Multi-scale resilience assessment method, device, terminal and medium for urban underground space

Abstract

The present invention discloses a multi-scale resilience assessment method, device, terminal and medium for urban underground space. The method determines the index data of each node in the urban underground space network based on underground space information; determines the node resilience assessment result of each node based on the index data of each node, determines the failed node based on the node resilience assessment result; determines several node repair plans based on each failed node; calculates the comprehensive resilience assessment result of the urban underground space network when each node repair plan is adopted, and selects the node repair plan as the target node repair plan based on each comprehensive resilience assessment result. The present invention performs resilience assessment on nodes and urban underground space networks according to different indicators, and formulates and selects node repair plans based on the resilience assessment results. This solves the problem of how to perform resilience assessment on urban underground space networks after they are damaged, and formulate repair plans for nodes based on the resilience assessment results.

Description

Technical Field

[0001] The present invention relates to the field of urban resilience assessment, and in particular to a multi-scale resilience assessment method, device, terminal and medium for urban underground space. Background Art

[0002] The urban underground space network in a city is closely related to the lives of urban residents. The urban underground space network is a comprehensive three-dimensional spatial system, including subway networks, underground commercial streets, underground integrated pipeline corridors, etc. These facilities are planned and connected to form an interconnected and interactive organic whole.

[0003] Natural disasters or urban expansion and construction can damage nodes in the urban underground space network (such as subway stations and underground shopping malls), impacting the lives and safety of urban residents. Therefore, to provide a foundation for the normal operation of cities and the normal production and life of urban residents, it is necessary to accurately assess the resilience of urban underground space after damage to the urban underground space network. This allows for the development of targeted repair plans for nodes in the underground space network, mitigating the risks and inconveniences caused by disasters, urban expansion, and construction. Summary of the Invention

[0004] The technical problem to be solved by the present invention is to provide a multi-scale resilience assessment method, device, terminal and medium for urban underground space in response to the above-mentioned defects of the existing technology, aiming to solve the problem of how to conduct resilience assessment of the urban underground space network after the urban underground space network is damaged, so as to formulate repair plans for the nodes in the urban underground space network based on the resilience assessment.

[0005] The technical solutions adopted by the present invention to solve the problem are as follows:

[0006] In a first aspect, an embodiment of the present invention provides a multi-scale resilience assessment method for urban underground space, wherein the method comprises:

[0007] Obtaining underground space information corresponding to the urban underground space network, and determining indicator data corresponding to each indicator of each node in the urban underground space network based on the underground space information;

[0008] Determine the node resilience assessment result of each node based on the indicator data corresponding to each node;

[0009] Determining a number of failed nodes in the urban underground space network based on the resilience assessment results of each of the nodes;

[0010] Determine several node repair solutions based on each of the failed nodes;

[0011] The comprehensive resilience change curve of the urban underground space network when each of the node repair schemes is adopted is drawn respectively, and the node repair scheme is selected as the target node repair scheme according to each of the comprehensive resilience change curves.

[0012] In one implementation method, determining a node resilience assessment result of a node based on indicator data corresponding to the node includes:

[0013] Obtaining a damage critical value corresponding to the damage level of each indicator, and determining an overall perceived superiority of the indicator data relative to each damage critical value based on each damage critical value and the indicator data corresponding to the node;

[0014] The node resilience assessment result of the node is determined based on the overall perceived superiority of the indicator data relative to each of the damage thresholds.

[0015] In one implementation method, determining the overall perceived superiority of the indicator data relative to each of the damage thresholds based on each of the damage thresholds and the indicator data corresponding to the node includes:

[0016] Determine a benefit-loss value matrix corresponding to each indicator based on the damage critical value and indicator data corresponding to each indicator;

[0017] Obtaining the combined weights corresponding to the indicators, and determining the individual perceived superiority matrix based on the combined weights and the benefit-loss value matrices;

[0018] The overall perceived superiority of the indicator data relative to each of the damage thresholds is determined according to the individual perceived superiority matrix.

[0019] In one implementation method, determining a benefit-loss value matrix corresponding to each indicator based on the damage threshold and the indicator data respectively includes:

[0020] Determine an original data matrix according to the damage critical value corresponding to each indicator and the indicator data;

[0021] The difference between the data corresponding to the same indicator in the original data matrix is ​​calculated, and the profit and loss value matrix corresponding to the indicator is determined according to each of the differences.

[0022] In one implementation method, a method for obtaining the combined weight corresponding to each indicator includes:

[0023] Determine the subjective weight corresponding to each indicator based on the hierarchical analysis method;

[0024] Determine the objective weight corresponding to each indicator based on the entropy weight method;

[0025] Game theory is used to determine the combined weight corresponding to each indicator based on the subjective weight and the objective weight corresponding to each indicator.

[0026] In one implementation method, a comprehensive resilience change curve of the urban underground space network when each of the node repair solutions is adopted is drawn, including:

[0027] Calculate the comprehensive resilience assessment results of the urban underground space network corresponding to each repair stage when the node repair scheme is adopted;

[0028] The comprehensive toughness change curve is drawn according to the comprehensive toughness evaluation results corresponding to each repair stage.

