77 results about "Seismic engineering" patented technology

The invention provides a building economic loss assessment method and device under the earthquake and secondary fire coupling effect, and relates to the technical field of earthquake engineering. The method comprises the following steps: acquiring a post-earthquake damage state of a building structure through nonlinear time-history analysis according to earthquake input data; establishing a secondary fire CFD analysis model; according to the positions of the flammable and explosive components, determining a highest probability fire point to perform CFD analysis, and outputting temperature field data and flue gas spreading data of a structural entity part, a non-structural entity part and an outer surface part of each component; analyzing according to the temperature field data to obtain damage states of a structural part and a non-structural part of the component; and obtaining the flue gas contamination condition of the outer surfaces of the components according to the flue gas spreading data, further calculating the economic loss of each component, and summarizing the loss of all the components to obtain the total loss of the building. According to the method, the technical blank of multi-disaster coupling loss evaluation is filled up, and a more effective and more scientific decision basis is provided for post-earthquake emergency and reconstruction.

The invention provides an earth crust spectrum unit optimization modeling method suitable for strong seismic wave field simulation under complex topographic conditions, and relates to the field of seismic engineering, and the method comprises the steps: determining topographic parameters of a research area; according to wave velocity structure parameters of a research area, determining a mesh refinement multiple, and obtaining a minimum distance from a wave velocity contour surface to the bottom; determining the position of a refinement conversion layer of the earth crust spectrum unit; determining the total number of three-way units before mesh refinement according to the position of the earth crust spectrum unit refinement conversion layer; carrying out mesh generation in the whole domain by adopting hexahedron units; according to the layer number of the earth crust spectrum units at the upper part of the conversion layer, carrying out superficial earth crust model refinement processing; and calculating grid quality, counting the number of the earth crust spectrum units to obtain an expected value of the earth crust spectrum units, and comparing the expected value with the estimated value. According to the method, the quality problem of the spectrum unit during modeling of the earth crust structure in regions with complex topographic conditions such as alpine and canyon can be solved, meanwhile, the calculation freedom degree is reduced to the minimum, and stable and low-cost seismic oscillation simulation based on the spectrum element method is achieved.

The invention relates to the technical field of seismic records, in particular to a near-source strong seismic record selection method and system considering a sliding impact effect, and the method comprises the following steps: introducing permanent displacement as a condition parameter into seismic oscillation selection based on a generalized condition intensity index; a target permanent displacement amount is given by an extended probability fault displacement danger analysis method; in the target seismic intensity index set, spectrum displacement is used for replacing common spectrum acceleration to represent spectrum components of seismic oscillation; an empirical correlation coefficient suitable for permanent displacement type near-source strong earthquake records is further calculated and given, corresponding condition intensity index target distribution is constructed, and finally optimization is carried out from a near-source strong earthquake database to obtain a permanent displacement type near-source strong earthquake data set which is most consistent with the target condition distribution; according to the method, a reasonable input vibration selection method can be provided for seismic response analysis of a near-seismic-source engineering structure under the strong vibration-fault movement coupling effect.

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 invention discloses an earthquake damage assessment method based on wavelet transform and a deep convolutional neural network, and relates to the technical field of earthquake engineering, and the method comprises the following steps: 1, obtaining the building information of a target region, simulating the target region, generating a plurality of seismic oscillation records, and adding a damage label to each building under the seismic records of each region; 2, carrying out wavelet transformation on a seismic oscillation time history in the seismic oscillation record, and generating a multi-scale two-dimensional time-frequency energy diagram; 3, building information, the multi-scale two-dimensional time-frequency energy diagram and damage labels are in one-to-one correspondence to construct a data set; 4, constructing and training an earthquake damage evaluation model; and step 5, carrying out earthquake damage assessment based on the trained earthquake damage assessment model. According to the method, intelligent identification of the earthquake damage level can be realized, and the method is suitable for post-earthquake rapid evaluation, key area screening, auxiliary emergency decision making and other application scenes.

