64 results about "Soil dynamics" patented technology

The invention discloses a gas pipeline and subway safety distance optimization method based on numerical simulation, and relates to the technical field of subway tunnel safety, and the method comprises the steps: simulating gas pipeline explosion data through a KFX Exsim gas explosion model; establishing a fluid-solid coupling model, a soil dynamic model and a thermodynamic coupling model, and coupling the three models to obtain a multi-physics coupling model; based on a multi-physics field coupling model, performing decomposition and region division on a numerical simulation task in combination with a parallel computing framework, and simulating the influence of gas pipe explosion on the subway; based on a numerical simulation result, evaluating the safety of the tunnel under the action of the explosion load; based on a safety evaluation result, optimizing a safety distance between the gas pipeline and the tunnel; according to the method, the fluid-solid coupling model, the soil dynamic model and the thermodynamic coupling model are established and coupled to form a multi-physical field coupling model comprehensively covering the explosion environment, and accurate simulation of complex behaviors of the subway tunnel in the explosion environment is achieved.

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 relates to the technical field of civil engineering, in particular to a pile-soil dynamic response simulation test method which comprises the following steps: acquiring a soil body parameter, a pile body parameter and a construction parameter of a target engineering site; establishing a pile-soil power system generalization model according to a preset similarity ratio, and respectively determining a soil body parameter of the sand soil stratum, a pile body parameter of the simulation pile, and a first power loading parameter and a second power loading parameter of a loading system; preparing a pile-soil system according to the soil body parameters of the sand soil stratum and the pile body parameters of the simulation pile, controlling the pile-soil system to carry out vibration pile sinking and vibration pile pulling based on the first power loading parameter and the second power loading parameter, and monitoring test data in the vibration pile sinking and vibration pile pulling process, and analyzing to obtain a pile-soil dynamic response simulation analysis result. Therefore, the problems of tedious work, high cost and difficulty in accurate description of research on the dynamic response rule between the pile and the soil are solved, and the dynamic response rule between the pile and the soil under different conditions can be efficiently and accurately simulated.

The invention discloses a layered foundation construction optimization method based on dynamic loading and intelligent inversion, and relates to the technical field of intelligent geotechnical engineering. In order to solve the problem that comprehensive analysis and optimization design of multiple layers of soil bodies are difficult to carry out in the prior art, the invention provides the following technical scheme: the layered foundation construction optimization method based on dynamic loading and intelligent inversion is characterized by comprising the following steps: S1, applying a dynamic load on a known layer of soil body; s2, acquiring response data, including acceleration, displacement and stress, of the soil body under the action of the dynamic load through a sensor; s3, deducing the dynamic response of the lower-layer soil body by using an inversion algorithm based on the acquired response data; s4, analyzing dynamic response characteristics of each layer of soil body; and S5, optimizing the compactness and the elastic modulus of the soil layer. The method can improve the accuracy and efficiency of soil dynamic response analysis, is suitable for mechanical property optimization in complex foundation engineering, and has wide engineering application value.

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 relates to the technical field of soil tests, and provides a water content and soil dynamic sounding characteristic combined measuring device which comprises a sounding rod with a probe part; the insulating sleeve is arranged on the feeler lever and is positioned on one side far away from the probe part; the four conductive pieces are evenly arranged on the peripheral side of the insulating sleeve at intervals, the main body parts of the conductive pieces are located in the insulating sleeve, and one ends of the conductive pieces are used for making contact with the soil body. According to the technical scheme, the problems of poor durability, high test error, unknown test range and long test period of a water content measuring device in the existing test technology, and the problems of high cost, low test efficiency and the like caused by the fact that the original instrument needs to be greatly modified or cannot be repeatedly applied when the instrument is used for testing are solved. And the operation is relatively tedious in the application process.

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 relates to the technical field of road construction, and discloses a roadbed soil dynamic resilience modulus testing device which comprises an outer frame, a material gathering hopper arranged in the outer frame and a sample preparation mechanism arranged below the material gathering hopper. The material collecting hopper is in a conical hopper shape with a wide upper part and a narrow lower part; the bottom of the material collecting hopper is a circular discharge pipe orifice; and a valve unit is arranged at the bottom of the discharge pipe orifice. The sample preparation mechanism comprises a sample preparation cylinder arranged under the discharging pipe opening and a quantitative transfer unit located between the sample preparation cylinder and the discharging pipe opening, and the quantitative transfer unit is used for receiving a certain amount of materials and transferring the materials into the sample preparation cylinder. Through the structure, materials can be automatically added into the sample preparation cylinder, and the materials can be conveniently and gradually compacted layer by layer in the sample preparation cylinder, so that the density of a sample is more uniform, and the dynamic resilience modulus test result of roadbed soil is more accurate.

