CN112241594A

CN112241594A - Rapid optimization method for side slope exploration drilling arrangement scheme

Info

Publication number: CN112241594A
Application number: CN202011141849.2A
Authority: CN
Inventors: 胡金政; 张洁; 王天鹏; 黄宏伟
Original assignee: Tongji University
Current assignee: Tongji University
Priority date: 2020-10-22
Filing date: 2020-10-22
Publication date: 2021-01-19
Anticipated expiration: 2040-10-22
Also published as: CN112241594B

Abstract

The invention discloses a method for quickly optimizing a side slope exploration drilling arrangement scheme. The method comprises the steps of firstly establishing a spatial distribution model of soil body mechanical parameters based on a random field theory, further generating simulated random samples of soil body parameters, slope safety factors and survey data, establishing a regression analysis model based on the samples, estimating the posterior failure probability of the slope by using the regression model, further evaluating expected gains of all alternative survey schemes in the aspects of engineering safety and economy, and finally determining the optimal survey drilling arrangement scheme of the slope. The method can quantitatively describe the expected action of the survey data in the slope engineering, can quickly determine the optimal survey design scheme before the development of the survey work, and has the advantages of high calculation efficiency, clear calculation flow, simple operation and the like.

Description

Rapid optimization method for side slope exploration drilling arrangement scheme

Technical Field

The invention relates to optimization of a side slope exploration drilling arrangement scheme, in particular to optimization of an exploration drilling scheme for providing a basis for reinforcement design of an engineering side slope.

Background

Slope damage is a common disaster accident all over the world, and causes huge economic loss and casualties every year. The safety stability of the side slope is closely related to the properties of soil bodies forming the side slope, and in order to reasonably reinforce the side slope and meet the requirements of engineering safety and economy, the soil bodies of the side slope need to be tested through exploration drilling holes, so that the design parameter information of physical mechanics and the like can be obtained. Whether the design parameter information of the soil body can be more accurately acquired or not is judged, more valuable reference is provided for slope reinforcement design, and the key point is the design of a prospecting drilling scheme. When the survey data is lacked, the engineering safety is not well mastered, and the design is often over-conservative or even impossible. The optimal exploration drilling scheme can improve the safety of slope reinforcement design and save exploration cost and engineering cost.

At present, the design and optimization of the exploration drilling scheme lack a uniform standard, the regulations in relevant specifications are more general, and the actual operation is mostly determined based on engineering experience. As the soil body has a plurality of uncertain factors in the natural weathering, carrying and depositing processes, the physical and mechanical properties of the soil body have large nonuniformity in spatial distribution. The optimization theory of the current exploration drilling scheme is imperfect, so that the exploration drilling arrangement of some engineering projects is unreasonable, even the soil body information of key areas is omitted, the temporary exploration is supplemented and the engineering project design scheme is changed, the economy of the engineering projects is reduced, and potential safety hazards can be caused. For example, the important landslide zone is omitted due to incomplete investigation in European village hydropower station engineering until construction excavation is discovered [1 ]. In the investigation of reinforcing engineering of reservoir bank of a certain reservoir in Fujian, a weak stratum is not found out, and the deviation of the value of the shear strength is large, so that the glide force is increased due to the design error to generate landslide [2 ]. The design of a slope of a certain highway in Guangdong is too simple due to insufficient exploration drilling, and exploration and design change have to be added to additionally reinforce the slope after diseases are found [3 ].

The design and optimization of exploration drilling schemes mainly face the following problems:

(1) because the soil body has a plurality of uncertain factors in the natural weathering, carrying and depositing processes, the physical and mechanical properties of the soil body have great nonuniformity in spatial distribution, the existing exploration drilling hole arrangement method does not consider the influence of the factors, so that exploration omission is easily caused, and the reliability of exploration data is reduced;

(2) the existing exploration drilling arrangement method does not consider the influence of exploration data on the final design of the slope engineering, and the exploration and the design are separated from each other, so that the representativeness of the exploration data is insufficient;

(3) if the traditional Monte Carlo method is used for carrying out the whole process simulation of the survey design, wherein the repeated Bayesian updating algorithm and the double integral simulation are involved, the calculation efficiency is very low.

The following related documents:

[1] teaching and revelation in the work of engineering geological surveying of wejungo, european home and village hydropower stations [ J ]. hydroelectric generation, 1990, (02):32-34.

[2] A reason analysis [ A ]// national geotechnical and engineering academic congress corpus (upper book) [ C ].2003 ] of bank landslide caused by wearing a buzz-Fujian reservoir bank strengthening project.

[3] The method comprises the following steps of (1) analysis of the stability of a cutting slope of a certain highway in Guangdong [ J ] survey design of the Guangdong highway 2015, 157(1):30-34.