The invention relates to the technical field of seismic engineering, and provides a method and system for solving a seismic wave propagation equation based on a physical information neural network, and the method comprises the steps: determining a space domain, a time domain, an initial condition and a boundary condition of a one-dimensional seismic wave equation; initial boundary value coordinate points are randomly extracted to serve as a training data set constraint network, and Latin hypercube sampling is utilized to generate space-time domain configuration points to meet partial differential equation constraint; a physical information neural network model is established, after space-time coordinates are input, equation residual errors are calculated through automatic differential, and initial boundary value loss and physical residual errors are combined to construct a composite loss function for training; and proposing a self-adaptive region sampling strategy based on residual errors, resampling a high residual error region according to an average residual error value of the configuration points in a training period, and iteratively optimizing network parameters after a newly added point and an initial configuration point are fused. According to the method, by dynamically enhancing the sampling density of a high-error region, the L2 relative error of a prediction solution is reduced by one order of magnitude, the network is effectively prevented from falling into local optimum, the convergence efficiency is remarkably improved, grid discretization or prior data support is not needed, and a high-precision meshless solution scheme is provided for a one-dimensional seismic wave equation.

The present invention provides a crustal spectral unit optimization modeling method suitable for simulating strong earthquake wave fields in complex terrain conditions, which relates to the field of earthquake engineering. The method comprises determining the terrain parameters of the study area; determining the grid refinement factor based on the wave velocity structure parameters of the study area, and obtaining the minimum distance of the wave velocity isosurface from the bottom; determining the location of the crustal spectral unit refinement transition layer; determining the total number of three-dimensional units before grid refinement based on the location of the crustal spectral unit refinement transition layer; using hexahedral units to mesh the entire area; refining the shallow crust model based on the number of crustal spectral unit layers above the transition layer; calculating the grid quality, counting the number of crustal spectral units to obtain the expected value of the crustal spectral units, and comparing it with the estimated value. The present invention can solve the quality problem of spectral units when modeling crustal structure in areas with complex terrain conditions such as high mountains and canyons, while minimizing the computational degrees of freedom, and achieving stable and low-cost simulation of earthquake motion based on the spectral element method.

The invention provides a site classification method and system based on a regional gradient-Vs30 mapping model, electronic equipment and a storage medium, and relates to the technical field of seismic engineering and site classification.The method comprises the steps that a grid where a drilling point in a to-be-measured area is located is used as a center pixel, a nine-square window is constructed, and a Vs30 mapping model is constructed; and calculating elevation change rates of the central pixel and the adjacent pixels in x and y directions based on the digital elevation data, and further obtaining a terrain slope value through a slope formula. A slope value is converted into a soil layer shear wave velocity predicted value by utilizing a pre-constructed regional gradient-Vs30 mapping model, and the model is optimized through local drilling data, so that the regional applicability is improved. And finally, according to the mapping relationship between the interval and the site category, classifying the predicted values and generating a site classification spatial distribution diagram. According to the method, the site classification precision and the engineering applicability are improved.

This invention provides a prototype pipe pile shaking table test system for simulating the effects of foundation and superstructure, belonging to the fields of structural engineering, earthquake engineering, and foundation engineering. It includes a shaking table, a prototype pipe pile specimen horizontally arranged on the shaking table surface, a foundation action simulation component, a pile top axial compression simulation component, a pile cap simulation component, and a superstructure dynamic simulation component. The foundation action simulation component is fixed to the shaking table surface and covers the outside of the prototype pipe pile specimen. The pile top axial compression simulation component penetrates the inside of the prototype pipe pile specimen and extends to the outside of the pile bottom. The pile cap simulation component is connected to the top of the prototype pipe pile specimen, and the superstructure dynamic simulation component is positioned above the pile cap simulation component. This invention, using the above-mentioned test system, solves the problems of existing prototype pipe pile shaking table tests, such as large space requirements, high cost of foundation simulation, difficulty in loading real superstructures, inconvenient adjustment of working conditions, difficulty in comprehensively simulating pile-soil-structure interactions, and inability to accurately measure dynamic changes in pile axial force.

