Underground structure prediction system, underground structure prediction method, and computer program

Abstract

Even without an analysis engineer present, it is possible to predict displacements occurring in the ground and stresses acting on construction structures with high accuracy, thereby reducing delays in the construction process. [Solution] The system includes an analysis unit that uses physical properties and a geological model of the ground to analyze the displacement occurring in the ground and the stress acting on the construction work, predicting the displacement occurring in the ground and the stress acting on the construction work provided on the wall surface of the underground structure due to the construction of the underground structure; a ground displacement data acquisition unit that acquires ground displacement data measured from the wall surface; a stress measurement data acquisition unit that acquires stress measurement data by measuring the stress acting on the construction work; a drilling data acquisition unit that acquires drilling data representing drilling energy and drilling position obtained from the front of the tunnel face by drilling into the ground; and a data assimilation processing unit that updates the physical properties based on the displacement and stress predicted by the analysis unit, the ground displacement data and stress measurement data, and the drilling data.

Description

[Technical Field]

[0001] This invention relates to an underground structure prediction system, an underground structure prediction method, and a computer program. [Background technology]

[0002] In the construction of underground structures such as mountain tunnels and underground power plants, information-based construction is employed, which involves modifying the design based on data from face observations and measurement work during construction. In particular, when modifying the design of mountain tunnels, one of the following methods is applied: (1) standard design, (2) design under similar conditions, or (3) analytical methods. The standard design method in (1) involves applying support patterns, which have been prepared in advance for each type of ground condition, according to the ground grade. The design method using the similar conditions in (2) involves designing based on past experience in designing mountain tunnels. The analysis method described in (3) is used when standard design or design methods for similar conditions cannot be applied, and involves designing based on the displacements occurring in the ground and the stresses acting on the support structure using an analysis method.

[0003] Regarding analytical methods, a tunnel measurement system is known that allows for the efficient measurement of the displacement of the ground on the inner wall surface of a mountain tunnel from the time the tunnel face is excavated until the lining concrete is poured, by quickly and accurately sighting a target using a total station (see, for example, Patent Document 1). Furthermore, a strain measurement system is known that can be installed on steel support structures in tunnels, allowing strain measurement to begin immediately after the steel support structures are erected, and enabling real-time prediction of ground behavior (see, for example, Patent Document 2). [Prior art documents] [Patent Documents]

[0004] [Patent Document 1] Japanese Patent Publication No. 2017-129598 [Patent Document 2] Japanese Patent Publication No. 2022-177992 [Overview of the project] [Problems that the invention aims to solve]

[0005] However, applying the analysis methods described above presents the following problems. For example, there are no established methods for setting analysis conditions such as initial stress levels, boundary conditions, and rock mass properties. Currently, these conditions are set rationally based on the experience and knowledge of the analysis engineer. Furthermore, because the analysis involves modeling the complex ground conditions, support structures, linings, and their interactions, it may not always be possible to fully reproduce the actual behavior. Moreover, evaluating the results requires empirical knowledge, demanding a high level of technical interpretation. As described above, when modifying the design of a mountain tunnel using analytical methods, there is a problem in that analytical engineers have to spend time and effort setting the analytical conditions and evaluating the analytical results. Furthermore, since setting analysis conditions and evaluating the analysis results takes time, interrupting construction to revise the design and then resuming construction while considering the revised design results would result in a period of construction interruption, which could lead to delays in the construction schedule.

[0006] This invention has been made in view of these circumstances, and its purpose is to provide an underground structure prediction system, an underground structure prediction method, and a computer program that can predict displacements occurring in the ground and stresses acting on the walls of underground structures with high accuracy, even in the absence of an analysis engineer, thereby reducing delays in the construction process. [Means for solving the problem]

[0007] To solve the above-mentioned problems, one aspect of the present invention includes: a storage unit for storing physical property values ​​representing the physical properties of the ground; an analysis unit that uses the physical property values ​​stored in the storage unit and a geological model representing the geology of the ground to analyze the displacement occurring in the ground and the stress acting on the construction work by excavating the ground, predicting the displacement occurring in the ground and the stress acting on the construction work provided on the wall surface of the underground structure for the section to be analyzed; and a ground displacement data acquisition unit that acquires ground displacement data, which is the result of measuring the displacement of the ground by measuring the wall surface of the underground structure. The underground structure prediction system comprises: a stress measurement data acquisition unit that acquires stress measurement data, which is the result of measuring the stress acting on the structure; a drilling data acquisition unit that acquires drilling data representing drilling energy and drilling position obtained from the drilling direction ahead of the face by drilling the ground with the face of the excavator; and a data assimilation processing unit that updates the physical property values ​​stored in the storage unit based on the displacement and stress predicted by the analysis unit, the ground displacement data and stress measurement data obtained by measuring the section to be analyzed, and the drilling data obtained by drilling.

[0008] Furthermore, one aspect of the present invention involves an analysis step in which an analysis model is used to analyze the displacement occurring in the ground and the stress acting on the construction work provided on the wall surface of the underground structure, using physical property values ​​stored in a memory unit that stores physical property values ​​representing the physical properties of the ground and a geological model representing the geology of the ground, and predicts the displacement occurring in the ground and the stress acting on the construction work provided on the wall surface of the underground structure for the section to be analyzed; a ground displacement data acquisition step in which ground displacement data is obtained, which is the result of measuring the displacement of the ground by measuring the wall surface of the underground structure; and measurement of the stress acting on the construction work. The underground structure prediction method comprises: a stress measurement data acquisition step of acquiring stress measurement data as a result of the analysis; a drilling data acquisition step of acquiring drilling data representing drilling energy and drilling position obtained from the drilling direction forward of the drilling face by drilling the ground with the face equipped with the excavator; and a data assimilation processing step of updating the physical property values ​​stored in the storage unit based on the displacement and stress predicted in the analysis step, the ground displacement data and stress measurement data obtained by measuring the section to be analyzed, and the drilling data obtained by drilling.

