39 results about "Soil dynamics" patented technology

The invention relates to the technical field of soil monitoring and data analysis, and discloses a soil carbon and nitrogen content dynamic prediction method based on deep learning. The method comprises the following steps: acquiring soil monitoring data from an environment monitoring platform, performing dimension reduction by using a multi-layer perceptron model to obtain core features, and dividing a dynamic monitoring data set according to the core features; taking the data set as input, and constructing an initial prediction model by using a time convolutional network; and constructing a meteorological factor library and an influence map, replacing an initial model time node, and obtaining a climatic factor node prediction model through cross validation. And performing regression fitting and cross validation verification by using a Gaussian process, and constructing a soil dynamic prediction model. According to the method, through multi-step data processing and model construction, the influence of soil data characteristics and meteorological factors is effectively mined, the dynamic change of the soil carbon and nitrogen content can be accurately predicted, and powerful support is provided for the fields of precision agriculture, environmental protection and the like.

The invention discloses a multivariate monitoring data fusion method and system for a slope tunnel model test, particularly relates to the technical field of geotechnical engineering physical model test, and aims to solve the problem that dynamic stress waves in an existing model test integrating static and dynamic measurement cause static monitoring signal distortion and further influence the model state evaluation accuracy. Coupling interference in static signals is identified by synchronously collecting dynamic excitation and static response signals; obtaining signal samples before and after a model state sudden change event to perform frequency domain comparative analysis, identifying characteristic frequency components related to sudden change, and evaluating a coupling interference dominant frequency band; separating an effective static response component from the original static signal based on the frequency band; and finally, fusing the effective component with a soil dynamic parameter derived from dynamic excitation to generate comprehensive stability evaluation data. Dynamic interference is effectively suppressed, the authenticity of static signals is improved, and the reliability of model stability state evaluation is improved.

The invention provides a simulation analysis method and system for tunnel structure response under the action of multi-source power. The simulation analysis method comprises the following steps: S1, constructing a numerical solution system for coupling load analysis; s2, constructing a track-tunnel-soil body implicit dynamic analysis finite element model based on the numerical solution system, and forming a structure-soil body dynamic coupling system; s3, setting a plurality of types of working conditions according to preset requirements, wherein the working conditions comprise actual measurement and simulation scenes of a vehicle body and an earthquake; s4, analyzing a structure response result to obtain a response rule under the action of multi-source power; a track-tunnel-soil body three-dimensional finite element implicit dynamic analysis model is constructed, key technologies such as static-dynamic ground stress balance conversion, viscoelastic artificial boundaries, seismic oscillation equivalent node force input and train vibration function loading are comprehensively adopted, and a reliable simulation system of tunnel structure response under the multi-source dynamic effect is established.

The invention discloses a vegetation and soil coupling effect evaluation method and system based on big data, and the method comprises the steps: collecting experiment data and monitoring data of a preset region, and carrying out the preprocessing of the experiment data and the monitoring data; performing multi-dimensional coupling correlation feature extraction on the experimental data and the monitoring data to obtain a coupling feature set, and performing space-air-ground collaborative coupling evaluation on the monitoring data through the coupling feature set to obtain an original coupling degree; performing disturbance evaluation on the soil data according to a soil dynamic adjustment decision to obtain a disturbance coupling degree, and performing coupling mechanism decomposition based on deep learning according to the original coupling degree and the disturbance coupling degree to obtain a coupling difference mechanism; and constructing a vegetation and soil coupling effect evaluation model according to the disturbance coupling effect and the coupling difference mechanism, inputting to-be-evaluated data into the vegetation and soil coupling effect evaluation model, and outputting an evaluation result.

The invention discloses a pile-soil coupling loss prediction method based on soil layer quantification and a neural network. The method comprises the following steps: firstly, through parameterized finite element-infinite element coupling numerical simulation, extracting a pile-soil coupling loss quantitative index-transfer function amplitude ratio; converting the multi-layer soil body distribution information into standardized soil layer distribution characteristic parameters through a normalized coordinate system; then, a neural network model is constructed, pile body parameters, load parameters, characteristic frequency points and soil layer distribution characteristic parameters serve as input, and a transfer function amplitude ratio serves as an output target for training; and finally, rapid and accurate prediction of the pile-soil coupling loss is realized through the trained model. According to the method, effective quantification of complex soil layer space distribution is innovatively realized, and the problems of insufficient precision and low efficiency of a traditional method in pile-soil dynamic coupling loss prediction are solved.