Disclosure of Invention

Aiming at the problems mentioned in the background technology, the invention provides a method for quickly optimizing a side slope exploration drilling arrangement scheme. Aiming at the problem (1), the method uses a random field model to consider the spatial nonuniformity of soil properties, and has good applicability to various probability distributions of soil parameters;

aiming at the difficult problem (2), the method takes expected safety and economic benefits as optimization targets, and the important value of the survey data on the design is quantified;

aiming at the problem (3), the method uses a regression analysis method, avoids a Bayesian updating algorithm and double integral simulation, and reduces the calculated amount by at least half in magnitude compared with the traditional method, for example, the traditional method needs 10,000 minutes of operation time, the method only needs less than 100 minutes, and the usability is greatly enhanced.

The purpose of the invention is as follows: the invention develops a method for quickly optimizing a side slope exploration drilling arrangement scheme. The method is characterized in that a space distribution model of soil body mechanical parameters is established based on a random field theory, the method can quantitatively describe the expected action of survey data in slope engineering, and an optimal survey design scheme can be quickly determined before the development of survey work.

The technical scheme is as follows:

a method for rapidly optimizing a side slope exploration drilling arrangement scheme comprises the following steps:

(1) estimating probability statistical information of soil body parameters, including an average value, a standard deviation, a probability distribution type, a relevant distance and the like, establishing a soil body parameter random field model based on the information, and generating a random simulation sample;

(2) establishing a slope stability analysis model, introducing the simulation samples of the random field model in the step (1) into the slope stability analysis model, and calculating a corresponding safety coefficient of each sample;

(3) establishing a conditional probability distribution model of the survey data according to the survey means, the test precision and the drilling arrangement of the alternative survey scheme, and further generating a sample simulating the survey data by using the conditional probability distribution based on each random field sample in the step (1);

(4) performing regression analysis on the safety factors generated in the step (2) and the sample of the simulated survey data to obtain a regression model for predicting the posterior failure probability according to the survey data;

(5) calculating the posterior failure probability corresponding to the simulated survey data generated in each step (3) by using the regression model obtained in the step (4), further obtaining a simulated design scheme based on a reliability design method, and calculating the average value of the profits of each simulated survey data to obtain the expected safety and economic profits of the survey drilling scheme;

(6) and (4) repeating the steps (3) to (5) for other alternative exploration drilling schemes, obtaining the expected benefits of all the alternatives, and determining the exploration drilling scheme with the highest expected net benefit as the optimal scheme by combining the exploration cost of each alternative.

The probability statistics information source in the step (1) comprises similar engineering soil data, similar engineering cases, engineering experience, geological exploration reports, expert consultation, literature data and the like in an existing exploration database. The random field model is to simulate the soil property of each point of the side slope soil into a plurality of random variables, so that the nonuniformity of the soil property on the spatial distribution can be described, and the uncertainty of the soil property in the absence of survey data can be reflected.

The correlation distance in the step (1) is a parameter of the random field model, and is used for describing the correlation of the soil properties of each point in the space, generally, if the distance between two points exceeds the correlation distance, the soil properties of the two points are considered to be uncorrelated, otherwise, the two points are considered to have a certain correlation statistically.

The random simulation sample for generating the random field in the step (1) refers to a sample for generating the soil property of each point in a random number sampling mode according to the probability model of the soil property of each point of the slope and the statistical correlation between each point.

The slope stability analysis model in the step (2) refers to an engineering mechanical model which gives the physical mechanical parameters of the slope soil body, analyzes whether the slope soil body is kept stable and does not slide and gives a safety coefficient. Commonly used methods include limit balance bar segmentation, finite element modeling, and the like. The invention is not limited in what specific method is used at this step.

The conditional probability distribution model of the survey data in the step (3) is a probability distribution model for describing possible values of the survey data under the condition of the actual value of the soil property. The variable number, variance, variable correlation and the like of the conditional probability distribution can reflect the characteristics of the investigation means, the test precision and the drilling arrangement of the alternative investigation scheme.

The purpose of the regression analysis model in step (4) is to obtain an approximate relationship between the survey data and the posterior probability of failure, and a logistic regression model is generally used. The failure probability refers to the probability of the instability of the slope described by the probability form when various factors in the slope engineering have certain uncertainty. The posterior failure probability refers to the failure probability after the understanding of the soil property is increased and the overall uncertainty is reduced after the simulated survey data is obtained. The posterior probability of failure is generally lower than without the survey data.

The reliability design method in the step (5) is characterized in that proper slope reinforcement measures are selected, so that the failure probability of the slope is smaller than a specified value, the reliability requirement is met, and the construction cost is the lowest. For each simulation survey data, a simulation design scheme can be calculated, and because the understanding of the soil property is increased after the simulation survey data are obtained, the new design scheme can generally improve the safety and the reliability and save the construction cost. The final evaluation averages the gains of these simulated designs (expectation), i.e., the expected gains of the survey.

The expected net gain in step (6) is the expected safety and economic gains calculated using the previous steps, minus the cost of the survey.

Drawings

The accompanying drawings, which are incorporated in and constitute a part of this application, illustrate an example of the application and, together with the description, serve to explain the application and not to limit the application.

