate earthquake-induced slope displacement D n Finally according to the earthquake induced slope displacement D n The landslide occurrence probability P of the target landslide area is calculated, the earthquake landslide risk evaluation of the target landslide area is completed, in the process, the historical earthquake landslide density is used as an influence factor to participate in the earthquake landslide risk evaluation, and the rock-soil body structure and the stability of the historical earthquake landslide area are reduced compared with the area without the earthquake landslide, so that the situation that the existing historical earthquake landslide area is low in risk in the risk evaluation result is avoided, and after the method is applied, the prediction accuracy of the earthquake landslide risk evaluation method based on the LS-D-Newmark model and the traditional Newmark model is improved to a certain extent, and the method is high in applicability.
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In order to more clearly illustrate the technical solutions in the embodiments of the present application, the drawings required to be used in the description of the embodiments are briefly introduced below, and it is obvious that the drawings in the description below are only some embodiments of the present application, and it is obvious for those skilled in the art to obtain other drawings based on these drawings without creative efforts.
FIG. 1 is a schematic flow chart of the LS-D-Newmark earthquake landslide risk evaluation method of the present application;
FIG. 2 is a schematic diagram of an application scenario of the LS-D-Newmark earthquake landslide risk evaluation method of the present application;
FIG. 3 is a schematic illustration of the historical seismic landslide density of the fresh water river fault zone of the present application;
FIG. 4 is a schematic diagram of an LS-D-Newmark model-based earthquake landslide risk assessment partition of the present application;
FIG. 5 is a schematic diagram illustrating a comparative earthquake landslide risk zone based on different risk evaluation methods according to the present application;
FIG. 6 is a schematic structural diagram of the LS-D-Newmark earthquake landslide risk assessment device of the present application;
FIG. 7 is a schematic diagram of a processing apparatus according to the present application.
Detailed Description
The technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the drawings in the embodiments of the present application, and it is obvious that the described embodiments are only a part of the embodiments of the present application, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present application.
The terms "first," "second," and the like in the description and in the claims of the present application and in the above-described drawings are used for distinguishing between similar elements and not necessarily for describing a particular sequential or chronological order. It will be appreciated that the data so used may be interchanged under appropriate circumstances such that the embodiments described herein may be practiced otherwise than as specifically illustrated or described herein. Moreover, the terms "comprises," "comprising," and "having," and any variations thereof, are intended to cover a non-exclusive inclusion, such that a process, method, system, article, or apparatus that comprises a list of steps or modules is not necessarily limited to those steps or modules explicitly listed, but may include other steps or modules not expressly listed or inherent to such process, method, article, or apparatus. The naming or numbering of the steps appearing in the present application does not mean that the steps in the method flow have to be executed in the chronological/logical order indicated by the naming or numbering, and the named or numbered process steps may be executed in a modified order depending on the technical purpose to be achieved, as long as the same or similar technical effects are achieved.
The division of the modules presented in this application is a logical division, and in practical applications, there may be another division, for example, multiple modules may be combined or integrated into another system, or some features may be omitted, or not executed, and in addition, the shown or discussed coupling or direct coupling or communication connection between each other may be through some interfaces, and the indirect coupling or communication connection between the modules may be in an electrical or other similar form, which is not limited in this application. The modules or sub-modules described as separate components may or may not be physically separated, may or may not be physical modules, or may be distributed in a plurality of circuit modules, and some or all of the modules may be selected according to actual needs to achieve the purpose of the present disclosure.
Before introducing the LS-D-Newmark earthquake landslide risk evaluation method provided by the present application, first, the background content related to the present application is introduced.
The LS-D-Newmark earthquake landslide risk evaluation method, the LS-D-Newmark earthquake landslide risk evaluation device and the computer readable storage medium can be applied to processing equipment and are used for adding historical earthquake landslide density factors when the Newmark model is used for predicting earthquake landslide risk so as to further improve the prediction precision of the earthquake landslide risk.
