CN106021853A - A method for developing slope stability reliability analysis software under spatial variation characteristics - Google Patents
A method for developing slope stability reliability analysis software under spatial variation characteristics Download PDFInfo
- Publication number
- CN106021853A CN106021853A CN201610297267.0A CN201610297267A CN106021853A CN 106021853 A CN106021853 A CN 106021853A CN 201610297267 A CN201610297267 A CN 201610297267A CN 106021853 A CN106021853 A CN 106021853A
- Authority
- CN
- China
- Prior art keywords
- slope
- bar
- analysis
- unstability
- soil
- 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.)
- Granted
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 field of slope stability analysis software development and relates to a method for developing slope stability reliability analysis software under spatial variation characteristics. The method comprises the steps of on the basis of preprocessed data input, performing slope discretization and integration analysis to obtain a safety coefficient of a specific instability mode; performing a certain number of times of minimum safety coefficient search and determining main instability areas; finally realizing slope stability reliability analysis software development based on multiple main instability modes through the Monte Carlo sampling method. The method gives full consideration to system features brought by the spatial variation characteristics of soil mass materials, fills up the blank of system feature calculation caused by spatial variation characteristics in conventional commercial software, and has a high engineering application value and a good commercial prospect.
Description
Technical field
The invention belongs to the technical field of slope stability analysis software development, relate to a kind of stochastic modeling slope steady
Determine the development approach of reliability analysis software, particularly a kind of determine stochastic modeling slope system based on limiting equilibrium method
The response of system, and the software development methodology of reliability analysis of slope stability is carried out based on system response.
Background technology
Stability of slope refers to that natural slope or Artificial Side-slope keep condition and the ability of safety and stability.The rock of this two classes side slope
The soil body is gradually changed under various internal and external factor effects, and slope body stress state changes the most therewith, when sliding force or the power of toppling reach
So that exceeding skid resistance or anchorage and during disequilibrium, i.e. occurring becoming destroying, cause disaster or threaten building safety.
Reliability analysis of slope stability is one of very important problem in geotechnical engineering design field, Slope Design or
During supporting, need to assess the possible failure probability of side slope and unstability region quantitatively.During traditional Slope Design, need by
Carry out limit equilibrium analysis in business software or calculate the antiskid minimum safety factor of stability of slope based on strength reduction method
And corresponding unstability region, and it is 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 presents obvious space
Variation property, this stochastic modeling causes side slope to present system performance when unstability, say, that have during slope instability
The main unstability region of more than one, this system performance seldom relates in conventional business software.At present, market does not also have
Have a kind of it can be considered that the reliability analysis of slope stability software of soil body material stochastic modeling.
Because above-mentioned analysis, exploitation is it can be considered that the reliability analysis of slope stability of soil body material stochastic modeling is soft
Part very ratio is wanted, and has stronger engineer applied simultaneously and is worth and commercial promise.
Summary of the invention
According to above the deficiencies in the prior art, the present invention provides a kind of stochastic modeling slope Analysis on Stable Reliability
The development approach of software, it is possible to fully take into account the system performance that soil body material stochastic modeling brings.
The development approach of a kind of stochastic modeling slope Analysis on Stable Reliability software of the present invention, its feature
Be to include implemented below process: on the basis of pre-processing data inputs, carry out side slope discretization and integrated analysis, draw to
Determine the safety coefficient of Failure Model, and then the minimum safety factor carrying out certain number of times searched for and determines main unstability region,
Reliability analysis of slope stability software developments based on multiple main Failure Models are realized finally by Monte Carlo sampling method.
