158 results about "Soil characteristics" patented technology

The invention relates to the technical field of intelligent agriculture, and particularly discloses an orchard intelligent water and fertilizer integration-based edge end fruit tree fertilizer demand prediction method, which comprises the following steps of: constructing each fruit tree as a graph node, and fusing canopy spatial characteristics extracted by unmanned aerial vehicle multispectral remote sensing and nutrient time sequence characteristics monitored by a soil sensor; space influence weights among nodes are calculated according to the terrain, the soil texture and the space distance, and a fruit tree individual relation graph is established; then, through a space-time diagram convolutional network, aggregating space neighborhood features and capturing time dynamic changes, and outputting target state features subjected to multi-scale enhancement; when the canopy conflicts with the soil characteristic indication, combined diagnosis is carried out based on a neighborhood consistency index and an adjacent node state, systematic nutrient stress and local non-nutrient factors are distinguished, and final fertilizer demand prediction is generated after the conflict is eliminated; a digital fertilization prescription map is generated through spatial interpolation, soil characteristics and slope correction, and the water and fertilizer integrated equipment is driven to execute precise operation.

The present invention provides an emergency supervision method for a smart city lifeline project and an Internet of Things large model system, which relate to the field of emergency supervision technology. The Internet of Things large model system includes an emergency supervision user platform, an emergency supervision service platform, an emergency supervision management platform, an emergency supervision sensor network platform, and an emergency supervision object platform. The method is executed by the emergency supervision management platform, and includes: in response to the gas environment characteristics corresponding to the target pipeline meeting the early warning conditions, every preset period: based on the spatial connectivity information corresponding to the target pipeline, determining the target sensor and obtaining the corresponding air flow data; based on the gas transportation data, spatial connectivity information, air flow data and regional soil characteristics of the target pipeline, determining the estimated diffusion amplitude of the target gas; based on the estimated diffusion amplitude, determining the inspection frequency and sampling frequency to obtain soil samples during the inspection; and receiving leakage warnings. The present invention can achieve accurate identification of leakage risks and timely warnings.

The invention relates to the technical field of artificial intelligence, and provides a soil texture recognition model construction method, a soil texture recognition model construction device, a computer readable storage medium and electronic equipment, and the soil texture recognition model construction method comprises the steps: screening key soil texture features from a plurality of ocean soil texture features; the feature importance score of the key soil feature is higher than a preset score threshold; collecting training data associated with the key soil characteristics, and training a plurality of initial machine learning models by using the training data; and according to a preset performance evaluation index, screening out a final target machine learning model for ocean soil texture identification from the plurality of initial machine learning models. According to the invention, through an automatic modeling mechanism combining feature optimization and multi-model performance screening, the classification precision and engineering applicability of the ocean soil texture identification model are improved.

The invention discloses a slope stability analysis method and system based on data analysis, belongs to the technical field of slope safety analysis, and aims to solve the problems of dependence on hypothesis simplified model and neglect of real-time dynamic change in the prior art. S2, dynamic environment factor analysis; s3, slope stability analysis; s4, establishing an intelligent decision-making and early warning system; s5, system integration and user interaction; s6, performing system optimization and continuous learning; by comprehensively considering complex soil body characteristics such as heterogeneity and anisotropy of the slope and dynamic changes of environmental factors such as external rainfall, meteorology and earthquakes, the system can provide a more real and accurate slope stability analysis result, an intelligent algorithm and a data analysis technology are adopted, and the stability of the slope is improved. The dependence on a simplified physical model and a static hypothesis is reduced, so that the scientificity and the practicability of an analysis result are improved.

The invention provides a slope displacement monitoring method and system for a high and steep slope in a loess area, and the method comprises the steps: carrying out the preprocessing of data through a point cloud denoising algorithm according to an initial point cloud data set, filtering noise points and irrelevant reflection points caused by a complex terrain, and generating an optimized refined point cloud data set; aiming at the refined point cloud data set, constructing a digital surface model of the side slope by utilizing a three-dimensional reconstruction algorithm, carrying out local detail correction on the model in combination with soil loosening characteristics of a loess area, and determining a preliminary morphological structure of the side slope; performing time sequence data acquisition on the preliminary morphological structure to obtain slope three-dimensional model data of multiple time periods, and analyzing the dynamic evolution trend of morphological change to obtain slope deformation feature distribution; according to the slope deformation characteristic distribution, a finite element analysis method is adopted to conduct simulation calculation on stress distribution of the high and steep slope, the stability risk of a deformation area is judged, and potential landslide risk points are determined.

