CN109063285B - A Design Method of Boring Hole Layout Scheme in Soil Slope - Google Patents

Abstract

A design method for an earth slope drilling hole arrangement scheme comprises the steps of firstly establishing an earth mass parameter model based on a non-stationary random field theory, further reflecting the influence of field information obtained from different drilling holes on earth mass parameter probability distribution through a Bayesian update analysis method, finishing the estimation of spatial variation earth mass parameter statistical characteristics and slope posterior failure probability, and finally determining the optimal drilling hole position and the optimal drilling hole distance of a slope according to information analysis. The method has the advantages of clear concept, high calculation precision, reasonable description of the spatial variability characteristics of the soil body parameters and the like, and can obtain more valuable field test data on the premise of consuming the least engineering investigation cost.

Description

A Design Method of Boring Hole Layout Scheme on Soil Slope

technical field

The invention relates to a method for designing a drilling arrangement scheme of a soil slope, in particular to a method for designing a drilling arrangement for an undrained saturated cohesive soil slope.

Background technique

Drilling is an important technical means of geological exploration. It is widely used in finding and exploring various minerals, oil and gas reservoirs, groundwater, geothermal and strata, and provides geological data for water conservancy construction, engineering construction and transportation facilities. Especially in slope engineering design, the acquisition of various parameters of the soil is particularly important. In order to obtain more realistic drilling experiment data, it is necessary to design a reasonable drilling layout scheme. Drilling layout mainly involves determining the drilling position, drilling spacing, drilling depth and number of drillings. The optimal drilling layout scheme can achieve the most valuable field test data under the premise of saving engineering survey costs.

At present, there is no unified understanding of the drilling layout design method, and only the "Code for Geotechnical Engineering Exploration (GB50021-2001)" provides the corresponding calculation regulations:

(1) The exploration line should be arranged vertically to the direction of the slope, and when there are weak interlayers or unfavorable structural planes, the drilling should be appropriately intensified. The depth of the exploration hole should pass through the potential sliding surface and penetrate 2-5 m into the stable layer. In addition to conventional drilling, boreholes, trenches, wells and deviated holes can be used as required.

(2) The impact of exploration on the natural environment of the project should be considered when arranging the exploration work to prevent damage to underground pipelines, underground engineering and the natural environment. Boreholes, exploratory wells and trenches should be properly backfilled after completion.

(3) The distance between exploration points on the main exploration line should not be greater than 50 m, and not less than 3 exploration points.

(4) The interval of exploration lines for slopes with exploration grade 1 is 20-30 m, and the interval of exploration points is 15-20 m; the interval of exploration lines for slopes with exploration grade 2 is 30-40 m, and the interval of exploration lines is 25-30 m; for slopes with an exploration level of third grade, the interval between exploration lines is 40-50 m, and the interval between exploration points is 30-40 m.

At present, how to design the optimal soil slope drilling arrangement, including determining the optimal drilling position, drilling spacing, and drilling number, is still a key problem under the premise of knowing the prior information of rock and soil parameters.

Imperfect drilling layout design theory and unreasonable drilling layout scheme design will lead to changes in site exploration schemes and increase construction costs. Not only is it difficult to obtain valuable field test data, but it may even cause safety accidents. For example, in September 2014, a large-scale landslide occurred in Zigui County, Hubei Province, in the Three Gorges Reservoir area, which caused the overall damage of Daling Power Station and the interruption of National Highway 348. The reason was that no real field experimental data was obtained during geological exploration, resulting in overestimation of the carrying capacity of shallow foundations. . Another example is that the 4 ^# coal seam of Shaqu Mine has not been well optimized due to the well-optimized drilling layout parameters, resulting in frequent stoppages of the tunneling unit (average 1.2 times/h) and frequent stoppages (average 3.6 times/month), which seriously affect the connection of excavation.

Therefore, there are many problems to be solved urgently in the design process of the current slope drilling layout scheme, such as:

(1) Affected by deposition, post-sedimentation, chemical weathering, transportation, and load history, even the soil properties at different positions of the homogeneous soil layer are not only different, but also have certain correlations, which are inherent in soil parameters Due to the spatial variability of soil parameters, the current design of drilling layout schemes does not reasonably describe the influence of spatial variability of soil parameters, which will result in conservative design schemes.