Specifically include implemented below process:
Pre-treatment is analyzed:
(1) related data for calculating stability of slope is read, including reading side slope geometric profile data, soil body material statistical number
According to, saturation position data or pore pressure data and external load data；
(2) the Failure Model type of slope sliding is supposed；
(3) determine the virtual soil layer number of each side slope soil layer according to the fluctuation range value in soil body material statistical data, go forward side by side
The secondary of row side slope geometric profile data updates；
Deterministic parsing:
(4) given Failure Model is carried out discretization, obtain a series of vertical soil bar, and it is several to combine the side slope after secondary updates
What model, draws the relevant parameter of each vertical soil bar；
(5) safety coefficient of prescribed limit balance method solves, on the basis of the relevant parameter obtaining all discrete vertical soil bars,
Bishop approach is utilized to calculate the safety coefficient of given Failure Model；
(6) convert different potential unstability regions, carry out solving of safety coefficient according to step (5), eventually pass through to compare and draw
There is the unstability region of minimum safety factor；
Slope system in response to determining that:
(7) in all of stochastic variable is carried out following iteration: the value arranging this stochastic variable is that its average deducts 1
Times standard deviation, remaining stochastic variable is taken as its average, after the value determining stochastic variable, carry out step (4), (5),
(6) computational analysis, draws the unstability region of the minimum safety factor under this kind of operating mode and correspondence thereof；
(8) all of stochastic variable is carried out the iterative computation of step (7), final each stochastic variable corresponding, all obtain one
The unstability region of individual minimum safety factor and correspondence thereof；
(9) the unstability region that step (7) and (8) obtain is collected, be regarded as the key component of slope system, limit
The Whole Response of slope system can be represented by these discrete unstability regions；
Reliability of slope is analyzed and post processing:
(10) generation meets the Monte-Carlo step sample value of stochastic variable distribution, in each Monte-Carlo step sample value
Under, for each the discrete unstability region obtained in step (9), carry out step (4) and the computational analysis of (5), draw every
The safety coefficient in one discrete unstability region, the safety coefficient that relatively all discrete unstability regions are corresponding, select minimum
Safety coefficient is as slope system response under this Monte-Carlo step sample value, simultaneously, it may be determined that this minimum safe system
The unstability region that number is corresponding；
(11) after the side slope response that all sample values are corresponding is obtained, the side slope response Monte Carlo sample less than 1 can be added up
Value number, is defined as the failure probability of side slope, this failure probability value by the ratio of this number with total Monte Carlo sample value number
The reliability degree of side slope can be represented；Additionally, there is the number of times of minimum safety factor and the most several in each unstability region
What position may be displayed on side slope profile, in order to more intuitively determines the main source that slope system responds.
Wherein, preferred version is as follows:
Side slope cross-sectional data described in step (1) includes slope height, slope angle, soil layer number and toe and top, slope expanded range
Scope；Soil body material statistical data includes average and standard deviation and the sign soil parameters sky of unit weight, cohesive strength, internal friction angle
Between the fluctuation range value of variation property degree.
The Failure Model of the slope sliding described in step (2) includes circular arc Failure Model and non-circular arc Failure Model.
The relevant parameter of the vertical soil bar described in step (4) include at the bottom of coordinate, bar at the bottom of the bar of each vertical soil bar with ground
The coordinate that face is corresponding, and internal friction angle, cohesive strength and the bar bottom outlet pressure data that vertical soil is at the bottom of the deadweight of bar, bar.
The formula of the Bishop approach described in step (5) is:
Wherein, FSFor safety coefficient, the i-th vertical soil bar width bi, bottom surface inclination alphai, conduct oneself with dignity Wi, bar bottom outlet pressure ui, internal friction angle, cohesive strength ci。
Step (10) utilize Cholesky decomposition method generate the Monte-Carlo step sample value meeting stochastic variable distribution.
It is an advantage of the current invention that: (1) has taken into full account the stochastic modeling of Soil Parameters, carries out on this basis
The secondary of side slope geometric profile data updates, and based on traditional limiting equilibrium method being determined property analysis, by random
The iterative analysis one by one of variable, the final response source obtaining slope system, utilize these response sources to carry out slope system reliability
Analyze, and in post processing, show failure probability and each response source percentage contribution to slope system of slope system.(2) fill out
The calculating having mended the system performance that current business software is brought because of stochastic modeling is blank, has stronger engineer applied and is worth
And commercial promise.