[0029] In one implementation method, the method for calculating the comprehensive toughness evaluation result includes:

[0030] Calculate the average network efficiency, structural entropy and betweenness of the urban underground space network respectively;

[0031] The coefficient of variation method is used to determine the weights corresponding to the average network efficiency, the structural entropy and the betweenness respectively;

[0032] The comprehensive resilience evaluation result is determined according to the network average efficiency, the structural entropy, the betweenness and the weights.

[0033] In a second aspect, an embodiment of the present invention further provides a multi-scale resilience assessment device for an urban underground space, wherein the multi-scale resilience assessment device for an urban underground space comprises:

[0034] a data acquisition module, configured to acquire underground space information corresponding to the urban underground space network, and determine indicator data corresponding to each indicator of each node in the urban underground space network based on the underground space information;

[0035] A node resilience assessment module is used to determine the node resilience assessment result of each node based on the indicator data corresponding to each node;

[0036] A failure node determination module is used to determine a number of failure nodes in the urban underground space network based on the resilience assessment results of each node;

[0037] A repair solution building module, configured to determine a number of node repair solutions based on each of the failed nodes;

[0038] The repair scheme determination module is used to draw the comprehensive resilience change curve of the urban underground space network when each of the node repair schemes is adopted, and to select the node repair scheme as the target node repair scheme based on the comprehensive resilience evaluation results.

[0039] In a third aspect, an embodiment of the present invention further provides a terminal comprising a memory and one or more processors; the memory stores one or more programs; the programs contain instructions for executing any of the multi-scale resilience assessment methods for urban underground space as described above; and the processor is used to execute the programs.

[0040] In a fourth aspect, an embodiment of the present invention further provides a computer-readable storage medium on which a plurality of instructions are stored, wherein the instructions are suitable for being loaded and executed by a processor to implement any of the above-mentioned multi-scale resilience assessment methods for urban underground space.

[0041] Beneficial effects of the present invention: The embodiments of the present invention determine the index data of each node in the urban underground space network based on the underground space information; determine the node resilience assessment results of each node based on the index data of each node, determine the failed node based on the node resilience assessment results; determine several node repair plans based on each failed node; calculate the comprehensive resilience assessment results of the urban underground space network when each node repair plan is adopted, and select the node repair plan as the target node repair plan based on each comprehensive resilience assessment result. The present invention performs resilience assessments on nodes and urban underground space networks according to different indicators, and formulates and selects node repair plans based on the resilience assessment results. This solves the problem of how to perform resilience assessments on urban underground space networks after they are damaged, and formulate repair plans for nodes based on the resilience assessment results. BRIEF DESCRIPTION OF THE DRAWINGS

[0042] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the following briefly introduces the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings described below are only some embodiments recorded in the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0043] Figure 1 It is a flow chart of a multi-scale resilience assessment method for urban underground space provided by an embodiment of the present invention.

[0044] Figure 2 It is a flowchart of an implementation method of a multi-scale resilience assessment method for urban underground space provided by an embodiment of the present invention.

[0045] Figure 3 This is an example diagram of a composite performance curve provided by an embodiment of the present invention.

[0046] Figure 4 This is a diagram showing the relative positions of the foundation pit and the interval tunnel provided by an embodiment of the present invention.

[0047] Figure 5This is an evolution analysis diagram of multi-index compliance performance provided by an embodiment of the present invention.

[0048] Figure 6 It is a data matrix diagram provided by an embodiment of the present invention.

[0049] Figure 7 This is a diagram of betweenness calculation results provided by an embodiment of the present invention.

[0050] Figure 8 This is a diagram of performance calculation results provided by an embodiment of the present invention.

[0051] Figure 9 It is a comprehensive toughness change curve diagram of each node repair solution provided by an embodiment of the present invention.

[0052] Figure 10 It is a schematic diagram of the internal modules of the multi-scale resilience assessment device for urban underground space provided by an embodiment of the present invention.

[0053] Figure 11 This is a principle block diagram of a terminal provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0054] The present invention discloses a multi-scale resilience assessment method, device, terminal, and medium for urban underground space. To further clarify the objectives, technical solutions, and effects of the present invention, the present invention is further described below with reference to the accompanying drawings and examples. It should be understood that the specific examples described herein are intended only to illustrate the present invention and are not intended to limit the present invention.

[0055] It will be understood by those skilled in the art that, unless expressly stated otherwise, the singular forms "a", "an", "said" and "the" used herein may also include the plural forms. It should be further understood that the term "comprising" used in the description of the present invention refers to the presence of the features, integers, steps, operations, elements and / or components, but does not exclude the presence or addition of one or more other features, integers, steps, operations, elements, components and / or groups thereof. It should be understood that when we refer to an element as being "connected" or "coupled" to another element, it may be directly connected or coupled to the other element, or there may be intermediate elements. In addition, "connected" or "coupled" as used herein may include wireless connections or wireless couplings. The term "and / or" used herein includes all or any units and all combinations of one or more associated listed items.

[0056] It will be understood by those skilled in the art that, unless otherwise defined, all terms (including technical and scientific terms) used herein have the same meaning as commonly understood by those skilled in the art in the art to which the present invention belongs. It should also be understood that terms such as those defined in common dictionaries should be understood to have meanings consistent with their meanings in the context of the prior art and will not be interpreted in an idealized or overly formal sense unless specifically defined as herein.