The invention discloses a lolium perenne seedling returning nitrogen reduction amount regulation and control method based on soil multifunctional evaluation, and relates to the technical field of agricultural planting.According to the method, a closed-loop dynamic regulation and control system is constructed, aiming at the soil characteristic difference after lolium perenne seedlings are returned to the field, precise and personalized management of the application amount of nitrogen fertilizer is achieved, and the application amount of nitrogen fertilizer is improved. According to the method, the nitrogen fertilizer compensation amount is dynamically adjusted according to the soil multifunctionality real-time evaluation result of the key growth stage of crops, and the yield fluctuation caused by blind reduction of application is effectively avoided, so that the stability and improvement of the crop yield are ensured while the chemical nitrogen fertilizer input is remarkably reduced, and the economic benefit is increased. The technical scheme that physical, chemical and biological indexes of soil are comprehensively evaluated in the key growth stage of crops, and the nitrogen fertilizer correction amount is dynamically calculated based on the deviation between the evaluation result and the target function range is adopted, so that the accurate regulation and control of the nitrogen fertilizer application amount can be realized; therefore, the stable yield of crops is guaranteed and the soil health level is continuously improved while the application of chemical nitrogen fertilizer is reduced.

The invention provides a grounding resistance online monitoring method and system, a storage medium and electronic equipment, and relates to the technical field of grounding resistance monitoring. According to the technical scheme provided by the invention, the geological type of the transformer substation and the reference resistance threshold curve corresponding to the geological type are acquired, the second grounding resistance value is calculated by combining the first grounding resistance value of the branch node in the grounding network, and the comprehensive resistance correction amount is determined based on the soil characteristic parameters; personalized adjustment of the reference resistance threshold curve is realized, and a target resistance threshold curve suitable for a specific transformer substation is obtained. The actually measured third grounding resistance value is compared with the corresponding threshold value of the final resistance threshold value curve, the abnormal state of the grounding network can be accurately identified, the problems of false alarm and missing alarm caused by a fixed threshold value are avoided, and the accuracy of online monitoring of the grounding resistance is improved.

The invention discloses an AIoT water and fertilizer integrated regulation and control method and system based on a crop growth dynamic model, and relates to the technical field of water and fertilizer regulation and control, and the method comprises the steps: firstly obtaining multi-dimensional environment parameters and soil characteristics through an AIoT sensing network, and deeply analyzing a restriction mechanism of soil moisture on nutrient effectiveness based on the crop growth dynamic model; and quantifying the nutrient effectiveness coefficient. And then, inputting the coefficient into a water-fertilizer coupling prediction model, and dynamically deducing the actual nutrient absorption amount and the moisture evapotranspiration amount of the crop in a specific water-fertilizer interaction environment, so as to realize digital representation of the physiological demand. And further, in combination with future meteorological information and cost constraints, multi-target collaborative optimization is carried out by using a rolling time domain optimization algorithm, and an optimal regulation and control strategy considering growth requirements and economic benefits is generated and driven to be executed. In this way, quantitative and accurate regulation and control of the water and fertilizer synergistic effect can be achieved, and therefore the resource utilization efficiency and agricultural production economic benefits in the whole growth cycle of crops are greatly improved.

