50 results about "Vulnerability curve" patented technology

The invention discloses a bridge network anti-seismic performance rapid evaluation method based on capability spectrum analysis. The method comprises the following steps: firstly, carrying out finite element modeling on bridges in a regional bridge network needing to be analyzed by using OpenSees, extracting piers, and carrying out vulnerability analysis on the piers; a bridge vulnerability curve is obtained based on a capacity spectrum method, then the failure probability of the bridge in a certain damage state serves as a post-earthquake damage index, and the bridge failure probability is replaced by the post-earthquake failure probability of the corresponding road section; after the post-earthquake failure probability of each road section exists, all paths between a starting point and an ending point, namely, to-be-researched OD pairs in a network area are analyzed, the passing probability of each path after the earthquake is calculated based on the Bayesian theorem and an event independence calculation method, all the paths under the OD pairs are sorted according to the passing probability, and therefore the optimal passing path is obtained; and the path with small passing probability is avoided. According to the invention, a scientific basis is provided for regional bridge network anti-seismic planning and emergency management.

The embodiment of the invention provides an infrastructure system security assessment method and device, electronic equipment and a storage medium, and the method comprises the steps: obtaining an infrastructure undirected graph which is generated by a logic connection relation between a plurality of infrastructures in an infrastructure system; generating a vulnerability curve corresponding to each node in the infrastructure undirected graph; based on the vulnerability curve of each node, the simulation fault probability of each node is obtained; node division constraints of the infrastructure system are obtained, a similarity matrix is generated based on the simulation fault probability of each node, clustering division is carried out on the infrastructure system based on the similarity matrix and the node division constraints, multiple division subsystems are obtained, and each division subsystem at most comprises one fragile node; and carrying out security assessment on each divided subsystem to obtain a security assessment result of the infrastructure system, thereby greatly improving the accuracy and foresight of the security assessment result of the key information infrastructure cascade.

The invention provides a main shock and aftershock sequence side slope vulnerability analysis method and system based on double response indexes, and relates to the technical field of earthquake side slope vulnerability analysis, and the method comprises the steps: building a GeoStudio side slope model according to the physical parameters of a side slope soil body, and obtaining the initial static safety coefficient and critical acceleration of the side slope; performing incremental dynamic time history analysis according to the main earthquake ground motion data, the slope model and the initial static safety coefficient of the slope to obtain a soil shear strength parameter value after the main earthquake; updating the initial critical acceleration of the side slope to obtain the critical acceleration of the side slope after the main earthquake; performing aftershock increment dynamic time history analysis according to the aftershock oscillation data and the critical acceleration of the side slope after the main shock to obtain a safety coefficient value and an accumulated displacement result of the soil body after the aftershock; and defining a vulnerability function based on the logarithmic normal cumulative distribution function to obtain a multi-level slope vulnerability curve. According to the method, the slope risk assessment precision and the visual decision-making capability are improved.

The invention discloses an anti-seismic toughness evaluation method for an underground station structure, and belongs to the technical field of anti-seismic evaluation, and the method comprises the steps: building a finite element model of interaction of a soil-underground station structure, and selecting a natural seismic action as an input working condition; analyzing the vulnerability of the underground station structure based on an incremental dynamic analysis method, and constructing a vulnerability curve of the underground station structure; introducing an economic loss correction coefficient lambda L and a repair time correction coefficient lambda t to respectively determine economic loss rates and repair times of different damage stages, and obtaining an economic loss rate-seismic oscillation intensity curve and a repair time-seismic oscillation intensity curve according to the vulnerability curve; and selecting a proper recovery function to construct a station structure function curve, and calculating the toughness loss of the station structure through integration. According to the method, nonlinear characteristics of a soil body and input site vibration and site randomness are considered, average damage parameters are calculated according to unit area weighting, quantitative analysis is carried out on the structural damage state, and inaccuracy caused by intuitive judgment is overcome.