[0057] In response to the above problems, the present invention provides a multi-scale resilience assessment method for urban underground space, which determines the index data of each node in the urban underground space network based on underground space information; determines the node resilience assessment result of each node based on the index data of each node, determines the failed node based on the node resilience assessment result; determines several node repair plans based on each failed node; calculates the comprehensive resilience assessment result of the urban underground space network when each node repair plan is adopted, and selects the node repair plan as the target node repair plan based on each comprehensive resilience assessment result. The present invention performs resilience assessment on nodes and urban underground space networks according to different indicators, and formulates and selects node repair plans based on the resilience assessment results. This solves the problem of how to perform resilience assessment on the urban underground space network after it is damaged, and formulates repair plans for nodes based on the resilience assessment results.

[0058] Exemplary methods:

[0059] like Figure 1 As shown, the method includes the following steps:

[0060] Step S100: Obtain underground space information corresponding to the urban underground space network, and determine indicator data corresponding to each indicator of each node in the urban underground space network based on the underground space information.

[0061] When a disaster strikes or urban construction is underway, assessing the resilience of nodes (edges) in the urban underground network and determining the node resilience assessment results requires obtaining underground space information corresponding to the urban underground network. This information allows for rapid and accurate acquisition of the metrics required for node resilience assessment. Underground space information includes information such as the type of disaster and the strength of existing structures. Disaster types include construction disturbances and earthquakes.

[0062] like Figure 2As shown, to accurately assess the resilience of each node in the underground space network, this embodiment conveniently selects indicators based on geometry (spatial distribution / layout), deformation, and internal forces to establish a resilience index system. The resilience index system includes several primary indicators, each of which includes several secondary indicators. For example, the resilience index system includes a primary indicator: the existing underground structure indicator, which includes secondary indicators: cover-span ratio, existing underground structure type, existing underground structure health, proximity, tunnel vertical displacement, tunnel horizontal displacement, and tunnel radial convergence.

[0063] Step S200: Determine the node resilience assessment result of each node based on the indicator data corresponding to each node.

[0064] Simply put, the node damage status is judged based on the quality of the indicator data corresponding to the node, and the node resilience assessment result is obtained based on the node damage status.

[0065] In one implementation, determining a node resilience assessment result of a node based on indicator data corresponding to the node includes:

[0066] Step S201: Obtain the damage critical value corresponding to the damage level of each indicator, and determine the overall perceived superiority of the indicator data relative to each damage critical value based on each damage critical value and the indicator data corresponding to the node, specifically including: Step S2011: Determine the benefit-loss value matrix corresponding to each indicator based on the damage critical value and the indicator data corresponding to each indicator; Step S2012: Obtain the combination weight corresponding to each indicator, and determine the individual perceived superiority matrix based on each combination weight and each benefit-loss value matrix; Step S2013: Determine the overall perceived superiority of the indicator data relative to each damage critical value based on the individual perceived superiority matrix.

[0067] In one implementation, step S2011, determining the profit-loss value matrix corresponding to each indicator based on the damage critical value and the indicator data corresponding to each indicator, includes: determining the original data matrix based on the damage critical value and the indicator data corresponding to each indicator; calculating the difference between the data corresponding to the same indicator in the original data matrix, and determining the profit-loss value matrix corresponding to the indicator based on each difference.

[0068] Specifically, according to the proposed toughness index system, the prediction results of each index can be divided into four states: no damage, low damage, medium damage and high damage. The superiority between the damage threshold value and each known damage level reaches When , it means no damage; similarly, Indicates low damage; if , it means medium damage; when When , it indicates high damage. The index data and the damage critical value of each known damage level are combined into the original data matrix. As shown in Table 1, For indicator data, are the damage critical values ​​of different damage levels corresponding to each indicator, For each indicator, for index Critical value or indicator data corresponding to the damage level.

[0069] Table 1 Original data table

[0070]

[0071] To facilitate subsequent calculations, this embodiment normalizes each element in the original data matrix to eliminate the influence of different dimensions on the calculation results.

[0072] ,

[0073] ,

[0074] in, for index The critical value or indicator data corresponding to the damage level, is the normalized data, It includes indicator data corresponding to positive indicators (i.e. profitability indicators) and indicator data corresponding to negative indicators (i.e. consumption indicators). Indicates the data after normalization of the indicator data corresponding to the positive indicator. Indicates the normalized data of the indicator data corresponding to the negative indicator.

[0075] According to the normalized original data matrix, each indicator Separate analysis was performed to compare the data between each injury level and calculate the index between levels. The profit and loss value constitutes the indicator The profit and loss value matrix ,Right now , m is the number of damage levels, =1, 2, 3, ..., n , n Indicates the total number of indicators. Damage level Relative to the damage level About indicators The value of the loss or gain. When ≤0, about the indicator ,grade Relative to level is lost; on the contrary, the level Relative to level It is profitable.

[0076] in, , , Indicator The corresponding The data of the damage level, that is, the first damage level in the normalized original data matrix Rank Elements of the column, Indicator The corresponding The data of the damage level, that is, the first damage level in the normalized original data matrix Rank Elements of a column.

[0077] .