The invention belongs to the technical field of ground source heat operation management, and particularly discloses an intelligent operation management system for geothermal energy in a severe cold area. The system comprises an acquired data verification module, a soil dynamic analysis module, a thermal imbalance risk prediction module and a control priority determination module. According to the method, geothermal operation data are collected and verified in real time, key indexes such as heating power, soil accumulated heat taking capacity and heat recovery rate are calculated, meteorological prediction data are combined to drive a soil heat transfer model to conduct prospective simulation, and a heat imbalance risk index is output. And the control priority of the heat supply quality and the soil heat imbalance is dynamically determined and output based on the risk index and the change trend thereof, so that the heat recovery capability of the soil is effectively maintained while the heat supply requirement is met, and meanwhile, the priority management direction between the heat supply quality guarantee and the soil heat imbalance prevention and control is defined; and therefore, effective balance is realized between maintaining the heating demand of the user and protecting the sustainability of terrestrial heat.

This application discloses a method, apparatus, device, and storage medium for predicting the dynamic strength of lightweight soil using bubble-based methods. The method includes: determining lightweight soil sample information; inputting the lightweight soil sample information into a preset dynamic strength prediction model; and performing dynamic strength prediction processing on the lightweight soil sample information based on the dynamic strength prediction model to obtain lightweight soil dynamic strength data. The dynamic strength prediction model is trained using a preset number of dynamic strength corrosion resistance coefficient prediction formulas under different environmental factors. This application relates to the field of concrete strength prediction technology. By using a dynamic strength prediction model trained with a preset number of dynamic strength corrosion resistance coefficient prediction formulas under different environmental factors to predict the dynamic strength of lightweight soil samples, the accuracy of the dynamic strength prediction data for lightweight soil samples is improved by considering different environmental factors.

The invention discloses a covering layer foundation soil dynamic pore pressure-deformation indoor triaxial test method for reflecting an earthquake loading process, and belongs to the field of geotechnical engineering and earthquake engineering. Firstly, a numerical geometric model is created, and soil physical and mechanical parameters are input; secondly, carrying out power time history response analysis, outputting seismic dynamic stress response time histories of soil mass units at different positions and different depths in a numerical simulation result, and converting the seismic dynamic stress response time histories into test control loads; thirdly, carrying out an indoor dynamic test, loading a test control load, and collecting dynamic response data of the soil body under the earthquake action; and finally, on the basis of the dynamic response data, determining dynamic test results of all units of the covering layer by adopting an interpolation method according to stress states and dynamic strain amplitude interpolation, and completing dynamic characteristic analysis. According to the method, excessive simplification and blind test of a traditional test can be avoided, the authenticity and accuracy of the foundation soil dynamic test are remarkably improved, and the method is suitable for accurate evaluation of the dynamic characteristics of the ultra-deep soft covering layer foundation soil.

The invention discloses a paddy wheel mud soil dynamic response analysis method and system based on multi-sensor fusion, and relates to the technical field of agricultural information perception, and the method comprises the steps: collecting mud soil response data from different depths and orientations; processing the mud soil response data based on a multilayer information fusion network model to obtain a high-correlation response feature subset, obtaining a soil physical field excitation sequence under a multilayer coupling boundary condition based on feature subset inversion, and performing multi-time-domain parallel response analysis on a target area; obtaining a stress-pore pressure coupling peak value region in response output and spatial distribution thereof, and constructing a mud soil weak response fingerprint spectrum; and finally, proposing optimization suggestions for the mud wheel path, the operation rhythm and the pressure parameters based on the atlas, and realizing dynamic pre-response evaluation and decision support before the mud wheel operation of the paddy field. The method has the advantages of being high in coupling recognition precision, high in risk perception capability, intelligent in operation parameter regulation and control and the like, and is suitable for an intelligent agricultural equipment system and a precise paddy field management scene.

