CN115238441B - 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, an LS-D-Newmark earthquake landslide risk evaluation device and processing equipment, which are used for adding a historical earthquake landslide density factor when forecasting the earthquake landslide risk by using a Newmark model, so that the forecasting precision of the earthquake landslide risk is further improved. The method comprises the following steps: acquiring seismic landslide data of a target seismic landslide; according to the seismic landslide data, determining the historical seismic landslide density of the target seismic landslide; inputting the seismic landslide data into an LS-D-Newmark model, and adjusting related model parameters by using rock-soil body mechanical parameters and slope form parameters to ensure that the slope has a static safety coefficient F under the action of no external power s Greater than 1; bringing the historic seismic landslide density to LS-D-Newmark model and to F s Performing optimization assignment; f based on optimization assignment s Calculating the critical acceleration a of the slope c The method comprises the steps of carrying out a first treatment on the surface of the At a c Based on (1), calculating the earthquake induced slope displacement D by using the known earthquake motion peak acceleration value PGA n The method comprises the steps of carrying out a first treatment on the surface of the According to D n And calculating the landslide occurrence probability P of the target landslide region.
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, an LS-D-Newmark earthquake landslide risk evaluation device and an LS-D-Newmark earthquake landslide risk evaluation processing device.
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 mass or soil body suddenly breaks away from a landslide source area and is instantaneously unstable due to earthquake vibration, the earthquake landslide risk is defined according to international landslide risk assessment, the earthquake is strictly used as a potential uncertain factor, the space-time distribution probability of the potential earthquake and the landslide induction is analyzed, and specific risk description factors comprise the position, volume or area of the potential earthquake landslide, the landslide type and migration velocity, the occurrence probability in a certain period and the like. It can be seen that the risk of earthquake landslide has clear predictive properties.
The current model method for evaluating the earthquake landslide hazard mainly comprises the following steps:
1. comprehensive evaluation method based on statistical analysis: based on statistical analysis of correlation between a seismic landslide and a seismic geological background, the control action of the seismic geological background on the landslide is revealed, the main control factors of the seismic landslide are excavated, and the evaluation and research of the risk of the seismic landslide based on multiple factors are completed by adopting methods such as a support vector machine, information quantity, logistic regression and the like;
2. pseudo-static method based on limit balance theory: decomposing seismic power acting on a slope body along a sliding surface (or the direction of the maximum gradient), and then calculating the ratio of the sliding force of the slope under the action of the seismic vibration to the sliding resistance to evaluate the risk of the slope;
3. newmark model based on slope accumulated displacement: and predicting and evaluating the risk of earthquake-induced landslide by calculating the slope displacement under the action of earthquake load.
In the research process of the prior related technology, the inventor finds that the currently adopted Newmark model carries out the seismic landslide risk evaluation through the terrain gradient, the rock-soil body mechanical parameter and the seismic peak acceleration (Peak Ground Acceleration, PGA), and still has the condition that the prediction precision is not kept stable or has the problem that the prediction precision is inaccurate to a certain extent.
Disclosure of Invention
The application provides an LS-D-Newmark earthquake landslide risk evaluation method, an LS-D-Newmark earthquake landslide risk evaluation device and processing equipment, which are used for adding a historical earthquake landslide density factor when forecasting the earthquake landslide risk by utilizing a Newmark model so as to further improve the forecasting precision of the earthquake landslide risk.
In a first aspect, the application provides an LS-D-Newmark seismic landslide risk evaluation method, which comprises the following steps:
acquiring seismic landslide data of a target seismic landslide;
according to the seismic landslide data, determining the historical seismic landslide density of the target seismic landslide;
inputting the seismic landslide data into an LS-D-Newmark model, and adjusting related model parameters by using rock-soil body mechanical parameters and slope form parameters to ensure that the static safety coefficient F of the slope under the action of no external power s Greater than 1;
bringing the historical seismic landslide density into LS-D-Newmark model to add the historical seismic landslide factor, and applying the static safety factor F to s Performing optimization assignment;
based on static safety coefficient F after optimization assignment s Calculating the critical acceleration a of the slope c ；
At a critical acceleration of slope a c Based on (1), calculating the earthquake induced slope displacement D by using the known earthquake motion peak acceleration value PGA n ；
According to earthquake induced slope displacement D n And calculating the landslide occurrence probability P of the target landslide area, and finishing the seismic 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 the target seismic landslide according to the seismic landslide data includes:
in the data according to the earthquake landslide, the historical earthquake landslide density is calculated by a nuclear density algorithm by taking 5km as a searching radius.