[0078] In one implementation, step S2012, obtaining the combined weights corresponding to the indicators, and determining the individual perceived superiority matrix based on the combined weights and the benefit-loss value matrices, includes:

[0079] use Indicates the combined weights corresponding to the secondary indicators in the resilience index system, Used to indicate the resilience index system Secondary indicators, Indicates the weight corresponding to the first-level indicator in the resilience index system, A Indicates the A First-level indicators, get the corresponding combined weights of each indicator:

[0080] (1) Determine the subjective weight corresponding to each indicator based on the hierarchical analysis method ;

[0081] The AHP method uses expert judgment to determine the subjective weight of each evaluation indicator. According to expert experience, a larger weight indicates a greater impact on security resilience. Conversely, a smaller weight indicates a smaller impact.

[0082] (2) Determine the objective weight corresponding to each indicator based on the entropy weight method ;

[0083] The entropy weighting method can truly reflect the customer information involved in the issue, eliminating errors caused by human factors in the weight calculation process. Information entropy is used to measure the amount of useful information provided by the indicator. Therefore, the greater the information entropy, the greater the dispersion of the indicator within security resilience, and the corresponding entropy weight is smaller.

[0084] (3) Using game theory, the combined weight corresponding to each indicator is determined based on the subjective weight and the objective weight corresponding to each indicator.

[0085] Based on subjective weight and objective weight On the basis of the introduction of the idea of ​​game theory, the combination weight model of game theory is established to achieve the optimal goal of the combination weight . Any linear combination of weight vectors is as follows:

[0086] ,

[0087] in, and is the combination coefficient between each vector.

[0088] According to game theory, the optimal combination weight is obtained H It can be summarized as the optimal combination coefficient and After matrix operations and normalization, the results are as follows:

[0089] ,

[0090] .

[0091] After obtaining the combined weights corresponding to each indicator, the individual perceived superiority matrix is ​​determined based on the combined weights corresponding to each indicator and the benefit-loss value matrix. is determined as follows:

[0092] ,

[0093] Among them, the individual perception superiority matrix of all indicators is The calculation is as follows:

[0094] ,

[0095] ,

[0096] ,

[0097] in, represents the loss decay coefficient, , For indicators The corresponding combination weight; Damage level Relative to the damage level About indicators The value of the loss or gain, and is the positive individual perceived superiority and the negative individual perceived superiority, is the number of indicators of loss value, n is the total number of indicators.

[0098] In one implementation, step S2013, determining the overall perceived superiority of the indicator data relative to each of the damage thresholds according to the individual perceived superiority matrix, includes:

[0099] Determine the damage level based on the individual perception superiority matrix of the damage level Overall perceived superiority relative to all other impairment levels :

[0100] ,

[0101] m is the number of columns in the individual perceived superiority matrix.

[0102] In the original data matrix, the indicator values ​​are also expressed in terms of damage levels. Therefore, the damage level corresponding to the indicator data can be determined according to the individual perception superiority matrix Overall perceived superiority relative to each damage threshold.

[0103] Step S202: determining the node resilience assessment result of the node according to the overall perceived superiority of the indicator data relative to each of the damage thresholds.

[0104] Specifically, the damage level Overall perceived superiority relative to all other impairment levels Normalize to get ,according to The node damage status is judged according to the order of the overall perceived superiority of the indicator values ​​relative to the rest of the damage levels, and the node damage status is used as the node resilience assessment result of the node.

[0105] .

[0106] The overall perceived superiority is expressed as a percentage as the node's composite performance, and the node's damage status is judged based on the node's composite performance.

[0107] This embodiment evaluates the comprehensive toughness of the node from the perspective of maximum damage. Q It is divided into four levels: I. No damage; II. Low damage; III. Medium damage; IV. High damage. The no damage and low damage states are considered usable, while the medium damage and high damage states are considered failed. Table 2 shows the judgment intervals for each damage level.

[0108] Table 2 Judgment intervals for each damage level

[0109]

[0110] Step S300: Determine several failed nodes in the urban underground space network based on the resilience assessment results of each node.

[0111] Since the composite performance of nodes changes during disasters or construction, a composite performance curve is drawn based on the composite performance of each time node to reflect the changes in the node resilience assessment results, such as Figure 3 When the minimum value of the composite performance curve is in the medium damage or high damage range, that is, the node toughness assessment result of the time node corresponding to the minimum value is in the medium damage state or high damage state, the node is determined to be a failed node.

[0112] ,

[0113] in, Represents composite performance over time T The change function of is the minimum value of the composite performance curve.

[0114] Step S400: Determine several node repair solutions based on each of the failed nodes.

[0115] An urban underground space network may contain multiple failed nodes, each of which has a different impact on the resilience of the network. Therefore, different repair orders for each failed node will result in different recovery speeds for the network's resilience. This embodiment provides several node repair schemes based on the order in which each failed node is repaired.

[0116] Step S500: Draw the comprehensive resilience change curve of the urban underground space network when each of the node repair schemes is adopted, and select the node repair scheme as the target node repair scheme according to each of the comprehensive resilience change curves.

[0117] In order to select the optimal repair plan from various repair plans, thereby quickly restoring the resilience of the urban underground space network and reducing the impact of node failure on the lives and safety of urban residents, this embodiment draws the comprehensive resilience change curve of the urban underground space network when each node repair plan is adopted, and selects the optimal node repair plan from each node repair plan as the target node repair plan according to the change trend of each comprehensive resilience change curve.