[0009] In addition, one aspect of the present invention is a computer having storage means for storing physical property values representing the physical properties of the natural ground. Using the physical property values stored in the storage means and a geological model representing the geology of the natural ground, displacement generated in the natural ground and stress acting on the construction work are analyzed by an analysis model. Analysis means for predicting, for an analysis target section, the displacement generated in the natural ground and the stress acting on the construction work provided on the wall surface of the underground structure; ground displacement data acquisition means for acquiring ground displacement data which is a result of measuring the displacement of the natural ground by measuring the wall surface of the underground structure; stress measurement data acquisition means for acquiring stress measurement data which is a result of measuring the stress acting on the construction work; boring data acquisition means for acquiring boring data representing boring energy and a boring position obtained from the front side in the boring direction from a face provided in an excavator by boring the natural ground with the face; data assimilation processing means for updating the physical property values stored in the storage means based on the displacement and stress predicted by the analysis means, the ground displacement data and the stress measurement data obtained by measuring for the analysis target section, and the boring data obtained by the boring. It is a computer program for functioning as.

Effects of the Invention

[0010] According to the present invention, even if there is no analytical engineer, it is possible to accurately predict the displacement generated in the natural ground and the stress acting on the construction work on the wall surface of the underground structure, and it is possible to reduce the delay in the construction process.

Brief Description of the Drawings

[0011] [Figure 1] It is a schematic configuration diagram showing the configuration of an underground structure prediction system S according to an embodiment of the present invention. [Figure 2] It is a diagram showing the data flow of the underground structure prediction system S. [Figure 3] It is a schematic block diagram for explaining the functions of the analysis computer 20. [Figure 4] It is a flowchart for explaining the operation of the underground structure prediction system S. [Figure 5] This is a diagram for explaining the uniaxial compressive strength qu, deformation coefficient E, adhesion c, and internal friction angle φ calculated when boring into the natural ground at the face of the jumbo drill D. [Figure 6] This is a diagram showing an example of the probability distribution of the prediction results.

Embodiments for Carrying out the Invention

[0012] Hereinafter, a subsurface structure prediction system S according to an embodiment of the present invention will be described with reference to the drawings. The subsurface structure prediction system S in this embodiment is a system that, in response to the above-described problems, uses excavation analysis incorporating data assimilation processing to accurately identify the physical properties of the natural ground and predict the displacement generated in the natural ground due to excavation and construction and the stress acting on construction objects such as support works. Generally, a calculation model is not only constructed based on mathematical models such as idealized and simplified partial differential equations, initial and boundary conditions, and constitutive equations for actual phenomena, but also includes discretization errors and rounding errors, etc., so it is difficult to perfectly reproduce actual phenomena. In contrast, the subsurface structure prediction system S performs data assimilation, takes into account the errors of the calculation model, utilizes measurement data during the execution of the simulation to correct the calculation model, and enables improvement of the analysis and prediction performance. In addition, the subsurface structure prediction system S acquires the drilling energy and drilling position in the region on the front side (hereinafter also referred to as the front of the face) of the geological boundary on the front side (also referred to as the back side) of the excavation direction from the face of the jumbo drill D as drilling data, and by utilizing this acquired drilling data for data assimilation, at the time when the drilling energy is acquired, it improves the prediction performance of the displacement generated in the natural ground and the stress acting on the construction object when excavating the region. In this embodiment, a mountain tunnel is used as the target of construction as an underground structure, and the method for predicting the displacement that occurs in the ground and the stress acting on the construction structure (steel support structure SR and shotcrete SC) during construction is described. Here, the method for data assimilation is described using an ensemble Kalman filter, which is a sequential data assimilation method and an ensemble-based data assimilation method.

[0013] Figure 1 is a schematic diagram showing the configuration of an underground structure prediction system S according to one embodiment of the present invention. The underground structure prediction system S is used, for example, at a construction site where a mountain tunnel is being built. In mountain tunnels, where mountainous terrain is excavated, shotcrete (SC) and steel support structures (SR) are applied to the inner circumferential surfaces (walls) other than the roadbed (RB). Multiple steel support structures (SR) are installed at predetermined intervals relative to the excavation direction of the mountain tunnel.

[0014] Components and their roles The underground structure prediction system S includes a prism P, a total station TS, a strain gauge SG, a drill jumbo D, a concrete stress meter SM, a measurement computer 10, a data logger DL, a router RT, and an analysis computer 20.

[0015] <Measurement of ground displacement> Multiple prisms P are attached to the sprayed concrete SC. For example, the prisms P may be arranged along the circumferential direction of the inner circumference of the tunnel. The total station TS is placed on the roadbed RB during measurement and measures distance by shining light onto prisms P and receiving the light reflected from the prisms P. This distance measurement is performed for each prism P. The total station TS outputs the measurement data to the measurement computer 10. The measurement computer 10 measures the displacement of the ground based on measurement data acquired from the total station TS.

[0016] <Measurement of stress> The strain gauge SG is attached along the longitudinal direction of the steel support structure SR to measure the strain of the steel support structure SR. The concrete stress meter SM is installed, for example, between the ground and the sprayed concrete SC, or embedded within the sprayed concrete SC. After being installed in the ground, the concrete stress meter SM may be covered with sprayed concrete. The concrete stress meter SM measures the stress in the sprayed concrete SC. The data logger DL acquires and stores measurement data from the strain gauge SG, and acquires and stores measurement data from the concrete stress meter SM, and outputs these stored measurement data results to the measurement computer 10. The measurement computer 10 collects measurement data from the data logger DL, including the results measured by the strain gauge SG and the results measured by the concrete stress meter SM, and stores this measurement data. Furthermore, based on the measurement data from the strain gauge SG and the results measured by the concrete stress meter SM, the measurement computer 10 measures the stress acting on the steel support structure SR and the shotcrete SC during the construction of the mountain tunnel.

