29988 results about "Geotechnical engineering" patented technology

The invention provides a pre-control and monitoring method for a whole process of actual grouting engineering based on digital geological model, comprising: extracting discontinuous fracture surfaces in a geologic body structure, to build a underground geologic body structure model; build a multi-source geologic body attribute model, optimizing and solving grouting simulations of a disaster high-risk region by using multiphase flow calculation method, and controlling grouting equipment by using optimized grouting parameters to carry out an actual grouting engineering; obtaining a multi-factor diffusion range of variable coefficients by adjusting physical values of the parameters in the grouting simulation and attribute data structure model by using a control variable method, learning and capturing complex mapping relationship between different parameters by using a neural network, optimizing the grouting parameters in the actual engineering in real-time, so as to realize the pre-controlling, monitoring and optimization of the whole process of the actual grouting engineering.

The invention discloses a geotechnical engineering stability early warning system and method combining side slope deformation monitoring and numerical simulation, and relates to the technical field of geotechnical engineering safety monitoring and disaster early warning. Side slope deformation monitoring and numerical simulation are combined, and multi-source real-time monitoring data of side slope deformation and numerical simulation are fused; constructing a dynamically updated slope deformation evolution analysis system; performing dynamic partition identification on the slope deformation evolution process according to the multi-source real-time monitoring data, and identifying a slope deformation threshold value and abnormal evolution characteristics of rock and soil; and setting an automatic triggering grading early warning signal of a geotechnical engineering early warning index, and completing slope risk dynamic assessment and early warning output of the rock and soil. According to the invention, the automatic triggering of the grading early warning signal is realized, the response speed, the judgment accuracy and the risk assessment scientificity of the geotechnical engineering early warning system are obviously improved, and the intelligent, dynamic and systematic technical support is provided for the safety prevention and control of the side slope.

The invention relates to the technical field of geological disaster monitoring, and discloses an intelligent early warning method and system for geological disasters in geotechnical engineering, and the system comprises a data collection module, a data processing module, a feature extraction module, an early warning model module, a response execution module and an optimization feedback module. Static geological parameters, dynamic environment parameters and historical disaster data are integrated, a standardized space-time correlation data set is constructed, the limitation of a single data source is broken through, multi-dimensional dynamic response characteristics of a rock-soil body are captured, a reliable data basis is provided for accurate early warning, the rigidity defect of a traditional fixed threshold value is avoided, and the early warning accuracy is improved. The method achieves the self-adaption of the risk early warning sensitivity, reduces the misjudgment and missing judgment caused by environment interference, intercepts a dynamic data stream in real time through a sliding window, calculates the risk mean value and variance, quickly responds to sudden environmental changes such as rainfall sudden change and vibration abnormality, and generates a graded early warning signal.

The invention discloses a tunnel deep-buried drainage ditch rapid blasting excavation method based on vertical drilling, which comprises the following steps: step 1, detecting the geology in front of a tunnel by using vertical drilling coring, geological radar and TSP seismic wave technology, and constructing a three-dimensional model; 2, generating an asymmetric hole net layout based on a geological model and AI, and setting a drilling-free vibration isolation belt; the design of dense inside and sparse outside is adopted, and vibration propagation is blocked; thirdly, a three-stage air spacer is arranged at the bottom of the blast hole, segmented charging is implemented, the explosive energy release time is prolonged, and the single-segment explosive quantity peak value is reduced; fourthly, an electronic detonator is adopted for millisecond detonation, and peak vibration is weakened through the waveform superposition offset effect; 5, arranging fiber grating sensors in the tunnel, collecting data in real time and transmitting the data to the cloud AI platform; dynamically adjusting parameters based on the monitoring data; and 6, evaluating a blasting effect through a three-dimensional laser scanner, generating an evaluation report in combination with data, updating a BIM model database, and continuously optimizing an AI algorithm.