[0118] In one implementation, a comprehensive resilience change curve of the urban underground space network when each node repair solution is adopted is drawn, including:

[0119] Step S501: Calculate the comprehensive resilience assessment results of the urban underground space network corresponding to each repair stage when the node repair solution is adopted;

[0120] Step S502: Draw the comprehensive toughness change curve according to the comprehensive toughness evaluation results corresponding to each repair stage.

[0121] The repair phase can be the time corresponding to the node repair plan or the project completion phase in the node repair plan. In this embodiment, the repair phase is related to the number of failed nodes repaired. When one failed node is repaired, the repair phase is the first phase. If two failed nodes are repaired, the repair phase is the second phase.

[0122] In one implementation, the method for calculating the comprehensive toughness evaluation result includes:

[0123] Step S5011, respectively calculating the network average efficiency, structural entropy and betweenness corresponding to the urban underground space network;

[0124] Step S5012: Determine the weights corresponding to the network average efficiency, the structural entropy, and the betweenness respectively using the coefficient of variation method;

[0125] Step S5013: Determine the comprehensive resilience evaluation result according to the network average efficiency, the structural entropy, the betweenness, and the weights.

[0126] This embodiment selects network average efficiency, structural entropy and betweenness as structural indicators of urban underground space network resilience.

[0127] Network average efficiency. Network average efficiency is a characteristic parameter that measures the connectivity level of urban underground space networks. It is defined as the average value of the sum of the reciprocals of all shortest paths in the urban underground space network. The calculation formula is:

[0128] ,

[0129] in, For nodes and nodes The distance between N is the total number of nodes.

[0130] (2) Structural entropy.

[0131] The more uneven the degree distribution of nodes in the urban underground space network is, the greater the structural entropy of the urban underground space network is. The calculation formula is:

[0132] ,

[0133] in, The degree of any node in the urban underground space network is exactly t probability.

[0134] The urban underground space network is moderate t The probability is:

[0135] ,

[0136] in, The urban underground space network is moderately t The number of nodes.

[0137] (3) Betweenness.

[0138] The calculation of betweenness is as follows:

[0139] ,

[0140] in, Representation node s and t The shortest paths through nodes The number of paths, Representation node s and t The number of all shortest paths between nodes i Betweenness for:

[0141] ,

[0142] The betweenness of the urban underground space network is obtained by taking the average betweenness of all nodes in the network.

[0143] After obtaining the average network efficiency, structural entropy, and betweenness for the urban underground space network, the coefficient of variation method is used to determine the corresponding weights for the average network efficiency, structural entropy, and betweenness. In this embodiment, the coefficient of variation obtained based on the average network efficiency and the upper-level betweenness is normalized and used as the weights for the average network efficiency, structural entropy, and betweenness.

[0144] The method for solving the weight of each indicator based on the coefficient of variation method is as follows:

[0145] Assume that there is m There are evaluation indicators, n evaluation objects, X is the original data matrix, where For the The object's The original data matrix is ​​as follows:

[0146] ,

[0147] Calculate the standard deviation of each indicator;

[0148] ,

[0149] in, Indicates the The standard deviation of the indicator, Indicates the The average value of the indicators.

[0150] Calculate the coefficient of variation of each indicator;

[0151] ,

[0152] The coefficient of variation of each indicator is normalized to obtain the weight of each indicator.

[0153] After obtaining the network average efficiency, structural entropy, and betweenness corresponding to the urban underground space network and the weights corresponding to the network average efficiency, structural entropy, and betweenness, the network average efficiency, structural entropy, and betweenness are weighted according to the weights and added together to obtain the structural resilience function of the urban underground space network (structural entropy and betweenness are negative indicators, so the weights are negative):

[0154] ,

[0155] in, is the network structure resilience function, and the network structure resilience function value is the comprehensive resilience evaluation result; The average network efficiency E , structural entropy H and betweennessB The weight of .

[0156] Example 1:

[0157] (1) Project overview.

[0158] A foundation pit project is planned for a certain project. The foundation is a pile foundation with a depth of 13.0m, side lengths of 195m and 175m, a width of 136m, a total perimeter of 680m, and an area of ​​27852m. 2 The construction pit is 25m~30m away from the left line of the Metro Line 1 section. The vertical relationship between the foundation pit and the section tunnel is as follows: Figure 4 shown.

[0159] Metro Line 1 runs east-west for 25.739 kilometers and has 24 stations, all of which are underground. The right tunnel section is 790.292 meters long, while the left tunnel section is 791.425 meters long, including a 1.133-meter long chain. The section was constructed using the shield method, while the connecting tunnels were constructed using the mining method. The section features one connecting tunnel and one pump station, both of which are built together. The tunnel section affected by the foundation pit is essentially straight, with a center-to-center spacing of approximately 15.5 meters.

[0160] Exploration revealed that the site, below a maximum exploration depth of 76.00 m, consists of artificial fill, Quaternary sediments, and early Yanshanian albitized biotite granite porphyry. Based on the differences in soil (rock) characteristics and their physical and mechanical properties, it can be divided into 11 engineering geological layers, further subdivided into 16 engineering geological sublayers.