(2) The prior information of soil parameters is very critical to the optimal design of drilling layout schemes. However, the characteristic that the mean value and standard deviation of soil parameters gradually increase along the buried depth is basically not considered when characterizing the prior information of soil parameters. It will cause a large deviation between the designed drilling layout and the actual project.

(3) The commonly used multi-objective optimization design method not only has a very large amount of calculation in the optimization process, but also cannot make good use of limited field test data and other site information; the Markov chain Monte Carlo simulation method is difficult to solve the soil parameter space High-dimensional optimization design problem of slope drilling layout scheme with variability.

Contents of the invention

The purpose of the present invention is to provide a method for designing a soil slope drilling arrangement scheme for the above-mentioned state of the art, to carry out accurate and efficient optimization design on the drilling arrangement scheme, and to realize determining the optimal drilling position and position of the slope in a more convenient way. Optimum borehole spacing and the most valuable survey experiment data can be obtained with the lowest cost of engineering survey, so as to provide more comprehensive stratum information for understanding slope stability.

The present invention is achieved through the following technical solutions.

A kind of earth slope drilling arrangement scheme design method according to the present invention, according to the following steps.

(1) Construct a non-stationary random field model of soil parameters.

Collect approximate prior information of soil parameters (mean value, standard deviation, probability distribution, fluctuation range, etc.), divide the slope random field grid, and generate non-stationary random field realization values of soil parameters that gradually increase with slope depth. And the realized value of the random field is assigned to the slope model in turn.

(2) Randomly arrange representative boreholes and simulate virtual field test data.

According to the "Code for Geotechnical Engineering Exploration (GB50021-2001)" and the grade of the slope, some representative drill holes are randomly arranged on the slope surface with a series of drill hole positions and drill hole spacing, and for each representative drill hole , based on the prior information of the soil parameters, the quasi random sampling technique is used to simulate the virtual field test data obtained from the borehole.

(3) Establish a model for updating the statistical characteristics of spatially variable soil parameters.

Based on the virtual field test data, establish the likelihood function considering the uncertainty of measurement and model conversion, and determine the constants related to the likelihood function, define a new failure area, and calculate the occurrence probability of site information events by using the subset simulation method , from which the failure samples are obtained, and then the posterior probability density functions of spatially variable soil parameters corresponding to different representative borehole combinations are estimated according to these failure samples.

(4) Calculate the posterior failure probability of the slope.

On the basis of using the subset simulation method to estimate the posterior probability density function of spatially variable soil parameters, the slope failure area is constructed, and the subset simulation method is used again to calculate the slope posterior failure probability corresponding to different representative borehole combinations.

(5) Analysis of site information.

Based on the posterior probability density function of soil parameters and the posterior failure probability of the slope, the expected value of site information is used to reflect the influence of site information on slope reliability update and information analysis, and the optimal representative drilling combination is determined. The corresponding drilling position and drilling spacing can guide the design of the optimal slope drilling layout.

When using the above analysis model to calculate the optimal borehole layout: the soil shear strength parameters can be simulated as a non-stationary log-normal random field, and the volumetric value of the soil can be regarded as a constant; the prior information of the described site can be obtained from the project It is obtained from data such as experience, engineering analogy, geological survey reports and related literature.

Site information such as field test data collected from different boreholes in a specific site is used to update the statistical characteristics of soil parameters. Density function and slope posterior failure probability to reflect. The smaller the discreteness of the posterior probability density function and the lower the posterior failure probability of the slope, the more reasonable the borehole layout is.

The present invention is characterized in that, based on the Bayesian method, the probability density function of spatially variable soil parameters is updated and the posterior failure probability of the slope is calculated, and the optimal drilling position and the optimal drilling distance of the slope are determined according to the analysis of site information. This method has the advantages of clear concept, high calculation accuracy, and reasonable description of the inherent spatial variability of soil parameters, and can obtain more valuable field test data under the premise of consuming the least engineering survey cost.

Description of drawings

Accompanying drawing 1 is the three-dimensional arrangement diagram of drilling.

Accompanying drawing 2 is the drilling layout plan.

Accompanying drawing 3 is a section view of a borehole.