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, a static security coefficient formula is adopted as follows:
wherein c' is cohesive force, gamma is rock mass weight, t is potential sliding body thickness, alpha is potential sliding inclination angle,
for effective internal friction angle, m is the ratio of saturated part in potential sliding body to total sliding body thickness, gamma w Is the ground water gravity.
In a third possible implementation manner of the first aspect of the present application, in combination with the first aspect of the present application, the static security factor F s In the process of optimizing assignment, the adopted static safety coefficient optimizing assignment formula is as follows:
in a fourth possible implementation manner of the first aspect of the present application, in combination with the first aspect of the present application, the slope critical acceleration a is calculated c In the process of (2), the adopted slope critical acceleration formula is as follows:
wherein g is gravity acceleration, and alpha is potential slip angle.
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 seismic-induced slope displacement D is calculated n In the process of (2), the adopted earthquake induced slope displacement formula 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 a process of calculating a landslide occurrence probability P of a target landslide area, an adopted landslide occurrence probability calculation formula is:
P＝0.335[1-exp(-0.048D n 1.565 )]。
in a second aspect, the present application provides an LS-D-Newmark seismic landslide risk assessment apparatus, the apparatus comprising:
the acquisition unit is used for acquiring the 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 related model parameters by utilizing the rock-soil body mechanical parameters and the slope form parameters so as to enable the static safety coefficient F of the slope under the action of no external power s Greater than 1;
an optimizing unit for adding the historical seismic landslide factors to the LS-D-Newmark model and adding the static safety factor F to the model s Performing optimization assignment;
a calculation unit for optimizing the assigned static safety factor F s Calculating the critical acceleration a of the slope c ；
A calculating unit for calculating critical acceleration a at a slope c Based on (1), calculating the earthquake induced slope displacement D by using the known earthquake motion peak acceleration value PGA n ；
A computing unit for 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 seismic 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:
in the data according to the earthquake landslide, the historical earthquake landslide density is calculated by a nuclear density algorithm by taking 5km as a searching radius.
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 a process of adjusting a model parameter, a static safety coefficient formula is adopted as follows:
wherein c' is cohesive force, gamma is rock mass weight, t is potential sliding body thickness, alpha is potential sliding inclination angle,
for effective internal friction angle, m is the ratio of saturated part in potential sliding body to total sliding body thickness, gamma w Is the ground water gravity.
In a third possible implementation manner of the second aspect of the present application, in combination with the second aspect of the present application, the static security factor F s In the process of optimizing assignment, the adopted static safety coefficient optimizing assignment formula is as follows:
in a fourth possible implementation manner of the second aspect of the present application, in combination with the second aspect of the present application, the slope critical acceleration a is calculated c In the process of (2), the adopted slope critical acceleration formula is as follows:
wherein g is gravity acceleration, and alpha is potential slip angle.
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 seismic-induced slope displacement D is calculated n In the process of (2), the adopted earthquake induced slope displacement formula 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 calculating the landslide occurrence probability P of the target landslide area, an adopted landslide occurrence probability calculation formula is:
P＝0.335[1-exp(-0.048D n 1.565 )]。
in a third aspect, the present application provides a processing device, comprising a processor and a memory, the memory having stored therein a computer program, the processor executing the method provided by the first aspect of the present application or any one of the possible implementations 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 adapted to be loaded by a processor to perform the method provided in the first aspect of the present application or any one of the possible implementations of the first aspect of the present application.
From the above, the present application has the following advantages:
aiming at the prediction of the danger of the earthquake landslide, 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 objective earthquake landslide according to the earthquake landslide data after acquiring the earthquake landslide data of the objective earthquake landslide, inputs the earthquake landslide data into the LS-D-Newmark model, and adjusts related model parameters by utilizing the rock-soil body mechanical parameters and the slope shape parameters so as to ensure that the static safety coefficient F of the slope under the action of no external power s Is larger than 1, and then the historic earthquake landslide density is brought into the LS-D-Newmark model to add the historic earthquake landslide factor, and the static safety factor F is calculated s Performing optimization assignment, wherein the optimization assignment is based on the static safety coefficient F s Calculating the critical acceleration a of the slope c Then at the slope critical acceleration a c Based on (1), calculating the earthquake induced slope displacement D by using the known earthquake motion peak acceleration value PGA n Finally according to the earthquake induced slope displacement D n Calculating landslide occurrence probability P of a target landslide area, and finishing seismic landslide risk evaluation of the target landslide area, wherein in the process, historical seismic landslide is performedThe density is taken as an influence factor to participate in the risk evaluation of the earthquake landslide, and the structure and the stability of a rock-soil body in a historical earthquake landslide area are reduced compared with those in an area where the earthquake landslide does not occur, so that the situation that the risk of the existing historical earthquake landslide area is low in a risk evaluation result is avoided, and 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 after the application, and the applicability is higher.