The invention discloses a post-earthquake evacuation method and system based on image analysis, belongs to the technical field of earthquake engineering, and aims to solve the problems of slow response and inaccurate guidance due to the fact that dynamic changes of secondary disasters such as aftershocks and fire disasters cannot be handled in real time by means of manual guidance and traditional emergency broadcast and static evacuation routes. Comprising the steps of obtaining high-definition image data through an unmanned aerial vehicle, a satellite, a camera, a LiDAR and a spectrum sensor in an earthquake influence area, performing multi-dimensional processing on the image data based on a deep learning model, and generating a risk thermodynamic diagram of a dangerous area; through deep analysis of different types of image data, multiple risk sources in the post-earthquake environment can be identified, the dangerous area thermodynamic diagram is generated according to the risk sources, the system can dynamically plan the optimal evacuation path based on the dangerous area thermodynamic diagram, it is ensured that personnel avoid high-risk areas in the evacuation process, and the personnel evacuation efficiency is improved. Therefore, the evacuation efficiency and the personnel safety are improved.

The application discloses a kind of based on spatial intelligence's active fault three-dimensional model automatic construction method, belong to geological exploration and earthquake engineering technical field;Method includes: collection data, analysis and extract minimum complete subdirectory;Through adaptive threshold hierarchical clustering combined with improved RANSAC algorithm, the exclusive small earthquake cluster of each fault is automatically identified;Based on local weighted regression, three-dimensional automatic slice is made to small earthquake cluster, and each profile fault interpretation line is fitted by moving least square method;Finally, active fault three-dimensional fine model is constructed;Test model rationality and output model file;The application realizes the automation, quantification of fault modeling whole process, can be fused multi-source data and realize multi-element constraint modeling, adapt complex fault zone modeling, and the fine three-dimensional model constructed can provide key data support for fault present-day deformation inversion, three-dimensional potential source research, earthquake geological disaster assessment, with higher engineering application value.

The application discloses a kind of based on visual element's floating non-structural member earthquake damage identification method, belong to the technical field of earthquake engineering;Including the following steps: with double flow length time sequence convolution video understanding model as foundation to build the earthquake damage identification system of floating non-structural member, the model is composed of three-channel convolutional neural network and bidirectional long time sequence prediction model;Spatial time sequence information is extracted using three-channel convolutional neural network, and the feature map and time sequence information are built using bidirectional long time sequence prediction model;Finally, the feature fusion of two kinds of ways is carried out, so as to realize the class prediction and damage state identification of floating non-structural member in earthquake damage video.The application method combines double flow video understanding model and long time sequence convolution processing model, utilizes the feature fusion of spatial information and time sequence information, strengthens the information sharing and fusion between each video frame, and makes more accurate judgment on the post-disaster situation of building.

The invention discloses a complex terrain seismic oscillation amplification coefficient prediction and correction method and system based on a convolutional neural network model, and belongs to the application of a deep learning method in the field of seismic engineering. The method comprises the following steps: firstly, respectively establishing seismic oscillation databases of isolated terrains and regional complex terrains; training by using a BP neural network to obtain an isolated terrain seismic oscillation amplification coefficient prediction model, and training by using a convolutional neural network to obtain a regional terrain influence coefficient prediction model; and multiplying the isolated terrain prediction coefficient of the to-be-measured site by the regional terrain influence prediction coefficient to obtain an accurately corrected seismic oscillation amplification coefficient. The method overcomes the defect that an existing method neglects the regional terrain coupling effect, effectively improves the prediction precision of the seismic oscillation amplification coefficient under the complex terrain condition, and provides more reliable technical support for engineering aseismic design and seismic risk assessment.

