CN106021853B - A kind of development approach of stochastic modeling slope Analysis on Stable Reliability software - Google Patents
A kind of development approach of stochastic modeling slope Analysis on Stable Reliability software Download PDFInfo
- Publication number
- CN106021853B CN106021853B CN201610297267.0A CN201610297267A CN106021853B CN 106021853 B CN106021853 B CN 106021853B CN 201610297267 A CN201610297267 A CN 201610297267A CN 106021853 B CN106021853 B CN 106021853B
- Authority
- CN
- China
- Prior art keywords
- slope
- analysis
- stochastic
- value
- unstability
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Active
Links
Classifications
-
- G—PHYSICS
- G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
- G16Z—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS, NOT OTHERWISE PROVIDED FOR
- G16Z99/00—Subject matter not provided for in other main groups of this subclass
Abstract
The invention belongs to the technical fields of slope stability analysis software development, it is related to a kind of development approach of stochastic modeling slope Analysis on Stable Reliability software, including following implemented process: on the basis of pre-processing data input, carry out side slope discretization and integrated analysis, the safety coefficient for obtaining given Failure Model, and then main unstability region is searched for and determined to the minimum safety factor for carrying out certain number, realizes the reliability analysis of slope stability software development based on multiple main Failure Models finally by Monte Carlo sampling method.The present invention has the advantages that (1) can fully take into account soil body material stochastic modeling bring system performance.(2) current business software has been filled up because of the calculating blank of stochastic modeling bring system performance, and there is stronger engineering application value and commercial promise.
Description
Technical field
The invention belongs to the technical fields of slope stability analysis software development, and it is steady to be related to a kind of stochastic modeling slope
Determine the development approach of reliability analysis software, especially one kind determines stochastic modeling slope system based on limiting equilibrium method
The response of system, and the software development methodology for carrying out reliability analysis of slope stability is responded based on system.
Background technique
Stability of slope refers to that natural slope or Artificial Side-slope keep the condition and ability of safety and stability.The rock of these two types of side slopes
The soil body is gradually changed under the effect of various internal and external factors, and slopes stress state also changes correspondingly, when sliding force or power of toppling reach
So that more than skid resistance or anchorage when disequilibrium, that is, occurring becoming destroying, causes disaster or threaten building safety.
Reliability analysis of slope stability is one of very important project in geotechnical engineering design field, Slope Design or
When supporting, need quantitatively to assess the possible failure probability of side slope and unstability region.When traditional Slope Design, need by
Limit equilibrium analysis is carried out in business software or the antiskid minimum safety factor of stability of slope is calculated based on strength reduction method
And corresponding unstability region, and be designed based on this minimum safety factor and corresponding unstability region.On the other hand,
Due to the uncertainty of geomaterial, especially under long-term geologic process, soil body material shows apparent space
Variation property, this stochastic modeling cause side slope to show system performance in unstability, that is to say, that have when slope instability
The main unstability region of more than one, this system performance are seldom related in conventional business software.Currently, not having also in the market
Have it is a kind of it can be considered that soil body material stochastic modeling reliability analysis of slope stability software.
In view of above-mentioned analysis, develop it can be considered that the reliability analysis of slope stability of soil body material stochastic modeling is soft
Part has stronger engineering application value and commercial promise very than wanting.
Summary of the invention
According to the above-mentioned deficiencies of the prior art, the present invention provides a kind of stochastic modeling slope Analysis on Stable Reliability
The development approach of software can fully take into account soil body material stochastic modeling bring system performance.
A kind of development approach of stochastic modeling slope Analysis on Stable Reliability software of the present invention, feature
Be to include following implemented process: on the basis of pre-processing data input, carry out side slope discretization and integrated analysis, obtain to
Determine the safety coefficient of Failure Model, and then main unstability region is searched for and determined to the minimum safety factor for carrying out certain number,
The reliability analysis of slope stability software development based on multiple main Failure Models is realized finally by Monte Carlo sampling method.