The invention discloses a soil nonlinear site seismic shear stress determination method, which comprises the following steps of: firstly, constructing a site stratified soil simplified model, and fitting a soil dynamic curve; then, the equal-amplitude cyclic stress of the seismic oscillation waves is vertically incident from the bottom of the site bedrock; constructing a transfer matrix to obtain an amplitude matrix of each soil layer, solving to obtain seismic shear stress of each soil layer, calculating normalized dynamic shear strain of each soil layer by using a time-domain dynamic shear strain component, substituting the normalized dynamic shear strain into a soil dynamic curve, determining new dynamic shear modulus and damping ratio of each soil layer, and calculating the seismic shear stress of each soil layer. Iteration calculation of the new dynamic shear modulus and the damping ratio is repeated, the dynamic shear modulus and the damping ratio output after iteration are called as the equivalent shear modulus and the equivalent damping ratio, and the seismic shear stress of each soil layer of a non-linear field of a soil body is solved when seismic waves are vertically incident, so that a foundation is provided for earth and rockfill dam seismic response research; and reference is provided for site selection of a proposed project, design of a site anti-liquefaction scheme and the like.

The application relates to the technical field of power system risk assessment, and discloses a power tower risk grade evaluation method based on operation condition analysis. The method first investigates the tower distribution and geological environment through a geographic information system, collects meteorological, soil and physical parameters, secondly studies the frost heaving mechanism and establishes a mechanical and response model to deduce the long-term deformation law of the structure, then constructs a deformation early warning system by using a multidimensional sensor network and an intelligent algorithm to realize data cleaning, filtering and automatic alarm, and finally defines a multistage safety risk standard to generate a differentiated operation and maintenance decision scheme based on the monitoring results. The application realizes quantitative analysis of the influence of frost heaving by fusing climate characteristics and soil dynamics mechanism, effectively makes up for the deficiency of artificial inspection in timeliness by combining high-precision real-time monitoring, improves the evaluation accuracy and reliability of power facilities in extremely cold regions, and guarantees the safe and stable operation of the power system in complex geological environments.

The application belongs to the technical field of electric digital data processing, and particularly relates to a digital processing system for adaptive depth of a land leveler. The system acquires a tool spindle torque signal sequence and a rack three-axis acceleration signal sequence in real time, extracts a frequency domain feature vector through fast Fourier transform of a sliding window, and inputs a classifier to output a soil dynamics parameter set. The dynamics parameter set is substituted into a state space equation, a torque fluctuation variance minimization and an effective soil breaking volume maximization are taken as double objective functions, a maximum response rate of a hydraulic system and an allowable maximum structural stress are combined to construct a nonlinear programming model. A sequential quadratic programming algorithm is called to iteratively solve and output an optimal loosening depth setting value, which is converted into a hydraulic proportional valve current control sequence through trajectory interpolation. The application suppresses depth control oscillation during operation of soft and hard alternating soil, reduces transient impact load of a transmission system, and balances loosening operation power consumption and soil breaking quality.

The application provides a method for analyzing variation rules of deep filling soil dynamic compaction reinforcement depth and surface wave velocity. The method is as follows: selecting at least four test areas in deep filling soil site, carrying out dynamic compaction construction with different energy levels, the dynamic compaction energy levels include low, medium, high and super high energy levels, and respectively carrying out heavy dynamic penetration test and multi-channel transient surface wave test before and after dynamic compaction of each area; determining the first reinforcement depth H1 and the second reinforcement depth H2 through the dynamic penetration blow count growth rate; and counting the dynamic penetration blow counts and corresponding surface wave velocities before and after dynamic compaction of the same position in different test areas, establishing the relationship curve between the surface wave velocity of the filling soil and the dynamic penetration blow count, and determining the judgment standard of the filling soil density in the site. The application provides reliable theoretical basis and technical guidance for obtaining key mechanical indexes of deep filling soil and reasonably determining the dynamic compaction reinforcement depth, lays a solid foundation for design and construction of similar projects, and has wide application prospect.