According to the LS-D-Newmark earthquake landslide risk evaluation method, an execution main body can be an LS-D-Newmark earthquake landslide risk evaluation device, or different types of processing Equipment such as a server, a physical host or User Equipment (UE) integrated with the LS-D-Newmark earthquake landslide risk evaluation device. The LS-D-Newmark earthquake landslide risk evaluation device may be implemented in a hardware or software manner, the UE may specifically be a terminal device such as a smart phone, a tablet computer, a notebook computer, a desktop computer, or a Personal Digital Assistant (PDA), and the processing device may be set in a device cluster manner.
The LS-D-Newmark earthquake landslide risk evaluation method provided by the application is introduced.
First, referring to fig. 1, fig. 1 shows a schematic flow diagram of the LS-D-Newmark earthquake landslide risk evaluation method according to the present application, and the LS-D-Newmark earthquake landslide risk evaluation method according to the present application may specifically include the following steps S101 to S107:
s101, acquiring seismic landslide data of a target seismic landslide;
it can be understood that the seismic landslide data can be similar to the data content involved in the evaluation of the risk of seismic landslide based on the Newmark model in the prior art, and the optimized data processing is performed on the basis of the initial data, namely the seismic landslide data.
Of course, in specific applications, the present application may also relate to further optimization processing in terms of data acquisition modes or data contents of the seismic landslide data related to the evaluation of the risk of seismic landslide.
For example, in practical application, the seismic landslide data may be extracted from a pre-established seismic landslide database, which is easily understood to be specially logged in and stored in different areas for later data calling.
The earthquake landslide database can be obtained by establishing a data source in the aspects of remote sensing interpretation, historical data collection or field on-site investigation and the like as a practical implementation mode.
Step S102, determining the historical earthquake landslide density of the target earthquake landslide according to the earthquake landslide data;
it can be understood that, when the earthquake Landslide risk evaluation is performed based on a Newmark model, the Newmark model is optimally set, that is, the earthquake Landslide risk evaluation is performed based on an LS-D-Newmark model configured in the present application, a factor of historical earthquake Landslide Density (LS-D) is added to the Newmark model (i.e., landslide-Density-Newmark model), and correspondingly, the input parameters of the model are also optimally set, that is, the factor of historical earthquake Landslide Density referred to herein.
Correspondingly, on the basis of the seismic landslide data obtained in the front, the method can determine the historical seismic landslide density based on the directly described or potential (data processing required) related geological characteristics, and provide data support for the rear.
As another practical implementation, the historical seismic landslide density may be calculated by a kernel density algorithm according to the seismic landslide data and with 5km as a search radius.
The kernel density algorithm is a pre-configured search algorithm and is used for searching the landslide density of the earthquake.
It should be understood that, the kernel density algorithm may be directly configured, and algorithms in other aspects may also be used, for example, a kernel density algorithm in the ArcGIS software spatial analysis may be used, so that the requirement of density search may be satisfied.
Step S103, inputting the earthquake landslide data into an LS-D-Newmark model, and adjusting relevant model parameters according to rock-soil body mechanical parameters and slope body dynamic parameters to enable the slope to have a static safety coefficient F under the action of no external power s Greater than 1;
it can be understood that the adjustment of the model parameters is realized by utilizing rock-soil body mechanical parameters and slope body configuration parameters through multiple cyclic iterative computations, and the adjustment of the model parameters is based on a Newmark model and is used for providing an effective model parameter environment for subsequent data processing, so that the static safety factor F of a slope in the model under the action of no external power s Greater than 1.