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In order to more clearly illustrate the technical solutions of the embodiments of the present application, the drawings that are needed in the description of the embodiments will be briefly introduced below, it being obvious that the drawings in the following description are only some embodiments of the present application, and that other drawings may be obtained according to these drawings without inventive effort for a person skilled in the art.
FIG. 1 is a schematic flow chart of a method for evaluating the risk of an LS-D-Newmark seismic landslide of the application;
FIG. 2 is a schematic diagram of an application scenario of the LS-D-Newmark seismic landslide risk evaluation method of the present application;
FIG. 3 is a schematic view of the historical seismic landslide density of the fresh water river fracture zone of the present application;
FIG. 4 is a schematic diagram of a seismic landslide risk assessment partition based on LS-D-Newmark model in the present application;
FIG. 5 is a schematic diagram of a comparison of seismic landslide hazard partitions based on different hazard assessment methods of the present application;
FIG. 6 is a schematic structural view of the LS-D-Newmark seismic landslide risk evaluation device of the present application;
fig. 7 is a schematic view of a structure of the processing apparatus of the present application.
Detailed Description
The following description of the embodiments of the present application will be made clearly and fully with reference to the accompanying drawings, in which it is evident that the embodiments described are only some, but not all, of the embodiments of the present application. All other embodiments, which can be made by those skilled in the art based on the embodiments herein without making any inventive effort, are intended to be within the 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 figures, are used for distinguishing between similar objects and not necessarily for describing a particular sequential or chronological order. It is to be understood that the data so used may be interchanged where appropriate such that the embodiments described herein may be implemented in other sequences than those illustrated or otherwise described herein. Furthermore, 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 that are expressly listed or inherent to such process, method, article, or apparatus. The naming or numbering of the steps in the present application does not mean that the steps in the method flow must be executed according to the time/logic sequence indicated by the naming or numbering, and the execution sequence of the steps in the flow that are named or numbered may be changed according to the technical purpose to be achieved, so long as the same or similar technical effects can be achieved.
The division of the modules in the present application is a logical division, and may be implemented in another manner in practical application, for example, a plurality of modules may be combined or integrated in another system, or some features may be omitted or not implemented, and in addition, coupling or direct coupling or communication connection between the modules that are shown or discussed may be through some interfaces, and 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 separate, 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 purposes of the present application.
Before describing the LS-D-Newmark seismic landslide risk evaluation method provided by the application, the background content related to the application is first described.
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 used for adding historical earthquake landslide density factors when the Newmark model is used for carrying out earthquake landslide risk prediction processing so as to further improve the prediction accuracy of 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) and the like integrated with the LS-D-Newmark earthquake landslide risk evaluation device. The LS-D-Newmark earthquake landslide risk evaluation device can be realized in a hardware or software mode, the UE can be specifically terminal equipment such as a smart phone, a tablet personal computer, a notebook computer, a desktop computer or a personal digital assistant (Personal Digital Assistant, PDA) and the processing equipment can be arranged in an equipment cluster mode.
The LS-D-Newmark seismic landslide risk evaluation method provided by the application is initially described.
Firstly, referring to fig. 1, fig. 1 shows a flow chart of an LS-D-Newmark seismic landslide risk evaluation method according to the present application, where the LS-D-Newmark seismic landslide risk evaluation method specifically includes steps S101 to S107:
step S101, obtaining 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 seismic landslide risk evaluation based on a Newmark model in the prior art, and the optimized data processing performed by the method is performed on the basis of initial data, namely the seismic landslide data.
Of course, in specific applications, the application may also relate to further optimization processing on aspects such as a data acquisition mode or data content of the seismic landslide data related to the seismic landslide risk evaluation.
For example, in practical application, the seismic landslide data may be extracted from a pre-established seismic landslide database, which is easy to understand, and is specially used for logging in and storing the seismic landslide data of different areas for later data recall.
The earthquake landslide database is used as a practical implementation mode and can be established by remote sensing interpretation, historical data collection or field investigation and other data sources.