The invention relates to the technical field of coast engineering, in particular to a beach change evolution inversion method combining numerical simulation and actually measured data, which comprises the following steps: S1, acquiring an actually measured shoreline data set of a current period; s2, establishing a wave-tidal current-sediment coupling numerical model; s3, outputting a simulated shoreline data set; s4, performing spatial matching on the actually measured shoreline data set and the simulated shoreline data set to generate a spatial discrete residual field; s5, taking the spatial discrete residual field as a constraint condition, and reversely solving an optimal hydrodynamic parameter combination; and S6, inputting the optimal hydrodynamic parameter combination into the wave-tide-sediment coupling numerical model, and outputting the beach evolution form in the future period. According to the method, dynamic coupling of the hydrodynamic parameters and the beach evolution process is realized by constructing an inversion optimization mechanism based on actual measurement data driving, and the accuracy of shoreline change simulation and the reliability of prediction are greatly improved.

The invention relates to the technical field of geothermal drilling monitoring management, in particular to a construction monitoring system and method for geothermal drilling. The method comprises the following steps: constructing a state variable set, quantifying structural disturbance intensity by adopting a disturbance derivative method, normalizing the structural disturbance intensity, and defining a state transition tensor mapping behavior influence coefficient; in combination with the high-order derivative of the disturbance trend function and the behavior collaborative change matrix, an offset risk factor is generated through fusion for early warning; dividing a well drilling area into three-dimensional grids, calculating local stress potential energy, adjusting weight through a dynamic sensitive belt, and generating a risk distribution diagram through smooth filtering; performing closed-loop dynamic regulation and control by using risk potential energy centroid coordinates and gradient field inversion intervention vectors for medium and high risk areas; and through multi-period risk potential energy tensor analysis, calculating the matching degree of a self-healing index and a stable cone region, evaluating the self-healing capability of the system and feeding back a regulation and control strategy. According to the invention, a closed-loop monitoring and active control system for nonlinear risks of geothermal drilling is formed.

The invention belongs to the technical field of oil and gas reservoir energy development, and discloses a three-dimensional injection and production well pattern construction method based on a multi-objective algorithm. The problem that the delimited potential area is difficult to effectively use due to the fact that existing potential evaluation is only based on a single index is effectively solved. Comprising the steps that a fault inner core, a fault outer core, a fracture development dense zone and a secondary fracture zone are proposed; carrying out inter-well connectivity analysis on the oil reservoir units by utilizing an oil reservoir engineering method and a numerical simulation streamline method; based on the embedded discrete fracture model, analyzing a remaining oil distribution mode under the control of the nuclear band structure; a multi-parameter comprehensive evaluation system is constructed by combining the remaining oil utilization potential, the displacement power, the flow capacity, the connectivity relation and the reserve abundance; a three-dimensional injection-production well pattern construction technology is formed for an oil reservoir with or without bottom water; based on a multi-objective optimization algorithm, three-dimensional collaborative optimization of the recovery ratio, the well control reserves and the net present value is taken as a core, and a high-efficiency well location deployment technology for different fault zones is constructed.

The invention belongs to the field of geotechnical engineering and engineering geological information modeling, and relates to a stratum-parameter coupling randomness three-dimensional random field modeling and shield construction ground surface settlement rapid prediction method and device based on multi-source data fusion. According to the method, a three-dimensional joint random field acting on stratum types and rock-soil key physical property parameters at the same time can be constructed under the joint constraint of multi-source data such as drilling, geophysical prospecting, geotechnical tests and terrains, and a calibrated, explainable and updatable geological section automatic generation and uncertainty quantification channel is formed; on the premise that geological rationality is guaranteed, section geometry and parameter distribution under the conditions of complex structures and lateral phase change are restored robustly, the accuracy, consistency and interpretability of the three-dimensional geological section are remarkably improved, and a combined uncertainty result which can be directly used for rapid prediction and risk assessment of shield construction settlement is output. The technical problems that a geological section generated by an existing method is not accurate enough, uncertainty is difficult to quantify, and the extrapolation capacity of a complex scene is weak are solved.