As another practical implementation manner, in the process of adjusting the model parameters, a static safety factor formula (a slope safety factor formula based on a slider limit balance theory of the Newmark model) may specifically be:
wherein c' is cohesion (kPa), and gamma is rock mass gravity (kN/m) 3 ) T is the potential slide thickness (m), α is the potential slide inclination angle,
effective internal friction angle (°), m is the proportion of saturated portions of the potential slip to the total slip thickness, γ w Is the groundwater gravity (kN/m) 3 )。
Step S104, introducing historical earthquake landslide density into the LS-D-Newmark model to add historical earthquake landslide factor, and adding the static safety factor F s Carrying out optimized assignment;
as mentioned above, the optimized setting of the input parameters of the LS-D-Newmark model can be embodied by historical seismic landslide density factors.
At this time, the previously determined historical seismic landslide density can be substituted into the LS-D-Newmark model with optimized model parameters, and in the model, a static safety factor F is carried out based on the input historical seismic landslide density s And (4) optimizing and assigning values.
Briefly, the processing performed herein may be understood as a static safety factor F due to the lower stability of the historical seismic landslide area relative to the non-historical seismic landslide area s The static safety factor F is lower, but the historical earthquake landslide area does not generate deformation sliding under the action of no external force s Still greater than 1, in which case the application is directed to a static factor of safety F s Optimizing, adding earthquake landslide density factor, and comparing the static safety factor F s Carrying out optimized assignment to distinguish static safety factors F of the earthquake landslide area and the non-historical earthquake landslide area s In the calculation, the earthquake landslide area and the non-historical earthquake landslide area are subjected to more definite and clear subdivision processing in the model, so that the subsequent earthquake landslide risk evaluation can be subjected to more detailed processing.
As another practical implementation, the present application is directed to the static safety factor F s In the process of performing optimized assignment, the adopted static safety factor optimized assignment formula can be specifically as follows:
it should be understood that the present application optimizes the static safety factor F based on the historical seismic landslide density factor s A floor plan is proposed.
Step S105, based on the optimized static safety factor F after assignment s Calculating the critical acceleration a of the slope c ；
Static safety factor F after obtaining optimized assignment s InAfter the seismic landslide area and the non-historical seismic landslide area are subjected to more definite and clear subdivision processing in the model, the slope critical acceleration a can be continuously calculated c It can be understood that under the action of seismic dynamic load, the gliding force of the slide block is equal to the seismic dynamic acceleration corresponding to the anti-sliding force (in the limit balance state).
Specifically, as another practical implementation mode, the method establishes a slider limit balance state equation under the action of earthquake by comparing the stress states of the slider under the static force and earthquake dynamic conditions, namely, calculating the slope critical acceleration a c In the process, the adopted slope critical acceleration formula may specifically be:
wherein g is gravity acceleration (m/s) 2 ) And α is a potential slip angle (°).
Step S106, at the critical acceleration a of the slope c Based on the known seismic peak acceleration value PGA, calculating the earthquake-induced slope displacement D n ；
At the moment of obtaining the critical acceleration a of the slope c Then, the earthquake-induced slope displacement D can be continued n Is easy to understand, the earthquake induced slope displacement D is positioned in n And the seismic landslide area and the non-historical seismic landslide area are also distinguished.
The known seismic peak acceleration value PGA is public and general data, and for example, in practical applications, the known seismic peak acceleration value PGA in "chinese seismic peak acceleration plot" (GB 18306-2015) with a 50-year overrun probability of 10% may be specifically used.
In addition, the method obtains the earthquake-induced slope accumulated displacement D by statistically analyzing a large number of earthquake acceleration records and earthquake landslide examples n Critical acceleration of slope a c And seismic peak acceleration PGA, i.e. as yet another practical implementation, where the calculation is madeEarthquake-induced slope displacement D n In the process, the adopted earthquake-induced slope displacement formula is as follows:
it can also be seen that in the landing scheme here, the slope accumulates the displacement D n Proportional to the seismic oscillation peak acceleration PGA and the slope critical acceleration a c In inverse proportion.
Step S107, according to earthquake induced slope displacement D n And calculating the landslide occurrence probability P of the target landslide area, and finishing the earthquake landslide risk evaluation of the target landslide area.