Accompanying drawing explanation
Fig. 1 is the FB(flow block) of the present invention.
Detailed description of the invention
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 implemented below process:
Pre-treatment is analyzed:
(1) related data for calculating stability of slope is read, including reading side slope geometric profile data, soil body material statistical number
According to, saturation position data or pore pressure data and external load data.Wherein, side slope cross-sectional data include slope height, slope angle,
Soil layer number and toe push up the scope of expanded range with slope；Soil body material statistical data includes unit weight, cohesive strength, internal friction angle
Average and standard deviation and characterize the fluctuation range value of soil parameters stochastic modeling degree.Need to offer public number herein
Group preserves these data.
(2) the Failure Model type of slope sliding, such as circular arc Failure Model or non-circular arc Failure Model are supposed.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 variablees such as radius, needing to judge whether circular arc has intersection point with side slope ground herein, if having, then needing to preserve itself and side slope ground
Two intersection point slipping into a little and skidding off a little as unstability region in face；If there is no intersection point, then need to reject this Failure Model.
(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 carrying out side slope geometric profile data updates, need to offer new array several to store the side slope after secondary updates herein
What cross-sectional data.Need to set option herein and independently determined the degree that cross-sectional data secondary updates by user, i.e. true by user
The product of the coefficient between fixed 0.1 ~ 0.2, this coefficient and fluctuation range is as the foundation updated.
Deterministic parsing:
(4) selected the spacing of vertical soil bar by user, certainly skid off and a little start, a little terminate to slipping into, given Failure Model is carried out
Discretization, obtains a series of vertical soil bar, and combines the side slope geometric model after secondary updates.Need to offer array note herein
Record coordinate corresponding with ground at the bottom of coordinate, bar at the bottom of the bar of each vertical soil bar, and at the bottom of the vertical the most native deadweight of bar, bar in rub
Wipe angle, cohesive strength and bar bottom outlet pressure data.
(5) the stable safety system in the unstability region after the calculating of the Bishop approach in limit of utilization balance method is discrete
Number, needs to work out subprogram herein and is iterated calculating.
(6) according to certain change rule, such as gridding method, complex method, harmonic search algorithm convert different diving
In unstability region, subprogram in invocation step (5) calculates the safety coefficient of different Failure Model, and offers array and protect
Deposit, through relatively or optimize determine minimum value of safety factor value.
Slope system in response to determining that:
(7) in all of stochastic variable is carried out following iteration: the value arranging this stochastic variable is that average deducts 1 times
Standard deviation, remaining stochastic variable is taken as its average, after the value determining stochastic variable, is considered as determining by these values
Value also carries out step (4), (5), the calculating of (6), until finally determining safety coefficient and the unstability region of correspondence thereof of minimum,
Need to offer the mathematical description variable in array record unstability region herein.
(8) all of stochastic variable is carried out the iterative computation of step (7), final each stochastic variable corresponding, all
To a minimum safety factor and the unstability region of correspondence thereof, and it is saved in the array offered.
(9) representative that the unstability region being saved in array is responded as slope system, say, that side slope is in difference
Soil parameters under, its minimum safety factor value can be determined by the tentative calculation in these unstability regions.
Reliability of slope is analyzed and post processing:
(10) utilize the sample value of Cholesky decomposition method generating random variable, Monte-Carlo step need to be determined by user herein
Number of times, for each sample value, is regarded as side slope and inputs definite value really, determines that the unstability region being saved in array is corresponding
Value of safety factor value, select minima as slope system response under this sample value, and judge whether this response value is less than
1, the most then this sample is called inefficacy sample, and unstability region corresponding to this response value is referred to as marking area；If it is not, be then non-
Inefficacy sample.
(11) adding up in all sampling samples the number of the sample that lost efficacy, this number claims with the ratio of total sampling number of samples
The failure probability for slope system.The unstability region preserved in array can judge limit intuitively as the number of times of marking area
The response source of slope system, needs to offer array herein and records each unstability region number of times as marking area, and final on limit
The position in each unstability region and corresponding marking area number of times is shown, in order to display for a user slope system on the section of slope
Response source.