In the attached drawings: d ₁ is the horizontal distance of the borehole, d ₂ is the axial distance of the borehole, CPT1, ..., CPT14 are the static penetration drilling, 1-2 is plain fill, 3-2 is silty clay, 3-3 is siltstone, W ₂ is weakly weathered soil layer, and W ₃ is strongly weathered soil layer.

Detailed ways

The specific implementation manner of the present invention will be further described below in conjunction with the accompanying drawings.

(1) Construct a non-stationary random field model of soil parameters.

The soil on the slope surface is affected by factors such as ground rainfall, weathering, vegetation transpiration and traffic, so the logarithmic normal distribution is used to simulate the uncertainty of the shear strength parameters of the slope soil surface; the lognormal distribution is used to simulate the uncertainty of the soil surface The variability of the rate (trend component) of the shear strength parameters of the soil mass increases with the buried depth; the variability of the random fluctuation component of the shear strength parameters of the soil mass is simulated by using a stationary normal random field with a mean of 0 and a constant standard deviation. Then, the slope random field unit grid is divided, and the Karhunen-Loève series expansion method is used to discretize the stationary normal random field. On this basis, the realized value of the non-stationary random field of soil parameters is calculated.

(2) Establish a model for updating the statistical characteristics of spatially variable soil parameters.

Select boreholes at different positions and any combination of two boreholes with different spacings from CPT1,…, CPT14, and simulate different soil layers (plain fill, silty clay, siltstone) obtained from them based on the Quasi random sampling technique Based on the virtual field test data, the likelihood function considering the uncertainty of measurement and model conversion is established, and the constants related to the likelihood function are determined, a new failure area is defined, and Bayesian update and structural reliability analysis are established. The bridge between them converts the complex Bayesian update problem into an equivalent structural reliability problem, and uses the subset simulation method to solve the structural reliability problem, estimating the posterior probability density function of the spatial variation parameter.

(3) Calculate the posterior failure probability.

On the basis of using the subset simulation method to estimate the posterior probability density function of the spatially variable soil parameters, the failure area of the slope is constructed, and the subset simulation method is used again to calculate the posterior failure probability of the slope.

(4) Analysis of site information.

By comparing the experimental data obtained by different drilling layout schemes, the amount of information provided to understand the stability of the slope can be determined to determine the optimal drilling position and optimal drilling spacing. The greater the value of information, the greater the amount of information provided by the experimental data obtained in a certain drilling layout plan for understanding the slope stability, that is, the more reasonable the designed drilling position and spacing, and vice versa.

The specific implementation examples of the present invention are as follows.

1. The slope height of an undrained saturated clay slope is 10 m, the slope angle is 26.6°, and the soil bulk density is 20 kN/m ³ as a constant. The horizontal distance of the slope is 60 m, and the elevation is -20 m~0.

2. According to the present invention, the design steps of the above-mentioned slope drilling layout scheme are as follows.

(1) Construct a non-stationary random field model of soil parameters.

Based on the collected prior information of the site, the undrained shear strength of the slope surface is simulated as a log-normal random variable with a priori mean of 14.67 kPa and a priori standard deviation of 4.034 kPa; The rate of increase (trend component) is simulated as a lognormal random variable with a priori mean of 0.3 and a priori standard deviation of 0.09; the fluctuation component of the soil shear strength parameter is simulated as a priori mean of 0 and a priori standard deviation is a stationary normal random field of 0.24, and the horizontal and vertical fluctuation ranges of the soil parameters obtained from the field cross-plate shear test are 38 m and 3.8 m, respectively. The slope random field unit grid is divided into 910 quadrilateral and triangular mixed units with horizontal and vertical dimensions of 2.0 m and 0.5 m, respectively. Then, the Karhunen-Loève series expansion method is used to simulate the stationary normal random field of the fluctuation component of the soil parameters, and on this basis, the realized value of the non-stationary random field of the soil parameters is calculated.

(2) Establish a model for updating the statistical characteristics of spatially variable soil parameters.

Select boreholes at different positions and any two borehole combinations with different spacings from CPT1,...,CPT14, and multiply the non-stationary random field realized value with the total error realized value considering the measurement and simulation conversion uncertainties to generate Multiple sets of virtual field test data obtained from some boreholes, where the total error is modeled as a lognormal distribution with a median of 1.0 and a constant standard deviation. Based on this, the likelihood function required by Bayesian analysis is established, a new failure region is defined, and the complex Bayesian update problem is transformed into an equivalent structural reliability problem.

