226 results about "Ground motion" patented technology

The invention discloses a ground motion intensity measure optimization method for seismic response prediction. The method includes the following steps: (1) building a building damage database; (2) optimizing ground motion intensity measures; (3) constructing a machine learning model; and (4) predicting damage states. According to the method, a combination of optimal ground motion intensity measures is selected by an elastic-net algorithm, wherein the efficiency and practicability in a current selection criterion are updated based on the goodness of fit and regression coefficient of the elastic-net model, thereby avoiding an assumption that intensity measures and structure response need to obey a logarithmic linear relationship and the limitation of intensity measure dimensions in traditional methods. By using the combination of optimal ground motion intensity measures as input variables, the prediction accuracy can be remarkably improved, and meanwhile the number of samples required is reduced.

The invention provides a slope quality monitoring and early warning method and system based on seismic oscillation data, and the method comprises the steps: firstly obtaining a seismic oscillation monitoring data set of a target slope region, covering seismic oscillation waveform data and environment correlation parameters of a plurality of monitoring nodes in a preset time period, and then carrying out the dynamic preprocessing of the seismic oscillation monitoring data set, comprising data alignment, noise filtering and dimension unification, a standardized data set is obtained, then a dynamic association feature set containing seismic oscillation energy distribution, slope response frequency and environment coupling fluctuation features is extracted based on the standardized data, and then a slope quality analysis model is called to carry out state prediction on the feature set. And generating a slope quality evaluation result according to the difference degree between the stable state characteristics and the abnormal fluctuation characteristics, and finally determining an early warning strategy according to the slope quality evaluation result and triggering early warning signal output, thereby realizing effective monitoring and early warning of the slope quality.

The invention relates to a multi-dimensional seismic risk assessment method based on seismic oscillation space-time distribution. The method comprises the following steps: S1, selecting IM indexes; s2, key structure parameters are extracted; s3, recording an engineering demand parameter EDP; s4, selecting an optimal IM index; s5, establishing an agent model of structural seismic response; s6, establishing an earthquake prediction equation; s7, establishing an aftershock risk analysis model; s8, obtaining aftershock intensity samples of the positions of the target structures; s9, obtaining an aftershock vulnerability curve; and S10, determining repair time and repair cost according to the repair of the structure and the repair of the structure function so as to finally determine the total repair cost of the structure of the regional line and the anti-seismic capacity after repair. Compared with the prior art, the method has the advantages of improving the accuracy of earthquake risk estimation and the like.

The invention relates to the technical field of earthquake prediction, in particular to a submarine seismic oscillation prediction method and device based on earthquake exploration, and the method comprises the following steps: selecting a monitoring region, collecting the submarine topographic data of the monitoring region, and drawing a topographic map; selecting a plurality of monitoring points according to the topographic map; geomagnetic field information, electric wave information, micro-seismic activity information and seabed deformation information of each monitoring point are collected and recorded; converting the collected information into acoustic signals and transmitting the acoustic signals to a sea surface buoy, and converting the acoustic signals into electric signals by the sea surface buoy and transmitting the electric signals to a ground data center; by optimizing site selection of monitoring points, integrating geomagnetic-electric wave-microseismic-deformation multi-source data, realizing high-efficiency data transmission by using an acoustic-electric staged communication chain, and finally realizing early recognition of earthquake precursor in combination with threshold analysis, the method can significantly improve the coverage range, data precision and early warning timeliness of seafloor earthquake monitoring, and has good application prospects. And a technical support is provided for marine geological disaster prevention and control.

The invention relates to the technical field of debris flow identification, and discloses a debris flow seismic oscillation signal identification method based on machine learning. The method comprises the following steps: acquiring a debris flow ground motion signal; constructing a debris flow seismic oscillation signal identification model based on a slice attention mechanism; the debris flow seismic oscillation signal identification model based on the slice attention mechanism is utilized to firstly perform instance normalization processing on debris flow seismic oscillation signals, then cut the debris flow seismic oscillation signals through overlapped sliding windows, and then perform Fourier transform processing on each slice. And then slice time sequence features are extracted from the slice sequence subjected to Fourier transform through an LSTM model, the attention weight is calculated by adopting a multi-head attention mechanism in combination with position codes of slices at different positions, and finally a debris flow seismic oscillation signal identification result is obtained through a full connection layer.