The application provides an in-situ passivation remediation method for heavy metals in farmland soil, and belongs to the field of heavy metal passivation in soil. The in-situ passivation remediation method for heavy metals in farmland soil is composed of the following steps: premixing, primary fermentation and secondary fermentation. The premixing is to uniformly mix pig manure, chicken manure, a composite passivation agent, a microbial inoculum and farmland soil, to adjust the C / N ratio and the water content of the mixture, to obtain a premix, and then to perform primary fermentation and secondary fermentation in an aerobic environment. The in-situ passivation remediation method for heavy metals in farmland soil can effectively combine the passivation agent with the compost fermentation, avoid the adverse effects of the fermentation components on the passivation agent during the composting process, improve the adaptability to different soil characteristics, realize stable and efficient treatment of different characteristic soils, further improve the in-situ passivation remediation effect on heavy metals in farmland soil, and effectively avoid the situation that the heavy metals in the soil are released again after the soil heavy metals are passivated.

The invention provides a variable-rate fertilization control system and method, and relates to the technical field of variable-rate fertilization control. A soil water quantity diffusion model is established through a water quantity diffusion model module according to soil characteristics of a region to be fertilized, a drip irrigation fertilization range is determined through a drip irrigation range calculation module, and the volume of the drip irrigation fertilization range is calculated; the fertilization amount calculation module is used for performing real-time concentration detection on the types of fertilizer elements in a drip irrigation fertilization range in which the fertilizer element detection plants are located, and judging the demand quantity and the lowest absorption content of the plants on each type of fertilizer elements in a fertilization period; the fertilization safety module calculates the maximum fertilization amount according to the soil inorganic salt content and the volume of the drip irrigation fertilization range, formulates a fertilization strategy through the concentration matching module, calculates the fertilization drip irrigation speed and the fertilization drip irrigation water amount according to the water amount diffusion model and the drip irrigation fertilization range, and calculates the fertilizer preparation concentration of each fertilizer element type according to the fertilization drip irrigation water amount.

The invention discloses a slope stability prediction method in heavy rainfall weather, and relates to the technical field of road slopes. The method comprises the following steps: collecting soil characteristic data before and after rainfall in a road slope sub-region, and fitting a water-soil characteristic function and a saturated permeation function through a least square method; the method comprises the following steps: establishing a road slope three-dimensional model by using a laser radar, obtaining soil parameters of each point of the road slope three-dimensional model based on an inverse distance square weighting method, and obtaining simulated initial soil matrix suction and simulated initial unsaturated permeability coefficients; simulating moisture movement through an unsaturated seepage control equation to obtain simulated soil moisture saturation and simulated pore water pressure of each point, screening risk points through a preset threshold value, and generating risk clusters through density clustering; and searching a potential sliding surface in the risk cluster by adopting a particle swarm optimization algorithm, calculating the safety coefficient of the sliding surface in combination with a soil strip method, and quantifying the area of the sliding surface. And fusing the safety coefficient and the area proportion to calculate a slope risk index and divide stability grades.

The invention relates to the technical field of geological disaster monitoring, in particular to a geological disaster real-time monitoring platform and method based on intelligent AI. The method comprises the following steps: acquiring multi-source monitoring data; analyzing the multi-source monitoring data, and determining the stability of the soil body; determining soil body characteristic parameters based on soil body stability; obtaining environmental hydrological data, and determining a geologic structure dynamic response mode according to the environmental hydrological data; and determining a geological disaster risk level according to the soil body characteristic parameters and the geological structure dynamic response mode. Soil body characteristic parameters are determined, quantitative indexes of building specificity are provided, and customized risk assessment is supported. The method comprises the following steps: acquiring environmental hydrological data, determining a dynamic response mode of a geologic structure according to the environmental hydrological data, capturing real-time behavior characteristics of the geologic structure under environmental change, and identifying a weak area of the geologic structure. And according to the soil body characteristic parameters and the geological structure dynamic response mode, determining the geological disaster risk level, realizing building level early warning, and quantifying the risk evolution rate.