Step S102, according to the seismic landslide data, determining the historical seismic landslide density of the target seismic landslide;
it can be understood that when the seismic Landslide risk evaluation is performed based on the Newmark model, the Newmark model is optimally set, that is, the seismic Landslide risk evaluation is performed based on the LS-D-Newmark model configured by the application, and the LS-D-Newmark model (namely, the Landside-Density-Newmark model) is added with the factor of the historical seismic Landslide Density (Landslide Density, LS-D) on the basis of the Newmark model, and correspondingly, the input parameters of the model are also optimally set, that is, the historical seismic Landslide Density factor referred to herein.
Correspondingly, on the basis of the seismic landslide data obtained in the front, the method can be used for determining and processing the historical seismic landslide density based on the direct description or the potential (data processing required) related geological characteristics, and data support is provided for the rear.
As yet another implementation suitable for practical use, the historical seismic landslide density may be calculated from the seismic landslide data by a kernel density algorithm with a search radius of 5 km.
The nuclear density algorithm is a preconfigured searching algorithm and is used for searching the earthquake landslide density.
It should be understood that the kernel density algorithm can be directly configured, other algorithms can be used in the application, for example, the kernel density algorithm in ArcGIS software space analysis can be utilized, and the density search requirement can be met.
Step S103, inputting the seismic landslide data into an LS-D-Newmark model, and adjusting related model parameters according to the rock-soil body mechanical parameters and the slope form parameters to enable the static safety coefficient F of the slope 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 using the rock-soil body mechanical parameters and slope form parameters in a plurality of cyclic iterative calculations, and the adjustment of the model parameters is based on a Newmark model for providing an effective model parameter environment for subsequent data processing, so that the static safety coefficient F of the slope in the model is not under the action of external power s Greater than 1.
As yet another implementation manner suitable for practical use, in the process of adjusting the model parameters, the static safety coefficient formula (the slope safety coefficient formula based on the slide limit balance theory of the Newmark model) may be specifically:
wherein c' is cohesion (kPa), and gamma is rock mass weight (kN/m) 3 ) T is the potential slip thickness (m), alpha is the potential slip angle,
the effective internal friction angle (DEG), m is the ratio of the saturated part in the potential sliding body to the total thickness of the sliding body, and gamma w Is the underground water gravity (kN/m) 3 )。
Step S104, the LS-D-Newmark model is added with the historical seismic landslide density to add the historical seismic landslide factor, and the static safety factor F is calculated s Performing optimization assignment;
in the above, the present application, which optimizes the input parameters of LS-D-Newmark model, can be embodied from historical seismic landslide density factors.
At this time, thenThe previously determined historical seismic landslide density may be brought into a model parameter optimized LS-D-Newmark model and in the model, a static security factor F is performed based on the input historical seismic landslide density s Is a function of the optimization assignments of (a).
Briefly, the process performed herein is understood to be static safety factor F due to the low stability of the historical seismic landslide region relative to the non-historical seismic landslide region s Lower, but no deformation and sliding occur in the history earthquake landslide area under the action of no external force, thus the static safety coefficient F s Still greater than 1, in which case the present application is directed to a static safety factor F s Optimizing, adding the seismic landslide density factor, and obtaining a static safety factor F s Performing optimization assignment to distinguish static safety coefficient F of earthquake landslide area and non-history earthquake landslide area s In this way, the seismic landslide area and the non-historical seismic landslide area are subjected to more clear and clear subdivision processing in the model, so that the subsequent seismic landslide risk evaluation can be subjected to more detailed processing.
As a further practical implementation, the application is directed to a static safety factor F s In the process of optimizing assignment, the adopted static safety coefficient optimizing assignment formula can be specifically:
it is to be understood that here the application optimizes the static security factor F based on historical seismic landslide density factors s A landing scheme is proposed.
Step S105, based on the static safety coefficient F after the optimization assignment s Calculating the critical acceleration a of the slope c ；
Static safety coefficient F after obtaining optimized assignment s After the seismic landslide area and the non-historical seismic landslide area are subjected to more clear subdivision processing in the model, the slope critical acceleration a can be continuously calculated c It can be understood asUnder the action of the earthquake motion load, the sliding force of the sliding block is equal to the corresponding earthquake motion acceleration when the sliding block is in an anti-sliding force (limit balance state).
