KR101926304B1 - Method of selecting representative boring investigation data in buildings region - Google Patents

Abstract

The present invention relates to a method to select representative boring investigation data in a building area, capable of reasonably selecting drilling investigation data representing a building area. According to the present invention, the method to select representative drilling investigation data in a building area comprises: a step (c-1) of setting an extension area including the building area with respect to a spatial central point of the building area; a step (c-2) of selecting a plurality of candidate extension area groups including the extension area and gradually increased; a step (c-3) of collecting drilling investigation data for the extension area and the candidate extension area groups; a step (c-4) of space-interpolating one geotechnical characteristic value for the extension area and the candidate extension area groups, and calculating a residual between estimated and measured characteristic values to determine an area, which is estimated as the least root mean square errors (RMSE), as a target building area in order to determine an area with the highest spatial correlation as the target building area among the extension area and the candidate extension area groups; a step (c-5) of removing an abnormal value in accordance with a boring date and altitude from the boring investigation data of the target building area; a step (c-6) of selecting statistical representative boring investigation sample data based on the geotechnical characteristic vessel from the boring investigation data from which the abnormal value is removed; and a step (c-7) of selecting the closest boring investigation data based on the spatial central point of the building area as the representative boring investigation data among the statistical representative boring investigation sample data.

Description

{METHOD OF SELECTING REPRESENTATIVE BORING INVESTIGATION DATA IN BUILDINGS REGION}

The present invention relates to a method of selecting representative drilling survey data for a building area, and more particularly, to a method of selecting a drilling survey data for a building area including a large-sized housing complex or an industrial facility that causes serious damage in case of an earthquake, This is a method of selecting representative drilling survey data for a building area that rationally selects drilling survey data that can represent the corresponding building area on site vulnerability side.

In order to ensure the efficiency and promptness of earthquake warning and earthquake disaster response in case of earthquake, the necessity of establishment of seismic acceleration meter in free field and structure area and construction of integrated observation network in connection with it are emerging.

In particular, by imposing an earthquake accelerometer on the national infrastructure, it is possible to quantitatively determine the level of earthquake excitation at the peak ground acceleration (PGA) level of each facility by installing seismic accelerometers of appropriate positions and sizes. And to evaluate the magnitude of earthquake damage.

The earthquake accelerometer installed in facilities (including buildings) is largely classified as free-space type (ground surface where there are no general facilities such as buildings or structures that can represent ground motion of facilities subject to seismic acceleration measurement), borehole type (drilling from ground surface to bedrock (Seismic accelerometer installed to measure seismic acceleration of bedrock), structure type (earthquake accelerometer installed in the lowest, uppermost, or middle layer to evaluate the effect of the seismic behavior of the structure).

In addition, rapid evaluation of the safety evaluation of seismic safety index based on the acceleration measurement results of free long observation station and structural observation station is being actively developed for single structure.

However, the installation of the earthquake accelerometer and the operation of the observation network are conducted for a single facility, and there are insufficient guidelines for selecting the location of an optimal seismic accelerometer installation for a large building area composed of a large number of kinds of facilities Do. In addition, it is necessary to select the measurement site considering the site effect in the facility area and to determine the optimal free - field condition (bedrock or rock outcrop) of the earthquake engineering.

In order to select the optimal location of the earthquake acceleration instrument, it is important to select the drilling survey data that can represent the area of the building in a reasonable manner.

SUMMARY OF THE INVENTION The present invention has been made in order to solve the above-mentioned problems and it is an object of the present invention to provide an earthquake-based measuring instrument capable of selecting a reasonable and efficient installation position of an earthquake acceleration meter for a building area including a large-scale housing complex or an industrial facility, This is to provide a method for selecting representative drilling survey data for a building area that rationally selects drilling survey data that can represent the corresponding building area on site vulnerability.

According to the present invention, the drilling survey data is collected for the extended area of the building area, and the representative drilling survey data centered on the building area is selected based on the time, A method of selecting representative drilling survey data, comprising the steps of: (c-1) setting an extension area including a building area based on a spatial center point of a building area; (c-2) setting a plurality of extended region candidate groups including the extended region and gradually increasing; (c-3) collecting survey data on the extension area and the plurality of extension area candidates, respectively; (c-4) One geotechnical property value for each of the extension area and the plurality of extension area candidates is determined as a spatial structure interpolation area to determine a region having a high spatial correlation among the extension area and the plurality of extension area candidates as a target building area. Determining a region in which a root mean square error (RMSE) is estimated to be the smallest as a target building area by calculating a residual between a predicted characteristic value and a measured characteristic value; (c-5) removing an abnormal value according to a drilling date and a drilling elevation among drilling survey data of the target building area; (c-6) selecting statistical representative drilling survey specimens based on geotechnical characteristics of drilling survey data from which anomalies have been removed; And (c-7) selecting, as a representative drilling survey data, a drilling survey data of the representative drilling survey sample data based on the spatial center point of the building area; And a control unit.

Preferably, in the step (c-3), at least seven or more extension candidate groups are set, and an interval between the extension candidate groups is a square root of the building area area.

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Preferably, the geotechnical property value is a layer thickness or a standard penetration test N value.

Preferably, the step (c-5) further comprises the steps of: (c-5-1) defining a material in which the drilling date is in the lower 10% of the drilling date of the target building area, ; And (c-5-2) comparing the land elevation errors based on the numerical elevation model among the drilling survey data of the target building area, and removing the data corresponding to the upper 10% with a large error, as an abnormal value; And a control unit.

Preferably, in the step (c-6), the geotechnical characteristic value is a thickness of the layer, and in the drilling data of the (c-6-1) Deriving a distribution function; (c-6-2) calculating a mean value, a median value, and a mode value for a sample group having a confidence interval of 95% or more on the probability distribution function of the thickness per layer; (c-6-3) calculating stratum thickness and intercomparison error measured for each drilling data based on the calculated mean, median, and mode indices; And (c-6-4) selecting the drilling survey data composed of the strata within the lower 10% of the probability distribution of the error according to the thickness determination index as the representative drilling survey data as a result of the calculation of the mutual comparison error; And a control unit.

Preferably, in the step (c-6), the geotechnical property value is set to the value of the standard penetration test N, and the average value of the standard penetration test N value in the drilling survey data in which the (a) Defining as a representative N value; (c-6-6) calculating a mean value, a median value, and a mode value for a sample group having a confidence interval of 95% or more on a probability distribution function of representative N values per layer; (c-6-7) calculating intercomparison errors according to representative N values for each drilling survey data on the basis of the calculated mean, median, and mode indices; (c-6-8) selecting drill survey data as representative drill survey data having a representative N value within the lower 10% of the probability distribution of the error according to the N value determination index as a result of the calculation of the mutual comparison error; And a control unit.