The invention relates to a distributed hydrological model hydrological parameter gridding method based on deep learning, and the method comprises the following steps: collecting the feature data of regional hydrological parameters based on a VIC model, and carrying out the preprocessing of the data, and forming a data set; constructing a multi-layer perceptron (MLP) neural network model, and establishing a mapping relation between an input variable and an optimization parameter; loss changes in the training process are monitored, and the prediction precision and deviation distribution of the model are evaluated through a scatter diagram contrast ratio fixed value and calculated value; original hydrological parameters in the model parameters are updated to hydrological parameters automatically calibrated based on machine learning, the flood process of the research area is simulated and analyzed, and then the optimized parameters are verified through Nash efficiency coefficients. According to the method, a traditional manual parameter adjusting mode is replaced, the complex nonlinear relation between the soil characteristic data and the environment variables is deeply excavated, the model parameters are automatically adjusted, the simulation precision of the hydrological model is improved, and the spatial distribution reasonability and continuity of the hydrological parameters are improved.

The invention relates to the technical field of forest resource monitoring, in particular to a forest carbon reserve calculation system and method, and the method comprises the steps: obtaining target data corresponding to a target forest; obtaining forest stand features, climate features and external influence features corresponding to the target forest based on the target data; obtaining forest types, forest stand density, forest stand age groups and soil characteristics based on forest stand characteristics; based on the forest type and the stand density, vegetation carbon reserves are obtained; based on soil characteristics and forest stand age groups, obtaining soil carbon reserves; obtaining a carbon reserve calibration coefficient based on the climate characteristics and the external influence characteristics; and obtaining the forest carbon reserve based on the vegetation carbon reserve, the soil carbon reserve and the carbon reserve calibration coefficient. According to the invention, the calculation precision of the carbon reserves can be improved.

The invention discloses an intelligent management method based on landscaping plant irrigation, and relates to the technical field of landscaping management, and the intelligent management method comprises the following steps: obtaining multi-source real-time data of a landscaping area, and based on terrain elevation data and plant physiological data, in each irrigation grid unit, carrying out the irrigation of the landscaping area; the method has the advantages that it is ensured that the units are accurately matched with the surface fluctuation and the plant water demand difference, in each grid, in combination with soil characteristics and meteorological data, the soil moisture migration simulation result and the plant physiological data are combined, and the plant moisture migration simulation result and the plant physiological data are combined to control the irrigation equipment to execute operation. According to the method, the soil moisture kinetic equation coupled with the root system water absorption function is used for finely simulating moisture migration, the problem of uneven local irrigation caused by terrain complexity and plant water demand space difference is effectively solved, the water resource space configuration precision is remarkably improved, and a scientific foundation is laid for accurate irrigation decision making.

The invention provides a soil nutrient content measuring method, device and system, and belongs to the technical field of soil detection.The method comprises the steps that a region of interest of soil at a target sampling point is determined, and the region of interest is divided into a plurality of grid regions; receiving an RGB image and a depth image of soil at the target sampling point; calculating the score of each grid region according to the RGB image and the depth image; taking the grid region with the highest score as an optimal insertion point of the sensor; after the coordinates of the optimal insertion point are output, sensing data obtained at the optimal insertion point are received; and obtaining the soil nutrient content of the target sampling point according to the sensing data. The optimal insertion point of the sensor is determined based on the score of the grid region, the soil nutrient content of the target sampling point is determined based on the sensing data of the optimal insertion point, it is ensured that the collected sensing data can comprehensively reflect the real soil characteristics of the target sampling point, and the accuracy and reliability of a measurement result are improved.

The invention discloses a dry land wheat green high-yield cultivation optimization method and system, and relates to the technical field of agricultural cultivation. The method comprises the following steps: firstly, obtaining typical rainfall characteristic data and soil characteristic data of a target planting area, constructing a micro-furrow simulation model, and carrying out optimization solution by taking predicted water catchment maximization as a target to obtain optimal micro-furrow parameters. And calculating a confidence wetting depth by combining rainfall characteristic data and an optimization result, and determining furrow sowing parameters according to the optimization result and wheat water demand characteristics. Finally, cultivation operation is executed based on the micro-furrow parameters, the furrow sowing parameters and the confidence wetting depth, wherein the fertilizer application depth is determined based on the confidence wetting depth. Precise matching of a micro-furrow structure, crop layout and water and fertilizer management is achieved, the problems that in traditional cultivation, the water utilization efficiency is low, and water and fertilizer space matching is poor are solved, and the rainfall utilization efficiency and the yield level of dry land wheat are improved.