The invention relates to the technical field of online monitoring, in particular to an intelligent fill deformation sensing system and method based on hydraulic characteristics of collapsible loess, and the method comprises the steps: evaluating the brittleness of a loess structure based on characteristic data of collapsible loess, and obtaining a brittleness index of the loess structure; constructing a collapsibility risk assessment model, and importing the loess structure brittleness index, hydraulic characteristic data in the fill body and soil dynamic response data in the deformation process of the fill body into the collapsibility risk assessment model to obtain a collapsibility risk index; judging whether to position a water source intrusion point according to the collapse risk index, constructing a water source intrusion positioning model, and tracing the water source intrusion point; and visualizing the collapse risk index and the positioned coordinates of the water source invasion point to a fill early warning platform in real time. The problems that in the prior art, only the deformation consequence can be passively dealt with, an early predictive intervention strategy is lacked, and early quantitative early warning and deformation intervention of the collapse risk cannot be achieved are solved.

The application discloses a paddy field wheel mud soil dynamic response analysis method and system based on multi-sensor fusion, relates to the technical field of agricultural information perception, and collects mud soil response data from different depths and directions; high correlation response feature subsets are obtained by processing mud soil response data based on a multi-layer information fusion network model, a soil physical field excitation sequence under multi-layer coupled boundary conditions is obtained by inversion based on the feature subsets, multi-time domain parallel response analysis is carried out on a target region; a stress-pore pressure coupling peak value region and its spatial distribution in response output are obtained, and a mud soil weak response fingerprint spectrum is constructed; finally, optimization suggestions are proposed for wheel mud paths, operation rhythms and pressure parameters based on the spectrum, dynamic pre-response evaluation and decision support before paddy field wheel mud operation are realized; the method has the advantages of high coupling identification precision, strong risk perception capability and intelligent operation parameter regulation, and is suitable for intelligent agricultural equipment systems and precise paddy field management scenes.

The application provides a rockfill dam seismic response randomness analysis method based on a test database, and belongs to the technical field of hydraulic engineering. First, a coarse-grained soil dynamic property database Geo-Gravel is constructed, and a deep learning model based on given physical parameters to generate corresponding dynamic parameters is trained; second, a finite element model and a material parameter random field are constructed, and the material parameter random field is assigned to the finite element model; third, the dam body dynamic response is obtained through calculation by using a finite element software; finally, the extreme values of the displacement and acceleration of the dam body dynamic response and the probability distribution thereof are counted, and the statistical results are analyzed to quantify the influence of the material physical parameter randomness on the dam body dynamic response. The application can effectively reduce the test cost, truly reflect the spatial variation characteristics of the rockfill material, and show through the probability distribution analysis that the parameter randomness significantly influences the dynamic response result, and the dispersion degree and the variation coefficient are positively correlated, thereby providing a reliable basis for seismic design.

The application belongs to the technical field of ground source heat operation management, and specifically discloses an intelligent operation management system for geothermal energy in severe cold regions. The system comprises a data acquisition and verification module, a soil dynamic analysis module, a thermal imbalance risk prediction module and a control priority determination module. The application collects and verifies geothermal operation data in real time, calculates key indicators such as heating power, cumulative soil heat extraction and heat recovery rate, drives a soil heat transfer model in combination with meteorological prediction data to perform forward-looking simulation, and outputs a thermal imbalance risk index. Based on the risk index and its change trend, the control priority of heating quality and soil thermal imbalance is dynamically determined and output, so that the soil heat recovery capacity is effectively maintained while meeting the heating demand, and the priority management direction between the heating quality guarantee and the soil thermal imbalance prevention and control is clarified, thereby achieving effective balance between maintaining user heating demand and protecting geothermal sustainability.