[0161] Table 3 Parameters of soil physical and mechanical properties

[0162]

[0163] Resilience Index System. This embodiment proposes a resilience index system based on cross-matrix analysis, as shown in Table 4, which includes 7 indicators for existing underground structures.

[0164] Table 4 Resilience index system

[0165]

[0166] (3) The combined weights of indicators in the resilience index system.

[0167] The first step is to determine the subjective weights using the analytic hierarchy process (AHP) and construct the weight analysis matrix of the first and second level indicators, as shown in Table 5.

[0168] Table 5 Weight analysis matrix of secondary indicators of existing underground structures

[0169]

[0170] Construct a judgment matrix based on the importance of the evaluation indicators. The weights of other indicators except A1 to A4 are shown in Table 5, and the weights of secondary indicators are calculated, as shown in Table 6.

[0171] Table 6 Total weight table based on analytic hierarchy process

[0172]

[0173] In the second step, based on the resilience index system and grade description in Table 4, the objective weight Z of the secondary indicator is obtained, as shown in Table 7.

[0174] Table 7 Simplified objective weight table of secondary indicators

[0175]

[0176] The third step is to solve the combination coefficient and combination weights H .Combination weight H Expressed as The normalized result of the combination coefficient of the subjective vector and the objective vector is The vector values ​​of these weights are listed in Table 8.

[0177] Table 8 Summary of weights of primary and secondary indicators

[0178]

[0179] (4) Composite performance calculation.

[0180] In order to analyze the deformation of existing underground structures and the evolution of the composite performance of the underground space network under multiple indicators, this embodiment selected nine working conditions based on the construction process of a new tunnel, as shown in Table 9.

[0181] Table 9 Composite performance results under various working conditions

[0182]

[0183] Among them, T1 indicates the construction of the top beam of the wall and the first support; T2 indicates the excavation of the first layer of earth in the foundation pit to 2.43m; T3 indicates the excavation of the first layer of earth in the foundation pit to 5m; T4 indicates the construction of the waist beam and the second support; T5 indicates the excavation of the second layer of earth in the foundation pit to 7.91m; T6 indicates the excavation of the second layer of earth in the foundation pit to 9.45m; T7 indicates the construction of the waist beam and the third support; T8 indicates the excavation of the third layer of earth in the foundation pit to 11.92m; T9 indicates the excavation of the foundation pit to the bottom of the pit.

[0184] (5) Obtain the node resilience assessment results.

[0185] According to the data in Table 9, based on the combined weights of the indicators calculated in Table 8, the toughness assessment of the project is quantified to determine the node toughness assessment results of a foundation pit project. Figure 5 As shown, the horizontal axis is the time step (working condition), from T1 to T9 respectively represents the process of foundation pit excavation, and the vertical axis is the calculated composite performance.

[0186] The specific node resilience evaluation results R and classification are shown in Table 10:

[0187] Table 10 Node resilience evaluation results

[0188]

[0189] Example 2:

[0190] (1) Project overview.

[0191] The 2016 subway network map of a certain city includes 6 lines, namely Line 1, Line 2, Line 3, Line 4, Line 5 and Line 11, with 132 nodes and 142 sections.

[0192] (2) Select an indicator system and determine the indicator weights.

[0193] Select the indicator system: Network average efficiency, structural entropy and betweenness are selected as structural indicators of subway network resilience.

[0194] Determine indicator weights:

[0195] Process the raw data and convert the graph into a matrix. Connected nodes are assigned 1 and invalid nodes are assigned 0. Make a 132×132 matrix, such as Figure 6 As shown (because the table is too large, only part of it is shown);

[0196] Calculate the betweenness and effectiveness (closeness) of each node, such as Figure 7 、 Figure 8 As shown (because the table is too large, only part of it is shown).

[0197] The standard deviation of betweenness is:

[0198] ,

[0199] in, is the value in the original data matrix, Indicates the The average value of the indicators, the coefficient of variation of the betweenness is:

[0200] .

[0201] The standard deviation of the efficacy is:

[0202] ,

[0203] in, is the value in the original data matrix, Indicates the The average value of the indicators, the coefficient of variation of the average network efficiency is:

[0204] .

[0205] The degree of each node can be obtained from the subway line network diagram, and the structural entropy of the subway network can be calculated as follows:

[0206] , ,

[0207] , ,

[0208] ,

[0209] ,

[0210] The standard deviation of node degree is:

[0211] .

[0212] in, is the degree of each node, Represents the average value of the degree of each node, and the coefficient of variation of the structural entropy is:

[0213] .

[0214] Assume that the coefficient of variation of network average efficiency, structural entropy and betweenness are expressed as 、 、 , the coefficient of variation of network average efficiency, structural entropy and betweenness is normalized, and the weights of each indicator are obtained as follows:

[0215] , , .

[0216] From the above, we can see that the largest weight is the betweenness, which is 0.622765611, and the smallest weight is the network average efficiency, which is 0.147652583. The size of the weight reflects the size of the evaluation indicator's ability to distinguish between the evaluation objects.

[0217] From the calculation, we can get the network structure resilience function as follows:

[0218] .