Specifically, as yet another implementation suitable for practical use, the present application establishes a slider limit equilibrium state equation under seismic action by comparing the stress states of the slider under static and seismic dynamic conditions, i.e., by calculating the critical acceleration a of the slope c In the process of (2), the adopted slope critical acceleration formula can be specifically:
wherein g is the gravitational acceleration (m/s 2 ) Alpha is the potential slip angle (°).
Step S106, at the slope critical acceleration a c Based on (1), calculating the earthquake induced slope displacement D by using the known earthquake motion peak acceleration value PGA n ；
At the time of obtaining the slope critical acceleration a c Then, the earthquake-induced slope displacement D can be continued n Is easy to understand, the seismic induced ramp displacement D at which it is located n 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 in practical applications, for example, the seismic peak acceleration value PGA data in "chinese seismic peak acceleration demarcation map" with a 50-year override probability of 10% (GB 18306-2015) may be used.
In addition, the application obtains the accumulated displacement D of the earthquake-induced slope through statistically analyzing a large number of earthquake acceleration records and earthquake landslide examples n Critical acceleration of slope a c And the seismic peak acceleration PGA, i.e., as yet another practical implementation, where the seismic induced ramp displacement D is calculated n In the process of (2), the adopted earthquake induced slope displacement formula is as follows:
it can also be seen that in the landing scenario herein, the slope accumulates displacement D n In proportion to the peak acceleration PGA of the earthquake motion and the critical acceleration a of the slope c Inversely proportional.
Step S107, according to the seismic induced slope displacement D n And calculating the landslide occurrence probability P of the target landslide area, and finishing the seismic landslide risk evaluation of the target landslide area.
While winning an earthquake-induced ramp displacement D n And then, according to the corresponding relation between the induced slope displacement and the landslide occurrence probability, determining the corresponding landslide occurrence probability P as an earthquake landslide risk evaluation result of the target landslide region.
In another implementation manner suitable for practical use, a set of landing scheme is provided for calculating the landslide occurrence probability P, that is, in the process of calculating the landslide occurrence probability P of the target landslide area, the adopted landslide occurrence probability calculation formula may specifically be:
P＝0.335[1-exp(-0.048DD n 1.565 )]。
furthermore, on the basis of taking the landslide occurrence probability P as an earthquake landslide risk evaluation result, the application can also relate to dangerous partition processing, namely, according to the landslide occurrence probabilities P of different target earthquake landslide areas, the whole earthquake landslide area is subjected to earthquake landslide risk partition so as to divide areas with different earthquake landslide risks.
With this arrangement, it is apparent that more detailed data guidance can be provided for practical applications.
To further understand the above aspects (including the aspects of the exemplary embodiments), a further understanding may be obtained by the following example on the basis of an application scenario schematic diagram of the LS-D-Newmark seismic landslide risk evaluation method of the present application shown in fig. 2.
The method takes the positions about 20km on two sides of a fracture zone of a fresh water river in Sichuan province as a research area, and calculates the risk of the earthquake landslide by an earthquake landslide risk evaluation method based on an LS-D-Newmark model. The seismic landslide risk evaluation method based on the LS-D-Newmark model is completed by adding a factor of historical seismic landslide density on the basis of the Newmark model, and mainly comprises the following processing flows:
through remote sensing interpretation, historical data collection and field investigation, a historical earthquake landslide database of the fresh water river fracture zone is established.
According to the established seismic landslide database of the fresh water river fracture zone, obtaining the historical seismic landslide density (position/km) of the fresh water river fracture zone by using a nuclear density algorithm in ArcGIS software space analysis and taking 5km as a search radius 2 ) The seismic landslide of the research area is mainly distributed in a strip shape along the fracture zone of the fresh water river, wherein the highest density of the seismic landslide can reach 0.64 place/km 2 。
The historical seismic landslide density of the fresh water river fracture zone can refer to a schematic diagram of the historical seismic landslide density of the fresh water river fracture zone shown in fig. 3.
And obtaining the terrain gradient of the fresh water river fracture zone according to the terrain data.
And comprehensively considering factors such as geological structure, stratum age, rock-soil body type, rock-mass weathering breaking degree and the like, and dividing the engineering geological rock group of the research area.
The physical and mechanical parameters of the engineering geological rock group shown in the representation are comprehensively initialized according to engineering geological handbook (fifth edition).
Remarks: c' is the cohesive force of the adhesive,
gamma is the rock mass weight, which is the effective internal friction angle.