The invention discloses a transmission tower vulnerability analysis method and system based on seismic simulation, and belongs to the technical field of electric power facility disaster prevention, and the method comprises the steps: correcting bedrock seismic oscillation parameters based on equivalent shear wave velocity, and generating a high-precision earth surface PGA distribution diagram; automatically positioning a key node layer through eigenvalue decomposition, reducing the order of the three-dimensional model of the power transmission tower into a two-dimensional series multi-degree-of-freedom model, and outputting a layer mass vector, a condensation stiffness matrix and rod piece bending stiffness; performing time-history analysis by using the corrected PGA-driven reduced-order model to generate an earthquake damage probability; the multi-source remote sensing data and the PGA are fused, the landslide space probability is output through a deep learning model, and the impact strength and the landslide kinetic energy are calculated to judge the landslide damage probability; and based on the dual-threshold condition triggering probability union set, calculating a comprehensive damage probability, and generating a three-dimensional vulnerable curved surface. According to the method, the problems of high missing report rate and low calculation efficiency of single disaster assessment are solved, and minute-level accurate early warning of the composite disaster risk of the power transmission tower is realized.

The invention relates to the technical field of earthquake prediction, in particular to a three-dimensional earthquake motion field rapid prediction method based on deep learning and physical constraint, and the method comprises the following steps: S1, data collection: obtaining original data related to an earthquake event in real time; s2, data preprocessing and multi-modal data fusion: preprocessing the original data, and fusing the preprocessed original data into multi-modal data; s3, spatial interpolation: realizing seismic oscillation feature interpolation prediction of the epicentral region, and outputting spatial spectrum data; s4, time sequence prediction and physical information optimization: generating a seismic oscillation time domain prediction sequence, and correcting errors by using an SVM model; s5, real-time reasoning and emergency response: realizing real-time minute-level response under the GPU architecture, and outputting three-dimensional seismic motion field data; according to the method, high-precision minute-level prediction of the three-dimensional seismic motion field is realized, and the efficiency and reliability of post-earthquake emergency response are remarkably improved.

The invention discloses a seismic oscillation generation method based on a DFEM model, and the method comprises the steps: obtaining multi-source data in a target simulation region, and obtaining fusion stratum wave velocity structure data; determining the minimum grid size of the DFEM model according to the fused stratum wave velocity structure data and a preset simulation frequency upper limit, and dividing grids and determining nodes according to the minimum grid size; constructing a seismic propagation related physical constraint set; the physical constraint is embedded into a primary training process of a DFEM model, a Green function of a fracture surface sub-source in a target simulation area is obtained, convolution operation is carried out on the Green function, expanded seismic oscillation samples under different scenes are generated, and the expanded seismic oscillation samples and full-physical simulation seismic oscillation samples form a data set; performing secondary training on the DFEM model based on the data set to obtain a seismic motion prediction model; and generating diversified vibration samples based on the seismic motion prediction model. The problems that traditional pure physical simulation seismic oscillation simulation is high in cost, long in time and the like are solved.

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 relates to the technical field of seismic data analysis, in particular to a seismic station ground motion noise quantification method and related equipment based on a GPU (Graphics Processing Unit), and the method comprises the steps: firstly obtaining waveform record data of a target seismic station in a set time period; performing sliding window segmentation processing on the waveform recording data in parallel by utilizing a GPU (Graphics Processing Unit) to obtain a plurality of waveform recording sub-segments; preprocessing the data of the plurality of waveform recording sub-segments in parallel through a GPU (Graphics Processing Unit); finally, the power spectrum density of the ground motion noise in the preprocessed sub-segments is calculated in parallel through the GPU; and carrying out parallel statistics on a power spectrum density probability density function result based on the power spectrum density by utilizing a GPU (Graphics Processing Unit) to complete the quantitative calculation of the earth motion noise. According to the method, the data processing efficiency is improved based on the parallel computing capability of the GPU, hardware computing resources are fully called, and the earthquake noise quantification of the seismic station record can be efficiently realized. The whole method is based on a CUDA programming model and a C language, cross-platform transplantation is easy, and the large-scale seismic network monitoring capability can be effectively improved.

The invention provides a ground vibration spectrum acceleration prediction method, a transfer learning method, equipment and a medium, a global model is obtained through first training by using a basic knowledge data set, the first training is evaluated by using a regional knowledge data set, and then a transfer model is obtained through second training by using the regional knowledge data set. And the second training is evaluated by adopting the regional knowledge data set, and the establishment method of the migration model retains the data features of the regional database and learns the difference between the global data set and the regional data set, so that the prediction precision of the model is ensured, and the generalization ability of the model is enhanced.