FIG. 1 is a flow chart of an implementation of the method of the present invention;

FIG. 2 is a schematic view of an example slope;

FIG. 3 is a schematic diagram of an example slope survey borehole location selection.

Detailed Description

It should be noted that the following detailed description is exemplary and is intended to provide further explanation of the disclosure. Unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this application belongs.

It is noted that the terminology used herein is for the purpose of describing particular embodiments only and is not intended to be limiting of example embodiments according to the present application. As used herein, the singular forms "a", "an" and "the" are intended to include the plural forms as well, and it should be understood that when the terms "comprises" and/or "comprising" are used in this specification, they specify the presence of stated features, steps, operations, devices, components, and/or combinations thereof, unless the context clearly indicates otherwise.

The following describes a specific implementation of the method in a certain slope investigation case:

as shown in FIG. 2, the slope height of a clay slope is 10m, the slope ratio is 1:2, and the length of the section slope is 50 m. The design consideration parameter is the non-drainage shear strength of the soil body, the design target is to determine the slope cutting scheme of the slope, the position of the slope toe is required to be unchanged, and the slope top is required to retreat. The design target reliability is 3.0, i.e., the failure probability is required to be not higher than 0.13%. Planning to arrange a drill hole at the section requires optimization of the position of the drill hole. As shown in FIG. 3, 60 alternative positions are used as alternative positions of drilling holes at intervals of 1m from 19.5m behind the top of the slope to 19.5m in front of the toe of the slope.

(1) Probabilistic statistical information estimation of soil parameters

According to the relevant data of the slope soil, the soil parameters of the slope before exploration can be simulated into a random field represented by the following formula:

s_u(x,y)＝s_u0+bγz exp[w(x,y)] (1)

wherein s is_u0The non-drainage shear strength at the surface; b is the rate of increase of non-draining shear strength with depth; gamma is the soil mass gravity; z is depth; w (x, y) is a smooth Gaussian random field with a mean value of 0; (x, y) is the coordinates of a point. s_u0Obeying a lognormal distribution with a mean value of 14.669kPa and a standard deviation of 4.034 kPa; b obey a log normal distribution with a mean of 0.3 and a standard deviation of 0.09; gamma is a constant of 20kN/m³(ii) a w (x, y) follows a normal distribution with a mean of 0 and a standard deviation of 0.24. The random field has a horizontal direction correlation distance of 80m and a vertical direction correlation distance of 8 m. Based on the random field generation30,000 samples of undrained shear strength were obtained.

(2) Establishing a slope stability analysis model by using a finite difference method, introducing 30,000 simulation samples of a random field model into the slope stability analysis model, calculating a corresponding safety coefficient of each sample, and obtaining that the safety coefficients of 993 samples are less than 1 and the rest are greater than 1;

(3) according to the characteristics and relevant data of the drilling test, the error of the survey data is about 12.5%, and the simulation is carried out by using the log normal condition distribution which takes the real value of the non-drainage shear strength at the drilling position as a median and has the coefficient of variation of 12.5%. Taking a candidate borehole location, extracting simulated survey data from the conditional distribution for 30,000 simulated samples of each random field model;

(4) performing regression analysis on the safety factors generated in the steps (2) and (3) and the sample of the simulated survey data to obtain a regression model for predicting the posterior failure probability according to the survey data;

(5) and (5) calculating the posterior failure probability corresponding to the simulation survey data generated in each step (3) by using the regression model obtained in the step (4), and further obtaining an expected design scheme based on a reliability design method: according to the information in the step (1), when no survey data exists, the failure probability is 993/30000-3.31%, in order to meet the reliability requirement, the slope is cut to a slope ratio of 1:3.6, the top of the slope retreats by 16m, and the earthwork amount is 4000m³(ii) a Calculating the posterior failure probability of 0.22% by using a regression model on the first simulation survey data sample, wherein the slope is cut to a slope ratio of 1:2.4, the top of the slope is retreated by 4m and the earthwork amount is 1000m to meet the requirement of reliability through calculation³Then for the first simulated survey data sample, the yield is a saving of 3000m³The earthwork amount of (a); then, averaging the profits of the simulated survey data to obtain the expected profits of the survey drilling scheme;

(6) repeating the steps (3) to (5) for the remaining 59 candidate exploration drilling positions, obtaining the expected benefits of all the alternatives, and determining the exploration drilling scheme with the highest expected net benefit as the optimal scheme by combining the exploration cost of each alternative. Through the calculation and comparison, the method has the advantages that,drilling at a distance of 3.5m from the top of the slope on the slope is the optimal drilling scheme, and 3674.5m is expected to be saved³The amount of earthwork of (1).

Claims

1. A method for quickly optimizing a side slope exploration drilling arrangement scheme is characterized by comprising the following steps: the method comprises the following steps:

(1) estimating probability statistical information of soil body parameters, establishing a soil body parameter random field model, and generating a random simulation sample;