The invention discloses a method, a system, equipment and a medium for measuring the impact grounding resistance of a base tower, and particularly relates to the technical field of high voltage, and the technical key points are as follows: establishing a factor directed graph based on a first influence factor set constructed by environment characteristics and soil characteristics of a base tower mounting area and in combination with a pre-constructed factor association rule; processing the node features by using a random forest to obtain an influence factor generation model; obtaining a second influence factor set constructed by the environmental characteristics and soil characteristics of the base tower installation area at the current measurement moment, and inputting the second influence factor set into the influence factor generation model to obtain an influence factor at the current measurement moment; inputting impact current into a grounding loop formed by the first base tower and the second base tower, and measuring to obtain the initial impact grounding resistance of the grounding device of the second base tower; and correcting the initial impact grounding resistance by using the influence factor, and outputting the corrected impact grounding resistance.

The application discloses a soil deep loosening simulation method based on DEM-FEM bidirectional coupling. The method comprises the following steps: establishing a soil discrete element model and a deep loosening tool finite element model; using the discrete element DEM simulation to analyze the influence law of soil characteristic parameters and deep loosening tool motion parameters on soil deep loosening effect and deep loosening tool working resistance; changing the soil characteristic parameters and deep loosening tool motion parameters, and calculating the information such as soil deep loosening particle mixing degree, deep loosening tool working efficiency and working resistance under different variables; analyzing the influence law of the working resistance obtained from the DEM on the deep loosening tool structure through the finite element FEM analysis, changing the soil structure parameters and deep loosening tool structure parameters, and counting the statics and dynamics analysis results under different variables; simulating through the DEM-FEM bidirectional coupling, analyzing the soil deep loosening mechanism of the deep loosening tool, and obtaining the parameter and structure optimization results. Compared with the prior art, the application can effectively reduce resistance and consumption, and improve working efficiency.

The application discloses a kind of mine contaminated soil heavy metal high-efficiency leaching removal effect prediction methods, belong to soil leaching data processing technical field.The method includes the following steps: according to the soil characteristic parameter of specified area soil, the concentration of reference leaching agent is corrected, and the corresponding initial leaching agent concentration is obtained;According to the soil state parameter of each time monitoring point of specified area soil, the leaching speed of specified area soil is dynamically adjusted;According to the soil permeability parameter of each monitoring period of specified area soil, the leaching agent injection time of specified area soil is dynamically adjusted, and the corresponding leaching removal effect is predicted after each monitoring period ends.The application can improve the efficiency and effect of leaching process by correcting the concentration of leaching agent, dynamically adjusting the speed of leaching agent and the injection time of leaching agent, and can also optimize the leaching scheme according to real-time monitoring data to ensure the best removal effect.

The invention provides a permeable breakwater and a design method thereof, and relates to the technical field of permeable breakwater. Aiming at the lack of a design method for high-precision environment coupling and high-accuracy structure stress prediction during design of a permeable breakwater in the prior art, the method comprises the following steps: establishing a wave-structure-foundation coupling model based on structure stress data, environment soil characteristics and a transmission coefficient of waves; s5, selecting a wave-structure-foundation coupling model, simulating different structure parameter combinations based on the wave-structure-foundation coupling model, and when the simulation results do not meet the target requirements, circularly executing the steps S2 to S5 until the simulation results meeting the target requirements are screened out, and determining a corresponding final structure parameter combination. The cooperative working mechanism of the reduction foundation and the pile foundation is realized, the dynamic interaction of the wave load and the structural response is simulated, and the environmental coupling precision and the structural stress prediction accuracy are improved.

The invention discloses a system for dynamically matching microwave radiation and catalytic reaction based on soil characteristics and a use method, and belongs to the technical field of soil remediation and improvement. The system integrates microwave radiation catalysis, intelligent sampling detection, artificial intelligence analysis and remote control technologies, and realizes full-process intelligent treatment of efficient decomposition of soil organic matters and soil hardening improvement. The system comprises an intelligent sampling module, an AI analysis and evaluation module, a feedback control module, a microwave radiation module and a catalytic reaction module, can realize large-area operation by carrying unmanned equipment, can also be manually operated to adapt to small-area scenes, has the characteristics of high efficiency, accuracy and universality, and is suitable for various soil improvement scenes such as farmlands, mining areas, urban green lands and the like.