The invention relates to the technical field of geological exploration, and discloses a water-rich sandy stratum tunnel base settlement prediction method and system, and the method comprises the steps: constructing a multi-source cooperative exploration system; deploying a sanding-seepage-stress coupling model at an edge computing node, and mining the relevance of data of different dimensions through a space-time attention fusion network; based on the prediction matrix and mineral exploitation working condition parameters; when the predicted settlement exceeds a safety threshold value or the sanding expansion rate is abnormal, a high-precision remeasurement mechanism is triggered, and a cross-hole radar and acoustic logging combined verification module is activated; and iteratively optimizing coupling model parameters by adopting a transfer learning algorithm through deviation analysis of measured data and a prediction result. According to the method, a scientific basis is provided for stratum stability evaluation and prevention and control measure formulation in the mineral exploitation process, and the probability of engineering risks caused by base settlement of the water-rich sandy stratum is effectively reduced.

The invention discloses a coal mine rock burst risk assessment system which comprises a data acquisition module, an energy accumulation rate calculation module, a roadway network modeling module, a risk assessment module and an early warning regulation and control module. The method comprises the following steps of: firstly, calculating an energy accumulation rate of a roadway, then constructing a roadway network diagram, identifying a high stress conduction path, calculating a dynamic risk index and delimiting a risk area by integrating factors such as a historical impact event and an energy index, and automatically triggering corresponding early warning and regulation measures by a system according to a risk level so as to realize accurate early warning and dynamic regulation. And mine operation decision making and accident prevention are assisted.

The invention discloses a building structure anti-seismic toughness optimization method and system based on deep learning, and relates to the technical field of anti-seismic toughness optimizing.In operation of the system, a sensing network is deployed, multi-dimensional dynamic response parameters in the vibration process of a building structure are collected, preprocessing and sliding window characterization are carried out on a collected parameter set, and the anti-seismic toughness of the building structure is optimized; encoding the input tensor TXF, extracting a deep space-time coupling feature generation coefficient, performing multi-dimensional composite calculation on an anti-seismic stress energy coefficient SEC, a response co-motion coefficient RSC and a damage evolution index DEI to generate a system-level evaluation core index toughness spectrum evolution index REX, and comparing the toughness spectrum evolution index REX with a preset threshold value to obtain the evaluation core index. Grading and risk positioning are carried out on the current state of the building structure, a generated control strategy is sent to an execution layer, a damping adjusting device, a shock insulation layer controller or component repairing equipment is linked to complete structure regulation and control, and response is carried out after real-time acquisition and optimization.

The invention relates to the technical field of engineering construction control, in particular to a self-adaptive control method and system for a cement mixing pile, and the method comprises the steps: setting the slurry preparation ratio parameter of a slurry preparation barrel of a feeding hopper according to the working information of the cement mixing pile, and conveying the prepared slurry to a slurry storage barrel of a discharging hopper; collecting a slurry static pressure signal of a slurry storage barrel of the blanking hopper, and monitoring the load dynamic characteristics of a stirring motor of the blanking hopper in real time in the stirring process; the slurry spraying quality parameters of the slurry are analyzed, and when the slurry spraying quality parameters reach the preset feeding standard, the slurry is conveyed to a slurry spraying pipeline to be matched with a cement mixing pile for pile forming work; when the guniting quality parameter exceeds the interval of the feeding standard, a real-time matching error is obtained; and generating a ratio correction instruction to correct the pulping ratio parameters. According to the invention, the dynamic closed-loop control of the pile forming quality of the cement mixing pile under the complex geological condition is effectively realized, and the industry bottleneck that the traditional open-loop proportioning system cannot respond to the slurry state change in real time is broken through.

The invention discloses an on-site monitoring system for the performance of an elastic loose type anchorage system suitable for deep-sea buoys, and particularly relates to the field of deep-sea monitoring. The on-site monitoring system auxiliary comprises a central processing module, wherein the output end of the central processing module is separately connected with an information display module,an information storage module, an auxiliary recovery module and a driving module, and the input end of the central processing module is separately connected with a power supply module, a monitoring module, a correction module and a positioning module. According to the on-site monitoring system for the performance of the elastic loose type anchorage system suitable for the deep-sea buoys, the auxiliary recovery module is arranged, air bags are installed at a plurality of node positions on the anchorage system, a booster pump in a pressurization unit is used, outside air is conveyed into a floating ball unit through a pipeline unit, so that the retractable air bags are enabled to bulge upwards to float, the whole anchor system is directly floated in sections, people conveniently recycle theanchorage system greatly, the workload during the recycling process is reduced, and the practicability is high.