The invention discloses a river valley area bridge earthquake vulnerability intelligent evaluation and earthquake resistance optimization analysis method, and relates to the technical field of bridge structure earthquake resistance analysis. The method comprises the following steps: constructing a geological model of an area where a bridge is located and a three-dimensional structure model of the bridge; a plurality of monitoring points are arranged in a bridge and a river valley area where the bridge is located, and collected data are uploaded to a cloud data center through a wireless transmission subsystem; carrying out seismic oscillation time history analysis based on the digital twinborn body, and visualizing the weak part of the structure through a cloud picture by adopting an artificial wave and actual measurement wave mixed input mode; and generating a multi-objective optimization scheme according to the vulnerability curve. According to the method, seismic oscillation time history analysis is carried out based on the digital twin, an artificial wave and actually measured wave mixed input mode is adopted, a weak part of a structure is visualized through a cloud picture, a multi-target optimization scheme is generated according to monitoring data, the seismic monitoring efficiency and supervision strength of a bridge in a river valley area are improved, and a bridge reinforcement method is rapidly provided.

The invention discloses a damage assessment method for a shallow-buried foundation bridge under a flood disaster. The method comprises the following steps: constructing a finite element model of the shallow-buried foundation bridge; introducing uncertainty of flood level height, foundation scouring pit length and scouring depth by applying a random Pushover method, obtaining bridge pier top yield displacement of the shallow foundation bridge under multiple groups of scouring working conditions, and calculating first two moments of logarithm of the flood-fighting capacity of the structure to obtain the flood-fighting capacity; performing flood-fighting demand analysis on the response of the shallow-buried foundation bridge in different flood washing environments based on a finite element reliability method; the flood-fighting capacity is compared with demand analysis, the failure probability of the shallow-buried foundation bridge under different working conditions is evaluated, fitting is conducted through the least square method, and a vulnerability curve of the shallow-buried foundation bridge is generated. According to the damage assessment method for the shallow-buried foundation bridge under the flood disaster, the influence of multiple factors such as the flow velocity and the scouring depth on the performance of the shallow-buried foundation bridge can be quantified, and the damage state of each stage of the shallow-buried foundation bridge is effectively assessed.

The invention provides a reinforced concrete member damage assessment method, system, equipment and medium, and belongs to the technical field of structural damage assessment, and the method comprises the steps: constructing a fire response feature knowledge base containing fire physical test data and simulation data of a reinforced concrete member, training the machine learning agent model by taking component design parameters and fire working condition parameters of the reinforced concrete component in the knowledge base as input parameters and taking post-fire component response data as output parameters to obtain a prediction model for predicting direct physical damage indexes of the post-fire reinforced concrete component; constructing a fire vulnerability curve representing the relationship between the failure probability and the fire intensity based on the prediction model; and receiving parameters of a to-be-evaluated component, and generating and outputting a damage evaluation result of the component based on the prediction model and the fire vulnerability curve. According to the invention, through data and model collaborative optimization, high-efficiency and accurate post-fire reinforced concrete member damage evaluation is realized.

The invention discloses a buried pipeline earthquake vulnerability analysis method based on three-parameter square normal distribution, belongs to the field of civil engineering and earthquake engineering, and solves the problem of failure probability calculation deviation caused by the fact that an existing logarithmic normal distribution model cannot accurately reflect skewness characteristics of structural response data. The method comprises the steps of generating seismic oscillation input data, establishing a buried pipeline finite element model, performing nonlinear time-history analysis, extracting pipeline response data, calculating buried pipeline failure probabilities based on three-parameter square normal distribution under different seismic oscillation intensities, and drawing a vulnerability curve. According to the method, a complete system covering seismic oscillation simulation, buried pipeline response analysis and seismic vulnerability analysis is constructed, and the calculation precision of the buried pipeline seismic failure probability is improved by introducing three-parameter square normal distribution capable of accurately reflecting the structure response data skewness characteristics; therefore, an earthquake vulnerability model which is wider in application range and higher in precision is provided.