The invention relates to a tunnel earthquake vulnerability analysis method based on a fuzzy comprehensive evaluation method, and the method comprises the steps: selecting an optimal earthquake intensity index through the fuzzy comprehensive evaluation method, and building a tunnel structure earthquake vulnerability curve through the selected earthquake intensity index. According to the method, the influence of different tunnel burial depths can be considered in the selection process of the seismic oscillation intensity index IM; according to the method, index evaluation optimization can be performed in consideration of four aspects of correlation, effectiveness, practicability and benefit; according to the method, a fuzzy comprehensive evaluation method is adopted, and on the basis of a fuzzy relation comprehensive theory, qualitative factors are converted into quantitative factors for comprehensive evaluation; by using the method, the seismic oscillation intensity index IM can be effectively selected, the calculation result is relatively accurate, and the method has positive significance for accurately analyzing the seismic vulnerability of the underground structure.

The invention belongs to the technical field of underground engineering and computer-aided engineering analysis, and particularly relates to an anti-seismic safety collaborative analysis method for multi-modal data of proximity tunnel engineering. By integrating engineering geology, structural design, construction monitoring and multi-level seismic oscillation data, a three-dimensional numerical model fusing geology and structural information is constructed. Firstly, refined simulation of the whole construction process and the operation static load is carried out, and a reference mechanical state is obtained; carrying out multi-task condition earthquake dynamic time history analysis on the basis, dynamically capturing dynamic response of surrounding rock and a structure, carrying out collaborative interpretation on static and dynamic analysis results, emphatically analyzing spatio-temporal evolution and connectivity risks of a tunnel anchor and an adjacent highway tunnel surrounding rock plastic zone, and extracting a plurality of quantitative collaborative indexes; and an interactive analysis report integrating a three-dimensional visual scene, a multi-dimensional comparison chart and a rule base-based safety interpretation conclusion is automatically generated, and systematic decision support is provided for seismic design, construction control and safety evaluation of proximity projects.

The invention discloses an intelligent anti-seismic structure optimization design method and system for a high-rise building, and relates to the technical field of anti-seismic design of the high-rise building. A working condition database considering multidirectional seismic oscillation and soil-structure interaction is established in combination with seismic oscillation time history and site investigation parameters; constructing a structure model on the BIM platform, and importing frequency characteristics and load to generate a preliminary design; an inter-story displacement angle, a story acceleration, a plastic rotation angle and an energy dissipation ratio index are set in the model, an anti-seismic performance comprehensive function is constructed, constraints are set according to a standard limit value, the structure model is converted into an optimizable problem, and optimal design is achieved by iteratively calling a working condition database and automatically correcting key component parameters and damping arrangement. According to the method disclosed by the invention, the structural optimization design of the high-rise building under the multidirectional earthquake action is realized by establishing an earthquake working condition database and parameterizing structural modeling and performance function constraint.

The invention discloses a multi-frequency-band preprocessing machine learning seismic oscillation data denoising method, relates to the technical field of seismic signal processing, and solves the problems that noise and effective signals are aliasing, accurate recognition is difficult and noise remains due to the fact that seismic data cannot be effectively denoised in an existing method. The adopted seismic data de-noising network has a good de-noising effect on noise in a full frequency range, the noise can be effectively separated from effective signals, the effective signals and interference noise can be automatically distinguished through the network, the situation that the effective signals are mistakenly recognized as noise and filtered out is avoided, the two sub-modules are combined together, and the noise reduction efficiency is improved. According to the method, more details can be extracted, the denoising effect is improved, and a good denoising effect is achieved in actually measured seismic data.

The invention provides a physical information long-short-term memory network site seismic response prediction method based on kinematics derivative constraint and data folding. The method comprises the following steps: collecting and preprocessing bedrock and ground surface seismic oscillation data; displacement, speed and acceleration supervision labels are constructed through surface acceleration integration; constructing a long-short-term memory network containing a data folding and unfolding module; physical constraint loss is constructed by utilizing kinematics derivative relations between displacement and speed and between speed and acceleration, and a network is trained by combining an adaptive weight strategy; and outputting earth surface displacement, speed and acceleration time history by adopting the trained network. According to the method, under the condition that constitutive parameters of a soil layer are not explicitly given, physical consistency constraint can be applied to the field seismic response prediction process, the long-time program train training burden is reduced through sequence folding processing, and the method is suitable for field seismic response prediction.