The invention discloses an intelligent double-liquid grouting system and a grouting method. The system comprises a liquid A stirring barrel, a liquid B stirring barrel, a double-liquid grouting pump, a slurry mixer, a PID (Proportion Integration Differentiation) regulating valve, a control system, a flow meter, a pressure meter, a flow sensor and a pressure sensor. The liquid A and the liquid B are respectively prepared and then sent out by a double-liquid grouting pump, enter a slurry mixer to be compounded and mixed, and are injected into a target stratum through a directional grouting pipe. The system collects and analyzes flow and pressure data through a control system, and closed-loop regulation and control of grouting flow and proportion are achieved through PID regulation logic. The PID regulating valve has the functions of over-voltage current limiting and overflow prevention at the same time. The method is suitable for reinforcement and leakage treatment under a complex stratum in geotechnical engineering, and has the advantages of being high in matching precision, high in mixing efficiency, good in safety, high in adaptability and the like.

The invention discloses a large-section long-footage mechanical blasting mixed excavation method suitable for a subway station, and relates to the technical field of underground rail transit engineering, and the method comprises the following steps: obtaining a tunnel section contour, a geologic structure and blasting parameters, building a three-dimensional blasting wave propagation inversion model, and combining geology and material heterogeneity to obtain a three-dimensional blasting wave propagation inversion model; and identifying a closed space region forming reflection interference, and predicting a space point location where blasting wave energy is abnormally accumulated. Based on the three-dimensional blasting wave propagation inversion model, the abnormal wave energy accumulation area is predicted in combination with geological heterogeneity, the high-risk blasting section is recognized, parameters are reconstructed, vibration real-time monitoring and model feedback correction are assisted, a closed-loop control system is constructed, local wave crest abnormity is effectively restrained, and the safety and controllability of large-section tunnel blasting construction are improved.

The invention discloses a viscous coarse-grained soil permeability coefficient prediction method based on a physical constraint neural network, and the method comprises the following steps: carrying out an indoor viscous coarse-grained soil seepage test, and establishing a viscous coarse-grained soil permeability coefficient formula considering porosity and grain composition characteristics, further constructing a mixed model containing a physical driving item and a neural network data driving item, forming a complete data set through a numerical simulation technology and literature investigation on the basis of a seepage test, complementarily collecting porosity, grain composition characteristics and corresponding permeability coefficient data of the viscous coarse-grained soil sample, and dividing the complete data set into a training set and a test set; according to the method, optimal hyper-parameters are dynamically searched in combination with Bayesian optimization for model training, a loss function curve and permeability coefficients of the viscous coarse-grained soil under different porosity and grading characteristics are obtained, tests show that high-precision prediction of the permeability coefficients of the viscous coarse-grained soil is achieved, and the problems that a traditional method is insufficient in physical constraint and low in prediction precision are solved.

The invention provides a multi-layer soft soil foundation settlement prediction method, and relates to the field of settlement prediction, and the method comprises the steps: obtaining soft soil parameters through arranging a multi-source monitoring device, carrying out inversion to generate multi-dimensional feature vectors containing particle size distribution, void ratio, compression modulus gradient and effective stress, and dividing structure piece elements to construct a feature set; the Euclidean distance between the fragments is calculated and clustered to generate a structural similar region, and a judgment threshold is dynamically adjusted and combined based on the change rate of the structural information entropy to construct a dynamic structural map; newly added or cracked similar areas are identified, a structure sudden change strength index is generated, and when a threshold value is exceeded, a jump prediction model is constructed according to entropy change, pore pressure gradient and deformation rate to output discontinuous settlement increment; and generating an error field by using the difference value of the actually measured settlement and the predicted value, and correcting the structural information entropy and merging the threshold value after weighted averaging according to the similar region, thereby realizing the self-adaptive correction of the structural map and iterative optimization prediction.