According to a slope safety coefficient formula (1) based on a slide block limit balance theory, calculating the static state of the regional slope body by using the rock-soil body mechanical parameter and the slope body shape parameterCoefficient of dynamic safety F s The slope is not deformed and slid under the action of no external force, thus the static safety coefficient F s Greater than 1.
Because the stability of the earthquake landslide in the historical earthquake landslide area is lower, the static safety coefficient F s The static safety coefficient F of the earthquake landslide area is lower, but the history earthquake landslide area does not deform and slide under the action of no external force s Still greater than 1, for static safety factor F s The formula is optimized and adjusted, seismic landslide factors are added, and static safety coefficients F of the seismic landslide areas and the non-historical seismic landslide areas are distinguished s Is calculated by the computer.
The addition of the seismic landslide density factor avoids the higher stability of the historical seismic landslide area or lower risk of seismic induced landslide, and the static safety factor F is calculated by the following formula (2) s And performing optimization assignment.
By comparing the stress states of the sliding block under the static force and the earthquake dynamic force, a sliding block limit balance state equation under the earthquake action can be established, and the static safety coefficient F is utilized s (obtained by 2) deriving the critical acceleration of slope a c The calculation formula (formula 3);
calculating critical acceleration a of the investigation region by formula (3) c 。
Establishing an 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 the seismic peak acceleration PGA (equation 4).
Wherein, the partition value of Chinese earthquake motion peak acceleration partition map (GB 18306-2015) with the 50-year override probability of 10% is adopted to calculate the earthquake-induced slope displacement D n 。
According to seismic ramp displacement D n And the landslide occurrence probability P (formula 5), and calculating the landslide occurrence probability P under the action of earthquake.
P＝0.335[1-exp(-0.048Dn 1.565 )] (5)
The evaluation of the seismic landslide risk of the fresh water river fracture zone based on the LS-D-Newmark model is completed, wherein the result of the seismic landslide risk evaluation partition of the fresh water river fracture zone can be referred to a schematic diagram of the seismic landslide risk evaluation partition based on the LS-D-Newmark model shown in fig. 4, and the comparison with the traditional Newmark model can be referred to a comparison schematic diagram of the seismic landslide risk partition based on different risk evaluation methods shown in fig. 5.
In general, as can be seen from the above, with respect to prediction of the risk of a seismic landslide, the present application optimizes a Newmark model, configures an LS-D-Newmark model on the basis of the Newmark model, determines the historical seismic landslide density of the target seismic landslide according to the seismic landslide data after acquiring the seismic landslide data of the target seismic landslide, inputs the seismic landslide data into the LS-D-Newmark model, and adjusts the related model parameters by using the rock-soil body mechanical parameters and the slope body physical parameters so that the static safety coefficient F of the slope under the action of no external power s More than 1, continuously bringing the historical seismic landslide density into the LS-D-Newmark model to add the historical seismic landslide factor, and obtaining the static safety factor F s Performing optimization assignment, wherein the optimization assignment is based on the static safety coefficient F s Calculating the critical acceleration a of the slope c Then at the slope critical acceleration a c Based on (1), calculating the earthquake induction by using the known earthquake motion peak acceleration value PGASlope displacement D n Finally according to the earthquake induced slope displacement D n Calculating landslide occurrence probability P of a target landslide area, and finishing seismic landslide risk evaluation of the target landslide area, wherein in the process, historical seismic landslide density is used as an influence factor to participate in the seismic landslide risk evaluation, and the structure and stability of a rock-soil body of the historical seismic landslide area are reduced compared with those of areas where no seismic landslide occurs, so that the situation that the existing historical seismic landslide area in the risk evaluation result is low in risk is avoided, and after application, the prediction accuracy of the seismic landslide risk evaluation method based on an LS-D-Newmark model and a traditional Newmark model is improved to a certain extent, and the applicability is higher.
The LS-D-Newmark earthquake landslide risk evaluation device is further provided from the angle of a functional module in order to facilitate better implementation of the LS-D-Newmark earthquake landslide risk evaluation method.