The invention discloses a method for generating a post-earthquake seismic oscillation parameter field in a peripheral area of a railway by considering a topographic site, which can consider the influence of topographic features on seismic oscillation, improve the estimation precision of the post-earthquake seismic oscillation parameter field and provide technical support for post-earthquake inspection and driving order recovery. Meanwhile, railway workers can carry out targeted field inspection according to the mileage range, the inspection range is reduced, the emergency disposal time is shortened, the road network post-earthquake emergency disposal capacity is improved, the post-earthquake loss is reduced, and the railway transportation safety is guaranteed; moreover, the calculation work can be completed before the earthquake occurs, the calculation amount is relatively small after the earthquake occurs, and the actual demand of quick response after the earthquake of the railway can be met; besides, earthquake rapid report and station observation data from an earthquake station network center are comprehensively applied, information of a railway self-built station is fused, information utilization is comprehensive, and meanwhile, earthquake oscillation around the railway is better reflected.

The invention discloses a physical simulation method and device for seismic response certainty of an urban underground rail transit network, and the method comprises the steps: constructing a mixed seismic source model based on the active fault parameters and kinematic parameters of a target region, the seismic source model integrates a low-wavenumber deterministic slip component and a high-wavenumber random slip component on a fault fracture surface to generate a broadband seismic wave field source reflecting the physical process of a seismic source; the constructed seismic source model is used as input, a regional crustal velocity structure model is combined, propagation of seismic waves in a layered geological medium is simulated through a frequency-wavenumber domain method, and a seismic oscillation space-time field is obtained through calculation; and establishing a finite element model of the urban underground rail transit network, applying the seismic oscillation time-space field as non-consistent seismic oscillation input to the finite element model, and solving through dynamic time-history analysis to obtain the dynamic response of the whole underground rail transit network in the earthquake process. According to the invention, a complete physical chain from seismic source fracture to structural response can be reproduced.

The invention relates to a physical-data-driven sequence type seismic oscillation generation method. The method comprises the following steps: acquiring a historical seismic record; constructing a main earthquake ground motion random field model based on the physical mechanism of the ground motion field; the physical mechanism comprises a seismic source, a propagation path and a local site model; obtaining main earthquake parameters based on historical earthquake records according to the main earthquake ground motion random field model; the main earthquake parameter is used for predicting an unknown main earthquake seismic record according to a main earthquake seismic oscillation random field model to obtain a main earthquake seismic oscillation time history; and constructing an aftershock seismic oscillation generation model based on a conditional generative adversarial network model according to the main seismic oscillation time history to realize prediction of a seismic oscillation field. According to the method, the parameters of the main earthquake are generated based on the earthquake motion field of the physical mechanism, the time history of the main earthquake is obtained, the aftershock prediction model is constructed according to the conditional generative adversarial network, the physical mechanism model is combined with artificial intelligence, the model prediction fitness and accuracy are improved, the aftershock is predicted, the prediction effect is improved, complex calculation is avoided, and the model construction efficiency is improved.

The invention discloses a permanent displacement-containing near-source seismic oscillation synthesis method based on an equivalent pulse model, and the method comprises the steps: obtaining a permanent displacement time history of a seismic oscillation low-frequency part under different earthquake magnitude conditions through employing the permanent displacement characteristics of the equivalent pulse model and combining with a formula between different earthquake magnitudes and fault displacement amounts; and finally, according to near-source seismic oscillation characteristics, synthesizing near-source seismic oscillation capable of representing permanent displacement under different seismic magnitude conditions. The seismic oscillation obtained through the synthesis method can meet the requirements for the seismic oscillation attenuation characteristic and the acceleration peak value of an engineering site area, and can also reflect permanent displacement and near-field strong vibration caused by fracture and dislocation at the same time; according to the seismic oscillation obtained by the synthesis method, the seismic oscillation duration can be adjusted, so that time and cost are saved for subsequent related calculation and analysis.

A method for seismic fragility analysis of a shield tunnel considering surface surcharge effects includes the steps of: determining mechanical property parameters of tunnel materials and physical-mechanical parameters of soil layers; investigating case studies of surface surcharge to define surface surcharge scenarios; selecting seismic waves and performing one-dimensional equivalent linear site response analysis on soil conditions; establishing a dynamic finite element numerical model of a soil-tunnel system considering surface surcharge; defining ground motion intensity measures (IM), tunnel damage measures (DM), and damage states (DS); and establishing probabilistic seismic demand models for the tunnel under various surface surcharge effects. Based on key parameters, seismic fragility curves for tunnel structures under surface surcharge effects are established. Through a nonlinear incremental dynamic analysis method, this method establishes the finite element numerical model of the soil-tunnel system, allowing for quantitative assessment of tunnel seismic fragility and seismic performance under various surface surcharge effects.