The invention discloses a deep soil sampling device, and belongs to the technical field of soil sampling, the deep soil sampling device comprises a main cylinder, a bottom cylinder, a petal-type soil drilling cone, a sampling cylinder, a limiting connection assembly, a driving screw rod and a driving positioning member, a plurality of mounting slideways are arranged on the side wall of the bottom cylinder, elastic reset members are arranged on the mounting slideways, the petal-type soil drilling cone comprises a plurality of petal-type cone sheets, and the petal-type cone sheets are arranged on the bottom cylinder. The petal-type conical piece is movably connected with the elastic reset piece through a rigid connecting piece, fixing columns are symmetrically arranged on the outer edge of a top plate at the upper end of the sampling barrel along the diameter line, locking openings are formed in the fixing columns, the limiting connecting assembly comprises a quick-release locking piece matched with the locking openings, the driving screw rod is rotationally connected with the limiting disc, and the driving positioning piece comprises a semi-ring piece. Threaded teeth are arranged on the inner side walls of the semi-ring pieces, and the two semi-ring pieces form a positioning thread sleeve matched with the driving screw. The soil sampling device has the beneficial effects that soil sampling at different depths can be efficiently and accurately completed without repeated drilling, the structural integrity of the sampled soil is guaranteed, and the characteristics of the soil at different depths are truly reflected.

The invention discloses an intelligent application method and system of a biological fertilizer for rapidly fertilizing black soil, and relates to the technical field of intelligent fertilization. The method comprises the following steps: by taking lipid molecules, a black soil environment, functional microorganisms and a target plant as main body nodes, analyzing an association relationship, fusing target black soil characteristics, and constructing a fertility improvement graph structure; carrying out planting full-period analysis on the target black soil, constructing a period planting chain, and configuring deviation parameters according to the soil demand relationship of the planting period; according to the fertilization graph structure and the deviation parameters, fertilization main body difference mapping is carried out on the periodic planting chain, and node fertilization difference is obtained; and by taking the node fertility difference as an application compensation target, performing target compensation analysis according to an application time sequence variable relationship, obtaining a compensation application strategy with optimal input minimum compensation, and generating application control information. The technical problem that in the prior art, fertilization is not accurate, and consequently the black soil fertilization period is long is solved, and the technical effects of shortening the fertilization period and improving the fertilization accuracy are achieved.

The invention relates to the technical field of soil improvement, and discloses a soil improvement effect real-time monitoring method and system and a storage medium. The method comprises the following steps: collecting multiple depth data samples in the vertical direction of soil, and constructing a layered soil characteristic data set; identifying the position of the high-heterogeneous section based on the data set; injecting a tracer agent at the position and imaging in real time to obtain a permeation path image sequence; predicting a diffusion velocity and a retardation point position by using a random forest model, dynamically adjusting injection parameters to eliminate retardation, and obtaining permeation path data; tracking and quantifying the action change of the modifier in each soil layer through time sequence analysis to obtain an action effect quantitative index; the index is compared with an initial data set, a hierarchical model is optimized, and a hierarchical monitoring framework is constructed; and integrating multiple depth data samples to verify the framework, and generating an evaluation report of the soil improvement effect. According to the invention, the accurate characterization of the vertical layering characteristic of the soil and the scientific and quantitative evaluation of the improvement effect are realized, and the use efficiency of the modifier is improved.