While winning the earthquake-induced slope displacement D n Then, according to the corresponding relation between the induced slope displacement and the landslide occurrence probability, the corresponding landslide occurrence probability P can be determined and used as the earthquake landslide risk evaluation result of the target landslide area.
As another practical implementation manner, the present application also provides a set of landing schemes for calculating the occurrence probability P of the landslide, that is, in the process of calculating the occurrence probability P of the landslide in the target landslide area, the adopted formula for calculating the occurrence probability of the landslide may specifically be:
P＝0.335[1-exp(-0.048DD n 1.565 )]。
further, on the basis that the landslide occurrence probability P is used as the earthquake landslide risk evaluation result, the method can also involve risk zoning, namely, earthquake landslide risk zoning is performed on the whole earthquake landslide area according to the landslide occurrence probabilities P of different target earthquake landslide areas so as to divide areas with different earthquake landslide risks.
Under the setting, obviously, more detailed data guidance can be provided for practical application.
For further understanding of the contents of the above schemes (including contents of various exemplary embodiments), a further understanding can be performed by the following example on the basis of an application scenario diagram of the LS-D-Newmark earthquake landslide risk assessment method of the present application shown in fig. 2.
The method is characterized in that the positions about 20km on two sides of a fresh water river fracture zone in Sichuan province are taken as research areas, and earthquake landslide risk calculation is carried out through an earthquake landslide risk evaluation method based on an LS-D-Newmark model. The earthquake landslide risk evaluation based on the LS-D-Newmark model is completed by adding a factor of historical earthquake landslide density on the basis of the Newmark model, and mainly comprises the following processing flows:
and establishing a fresh water river fracture zone historical earthquake landslide database through remote sensing interpretation, historical data collection and field on-site investigation.
According to the established fresh water river fracture zone earthquake landslide database, the historical earthquake landslide density (place/km) of the fresh water river fracture zone is obtained by using a nuclear density algorithm in ArcGIS software space analysis and taking 5km as a search radius 2 ) The earthquake landslides in the research area are mainly distributed along the fracture zone of the fresh water river in a strip shape, wherein the highest density of the earthquake landslides reaches 0.64 position/km 2 。
The historical earthquake landslide density of the fresh water river fracture zone can refer to a schematic diagram of the historical earthquake landslide density of the fresh water river fracture zone in the application shown in fig. 3.
And acquiring the terrain slope of the fresh water river fracture zone according to the terrain data.
And (4) comprehensively considering factors such as geological structure, stratum age, rock and soil body type, rock weathering and crushing degree and the like, and dividing engineering geological rock groups in the research area.
The physical-mechanical parameters representing the set of engineered geological rocks shown are comprehensively initialized according to the handbook of engineering geology (fifth edition).
Remarking: c' is the cohesive force of the polymer,
the effective internal friction angle, γ is the rock mass weight.
According to the slope safety coefficient based on the slider limit balance theoryThe static safety factor F of the regional slope body is calculated by using the mechanical parameters of the rock-soil body and the morphological parameters of the slope body in the formula (1) s The slope does not deform and slide under the action of no external force, so the static safety factor F s Greater than 1.
Because the stability of the earthquake landslide in the historic earthquake landslide area is lower, the static safety factor F s The static safety factor F of the earthquake landslide area is lower, but the deformation sliding does not occur in the history earthquake landslide area under the action of no external force s Still greater than 1, for static safety factor F s Optimizing and adjusting a formula, adding an earthquake landslide factor, and distinguishing static safety factors F of an earthquake landslide area and a non-historical earthquake landslide area s And (4) calculating.
The addition of the density factor of the earthquake landslide avoids higher stability of a historical earthquake landslide region or lower danger of landslide induced by earthquake, and the static safety factor F is obtained by the following formula (2) s And carrying out optimized assignment.