The invention discloses a multi-source wave velocity structure fusion method, which comprises the following steps: acquiring original data sources including a large-range wave velocity structure data set covering the range of an engineering structure, an earth surface geological lithology distribution diagram and engineering site drilling exploration information; for the earth surface geological lithology distribution map, classifying rocks through image recognition, and setting a wave velocity based on rock categories; for the remaining original data sources, outliers are removed through data cleaning and standardization processing so as to determine corresponding wave velocities; according to the wave velocity determined based on engineering site drilling exploration information, a transition area is additionally arranged around a drilling point to convert the one-dimensional wave velocity into the three-dimensional wave velocity; performing data enhancement on the three-dimensional wave velocity corresponding to each original data source through an interpolation method; and carrying out weight fusion on various wave velocities after data enhancement to obtain a fused wave velocity structure. According to the method, the modeling precision and efficiency of the wave velocity structure are improved, so that the wave velocity structure can be matched with broadband seismic oscillation numerical simulation of the required calculation frequency.

The invention discloses a ground vibration simulation method, system and device and a medium, and relates to the field of seismic analysis, and the method comprises the steps: obtaining a plurality of seismic oscillation records; performing data filling on each seismic oscillation record by adopting a random finite fault method to obtain a plurality of sample seismic oscillation records; determining a plurality of condition parameters of each sample seismic oscillation record to obtain a multi-label vector of each sample seismic oscillation record; constructing a seismic oscillation simulation model based on the conditional denoising diffusion probability model, each sample seismic oscillation record and the multi-label vector of each sample seismic oscillation record; and carrying out seismic oscillation simulation under different seismic scenes based on the seismic oscillation simulation model. According to the invention, the complexity of the ground motion simulation model is reduced, and the precision of ground motion simulation is improved at the same time.

The invention discloses a site characteristic and displacement loading-based on-bridge ballastless track seamless track response simulation method under an earthquake. The method comprises the following steps: S1, constructing a site soil layer model containing a non-uniform soil layer; s2, inputting transverse and vertical seismic waves at the boundary of the field soil layer model at the same time, and simulating dual-path seismic oscillation transmission; s3, extracting a three-way displacement time history of surface nodes of the field soil layer model; and S4, inputting the three-way displacement time history into a bridge-track coupling model, and obtaining the dynamic response and damage state of the track structure. According to the method, the amplification and attenuation effects of a real site on seismic oscillation can be simulated, and the simulation precision of a real seismic situation is improved, so that the prediction capability of local failure and residual deformation of the ballastless track under a strong earthquake is improved.

The invention provides a seismic intensity field prediction method and system and electronic equipment, and the method comprises the steps: obtaining the seismic data of each station according to the triggering sequence of each station, determining the resultant acceleration sequence and the resultant speed sequence of each station according to the seismic data of each station, and obtaining the seismic intensity field of each station according to the resultant acceleration sequence and the resultant speed sequence. Determining a seismic oscillation energy characteristic parameter and a seismic oscillation amplitude characteristic parameter of each station according to the resultant acceleration sequence and the resultant speed sequence of each station, and determining a characteristic pattern sequence of the station network according to the seismic oscillation energy characteristic parameter and the seismic oscillation amplitude characteristic parameter of each station, and inputting the feature map sequence of the station network into a seismic intensity field prediction model, and performing prediction by the seismic intensity field prediction model to obtain a seismic intensity field prediction result. The seismic intensity field prediction accuracy is improved, and the prediction complexity is reduced.

The invention provides a roller compacted concrete dam based on prestress seismic resistance and a construction method thereof. The roller compacted concrete dam comprises a dam body, branch pipes, prestressed steel bars, top anchorage devices and bottom anchorage devices. The dam body comprises a plurality of dam body units formed by layered pouring in the height direction; the branch pipe is embedded in the dam body during dam body pouring construction, and a mounting hole channel is formed in the branch pipe; the prestressed reinforcements penetrate through the mounting hole channels; the top anchorage device and the bottom anchorage device are connected with the two ends of the prestressed reinforcement correspondingly so as to be suitable for conducting prestressed tensioning and anchoring on the prestressed reinforcement. Prestress tensioning is conducted on the dam body through the prestressed steel bars, an active prestress area can be formed, the tensile stress caused by seismic oscillation is effectively eliminated, and the anti-seismic stability and safety of the dam body are remarkably enhanced; the installation of the prestressed reinforcements is realized by presetting the branch pipes, so that the construction efficiency can be greatly improved, and the damage to the internal structure of the concrete in the construction process is reduced.