According to the present invention, in order to select an installation location of a rational and efficient seismic acceleration meter for a building area including a large-scale housing complex or an industrial facility that causes serious damage in the event of an earthquake, The results of this study are as follows.

BRIEF DESCRIPTION OF THE DRAWINGS FIG. 1 is a block diagram showing a positioning system in which a method for selecting an optimum installation position of an earthquake acceleration meter for a building area according to the present invention is driven.
2 is a flowchart for explaining a method of selecting an optimum installation position of an earthquake acceleration meter for a building area according to the present invention.
FIG. 3 is a view for explaining representative drilling survey data and determination of an installable area for an influence radius per single building for installation of an earthquake acceleration meter for a building area according to the present invention; FIG.
4 is a view for explaining a process of building a representative site space grid of a group of buildings through construction of an optimal site space grid according to the present invention.
FIG. 5 is a diagram for explaining a process of selecting and installing an optimal seismic acceleration measuring instrument in consideration of site response characteristic spatial information according to the present invention. FIG.
FIG. 6 is a diagram for explaining a process of selecting a target extension region candidate based on facilities and a cross validation based extension region according to the present invention; FIG.
FIG. 7 is a diagram for explaining the selection and optimization of an abnormal value of the drilling data based on the drilling date and the drilling height according to the present invention; FIG.
8 is a view for explaining a process of selecting representative drilling survey data based on average value, median value, and mode value according to the layer thickness according to the present invention and the N value of the standard penetration test.
9 is a view for explaining a process of drilling survey data considering a spatial center point of a facility area according to the present invention.
FIG. 10 is a view for explaining an integration process through standardization and spatial overlapping of a drilling column diagram and an earth-covered spatial layer according to the present invention; FIG.
11 is a diagram for explaining a process of determining an optimal lattice structure (lattice size) based on the result of cross-validation of a thickness target of a drilling survey data according to the present invention.
12 is a diagram for explaining a spatial grid transformation process of a geological map according to the present invention;
13 is a view for explaining a process of determining a representative area stratification of a facility area based on a site complex space grid according to the present invention.

While the invention is susceptible to various modifications and alternative forms, specific embodiments thereof are shown by way of example in the drawings and will herein be described in detail. It should be understood, however, that the invention is not intended to be limited to the particular embodiments, but includes all modifications, equivalents, and alternatives falling within the spirit and scope of the invention. Like reference numerals are used for like elements in describing each drawing.

The terms first, second, A, B, etc. may be used to describe various elements, but the elements should not be limited by the terms. The terms are used only for the purpose of distinguishing one component from another. For example, without departing from the scope of the present invention, the first component may be referred to as a second component, and similarly, the second component may also be referred to as a first component. And / or < / RTI > includes any combination of a plurality of related listed items or any of a plurality of related listed items.

It is to be understood that when an element is referred to as being "connected" or "connected" to another element, it may be directly connected or connected to the other element, . On the other hand, when an element is referred to as being "directly connected" or "directly connected" to another element, it should be understood that there are no other elements in between.

The terminology used in this application is used only to describe a specific embodiment and is not intended to limit the invention. The singular expressions include plural expressions unless the context clearly dictates otherwise. In the present application, the terms "comprises" or "having" and the like are used to specify that there is a feature, a number, a step, an operation, an element, a component or a combination thereof described in the specification, But do not preclude the presence or addition of one or more other features, integers, steps, operations, elements, components, or combinations thereof.

Unless defined otherwise, all terms used herein, including technical or scientific terms, have the same meaning as commonly understood by one of ordinary skill in the art to which this invention belongs. Terms such as those defined in commonly used dictionaries are to be interpreted as having a meaning consistent with the contextual meaning of the related art and are to be interpreted as either ideal or overly formal in the sense of the present application Do not.

Hereinafter, preferred embodiments according to the present invention will be described in detail with reference to the accompanying drawings.

FIG. 1 is a block diagram showing a location selection system 100 in which a method for selecting an optimal installation position of an earthquake acceleration meter for a building area according to the present invention is operated.

The location system 100 collects a plurality of drilling survey data and land cover data for the building area from the outside, analyzes the data, and determines an installation location of the optimum seismic acceleration measuring instrument considering site response characteristic spatial information.

The positioning system 100 includes an external interface unit 110, a data collection unit 130, a data density calculation unit 140, a first processing unit 150, a second processing unit 160, a positioning unit 171, A type determination unit 172, a place determination unit 173, a data management unit 180, and a control unit 120 capable of controlling the respective sub-configurations.

The location system 100 is a typical system component. The location system 100 is a web browser that retrieves a web page based on URL (Uniform Resource Locator), interprets it as HTML (Hyper-Text Markup Language) (OS) program for overall management and control of a browser program and a computer system.

The external interface unit 110 receives a plurality of drilling survey data and land cover data for the building area from the outside.

The data collection unit 130 collects a plurality of drilling survey data and land cover data for the building area received through the external interface unit 110 and stores the collected data in the data management unit 180 do.

The data density calculation unit 140 calculates the spatial density of the building area using the drilling data among the data collected through the data collection unit 130. The first processing unit 150 and the second processing unit 160, which will be described later, will be selectively driven through the calculated spatial density values.

The first processing unit 150 is driven when the spatial density calculated by the data density calculating unit 140 is equal to or greater than a reference value and collects the drilling data on the extended area of the building area, , Geomorphology, statistics, and spatial criteria to determine representative drilling survey data centered on the building area.

The second processing unit 160 is driven when the spatial density calculated by the data density calculating unit 140 is less than a reference value, interpolates the drilling data and the land cover data of the building area through kriging, We construct a layer, construct the integrated grid size through the verification of this spatial layer, and build a ground grid complex space grid with an integrated grid size to determine the representative stratification of the center of the building area.

The positioning unit 171 selects an installation position of the seismic acceleration measuring instrument based on the site period value selected through the representative drilling irradiation data of the first processing unit 150 or the representative layer stratification of the second processing unit 160 do.

The type determining unit 172 and the place determining unit 173 determine the installation type of the earthquake acceleration measuring instrument and the installation type of the earthquake acceleration measuring instrument based on the relation with the surrounding buildings based on the installation position of the earthquake acceleration measuring instrument selected by the positioning unit 171 And determine the location.

Referring now to FIG. 2, a method for selecting an optimal installation position of an earthquake acceleration meter for a building area according to the present invention will be described.

In the case of large-scale industrial facilities or residential complexes, the regional variability of the topography (geographical indication) and the constituent strata are severe in the small-scale region through the cut-off and embankment in the construction process, and thus the types and composition of the surface layer adjacent to the building are different.