[0017] <Measurement of drilling energy> The Drill Jumbo D is an excavator that operates a drilling arm equipped with a face to drill and excavate the ground using the face. The Drill Jumbo D is equipped with a drilling information acquisition device that acquires information related to drilling, such as the impact energy of the face, the number of blows, the drilling speed, and the coordinate values ​​of the drilling position. When drilling into the ground with the face of the Drill Jumbo D, the drilling information acquisition device calculates the drilling energy based on the acquired drilling information, such as impact energy, number of impacts, and drilling speed, corresponding to the drilling position, and stores drilling data of the calculated drilling energy and the coordinate values ​​of the drilling position. For example, when performing drill logging with the Drill Jumbo D, the drilling information acquisition device acquires drilling information, calculates the drilling energy, and stores drilling data of the calculated drilling energy and the coordinate values ​​of the drilling position. This drilling information acquisition device may, for example, be mounted on the platform of the drill jumbo D, or it may be provided separately from the drill jumbo D so as to be able to communicate with the drill jumbo D.

[0018] <Data communication> The router RT receives data from the measurement computer 10 representing the displacement of the ground measured by the measurement computer 10, and data representing the stress acting on the steel support structure SR and shotcrete SC, and transmits this measurement data wirelessly to the analysis computer 20. In addition, the router RT receives drilling data, which consists of drilling energy and the coordinate values ​​of the drilling position, stored in the drilling information acquisition device, and transmits this drilling data wirelessly to the analysis computer 20.

[0019] <Data Analysis> The analysis computer 20 is installed, for example, in an office located near the construction site of a mountain tunnel. The analysis computer 20 has an excavation analysis program and a data assimilation program installed. By executing these installed programs, the analysis computer 20 performs excavation analysis processing, data assimilation processing using the prediction results obtained from the excavation analysis, measurement data, drilling data such as drilling energy and coordinate values ​​of the drilling location, and predictive analysis processing. The analysis computer 20 performs excavation analysis and predictive analysis by executing the excavation analysis program. In addition, the analysis computer 20 performs data assimilation by executing the data assimilation program. The drilling analysis program and the data assimilation program may be configured as a single executable program, or as separate executable programs. The analysis computer 20 has a display device connected to or built into it, and the results of various processes are displayed on this display device.

[0020] <Data flow of the underground structure prediction system S> Figure 2 shows the data flow of the underground structure prediction system S. The underground structure prediction system S comprises a measurement data collection unit 1, an analysis unit 2, and a prediction result display unit 3. The measurement data collection unit 1 includes various measuring instruments installed at the construction site of the mountain tunnel (prism P, total station TS, strain gauge SG, concrete stress meter SM, etc.), devices used to transfer measurement data and drilling data to the analysis computer 20 (data logger DL, router RT), and a drilling information acquisition device installed on the drill jumbo D. The analysis unit 2 performs drilling analysis assuming drilling, data assimilation processing using the prediction results obtained from the drilling analysis and the measurement data and drilling data acquired from the measurement data collection unit 1, and predictive analysis processing, and outputs the drilling analysis results and predictive analysis results to the predictive result display unit 3. The predictive result display unit 3 is, for example, a display device that displays various data. The analysis unit 2 and the predictive result display unit 3 are implemented by the analysis computer 20.

[0021] Computer for analysis Figure 3 is a schematic block diagram illustrating the functions of the analysis computer 20. The analysis computer 20 includes a communication unit 201, a storage unit 202, a ground displacement data acquisition unit 203, a stress measurement data acquisition unit 204, a drilling data acquisition unit 210, an analysis unit 205, a data assimilation processing unit 206, a control unit 207, and an output unit 208.

[0022] The communication unit 201 is connected to the router RT wirelessly and communicates with the router RT. The memory unit 202 stores various types of data. For example, the memory unit 202 stores various measurement data acquired from the measurement computer 10 and drilling data acquired from the router RT. The memory unit 202 also stores the physical property values ​​of a geological model that represents the physical properties of the ground where the mountain tunnel is to be constructed. The storage unit 202 is composed of a storage medium, such as an HDD (Hard Disk Drive), flash memory, EEPROM (Electrically Erasable Programmable Read Only Memory), RAM (Random Access Read / Write Memory), ROM (Read Only Memory), or any combination of these storage media. For example, non-volatile memory can be used as the storage unit 202.

[0023] The ground displacement data acquisition unit 203 acquires ground displacement data, which is the result of measuring the displacement of the ground on which the mountain tunnel is constructed by measuring the inner surface (wall surface) of the concrete sprayed on the inner surface of the tunnel, from the measurement computer 10 via the router RT and the communication unit 201. The stress measurement data acquisition unit 204 acquires stress measurement data, which is the result of measuring the stress acting on construction materials (e.g., shotcrete SC, steel support structures SR) installed along the inner circumference of the tunnel, from the measurement computer 10 via the router RT and the communication unit 201.

[0024] The drilling data acquisition unit 210 acquires drilling data obtained from the drill jumbo D as it excavates and drills into the ground, from the drilling information acquisition device via the router RT and the communication unit 201.