Specifically include following implemented process:
Pre-treatment analysis:
(1) related data for calculating stability of slope is read, including reads side slope geometric profile data, soil body material system
It counts, infiltrate wire position data or pore pressure data and external load data；
(2) assume the Failure Model type of slope sliding；
(3) the virtual soil layer number of each side slope soil layer is determined according to the fluctuation range value in soil body material statistical data,
And carry out the secondary update of side slope geometric profile data；
Deterministic parsing:
(4) given Failure Model is subjected to discretization, obtains a series of vertical native item, and combine secondary updated side
Slope geometrical model obtains the relevant parameter of each vertical native item；
(5) safety coefficient of prescribed limit balance method solves, and is obtaining the relevant parameter base of all discrete vertical soil items
On plinth, the safety coefficient of given Failure Model is calculated using Bishop approach；
(6) different potential unstability regions is converted, the solution of safety coefficient is carried out according to step (5), eventually passes through and compares
Obtain the unstability region with minimum safety factor；
Slope system in response to determining that:
(7) carry out following iteration to one in all stochastic variables: the value that the stochastic variable is arranged is its mean value
1 times of standard deviation is subtracted, remaining stochastic variable is taken as its mean value, after the value of stochastic variable has been determined, carries out step
(4), the calculating analysis of (5), (6), obtains the minimum safety factor under this kind of operating condition and its corresponding unstability region；
(8) iterative calculation that step (7) are carried out to all stochastic variables, finally corresponds to each stochastic variable,
To a minimum safety factor and its corresponding unstability region；
(9) the unstability region that step (7) and (8) obtain is summarized, is regarded as the main composition portion of slope system
Point, the Whole Response of slope system can be represented by these discrete unstability regions；
Reliability of slope analysis and post-processing:
(10) the Monte-Carlo step sample value for meeting stochastic variable distribution is generated, in each Monte-Carlo step sample
Under value, for each discrete unstability region obtained in step (9), the calculating analysis of step (4) and (5) is carried out, is obtained
The safety coefficient in each discrete unstability region, more all discrete corresponding safety coefficients in unstability region, selects minimum
Response of the safety coefficient as slope system under the Monte-Carlo step sample value, meanwhile, can determine the minimum safe
The corresponding unstability region of coefficient；
(11) after the corresponding side slope response of all sample values is found out, Monte Carlo of the side slope response less than 1 can be counted
The number and total the ratio between Monte Carlo sample value number, are defined as the failure probability of side slope by sample value number, and the failure is general
Rate value can represent the reliability degree of side slope；In addition, there is the number of minimum safety factor and its corresponding in each unstability region
Geometric position may be displayed on side slope sectional view, so as to more intuitively determine slope system response main source.
Wherein, preferred embodiment is as follows:
Side slope cross-sectional data as described in step (1) includes that slope height, slope angle, soil layer number and slope foot and top of the slope extend model
The range enclosed；Soil body material statistical data includes bulk density, cohesive strength, the mean value of internal friction angle and standard deviation and characterization soil layer ginseng
The fluctuation range value of number space variation property degree.
The Failure Model of slope sliding described in step (2) includes circular arc Failure Model and non-circular arc Failure Model.
The relevant parameter of vertical soil item described in step (4) includes item bottom coordinate, item bottom and the ground of each vertical native item
The corresponding coordinate in face, and the vertical native self weight of item, the internal friction angle at item bottom, cohesive strength and bottom outlet press data.
The formula of Bishop approach described in step (5) are as follows:
The Monte-Carlo step sample value for meeting stochastic variable distribution is generated in step (10) using Cholesky decomposition method.
The present invention has the advantages that (1) has fully considered the stochastic modeling of Soil Parameters, carry out on this basis
The secondary update of side slope geometric profile data, and analyzed based on traditional being determined property of limiting equilibrium method, by random
The iterative analysis one by one of variable, the final response source for obtaining slope system carry out slope system reliability using these response sources
Analysis, and show in post-processing the failure probability of slope system and the percentage contribution of each response source side slope system.(2) it fills out
Current business software has been mended because of the calculating blank of stochastic modeling bring system performance, there is stronger engineering application value
And commercial promise.
