25887 results about "Geotechnical engineering" patented technology

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 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 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 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 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 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 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.

The invention relates to the technical field of geological reservoirs, in particular to a reservoir microcosmic connectivity characterization method based on pore throat boundary intelligent identification, which comprises the following steps of: performing threshold segmentation processing on a rock casting body slice by using image analysis software, and depicting partition images of pore throats and skeleton particles; based on the partition image, combining image analysis software to measure and extract the diameter, perimeter and area of the pore throat, and calculating quantitative parameters of the pore throat structure; constructing a one-dimensional Gaussian distribution model of the nuclear magnetic logging of the reservoir; based on a one-dimensional Gaussian distribution model, establishing a Gaussian collaborative factor for pore structure evaluation; based on the quantitative parameters of the pore throat structure and the established Gaussian collaborative factors, establishing a multi-factor evaluation mathematical method to establish a multi-element evaluation model of the pore structure; and performing multivariate nonlinear fitting on the porous structure multivariate evaluation model, the nuclear magnetic movable fluid saturation and the reservoir pressure measurement fluidity, and constructing a quantitative characterization model for characterizing the reservoir microscopic connectivity. According to the method, the microscopic connectivity of the reservoir can be accurately, rapidly and quantitatively evaluated.

The invention discloses a rock mass fracture multi-field coupling two-phase flow analysis method and a test system, and relates to the technical field of rock fracture temperature-seepage-stress coupling action mechanism research. The analysis method comprises the following steps: saturating a crack sample with a first dyeing fluid under a target temperature and pressure condition, and obtaining a single-phase saturated flow image of the crack sample; on the basis of the single-phase saturated flow image, through optical iteration inversion calculation, obtaining fracture opening two-dimensional distribution characteristics under a target condition; under the condition of the same temperature and pressure, displacing the first dyeing fluid with the second dyeing fluid or co-flowing with the first dyeing fluid to obtain a two-phase flow image of the crack sample; performing digital image processing on the two-phase flow image and the single-phase saturated flow image, and extracting phase distribution information of the second dyeing fluid; and performing fusion analysis on the phase distribution information of the second dyeing fluid and the fracture opening two-dimensional distribution characteristics, and calculating a two-phase flow structure and saturation distribution characteristics. According to the method, rock mass fracture two-phase flow process quantitative analysis can be realized under different temperature and pressure conditions.

The invention relates to the technical field of electric digital data processing, and particularly provides a method for judging seepage failure of an immersed roadbed under the action of repeated seepage, which comprises the following steps of: constructing a water-force-chemical coupling test mechanism, monitoring dynamic change of a permeability coefficient, a fine particle loss rate and three-dimensional reconstruction of a pore structure in real time through a sensor, and determining seepage failure of the immersed roadbed under the action of repeated seepage. A scanning technology is combined to quantify an evolution rule of a seepage path; key parameters such as seepage path fractal dimension, fine particle mobility and dynamic porosity change are extracted on the basis of an evolution rule, the weight of each index is determined by introducing fuzzy analytic hierarchy process, and a seepage failure comprehensive index is constructed; and establishing a time sequence prediction model, inputting a seepage failure comprehensive index and an environment variable, outputting a seepage failure probability, and dividing safety-critical-danger three-level early warning. According to the method, the limitation of a traditional static evaluation method is broken through, and the whole-process monitoring and prediction of seepage failure under the dynamic action of repeated seepage are realized; and the discrimination precision is obviously improved.

The invention discloses a high-pressure jet grouting pile construction optimization control method and system, and belongs to the technical field of pile foundation construction. According to the method, the pile body strength is predicted based on the XGBoost regression model, the HSIO hybrid swarm intelligent optimization algorithm is combined with the artificial bee colony algorithm and the seathead optimization algorithm, the construction parameter combination is dynamically adjusted, and optimal matching of the target strength and the real-time construction state is achieved. The method solves the problems of parameter setting deviation and non-uniform pile forming quality caused by the fact that traditional construction depends on artificial experience, is particularly suitable for high-precision construction requirements under complex geological conditions (such as karst areas and deep and thick sludge layers), remarkably improves the pile body strength stability, construction efficiency and quality controllability, and reduces the construction cost. And meanwhile, material waste and personal error risks are reduced.