By comparing the stress states of the slide block under the static and earthquake dynamic conditions, an extreme balance state equation of the slide block under the earthquake action can be established, and the static safety factor F is utilized s (obtained by the equation 2) to derive a slope critical acceleration a c Formula (3);
calculating the critical acceleration a of the research area by the formula (3) c 。
Establishing earthquake-induced slope accumulated displacement D by statistically analyzing a large number of earthquake acceleration records and earthquake landslide instances n Critical acceleration of slope a c And seismic peak additionThe speed PGA (equation 4).
Wherein, the partition value of 'Chinese earthquake peak acceleration zone chart' (GB 18306-2015) with 50-year surpassing probability of 10% is adopted to calculate earthquake-induced slope displacement D n 。
According to seismic slope displacement D n And calculating the landslide occurrence probability P under the action of the earthquake according to the correlation (formula 5) between the landslide occurrence probability P and the earthquake occurrence probability P.
P＝0.335[1-exp(-0.048Dn 1.565 )] (5)
The earthquake landslide risk evaluation of the fresh water river fracture zone based on the LS-D-Newmark model is completed, wherein the earthquake landslide risk evaluation zone results of the fresh water river fracture zone can refer to a schematic diagram of the earthquake landslide risk evaluation zone based on the LS-D-Newmark model shown in fig. 4, and the comparison with the traditional Newmark model can refer to a comparison schematic diagram of the earthquake landslide risk zone based on different risk evaluation methods shown in fig. 5.
In summary, it can be seen from the above contents that, aiming at prediction of earthquake landslide risk, the application optimizes a Newmark model, configures an LS-D-Newmark model on the basis of the Newmark model, determines historical earthquake landslide density of a target earthquake landslide according to earthquake landslide data after acquiring the earthquake landslide data of the target earthquake landslide, inputs the earthquake landslide data into the LS-D-Newmark model, and adjusts related model parameters by using rock-soil body mechanical parameters and slope body configuration parameters, so that a static safety coefficient F of a slope under the action of no external power is enabled s If the static safety factor is larger than 1, continuously bringing historical earthquake landslide density into the LS-D-Newmark model to add historical earthquake landslide factors, and carrying out F on the static safety factor s Carrying out optimized assignment, wherein the optimized assignment is based on the static safety factor F s Calculating the critical acceleration a of the slope c Then the critical acceleration a of the slope c On the basis of the known seismic peak acceleration value PGACalculating the earthquake-induced slope displacement D n Finally according to the earthquake induced slope displacement D n The landslide occurrence probability P of the target landslide area is calculated, the earthquake landslide risk evaluation of the target landslide area is completed, in the process, the historical earthquake landslide density is used as an influence factor to participate in the earthquake landslide risk evaluation, and the rock-soil body structure and the stability of the historical earthquake landslide area are reduced compared with the area without the earthquake landslide, so that the situation that the existing historical earthquake landslide area is low in risk in the risk evaluation result is avoided, and after the method is applied, the prediction accuracy of the earthquake landslide risk evaluation method based on the LS-D-Newmark model and the traditional Newmark model is improved to a certain extent, and the method is high in applicability.
The LS-D-Newmark earthquake landslide risk evaluation method is introduced, and the LS-D-Newmark earthquake landslide risk evaluation device is provided from the perspective of a functional module, so that the LS-D-Newmark earthquake landslide risk evaluation method provided by the application is better implemented.