Accordingly, we have established a priority setting method (guideline) for determining the location of a reasonable seismic acceleration measuring instrument for large-scale housing complexes and municipalities that cause serious damage in the event of an earthquake.

Especially, in the area of large scale buildings, it is necessary to select the optimal installation position of the earthquake acceleration instrument in consideration of the spatial heterogeneity of the site ground and the rapid localization of site response characteristics according to the topographical effect. Determine the ground information by selecting drilling survey data or by constructing an optimal site space grid.

In addition, since the facilities with different size, spatial shape, application, and structural engineering vulnerability are unevenly distributed in the large-scale building area, the ground information representing the target area is determined according to the three-dimensional spatial distribution characteristic of the structure, And the representative installation position of the free length and structure acceleration measuring instrument is determined.

Especially, the ground structure (base structure: shallow foundation, deep foundation) on the bottom of the building is different, and is generally located in the bedrock. Considering this fact, it is necessary to examine the suitability of three-dimensional structure accelerometer installation in 3D space for underground floor including building 1 story or underground parking lot.

A method for selecting an optimal installation position of an earthquake acceleration meter for a building area according to the present invention is as follows.

Due to the economic constraints of the installation and operation of the earthquake accelerometer, it is not possible to install and operate an earthquake accelerometer for every building in a large building area. Therefore, it is necessary to install one or two representative earthquake accelerometers .

In this paper, we propose a method of selecting a vulnerable area considering site response characteristics (site classification) such as bedrock depth and site period of a complex area, conservative evaluation of earthquake accelerometer Establish location selection method.

There are two methods to determine vulnerable site response area. Firstly, the method of determining the representative drilling data and the method of constructing the optimal site space grid are used to secure the ground columnarity of the vulnerable location first.

The representative ground information is the stratigraphic column, the Standard Penetration Test (SPT) N value columnarity information (also the shear wave velocity column information through the correlation between the N value and the shear wave velocity).

In this case, if a free-field earthquake accelerometer is installed in the area adjacent to the upper building, there is concern about the coherence or noise of the seismic wave. Therefore, the influence radius of the horizontal space (X, Y coordinate) And excluded when selecting drilling survey or spatial grid representative ground information.

Finally, the geomorphic type (land surface type, borehole type) is selected according to the surface or ground conditions through the determination of the topography, the stratum and the shear wave velocity columnar information of the representative ground information of the target large land area.

According to the present invention, the drilling data of the large building area is collected through the data collection unit 130 according to the process of selecting the optimal installation location of the earthquake accelerometer of FIG. 2, and the methodology for determining the optimal grounding degree It is selected based on the spatial density. Accordingly, when the drilling survey data of a number (> 100ea / km ²⁾ distribution selected optimum drilling survey sample data, and when the drilling survey data of a small number (<100ea / km ²⁾ distribution builds the optimal site space grid . Then, the representative site information at the center of the building area is determined, and the spatial response information (site period) spatial information is analyzed and the location of the optimal seismic accelerometer installed in the conservative viewpoint of the earthquake disaster . After that, the type of earthquake acceleration meter and the installation location are determined according to the installation location.

Next, a method for determining the optimal ground columnarity (drilling survey, site space grid) based on the drilling data space density based on the data density calculation unit 140 will be described.

In the area of buildings such as large residential areas, industrial facilities, space intensive drilling survey is essential for grasping the site characteristics and estimating the design ground factor in the architectural design and construction phase.

In particular, existing drilling survey data is also distributed in a large residential area site, which is developed for urban renewal and reconstruction.

Based on the collected data, we propose a decision method for selecting the optimal soil profile (drilling survey data, site space grid).

If the reference spatial density of the drilling data in the target area (for example, the number of drilling data per unit area is 100ea / km ² ) or more than a certain standard value (when many drilling data are used), the representative drilling data determination method , While if it is below the reference value (if a small number of drilling survey data is used), the representative site stratification information is extracted by selecting the site space grid construction method (see FIG. 2).

By applying the method of determining representative survey data and the method of constructing the site space grid, it is possible to determine the installation position of the optimum seismic acceleration measuring instrument for a large building area considering variability of various terrain and ground characteristics.

In other words, considering the quantitative number and spatial distribution characteristics of the drill survey data used to select the representative strata settlement information for evaluating the site response characteristics, the representative drill survey data and site space grid construction method described above are selectively applied .

Next, description will be made of representative ground space information grasping process through selection of representative representative drilling survey data of a large building area through the first processing unit 150. FIG.

Based on the topography and ground information, spatial modeling of site response characteristics using representative drilling data selection method considering three - dimensional spatial distribution of building group is performed to select the optimal seismic acceleration measuring instrument installation location of large - scale housing complex.

The drilling survey data to identify the engineering characteristics of the ground involved in the construction work in the area of the large-scale housing complex including the large-scale housing complex is conducted in a step-by-step sequence such as preliminary survey, main survey and supplementary survey. Collect.

First, in order to select the target expansion area and the drilling data in the area covering the big building area, the root mean square error (RMSE) based on the drilling survey data of the extension area candidates is sequentially calculated based on the cross- ) Verification.

By selecting the extension area with a relatively small error, the drilling survey data with high spatial correlation is defined as the target data for the representative ground information selection.

In addition, since the large-scale building area has a three-dimensional site condition in the three-dimensional space in the construction process of the embankment and the cutout, in order to consider the ground condition and the terrain condition of the present condition of the large-scale building area, Digital elevation model (DEM) and numerical map are collected through LiDAR survey, and extracted based on the selected extended area space range to obtain numerical geospatial and ground survey information. do.

In order to identify the site condition of the present condition, the drilling date of the drilling column is sorted in the latest order in order to select the drilling survey data at the time of completion of construction, and the lower 10% (relatively old drilling survey data) The data are defined as temporal outliers and excluded from drilling survey sample data.

In addition, to select the drilling survey data reflecting the present precise topographical characteristics, the top 10% of the sample group of the error between the surface elevation on the drilling column and the numerical elevation model of the corresponding location is defined as the topographic outliers, Excluded from the process.

Finally, the depth (unified classification based on stratification classification) thickness, depth of bedrock and standard penetration test N value are defined as geotechnical indicators in the property information of drill survey specimen data excluding temporal and geographical ideal values, Average value, median value, and mode value).

Based on this, the error between the three representative values is calculated for each geotechnical indicator and the top 10% of the probability distribution is defined as statistical outliers and excluded from the representative drill survey data selection process.

Optimization of drill survey sample data in the extension area selected for large-scale housing complex excluding temporal, topographical and statistical anomalies, and spatial modeling based on three-dimensional spatial coordinate system (X, Y, Z coordinate plane) Identify positional cross-correlations with groups.