The invention relates to the technical field of seismic engineering and artificial intelligence, in particular to a seismic oscillation selection method and system based on spectral feature extraction and clustering, and discloses a seismic oscillation record selection method based on principal component analysis dimensionality reduction and K-means clustering. The method comprises the following steps: firstly, acquiring candidate records from a database according to set seismic parameters of a site, and performing pulse and non-pulse label division; amplitude modulation and normalization preprocessing are carried out on the response spectrum data, and a high-dimensional acceleration response spectrum is compressed into low-dimensional potential features through PCA dimension reduction; and finally, on the basis of a dimension reduction result, performing grouping by applying a K-means clustering method, and performing record selection and response spectrum comparison. The system comprises a record reading and processing module, a feature extraction module, a feature clustering module, a verification module and an output module, velocity pulse and non-pulse classification is carried out before an alternative record data set is constructed, and a near fault velocity pulse effect is considered at the beginning of record selection.

This invention discloses a machine learning-based method for predicting earthquake-induced sand liquefaction deformation, relating to the fields of earthquake engineering and machine learning. The method constructs a multi-source coupled earthquake dataset using engineering survey reports and monitoring data from historical earthquake cases. This dataset undergoes missing value processing, outlier detection, feature selection, and standardization to obtain an earthquake-induced sand liquefaction deformation dataset. Based on this dataset, a prediction model is constructed. The root mean square error, mean absolute error, and coefficient of determination of the model are calculated. Based on corresponding thresholds, the model is adjusted for hyperparameters using Bayesian optimization or encapsulated using Flask. New earthquake-induced sand liquefaction feature data is then processed and input into the encapsulated model to obtain the predicted earthquake-induced sand liquefaction deformation results. This method can effectively predict earthquake-induced sand liquefaction deformation, providing support for earthquake disaster prevention and engineering design.

The invention discloses a near-fault multi-point multi-dimensional fully non-stationary seismic oscillation dimension reduction simulation method and system, and belongs to the technical field of seismic engineering and disaster prevention and reduction. The method provided by the invention comprises the following steps: firstly, screening near-fault strong earthquake records containing horizontal and vertical velocity pulses, fitting the extracted pulses by using a Gabor wavelet model, identifying low-frequency key parameters and establishing probability distribution; a high-frequency component is simulated by a 1D-nV non-stationary random vector process, and dimensionality reduction is carried out in combination with a random orthogonal function; and generating a representative point set through number theory point selection and equal probability inverse transformation, substituting the representative point set into the model to generate high and low frequency speed time histories, and superposing the high and low frequency speed time histories to obtain a seismic oscillation sample with complete probability information. The system comprises a data screening module, a parameter identification module and the like. According to the method, samples meeting the precision are generated by using extremely few random variables, the simulation efficiency is improved, and the method can be combined with the probability density evolution theory for engineering structure dynamic response and anti-seismic reliability analysis.

The invention discloses a site differentiation earthquake response analysis method and system based on earthquake motion types, and belongs to the technical field of building earthquake-proof engineering, and the method comprises the steps: dividing a target site into three types of sites according to the obtained drilling information of the target site, and constructing a site model corresponding to each type of site; respectively calculating dynamic response results of each site model under the near-field pulse type seismic motion and the near-field non-pulse type seismic motion by adopting a time domain nonlinear analysis method; generating two groups of surface response spectrum amplification coefficients according to the dynamic response result of each site model, and comparing peak values with periods; and according to a comparison result of the peak value and the period, combining each site model to obtain a differential earthquake response analysis result. According to the method, the significant amplification effect of pulse type seismic oscillation on a soft soil site and the significant amplification effect of non-pulse type seismic oscillation on a medium-hard soil site are effectively revealed, and the problem that the difference of seismic oscillation types is not fully considered in existing analysis is solved.