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 method for optimizing the safe distance between a gas pipeline and a subway based on numerical simulation, which relates to the field of subway tunnel safety technology, including: simulating gas pipeline explosion data through a KFX Exsim gas explosion model; establishing a fluid-solid coupling model, a soil dynamics model and a thermodynamic coupling model, and coupling the three to obtain a multi-physical field coupling model; based on the multi-physical field coupling model, combining a parallel computing framework to decompose and divide the numerical simulation tasks into regions, and simulating the impact of the gas pipe explosion on the subway; based on the numerical simulation results, evaluating the safety of the tunnel under the action of the explosion load; based on the safety evaluation results, optimizing the safe distance between the gas pipeline and the tunnel; the invention establishes a fluid-solid coupling model, a soil dynamics model and a thermodynamic coupling model, and couples the three to form a multi-physical field coupling model that comprehensively covers the explosion environment, thereby realizing an accurate simulation of the complex behavior of the subway tunnel under the explosion environment.

The invention provides a construction safety assessment method and system for a new building pile foundation along a subway in a soft soil area, and the method comprises the steps: building a numerical model of a pile foundation adjacent to an operating subway and a surrounding soil body, and obtaining the distribution of a stress field around the pile foundation; through data collection and equation fitting, a relation model of the dynamic shear modulus and the dynamic shear strain of the soil body around the pile foundation and the mechanical property parameters of the soil body of the soft soil is obtained; according to the relation model, a relation model between the soft soil dynamic stress and the static strength reduction rate is constructed; according to the relation model between the soft soil dynamic stress and the static strength reduction rate, a pile side resistance experience composition formula is combined, the pile foundation bearing capacity obtained after reduction is calculated, then the loss ratio of the pile foundation bearing capacity obtained after reduction is calculated, and therefore the construction safety rating of the newly-built building pile foundation along the subway is evaluated. According to the method, regular summary of the bearing capacity loss of the pile foundation in the soft soil area is achieved, and effective guidance and an optimized path are provided for planning and construction of newly-built buildings along subways in the soft soil area.

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 invention belongs to the technical field of soil monitoring, and particularly relates to a dynamic monitoring method for under-forest ecological cultivation soil. A soil dynamic monitoring device comprises a server platform, a client connected with the server platform, a LoRa base station connected with the server platform and a plurality of monitoring units connected with the server platform and the LoRa base station, and each monitoring unit comprises a case and a monitoring system; the monitoring system comprises an information acquisition module, an AI edge calculation module and an information transmission module. According to the under-forest ecological state soil dynamic monitoring method, when a mobile communication signal exists in an area, an AI edge calculation module communicates with a server platform through a mobile communication module; when there is no mobile communication signal in the located area, the AI edge calculation module communicates with the server platform through the LoRa communication module and the LoRa base station, thereby effectively avoiding the problems existing when information transmission is realized by independently relying on the mobile communication module, facilitating the development of under-forest ecological cultivation, and conforming to the actual situation of under-forest ecological cultivation.

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 invention provides a hydraulic reclamation silty soil dynamic compaction foundation quality detection method and system, and relates to the field of foundation quality detection.The method comprises the steps that a vibration detection assembly is arranged on a hydraulic reclamation silty soil dynamic compaction foundation to be detected; carrying out a vibration detection test, and collecting vibration detection data of the hydraulic reclamation silty soil dynamic compaction foundation to be detected; determining an in-situ detection test scheme and a Rayleigh wave detection test scheme according to the vibration detection data of the to-be-detected hydraulic fill silty soil dynamic compaction foundation; according to the in-situ detection test scheme, an in-situ detection test is carried out on the hydraulic reclamation silty soil dynamic compaction foundation to be detected, and in-situ detection test data are collected; according to the Rayleigh wave detection test scheme, performing a Rayleigh wave detection test on the to-be-detected hydraulic fill silty soil dynamic compaction foundation, and collecting Rayleigh wave detection test data; according to the in-situ detection test data and the Rayleigh wave detection test data, the quality of the hydraulic reclamation silty soil dynamic compaction foundation to be detected is determined, and the method has the advantage that the efficiency and accuracy of hydraulic reclamation silty soil dynamic compaction foundation quality detection are improved.