The application discloses a kind of in-situ dynamic test bench of ground soil vibration subsidence and test method thereof, including vibration table system and sensor in ground soil, water injection trench around ground soil.In-situ test site is vibrated by vibration table to the underlying ground soil body and applies horizontal vibration load, and the dynamic response of ground soil is measured by sensor buried in different positions, reflecting the vibration subsidence deformation of soil body.At present, soil vibration subsidence test includes dynamic simple shear, dynamic triaxial, dynamic torsional shear indoor test method, but there is no mature method for in-situ vibration subsidence test of ground soil.Through the vibration effect of in-situ soil column by vibrator, a method for testing the dynamic response and vibration subsidence deformation of ground soil is proposed, filling the soil dynamics test method.The acceleration response and vibration subsidence deformation of ground soil under in-situ conditions are determined by the application, which has good practical significance for disaster prevention.

The invention discloses a method for determining a dynamic shear modulus ratio curve and a damping ratio curve of a soil body under different strain amplitudes, and relates to the technical field of indoor soil body dynamic characteristic testing. Comprising the following steps: acquiring a soil sample of an engineering site, dividing experimental points according to a strain interval, respectively carrying out an indoor resonant column experiment and a dynamic triaxial experiment, obtaining dynamic shear moduli and damping ratios of the experimental points through the resonant column experiment, and obtaining hysteretic curves of the experimental points through the dynamic triaxial experiment. Performing shape regularity index and positive and negative loading path stress-strain curve coincidence degree evaluation on the hysteretic curve of each experimental point, performing classified calculation to obtain the damping ratio of the experimental point, obtaining the dynamic shear modulus of the experimental point based on the stress-strain curve, setting a dynamic shear modulus ratio prediction function and a damping ratio prediction function, and calculating the dynamic shear modulus of the experimental point. And determining a shear modulus ratio curve and a damping ratio curve by combining the data of the resonant column experiment and the dynamic triaxial experiment. Different types of damping ratio calculation formulas are matched according to the evaluation result, and accurate calculation of the damping ratio is achieved.

GeoSoilX is a handheld soil sensor device that integrates 10 soil quality parameters in one Internet of Things (IoT)-based unit with the support of artificial intelligence processing at the device level (Edge AI) for automatic and real-time measurements in the field. The ten parameters include Nitrogen, Phosphorus, Potassium, moisture, pH, electrical conductivity, temperature, salinity, soil color, and soil compaction level. Existing soil diagnostic systems still rely on the use of separate tools, non-uniform data acquisition processes, and do not have a centralized soil data history to monitor long-term soil dynamics, thereby reducing efficiency, data consistency, and the accuracy of soil management decisions. The GeoSoilX invention was developed to overcome these limitations through ten-in-one measurements using a single handheld device that produces more consistent data output across time and measurement locations.This device is connected to a mobile phone application and a web platform as a user interface to display measurement results and manage historical data storage centrally in a data center. Centralized storage enables continuous monitoring of soil conditions and tracking of soil condition records as a basis for data-driven decision-making in precision agriculture and plantation ecosystems, particularly to support site- and commodity-specific soil and crop management and the implementation of adaptive and sustainable nutrient intervention management.

The present invention discloses a method for calculating the dynamic residual deformation of saturated soil and an implementation method thereof; it relates to the field of dynamic characteristics of geotechnical engineering, and the calculation method comprises: S1, establishing a calculation model for the dynamic residual deformation of saturated soil; S2, obtaining existing original test data; S3, processing the test data to obtain fitting data; S4, training and fitting the calculation model to obtain a trained calculation model; S5, calculating the dynamic residual deformation of saturated soil according to the calculation model; the implementation method comprises: S1, establishing a worksheet in Excel; S2, inputting the calculation model for the dynamic residual deformation of saturated soil; S3, calculating the parameters of the sample after consolidation, the axial dynamic stress and axial dynamic strain; S4. Filter the data in step S3 and output them to the data processing worksheet; S5. In the data processing worksheet, calculate the residual shear strain and residual volume strain; S6. Use the regression analysis calculation formula to calculate the model parameters and the determination coefficient R to obtain the calculation model; S7. Use the calculation model to calculate the dynamic residual deformation of saturated soil; This application first improves the original saturated soil dynamic residual deformation calculation model, and then uses a large amount of data to fit the model so that the model conforms to the data obtained from the actual experiment. The model can be used to measure the relationship between the vibration cycle of the soil and the dynamic residual deformation.