The invention discloses an FE-VFIFE hybrid calculation method for nonlinear dynamic analysis of a complex structure, which is suitable for the fields of seismic engineering, ocean engineering and the like which require real-time simulation and analysis of the complex structure, the FE and the VFIFE are combined, dimension reduction of each linear substructure is realized through a modal superposition method in a conventional finite element, and the nonlinear dynamic analysis of the complex structure is realized. The whole system is decoupled into a series of modal equations, and the calculation amount is reduced; vector type finite elements are used for calculating the internal force of the nonlinear part, the situation that a global stiffness matrix is repeatedly updated in the calculation process is avoided, meanwhile, a Chang method is adopted for unconditional stable integration, and mass and damping correction factors are introduced to improve the calculation precision, increase the integration step length and improve the calculation efficiency. The method can be efficiently applied to real-time hybrid simulation of the local nonlinear problem of a complex structure system, and powerful support is provided for performance evaluation and design optimization of the complex structure under the action of complex dynamic loads such as earthquakes and marine environments.

A speed pulse recognition method based on zero-crossing closing interval and decoupling criterion belongs to the field of earthquake engineering and seismic signal processing, and comprises the following steps: step 1, speed time history acquisition and pretreatment; step 2, candidate interval of closing pulse is constructed; step 3, energy calculation and candidate screening; step 4, global energy concentration window construction and screening: cumulative energy curve is constructed, and consistent constraint screening is carried out based on the global energy concentration window; step 5, adjacent interval continuity discrimination and boundary marking: the continuity of adjacent intervals is discriminated, and the decoupling and to-be-merged boundary are marked; step 6, merging and reorganization iteration and pulse group generation; step 7, energy concentration review and determination output: the concentration is reviewed, and the pulse type and key parameters are output. And a speed pulse recognition device based on zero-crossing closing interval and decoupling criterion is provided. The present application improves the reliability and engineering applicability of the pulse recognition result under complex seismic motion conditions.

The present invention belongs to the field of seismic engineering drawing, and discloses a method for batch generating result data drawing library files. First, the field acquisition parameter list and processing parameter list are extracted from the field report file and the seismic line CMP coordinate - elevation file, and saved in the LTP and LSL library files, and the standard templates of the LTP and LSL library files are established; the field report files and seismic line CMP coordinate - elevation files of each seismic line are collected and named in a unified format; the information extracted from the seismic line CMP coordinate - elevation file and the field report file is synthesized to obtain the total drawing parameter information table, and the total drawing parameter information table is batch written into the standard drawing library files according to the established standard templates of the LTP and LSL library files. The present invention is applicable to batch generating result data drawing library files. By batch writing the total drawing parameter information table into the standard drawing library files according to the established standard templates of the LTP and LSL library files, the production efficiency is improved and the workload of processing personnel is reduced.

The application discloses a kind of Rayleigh wave multimode coupling's soil-structure interaction system seismic response calculation method, it is related to soil-structure dynamic interaction technical field in earthquake engineering. Including: obtaining seismic wave time domain signal and site, foundation, upper structure parameter and modeling;Seismic wave time domain signal is Fourier transformed to obtain frequency domain signal and several discrete frequency points;For each discrete frequency point, construct site overall dynamic stiffness matrix, solve each order modal dispersion curve of Rayleigh wave, calculate each order modal free field response, calculate modal participation coefficient based on energy flow density and superimpose coupling to obtain free field overall response;Utilize Green function to calculate rigid foundation dynamic impedance and effective input;Solve foundation and structure frequency domain response, then inverse transform time domain response is obtained.The application has the advantages of frequency domain processing and time domain stability, significantly improves the calculation precision under wideband input, and is suitable for complex site infrastructure seismic evaluation and design.

The utility model relates to the technical field of structure anti -seismic engineering discloses a kind of intercolumnar energy dissipation shock absorber for silo, including base, the top of base is slidably connected with base, and self-adapting buffer assembly is arranged between base and base, multiple support columns are evenly arranged on the side of base away from base, symmetric shock absorber assembly and tensile energy-absorbing component are arranged between a pair of support columns, and fixed component is arranged in the middle of support column, symmetric shock absorber assembly includes box one, and box one is assembled in the middle of support column, and box two is slidably connected in the inside of box one. By the cooperation of support column, box one, box two, box three, lead to groove, wave buffer piece, honeycomb elastic sheet and other structures, convert seismic energy into deformation energy and heat energy inside material, multidirectional reduce vibration impact, ensure support column stability, and then stabilize the overall structure of silo.