[0025] The analysis unit 205 uses physical properties and a geological model representing the geology of the ground to predict the displacement occurring in the ground and the stress acting on the construction structure during the construction of the mountain tunnel by excavating the ground, for the section under analysis, using an analytical model that analyzes the displacement occurring in the ground and the stress acting on the construction structure installed on the inner surface of the tunnel. The geological model is a three-dimensional geological model that represents the geological structure of the ground when excavating a mountain tunnel to be constructed. The geological model may be created using the results of a geological survey of the ground to be excavated for the mountain tunnel to be constructed. The three-dimensional geological model includes models representing multiple geological layers, and physical properties (various parameters) are assigned to elements corresponding to each layer. Examples of physical properties include the deformation coefficient E of the ground, Poisson's ratio ν, density ρ, cohesion c, and internal friction angle φ. Such physical properties are stored in the memory unit 202. The analytical model is a model that simulates the excavation of a mountain tunnel, and is used to calculate the displacement of nodes in the analytical model corresponding to the locations of measurement points where measurement data is obtained, as well as the stresses acting on the elements. For example, the analytical model is a model to which an analytical mesh is applied to a geological model, and physical property values ​​are assigned to each rock mass in the geological model.

[0026] The analysis unit 205 can perform analysis on sections that have already been constructed, but by performing analysis on sections to be excavated in the future, it predicts the displacement and stress in the analysis target section, which is the section to be predicted. When making a prediction, the analysis unit 205 uses the physical property values ​​updated by the data assimilation processing unit 206 (described later) and makes the prediction starting from the most recent construction section (for example, the second section described later). The analysis unit 205 obtains, as analysis results, a probability distribution of predicted displacement values ​​and a probability distribution of predicted stress values.

[0027] The data assimilation processing unit 206 updates the physical properties of the ground based on the displacement and stress predicted by the analysis unit 205 for the section under analysis, the ground displacement data and stress measurement data obtained by measuring the section under analysis, and the drilling data obtained by drilling (e.g., drill logging) into the ground at the face of the drill jumbo D. The updated physical properties are stored in the storage unit 202. Furthermore, the data assimilation processing unit 206 updates the physical properties of the ground stored in the storage unit 202 by performing data assimilation processing using a state vector generated based on the predicted results for the first section and the predicted results for the second section, and a measured value vector generated based on ground displacement data and stress measurement data obtained by measuring the first section, drilling data obtained by drilling the first section, ground displacement data and stress measurement data obtained by measuring the second section, and drilling data obtained by drilling the second section. Section 1 is the section constructed by performing the first excavation into the natural ground. Section 2 is the section constructed by performing the second excavation from Section 1. The explanation will describe the case where Section 1 and Section 2 are consecutive sections, but they do not necessarily have to be consecutive sections, and Section 1 and Section 2 may be separated, as long as it is possible to determine the probability distribution of the prediction results, which will be described later.

[0028] The control unit 207 controls each part of the analysis computer 20.

[0029] The output unit 208 outputs information that allows users to understand the relationship between the predicted displacement and stress for the analysis section and the displacement reference value and stress reference value. The output unit 208 displays on the display screen at least one of the following images: an image in which a figure representing the displacement reference value is added to a graph representing the predicted probability distribution of displacement, and an image in which a figure representing the stress reference value is added to a graph representing the predicted probability distribution of stress.

[0030] The communication unit 201, ground displacement data acquisition unit 203, stress measurement data acquisition unit 204, drilling data acquisition unit 210, analysis unit 205, data assimilation processing unit 206, control unit 207, and output unit 208 of the analysis computer 20 may be composed of a processing unit such as a CPU (Central Processing Unit) or a dedicated electronic circuit.

[0031] 《Implementation Procedure》 Figure 4 is a flowchart illustrating the operation of the underground structure prediction system S. Here, we will explain using the case where the Drill Jumbo D performs drilling and logging as an example. After the processing begins, the processing steps are divided into processing step S1 and processing step S2. Note that the start times of processing step S1 and processing step S2 do not necessarily have to be simultaneous.

[0032] (Processing step S1) The analysis unit 205 of the analysis computer 20 performs an excavation analysis assuming excavation steps n (where n is a positive integer) from construction step 0. One construction step is a single process in which excavation is carried out in one section from the portal of the mountain tunnel in the direction of extension of tunnel excavation, and shotcrete SC and steel support SR are installed. When using an ensemble Kalman filter as a data assimilation method, the analysis unit 205 of the analysis computer 20 considers the uncertainty of the parameters used in the excavation analysis and performs the excavation analysis using multiple predictive models (ensemble members) with varying parameters. The parameters referred to here are physical properties such as the deformation coefficient E, Poisson's ratio ν, density ρ, cohesion c, and internal friction angle φ of the ground. After processing step S1, the process proceeds to processing step S4.

[0033] (Processing step S2) For each section, the work involves excavating the natural ground for the mountain tunnel and constructing materials such as shotcrete (SC) and steel support structures (SR).

[0034] (Processing step S3) Next, the displacement of the ground and the stress acting on the construction structure are measured at construction steps n-1 and n. A measurement computer 10, a total station TS, and a prism P are used to measure the displacement of the ground. A measurement computer 10, a strain gauge SG, a concrete stress meter SM, and a data logger DL are used to measure the stress acting on the construction structure. The total station TS irradiates light onto the prism P installed in the sprayed concrete SC, measures the distance by receiving the light reflected from the prism P, and outputs the measurement data to the measurement computer 10. The measurement computer 10 measures the displacement of the ground based on the measurement data acquired from the total station TS. The strain gauge SG measures the strain of the steel support structure SR and outputs the measurement results to the data logger DL. The concrete stress meter SM measures the stress of the sprayed concrete SC and outputs the measurement results to the data logger DL. The measurement data for displacement and stress are stored in the measurement computer 10 and then transferred to the analysis computer 20 via the router RT. When drilling into the ground with the face of the drill jumbo D, the drilling information acquisition device calculates the drilling energy based on the impact energy, number of impacts, drilling speed, etc., corresponding to the drilling location, and stores drilling data of the calculated drilling energy and the coordinate values ​​of the drilling location. The drilling data stored in the drilling information acquisition device is transferred to the analysis computer 20 via the router RT. After processing step S3, the process proceeds to processing step S4.