The invention belongs to the technical field of mine monitoring, and particularly relates to a multi-field joint simulation method for mining-induced fractures of top and bottom plates of a gas outburst mine. Comprising the following steps: S1, determining development heights of a working face water flowing fractured zone and a caving zone and depth characteristics and evolution laws of a floor failure zone by adopting various in-situ space-time monitoring technologies; s2, constructing a numerical model based on mechanical parameters actually measured by engineering, and obtaining an upper layer overlying strata damage simulation result; s3, establishing a parameter correction model, obtaining a corrected simulation result, and applying the corrected simulation result to overlying strata failure simulation after full-layer mining after the actual measurement precision is met; s4, collecting overlying strata damage data of all fully mechanized coal mining faces in the mining area or the region, fusing the corrected numerical simulation results, and analyzing to obtain a regression prediction model of the height of the water flowing fractured zone; and S5, collecting overlying strata failure data of each fully mechanized coal mining face in the mining area or the region, fusing the corrected numerical simulation results, and analyzing to obtain a regression prediction model of the floor failure zone height. The invention creates a numerical simulation method for the mining process and overlying strata failure evolution.

The invention discloses a foundation settlement early warning method and system based on an intelligent algorithm, and relates to the technical field of settlement early warning. During operation of the system, through combined use of various sensors, foundation settlement related data from multiple sources are collected and processed and fused in real time, foundation settlement is predicted through the intelligent algorithm, and the early warning effect is achieved. The settlement risk of different areas is evaluated by combining a space-time big data analysis technology, a settlement risk index GSI is calculated, an early warning grade is output, early warning decision making is carried out according to a prediction result and a set dynamic threshold value, the severity of the settlement risk is judged and classified, a system automatically generates an early warning report, and once early warning is triggered, the early warning is automatically carried out. The system automatically starts an emergency response scheme, dynamically adjusts reinforcement and intervention strategies according to the actual change of foundation settlement, provides a real-time visual interface of settlement data and early warning information, and displays the settlement state, the early warning level and historical data.

The invention relates to the technical field of mine safety monitoring, in particular to an anti-shielding real-time deformation monitoring method and system for roof fall and wall caving disasters. The method comprises the following steps: extracting a bounding box and a mask of a discontinuous region from roof caving and rib spalling point cloud data, generating complete point cloud data, and analyzing a preliminary deformation index; extracting a track list of the shielding target, a prediction shielding area, a deformation trend and a deformation prediction value; in combination with the bounding box, the mask and the initial deformation index, obtaining a displacement vector and curvature change of the repaired missing region; and in combination with the trajectory list, the predicted shielding region and the deformation characteristics after compensation completion of the initial deformation index, obtaining a compensated and corrected displacement vector and curvature change, and further evaluating a deformation state and an early warning level. The method combines shielding detection, dynamic object tracking, multi-view fusion and deep learning completion to realize anti-shielding deformation feature extraction, time sequence trend prediction and accurate early warning, and provides reliable technical support for mine safety production.

The invention discloses a deep learning-based middle-deep layer geothermal pipe group multi-field coupling simulation method, which comprises the following steps: carrying out numerical simulation cross mutual verification to obtain a middle-deep layer buried pipe heat pump system model, and carrying out system configuration by adopting a Monte Carlo method to obtain a first parameter environment set; screening the first parameter environment set according to a parameter environment function to obtain a second parameter environment set, performing data augmentation to obtain mid-deep layer geothermal pipe group simulation data, constructing a mid-deep layer geothermal pipe group multi-field coupling deep learning model, and obtaining simulation heat exchange data and prediction coupling heat exchange data; and adaptive grid optimization is carried out to obtain an optimized grid size, and the optimized grid size is adopted to adjust the mid-deep layer buried pipe heat pump system model to output the mid-deep layer buried pipe multi-field coupling model. According to the method, accurate and rapid simulation of the multi-field coupling process of the medium-deep geothermal pipe group can be realized under complex geological conditions, and the method has important practical significance for promoting large-scale development and utilization of medium-deep geothermal resources.