[0219] (3) Assume that nodes 13, 11, and 110 fail.

[0220] Assume that nodes 13, 11, and 110 fail and observe the changes in the comprehensive toughness evaluation results.

[0221] When all nodes (edges) are working properly, the average network efficiency, structural entropy and betweenness are:

[0222] ,

[0223] ,

[0224] ,

[0225] Calculated:

[0226] .

[0227] Assume that after node 13, node 11, and node 110 fail, the average network efficiency, structural entropy, and betweenness are:

[0228] ,

[0229] ,

[0230] ,

[0231] Can be obtained:

[0232] .

[0233] Similarly, the average network efficiency, structural entropy, and betweenness of each site after restoration are calculated. The results are shown in Table 11.

[0234] Table 11 Calculation results

[0235]

[0236] (4) Draw the comprehensive toughness change curve, such as Figure 9 shown.

[0237] (5) Determine the target node repair plan based on the comprehensive toughness change curve. Figure 9 It can be seen that node 110-node 11-node 13 is the best node repair solution.

[0238] Based on the above embodiments, the present invention also provides a multi-scale toughness assessment device for urban underground space, such as Figure 10As shown, the device includes:

[0239] Data acquisition module 01 is used to obtain underground space information corresponding to the urban underground space network, and determine the indicator data corresponding to each indicator of each node in the urban underground space network based on the underground space information;

[0240] Node resilience assessment module 02, used to determine the node resilience assessment result of each node based on the indicator data corresponding to each node;

[0241] A failure node determination module 03 is used to determine a number of failure nodes in the urban underground space network according to the resilience assessment results of each node;

[0242] A repair solution building module 04 is used to determine several node repair solutions based on each of the failed nodes;

[0243] The repair scheme determination module 05 is used to draw the comprehensive resilience change curve of the urban underground space network when each of the node repair schemes is adopted, and select the node repair scheme as the target node repair scheme according to each of the comprehensive resilience change curves.

[0244] Based on the above embodiment, the present invention further provides a terminal, whose principle block diagram can be shown as follows: Figure 11 As shown. The terminal includes a processor, a memory, a network interface, and a display screen connected via a system bus. The processor of the terminal is used to provide computing and control capabilities. The memory of the terminal includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system and a computer program. The internal memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The network interface of the terminal is used to communicate with an external terminal via a network connection. When the computer program is executed by the processor, a multi-scale resilience assessment method for urban underground space is implemented. The display screen of the terminal can be a liquid crystal display or an electronic ink display.

[0245] Those skilled in the art will understand that Figure 11 The principle block diagram shown in the figure is only a block diagram of a partial structure related to the solution of the present invention, and does not constitute a limitation on the terminal to which the solution of the present invention is applied. The specific terminal may include more or fewer components than shown in the figure, or combine certain components, or have a different component arrangement.

[0246] In one implementation, the terminal stores one or more programs in its memory and is configured to be executed by one or more processors, wherein the one or more programs include instructions for performing a multi-scale resilience assessment method for urban underground space.

[0247] In summary, the present invention discloses a multi-scale resilience assessment method, device, terminal and medium for urban underground space. The method determines the index data of each node in the urban underground space network based on the underground space information; determines the node resilience assessment result of each node based on the index data of each node, determines the failed node based on the node resilience assessment result; determines several node repair schemes based on each failed node; calculates the comprehensive resilience assessment result of the urban underground space network when each node repair scheme is adopted, and selects the node repair scheme as the target node repair scheme based on each comprehensive resilience assessment result. The present invention performs resilience assessment on nodes and urban underground space networks according to different indicators, and formulates and selects node repair schemes based on the resilience assessment results. This solves the problem of how to perform resilience assessment on the urban underground space network after it is damaged, and formulates repair schemes for nodes based on the resilience assessment results.

[0248] It should be understood that the application of the present invention is not limited to the above examples. For those skilled in the art, improvements or changes can be made based on the above description. All these improvements and changes should fall within the scope of protection of the claims attached to the present invention.

Claims

1. A multi-scale resilience assessment method for urban underground space, characterized by: The method comprises: Obtaining underground space information corresponding to the urban underground space network, and determining indicator data corresponding to each indicator of each node in the urban underground space network based on the underground space information; Determine the node resilience assessment result of each node based on the indicator data corresponding to each node; Determining a number of failed nodes in the urban underground space network based on the resilience assessment results of each of the nodes; Determine several node repair solutions based on each of the failed nodes; Draw a comprehensive resilience change curve of the urban underground space network when each of the node repair schemes is adopted, and select the node repair scheme as the target node repair scheme based on each of the comprehensive resilience change curves; The indicators of each node in the urban underground space network include: cover-span ratio, type of existing underground structure, health status of existing underground structure, proximity, vertical displacement of tunnel, horizontal displacement of tunnel and radial convergence of tunnel; The node resilience assessment result of the node is determined based on the indicator data corresponding to the node, including: Obtaining a damage critical value corresponding to the damage level of each indicator, and determining an overall perceived superiority of the indicator data relative to each damage critical value based on each damage critical value and the indicator data corresponding to the node; Determining the node resilience assessment result of the node according to the overall perceived superiority of the indicator data relative to each of the damage thresholds; According to the resilience assessment results of each node, several failed nodes in the urban underground space network are determined, including: Based on the composite performance of each time node, a composite performance curve is drawn to reflect the changes in the node resilience assessment results; When the minimum value of the composite performance curve is in the medium damage interval or the high damage interval, the node is determined to be a failed node; The comprehensive resilience change curves of the urban underground space network when each node repair scheme is adopted are drawn separately, including: Calculate the comprehensive resilience assessment results of the urban underground space network corresponding to each repair stage when the node repair scheme is adopted; Draw the comprehensive toughness change curve according to the comprehensive toughness evaluation results corresponding to each repair stage; The calculation method of the comprehensive toughness evaluation result includes: Calculate the average network efficiency, structural entropy and betweenness of the urban underground space network respectively; The coefficient of variation method is used to determine the weights corresponding to the average network efficiency, the structural entropy and the betweenness respectively; The comprehensive resilience evaluation result is determined according to the network average efficiency, the structural entropy, the betweenness and the weights.