The present invention discloses a method for assessing the vulnerability of a commutating branch tower to wind disasters that takes into account the variation of material parameters. When calculating the wind-induced response of a commutating branch tower, a sampling operation is used to consider the variation patterns of various structural material parameters, and an intelligent prediction model is used to learn the relationship between wind speed and the mean and standard deviation of structural demand indicators. Finally, the exceedance probability of the structure under a series of wind speed values ​​is predicted to form a comprehensive wind disaster vulnerability result that takes into account the variation of multiple structural material parameters. The method of the present invention provides a more accurate exceedance probability assessment based on the existing wind disaster vulnerability assessment of transmission towers, taking into account more uncertain risks. The present invention considers the uncertainty of multiple types of variation parameters through random sampling, reducing the amount of calculation. By using an intelligent prediction model, the quantitative relationship between wind speed and exceedance probability, as well as the relationship between wind speed and multiple types of material parameters and exceedance probability are obtained. Under a specified wind speed, the exceedance probability can be calculated more quickly through the intelligent prediction model, and vulnerability curves or surfaces under multiple wind speeds can be obtained, greatly improving the analysis efficiency.

This invention discloses an LSTM-driven dynamic prediction method and system for the operational resilience of integrated utility tunnels, relating to the field of deep learning. The method includes: acquiring vibration acceleration time histories, extracting peak acceleration and vibration energy accumulation time history curves, and generating a dynamic angle sequence; correcting the baseline vulnerability curve to obtain a dynamic damage probability curve, substituting the peak acceleration and vibration energy accumulation values ​​of the cross-section into the curve, and outputting a time-varying damage index sequence; identifying critical cross-sections with abrupt changes in the damage index, calculating the average damage index using the critical cross-section as a dividing point, and determining functional bottleneck sections; obtaining the average damage index and the redundancy of subsequent alternative paths, calculating the overall functional degradation rate of the utility tunnel, and obtaining the functional recovery multiple; calculating the initial recovery time, inputting it into a pre-trained dynamic time-series prediction model, and outputting the corrected final recovery time. This invention solves the problem of low prediction accuracy and high misjudgment rate in the prediction of the operational resilience of integrated utility tunnels due to the reliance on static experience for rough estimation in existing technologies.

The invention discloses a flood disaster vulnerability curve model construction method, which comprises the following steps of: selecting an optimal daily scale extreme precipitation threshold and an optimal continuous day number, and carrying out grid-by-grid calculation to obtain annual total extreme precipitation data corresponding to a precipitation parameter combination; carrying out statistics on the land coverage change data and the slope data by adopting a density calculation method to obtain a corresponding weight matrix; in combination with the weight matrix, rasterizing county-level annual total loss data obtained through statistics by county and year; and based on the rasterized county-level annual total loss data and annual total extreme rainfall data, dynamically constructing a flood disaster loss curve by adopting a deep learning multi-objective optimization four-parameter Logistic function. The technical problems that in the existing flood disaster loss curve construction process, the data size is insufficient, precision is low, and the method is limited to flood events or local cities and cannot be popularized to a large scale and a large range can be solved.

This invention relates to the field of disaster prevention and mitigation technology for marine engineering structures, and discloses a method for plotting vulnerability curves of guide seawall structures based on random load combinations. The method includes: constructing a nonlinear finite element model of a deep-water guide seawall; introducing a two-dimensional phase coupling vector to generate random dynamic load samples containing temporal coupling characteristics of earthquakes and waves; inputting the samples into the model, tracking the structural frequency drift in real time and considering pore flow abrupt change damping, and calculating the multidimensional dynamic response of the structure; constructing a multidimensional dynamic limit state surface that shrinks with cumulative plastic damage, and determining the failure state based on the relative relationship between the dynamic response and the state surface; estimating the failure probability using extreme value statistics theory, and establishing a probabilistic demand model containing cross-coupling terms of earthquake and wave intensity; and plotting a vulnerability surface describing the change of the failure probability with bivariate strength indices based on this model. This invention can accurately assess the dynamic reliability of deep-water guide seawalls under the coupling effects of multiple disasters.