Referring to fig. 6, fig. 6 is a schematic structural diagram of an LS-D-Newmark seismic landslide risk evaluation device according to the present application, in which an LS-D-Newmark seismic landslide risk evaluation device 600 specifically includes the following structure:
an acquiring 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;
the adjusting unit 603 is configured to input the seismic landslide data into the LS-D-Newmark model, and adjust related model parameters according to the rock-soil body mechanical parameters and the slope form parameters, so that the static safety coefficient F of the slope under the action of no external power s Greater than 1;
an optimizing unit 604 for adding the historical seismic landslide factors to the LS-D-Newmark model by substituting the historical seismic landslide densities for the static safety factor F s Performing optimization assignment;
a computing unit 605 for optimizing the assigned static securityCoefficient F s Calculating the critical acceleration a of the slope c ；
The calculating unit 605 is also used for controlling the critical acceleration a at the slope c Based on (1), calculating the earthquake induced slope displacement D by using the known earthquake motion peak acceleration value PGA n ；
A calculation unit 605 for 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 seismic landslide risk evaluation of the target landslide area.
In an exemplary implementation, the determining unit is specifically configured to:
in the data according to the earthquake landslide, the historical earthquake landslide density is calculated by a nuclear density algorithm by taking 5km as a searching radius.
In yet another exemplary implementation, in adjusting the model parameters, a static security coefficient formula is used as follows:
wherein c' is cohesive force, gamma is rock mass weight, t is potential sliding body thickness, alpha is potential sliding inclination angle,
for effective internal friction angle, m is the ratio of saturated part in potential sliding body to total sliding body thickness, gamma w Is the ground water gravity.
In yet another exemplary implementation, the static security factor F is applied to a historical seismic landslide area s In the process of optimizing assignment, the adopted static safety coefficient optimizing assignment formula is as follows:
in yet another exemplary implementation, the ramp critical acceleration a is calculated c In the process of (1) using a ramp critical accelerationThe degree formula is:
wherein g is gravity acceleration, and alpha is potential slip angle.
In yet another exemplary implementation, the seismic induced slope displacement D is calculated n In the process of (2), the adopted earthquake induced slope displacement formula is as follows:
in still another exemplary implementation, in calculating the landslide occurrence probability P of the target landslide region, a 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 the perspective of a hardware structure, referring to fig. 7, in which fig. 7 shows a schematic structural diagram of the processing device, specifically, the processing device may include a processor 701, a memory 702, and an input/output device 703, where the processor 701 is configured to implement steps of the LS-D-Newmark seismic landslide risk evaluation method in the corresponding embodiment of fig. 1 when executing a computer program stored in the memory 702; alternatively, the processor 701 is configured to implement the functions of each unit in the corresponding embodiment of fig. 6 when executing the computer program stored in the memory 702, and the memory 702 is configured to store the computer program required for the processor 701 to execute the LS-D-Newmark seismic landslide risk evaluation method in the corresponding embodiment of fig. 1.
By way of example, a computer program may be partitioned into one or more modules/units that are stored in the memory 702 and executed by the processor 701 to complete the present application. One or more of the modules/units may be a series of computer program instruction segments capable of performing particular functions to describe the execution of the computer program in a computer device.
The processing devices may include, but are not limited to, a processor 701, a memory 702, and an input output device 703. It will be appreciated by those skilled in the art that the illustrations are merely examples of processing devices, and are not limiting of processing devices, and may include more or fewer components than shown, or may combine some components, or different components, e.g., processing devices may also include network access devices, buses, etc., through which the processor 701, memory 702, input output device 703, etc., are connected.
The processor 701 may be a central processing unit (Central Processing Unit, CPU), but may also be other general purpose processors, digital signal processors (Digital Signal Processor, DSP), application specific integrated circuits (Application Specific Integrated Circuit, ASIC), field programmable gate arrays (Field-Programmable Gate Array, FPGA) or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, or the like. A general purpose processor may be a microprocessor or the processor may be any conventional processor or the like, which is a control center for a processing device, with 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 the various functions of the computer device 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 storage program area and a storage data area, wherein the storage program area may store an operating system, application programs required for at least one function, and the like; the storage data area may store data created according to the use of the processing device, or 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, memory, plug-in hard disk, smart Media Card (SMC), secure Digital (SD) Card, flash Card (Flash Card), at least one disk storage device, flash memory device, or other volatile solid-state storage device.
The processor 701 is configured to execute the computer program stored in the memory 702, and may specifically implement the following functions:
acquiring seismic landslide data of a target seismic landslide;
according to the seismic landslide data, determining the historical seismic landslide density of the target seismic landslide;
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 form parameters to enable a static safety coefficient F of the slope under the action of no external power s Greater than 1; bringing the historical seismic landslide density into LS-D-Newmark model to add the historical seismic landslide factor, and applying the static safety factor F to s Performing optimization assignment;
based on static safety coefficient F after optimization assignment s Calculating the critical acceleration a of the slope c ；
At a critical acceleration of slope a c Based on (1), calculating the earthquake induced slope displacement D by using the known earthquake motion peak acceleration value PGA n ；
According to earthquake induced slope displacement D n And calculating the landslide occurrence probability P of the target landslide area, and finishing the seismic landslide risk evaluation of the target landslide area.