2. The multi-scale resilience assessment method for urban underground space according to claim 1 is characterized in that: Determining, based on each of the damage thresholds and the indicator data corresponding to the node, an overall perceived superiority of the indicator data relative to each of the damage thresholds, includes: Determine a benefit-loss value matrix corresponding to each indicator based on the damage critical value and indicator data corresponding to each indicator; Obtaining the combined weights corresponding to the indicators, and determining the individual perceived superiority matrix based on the combined weights and the benefit-loss value matrices; The overall perceived superiority of the indicator data relative to each of the damage thresholds is determined according to the individual perceived superiority matrix.

3. The multi-scale resilience assessment method for urban underground space according to claim 2 is characterized in that: Determining the benefit-loss value matrix corresponding to each indicator based on the damage critical value and the indicator data corresponding to each indicator, including: Determine an original data matrix according to the damage critical value corresponding to each indicator and the indicator data; The difference between the data corresponding to the same indicator in the original data matrix is ​​calculated, and the profit and loss value matrix corresponding to the indicator is determined according to each of the differences.

4. The multi-scale resilience assessment method for urban underground space according to claim 2, characterized in that: The method for obtaining the combined weight corresponding to each indicator includes: Determine the subjective weight corresponding to each indicator based on the hierarchical analysis method; Determine the objective weight corresponding to each indicator based on the entropy weight method; Game theory is used to determine the combined weight corresponding to each indicator based on the subjective weight and the objective weight corresponding to each indicator.

5. A multi-scale resilience assessment device for urban underground space, characterized in that: The device comprises: a data acquisition module, configured to acquire underground space information corresponding to the urban underground space network, and determine indicator data corresponding to each indicator of each node in the urban underground space network based on the underground space information; A node resilience assessment determination module is used to determine the node resilience assessment result of each node based on the indicator data corresponding to each node; A failure node determination module is used to determine a number of failure nodes in the urban underground space network based on the resilience assessment results of each node; A repair solution building module is used to determine a number of node repair solutions based on each of the failed nodes; A repair scheme determination module is used to draw the comprehensive resilience change curve of the urban underground space network when each node repair scheme is adopted, and select the node repair scheme as the target node repair scheme according to each comprehensive resilience change curve; The indicators of each node in the urban underground space network include: cover-span ratio, type of existing underground structure, health status of existing underground structure, proximity, vertical displacement of tunnel, horizontal displacement of tunnel and radial convergence of tunnel; The node resilience assessment result of the node is determined based on the indicator data corresponding to the node, including: Obtaining a damage critical value corresponding to the damage level of each indicator, and determining an overall perceived superiority of the indicator data relative to each damage critical value based on each damage critical value and the indicator data corresponding to the node; Determining the node resilience assessment result of the node according to the overall perceived superiority of the indicator data relative to each of the damage thresholds; According to the resilience assessment results of each node, several failed nodes in the urban underground space network are determined, including: Based on the composite performance of each time node, a composite performance curve is drawn to reflect the changes in the node resilience assessment results; When the minimum value of the composite performance curve is in the medium damage interval or the high damage interval, the node is determined to be a failed node; The comprehensive resilience change curves of the urban underground space network when each node repair scheme is adopted are drawn separately, including: Calculate the comprehensive resilience assessment results of the urban underground space network corresponding to each repair stage when the node repair scheme is adopted; Draw the comprehensive toughness change curve according to the comprehensive toughness evaluation results corresponding to each repair stage; The calculation method of the comprehensive toughness evaluation result includes: Calculate the average network efficiency, structural entropy and betweenness of the urban underground space network respectively; The coefficient of variation method is used to determine the weights corresponding to the average network efficiency, the structural entropy and the betweenness respectively; The comprehensive resilience evaluation result is determined according to the network average efficiency, the structural entropy, the betweenness and the weights.

6. A terminal, characterized in that: The terminal includes a memory and one or more processors; the memory stores one or more programs; the program contains instructions for executing the multi-scale resilience assessment method for urban underground space as described in any one of claims 1-4; and the processor is used to execute the program.

7. A computer-readable storage medium having a plurality of instructions stored thereon, characterized in that: The instructions are suitable for being loaded and executed by a processor to implement the steps of the multi-scale resilience assessment method for urban underground space described in any one of claims 1-4 above.

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