For this purpose, the structure of large-scale housing complexes is collected and the three-dimensional spatial location of each building group and the ground information of the drilling survey data are used to identify the ground structure and bedrock location of the bottom floor of each building and the type of foundation structure .

First, as shown in FIG. 3, the influence range of the circle is selected based on the center point of the plane shape (X, Y coordinate plane) of a single building having various spatial shapes on the elevation view, and the drill survey sample data Clusters.

At the same time, the earthquake accelerometer installed in the free field should be installed far enough away from the facility so as not to be influenced by the interaction with the facility. If the free field observatory is not installed, Free field data can be used.

Therefore, in order to consider the center point of the planar shape and the planar non-uniformity for each single building, the influence range of the circle covering the whole area is set according to the central point of the building, Define the range of influence (eg, 3d ~ 5d for maximum 3 to 5 times) as the range of influence. At this time, the influence range must include the planar area of the building. This will determine drilling survey data within the maximum impact range.

In order to establish the range of the interaction of the facilities, several distances smaller than the influence range (for example, 1 to 1.5 times in the case of maximum 1 to 2 times) based on the longest distance (d) ) Is defined as an exclusion range. In this case, the exclusion range must include the planar area of the building.

Finally, to determine the installation location of the free-length acceleration measuring instrument adjacent to the single structure, the influence range excluding the excluded range is selected as an optimal free-length acceleration measuring instrument installable area (planar shape of the donut) As the representative drilling survey data.

The average value of the standard penetration test N value is used by calculating the layer thickness of the selected representative drilling survey data.

Next, description will be made of a representative ground space information grasping process of a group of buildings based on an optimal site space grid construction through the second processing unit 160.

To construct the site-specific spatial grid, we use the previously collected drill survey data and the numerical elevation model, and the representative representative drill survey data with temporal, geographical, and statistical anomalies removed.

In order to construct a spatial grid using ordinary kriging method to construct a spatial grid and to construct a space grid with a relatively high spatial correlation, a grid with various grid sizes is selected and a cross-validation-based prediction error (RMSE) Verify.

By using spatial interpolation of the geomorphic information (using the high-level information based on the digital elevation model), the layer thickness, and the average standard penetration test N of the layer, the grid size estimated with a small prediction error (high spatial correlation) We derive separate strata information.

In the same manner as the representative drilling data determination process for installing the building area acceleration meter described above, the influence range and the exclusion range of the single structure are set, and the site space grid information is extracted.

As shown in FIG. 4, a space-modeled spatial space grid of three-dimensional space is constructed for each building as shown in FIG. 4, and the layer type, thickness, and standard penetration test N value are stored for each cell of each grid.

Next, an optimal seismic acceleration measuring instrument installation location selection process considering the site response characteristic spatial information through the positioning unit 171 will be described.

Disasters caused by earthquakes are more prominent in areas of soft soil and thicker areas than in solid areas or rocky areas due to differences in site effects associated with amplification of ground motion. In general, the spatial distribution of disaster severity in metropolitan areas where earthquake damage has occurred is directly related to densities of residential and industrial dwellings, structural seismic vulnerability, and ground effect, which is fundamentally the seismic sensitivity of the ground. Since the site effect has spatial variability depending on the local geology and geotechnical characteristics of the region, evaluation of the site response through construction of geotechnical information space system is the most fundamental and important issue for the regional earthquake disaster.

The earthquake response characteristics of the ground such as shear stiffness, stratification, and sharing period are calculated through empirical correlation. In this process, the site effect is high (possibility of earthquake disaster is high) Conservative seismic measurements can be considered at the corresponding level. In this case, it is necessary to measure seismic acceleration according to the site effect in order to cope with the earthquake of a conservative viewpoint of a large building area, and it is possible to evaluate a preliminary level of earthquake motion and magnitude.

In order to consider site response characteristics (including site effects) for this purpose, site cycle is evaluated based on representative drill survey or site space grid, and seismic accelerometer installation location is selected centering on the area where the site cycle is maximum.

Based on the determined representative landform information, the N value of the standard penetration test is converted into the columnar information of the shear wave velocity of the stratum through the correlation equation (Equation 1) between the shear wave velocity and the N value proposed by the existing researchers.

Based on the drilled survey data or the site space grid, the spatial grid, the layer thickness (D), and the shear wave velocity (V _S ) of each layer to evaluate the site response characteristics, 2).

The site period is calculated based on the thickness of the bedrock upper layers of each site and the calculated shear wave velocity, which is the index of the earthquake engineering characteristics that indicates the resonance period of the site in case of an earthquake. Such a site period becomes larger as the depth of bedrock becomes deeper The ground motions near the site cycle can be largely amplified.

As shown in FIG. 5, when the representative drill survey data or the optimal site space grid is selected for each single building, in order to select a weak region based on the site response based on the calculated site period, the site maximum value (conservative earthquake disaster response perspective) It is necessary to determine the columnar level. For this purpose, we select the top 10% data from the representative drilling survey data or the spatial grid from the probability distribution.

In this case, in order to install one or two sets of earthquake accelerometers representing the building complex, it is necessary to determine an optimal position. For this purpose, the center point of the entire object area is considered as a place having spatial representativeity.

Thus, the center point of the atypical building complex area and the nearest drilling survey data or the site space grid are selected based on the selected optimum stratum columnarity (including site period results).

If two or more seismic accelerometers can be installed according to the importance of the target building complex or institutional level decision, the spatial center of each zone and the nearest stratum column are selected by dividing the target area into two or more zones And it is judged as a place representative of the ground motion of the target area.

Next, the type of earthquake acceleration meter and the process of determining the installation location according to site response characteristics through the type determination unit 172 and the site determination unit 173 will be described.

Determine the type of earthquake accelerometer and depth of installation based on the selected single (or two) seismic accelerometer installation location (site).

If there are two or more buildings in the same site nearest to the selected installation site, install the earthquake accelerometer on the highest building in the site or the building that has the greatest impact in case of damage.

Install a free length measuring instrument around the selected installation location. If the selected location is covered with road pavement, outdoor structure, etc., it is difficult to install a free length measuring instrument on the lowest floor of the nearest single building.

In addition, if the installation site selected as a site with weak site response characteristics has a bedrock depth of 20m or more, the seismic acceleration of the bedrock is measured using a borehole seismic accelerometer together with the surface free field measurement.

Now, the process of identifying the representative ground space information through the selection of representative representative drilling data of the above-mentioned large-scale building area will be described in more detail as follows.

Numerous geotechnical data have been accumulated throughout the country in accordance with the existing large-scale civil engineering and construction projects, and the geotechnical characteristics of the geotechnical survey data have been derived through various statistical analyzes Design constants are being calculated.