Claims (7)
1. the development approach of a stochastic modeling slope Analysis on Stable Reliability software, it is characterised in that include following reality
Existing process: on the basis of pre-processing data inputs, the peace carry out side slope discretization and integrated analysis, drawing given Failure Model
Overall coefficient, and then the minimum safety factor carrying out certain number of times searches for and determines main unstability region, finally by Meng Teka
Sieve sampling approach realizes reliability analysis of slope stability software developments based on multiple main Failure Models.
The development approach of a kind of stochastic modeling slope Analysis on Stable Reliability software the most according to claim 1,
It is characterized in that including implemented below process:
Pre-treatment is analyzed:
(1) related data for calculating stability of slope is read, including reading side slope geometric profile data, soil body material statistical number
According to, saturation position data or pore pressure data and external load data；
(2) the Failure Model type of slope sliding is supposed；
(3) determine the virtual soil layer number of each side slope soil layer according to the fluctuation range value in soil body material statistical data, go forward side by side
The secondary of row side slope geometric profile data updates；
Deterministic parsing:
(4) given Failure Model is carried out discretization, obtain a series of vertical soil bar, and it is several to combine the side slope after secondary updates
What model, draws the relevant parameter of each vertical soil bar；
(5) safety coefficient of prescribed limit balance method solves, on the basis of the relevant parameter obtaining all discrete vertical soil bars,
Bishop approach is utilized to calculate the safety coefficient of given Failure Model；
(6) convert different potential unstability regions, carry out solving of safety coefficient according to step (5), eventually pass through to compare and draw
There is the unstability region of minimum safety factor；
Slope system in response to determining that:
(7) in all of stochastic variable is carried out following iteration: the value arranging this stochastic variable is that its average deducts 1
Times standard deviation, remaining stochastic variable is taken as its average, after the value determining stochastic variable, carry out step (4),
(5), the computational analysis of (6), draw the unstability region of the minimum safety factor under this kind of operating mode and correspondence thereof；
(8) all of stochastic variable is carried out the iterative computation of step (7), final each stochastic variable corresponding, all obtain one
The unstability region of individual minimum safety factor and correspondence thereof；
(9) the unstability region that step (7) and (8) obtain is collected, be regarded as the key component of slope system, limit
The Whole Response of slope system can be represented by these discrete unstability regions；
Reliability of slope is analyzed and post processing:
(10) generation meets the Monte-Carlo step sample value of stochastic variable distribution, in each Monte-Carlo step sample value
Under, for each the discrete unstability region obtained in step (9), carry out step (4) and the computational analysis of (5), draw every
The safety coefficient in one discrete unstability region, the safety coefficient that relatively all discrete unstability regions are corresponding, select minimum
Safety coefficient is as slope system response under this Monte-Carlo step sample value, simultaneously, it may be determined that this minimum safe system
The unstability region that number is corresponding；
(11) after the side slope response that all sample values are corresponding is obtained, the side slope response Monte Carlo sample less than 1 can be added up
Value number, is defined as the failure probability of side slope, this failure probability value by the ratio of this number with total Monte Carlo sample value number
The reliability degree of side slope can be represented；Additionally, there is the number of times of minimum safety factor and the most several in each unstability region
What position may be displayed on side slope profile, in order to more intuitively determines the main source that slope system responds.
The development approach of a kind of stochastic modeling slope Analysis on Stable Reliability software the most according to claim 2,
It is characterized in that the side slope cross-sectional data described in step (1) includes that slope height, slope angle, soil layer number and toe extend with top, slope
The scope of scope；Soil body material statistical data includes average and standard deviation and the sign soil layer of unit weight, cohesive strength, internal friction angle
The fluctuation range value of parameter space variation property degree.