Referring to fig. 6, fig. 6 is a schematic structural diagram of the LS-D-Newmark earthquake landslide risk evaluation apparatus according to the present application, in which the LS-D-Newmark earthquake landslide risk evaluation apparatus 600 may specifically include the following structure:
an acquisition unit 601 configured to acquire seismic landslide data of a target seismic landslide;
a determining unit 602, configured to determine a historical seismic landslide density of the target seismic landslide according to the seismic landslide data;
an adjusting unit 603, configured to input the landslide data into the LS-D-Newmark model, and adjust relevant model parameters according to the rock-soil body mechanical parameters and the slope body configuration parameters, so that the static safety factor F of the slope under the action of no external power s Greater than 1;
an optimization unit 604 for substituting the historical seismic landslide density into the LS-D-Newmark model to add a historical seismic landslide factor and for a static safety factor F s Carrying out optimized assignment;
a calculation unit 605 for calculating the static safety factor based on the optimized assignmentF s Calculating the critical acceleration a of the slope c ；
A calculation unit 605, also for the critical acceleration a on the slope c On the basis, the known earthquake peak acceleration value PGA is utilized to calculate earthquake-induced slope displacement D n ；
A computing unit 605 for further inducing a slope displacement D according to the earthquake n And calculating the landslide occurrence probability P of the target landslide area, and finishing the earthquake landslide risk evaluation of the target landslide area.
In an exemplary implementation manner, the determining unit is specifically configured to:
and calculating the historical seismic landslide density by using a nuclear density algorithm and taking 5km as a search radius in the seismic landslide data.
In another exemplary implementation, in the process of adjusting the model parameters, the static safety factor formula is:
wherein c' is cohesive force, gamma is the weight of the rock mass, t is the thickness of the potential sliding body, alpha is the inclination angle of the potential sliding surface,
for effective internal friction angle, m is the proportion of saturated portion in the potential slide to the total slide thickness, γ w Is the groundwater gravity.
In yet another exemplary implementation, a static safety factor F is provided in the area of landslide to historical earthquakes s In the optimization assignment process, the adopted static safety factor optimization assignment formula is as follows:
in yet another exemplary implementation, the slope critical acceleration a is calculated c In the process, the formula of the slope critical acceleration is as follows:
where g is the gravitational acceleration and α is the potential slip plane inclination.
In yet another exemplary implementation, the seismic-induced slope displacement D is calculated n In the process, the adopted earthquake-induced slope displacement formula is as follows:
in still another exemplary implementation, in the calculating the landslide occurrence probability P of the target landslide area, the landslide occurrence probability calculation formula is adopted as follows:
P＝0.335[1-exp(-0.048D n 1.565 )]。
the present application further provides a processing device from a hardware structure perspective, referring to fig. 7, fig. 7 shows a schematic structural diagram of the processing device of the present application, specifically, the processing device of the present application may include a processor 701, a memory 702, and an input/output device 703, where the processor 701 is configured to implement, when executing a computer program stored in the memory 702, the steps of the LS-D-Newmark earthquake landslide risk evaluation method in the corresponding embodiment of fig. 1; alternatively, the processor 701 is configured to implement the functions of the units in the embodiment corresponding to fig. 6 when executing the computer program stored in the memory 702, and the memory 702 is configured to store the computer program required by the processor 701 to execute the LS-D-Newmark earthquake landslide risk assessment method in the embodiment corresponding to fig. 1.
Illustratively, a computer program may be partitioned into one or more modules/units, which are stored in memory 702 and executed by processor 701 to complete the present application. One or more modules/units may be a series of computer program instruction segments capable of performing certain functions, the instruction segments being used to describe the execution of the computer program in the computer apparatus.
The processing devices may include, but are not limited to, a processor 701, a memory 702, and input-output devices 703. Those skilled in the art will appreciate that the illustration is merely an example of a processing device and does not constitute a limitation of the processing device and may include more or less components than those illustrated, or combine certain components, or different components, for example, the processing device may further include a network access device, a bus, etc., and the processor 701, the memory 702, the input output device 703, etc., are connected by the bus.
The Processor 701 may be a Central Processing Unit (CPU), other general purpose Processor, a Digital Signal Processor (DSP), an Application Specific Integrated Circuit (ASIC), a Field Programmable Gate Array (FPGA) or other Programmable logic device, discrete Gate or transistor logic, discrete hardware components, etc. The general purpose processor may be a microprocessor or the processor may be any conventional processor or the like, the processor being the control center for the processing device and the various interfaces and lines connecting the various parts of the overall device.