The invention relates to the technical field of geotechnical mechanics and engineering, and particularly discloses a soft soil foundation settlement monitoring method and system based on multi-field multi-source information, and the method comprises the steps: collecting multi-source data of a target soft soil area; performing constitutive parameter inversion, data standardization and discrete Fourier transform frequency domain conversion on the data to obtain a standardized frequency domain multi-field multi-source data set; based on the data set, a soft soil constitutive parameter library and a soil mechanics physical equation, constructing an FD-PINN frequency domain physical information neural network, embedding the physical equation as a prior constraint, and training the model by adopting an alternating optimization strategy; inputting the real-time frequency domain data flow into the model, and outputting the current settlement amount, the settlement rate and the multi-physical field frequency domain distribution; and in combination with a pre-established large scale model test result, through IDFT inverse transformation, a time-space domain settlement field is reconstructed, multi-stage early warning is triggered, a targeted reinforcement scheme is recommended, the soft soil foundation settlement monitoring precision and the engineering practicability are remarkably improved, and the method is suitable for construction, operation and maintenance of infrastructures such as high-speed rails and highways.

The invention relates to the technical field of coal mine safety, in particular to a water inrush and rock burst composite disaster risk multi-source judgment method which comprises the steps that four fields of original data of a target underground area are collected in real time, and the four fields comprise a stress field, a vibration field, an energy field and a seepage field; extracting multivariate feature indexes from the four-field original data to obtain four-field multivariate indexes; constructing a core composite index based on the four-field multi-element indexes, quantifying the coupling strength of water inrush and rock burst, and judging a disaster dominant type; and calculating a comprehensive risk index based on the four-field multi-element indexes and the disaster dominant type, and judging the risk level of the water inrush and rock burst composite disaster according to the comprehensive risk index. According to the invention, accurate identification and graded prevention and control of composite disasters are realized, and the accuracy and timeliness of early warning of mine disasters are significantly improved.

The invention provides an intelligent safety and stability assessment method, system and device for an underground cavern and a medium, and the method comprises the following steps: S1, building a three-dimensional geological model of the underground cavern according to initial geological exploration data; s2, multiple monitoring instruments are pre-buried in key parts of the underground cavern, and monitoring data are collected in real time; s3, constructing an underground cavern safety and stability evaluation model based on a deep learning algorithm; s4, inputting real-time monitoring data into an evaluation model, combining historical monitoring data and geological model information, analyzing and comparing with a three-dimensional numerical calculation result, adjusting geological parameters, performing reconstruction evaluation, and outputting a safety and stability level; and S5, according to an evaluation result, automatically generating early warning information and processing suggestions. According to the method, the problems of poor real-time performance and low data utilization rate of traditional evaluation under complex geological conditions are solved, and the intelligent level of construction safety monitoring of underground cavern groups such as hydropower stations and pumped storage projects can be effectively improved.

The invention provides a reservoir bank slope deformation body instability volume prediction method, which comprises the following steps: respectively acquiring earth surface displacement and rock mass internal deformation data through a millimeter wave radar and a tilt angle sensor, and after processing through an adaptive noise decomposition algorithm, identifying a key deformation area and generating a data set. And performing space-time alignment on the data by using the engineering coordinate system and the topological relation to generate a fusion matrix. And reconstructing a potential slip crack surface geometric model in combination with slip crack surface features of historical cases, and calculating instability volume probability distribution by adopting Monte Carlo simulation. And finally, inputting the multi-dimensional data into the space-time prediction model, and outputting an instability volume prediction result with probability distribution. According to the invention, the accuracy and reliability of the prediction result can be improved, and scientific basis and technical support are provided for safety monitoring and disaster early warning of the reservoir bank slope.