Recently, underground rehabilitation projects such as Daejindo underground tunnels have been actively planned and progressed along with large-scale redevelopment projects centered on urban areas and urban renewal. As a result, stratification, wetness, density, stiffness, Drilling survey is essential to understand overall geotechnical characteristics.

Therefore, it is necessary to acquire additional drilling data from existing drilling surveys, because the burden of economic and time - consuming burden is large in terms of overall construction.

Therefore, it is possible to secure additional samples of the input information population for determining reliable geotechnical characteristics by expanding the existing drilling survey data in the extended area covering the adjacent area.

The area of interest from the engineering point of view is small, ranging from a single residential building area to a large-scale building or facility area with a complex shape, a medium-sized residential or facility complex area, a large-scale facility or industrial production area, Do. Although it may vary depending on the user's demand or the purpose of the target, although the variability depending on the location of the underground ground condition may be large, in terms of practical efficiency, a representative single ground condition is required for the area of interest, or a limited number of ground conditions I have been making decisions and designing based on this. The derivation and selection of the representative ground condition can be applied not only for the purpose of designing or performance evaluation of the facility area, but also for the preliminary analysis for the land where the facility is not located. Especially, it can be used directly as a target ground condition for the design and performance evaluation of traditional geotechnical point of view as well as the representative ground condition of seismic engineering point of view and dynamic response analysis using it.

The drilling survey conducted for the purpose of confirming the process during the construction of the ground or before the construction is not suitable for grasping the completed topography and the ground condition of the completed construction through earthworks such as embankment, It is necessary to select drilling survey column.

The drilling survey data in the same area also has a wide variability of geotechnical characteristics depending on the geotechnical area specificity. In order to calculate a reasonable geotechnical design parameter, drilling survey data deviating from the statistical tendency is defined as an outlier, .

As a result, it is necessary to select a single drilling survey data (columnar map) that has statistical representativeness of the ground feature value among the sample drilling survey data.

It is possible to acquire drilling survey data as the civil works are carried out mainly on the roads, railways and large-scale building areas in collecting survey data of a certain wide area, and these data are mostly linear or non- And has a nonuniform spatial distribution of clustered shapes.

Therefore, it is necessary to select the representative drilling survey data by considering the spatial center point of the drilling data collection in the target area.

As shown in FIG. 2, in order to calculate the systematic ground design constants of the target structure site, the latest drilling survey data considering the current ground condition is selected, and then the sample drilling survey data having the representative value is selected. Finally, A method of selecting representative drilling survey data (column chart) of the target site was established.

Next, the process of selecting the target extension area and drilling survey data centered on facilities will be described in detail as follows.

In collecting the existing drilling survey data of the extended area covering the area of interest and the area of interest that may be the target facility area, the geotechnical characteristics of the site of the facility should be reflected in consideration of the spatial continuity of the ground and the ground The drilling survey data should be collected by setting the optimal adjacent area (extended area) for the area.

The shape of the region of interest can be an irregular polygon, which can be converted to a circle or an ellipse of equivalent area, and thus the expanded region can also be considered circular or elliptical. In addition, the area of interest and the extended area can be idealized in a rectangular shape in a more intuitive manner.

As shown in FIG. 6, an extension area having a circular radius of influence is defined based on the spatial center point of the facility area and the facility area is included for the drilling survey data collection.

In this case, to determine the optimum impact radius, the influence radius is gradually increased at a constant interval, and a plurality of extension area candidates are set, and the drill survey data is collected for each extension area. At least 7 regions are selected for the extension candidate group, and the interval between candidates is based on 0.1 times the square root of the target facility area (root value).

In order to determine the geotechnical characteristics with a certain tendency based on the drilling survey data in the target area, it is necessary to have a high spatial correlation in addition to the statistical correlation between drilling data in the same area. That is, they should have similar properties between spatially adjacent data.

In order to analyze the spatial correlation and sensitivity of drilling survey data for each extension area, the spatial correlation is evaluated by verifying the residuals for each extension area using the cross-validation technique among the geostatistical techniques.

Cross-validation computes the residual between the predicted and measured characteristic values by spatial interpolation of the geotechnical properties (layer thickness, standard penetration test N value) except for one of the drilling data. Sequentially obtain residuals for all drilling data.

In this case, root mean squared errors (RMSE) are calculated as an index for evaluating the correlation according to the results of cross validation for each extension region, and when the RMSE is evaluated to be the smallest, high spatial correlation is obtained.

We select the extension area with the smallest RMSE as the target facility area and select the drilling survey data in the area as the target drilling survey data.

Next, the drilling survey data selection process considering the current ground condition and topography condition will be described in detail as follows.

Based on the drilling survey data in the selected target extension area, representative drilling survey data centering on the spatial domain with statistical representation considering the present ground level and topography conditions are selected.

In order to select the drilling survey that reflects the current ground condition of the existing drilling survey data, the present time and the land surface height are compared based on the drilling date and the drilling height information on the drilling column, Are selected.

As the earthworks are frequently performed in excavation, embankment, etc. in the urban area, the terrain conditions such as the elevation of the ground state (natural state) and the slope before the construction have time-variability.

In addition, since the bedrock topsoil has a variation with time according to the construction of the ground improvement and the ground replacement, the drilling data population is sorted on the basis of the drilling date and the highland condition based on the drilling column chart as shown in FIG. 7, Exclude nonconforming data from sample selection.

When the drilling date of the target drilling survey data population is sorted in chronological order, the data corresponding to the lower 10% is defined as outliers and excluded from the drilling survey sample data.

Based on the Digital Elevation Model (DEM), which is based on the drilling elevation and the current precise topographic features (including the index), the optimized drill survey specimens are excluded from the 10% The index error of each point is compared with each other.

In the numerical elevation model, irregular terrain relief is constructed in the form of three - dimensional coordinates, and the drilling survey data is constructed as spatial data in the form of a two - dimensional columnar shape in three - dimensional coordinate space.

The numerical elevation model is composed of a certain grid and the error between the grid height and the elevation of the elevation of the numerical elevation model is compared with all the surveying points of the target area. Is defined as an outlier and excluded from the determination of representative ground survey data.

By setting the drilling date and the anomaly according to the drilling height, it is set as a sample group for the representative drilling survey data considering the condition of the completed construction site.

Next, the representative drilling data determination process considering the statistical tendency of geotechnical characteristics is described as follows.

The representative geotechnical characteristics based on the drilling column for the estimation of the design soil parameters include the N values of the soil types (sedimentation, sedimentation, weathering residue, weathered rock), thickness and standard penetration test (SPT).