The development approach of a kind of stochastic modeling slope Analysis on Stable Reliability software the most according to claim 2,
It is characterized in that the Failure Model of the slope sliding described in step (2) includes circular arc Failure Model and non-circular arc Failure Model.
The development approach of a kind of stochastic modeling slope Analysis on Stable Reliability software the most according to claim 2,
It is characterized in that the relevant parameter of the vertical soil bar described in step (4) include at the bottom of coordinate, bar at the bottom of the bar of each vertical soil bar with
The coordinate that ground is corresponding, and internal friction angle, cohesive strength and the bar bottom outlet pressure data that vertical soil is at the bottom of the deadweight of bar, bar.
The development approach of a kind of stochastic modeling slope Analysis on Stable Reliability software the most according to claim 2,
The formula that it is characterized in that the Bishop approach described in step (5) is:
Wherein, FSFor safety coefficient, the i-th vertical soil bar width bi, bottom surface inclination alphai, conduct oneself with dignity Wi, bar bottom outlet pressure ui, internal friction angleCohesive strength ci。
The development approach of a kind of stochastic modeling slope Analysis on Stable Reliability software the most according to claim 2,
It is characterized in that step (10) utilizing Cholesky decomposition method generate the Monte-Carlo step sample meeting stochastic variable distribution
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 true CN106021853A (en) | 2016-10-12 |
| CN106021853B 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) |
Cited By (12)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN106709182A (en) * | 2016-12-26 | 2017-05-24 | 华中科技大学 | Safety assessment method for stable reliability of consequent bedding rock slope 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 |
| CN108629111A (en) * | 2018-05-02 | 2018-10-09 | 四川大学 | A kind of analogy method of concrete gravity dam material parameter Spatial Variability |
| CN109063285A (en) * | 2018-07-18 | 2018-12-21 | 南昌大学 | A kind of slight slope layout scheme of boreholes design method |
| CN109446616A (en) * | 2018-10-18 | 2019-03-08 | 东北电力大学 | A kind of homogeneous slope method for evaluating reliability |
| CN109614708A (en) * | 2018-12-12 | 2019-04-12 | 青岛理工大学 | Building underlying security distance and the design method of embedded depth of foundation in side slope |
| CN109977554A (en) * | 2019-03-28 | 2019-07-05 | 青岛理工大学 | A kind of appraisal procedure of slope sliding area |
| CN110245429A (en) * | 2019-06-18 | 2019-09-17 | 贵州正业工程技术投资有限公司 | Convex annular Slope Stability Evaluation method based on Bishop approach |
| CN111444649A (en) * | 2020-03-24 | 2020-07-24 | 成都理工大学 | Slope system reliability analysis method based on intensity reduction method |
| CN113239435A (en) * | 2021-05-11 | 2021-08-10 | 青岛理工大学 | Novel 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 (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JPH07200534A (en) * | 1993-12-28 | 1995-08-04 | Toshiba Corp | System specification deciding device |
| 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 |
-
2016
- 2016-05-09 CN CN201610297267.0A patent/CN106021853B/en active Active
Patent Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JPH07200534A (en) * | 1993-12-28 | 1995-08-04 | Toshiba Corp | System specification deciding device |
| 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 |
|---|
| 李亮等: "Rosenblueth法在边坡可靠度分析中的应用", 《水利水电科技进展》 * |
| 李亮等: "基于Bishop法假定的边坡临界滑动场方法及应用", 《中南大学学报（自然科学版）》 * |
| 李亮等: "边坡临界滑动面与临界可靠度滑动面对比分析", 《华中科技大学学报（自然科学版）》 * |
Cited By (17)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN106709182A (en) * | 2016-12-26 | 2017-05-24 | 华中科技大学 | Safety assessment method for stable reliability of consequent bedding rock slope under earthquake action |
| 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 |
| CN108629111A (en) * | 2018-05-02 | 2018-10-09 | 四川大学 | A kind of analogy method of concrete gravity dam material parameter Spatial Variability |