The support comprises an upper seat plate, a spherical crown lining plate, a middle steel lining plate and a lower seat plate, the upper seat plate is fixedly installed at the bottom of a beam bottom, the spherical crown lining plate is arranged between the upper seat plate and the middle steel lining plate, the middle steel lining plate is arranged between the spherical crown lining plate and the lower seat plate, and the spherical crown lining plate is fixedly installed on the lower seat plate. The lower seat plate is fixedly mounted at the top of a bridge pier, the bottom surface of the upper seat plate is fixedly connected with a first limiting ring through a first anti-shear pin, the first limiting ring abuts against the middle steel lining plate, the top surface of the lower seat plate is fixedly connected with a second limiting ring through a second anti-shear pin, and the second limiting ring abuts against the middle steel lining plate. In a normal use state, the slip surface adopts a large curvature radius and a small friction coefficient to provide smaller damping, reduce the acting force of the support on a bridge and reduce the lifting of a beam end, and in an earthquake state, the slip surface adopts a small curvature radius and a large friction coefficient to provide larger damping, so that the shock absorption and isolation effect of the support is improved; and displacement of the bridge under the earthquake condition is controlled.

The invention discloses a sandstone reservoir deep acidification long-acting permeation enhancement effect numerical simulation method, and relates to the technical field of rock reservoir acidification transformation processes, and the method comprises the steps: collecting real-time sensor data and geological exploration data of a sandstone reservoir, and making a preliminary acidification operation plan; according to the preliminary acidification operation plan, in combination with real-time data feedback, the preliminary acid liquor concentration, the preliminary injection rate and the preliminary acid liquor injection temperature are optimized, and acidification parameters are output; based on real-time acidification operation monitoring data and sampling feedback data, a multi-field coupling numerical model is constructed and calibrated, the long-acting evolution track of the permeability of the acidified reservoir is simulated, the effective permeation increasing period and the final permeation increasing amount are evaluated, and an acidification long-acting permeation increasing effect simulation report is output. According to the method, the real-time regulation and control capability of acidification operation is improved, a scientific basis is provided for evaluating the economic validity period of acidification transformation, and an innovative solution is provided for efficient development of a deep sandstone reservoir.

The invention discloses a concrete arch dam global structural mechanical parameter zoning rapid inversion method, and relates to the technical field of dam operation safety monitoring and management, and the method comprises the steps: building a dam body and foundation three-dimensional finite element model through finite element software according to engineering design and monitoring data, and building a foundation three-dimensional finite element model according to damming material mechanical parameter information; partitioning the three-dimensional finite element model, analyzing the sensitivity of mechanical parameters of each region, determining sensitive mechanical parameters influencing the deformation of the concrete arch dam, and carrying out self-adaptive intelligent sampling on the sensitive mechanical parameters according to a sensitivity analysis result, and constructing a deep learning agent model reflecting a nonlinear relationship between the sensitive mechanical parameters of the dam and the deformation of each monitoring point, and carrying out deep learning inversion on the elastic modulus of the dam body and the deformation modulus of the bedrock. According to the invention, the method can efficiently and accurately invert and determine the structural mechanical parameters of the arch dam in the actual operation period, and provides a good basis for the safety analysis of the dam.

The invention provides a method and system for predicting corrosion evolution of a main cable of a suspension bridge, and the method comprises the steps: dividing the main cable into a plurality of cable segments, collecting the non-real-time physical information of the cable segments, and constructing a cable segment-level data structure model; a multi-dimensional input vector is generated by utilizing the characteristics of structural stress, environmental exposure, bridge age, maintenance records and the like, and corrosion risk scoring is realized in combination with the trained XGBoost model; further constructing a multi-state corrosion evolution model based on a Markov chain, dividing the corrosion state into pitting, expansion, precursor and critical stages, and establishing a time evolution path; risk distribution is visually displayed in a corrosion thermodynamic diagram mode, and residual life prediction and early warning information is output in combination with a threshold strategy; according to the method, the limitation of dependence on a real-time sensor is broken through, active prediction can be completed based on historical and structural parameters under a passive condition, and the corrosion identification accuracy and early warning timeliness are effectively improved.

The invention provides a geotechnical engineering slope deformation monitoring method and system, belongs to the field of geotechnical engineering monitoring, and is used for solving the problems of low monitoring precision and poor early warning reliability caused by spatial-temporal dislocation of multi-source data, static geological parameters, poor swivel scene adaptation and no closed-loop optimization in related technologies. According to the method, multi-source deformation data, geological parameters and rotation characteristics are collected, the type and progress of a rotation are identified, multi-resolution hierarchical fusion (dynamic weight adaptive data credibility and environmental interference) and dynamic inversion geological parameters are performed after space-time alignment to construct a prediction model, model parameters and an early warning threshold are dynamically scheduled in combination with the rotation characteristics, and the prediction result is obtained. The precision is improved through closed-loop feedback optimization iteration, the system provides hardware support for the method, and precise monitoring and efficient early warning of slope deformation are achieved.