Depending on the type of representative strata that are commonly defined in the drilling column, they include fill, deposited soils, weathered residual soils, weathered rocks, and soft rocks or more hard rocks And bedrock (bed rock). Even so, landfills, sediments, and weathering residues can be expressed or presented in detail by general field drilling procedures, indoor testing and analysis, Unified Soil Classification System (USCS), geological stratification, Bedrock can be classified according to rock type, color, crushing degree and so on. In addition, bedrock can be classified into soft rock, normal rock, light rock, and pole rock due to its hardness. These subdivided stratum configurations can be equally considered in terms of expanding the number of target strata in the applied technique by reflecting them into the subdivided conditions of the generalized five strata.

In general, the geologic formations of geologic formations are distributed in a specific order according to the depth of each stratum. The order of bedrock, weathered rock, weathering residue, sedimentation, and landfill is generally from the bottom. Weathered rocks and weathered residual soils are developed by the weathering of bedrock. In the case of sedimentary soils, sedimentation of external soil and sedimentation of landslides are formed by human civil engineering.

The formation and development processes of each of these strata have regional specificity and spatial variability even within the same area.

In addition, the presence or absence of specific strata or the thickness of each strata is a dominant factor in determining the ground stiffness, and is used as an important parameter of design parameter estimation and seismic design analysis by setting the standard construction cross section in earthworks such as dredging landfill .

Numerous drilling survey data in the target area A single drilling survey data with a representative stratigraphic columnar profile for the estimation of the design soil parameters representing the statistical tendency of the geotechnical characteristics, .

For this, as shown in FIG. 8, a probability distribution function according to each thickness is derived from four types of strata (bedding, sedimentation, weathering residue, weathering) on the bedrock.

Based on the probability distribution function of each layer thickness, the mean, median, and mode values for the sample with the confidence interval of 95% confidence level or higher are calculated and defined as an index for determining the representative section thickness.

Based on the thickness determination index of three types (mean, median, and mode) for each of the four types of strata, we compared the measured strata thickness with the target drilling data, Calculate the comparison error with the thickness determination index of the kind.

Therefore, drilling survey data consisting of strata within the lower 10% of each index on probability distribution of comparison error with three kinds of thickness determination indexes are selected. The drilling survey data within the lower 10% of the probability distribution of the errors is considered to represent the tendency to the thickness of the drilling survey data. In other words, the columnar chart of the determined drilling survey sample data is defined as a standard strata cross section.

As a result, some of the data of selected drill survey data set for each index can be duplicated because the drill survey data within the lower 10% that have representative thickness of each layer is selected based on three kinds of thickness determination indexes.

In addition, for the standard penetration test N values, the same procedures as for selecting the representative population with the thickness of the preceding layer are applied, but the test is applied at intervals of 1.0 m or 1.5 m in the depth direction on the basis of the standard penetration test procedure The representative N value for each floor should be determined in advance.

The standard penetration test is an intrusion test method to measure the N value to know the soil softness and relative density, and it is commonly used because it has many experience data and simple test.

The mean value of single or multiple standard penetration test N values measured by stratification is defined as the representative N value of the stratum.

The mean, median, and mode values for the sample population with a confidence interval of 95% or more on the probability distribution function of representative N values for each floor are calculated and the mutual comparison error is calculated according to the representative N value of each floor according to the drilling data.

As a result, the drill survey data having the representative N value within the lower 10% of the probability distribution of the error according to the three kinds of N value determination indexes are selected as representative drill survey sample data.

As a result, representative sampling data of three types of indicators based on the thickness of the layer and the N value of the standard penetration test are selected.

If additional parameters other than the thickness of the layer and the N value of the standard penetration test are taken into consideration, the drilling survey sample data is selected from the comparison error calculation based on the method of selecting the representative drilling data of the statistical index standard described above.

Next, a representative drilling survey data determination process considering the spatial center point of the target facility area will be described in detail with reference to FIG.

Based on representative sampling survey data considering statistical tendency of geotechnical engineering characteristics, representative survey data considering spatial center point are determined.

For the seismic design and seismic performance evaluation, which can involve dynamic analysis as well as the static design of the target facilities, typical geotechnical characteristics such as geological stratigraphy in the target area and N value of standard penetration test are used as input data , It is essential to select representative drill survey data for this purpose.

For this purpose, two-dimensional spatial distribution (based on X and Y coordinates) is implemented based on the drill survey specimen data with statistical representativeness, and the nearest drilling survey data with the spatial center of the target area or the target structure is selected based on this .

The nearest drilling survey data with the spatial center point are considered as the representative drilling survey which has the statistical representation of geotechnical characteristics and the ground condition and the condition of the present condition are taken into account in the drilling survey data in the target area. It should be used as an input ground condition.

Now, the representative ground space information grasping process of the building group based on the optimal site space grid construction will be described in more detail as follows.

In general, drilling survey is widely used in the case of ground survey for building construction purpose. The drilling survey provides reliable and detailed geotechnical information by identifying the sampled specimens, but it is difficult to grasp the stratified distribution of the entire site because it provides only limited geotechnical information.

Therefore, it is essential to construct a geostatistics optimal site space grid based on drilling survey data in order to grasp continuous site characteristics in 2D or 3D spatial coordinates.

In particular, to understand the site response characteristics of the facility area, various land cover data such as digital map, digital elevation model, geological map, land cover map, and satellite image are superimposed on the basis of the same spatial coordinate system And use it as integrated site information.

In the case of drilling survey data, it is expressed in the shape of a point shape on the 2-D spatial coordinates. In order to grasp the continuous site information of the entire object area, it is necessary to construct the ground information space layer based on the spatial interpolation technique.

Numerical modeling of a certain spatial grid size is required for the drilled surveyed data through spatial interpolation, and cross - validation - based precision error verification is performed to determine the optimal grid structure (unit grid size).

Based on the spatial grid based on the drilling survey data, the surface covered spatial layer is transformed and constructed into a spatial grid having the same grid size.

In the case of the surface-covered spatial layer, as in the numerical elevation model, it is composed of atmospheric polygons (polygons) such as spatial grid form, numerical map, and geological map of the cell unit. To grasp the quantitative distribution of the geotechnical characteristic values of the target area, Type spatial layer configuration is required.

Surface-covered spatial layers in the form of atypical polygons are transformed or projected into a grid-like spatial layer using geostatistical techniques.

Thus, a complex site space grid is constructed by spatial overlapping between three - dimensional spatial ground information space grid and ground cover space grid.

In the case of the geospatial grid, statistical representations (average, minimum, maximum) of geotechnical characteristics (layer thickness, standard penetration test N value, etc.) are determined for each grid of the facility area during the spatial interpolation process. Seismic design and seismic analysis In this paper, we propose a new method for selecting spatial grid based on engineering judgment.

Finally, it is possible to grasp the composite land cover information and the geotechnical property value information for each grid of a certain space grid, so that the optimal location of the earthquake acceleration instrument in the facility area and the quantitative spatial distribution characteristics of site response characteristics have.