This invention discloses a method for obtaining the wind-induced vulnerability curve of transmission towers based on failure probability, relating to structural engineering technology. The method includes the following steps: establishing a probability distribution model of the extreme response of the transmission tower to wind load; constructing a probability distribution model of the structural bearing capacity of the transmission tower; obtaining the failure probability based on vulnerability analysis using Latin hypercube sampling; plotting vulnerability curves with wind speed as the horizontal axis and failure probability as the vertical axis, drawing curves under different failure criteria to obtain vulnerability curves based on failure probability; performing vulnerability analysis in conjunction with engineering estimates to obtain the loss rate; plotting vulnerability curves; and finally, plotting a curve with wind speed as the horizontal axis and loss rate as the vertical axis to obtain vulnerability curves based on engineering estimates. This invention's method is characterized by its high efficiency in analytical calculation and is suitable for analyzing the failure probability and loss rate of transmission towers in engineering contexts.

The application relates to the technical field of disaster prevention and disaster reduction and resilience evaluation of urban infrastructure, and discloses an urban traffic system anti-seismic resilience evaluation system, which comprises a post-earthquake damage evaluation unit, an economic loss evaluation unit, a post-earthquake function evaluation unit, a repair and recovery simulation unit, a weak link identification unit, an anti-seismic resilience evaluation unit and a post-earthquake accessibility analysis unit. The system determines the self seismic damage state of roads and bridges through Monte Carlo simulation and traffic unit vulnerability curve, and determines the final damage state of the traffic unit in combination with the influence of the collapse of street buildings and the blocking of debris; direct economic loss and traffic capacity loss are calculated according to the final damage state, the repair and recovery process is simulated, the weak link is identified, the function-time curve is drawn, the resilience loss index is calculated, and the accessibility analysis of emergency services is carried out based on the post-earthquake road network state, so as to provide support for the anti-seismic planning of the urban traffic system and the post-earthquake repair decision.

The invention relates to the technical field of anti-seismic safety of power systems and structures, and provides a multi-source data intelligent-driven power transmission line earthquake risk prediction method and system in order to solve the problems that in the prior art, a model is single in applicable object, cannot be dynamically updated and lacks risk closed-loop management. The multi-source data intelligent driving power transmission line earthquake risk prediction method comprises the steps of processing an actual earthquake wave time history by using a continuously updated mixed deep learning model, and predicting a top displacement time history of a power transmission line to serve as a power transmission line dynamic response index; comparing the predicted top displacement time history of the power transmission line with a known structural performance limit value of the power transmission line, judging a structural performance state of the power transmission line and a corresponding risk level of the structural performance state, and converting the predicted top displacement time history into occurrence probabilities of different structural performance states by using a vulnerability curve method; the method has the characteristics of high prediction precision and strong adaptability, and can realize real-time risk early warning.

The present application provides a kind of wave action under breakwater and revetment structure's impact toughness evaluation method and system, comprising: the hydrological data of the area where breakwater and revetment structure are integrated, obtain representative wave hydrological characteristic value;Collect the design site information of the breakwater and revetment structure to be evaluated, determine the dominant failure mode and corresponding engineering demand parameter, and give the engineering demand parameter value under specific wave according to formula, numerical or physical model;The engineering demand parameter value is compared with vulnerability curve, and the damage grade of the breakwater to be evaluated and its probability distribution are obtained;According to the three performance indicators of casualty rate, economic loss rate and repair efficiency, the loss caused by different damage levels is evaluated, and the resilience evaluation index is calculated based on the decision proportion, and the resilience evaluation result is formed.It is logical, scientific and reasonable, and has strong operability, and the performance indicators considered are highly feasible, and has practical application value.