The invention provides a cooperative early warning method, system, equipment and medium for deformation stress of soft soil around a pile, and relates to the technical field of underground engineering, and the method comprises the steps that monitoring data of the soft soil around the pile are obtained based on monitoring points, and the monitoring points comprise pile body monitoring points and soil body monitoring points; feature extraction is conducted on the monitoring data, and monitoring indexes reflecting pile periphery soft soil deformation and stress evolution are obtained based on information contribution degree difference and sensitivity selection; performing model construction based on the monitoring data and the monitoring indexes, and obtaining a deformation-stress collaborative map of the soft soil around the pile by considering risk assessment and spatial heterogeneity; and on the basis of the deformation-stress collaborative atlas, abnormal recognition of the soft soil around the pile is carried out, an abnormal area is obtained through embedded learning and clustering analysis, graded early warning is carried out according to the abnormal area, and an early warning result of the soft soil around the pile is obtained. The problem that an existing early warning method for the soft soil around the pile lacks dynamic sensing and combined early warning in the pile-soil interaction process is solved.

The invention provides a rock damage evaluation method and device, and the method comprises the following steps: carrying out a compression test on a rock sample until the rock sample is damaged; treating the damaged rock sample to obtain a multi-scale damage fractal dimension of the damaged rock sample; based on the multi-scale damage fractal dimension, calculating a weight coefficient of each scale fractal dimension to the damage of the rock sample through an analytic hierarchy process; constructing a multi-scale rock damage evolution fractal model based on the weight coefficient; and evaluating the damage degree of the rock to be measured based on the rock damage evolution fractal model. The defect that the rock damage degree is determined from a single scale is overcome, rock damage can be more comprehensively and accurately quantified, long-term rock damage and stability evolution are effectively predicted, and reference is provided for comprehensively and accurately representing the rock damage degree and long-term evolution.

The invention discloses a grating dam safety evaluation and design method and structure based on debris flow blocking degree. Wherein the safety assessment method comprises the following steps: S100, calculating the safety of the debris flow on the basis of the solid matter concentration of a debris flow susceptible area, the particle size value corresponding to the accumulated content of 95% in a full particle size grading curve, the channel average gradient, the channel average width and the primary debris flow scale in the section range of the grating dam, the minimum particle size value of the maximum boulder in the drainage basin and the opening width of the grating dam; calculating a critical blocking judgment coefficient according to the correlation value of the height of the grating dam, the angle of the wedge-shaped structure and 60 degrees and the correlation value of the total amount of debris flow solid substances and the reservoir capacity of the wedge-shaped beam type grating dam; and S200, evaluating the safety of the grating dam based on the critical blocking discrimination coefficient. The evaluation and design method and structure incorporate the relative relation between the debris flow scale and the dam body storage capacity, meanwhile, the influence on active structure parameters such as wedge-shaped flow guide is quantified, and the blocking state prediction accuracy of the grating dam in actual operation is improved to a certain degree.

The invention belongs to the field of asphalt mixture performance analysis, and particularly discloses a fatigue performance analysis method for an asphalt mixture of an asphalt pavement, which comprises the following steps of: synchronously acquiring a dynamic strain field and a temperature field in a material by fusing an embedded sensor in a paving and rolling construction process; a temperature-strain coupled fatigue damage evolution model is combined to construct an on-line fatigue performance analysis system oriented to the whole construction process, so that a complex heat-force coupling environment and a non-uniform compaction process in actual paving operation are effectively restored; scale effect deviation and boundary condition distortion caused by difference between laboratory test piece preparation and on-site working conditions are remarkably reduced, and meanwhile, in the online detection process of the fatigue performance of the asphalt mixture, instant quantitative judgment of the performance state of the pavement structure is realized by positioning a damage remarkable overrun area; and the in-situ monitoring capability on the initial fatigue damage is fully reflected, so that the abnormal strain accumulation process before microcrack initiation can be captured.

The invention discloses a cross-scale rock elastic mechanical parameter measurement method and system, and relates to the technical field of rock measurement, and the method comprises the following steps: obtaining nano-scale rock elastic mechanical parameters and micro elastic-plastic deformation of rock through a nanoindentation experiment, so as to construct a molecular dynamics model of the rock; according to the molecular dynamics model of the rock, using an inclusion homogenization theory to upgrade the rock elastic mechanics parameters of the nanoscale to the rock elastic mechanics parameters of the centimeter scale, so as to construct a rock elastic mechanics parameter conversion model, and using environmental data in an in-situ environment for correction; and inputting the nano-scale rock elastic mechanical parameters into the corrected rock elastic mechanical parameter conversion model to obtain centimeter-scale rock elastic mechanical parameters. According to the invention, centimeter-scale rock elastic mechanical parameters in a deep stratum in-situ environment can be accurately measured.