Accordingly, as shown in FIG. 2, the land cover layer including the drilling survey is integrated, and the optimal grating structure is constructed by the geostatistical reliability verification technique. Then, based on the same grid structure, the drilling survey and each surface cover information are constructed as spatial grid information, and the representative stratification of the ground is determined according to the ground stiffness based on the standard penetration test N value.

Next, the integration process of the ground layer and the surface covering layer will be described in detail as follows.

A variety of land cover data such as drilling survey data, digital elevation model (DEM), geological map, land cover map, and satellite image sharing the same spatial coordinate system are collected in the target area.

Although drilling survey data provide clear and reliable geotechnical information, it is difficult to grasp the geotechnical characteristics of the whole site because it is performed at each point in the coordinate space. In order to overcome this, a spatial layer of ground information is constructed by performing spatial interpolation according to the layer thickness using kriging which is a geostatistical method.

는 가중치이며,

는 라그랑지(Lagrange) 계수이다.In Kriging, the weight of the existing data points for one point is calculated from the variance distribution of the existing data points, which is not the absolute magnitude of the variance for the existing data points at the point to be predicted, The relative variation of the variance between the points to be predicted and the maximum variance. Also, in kriging, existing data points do not have different individual distribution distributions, and existing data points in one region to be predicted have the same dispersion distribution. The variance distribution of existing data points within a domain can be represented as a function form, which is called a distributed function. In other words, each existing data point has its own variance function related to uncertainty (or reliability), and the variance function is used to determine the variance of the variance according to distance from the existing data point and to calculate the weight. In Kriging, this variance function is called a variogram. The variogram forms are empirically determined and are presented as linear, spherical, exponential, and Gaussian. Each variogram curve has a minimum value at a known point and increases with distance from a known point, and always has a maximum value after a certain distance. That is, the spots located a certain distance or more from the known point are not affected by the known points. The distance influenced by the known point is called the effective distance (α) or the influence range. There are several methods of kriging interpolation of unknown regions through the determined variogram modeling, and ordinary kriging is commonly used. Regular kriging is a method of estimating the corresponding value of a point by means of a variogram which determines the relation between the spatial position and the corresponding variable under the assumption that the mean of the population is unknown and constant beforehand. unbiased estimator. Normal kriging is applied to construct a spatial stratum distribution. The normal kriging is expressed by the following equations (3) and (4). here,

Is a weight,

Is the Lagrange coefficient.

The land cover data has various scales and ranges depending on the accuracy, and the accuracy of the collected data differs depending on the size of the target area.

For example, in the case of geology, large-scale to small-scale geological maps can be obtained in the order of 1: 50,000, 1: 250,000, and 1: 500,000 depending on the precision level, but 1:50,000 high-precision geology is not surveyed in some areas. It is composed of a polygonal (polygonal) geological boundary and a linear fault line structure.

In the numerical elevation model, the surface elevation information is stored in a grid of a certain size. The grid method, the contour method by continuously connecting the points with the same height, the profile method by the single layer, and the triangulated irregular network; irregular triangulation) method.

The land cover map is a map expressing the state of the ground surface using images taken by a satellite, and classifies physical conditions of the ground surface such as forest, grassland and concrete pavement into polygonal shape.

Obtain high-precision land cover data for the target area and extract and use continuous land cover data according to the area and shape of the target area.

In this case, since the surface elevation information of the drilling survey data does not reflect the drilling time and the present condition (since the completion of construction), the elevation information of the numerical elevation model or the numerical map is used instead of the surface covering data. In other words, the drilling data are standardized by superimposing the thickness information from the upper stratum to the depth direction of the drilling data, based on the surface cover based elevation information at the same point as the drilling survey data.

Finally, as shown in FIG. 10, the land cover data is integrated as a multi-spatial layer in the three-dimensional space in the form of a pillar-like drilling data in the depth direction from the ground surface and a superimposed form on the ground surface.

Next, the process of constructing the optimal grid structure of the site space grid will be described in detail as follows.

Based on the drill survey data, Kriging, which is the most widely used spatial interpolation method, is applied. As a result, a continuous two - dimensional spatial distribution of geotechnical characteristics based on drilling survey data is constructed.

The Kriging Estimation Equation of the Kriging Method is added to the condition that the Kriging Estimation Diagram is not biased, so that highly reliable spatial interpolation is possible and regular kriging is widely used in the field of geotechnical engineering.

It has a variance function related to the uncertainty of the existing drilling survey data. The variance function is used to determine the variation of the variance according to the distance from the existing data and to calculate the weights. In kriging, this variance function is defined as variogram.

The thickness information of representative layers (landfill, sedimentation, weathering residue, weathered rock) based on spatial coordinates (X, Y coordinates) among the various property information of the drilling survey data is calculated by applying regular kriging, Four identical spatial interpolation areas.

Four types of representative strata are universally used in the field of geotechnical engineering, and the geotechnical properties such as geotechnical stiffness and liquefaction disaster are determined according to the thickness of the strata. Even so, landfills, sediments, and weathering residues can be expressed or presented in detail by general field drilling procedures, indoor testing and analysis, Unified Soil Classification System (USCS), geological stratification, Bedrock can be classified according to rock type, color, crushing degree and so on. In addition, bedrock can be classified into soft rock, normal rock, light rock, and pole rock due to its hardness. These subdivided stratum configurations can be equally considered in terms of expanding the number of target strata in the applied technique by reflecting them into the subdivided conditions of the generalized five strata.

In this case, the spatial interpolation results are expressed as a numerical model of the lattice structure. In order to determine the optimal lattice size, error validation based on cross validation is performed for various lattice size candidates.

As shown in FIG. 11, the spatial interpolation prediction is performed by varying the grid size, and the cross-validation is performed to confirm the accuracy (or reliability) of the interpolation prediction result according to the specific grid size. The candidate size of the grid size is 7 or more, and cross validation is performed on the candidates according to the grid size of 5m, 10m, 20m, 30m, 50m, 70m, and 100m.

The cross validation method calculates the residual between the predicted characteristic value and the measured characteristic value by spatial interpolation of the geotechnical characteristic values (layer thickness, standard penetration test N value) except for one of the drilling survey data. Sequentially obtain residuals for all drilling data.

In this case, root mean squared errors (RMSE) are calculated as an index to evaluate the correlation according to the cross validation results based on the calculation conditions for each grid size. When the RMSE is evaluated to be the smallest, .

The RMSE determines the spatial interpolation condition using the smallest grid size (or lattice configuration) as the optimum grid size. As a result, the grid size with the same size and spatial coordinates in the certain target area is selected, And converts the spatial layer into a lattice structure having the same lattice size.

Also, based on the determined lattice structure, the layer thickness information is stored for each lattice to construct a ground space grid.