| CN109063285A (en) * | 2018-07-18 | 2018-12-21 | 南昌大学 | A kind of slight slope layout scheme of boreholes design method |
| CN109446616A (en) * | 2018-10-18 | 2019-03-08 | 东北电力大学 | A kind of homogeneous slope method for evaluating reliability |
| CN109614708A (en) * | 2018-12-12 | 2019-04-12 | 青岛理工大学 | Building underlying security distance and the design method of embedded depth of foundation in side slope |
| CN109977554A (en) * | 2019-03-28 | 2019-07-05 | 青岛理工大学 | A kind of appraisal procedure of slope sliding area |
| CN109977554B (en) * | 2019-03-28 | 2020-06-30 | 青岛理工大学 | Method for evaluating sliding area of side slope |
| CN110245429A (en) * | 2019-06-18 | 2019-09-17 | 贵州正业工程技术投资有限公司 | Convex annular Slope Stability Evaluation method based on Bishop approach |
| 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 |
| CN111444649A (en) * | 2020-03-24 | 2020-07-24 | 成都理工大学 | Slope system reliability analysis method based on intensity reduction method |
| CN113239435A (en) * | 2021-05-11 | 2021-08-10 | 青岛理工大学 | Novel method for determining optimal water discharge speed of reservoir |
| 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 |
Also Published As
| Publication number | Publication date |
|---|---|
| CN106021853B (en) | 2019-02-12 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN106021853A (en) | A method for developing slope stability reliability analysis software under spatial variation characteristics | |
| Li et al. | Efficient and consistent reliability analysis of soil slope stability using both limit equilibrium analysis and finite element analysis | |
| Dimitriadis et al. | Comparative evaluation of 1D and quasi-2D hydraulic models based on benchmark and real-world applications for uncertainty assessment in flood mapping | |
| Niemi et al. | Effects of bedrock landslides on cosmogenically determined erosion rates | |
| Abbiendi et al. | Measurement of| Vcb| using B̄0→ D∗+ ℓ− ν̄ decays | |
| US11268353B2 (en) | Energy deposit discovery system and method | |
| Mavrotas et al. | Robustness analysis methodology for multi-objective combinatorial optimization problems and application to project selection | |
| Montgomery Jr et al. | Dipole polarizabilities for a hydrogen atom confined in a penetrable sphere | |
| Anastasiou et al. | Perturbative QCD effects and the search for a\HWWlept signal at the Tevatron | |
| Lloyd et al. | Archaeology and geostatistics | |
| Vetter et al. | Global sensitivity analysis for stochastic ground motion modeling in seismic-risk assessment | |
| Xiao et al. | Structural reliability analysis using combined space partition technique and unscented transformation | |
| Yue et al. | A multi‐grid method of high accuracy surface modeling and its validation | |
| Panzeri et al. | Comparison of Ensemble Kalman Filter groundwater-data assimilation methods based on stochastic moment equations and Monte Carlo simulation | |
| Li et al. | Reliability analysis of serviceability performance for an underground cavern using a non-intrusive stochastic method | |
| Georgioudakis et al. | Probabilistic shape design optimization of structural components under fatigue | |
| Oladyshkin et al. | Chaos expansion based bootstrap filter to calibrate co2 injection models | |
| Farrow | A Monte Carlo approach to the 4D scattering equations | |
| Hardyniec et al. | A new efficient method for determining the collapse margin ratio using parallel computing | |
| Eshagh et al. | Software for generating gravity gradients using a geopotential model based on an irregular semivectorization algorithm | |
| Ahangar-Asr et al. | Determination of the most probable slip surface in 3D slopes considering the effect of earthquake force direction | |
| Cheng et al. | Simplified approach for locating the critical probabilistic slip surface in limit equilibrium analysis | |
| Mahmoudi et al. | Stochastic field simulation of slope stability problems: Improvement and reduction of computational effort | |
| US10209403B2 (en) | Method of modelling a subsurface volume | |
| US20210150440A1 (en) | Upper Confidence Bound Algorithm for Oilfield Logic |
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 |