(3) Estimate the posterior probability density function of the soil parameters and the posterior failure probability of the slope.

The subset simulation method is used to estimate the posterior probability density function of soil parameters and the posterior failure probability of slope, in which the number of samples for each layer is 1000, and the conditional probability is 0.1.

(4) Analysis results of site information.

According to the obtained slope posterior failure probability, Monte Carlo simulation is used to calculate the expected value of site information. The larger the expected value of the amount of information, the larger the amount of information provided by the field test data obtained from a certain drilling position to understand the formation characteristics and slope stability. It can be seen from the calculation results that when the drilling position gradually changes from the left side of the slope to the right side of the slope, the expected value of the amount of information first increases and then decreases, reaches the maximum near the top of the slope, and decreases to the minimum on the right side of the slope toe . Therefore, it can be inferred that the area near the top of the slope is the optimal drilling position. Similarly, by comparing the expected value of information calculated from the experimental data obtained from any combination of two boreholes with different spacings, the optimal drilling spacing can be obtained with a horizontal fluctuation range (19 m) that is about one-half times that of the boreholes.

Claims (3)

1. A method for designing an earth slope drilling arrangement scheme is characterized by comprising the following steps:

(1) Constructing a soil parameter non-stationary random field model:

collecting soil parameter prior information: dividing a slope random field grid into a mean value, a standard deviation, a probability distribution and a fluctuation range, generating a non-stationary random field realization value of which soil body parameters are gradually increased along with the slope burial depth, and sequentially assigning the random field realization value to a slope model;

(2) Representative boreholes were randomly placed and virtual field trial data was simulated:

according to geotechnical engineering exploration specifications and slope grades, randomly arranging a plurality of representative drill holes on the surface of a slope according to a series of drill hole positions and drill hole intervals, and simulating virtual field test data acquired from the drill holes by adopting a Quasi random sampling technology based on soil body parameter prior information aiming at each representative drill hole;

(3) Establishing a spatial variation soil parameter statistical characteristic updating model:

establishing a likelihood function considering measurement and model conversion uncertainty based on virtual field test data, determining a constant related to the likelihood function, defining a new failure area, calculating the occurrence probability of a field information event by adopting a subset simulation method, obtaining failure samples from the occurrence probability, and estimating posterior probability density functions of space variation soil body parameters corresponding to different representative borehole combinations according to the failure samples;

(4) Calculating the posterior failure probability of the slope:

on the basis of estimating the posterior probability density function of the spatial variation soil parameters by adopting a subset simulation method, constructing a slope failure area, and calculating the posterior probability of the slope corresponding to different representative drilling combinations by adopting the subset simulation method again;

(5) Analyzing the site information quantity:

based on a soil parameter posterior probability density function and a slope posterior failure probability, the influence of field information on slope reliability updating and information quantity analysis is reflected by utilizing a field information quantity expected value, and the larger the field information quantity expected value is, the larger the field test data obtained from a certain drilling position provides information quantity for understanding stratum characteristics and slope stability performance is, and the slope surface close to the top of the slope is taken as an optimal drilling position; also, the optimum drill hole pitch can be obtained by comparing the expected value of the amount of information calculated from the experimental data obtained from any two drill hole combinations at different pitches.

2. The method for designing an earth slope drilling arrangement scheme according to claim 1, wherein when the drilling arrangement is calculated: simulating the soil shear strength parameter into a non-stationary lognormal random field, and taking the soil volume weight as a constant; the site priors described are obtained from engineering experience, engineering analogies, geological survey reports and relevant literature data.

3. The method according to claim 1, wherein the field test data collected from different boreholes in a specific site is used to update the statistical characteristics of the soil parameters, and the influence of the field test data on the probability distribution of the soil parameters and the stability of the slope is reflected by the estimated posterior probability density function of the soil parameters and the posterior probability of failure of the slope, and the smaller the dispersion of the posterior probability density function is, the lower the posterior probability of failure of the slope is, indicating that the borehole is more reasonable to arrange.

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