Detailed description of the invention
Fig. 1 is flow diagram of the invention.
Specific embodiment
Below in conjunction with drawings and examples, the invention will be further described.
Embodiment 1:
A kind of development approach of stochastic modeling slope Analysis on Stable Reliability software, including following implemented process:
Pre-treatment analysis:
(1) related data for calculating stability of slope is read, including reads side slope geometric profile data, soil body material system
It counts, infiltrate wire position data or pore pressure data and external load data.Wherein, side slope cross-sectional data includes slope height, slope
The range at angle, soil layer number and slope foot and top of the slope expanded range；Soil body material statistical data includes bulk density, cohesive strength, interior rubs
Wipe the mean value at angle and the fluctuation range value of standard deviation and characterization soil parameters stochastic modeling degree.It needs to open up public affairs herein
Array is total to save these data.
(2) assume the Failure Model type of slope sliding, for example circular arc Failure Model or non-circular arc Failure Model.Every kind
The variable that the mathematical description of Failure Model needs is different, when being assumed to circular arc Failure Model, need the central coordinate of circle of circular arc with
And 3 variables such as radius, need to judge whether circular arc with side slope ground has intersection point herein, if so, then needing to save it with side slope
Two intersection points in face as unstability region slide-in point and skid off a little；If needing to reject the Failure Model without intersection point.
(3) the virtual soil layer number of each side slope soil layer is determined according to the fluctuation range value in soil body material statistical data,
And the secondary update of side slope geometric profile data is carried out, it is several to store secondary updated side slope to need to open up new array herein
What cross-sectional data.Need to set option herein by user independently to determine the degree of the secondary update of cross-sectional data, i.e., it is true by user
The product of coefficient between one 0.1 ~ 0.2 fixed, this coefficient and fluctuation range is as the foundation updated.
Deterministic parsing:
(4) spacing that vertical native item is selected by user, since skidding off a little, until sliding into point terminates, by given Failure Model
Discretization is carried out, obtains a series of vertical native item, and combine secondary updated side slope geometrical model.It needs to open up number herein
Item bottom coordinate, the item bottom coordinate corresponding with ground of each vertical native item of group record, and the self weight of vertical soil item, item bottom
Internal friction angle, cohesive strength and bottom outlet press data.
(5) Bishop approach in limit of utilization balance method calculate it is discrete after unstability region stablize safety system
Number, needs to work out herein subprogram and is iterated calculating.
(6) according to certain variation rule, for example gridding method, complex method, harmonic search algorithm are different latent to convert
In unstability region, the subprogram in invocation step (5) calculates the safety coefficient of different Failure Models, and opens up array and protected
It deposits, by relatively or optimization determines the smallest value of safety factor value.
Slope system in response to determining that:
(7) carry out following iteration to one in all stochastic variables: the value that the stochastic variable is arranged subtracts for mean value
1 times of standard deviation is removed, remaining stochastic variable is taken as its mean value, and after the value of stochastic variable has been determined, these values are regarded
To determine value and carrying out the calculating of step (4), (5), (6), up to finally determining the smallest safety coefficient and its corresponding mistake
Steady region needs to open up the mathematical description variable in array record unstability region herein.
(8) iterative calculation that step (7) are carried out to all stochastic variables, finally corresponds to each stochastic variable,
To a minimum safety factor and its corresponding unstability region, and it is stored in the array opened up.
(9) representative for responding in the unstability region being stored in array as slope system, that is to say, that side slope is in difference
Soil parameters under, minimum safety factor value can be determined by the tentative calculation in these unstability regions.