The invention discloses a heavy traffic asphalt pavement damage evolution prediction system, and relates to the technical field of road engineering, and the system comprises a data acquisition module which is used for obtaining continuous multi-frame time sequence images of pavement cracks, a vehicle-mounted axle load spectrum and environment temperature and humidity data; the image processing and space-time modeling module is used for performing multi-scale fractal processing and dynamic time warping on the time sequence image and calculating a cross-scale fractal dimension sequence; the material performance association module is used for establishing and updating a probability association model of the fractal dimension and the shear modulus in real time according to the test data of the dynamic shear rheometer; the multi-physics field data fusion module is used for performing multi-physics field feature fusion through the fractal attention network to generate a multi-physics field collaborative damage correction factor; and the damage prediction and early warning module is used for predicting a fractal dimension growth trend through a fractal domain adaptive transfer learning algorithm, and outputting damage evolution early warning based on a viscoelasticity phase consistency verification result.

Providing a method for assessing the impact of fragile structures on large-scale fracturing in deep thermal reservoirs "Solution: Based on a precise depiction of the fragile structure of the formation and a study of its mechanical properties, the spatial distribution of the structure is determined, well locations and networks are arranged, fracturing zones are selected, and the fracturing suitability of the formation is comprehensively evaluated. Furthermore, a thermal-fluid-solid coupled damage model and a thermal-fluid-solid-chemical coupled damage model are established to study the activation conditions of the original fragile structure surface, and the fluid filtration characteristics of the structure and the maximum discharge volume that can be safely fractured are evaluated. Based on this, triaxial fracturing physical simulations and numerical simulations are carried out to clarify the influence laws of the fragile structure surface on the expansion and seepage flow of fracture cracks, and to clarify the influence mechanism of the fragile structure on large-scale fracturing of the formation under high temperature and pressure conditions."

The invention discloses a geotechnical engineering slope deformation monitoring method and system. The method comprises the following steps: acquiring multi-modal image data, enhancing the weak deformation area contrast of the multi-modal image data by using a CLAHE algorithm, extracting gradient edge information through a Sobel operator, and filtering laser radar point cloud noise based on VMD; capturing a bidirectional dependency relationship of a time sequence based on a BiLSTM bidirectional long short-term memory network, and dynamically allocating weights of different time steps and spatial positions through an attention mechanism; optimizing hyper-parameters of the hybrid prediction model by using a GJO Golden Litsea Optimization algorithm to obtain a target hybrid prediction model; and inputting the feature image data into the target hybrid prediction model for prediction, generating a risk probability thermodynamic diagram, and positioning the position of the potential slip crack surface of the slope according to the risk probability thermodynamic diagram. And reliability and accuracy of geotechnical engineering slope image data analysis are improved.

The invention relates to the technical field of coast engineering, in particular to an estuary sandy coast erosion and deposition simulation system based on the coupling effect of flood peak runoff, waves and tide, which comprises a training data generation module, an intelligent agent model construction module, a dynamic prediction engine module and a scene evaluation module. The training data generation module is used for outputting a hydrodynamic state field, a wave characteristic field, a bed surface shear stress field and a bed surface elevation variable quantity by utilizing a traditional numerical model to construct a training data set; the intelligent agent model building module is based on a deep learning network and introduces physical constraint loss function training to obtain an intelligent agent model; the dynamic prediction engine module loads the trained deep learning network to realize bed surface elevation variation prediction and update terrain boundary conditions; and the scene evaluation module executes erosion and deposition evolution simulation according to different hydrological boundary condition combinations and extracts terrain evolution data to quantitatively evaluate the coast stability and the channel deposition risk. The invention relates to the field of estuary dynamic landform simulation and coast engineering.