The memory 702 may be used to store computer programs and/or modules, and the processor 701 implements various functions of the computer apparatus by running or executing the computer programs and/or modules stored in the memory 702 and invoking data stored in the memory 702. The memory 702 may mainly include a program storage area and a data storage area, wherein the program storage area may store an operating system, an application program required for at least one function, and the like; the storage data area may store data created according to use of the processing apparatus, and the like. In addition, the memory may include high speed random access memory, and may also include non-volatile memory, such as a hard disk, a memory, a plug-in hard disk, a Smart Media Card (SMC), a Secure Digital (SD) Card, a Flash memory Card (Flash Card), at least one magnetic disk storage device, a Flash memory device, or other volatile solid state storage device.
The processor 701, when executing the computer program stored in the memory 702, may specifically implement the following functions:
acquiring earthquake landslide data of a target earthquake landslide;
determining the historical earthquake landslide density of the target earthquake landslide according to the earthquake landslide data;
inputting the earthquake landslide data into an LS-D-Newmark model, and adjusting related model parameters according to rock-soil body mechanical parameters and slope body morphological parameters to ensure that the static safety coefficient F of the slope under the action of no external power s Greater than 1; introducing historical earthquake landslide density into LS-D-Newmark model to add historical earthquake landslide factor, and introducing static safety factor F s Carrying out optimized assignment;
static safety factor F based on optimized assignment s Calculating the critical acceleration a of the slope c ；
Critical acceleration a on the slope c Based on the known seismic peak acceleration value PGA, calculating the earthquake-induced slope displacement D n ；
According to earthquake-induced slope displacement D n And calculating the landslide occurrence probability P of the target landslide area, and finishing the earthquake landslide risk evaluation of the target landslide area.
It can be clearly understood by those skilled in the art that, for convenience and brevity of description, the specific working processes of the LS-D-Newmark earthquake landslide hazard evaluation apparatus, the processing device and the corresponding units thereof described above may refer to the description of the LS-D-Newmark earthquake landslide hazard evaluation method in the corresponding embodiment of fig. 1, and are not described herein in detail.
It will be understood by those skilled in the art that all or part of the steps of the methods of the above embodiments may be performed by instructions or by associated hardware controlled by the instructions, which may be stored in a computer readable storage medium and loaded and executed by a processor.
For this reason, the present application provides a computer-readable storage medium, where a plurality of instructions are stored, where the instructions can be loaded by a processor to execute the steps of the LS-D-Newmark earthquake landslide risk evaluation method in the embodiment corresponding to fig. 1 in the present application, and specific operations may refer to the description of the LS-D-Newmark earthquake landslide risk evaluation method in the embodiment corresponding to fig. 1, and are not described herein again.
Wherein the computer-readable storage medium may include: read Only Memory (ROM), random Access Memory (RAM), magnetic or optical disks, and the like.
Since the instructions stored in the computer-readable storage medium can execute the steps of the LS-D-Newmark earthquake landslide risk evaluation method in the embodiment corresponding to fig. 1, the beneficial effects that can be achieved by the LS-D-Newmark earthquake landslide risk evaluation method in the embodiment corresponding to fig. 1 can be achieved, which are described in detail in the foregoing description and are not described herein again.
The LS-D-Newmark earthquake landslide risk evaluation method, device, processing device, and computer-readable storage medium provided by the present application are introduced in detail above, and specific examples are applied herein to explain the principles and embodiments of the present application, and the descriptions of the above embodiments are only used to help understand the method and core ideas of the present application; meanwhile, for those skilled in the art, according to the idea of the present application, the specific implementation manner and the application scope may be changed, and in summary, the content of the present specification should not be construed as a limitation to the present application.