Reliability of slope analysis and post-processing:
(10) sample value for utilizing Cholesky decomposition method generating random variable, need to determine Monte Carlo by user herein
Frequency in sampling, for each sample value, be regarded as side slope input determines value, determines the unstability region being stored in array
Corresponding value of safety factor value selects response of the minimum value as slope system under the sample value, and whether judges the response
Less than 1, if so, the sample is referred to as failure sample, the corresponding unstability region of the response is referred to as marking area；If it is not, then
For non-failed sample.
(11) number for the sample that fails in all sampling samples is counted, the ratio of the number and total sampling samples number claims
The failure probability for slope system.The unstability region saved in array can intuitively judge side as the number of marking area
The response source of slope system needs to open up herein array and records number of each unstability region as marking area, and finally on side
Shown on the section of slope each unstability region position and corresponding marking area number, to display for a user slope system
Response source.
Claims (4)
1. a kind of development approach of stochastic modeling slope Analysis on Stable Reliability software, it is characterised in that including following reality
Existing process:
Pre-treatment analysis:
(1) related data for calculating stability of slope is read, including reads side slope geometric profile data, soil body material statistical number
According to, infiltration wire position data or pore pressure data and external load data；Wherein, side slope cross-sectional data include slope height, slope angle,
The range of soil layer number and slope foot and top of the slope expanded range；Soil body material statistical data includes bulk density, cohesive strength, internal friction angle
Mean value and standard deviation and characterize soil parameters stochastic modeling degree fluctuation range value；
(2) assume the Failure Model type of slope sliding；
(3) the virtual soil layer number that each side slope soil layer is determined according to the fluctuation range value in soil body material statistical data, goes forward side by side
The secondary update of row side slope geometric profile data；
Deterministic parsing:
(4) given Failure Model is subjected to discretization, obtains a series of vertical native item, and combine secondary updated side slope several
What model obtains the relevant parameter of each vertical native item；Wherein, the relevant parameter of vertical native item includes each vertical native item
Item bottom coordinate, item bottom coordinate corresponding with ground, and the vertical native self weight of item, the internal friction angle at item bottom, cohesive strength and
Bottom outlet presses data；
(5) safety coefficient of prescribed limit balance method solves, on the basis of obtaining the relevant parameter of all discrete vertical soil items,
The safety coefficient of given Failure Model is calculated using Bishop approach；
(6) different potential unstability region is converted, the solution of safety coefficient is carried out according to step (5), eventually passes through to compare and obtains
Unstability region with minimum safety factor；
Slope system in response to determining that:
(7) carry out following iteration to one in all stochastic variables: the value that the stochastic variable is arranged is that its mean value subtracts 1
Times standard deviation, remaining stochastic variable is taken as its mean value, after the value of stochastic variable has been determined, carry out step (4), (5),
(6) calculating analysis, obtains the minimum safety factor under this kind of operating condition and its corresponding unstability region；
(8) iterative calculation that step (7) are carried out to all stochastic variables, finally corresponds to each stochastic variable, obtains one
A minimum safety factor and its corresponding unstability region；
(9) the unstability region that step (7) and (8) obtain is summarized, is regarded as the chief component of slope system, side
The Whole Response of slope system is represented by these discrete unstability regions；
Reliability of slope analysis and post-processing:
(10) the Monte-Carlo step sample value for meeting stochastic variable distribution is generated, in each Monte-Carlo step sample value
Under, for each discrete unstability region obtained in step (9), the calculating analysis of step (4) and (5) is carried out, is obtained every
The safety coefficient in one discrete unstability region, more all discrete corresponding safety coefficients in unstability region, is selected the smallest
Response of the safety coefficient as slope system under the Monte-Carlo step sample value, meanwhile, determine the minimum safety factor pair
The unstability region answered；
(11) after the corresponding side slope response of all sample values is found out, Monte Carlo sample value of the statistics side slope response less than 1
The number and total the ratio between Monte Carlo sample value number, are defined as the failure probability of side slope by number, which represents
The reliability degree of side slope；In addition, each unstability region the number of minimum safety factor occurs and its corresponding geometric position is aobvious
Show on side slope sectional view, more intuitively to determine the main source of slope system response.