[0035] (Processing step S4) A state vector is generated from the results of the excavation analysis for construction steps n-1 and n performed by the analysis unit 205 of the analysis computer 20. The communication unit 201 of the analysis computer 20 receives measurement data and drilling data from the router RT. The data assimilation processing unit 206 of the analysis computer 20 generates a measured value vector from the measurement data and drilling data of construction steps n-1 and n.

[0036] Now, let's explain state vectors in detail. There are as many state vectors as there are ensemble members, and each state vector contains the following information: (a) Physical properties of the ground assigned to ensemble members by random numbers (b) Increment in the displacement of the nodes in the analysis model corresponding to the location of the measurement point of the displacement that occurred from construction step n-1 to n. (c) Stress increment of the elements of the analysis model corresponding to the location of the measurement point of the stress of the construction that occurred from construction step n-1 to n (d) Uniaxial compressive strength q of the ground corresponding to the drilling location u Unaxial compressive strength q u [MPa] can be calculated, for example, by the following formula (1).

[0037]

number

[0038] (e) Uniaxial compressive strength q of the ground corresponding to the drilling location u The deformation modulus E, cohesion c, and internal friction angle φ of the ground were calculated from the above. The deformation modulus E [MPa], cohesion c [MPa], and internal friction angle φ [°] of these rock formations are calculated using the uniaxial compressive strength q calculated by the above formula (1). u Using [MPa], the calculation is performed, for example, by formulas (2) to (4) below.

[0039]

number

[0040]

number

[0041]

number

[0042] Fig. 5 is a diagram for explaining the uniaxial compressive strength q u , deformation coefficient E, adhesion c, and internal friction angle φ calculated when the face of the jumbo drill D drills into the natural ground. Fig. 5 schematically shows the state where the jumbo drill D performs hole inspection layers near the intersection of line SL and line CL and at the top end. PS indicates the hole drilling position. The right figure of Fig. 5 is a roughly enlarged view of the rectangular area A in the left figure of Fig. 5. As shown in the right figure, the uniaxial compressive strength q is obtained by acquiring the adhesion c and internal friction angle φ of the element EL corresponding to the hole drilling position and calculating the formula (1), and further, the deformation coefficient E, adhesion c, and internal friction angle φ of the natural ground are obtained by calculating the formulas (2) to (4). Then, the uniaxial compressive strength q of the natural ground corresponding to the hole drilling position u , the deformation coefficient E, adhesion c, and internal friction angle φ of the natural ground calculated from this uniaxial compressive strength q u are stored in the state vector. u

[0043] Next, the measured value vector will be specifically described. The measured value vector includes the increment of the displacement of the natural ground at the measurement points generated from construction step n - 1 to n, the increment of the stress of the structure, the average drilling energy S E of each element of the analysis model, the uniaxial compressive strength q u calculated from this, and the deformation coefficient E, adhesion c, and internal friction angle φ of the natural ground calculated from the uniaxial compressive strength q u . The drilling energy S E [J / cm 3 , MPa] used to obtain the uniaxial compressive strength q u can be, for example, the following formula (5).

[0044]

Equation

[0045] <00002The data assimilation processing unit 206 of the analysis computer 20 performs data assimilation using state vectors and measured value vectors, and updates the physical properties of the ground for each state vector. For example, it calculates the Kalman gain from the variance-covariance of the measured data and the variance-covariance calculated from the state vectors of the ensemble members, and updates the physical properties of the geological model that constitutes the state vectors of the ensemble members. The state vector stores the deformation coefficient E, cohesion c, and internal friction angle φ of the ground for each element EL corresponding to the drilling location, and this information is updated by data assimilation. That is, if drilling data is obtained for the region ahead (behind) the geological boundary in front of the drilling face, the deformation coefficient E, cohesion c, and internal friction angle φ of the ground in that region will be updated.

[0046] (Processing step Q1) The control unit 207 of the analysis computer 20 determines whether or not the construction of the mountain tunnel has been completed. If it determines that the construction has been completed (processing step Q1-YES), it terminates the process. If it determines that the construction has not been completed (processing step Q1-NO), it proceeds to processing step S5.

[0047] (Processing step S5) The analysis unit 205 of the analysis computer 20 adds the updated physical properties of the ground to the pre-excavation analysis model, performs excavation analysis from construction step 0 to n+1, and predicts the displacement of the ground and the stress acting on the construction structure that will occur when construction proceeds in the section at construction step n+1. For example, construction has been completed up to the section corresponding to construction step n (e.g., the second section), and construction step n+1 is the construction step in which new excavation of the ground is carried out starting from this section, and shotcrete SC and steel support SR are installed. The analysis unit 205 predicts the displacement of the ground and the stress acting on the construction structure that will occur when construction proceeds with the newly excavated section.