The utility model discloses a novel fluidized soil dynamic fluidity testing device, which belongs to the field of civil engineering and comprises a support iron stand, a slurry cleaner, a transparent glass plate and a cylinder. The supporting iron frame comprises four vertical rods, four cross rods and a bottom plate, checks with the same size are engraved on the surface of the bottom plate, and the slurry cleaner comprises a push rod and an annular scraper. According to the utility model, the transparent glass plate at the bottom of the cylinder is rapidly drawn out at the test height, so that fluidized soil in the cylinder freely falls on the bottom plate, and the corresponding area is converted according to the number of grids occupied by the fluidized soil on the bottom plate, thereby obtaining the dynamic fluidity of the fluidized soil. The testing device disclosed by the utility model is simple in structure, convenient to operate and capable of simply, conveniently and effectively testing the dynamic fluidity of the fluidized soil.

The invention discloses a coarse-grained soil dynamic shear modulus and damping ratio prediction method based on an attention mechanism. The method comprises the following specific steps: step 1, constructing a coarse-grained soil test data set; step 2, constructing a GA-Net prediction model; 3, dividing the data set into a training set and a test set, inputting the training set into the GA-Net prediction model for training to obtain a trained GA-Net prediction model, and testing the trained GA-Net prediction model by using the test set to obtain a tested GA-Net prediction model; and step 4, inputting key parameters of the coarse-grained soil to be tested into the GA-Net prediction model after the test to obtain a group of dynamic shear moduli G and a group of damping ratios lambda. The method is high in prediction precision and high in prediction effect.

According to the multifunctional integrated PVC agricultural irrigation pipe system disclosed by the invention, soil humidity and various nutrient concentrations are continuously monitored in real time through the soil humidity sensor and the nutrient detection device, multi-dimensional soil information is provided, a reliable data foundation is laid for precise water and fertilizer regulation and control, and regulation and control errors caused by neglecting factors are avoided; besides, the control unit generates a comprehensive adjusting quantity by using a preset algorithm according to sensor feedback data and crop growth stage information, fully considers dynamic change of soil and requirements of crops at each stage, and solves the problem of lack of feedback adjusting mechanisms or single strategy in the prior art. The control unit can accurately control a water conveying runner and a fertilizer solution conveying runner valve, water and fertilizer waste is avoided, the utilization rate is increased, and crop growth is promoted; in addition, the system integrates all parts, is efficient in cooperation and rapid in information transmission, simplifies the production process, reduces the operation difficulty and management cost, and improves the agricultural production efficiency and benefits.

The application discloses a grassland degradation monitoring method based on remote sensing monitoring, comprising: acquiring multi-source remote sensing data; preprocessing the multi-source remote sensing data to obtain preprocessed remote sensing data; extracting multi-dimensional feature parameters based on the preprocessed remote sensing data to obtain a multi-dimensional feature parameter set; performing time sequence analysis on vegetation dynamic characteristics, soil dynamic characteristics and human disturbance characteristics by combining multi-time observation data through the multi-dimensional feature parameter set to construct a dynamic characteristic time sequence data set; performing deep fusion on spatial features and time sequence changes in the time sequence by using a convolutional neural network model according to the dynamic characteristic time sequence data set to generate a spatio-temporal fusion feature set; obtaining a degradation grade division result map according to the spatio-temporal fusion feature set; integrating multi-source remote sensing data based on the degradation grade division result map to obtain a refined grassland degradation evaluation result, and monitoring grassland degradation according to the evaluation result.

The application discloses a kind of overburden soil dynamic pore pressure-deformation indoor triaxial test methods reflecting seismic loading history, belong to geotechnical engineering and earthquake engineering field.First, create numerical geometric model, input soil physical and mechanical parameters;Second, carry out dynamic time-history response analysis, output the seismic stress response time-history of different positions, different depth soil units in numerical simulation results, and convert it into test control load;Third, carry out indoor dynamic test, load test control load, collect the dynamic response data of soil under the action of seismic motion;Finally, based on dynamic response data, using interpolation method, according to stress state and dynamic strain amplitude interpolation determines all units of overburden dynamic test results, completes dynamic characteristic analysis.The application can avoid the over-simplification and blind test of traditional test, significantly improve the authenticity and accuracy of foundation soil dynamic test, and is suitable for accurate evaluation of dynamic characteristics of super-deep soft overburden foundation soil.