2. a kind of development approach of stochastic modeling slope Analysis on Stable Reliability software according to claim 1,
It is characterized in that the Failure Model of slope sliding described in step (2) includes circular arc Failure Model and non-circular arc Failure Model.
3. a kind of development approach of stochastic modeling slope Analysis on Stable Reliability software according to claim 1,
It is characterized in that the formula of Bishop approach described in step (5) are as follows:
Wherein, FSFor safety coefficient, the i-th vertical soil width bi, bottom surface inclination alphai, be self-possessed Wi, bottom outlet pressure ui, internal friction angleCohesive strength ci。
4. a kind of development approach of stochastic modeling slope Analysis on Stable Reliability software according to claim 1,
It is characterized in that the Monte-Carlo step sample for meeting stochastic variable distribution is generated in step (10) using Cholesky decomposition method
This value.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201610297267.0A CN106021853B (en) | 2016-05-09 | 2016-05-09 | A kind of development approach of stochastic modeling slope Analysis on Stable Reliability software |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201610297267.0A CN106021853B (en) | 2016-05-09 | 2016-05-09 | A kind of development approach of stochastic modeling slope Analysis on Stable Reliability software |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN106021853A CN106021853A (en) | 2016-10-12 |
| CN106021853B true CN106021853B (en) | 2019-02-12 |
Family
ID=57081821
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201610297267.0A Active CN106021853B (en) | 2016-05-09 | 2016-05-09 | A kind of development approach of stochastic modeling slope Analysis on Stable Reliability software |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN106021853B (en) |
Families Citing this family (12)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN106709182B (en) * | 2016-12-26 | 2020-02-14 | 华中科技大学 | Bedding rock slope stability and reliability safety evaluation method under earthquake action |
| CN107239589A (en) * | 2017-04-07 | 2017-10-10 | 西安理工大学 | Reliability of slope analysis method based on MRVM AFOSM |
| CN108491575A (en) * | 2018-02-11 | 2018-09-04 | 华北水利水电大学 | A kind of computational methods for Side Slope Safety Coefficient of being paddled based on digital terrain progress reservoir |
| CN108629111B (en) * | 2018-05-02 | 2019-09-10 | 四川大学 | A kind of analogy method of concrete gravity dam material parameter Spatial Variability |
| CN109063285B (en) * | 2018-07-18 | 2022-12-02 | 南昌大学 | Design method of earth slope drilling arrangement scheme |
| CN109446616A (en) * | 2018-10-18 | 2019-03-08 | 东北电力大学 | A kind of homogeneous slope method for evaluating reliability |
| CN109614708B (en) * | 2018-12-12 | 2019-08-09 | 青岛理工大学 | Building underlying security distance and the design method of embedded depth of foundation in side slope |
| CN109977554B (en) * | 2019-03-28 | 2020-06-30 | 青岛理工大学 | Method for evaluating sliding area of side slope |
| CN110245429B (en) * | 2019-06-18 | 2020-09-04 | 贵州正业工程技术投资有限公司 | Annular convex slope stability evaluation method based on simplified Bishop method |
| CN111444649B (en) * | 2020-03-24 | 2022-10-18 | 成都理工大学 | Slope system reliability analysis method based on intensity reduction method |
| CN113239435B (en) * | 2021-05-11 | 2022-09-20 | 青岛理工大学 | Method for determining optimal water discharge speed of reservoir |
| CN113449429A (en) * | 2021-07-09 | 2021-09-28 | 中国电建集团贵阳勘测设计研究院有限公司 | Slope stability evaluation and correction method based on local average |
Citations (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN103134433A (en) * | 2013-02-02 | 2013-06-05 | 青岛理工大学 | Method of identifying slip factors causing slope instability by utilizing displacement monitoring |
| CN104899380A (en) * | 2015-06-11 | 2015-09-09 | 武汉大学 | Side slope stable reliability sensitivity analysis method based on Monte Carlo simulation |