[0048] The state vector stores the deformation coefficient E, cohesion c, and internal friction angle φ of the ground for each element EL corresponding to the drilling location. Therefore, when the analysis unit 205 uses the deformation coefficient E, cohesion c, and internal friction angle φ of the updated ground for the drilling analysis, it assumes the ground is homogeneous, calculates the average of the deformation coefficient E, cohesion c, and internal friction angle φ of the updated ground, and assigns that value to all elements. Alternatively, when the analysis unit 205 uses the deformation modulus E, cohesion c, and internal friction angle φ of the updated ground for the excavation analysis, it may assume that the ground is heterogeneous and assign the deformation modulus E, cohesion c, and internal friction angle φ of the updated ground to the corresponding elements. Here, numerical analysis is performed while taking into account the uncertainty of the parameters, so a probability distribution is obtained as the prediction result. Figure 6 shows an example of the probability distribution of the prediction results. When the analysis unit 205 obtains the prediction results, the output unit 208 of the analysis computer 20 outputs the prediction results by displaying them on the display screen of the display device equipped with the analysis computer 20. The output unit 208 displays the probability distribution as the prediction result on the display screen, for example, as shown in Figure 6. The output unit 208 displays the probability distribution as a graph for each of the predicted values ​​of ground displacement, predicted stresses acting on the steel support structure SR, and predicted stresses acting on the shotcrete SC. More specifically, for the predicted ground displacement, the horizontal axis of the graph represents the distance excavated from the tunnel entrance, and the vertical axis represents the predicted displacement. The vertical axis also displays the displacement reference value (control reference value). The displacement reference value is a value that is pre-input by the analysis engineer in the construction of the mountain tunnel. The horizontal axis displays the probability distribution as a graph at a position on the graph that indicates the distance from the tunnel entrance according to the current position of the tunnel face. This figure shows that each value represented by the probability distribution is distributed within a range that does not exceed the displacement threshold. Furthermore, the minimum and maximum predicted values ​​of ground displacement for the section from the tunnel entrance to the tunnel face are output. Here, at the tunnel face, the probability distribution falls between the minimum and maximum predicted values ​​of ground displacement. In this way, the prediction results are displayed on the screen, making them easy to interpret. Even without an analysis technician present, the results can be interpreted using clues such as the displacement reference value, probability distribution, and minimum and maximum predicted values.

[0049] The predicted stress values ​​acting on the steel support structure (SR) are generally similar to those of the ground displacement, except that the vertical axis represents the predicted stress values. In this figure, the probability distribution of the predicted stress values ​​acting on the steel support structure (SR) exceeds the stress threshold value (control threshold value) set in advance by the analysis engineer. In this case, the person in charge who checks this display (analysis engineer, design engineer, etc.) can consider whether it is necessary to revise the design of the mountain tunnel.

[0050] The predicted stress values ​​acting on the shotcrete (SC) are generally similar to those of the ground displacement, except that the vertical axis represents the predicted stress values ​​acting on the shotcrete. In this figure, a portion of the probability distribution of the predicted stress values ​​acting on the shotcrete exceeds the stress threshold values ​​(control threshold values) set in advance by the analysis engineer. In this case, the person in charge who checks this information (analysis engineer, design engineer, etc.) can consider whether it is necessary to revise the design of the mountain tunnel.

[0051] Furthermore, since the predicted values ​​of ground displacement, the predicted values ​​of stress acting on the steel support structure (SR), and the predicted values ​​of stress acting on the shotcrete (SC) are displayed side by side on the screen, it is possible to consider the relationship between these three prediction results and examine whether there is a need to revise the design of the mountain tunnel.

[0052] (Processing step Q2) After processing step S5, the control unit 207 of the analysis computer 20 determines whether or not a review of the design or construction method is necessary based on the results of the predictive analysis. For example, the control unit 207 makes a determination based on whether the displacement of the ground or the stress of the structure indicated by the prediction results of any number of ensemble members exceeds the management standard value, or whether the average value of the prediction results of the ensemble members exceeds the management standard value. If the displacement of the ground or the stress of the structure indicated by the prediction results of the ensemble members exceeds the management standard value, or if the average value of the prediction results of the ensemble members exceeds the management standard value, the control unit 207 determines that a review of the design or construction method is necessary (processing step Q2-YES), and proceeds to processing step S6. On the other hand, if the displacement of the ground or the stress of the structure indicated by the prediction results of the ensemble members does not exceed the management standard value, or if the average value of the prediction results of the ensemble members does not exceed the management standard value, the control unit 207 determines that a review of the design or construction method is unnecessary (processing step Q2-NO), and proceeds to processing step S2.

[0053] (Processing step S6) The analysis unit 205 of the analysis computer 20 performs predictive analysis using the updated physical properties of the ground through data assimilation, to determine what happens when the support pattern and construction method are changed.

[0054] (Processing step S7) The analysis engineer makes changes to the design and construction methods based on the prediction results of the predictive analysis performed in processing step S6. For example, they consider and judge the changes based on whether the ground displacement indicated by the prediction results of any number of ensemble members exceeds the control standard value, whether the support stress indicated by the prediction results of any number of ensemble members exceeds the control standard value, whether the average value of the prediction results of the ensemble members exceeds the control standard value, and whether the design and construction methods are economical. After the design and construction methods have been reviewed by the analysis engineers, the control unit 207 moves the process to processing step S2. Then, construction is carried out according to the revised design and construction methods.

[0055] Subsequently, if the data assimilation processing unit 206 determines in processing step Q2 that no revision of the design or construction method is necessary (i.e., no revision is required), it uses the measured value vector created from the measured data obtained in processing step S3 and the state vector created from the analysis results obtained in processing step S5 for data assimilation in the following processing step S4. Furthermore, if the data assimilation processing unit 206 determines in processing step Q2 that a review of the design or construction method is necessary (if a review is made), it uses the measured value vector created from the measured data obtained in processing step S3 and the state vector created from the analysis results obtained in processing step S6 for data assimilation in the subsequent processing step S4.