The invention is suitable for the technical field of structural seismic engineering, and provides a construction method, device and equipment of a wading underground structure seismic response prediction model, and the method comprises the steps: firstly, generating a seismic response database based on a simulation result of a structure-soil-fluid coupling finite element model; then, based on a plurality of seismic oscillation sample feature vectors extracted from the plurality of seismic oscillation sample data, performing clustering analysis on the plurality of seismic oscillation sample data to obtain a training data set; and finally, taking the target seismic oscillation sample data and the water depth parameter in the training sample data as input data, taking the seismic response data of a plurality of monitoring points in the training sample data as labels of the input data, training the initial seismic response prediction model, and obtaining a wading underground structure seismic response prediction model. Through the method, the prediction precision and prediction efficiency of the multi-monitoring-point earthquake response of the wading underground structure are improved.

This invention, a method for identifying seismic liquefaction of sand based on the spectral analysis of seismic acceleration data, belongs to the field of seismic engineering. It aims to solve the problems of low efficiency, high cost, and low accuracy in distinguishing between non-liquefiable and liquefiable soft soil sites using traditional methods. The invention collects bidirectional horizontal seismic acceleration time-history data, dividing it into training and testing sets. It extracts peak ground acceleration (PGA) and uses a liquefaction trigger threshold for initial identification; sites not reaching the threshold are directly classified as non-liquefiable. Once the threshold is reached, the data is segmented based on the first time the threshold is reached, and the spectrum is obtained through bandpass filtering and Fourier transform. The differences in the proportion of low-frequency components and the differences in characteristic frequencies are calculated. Using the two features as input, a discrimination model is constructed using logistic regression and maximum likelihood estimation, and the decision boundary is determined. The accuracy is verified using a test set. This method requires only acceleration time-history data, has low discrimination cost and high efficiency, effectively distinguishes between non-liquefiable and liquefiable soft soil sites, has strong anti-interference capabilities and high accuracy, and is suitable for rapid assessment of sand liquefaction after strong earthquakes and for seismic engineering applications.

The invention relates to the field of earthquake engineering technology, in particular to a method and system for selecting earthquake motion records matching an earthquake recurrence period; the method comprises the following steps: step one: generating a random earthquake event catalog; step two: calibrating the total earthquake occurrence rate; step three: determining a plurality of earthquake intensity indices related to an analysis structure; step four: determining the joint probability of a plurality of earthquake intensity indices; step five: obtaining a simulated spectrum through an error threshold of a Kendall recurrence period, and obtaining a target spectrum by calculating a mean and a standard deviation of the simulated spectrum; and step six: after the target spectrum distribution is known, selecting a set of records that meet the requirements from a target database; the invention constructs a target spectrum according to a multivariate Kendall recurrence period, which not only gets rid of the problem that a traditional wave selection scheme is greatly affected by the selection of a conditional earthquake motion intensity index, but also provides a mathematically rigorous scheme for constructing a wave selection target spectrum with an IM combined hazard level as a control index, thereby providing a more accurate earthquake demand estimation for earthquake motion records.

The application discloses a buried pipeline seismic vulnerability analysis method based on a three-parameter square normal distribution, belongs to the field of civil engineering and earthquake engineering, and solves the problem that an existing lognormal distribution model cannot accurately reflect the skewness characteristics of structural response data, thereby leading to the calculation deviation of failure probability, and the method comprises the following steps: generating seismic input data, establishing a buried pipeline finite element model, performing nonlinear time-history analysis, extracting pipeline response data, calculating the failure probability of the buried pipeline under different seismic intensity based on the three-parameter square normal distribution, and drawing a vulnerability curve; the application builds a complete system covering seismic simulation-buried pipeline response analysis-seismic vulnerability analysis, improves the calculation precision of the seismic failure probability of the buried pipeline by introducing the three-parameter square normal distribution which can accurately reflect the skewness characteristics of the structural response data, and thus a seismic vulnerability model with wider application range and higher precision is provided.