The application discloses a structure vulnerability evaluation method based on model updating hybrid test, and belongs to the technical field of anti-seismic performance evaluation. The purpose is to solve the problem of low precision and lack of applicability of the traditional vulnerability evaluation method of large complex civil engineering structures. The application combines online model updating technology, structure hybrid test technology and vulnerability calculation method to obtain the overall structure anti-seismic vulnerability curve. Firstly, 10-20 representative seismic records are selected, and the intensity parameters of the seismic records are ensured to be uniformly distributed; secondly, the selected seismic records are used for model updating hybrid test based on the SRCKF algorithm to obtain structure seismic response data; finally, the failure probability is calculated based on the structure damage index and the structure damage probability density function obtained by the test to obtain the structure vulnerability curve. The scheme provided by the application has the beneficial effect of improving the vulnerability evaluation precision of large complex civil engineering structures.

The application provides a vulnerability curve model construction method and device of a power transmission tower and electronic equipment, and the method comprises the following steps: obtaining experimental data of a scaled power transmission tower model of the power transmission tower under multiple different landslide impact working conditions; determining the damage level of the scaled power transmission tower model of the power transmission tower under each working condition according to the maximum horizontal displacement of the experimental tower top and a preset damage level table; determining the exceeding damage probability of each type of damage level corresponding to each target actual landslide impact force according to the experimental landslide impact force under each working condition and the damage level under each working condition; and performing nonlinear fitting on each target actual landslide impact force and the exceeding damage probability of each damage level corresponding to each target actual landslide impact force to construct a vulnerability curve model of the power transmission tower in a landslide disaster process. The construction of the vulnerability curve model of the power transmission tower under the landslide disaster process is realized.

The present invention relates to a time-varying vulnerability analysis method for cable-stayed bridges based on structural configuration and Bayesian networks, comprising the following steps: Step S1: Define external loads, cable-stayed bridge systems, and each component as nodes of a variable-structure discrete dynamic Bayesian network (VDDBN), and pre-define the VDDBN topology; Step S2: Consider the time-varying models and their uncertainties of structural parameters and external loads, and construct the VDDBN through parameter learning; Step S3: Input evidence into the VDDBN to infer the posterior probabilities of all nodes in all time slices, calculate the vulnerability probabilities of components to establish time-varying vulnerability curves of components, and finally establish the time-varying vulnerability curve of the structure through clustering. The present invention can effectively analyze the changes in the vulnerability of cable-stayed bridge systems over time history, providing reliable data for the safety and reliability of cable-stayed bridge systems.

The invention discloses a probabilistic grading fault scene generation method for an electrical integrated energy system, and relates to the technical field of integrated energy system optimization, and the method comprises the steps: firstly, considering the earthquake intensity uncertainty, discretizing a target earthquake magnitude range into a plurality of equidistant intervals, and calculating the occurrence probabilities of earthquakes of different earthquake magnitudes; secondly, modeling disaster-causing properties of earthquakes with different earthquake magnitudes by adopting a vulnerability curve, and calculating expected values of damaged elements of a power distribution system and a natural gas system; then, randomly generating a fault scene under each classification magnitude by using a Monte Carlo method, carrying out analogue simulation on the cascade fault of the electrical integrated energy system under the random fault scene, and recording the total loss load of the system; and finally, calculating an average load loss amount under each classification magnitude, and selecting a typical fault scene to form a classification fault scene set. According to the method, the tail risk of the small-probability extreme event is quantified, and a scene basis is provided for formulating a toughness improvement strategy of a comprehensive energy system.

The invention discloses a method and a system for improving the toughness of a power distribution network, which are used for solving the technical problem of poor toughness improvement effect of the power distribution network caused by the existing method for improving the toughness of the power distribution network. The method comprises the following steps: acquiring fault probabilities of a power distribution network element in multiple wind speed scenes, and constructing an element vulnerability curve; based on a Monte Carlo method, generating simplified scene distribution and a fault probability function of a power distribution network element in each wind speed scene according to a plurality of preset discrete wind speeds and an element vulnerability curve; establishing a two-stage random integer optimization model of active power distribution network planning based on the fault probability function and the simplified scene distribution of the power distribution network element in each wind speed scene; and solving the two-stage random integer optimization model of the active power distribution network planning, and generating a target power distribution network long-term toughness planning scheme.