[0056] <effect> In the construction of mountain tunnels, when performing excavation analysis using data assimilation, in order to accurately identify the physical properties of the ground beyond the geological boundary ahead of the tunnel face and to predict deformation behavior, the data assimilation processing unit 206 needed to assimilate the displacement amount of the measurement point obtained when the distance between the geological boundary and the tunnel face was approximately 3 [m] (Reference 1). <Reference 1> Yasuhisa Aono, Hideyuki Sakurai, Shinya Yamamoto, "Prediction Method for the Behavior of Underground Structures During Construction Using Data Assimilation," Proceedings of the Japan Society for Computational Engineering, Vol. 26, E-03-02, 2021. In mountain tunnel excavation, the tunnel face can advance 4 to 6 meters per day. If only the displacement of the ground is assimilated, the tunnel face may reach the ground beyond the geological boundary before the accuracy of identifying the physical properties of the ground beyond the boundary or predicting its deformation behavior can be improved. According to the embodiment described above, the drilling energy S of the region ahead (behind) the geological boundary in front of the tunnel face E By obtaining this drilling energy S E The uniaxial compressive strength q calculated from u , this uniaxial compressive strength q u By utilizing the deformation coefficient E, cohesion c, and internal friction angle φ of the ground calculated from the above data in data assimilation, the physical properties of the ground in that region are updated. Therefore, for example, at a point where the distance between the geological boundary ahead of the face and the face is approximately 3 [m] or more, the drilling energy SE If this is obtained, the ability to predict the displacement of the ground and the stress acting on the construction structure when that area is excavated can be significantly improved at that point in time. According to the embodiment described above, data such as ground displacement and construction stress measured on-site can be assimilated with data on ground displacement and construction stress predicted by sequential analysis under multiple different conditions, thereby updating and estimating the physical properties of the ground in the analysis model used in the sequential analysis. By performing numerical analysis while considering the uncertainty of the parameters, a probability distribution of the prediction results can be obtained, making it easier to interpret the prediction results and allowing the prediction results to be judged even when the analysis engineer is absent.

[0057] Furthermore, when numerical analysis is performed during the construction of mountain tunnels to modify the design or construction methods, the following problems arise: (a) the analysis engineers spend considerable time and effort setting analysis conditions and evaluating analysis results, and (b) the interruption of construction to modify the design or construction methods leads to delays in the construction process. The above-mentioned underground structure prediction system S provides the following benefits. Even without an analysis engineer, it is possible to estimate the analysis conditions (physical properties of the ground, initial stress, etc.) through data assimilation. Furthermore, since the analysis results yield a probability distribution, it is easier to evaluate the results even if an analysis technician is not available. Furthermore, by updating the analysis model using statistical mathematical methods, the predictive performance of ground behavior can be improved, the time and effort required to set analysis conditions can be reduced, and the evaluation of analysis results can be performed, thereby shortening the period during which construction is interrupted.

[0058] In the embodiments described above, the example of data assimilation was explained using both the displacement of the ground and the stress acting on the construction as measurement data, but either one of the measurement data may be used for data assimilation. Furthermore, in the embodiments described above, steel shoring (SR) and sprayed concrete (SC) were used as examples of construction works, but either steel shoring (SR) or sprayed concrete (SC) may be used as the construction work. Furthermore, although the above-described embodiment explained the case where the underground structure prediction system S is applied to the construction of mountain tunnels, it is not limited to mountain tunnels, and can be applied to any underground structure, such as the construction of large underground cavities like underground power plants.

[0059] Furthermore, while the above-described embodiment explains an example in which the displacement of the ground and the increment of stress acting on the construction object from construction step n-1 to n are used for data assimilation, the method is not limited to this. Increments from any construction step may be used for data assimilation, or cumulative displacement and stress since the start of measurement may be used for data assimilation.

[0060] In the above-described embodiment, the uniaxial compressive strength q is determined using the adhesive force c and the internal friction angle φ. u An example of calculating the uniaxial compressive strength q was shown, but for example, applying the formula described in Reference 2 below can be used. u You may also calculate this. <Reference 2> Keiki Goto, Kosuke Tanimura, Kosuke Kakimi, "Trial of ICT Excavation Management in Mountain Tunnels," Tunnel Engineering Reports, Vol. 33, I-21, 2023. Furthermore, in the above-described embodiment, the uniaxial compressive strength q of the ground corresponding to the drilling location is also present. u While examples have been shown using equations (2) to (4) to calculate the deformation coefficient E, cohesion c, and internal friction angle φ of the ground, one may also calculate the deformation coefficient E, cohesion c, and internal friction angle φ by applying the equations described in Reference 3 below. <Reference 3> Hiroyoshi Kikuchi, Introduction to Geotechnical Engineering, Civil Engineering Co., Ltd., p. 104, 1990

[0061] In the above-described embodiment, the drilling energy S obtained by drilling is E While we have shown an example of using this for data assimilation, for example, the drilling energy and the coordinates of the drilling location obtained during the installation of rock bolts or drilling for explosive charges may also be used for data assimilation.

[0062] The functions of the analysis computer 20 in the above-described embodiment may be realized by recording a program for realizing the functions of the analysis computer 20 on a computer-readable recording medium, loading the program recorded on this recording medium into a computer system, and executing it. Here, "computer system" includes hardware such as an OS and peripheral devices. Furthermore, "computer-readable recording medium" refers to portable media such as flexible disks, magneto-optical disks, ROMs, CD-ROMs, and storage devices such as hard disks built into a computer system. In addition, "computer-readable recording medium" may include those that dynamically hold programs for a short period of time, such as communication lines used when transmitting programs via networks such as the Internet or communication lines such as telephone lines, and those that hold programs for a certain period of time, such as volatile memory inside a computer system that acts as a server or client in such a case. Furthermore, the above-mentioned program may be for realizing only a part of the functions described above, or it may be a program that can realize the above-mentioned functions in combination with a program already recorded in the computer system, or it may be realized using a programmable logic device such as an FPGA (Field Programmable Gate Array).