The invention discloses a moraine soil dynamic compaction effect evaluation method based on a dynamic compaction method, and relates to the technical field of moraine soil compaction, and the moraine soil dynamic compaction effect evaluation method comprises the following steps: constructing a moraine soil foundation physical model, and simulating a dynamic compaction construction process according to the constructed moraine soil foundation physical model to obtain corresponding construction simulation parameters; comparing the obtained construction simulation parameters with actual construction process parameters to obtain a corresponding parameter comparison table; evaluating the compaction effect of the moraine soil in the dynamic compaction construction process based on the obtained parameter comparison table; the dynamic evolution process of particles in the moraine soil under the impact load and the influence of the particles on the overall compaction effect are determined, the microstructure change rule in the compaction process is revealed, and a scientific basis is provided for the moraine soil dynamic compaction reinforcement technology; the key process parameters influencing the compaction effect of the moraine soil accumulation body are identified and optimized by combining tests and numerical simulation, and an optimal reinforcement strategy aiming at the characteristics of moraine soil is provided.

The application discloses a shield tunnel-soil dynamic interaction simulation method based on OpenSees, and comprises the following steps: S1, setting boundary conditions, and establishing a tunnel-soil dynamic interaction finite element model; S2, performing gravity analysis on the tunnel-soil dynamic interaction finite element model; S3, performing zero-clearing processing on soil displacement; S4, adding shield tunnel segment, joint bolt and compression-resistant rubber gasket material unit and material information, and setting a contact surface between the tunnel and the soil; S5, binding a nonlinear beam unit based on a fiber section to the segment unit, and simulating nonlinear characteristics of the segment; S6, converting soil properties from linear elasticity to elastoplasticity; and S7, performing incremental dynamic analysis on the model, adopting an initial stress field of the soil as an initial state, and applying seismic excitation to the bottom of the model; and the application predicts and evaluates the anti-seismic capacity of the tunnel through the shield tunnel seismic response refined numerical modeling and calculation method.

The invention provides an anti-seismic performance evaluation method and device for a nuclear power plant, and relates to the technical field of anti-seismic performance evaluation, and the method comprises the steps: constructing a multi-element anti-seismic coupling analysis channel based on the soil dynamic characteristics of an area where a target nuclear power plant is located, a building anti-seismic response layer and a device anti-seismic response layer, comprising a soil-building response branch, a building-equipment response branch and an equipment-building feedback branch; and through the building anti-seismic response layer, the equipment anti-seismic response layer, the soil-building response branch, the building-equipment response branch and the equipment-building feedback branch, executing anti-seismic performance simulation evaluation of the target nuclear power station, and outputting comprehensive anti-seismic strength. Through the method, the technical problem of insufficient comprehensiveness and accuracy of anti-seismic performance evaluation caused by the fact that a traditional method cannot effectively process a complex coupling effect among soil, a building and equipment can be solved, more complete and accurate anti-seismic performance evaluation can be realized, and the accuracy, comprehensiveness and reliability of anti-seismic performance evaluation are remarkably improved.

This application discloses a method, device, and medium for evaluating the mobility of off-road vehicles based on a dynamic soil model, relating to the field of vehicle mobility evaluation technology. The method includes: calculating the soil cohesion modulus and soil friction modulus corresponding to the vehicle's speed using a dynamic soil bearing capacity model during each speed scan; performing iterative calculations of four-wheel vehicle dynamics and loads to obtain stable settlement and wheel load data; and further calculating the total vehicle resistance. Then, the hook traction force is determined using a dynamic soil shear model. Finally, dynamic constraint tests, comfort constraint tests, and hard passability constraint tests are performed using driver comfort indicators to determine a permissive maximum speed. The above-mentioned solution achieves off-road mobility evaluation that balances soil dynamics and occupant comfort, improving the authenticity and reliability of high-speed off-road mobility evaluation results.