The utility model discloses an electrostatic induction pendulum for earthquake monitoring and early warning based on electrostatic induction. The device comprises a pendulum and an electrostatic induction sensor, and tiny potential changes can be detected in the swinging process. As a core component, the electrostatic induction sensor consists of the following key parts: a weight module, a connecting layer I, an electrode layer, a connecting layer II and an electrostatic interaction layer. Wherein the weight module provides necessary mass so as to ensure the dynamic characteristics of the pendulum; the first connecting layer is used for fixing the connection between the weight module and the electrode layer; the electrode layer is responsible for detecting electrostatic induction signals generated by pendulum motion and converting the signals into measurable potential change; the second connecting layer is used for fixing the electrode layer and the electrostatic interaction layer; the material of the electrostatic interaction layer carries charges, and the electrostatic induction signal of the electrode layer is enhanced in the earthquake monitoring and early warning process. Through the design, the device can realize high-sensitivity monitoring of earthquake precursor, and can capture fine ground movement caused by earthquake waves. In combination with a data acquisition system and a machine learning algorithm, the device can analyze the signals in real time and automatically send early warning information to related departments and individuals when an abnormal vibration mode is detected, so that precious time is won for taking preventive measures.

The application discloses a main aftershock induced slope slip prediction method based on multi-parameter regression, aims to utilize a large amount of ground motion data and a Newmark rigid block method to construct an explicit expression for predicting permanent slip displacement of a slope under the action of a main aftershock from peak ground acceleration, peak velocity and slope yield acceleration. The method comprises the following steps: step 1, selecting ground motion data from a ground motion database NGA-West2 and calculating each ground motion parameter and the slope slip displacement under different slope yield accelerations; step 2, identifying optimal ground motion parameters according to effectiveness criteria and applicability criteria; step 3, obtaining a plurality of prediction models through optimal parameters and a multi-parameter nonlinear regression analysis method and then testing the prediction performance to determine a final slip prediction model; and step 4, predicting the permanent slip displacement of the slope under a given seismic scenario and slope condition. Based on the method, the application develops and discloses a main aftershock induced slope slip prediction model with good accuracy, universality and practicability, and has certain guiding significance for slope stability evaluation and seismic design under the action of a main aftershock.

The present invention provides a numerical simulation evaluation method for the mechanical properties of an undersea tunnel under earthquake action, which relates to the field of undersea tunnel damage technology. The specific steps include: systematically collecting parameters such as the geometric dimensions and material properties of the tunnel; using finite element analysis to establish a three-dimensional geometric model to perform numerical simulations of static and dynamic responses; constructing static and dynamic test models, training them through expert-assessed bearing capacity labels to obtain more accurate static and dynamic bearing capacities; performing data processing on environmental factors such as soil strength, groundwater level, and temperature changes, generating correction coefficients to correct bearing capacity values; and generating comprehensive coefficients by calculating static and dynamic stability coefficients to evaluate the damage state of the undersea tunnel. The present invention provides a scientific basis for seismic design, accurately reflects the damage state of the tunnel under the most unfavorable earthquake motion, and comprehensively considers the influence of environmental factors on tunnel damage, significantly improving the accuracy and reliability of the evaluation.

The present application relates to a kind of assembled frame structure earthquake response prediction algorithm based on LSTM algorithm, by establishing full-scale structure model and using ABAQUS to carry out nonlinear time-history analysis, obtain ground motion and inter-story displacement response data, construct structure earthquake response database.Based on the numerical simulation result, establish deep learning architecture, by the sensitivity study of window length, hidden layer and training sample size, use R and RMSE such as index to evaluate model performance, and select the model with minimum validation loss as the final prediction model.In the prediction phase, input any ground motion record can quickly generate complete inter-story displacement time-history through recursive slicing and step-by-step updating mechanism, so as to realize the efficient estimation of aluminum alloy foam concrete structure earthquake response.The present application can replace the high-cost iterative calculation of traditional finite element analysis, and provide fast and reliable decision support for regional seismic risk assessment, structure safety determination and aluminum alloy foam concrete structure seismic design.