The application provides a main aftershock sequence slope vulnerability analysis method and system based on double response indexes, relates to the technical field of earthquake slope vulnerability analysis, and comprises the following steps: constructing a GeoStudio slope model according to physical parameters of slope soil, obtaining an initial static safety factor and a critical acceleration of the slope; performing incremental dynamic time-history analysis according to main shock ground motion data, the slope model and the initial static safety factor of the slope, and obtaining shear strength parameter values of the soil after the main shock; updating the initial critical acceleration of the slope to obtain a critical acceleration of the slope after the main shock; performing aftershock incremental dynamic time-history analysis according to aftershock ground motion data and the critical acceleration of the slope after the main shock, and obtaining safety factor values and cumulative displacement results of the soil after the aftershock; and defining a vulnerability function based on a lognormal cumulative distribution function to obtain a multilevel slope vulnerability curve. The application improves slope risk assessment precision and visual decision-making capability.

The application provides a reinforced concrete component damage evaluation method, system, device and medium, and belongs to the technical field of structural damage evaluation, and comprises the following steps: constructing a fire response characteristic knowledge base containing reinforced concrete component fire physical test data and simulation data; taking component design parameters and fire working condition parameters of the reinforced concrete component in the knowledge base as input parameters, taking post-fire component response data as output parameters, training a machine learning agent model, and obtaining a prediction model for predicting direct physical damage indexes of the reinforced concrete component after the fire; constructing a fire vulnerability curve representing the relationship between failure probability and fire intensity based on the prediction model; receiving parameters of a component to be evaluated, and generating and outputting damage evaluation results of the component based on the prediction model and the fire vulnerability curve. Through data and model collaborative optimization, efficient and accurate post-fire reinforced concrete component damage evaluation is realized.

The invention discloses a traditional wood structure mortise and tenon joint asymmetric hysteretic model construction method based on openesses, and the method comprises the steps: introducing an asymmetric hysteretic restoring force model pinching4 uniaxial material model, and carrying out the asymmetric hysteretic restoring force model pinching4 uniaxial material model based on the test data of a dovetail joint joint; a multi-objective optimization algorithm is adopted to consider node energy consumption and node bending resistance to perform parameter identification on dovetail joint nodes with different lateral gaps, optimal parameters of a pinching4 model are obtained, and a zerolength unit in openases is defined based on the obtained optimal parameters to simulate the hysteretic performance of the simplified mortise and tenon joint nodes; corresponding space finite element models are established on the basis of tenon-and-mortise joint models with different gaps, incremental dynamic analysis is performed on the space finite element models, vulnerability curves of different models are obtained, and a reference basis is provided for evaluating the anti-seismic property of a traditional through-type wood structure dwelling.

The present invention discloses a method for constructing a flood vulnerability curve model, comprising: selecting an optimal daily extreme precipitation threshold and an optimal number of consecutive days, and calculating the annual total extreme precipitation data corresponding to this precipitation parameter combination on a grid-by-grid basis; statistically analyzing land cover change data and slope data using a density calculation method to obtain a corresponding weight matrix; combining the weight matrix, rasterizing the statistically obtained county-level annual total loss data by county and year; and dynamically constructing a flood loss curve using a deep learning multi-objective optimization four-parameter logistic function based on the rasterized county-level annual total loss data and annual total extreme precipitation data. This method can address the technical issues of insufficient data, low accuracy, and limitations on flood events or local cities in constructing flood loss curves, preventing their application to large-scale and large-scale data.

The invention discloses a power distribution network toughness evaluation method under a hurricane condition. The method comprises the following steps: acquiring hurricane comprehensive data; combining historical hurricane data with the corrected Rankine vortex model, establishing a wind field model and generating a hurricane scene; selecting a representative scene from the generated hurricane scene by adopting a scene reduction method based on hierarchical clustering; establishing a vulnerability curve for the power transmission line and the pole tower by taking real-time wind speed change, interaction effect between the pole tower and the line and component aging factors into account; the randomness of the fault probability in the vulnerability curve is converted into an equivalent resistance value; adjusting the baseline resistance value; and outputting an evaluation result of the hurricane influence on the power distribution network. The result shows that the evaluation result is highly consistent with the observed power shortage percentage.