Claims (10)
1. An LS-D-Newmark earthquake landslide risk evaluation method is characterized by comprising the following steps:
acquiring earthquake landslide data of a target earthquake landslide;
determining the historical seismic landslide density of the target seismic landslide according to the seismic landslide data;
inputting the seismic landslide data into an LS-D-Newmark model, and adjusting related model parameters according to rock-soil body mechanical parameters and slope body dynamic parameters to enable the static safety coefficient F of the slope under the action of no external power s Greater than 1;
introducing the historical seismic landslide density into the LS-D-Newmark model to add a historical seismic landslide factor, and applying the static safety factor F s Carrying out optimized assignment;
based on optimizing endowingSaid static safety factor F after value s Calculating the critical acceleration a of the slope c ；
Critical acceleration a on the slope c Based on the known seismic peak acceleration value PGA, calculating the earthquake-induced slope displacement D n ；
According to the earthquake-induced slope displacement D n And calculating the landslide occurrence probability P of the target landslide area, and finishing the earthquake landslide risk evaluation of the target landslide area.
2. The method of claim 1, wherein determining the historical seismic landslide density of the target seismic landslide from the seismic landslide data comprises:
and calculating the historical seismic landslide density by using a kernel density algorithm and 5km as a search radius in the seismic landslide data.
3. The method of claim 1, wherein in adjusting the model parameters, a static safety factor formula is used:
wherein c' is cohesion, gamma is the weight of the rock mass, t is the thickness of the potential sliding body, alpha is the inclination angle of the potential sliding surface,
for effective internal friction angle, m is the proportion of saturated portion in the potential slide to the total slide thickness, γ w Is the groundwater gravity.
4. The method of claim 1, characterized in that for said static safety factor F s In the optimization assignment process, the adopted static safety factor optimization assignment formula is as follows:
5. method according to claim 1, characterized in that the slope critical acceleration a is calculated c In the process, the formula of the slope critical acceleration is as follows:
where g is the gravitational acceleration and α is the potential slip plane inclination.
6. The method of claim 1, wherein D is calculated after the seismic-induced slope displacement is calculated n In the process, the adopted earthquake-induced slope displacement formula is as follows:
7. the method according to claim 1, wherein in calculating the landslide occurrence probability P of the target landslide region, the landslide occurrence probability is calculated using the formula:
P＝0.335[1―exp(―0.048D n 1.565 )]。
8. an LS-D-Newmark earthquake landslide risk evaluation device, comprising:
the acquisition unit is used for acquiring seismic landslide data of the target seismic landslide;
the determining unit is used for determining the historical seismic landslide density of the target seismic landslide according to the seismic landslide data;
an adjusting unit for inputting the seismic landslide data into LS-D-Newmark modelAdjusting related model parameters according to the mechanical parameters of the rock-soil body and the morphological parameters of the slope body to ensure that the slope has a static safety factor F under the action of no external power s Greater than 1;
an optimization unit for substituting the historical seismic landslide density into the LS-D-Newmark model to add a historical seismic landslide factor and the static safety factor F s Carrying out optimized assignment;
a calculation unit for optimizing the assigned static safety factor F s Calculating the critical acceleration a of the slope c ；
The calculation unit is also used for calculating the critical acceleration a of the slope c On the basis, the known earthquake peak acceleration value PGA is utilized to calculate earthquake-induced slope displacement D n ；
The computing unit is also used for inducing slope displacement D according to the earthquake n And calculating the landslide occurrence probability P of the target landslide area, and finishing the earthquake landslide risk evaluation of the target landslide area.
9. A processing device comprising a processor and a memory, a computer program being stored in the memory, the processor performing the method according to any of claims 1 to 7 when calling the computer program in the memory.
10. A computer-readable storage medium storing a plurality of instructions adapted to be loaded by a processor to perform the method of any one of claims 1 to 7.
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