The invention provides a slip rate control method and system for lunar rover wheel soil characteristics and electronic equipment, aiming at wheel soil dynamic differences caused by different earth-moon environments, a lunar rover slip rate characteristic curve shows that a lunar rover does not have a so-called'optimal slip rate 'fixed point, so that the longitudinal force of a tire reaches a peak value at the point, and the slip rate of the lunar rover reaches the optimal slip rate. The problem that a conventional ground optimal slip rate control method fails on the lunar surface is solved, a function about the tire load rate and the slip rate is introduced into a four-wheel torque distributor of the lunar rover to serve as a target optimization function, and four-wheel torque is distributed in a coordinated mode on the basis that the longitudinal driving requirement is met. According to the method, the special wheel soil dynamic characteristics of the lunar rover are considered, the tire force is controlled based on the slip rate and the tire load rate, the situation that the wheel slip rate is too large and the tire force is saturated is prevented, and the running dynamic property and safety of the lunar rover are effectively improved.

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 present invention discloses a soil dynamic characteristic parameter analysis method and device. The invention comprises: obtaining a general model according to a foundation model, a final deformation relationship and a bearing capacity characteristic value relationship, wherein the general model is #imgabs0#, #imgabs1# is a foundation reaction force coefficient, #imgabs2# is a bearing capacity characteristic value, #imgabs3# is a compressive stiffness reference coefficient, and #imgabs4# is an exponential correction coefficient; performing regression analysis on the general model to obtain a compressive stiffness reference coefficient and an exponential correction coefficient to obtain a final model, wherein the final model is #imgabs5#, wherein #imgabs6# is a compressive stiffness coefficient, and #imgabs7# is a soil type correction coefficient; obtaining the soil compressive stiffness coefficient according to the final model. Through the present invention, the problem that the analysis of the compressive stiffness coefficient in the related art is cumbersome and not applicable to a variety of soil types is solved.

The present invention relates to a dynamic deformation soil seepage simulation device, which belongs to the field of seepage simulation technology and is used to solve the problem that the existing seepage simulation device cannot perform dynamic deformation analysis on the experimental soil. The present invention includes: an experimental soil, a confining pressure control component, a seepage control component and a soil dynamic deformation control mechanism; wherein the confining pressure control component is a cylindrical structure, and the experimental soil is arranged inside the confining pressure control component; the soil dynamic deformation control mechanism is arranged below the experimental soil, and is used to control the deformation of the experimental soil; the seepage control component is arranged above the experimental soil, and is fixedly connected to the confining pressure control component; the seepage control component can allow liquid water to penetrate into the experimental soil. The present invention can realize soil seepage simulation under the dynamic deformation state of the soil.

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 invention discloses a method and system for simulating a submarine landslide problem based on double-layer double-phase non-local generalized particle dynamics, and belongs to the technical field of simulation calculation, and the method comprises the steps: dividing a submarine landslide calculation model into a fluid layer and a soil body layer, and respectively generating fluid material points and soil body material points; solving a fluid mass conservation equation by considering the relative speed between fluid substance points and soil substance points; calculating the nonlinear drag force between the fluid and the soil body; solving a motion equation of fluid substance points and soil substance points; updating respective substance information of the fluid substance points and the soil substance points, and applying boundary conditions; and obtaining a simulation analysis result of the submarine landslide calculation model based on the updated material information. A numerical framework is provided for researching the water-soil dynamic coupling problem of the submarine landslide, and more effective protection measures can be designed by simulating the interaction between soil and fluid, so that the influence of the submarine landslide on submarine foundations such as oil and gas pipelines and cables is reduced.

The present invention relates to the field of geotechnical testing technology, and proposes a combined determination device for moisture content and soil dynamic probing characteristics, including a probing rod having a probe portion; an insulating sleeve arranged on the probing rod, located on a side away from the probe portion; four conductive members, evenly spaced around the insulating sleeve, the main body of the conductive member is located inside the insulating sleeve, and one end thereof is used to contact the soil. Through the above technical scheme, the problems existing in the existing testing technology, such as poor durability of moisture content measuring devices, high test errors, unclear test ranges, long test cycles, and the need to make substantial changes to the original instrument and equipment or the original equipment cannot be reused when using the instrument for testing, resulting in excessively high costs, and cumbersome operations during application are solved.