The present application belongs to the technical field of pile foundation engineering construction, and relates to a soft soil slope pile foundation inclination correction structure and a construction method. The soft soil slope pile foundation inclination correction structure comprises a deviation pile, a pile top force device, a grid-gravel composite pile, a grouting pipe and a pile side reinforcement area, wherein the grid-gravel composite pile is composed of a grid casing and gravel. By setting the grid-gravel composite pile in front of the pile, on the one hand, it can serve as a stress release hole, and by pumping and draining water in the hole, the passive side soil pressure during correction is reduced; on the other hand, by grouting reinforcement, the soft soil characteristics are improved, a rigid gravel pile is formed in front of the pile, the pile side reinforcement area is combined, the bearing capacity of the deviation pile is improved, the landslide thrust borne by the deviation pile is reduced, and then the reliability and stability of the deviation pile during service are increased. The present application overcomes the problems of large correction difficulty and incomplete correction of the traditional correction measures, and has good economy and implementability.

The invention discloses an installation control method, system and equipment of a geothermal loop, a medium and a program, and belongs to the technical field of geothermal installation. The method comprises the steps that thermal load demand prediction is carried out based on building feature information and environment feature information of a heat supply building, and the maximum thermal load demand is obtained; constructing a heat exchange predictor according to the collected soil characteristic information of the geothermal area; by means of a heat exchange predictor, loop layout scheme optimization is carried out with the purpose of meeting the maximum heat load requirement, and an optimal loop layout scheme is obtained; and according to the optimal loop layout scheme, an installation control scheme of the geothermal loop is formulated. According to the method, the heat load is accurately predicted according to the building and environment characteristics, the loop layout scheme is optimized in combination with the soil characteristics, and the heat supply efficiency of the geothermal system is improved.

The invention discloses a soil mechanics theory-based erosion gully microscopic scale model construction method, which comprises the following steps of: firstly, carrying out field exploration on a target erosion gully to obtain geometric and soil mechanics parameters and meteorological data, and determining a scale proportion according to a similarity theory; preparing a similar soil material from quartz sand, clay and the like, and preparing a model substrate from a fiber reinforced composite material; laying materials layer by layer, implanting fibers, setting a vegetation layer simulation environment, setting boundary conditions and a loading and monitoring system; applying a simulated load, comparing model output with a prototype or theoretical result, determining key parameters by sensitivity analysis, and adjusting and optimizing the model. The model constructed by the method is highly similar to the mechanical behavior and erosion process of an actual erosion gully, soil characteristics can be accurately simulated, data are acquired through reliable monitoring, the accuracy is ensured through scientific calibration and optimization, an effective means is provided for erosion gully research, the research cost is reduced, and high universality is achieved.

The application relates to the field of civil engineering, and discloses a foundation pit finite element model parameterization rapid modeling method: a finite element model is constructed through foundation pit geometric information and soil characteristics, soil response is simulated by adopting a nonlinear constitutive relation and a random process, foundation pit stability optimization and dynamic adjustment are realized, and the application further provides a foundation pit finite element model parameterization rapid modeling system: an input module, a modeling module, a constitutive model module, a random process module, a simulation module, an optimization module, a grid refinement module and a real-time monitoring module. The application realizes simplified modeling process, improved calculation precision, accurate simulation of soil nonlinear behavior and dynamic response, and significantly improves the stability and safety in the foundation pit design and construction process by automatically generating a foundation pit finite element model, introducing a Kachanov-Delale nonlinear soil constitutive model, generating a soil elastic modulus random field based on a Gaussian process, and dynamically adjusting model parameters in real time.

The utility model discloses a spiral stirring roller for mixing nutrient soil. The spiral stirring roller comprises a roller shaft, a spiral blade I and a spiral blade II, wherein the spiral blade I and the spiral blade II are sleeved on the roller shaft; the first spiral blade is fixedly connected to the roller shaft. The second spiral blade is also connected to the roller shaft in a sleeving mode and can slide in the axis direction of the roller shaft; by adjusting the position of the spiral blade II on the roll shaft, the width of the stirring channel is adjusted, so that different soil characteristics and stirring requirements can be met. When a wider stirring channel is needed, the spiral blade II is attached to the spiral blade I, so that the stirring space can be quickly expanded, and the stirring device is particularly effective for treating soil with higher humidity or larger particles, and ensures that the soil can be fully turned over and mixed. When a narrower stirring channel is needed, the stirring space can be reduced and the stirring strength can be increased only by moving the second spiral blade to the middle part of the spiral groove formed by the first spiral blade.