[0063] Although embodiments of this invention have been described in detail above with reference to the drawings, the specific configuration is not limited to these embodiments and includes designs and the like that do not depart from the spirit of this invention. [Explanation of Symbols]

[0064] 1...Measurement data acquisition unit, 2...Analysis unit, 3...Prediction result display unit, 10...Measurement computer, 20...Analysis computer, 201...Communication unit, 202...Storage unit, 203...Ground displacement data acquisition unit, 204...Stress measurement data acquisition unit, 205...Analysis unit, 206...Data assimilation processing unit, 207...Control unit, 208...Output unit, 210...Drilling data acquisition unit, S...Underground structure prediction system

Claims

1. A memory unit that stores physical property values ​​representing the physical properties of the ground, An analysis unit predicts, for the section under analysis, the displacement generated in the ground and the stress acting on the construction work provided on the wall surface of the underground structure, using an analysis model that analyzes the displacement generated in the ground and the stress acting on the construction work provided on the wall surface of the underground structure, by using the physical properties values ​​stored in the memory unit and a geological model representing the geology of the ground, and by using an analysis model that analyzes the displacement generated in the ground and the stress acting on the construction work provided on the wall surface of the underground structure, by using the construction model that analyzes the displacement generated in the ground and the stress acting on the construction work provided on the wall surface of the underground structure, by using the physical properties values ​​stored in the memory unit and a geological model that represents the geology of the ground, A ground displacement data acquisition unit acquires ground displacement data, which is the result of measuring the displacement of the ground by measuring the wall surface of the underground structure. A stress measurement data acquisition unit acquires stress measurement data, which is the result of measuring the stress acting on the aforementioned construction object. A drilling data acquisition unit that acquires drilling data representing drilling energy and drilling position obtained from the drilling direction ahead of the drilling face by drilling the ground with the face of the drilling machine, A data assimilation processing unit updates the physical property values ​​stored in the storage unit based on the displacement and stress predicted by the analysis unit, the ground displacement data and stress measurement data obtained by measuring the analysis target section, and the drilling data obtained by drilling. An underground structure prediction system having the following features.

2. There is a first section constructed by performing a first excavation into the aforementioned ground, and a second section constructed by performing a second excavation from the first section. The aforementioned data assimilation unit is The physical properties are updated by performing data assimilation processing using a state vector generated based on the predicted results for the first section and the predicted results for the second section, and a measured value vector generated based on the ground displacement data and stress measurement data obtained by measuring the first section, the drilling data obtained by drilling the first section, the ground displacement data and stress measurement data obtained by measuring the second section, and the drilling data obtained by drilling the second section. The underground structure prediction system according to claim 1.

3. The aforementioned analysis unit, Using the updated material properties, the displacement and stress in the section to be analyzed, starting from the second section, are predicted. The underground structure prediction system is An output unit that outputs information that allows you to understand the relationship between the predicted displacement and stress for the analysis target section and the magnitude of the displacement reference value and stress reference value. The underground structure prediction system according to claim 2, having the following:

4. The aforementioned analysis unit, The probability distribution of the predicted displacement and the probability distribution of the predicted stress are obtained as analysis results. The underground structure prediction system according to claim 3.

5. The output unit is, The display screen will show at least one of the following: an image in which a figure representing the displacement reference value is added to a graph representing the predicted probability distribution of displacement, and an image in which a figure representing the stress reference value is added to a graph representing the predicted probability distribution of stress. The underground structure prediction system according to claim 4.

6. An analysis step in which, using the physical property values ​​stored in a memory unit that stores physical property values ​​representing the physical properties of the ground and a geological model representing the geology of the ground, an analysis model is used to analyze the displacement occurring in the ground and the stress acting on the construction work, thereby predicting the displacement occurring in the ground and the stress acting on the construction work provided on the wall surface of the underground structure, for the section to be analyzed, A ground displacement data acquisition step, which involves acquiring ground displacement data, which is the result of measuring the displacement of the ground by measuring the wall surface of the underground structure, A stress measurement data acquisition step, which involves acquiring stress measurement data, which is the result of measuring the stress acting on the aforementioned construction object, A drilling data acquisition step involves obtaining drilling data representing drilling energy and drilling position obtained from the drilling direction ahead of the drilling face by drilling the ground with the face of the drilling machine, A data assimilation processing step updates the physical property values ​​stored in the storage unit based on the displacement and stress predicted in the analysis step, the ground displacement data and stress measurement data obtained by measuring the section to be analyzed, and the drilling data obtained by drilling. A method for predicting underground structures.

7. A computer equipped with a storage means for storing physical property values ​​that represent the physical properties of the ground, An analytical means predicts, for the section under analysis, the displacement generated in the ground and the stress acting on the construction work provided on the wall surface of the underground structure, using the physical properties stored in the storage means and a geological model representing the geology of the ground, and an analytical model that analyzes the displacement generated in the ground and the stress acting on the construction work provided on the wall surface of the underground structure, by excavating the ground. Ground displacement data acquisition means for acquiring ground displacement data, which is the result of measuring the displacement of the ground by measuring the wall surface of the underground structure. A stress measurement data acquisition means for acquiring stress measurement data, which is the result of measuring the stress acting on the aforementioned construction object. Drilling data acquisition means that acquires drilling data representing drilling energy and drilling position obtained from the drilling direction ahead of the drilling face by drilling the ground with the face of the drilling machine, A data assimilation processing means updates the physical property values ​​stored in the storage means based on the displacement and stress predicted by the analysis means, the ground displacement data and stress measurement data obtained by measuring the analysis target section, and the drilling data obtained by drilling. A computer program designed to function as such.

Images