The invention provides a vibration table test-based roadbed-track line anti-seismic toughness evaluation method, which comprises the following steps of: constructing a vibration table reduced scale model and setting a target point, acquiring roadbed vertical displacement and steel rail transverse displacement of the target point as engineering demand parameters, extracting a median value of the engineering demand parameters, taking logarithms of the median value and seismic oscillation intensity, and calculating the seismic toughness of the vibration table test-based roadbed-track line according to the logarithms of the median value and the seismic oscillation intensity. Drawing a scatter diagram and fitting a regression straight line; after regression parameters are determined, different damage state exceeding probabilities are calculated, and a vulnerability curve is drawn. On the basis, the occurrence probability of each damage state is calculated, a damage function is obtained in combination with a loss rate, and residual functions after an earthquake are determined; and determining a repair function form in combination with repair conditions, calculating a toughness index according to the definition, and evaluating the roadbed-track line shock resistance toughness grade. According to the method, a theoretical basis can be provided for formulating a reasonable protection, reinforcement and repair strategy by quantifying the damage state and the toughness index of the roadbed-track structure, the repair cost is reduced, and the traffic interruption time is shortened.

The invention relates to the technical field of underground structure damage evaluation, in particular to an underground station earthquake vulnerability analysis method based on probability damage weight, which comprises the steps of collecting geological exploration reports and underground structure materials, generating random earthquake oscillation and determining corresponding assigned probability, establishing random earthquake oscillation with the same model input intensity, and adjusting the earthquake oscillation intensity. Carrying out incremental dynamic analysis; the method comprises the steps of solving a generalized probability density equation, calculating a cumulative probability density function of an extreme value of a seismic performance index of each structural component, deriving a vulnerability curve of each structural component, calculating a damage weight coefficient of each structural component, and deriving a vulnerability curve of the whole station structure. It is not needed to assume that the seismic oscillation intensity and the structural damage degree obey specific probability distribution in advance, and meanwhile contribution of damage of different structural members to overall structural damage can be reflected.

The invention discloses an anti-seismic toughness evaluation method and related equipment. The method comprises the following steps: determining a vulnerability curve of a to-be-evaluated object in each damage state, wherein the vulnerability curve is used for representing a failure probability corresponding to each damage state under a plurality of seismic intensity indexes; determining a corresponding recovery model of the to-be-evaluated object in each damage state; determining a first toughness index of each damage state based on the corresponding recovery model; determining a second toughness index of the to-be-evaluated object under the plurality of seismic intensity indexes based on the failure probability and the first toughness index corresponding to each damage state; and according to the evaluation threshold value of the evaluation object and the second toughness index, carrying out anti-seismic toughness evaluation on the to-be-evaluated object to obtain an evaluation result. According to the method, the toughness index levels among different systems can be reliably and effectively analyzed, the differentiated definition requirements of different types of objects on risk levels are met, the reliability of an anti-seismic toughness evaluation result is improved, and the method can be widely applied to the technical field of engineering toughness analysis.

The application discloses a kind of urban road network traffic flood vulnerability evaluation method based on multi-source multi-modal data, through multi-source data fusion technology, combine hydrology, water conservancy, land use, DEM, road network attribute, traffic flow, social economy, social media and mobile phone signaling and other multi-source data, constructs road network disaster vulnerability evaluation model. Weighted fusion method is used to efficiently integrate multi-modal data, and high-performance hydrodynamic integrated model HiPIMS is used to realize high-resolution water depth grid dynamic simulation, accurately capture the changes of road traffic flow, speed and traffic capacity under flood situation, and verify the reliability of its results through verification index. Based on the service characteristics of road grade and flood loss rate, the vulnerability curves of different grades of roads are derived, and the speed is verified by using mobile base station-based mobile phone signaling data, which innovatively realizes the quantitative analysis and grade division of road network disaster vulnerability, significantly improves the accuracy and timeliness of road network risk quantification.