Next, the construction process of the site complex space grid will be described in detail as follows.

A polygonal or linear data, such as a numerical map, which stores landmark or slope information, is transformed into a triangulated irregular network (TIN), which is again a grid-like numerical elevation model And use it as an index high spatial grid.

In order to regenerate geologic spatial data, the spatial grid of the relative layer boundary is determined by superimposing the layer thickness grid information of the previously constructed ground grid on the basis of the surface high spatial grid.

In addition, the N values of the unit grid and the floor are stored through spatial interpolation based on the optimal grid structure determined for the standard penetration test N value.

As the test is applied at 1m or 1.5m intervals in the direction of depth with reference to the surface of the standard penetration test procedure, representative N value for each layer should be determined in advance.

The standard penetration test is an intrusion test method to measure the N value to know the soil softness and relative density, and it is commonly used because it has many experience data and simple test.

The mean value of single or multiple standard penetration test N values measured by stratification is defined as the representative N value of the stratum.

As a result, the floor space grid is determined according to the layer boundary, the standard penetration test N value.

In addition, the geological map and the land cover map are stored in a separate polygon or a linear spatial object, and the spatial layer is converted into a grid structure to grasp the quantitative spatial distribution of geological information, tomographic information or land cover information in a specific area.

As shown in FIG. 12, the transformation method is a method of projecting and transforming the surface-covered spatial layers (lipid, land cover, etc.) of the same area on the basis of the optimal grid structure of the site space grid determined above, Land cover information is stored.

For example, in the case of geology, a spatial grid lattice that is closed around a geological boundary polygon is stored as a geological boundary property (eg, sedimentary rocks). A linear spatial layer such as a fault line structure has a cross- And the nearest spatial grid as the fault line structure property.

In the case of land cover, the spatial grid enclosed within the land cover type polygon is stored as the land cover attribute in the same manner as the lipid boundary polygon of the geological map.

Finally, a site complex space grid is constructed that includes land surface elevation, depth of stratum boundary (or layer thickness), N value of standard penetration test by floor, surface surface lipid, fault line structure, and land cover information.

Next, a description will be made of a representative ground stratification determining process for space segment based site response spatial zoning, with reference to FIG.

In order to determine the representative ground stratification for seismic analysis and seismic design of the facility area or to select the optimal seismic accelerometer installation location, a representative value of the geotechnical property value based on the ground complex space grid constructed earlier is determined.

For this purpose, the grid of the space grid occupied by the target facility is extracted and the statistical representations of the mean, minimum, and maximum values of the stored layer thicknesses and the standard penetration test N values are calculated.

Generally, for conservative seismic analysis and design, the layer thickness is relatively thick and the N value of the standard penetration test is small, which leads to the increase of the site effect. Therefore, the maximum value of the layer thickness The thickness and N value of the layer determined by the above method are used as the stratum corneum.

However, according to the practical purpose, the representative thickness of the layer thickness and the N value of the standard penetration test are selected and used for analysis.

In addition, multi - surface covered space grid information also determines representative lipid and land cover information by calculating mode value to determine representative characteristic value according to facility area.

While the present invention has been particularly shown and described with reference to exemplary embodiments thereof, it will be understood by those skilled in the art that various changes and modifications may be made without departing from the scope of the invention. Accordingly, the true scope of the present invention should be determined by the technical idea of the appended claims.

Claims (7)

Selected drill survey data for the area of architecture that collects the drill survey data for the extended area of the building area and selects the representative drill survey data centered on the building area based on the time, terrain, statistics and spatial reference of the collected drill survey data As a method,
(c-1) setting an extension area including the building area based on a spatial center point of the building area;
(c-2) setting a plurality of extended region candidate groups including the extended region and gradually increasing;
(c-3) collecting survey data on the extension area and the plurality of extension area candidates, respectively;
(c-4) One geotechnical property value for each of the extension area and the plurality of extension area candidates is determined as a spatial structure interpolation area to determine a region having a high spatial correlation among the extension area and the plurality of extension area candidates as a target building area. Determining a region in which a root mean square error (RMSE) is estimated to be the smallest as a target building area by calculating a residual between a predicted characteristic value and a measured characteristic value;
(c-5) removing an abnormal value according to a drilling date and a drilling elevation among drilling survey data of the target building area;
(c-6) selecting statistical representative drilling survey specimens based on geotechnical characteristics of drilling survey data from which anomalies have been removed; And
(c-7) selecting, as a representative drilling survey data, the drilling survey data of the representative drilling survey sample data based on the spatial center point of the building area; And selecting a representative drilling survey data for a building area.
The method according to claim 1,
In the step (c-3)
Wherein at least seven expansion zone candidates are set and the interval between the extension zone candidates is the square root of the building area area.
delete The method according to claim 1,
Wherein the geotechnical property value is a thickness of a layer or a value of N of a standard penetration test.
The method according to claim 1,
The step (c-5)
(c-5-1) a step of sorting the drilling dates of the drilling survey data in the target building area by time series to define data corresponding to the lower 10% of the drilling dates as an outliers; And
(c-5-2) comparing the land elevation errors based on the numerical elevation model among the drilling survey data of the target building area, and removing the data corresponding to the upper 10%, which has a large error, as an abnormal value; And selecting a representative drilling survey data for a building area.
The method according to claim 1,
The step (c-6)
The geotechnical properties are defined as the thickness of the layer,
(c-6-1) deriving a probability distribution function for each thickness of bedrock strata in the drilling survey data from which anomalies are removed;
(c-6-2) calculating a mean value, a median value, and a mode value for a sample group having a confidence interval of 95% or more on the probability distribution function of the thickness per layer;
(c-6-3) calculating stratum thickness and intercomparison error measured for each drilling data based on the calculated mean, median, and mode indices; And
(c-6-4) Selecting drill survey data consisting of strata within the lower 10% of the probability distribution of the error according to the thickness determination index as representative drill survey data; And selecting a representative drilling survey data for a building area.
6. The method according to claim 1 or 5,
The step (c-6)
The value of the geotechnical properties is taken as the value of the standard penetration test N,
(c-6-5) Defining the mean value of the standard penetration test N value in the drilling survey data from which the anomalous value is removed as representative representative N value;
(c-6-6) calculating a mean value, a median value, and a mode value for a sample group having a confidence interval of 95% or more on a probability distribution function of representative N values per layer;
(c-6-7) calculating intercomparison errors according to representative N values for each drilling survey data on the basis of the calculated mean, median, and mode indices;
(c-6-8) selecting drill survey data as representative drill survey data having a representative N value within the lower 10% of the probability distribution of the error according to the N value determination index as a result of the calculation of the mutual comparison error; And selecting a representative drilling survey data for a building area.

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