The present application belongs to the field of earthquake engineering and civil engineering, and particularly relates to a method for quickly formulating a demolition scheme of a damaged building based on a genetic algorithm and reinforcement learning. The method comprises the following steps: S1: establishing a data information base of a target damaged building to be demolished, mainly including various building structure types, structure plane arrangement, building site categories, and beam column member sizes; S2: establishing a finite element model for structure progressive collapse analysis according to the collected information; S3: determining the range of members allowed to be demolished during the collapse analysis of the demolished structure according to the collected information; S4: calculating a single demolition effect according to the finite element model for progressive collapse analysis; and S5: selecting a genetic algorithm or a Q-learning reinforcement learning algorithm according to whether the influence of the demolition sequence needs to be considered in actual conditions to obtain an optimal demolition scheme. The present application can be used for quickly formulating a demolition scheme of a severely damaged building in post-earthquake repair and reconstruction.

The invention relates to the technical field of earthquake engineering, in particular to an earthquake vibration model construction and evaluation method based on big data. Comprising a hardware and rule component and a platform architecture component (a relational / non-relational database, a data warehouse, a metadata center, an association rule / clustering algorithm module, an LSTM / GRU earthquake risk prediction model, a resource scheduling model and a scientific research / emergency / public differentiation application function module), the model construction assembly comprises a finite difference / finite element multi-scale site model, a building group / power transmission tower structure-site coupling sub-model, a seismology-deep learning mixed training framework and a model parameter staged correction module.

The application discloses a fault information independent near-fault pulse type ground motion selection method, belonging to the field of earthquake engineering and structural seismic analysis, and comprises the following steps: step 1, firstly, according to a target risk level, a target peak ground acceleration PGA of a site is determined through a ground motion parameter zoning map; a PGV / PGA recommended value is obtained by inquiring a pre-established PGV / PGA recommended value table according to the PGA value; and secondly, ground motion selection is carried out for the target site; step 2, based on a conditional parameter, it is assumed that the conditional parameter and a spectrum shape parameter joint vector conform to a multivariate normal distribution in a logarithmic space, and the conditional mean vector and the conditional covariance matrix of the four spectrum shape parameters are calculated from a ground motion database as target statistical characteristics by utilizing the conditional distribution properties; and step 3, a two-stage optimization algorithm is adopted to select matched ground motion. The application is free from fault information dependence, effectively incorporates the pulse effect, has strong practicability, is simple to operate, and has good risk consistency.

The utility model relates to the technical field of house corner clamps, and discloses a house reinforcing quakeproof corner clamp which comprises two vertical plates, the tops of the two vertical plates are fixedly connected with mounting plates, connecting mechanisms are arranged in the mounting plates, supporting mechanisms are arranged at the bottoms of the vertical plates, reinforcing mechanisms are arranged at the tops of the supporting mechanisms, and the reinforcing mechanisms are arranged on the tops of the supporting mechanisms. A welding mechanism is arranged at the top of the vertical plate; the supporting mechanism comprises two connecting plates, the tops of the two connecting plates are slidably connected to the bottoms of the two vertical plates correspondingly, a transverse plate is fixedly connected to the bottoms of the two connecting plates, and two connecting bolts are connected to the interior of the transverse plate in a threaded mode. According to the utility model, the corner clamp becomes a standardized module through the synergistic effect of all the mechanisms, modular connection and installation can be directly carried out in the house reinforcing and earthquake-proof engineering, complicated field processing and adaptation are not needed, the installation efficiency and effect are greatly improved, and the installation difficulty and cost are reduced.