It will be clearly understood by those skilled in the art that, for convenience and brevity of description, the detailed working process of the LS-D-Newmark seismic landslide risk evaluation device, the processing apparatus and the corresponding units thereof described above may refer to the description of the LS-D-Newmark seismic landslide risk evaluation method in the corresponding embodiment of fig. 1, and will not be repeated herein.
Those of ordinary skill in the art will appreciate that all or a portion of the steps of the various methods of the above embodiments may be performed by instructions, or by instructions controlling associated hardware, 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, in which a plurality of instructions capable of being loaded by a processor are stored, so as to execute the steps of the LS-D-Newmark seismic landslide risk evaluation method according to the corresponding embodiment of fig. 1, and the specific operation may refer to the description of the LS-D-Newmark seismic landslide risk evaluation method according to the corresponding embodiment of fig. 1, which is not repeated herein.
Wherein the computer-readable storage medium may comprise: read Only Memory (ROM), random access Memory (Random Access Memory, RAM), magnetic or optical disk, and the like.
Because the instructions stored in the computer readable storage medium may execute the steps of the LS-D-Newmark seismic landslide risk evaluation method according to the embodiment of fig. 1, the beneficial effects that can be achieved by the LS-D-Newmark seismic landslide risk evaluation method according to the embodiment of fig. 1 are achieved, which are described in detail in the foregoing, and are not repeated here.
The LS-D-Newmark seismic landslide risk evaluation method, apparatus, processing device and computer readable storage medium provided in the present application are described in detail, and specific examples are applied herein to illustrate the principles and embodiments of the present application, where the above examples are only used to help understand the method and core ideas of the present application; meanwhile, those skilled in the art will have variations in the specific embodiments and application scope in light of the ideas of the present application, and the present description should not be construed as limiting the present application in view of the above.
Claims (6)
1. An LS-D-Newmark earthquake landslide risk evaluation method is characterized by comprising the following steps:
acquiring seismic landslide data of a target seismic landslide;
according to the seismic landslide data, determining the historical seismic landslide density of the target seismic landslide;
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 form parameters to enable a static safety coefficient F of the slope under the action of no external power s Greater than 1;
bringing the historical seismic landslide density to the LS-D-Newmark model to add calendarHistory of earthquake landslide factors and for the static safety factor F s Performing optimization assignment;
based on the static safety coefficient F after optimization assignment s Calculating the critical acceleration a of the slope c ；
At the slope critical acceleration a c Based on (1), calculating the earthquake induced slope displacement D by using the known earthquake motion peak acceleration value PGA n ；
According to the earthquake induced slope displacement D n Calculating landslide occurrence probability P of the target landslide area, and finishing seismic landslide risk evaluation of the target landslide area;
the determining the historical seismic landslide density of the target seismic landslide according to the seismic landslide data comprises the following steps:
calculating the historical earthquake landslide density according to the earthquake landslide data by a nuclear density algorithm and taking 5km as a searching radius;
in the process of adjusting the model parameters, the adopted static safety coefficient formula is as follows:
wherein c' is cohesive force, gamma is rock mass weight, t is potential sliding body thickness, alpha is potential sliding inclination angle,
for effective internal friction angle, m is the ratio of saturated part in potential sliding body to total sliding body thickness, gamma w Is the ground water gravity;
in relation to the static safety factor F s In the process of optimizing assignment, the adopted static safety coefficient optimizing assignment formula is as follows:
2. the method according to claim 1, wherein, in calculating the ramp critical acceleration a c In the process of (2), the adopted slope critical acceleration formula is as follows:
wherein g is gravity acceleration, and alpha is potential slip angle.
3. The method of claim 1, wherein, in calculating the seismic-induced ramp displacement D n In the process of (2), the adopted earthquake induced slope displacement formula is as follows:
4. the method according to claim 1, wherein in calculating the landslide occurrence probability P of the target landslide region, a landslide occurrence probability calculation formula is adopted as follows:
P＝0.335[1-exp(-0.048D n 1.565 )]。
5. a processing device comprising a processor and a memory, the memory having stored therein a computer program, the processor executing the method of any of claims 1 to 4 when invoking the computer program in the memory.
6. 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 4.
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