Family Cites Families (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JPH07200534A (en) * | 1993-12-28 | 1995-08-04 | Toshiba Corp | System specification deciding device |
-
2016
- 2016-05-09 CN CN201610297267.0A patent/CN106021853B/en active Active
Patent Citations (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN103134433A (en) * | 2013-02-02 | 2013-06-05 | 青岛理工大学 | Method of identifying slip factors causing slope instability by utilizing displacement monitoring |
| CN104899380A (en) * | 2015-06-11 | 2015-09-09 | 武汉大学 | Side slope stable reliability sensitivity analysis method based on Monte Carlo simulation |
Non-Patent Citations (3)
| Title |
|---|
| Rosenblueth法在边坡可靠度分析中的应用;李亮等;《水利水电科技进展》;20120630;第32卷(第3期);第53-55页 |
| 基于Bishop法假定的边坡临界滑动场方法及应用;李亮等;《中南大学学报（自然科学版）》;20110930;第42卷(第9期);第2848-2852页 |
| 边坡临界滑动面与临界可靠度滑动面对比分析;李亮等;《华中科技大学学报（自然科学版）》;20120930;第40卷(第9期);第81-84页 |
Also Published As
| Publication number | Publication date |
|---|---|
| CN106021853A (en) | 2016-10-12 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN106021853B (en) | A kind of development approach of stochastic modeling slope Analysis on Stable Reliability software | |
| Li et al. | Efficient and consistent reliability analysis of soil slope stability using both limit equilibrium analysis and finite element analysis | |
| von Haden et al. | Soils' dirty little secret: Depth‐based comparisons can be inadequate for quantifying changes in soil organic carbon and other mineral soil properties | |
| Tricarico | The near-Earth asteroid population from two decades of observations | |
| Niemi et al. | Effects of bedrock landslides on cosmogenically determined erosion rates | |
| Van Werkhoven et al. | Sensitivity-guided reduction of parametric dimensionality for multi-objective calibration of watershed models | |
| Khoi et al. | The responses of hydrological processes and sediment yield to land‐use and climate change in the Be River Catchment, Vietnam | |
| US11268353B2 (en) | Energy deposit discovery system and method | |
| Muldrew et al. | The accuracy of subhalo detection | |
| Cheng | Seismic lateral earth pressure coefficients for c–φ soils by slip line method | |
| Montgomery Jr et al. | Dipole polarizabilities for a hydrogen atom confined in a penetrable sphere | |
| Reeves et al. | Extent of coterminous US rangelands: quantifying implications of differing agency perspectives | |
| Mavrotas et al. | Robustness analysis methodology for multi-objective combinatorial optimization problems and application to project selection | |
| Lloyd et al. | Archaeology and geostatistics | |
| US9897714B2 (en) | Use of monte carlo simulations for establishing correlations and their uncertainties | |
| Paterson et al. | Spatial variability of Australian soil texture: A multiscale analysis | |
| Pastén et al. | Time-based network analysis before and after the m w 8.3 illapel earthquake 2015 Chile | |
| CN109800459A (en) | Designing Method of Gravity Retaining Wall and device | |
| Ma et al. | Decomposition of small-footprint full waveform LiDAR data based on generalized Gaussian model and grouping LM optimization | |
| Holzmann et al. | Orbital-dependent backflow wave functions for real-space quantum Monte Carlo | |
| CN113360983B (en) | Slope reliability analysis and risk assessment method | |
| Mahmoudi et al. | Stochastic field simulation of slope stability problems: Improvement and reduction of computational effort | |
| Pulido-Velazquez et al. | Efficient conceptual model for simulating the effect of aquifer heterogeneity on natural groundwater discharge to rivers | |
| Rochman et al. | From flatness to steepness: Updating TALYS covariances with experimental information | |
| Dachanuwattana et al. | Application of assisted-history-matching workflow using proxy-based mcmc on a shale oil field case |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| C06 | Publication | ||
| PB01 | Publication | ||
| C10 | Entry into substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant |