7469results about "Permeability/surface area analysis" patented technology

The invention provides an intelligent sewage treatment process optimization method and system. The method comprises the following steps: continuously collecting the flux attenuation rate, transmembrane pressure difference and pollutant spectrum data of a ceramic membrane, carrying out time sequence analysis, constructing a pollution accumulation dynamic model, and predicting a critical threshold value; when a threshold value is reached, triggering an ultrasonic cavitation device, adjusting high-frequency vibration to generate a microbubble group, stripping pollutants by utilizing shock waves, and calculating membrane flux recovery data; fusing the spectral data and the recovery data to extract an actual pollution stripping efficiency value, and comparing a theoretical value to obtain a difference proportion; if the actual value is lower than the theoretical value, the cleaning period is shortened, the fluid pressure is increased to strengthen the stripping effect, and meanwhile, dynamic model parameters are reversely corrected based on the pressure adjustment amplitude to form closed-loop regulation and control. According to the invention, intelligent prediction, self-adaptive cleaning and closed-loop optimization of ceramic membrane pollution are realized, the sewage filtering efficiency is improved, and the energy consumption and cleaning cost are reduced.

A porous media grouting test system and method taking temperature effects into consideration. The system comprises a porous media formation simulation model (1), a grouting system (2), a water level adjustment system, a formation temperature control system and a data analysis system, wherein the porous media formation simulation model (1) is used for simulating a porous media formation; the water level adjustment system and the formation temperature control system are used for simulating the conditions of different water saturation levels and different water temperatures and ground temperatures; and the data analysis system is used for comparing different time-series data collected by sensors such as a temperature sensor and a pressure sensor with data such as temperature data and pressure data that is obtained by means of coupled solving of a heat transfer equation and a momentum equation, so as to verify and analyze a grouting diffusion path. Free simulation of different water saturation levels is realized by means of a water level adjustment system, and simulation of different ground temperatures is realized by means of a formation temperature control system, thereby realizing the research on grouting diffusion under different water levels and different water temperatures and ground temperatures.

The invention discloses a concrete strength remote monitoring method and system suitable for a complex environment, and belongs to the technical field of civil engineering structure health monitoring. The remote monitoring method comprises the following steps: step 1, acquiring performance data of a concrete structure and related environmental factor data, and transmitting multi-source heterogeneous data to a data processing center in real time through a preset wireless communication protocol; step 2, constructing a five-dimensional tensor data structure, and realizing accurate mathematical expression of a complex coupling relationship between environmental factors and material characteristics through tensor decomposition; step 3, capturing nonlinear time-varying characteristics of concrete strength evolution; 4, quantifying the age effect through an intensity development rate index; step 5, based on the intensity development rate change trend, adaptively adjusting the data sampling frequency and monitoring the environmental condition fluctuation; and step 6, evaluating the safety state of the concrete structure in real time, and ensuring safe and reliable operation of the concrete structure in a complex environment.

The invention relates to the technical field of material detection, in particular to a building engineering material detection method and system. The method comprises the following steps: performing multi-area scanning on a building decoration wall coating through an ultrasonic scanner to obtain a wall coating sound wave data set, identifying non-uniform distribution of coating texture, then calculating density distribution difference of an inner coating and an outer coating between layers according to the coating texture data, and further performing quantitative simulation on water resistance permeation loss to obtain the water resistance permeation loss of the building decoration wall coating. The method comprises the following steps: acquiring water-resistant permeation loss data, then inferring a permeation mechanism periodic aging process of the coating on the basis of the water-resistant permeation loss data, detecting the tolerance performance of a coating material in combination with permeation mechanism aging data, acquiring material tolerance performance data, and comprehensively evaluating the quality and durability of the coating. According to the invention, the detection technology is optimized, so that the detection technology is more perfect.

The invention discloses a deep learning-based intelligent identification method and system for rock and soil mechanical parameters, and aims to accurately identify the elastic modulus, strength parameter and permeability coefficient of rock and soil and support the decision and design of engineering projects under complex geological conditions. And starting from data demand analysis, determining a parameter identification target and planning a field test layout. A basic data set is constructed by comprehensively collecting and integrating multi-source data including laboratory and field test data, remote sensing information and the like. The data is pre-processed and analyzed to remove noise and explore associations between the data. The method comprises the following core steps: constructing a rock-soil mechanical model by using a deep learning algorithm, and realizing high-precision inversion of parameters by defining and optimizing an objective function. And verifying an inversion result and carrying out uncertainty analysis. According to the method, an analysis result is fed back to engineering design adjustment and decision support, and scheme optimization is achieved. The model and strategy are dynamically adjusted through continuous monitoring and real-time data, and safety and high efficiency of engineering implementation are guaranteed.

The invention relates to the technical field of design analysis, in particular to a soft soil deep foundation pit earth excavation construction scheme planning method and system.The soft soil deep foundation pit earth excavation construction scheme planning method comprises the following steps that a three-dimensional geological model is built based on geological exploration data, and rheological parameters, shear strength parameters and permeability coefficients of all soil layers are extracted to serve as layering parameters; according to the layering parameters and preset supporting structure rigidity parameters, a soil body rheological rate compensation coefficient is calculated, and an earthwork block excavation scheme with the grading thickness difference is generated; and in the excavation process, the displacement rate and pore water pressure data of the supporting structure are collected in real time, and when a monitoring value exceeds a preset threshold value, a dynamic adjustment instruction of the block excavation scheme is triggered. According to the method, the layering thickness and the blocking form are intelligently controlled according to different sensitivity levels, the matching coping capacity for soft soil instability inducements is improved, and the limitation that a single physical parameter dominates in traditional blocking design is broken through.

The invention provides a dynamic monitoring method for a soil mass seepage field of a power transmission tower slope. According to the method, related data of the slope are acquired through multi-source data acquisition and technologies of pressure sensing and static pressure measurement, displacement monitoring, multi-sensor fusion, Beidou / GPS positioning, resistivity method exploration, soil moisture content monitoring and the like; fusing the collected multi-source data, analyzing the dynamic change of the seepage field by using a risk assessment model and a machine learning algorithm, and predicting the evolution trend of the seepage field; a lightweight model is deployed at a monitoring terminal to realize local rapid processing of data, alarm information is immediately sent out once an abnormal state is monitored, and scientific and reasonable decision support is provided for protection and treatment of a transmission tower slope according to early warning information in combination with a pre-made decision scheme; according to the invention, the accuracy and timeliness of transmission tower slope soil seepage field monitoring can be effectively improved, and the threat of landslide and other disasters to a transmission line is reduced.

A grouting simulation test system and method for high-temperature water-rich filled fractures. The grouting simulation test system comprises: a water head intelligent sensing and adjusting module, a fracture medium intelligent simulation module, a double-liquid grouting module, a data analysis module, and an intelligent control module. The fracture medium intelligent simulation module comprises a water bath circulation temperature control unit, a fracture model (11), and an opening degree adjustment unit. The water bath circulation temperature control unit is arranged on upper and lower sides of the fracture model (11). Circulating water is provided in the water bath circulation temperature control unit, and the temperature of the circulating water is controllable. The fracture model (11) is formed by combining a plurality of model units. The opening degree adjustment unit is connected to the water bath circulation temperature control unit above the fracture model (11) and is capable of raising and lowering the water bath circulation temperature control unit. The present test system can achieve the study of a grouting diffusion mechanism under the coupling action of two or more factors such as different slurry properties, dynamic water flow velocity, dynamic water temperature, fracture medium multivariate factors, medium temperature, and filling conditions.

The invention relates to the technical field of construction surrounding rock stability evaluation, discloses a tunnel surrounding rock stability evaluation method and system based on multi-physics field parameter inversion, and aims to solve the problems that an existing method is insufficient in data collaboration, high in parameter inversion multiplicity and poor in surrounding rock stability evaluation accuracy and timeliness. According to the scheme, the method mainly comprises the steps that an acousto-optic electromagnetic vibration drill multi-mode sensing array is arranged, and time-space synchronization is implemented; establishing a mutual interference entropy spectral density model to realize multi-physics field collaborative excitation and acquisition; a unified feature vector is obtained through data correction, feature extraction and weighted fusion; a joint inversion objective function embedded with rock physical constraints is constructed, a three-dimensional physical property parameter field is obtained through inversion, and a dynamic permeability field is calculated in combination with acoustic emission energy; and finally, dynamically updating the model by utilizing ensemble Kalman filtering, and obtaining a final risk probability based on updated parameters and seepage-uncertainty coupling correction. According to the method, the accuracy, the real-time performance and the reliability of the stability evaluation of the surrounding rock of the deep-buried tunnel are improved.

The invention provides a rainfall flood resource retaining structure displacement intelligent monitoring method, and relates to the technical field of data processing, and the method comprises the steps: obtaining a second source point cloud and a second target point cloud of a clay region, and building a spatial distribution map; calculating a global rigid transformation matrix based on the second source point cloud and the second target point cloud; performing rigid-non-rigid mixed registration according to the spatial distribution map and the global rigid transformation matrix to obtain a registered point cloud; calculating a corrected displacement field sequence based on the registered point cloud; and carrying out time-frequency domain analysis on the displacement correction factor and the corrected displacement field sequence, extracting a characteristic frequency and a damping ratio to construct a space-time incidence matrix, and generating a displacement data sequence containing geological parameter space-time variation characteristics. According to the invention, the precision and reliability of displacement monitoring are improved.

The invention discloses a building outer wall leakage detection method and system, and belongs to the technical field of wall leakage detection. The method comprises the following steps: acquiring infrared thermal imaging, laser point cloud and multispectral imaging data, and generating a three-dimensional visual model with temperature information after environment temperature compensation correction, three-dimensional modeling and data fusion; and then extracting temperature characteristic parameters to identify an abnormal region, screening a to-be-verified region in combination with the building construction node coincidence degree and geometric parameters, and finally determining a leakage position through comparison of multispectral characteristic extraction and a preset leakage characteristic library. The system realizes full-process automatic detection by applying the method. According to the invention, temperature signal conduction limitation caused by insulation layer obstruction is broken through, the problem of misjudgment caused by a thermal bridge effect is solved through multi-source data fusion and spectral feature analysis, and the precision and reliability of leakage detection are improved.

A disclosed leaky coaxial resonant sensor system and methods. In use, the system includes at least one split-ring resonator (SRR) embedded within a material of the component. The at least one SRR is formed from a composite material. Additionally, the at least one SRR is configured to resonate at a first frequency in response to an interrogation signal from a leaky coaxial cable antenna. In some aspects, each SRR may resonate at a first frequency in response to an electromagnetic ping when the composite material is in a first state, and may resonate at a second frequency in response to the electromagnetic ping when the composite material is in a second state. A resonant frequency of the composite material may be based on physical characteristics of the composite material.

The invention provides a high earth and rockfill dam digital twinborn model construction method, and belongs to the technical field of high earth and rockfill dam health monitoring, and the method comprises the steps: constructing a measuring point monitoring model based on sensor monitoring data; constructing a mapping model, and constructing a mapping model dynamic monitoring loss function for adversarial training by adopting a domain adaptive method; inputting predicted values of deformation monitoring effect quantity and osmotic pressure monitoring quantity of the measuring point monitoring model on the seepage process and the deformation process of the high earth and rockfill dam into the mapping model to obtain a digital twinborn model, and constructing an extreme working condition digital twinborn model based on the digital twinborn model; knowledge graph reasoning is combined with a dam slope stability coefficient to realize interaction of an extreme working condition digital twinning model and a solid model, and the high earth and rockfill dam deformation-seepage digital twinning framework is proposed for the first time on the basis of deep learning and finite element methods so as to realize a more economical, efficient and reliable monitoring scheme. And technical support is provided for health monitoring of the high earth and rockfill dam structure in the future.

The invention provides a river levee flood control pile foundation stress analysis method and system, and relates to the technical field of river levee flood control pile foundation stress analysis. Multi-channel sensors are arranged on the pile top, the pile side and the pile end, and the sampling frequency is automatically switched along with the flood stage; inverting the soil saturation based on displacement and pore pressure change, dynamically correcting the permeability coefficient and the effective stress, and outputting a space-time coupling parameter matrix; determining a hazard source for the monitoring point, constructing an elliptical search domain by taking the hazard source as a center, and recursively incorporating abnormal points to form a risk area; a seepage-structure full-coupling finite element model is established in the risk area, the outside of the area is simplified through an equivalent spring boundary, and a pile foundation stress-strain field and a safety coefficient are calculated through self-adaptive time step control; and finally, generating a risk report according to safety factor classification, marking a high-risk area, automatically improving the sampling frequency and triggering early warning.

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.

A grading evaluation method for high-maturity gas source rock based on hydrocarbon generation and expulsion simulation includes: establishing a change curve of hydrocarbon generation yield based on a hydrocarbon generation thermal simulation experiment; establishing a change curve of hydrocarbon expulsion of source rocks based on a principle of material balance; determining a classification boundary of source rocks based on the change curve of hydrocarbon generation yield and the change curve of hydrocarbon expulsion of source rocks; and obtaining a spatial distribution of different types of source rocks by combining logging interpretation according to the classification boundary of source rocks. In the method, the evaluation model and change curve of hydrocarbon generation yield, retained gas volume and hydrocarbon expulsion volume of source rock are established, and the classification standard of gas source rock at different maturity stages is determined by combining the change curve of hydrocarbon expulsion efficiency under different maturities.

The invention provides a rock-soil body multi-field coupling intelligent monitoring system comprising a multi-field sensing device configured to monitor parameters of a deformation field, a seepage field, a temperature field and a stress field of a rock-soil body; the edge calculation and transmission device is configured to perform preprocessing and real-time transmission on the multi-field sensing data; and the intelligent decision-making device is configured to analyze the preprocessed data based on a multi-field coupling model and generate disaster early warning information. According to the rock-soil body multi-field coupling monitoring system and method provided by the invention, synchronous monitoring of a deformation field, a seepage field, a temperature field and a stress field is realized through the multi-field sensing device; real-time data processing is performed in combination with an edge calculation and transmission device, and a dynamic early warning mechanism is established by using an intelligent decision-making device, so that the technical problems of multi-field data space-time correlation failure, insufficient multi-source data fusion precision and poor early warning mechanism adaptability are effectively solved, and the geological disaster early warning method has the remarkable advantages of improving the geological disaster early warning accuracy and timeliness.

The invention provides a marine unfavorable geology reef limestone grouting strength prediction method based on a pore structure. The method comprises the following steps: calculating a reef limestone rock pore value of a reef limestone rock pore volume accounting for a reef limestone rock mass volume; performing size classification on the equivalent diameters of the communicated pores in the reef limestone, and calculating the volume ratio of each type of communicated pores; calculating the pore sphericity of the pore particles according to the pore particle surface area and the pore particle volume; classifying the pore particles according to the pore sphericity, and calculating the sphericity ratio of each type of pore particles; calculating a seepage coefficient based on the pore value of the reef limestone rock, the volume ratio of various communicated pores and the sphericity ratio of various pore particles; calculating the flow of the slurry flowing in the reef limestone rock under the action of different pressures according to the seepage coefficient; and calculating the tensile strength of the reef limestone rock based on the flow before and after grouting. Through accurate permeability analysis, the construction risk and cost are reduced, and meanwhile the bearing capacity of the foundation base is improved.

The invention relates to the technical field of detection, in particular to a thermal insulation performance detection system and method of a thermal insulation gel material.The method comprises the steps that surface temperature data and internal pore distribution data of a thermal insulation gel material sample are obtained and subjected to dynamic heat flow coupling treatment, and a dynamic coupling feature sequence is obtained; constructing a multi-dimensional thermal impedance tensor based on the dynamic coupling feature sequence and carrying out regularization constraint to obtain a thermal impedance time sequence; extracting a nonlinear thermal shielding index in the thermal impedance time sequence, constructing a high-dimensional feature vector, and generating a probability density distribution parameter set; and according to the probability density distribution parameter set, constructing a multi-dimensional input data set and carrying out iterative optimization, calculating a confidence interval of the thermal insulation performance boundary value, evaluating the thermal insulation performance grade of the thermal insulation gel material based on the confidence interval, and generating a performance evaluation parameter report. The comprehensive heat insulation effect of the heat insulation gel material in actual use can be more comprehensively and accurately reflected.

The invention relates to the technical field of sewage pipe network diagnosis, evaluation and detection, and discloses a sewage pipe network external water inflow and infiltration partition screening method based on gridding monitoring, which comprises the following steps: dividing monitoring points in a sewage pipe network, collecting dynamic flow and water quality data, calculating pollutant load and daily flow weighted average concentration, and calculating the water quality of the sewage pipe network. And determining a subarea inflow and infiltration risk level by comparing the concentrations of adjacent upstream and downstream monitoring points. And when the partition infiltration level is a second level, calculating the external water infiltration amount by utilizing a chemical mass balance model and upstream and downstream pollutant loads, and establishing an optimization positioning model and coupling an intelligent optimization algorithm by taking the infiltration amount as a constraint to realize external water infiltration point location positioning. According to the method, low-cost external water inflow and infiltration screening and positioning under the condition of continuous water operation of the sewage pipe network are realized.

The invention discloses a penetration discrimination method and system suitable for a double-layer dam foundation, and the method comprises the steps: S1, obtaining the geological parameters of a double-layer dam, and forming a geological parameter set; s2, constructing a seepage numerical model of the double-layer dam foundation, simulating the seepage field distribution condition of the double-layer dam foundation at each grid node, and obtaining seepage field data; s3, grid node seepage force is calculated, and a potential seepage failure area is determined; s4, monitoring pore water pressure and seepage flow changes of the preset monitoring points in the potential seepage failure area; s5, constructing a seepage failure judgment model, and outputting a seepage judgment result; and S6, performing grading processing according to the judgment result of seepage failure, and outputting grade seepage early warning information through a seepage grading model. According to the method, judgment, real-time monitoring and graded early warning of seepage damage of the double-layer dam foundation are achieved, and the safety of the heterogeneous double-layer dam is guaranteed.

The invention discloses a method and a device for testing moisture migration characteristics of frozen soil under low-temperature nuclear magnetic triaxial seepage, and relates to the technical field of frozen soil testing. In order to solve the problems that in the prior art, compatibility control of freezing and seepage cannot be achieved, and whole-process evolution of frozen soil moisture migration characteristics is difficult to dynamically capture, the scheme comprises the following steps that the real confining pressure, axial pressure and seepage speed of the environment where a soil sample is located are simulated; collecting a nuclear magnetic resonance image and an overall and layered T2 spectrum of the soil sample before freezing under the action of seepage; gradually freezing the soil sample based on different temperature gradients, and collecting a nuclear magnetic resonance image and an overall and layered T2 spectrum of the soil sample under the seepage and freezing coupling action in real time; data are collected according to the whole soil sample freezing process, and the evolution law of water migration characteristics in the soil body freezing process is analyzed. According to the invention, the whole-process, visual and nondestructive detection is realized, and the whole-process evolution rule of water migration characteristics such as unfrozen water content and pore cracks in the frozen soil under the seepage and freezing coupling action can be accurately captured.

The invention relates to the technical field of petroleum and natural gas engineering, in particular to a method, a system and equipment for acquiring artificial fracture parameters. The method comprises the following steps: acquiring initial fracture form data through a core experiment, wherein the initial fracture form data comprises the straightness, the branch number and the roughness parameter of a fracture; performing verification analysis based on morphology on the initial fracture morphology data, and adding morphological characteristics of irregular fractures to obtain fracture morphology data; according to the fracture form data, fracture conductivity simulation based on proppant distribution and stratum conditions is carried out, preliminary evaluation is carried out, and fracture conductivity data are generated; and carrying out dynamic adjustment processing based on crack pressure on the crack form data by using micro-seismic imaging to generate crack three-dimensional form model data. Through systematic core experiment and strict morphological verification, the obtained data has higher accuracy and reliability, and firm data support is provided for subsequent flow conductivity analysis and model construction.

The invention discloses an activated carbon pore regulation and control method and monitoring equipment, and belongs to the technical field of spectrum analys.The method comprises the steps that on the basis of a probability prediction model, spectrum scanning frequency is dynamically adjusted, and real-time global spectrum collection is carried out; the method comprises the following steps: setting a self-adaptive threshold value, extracting time sequence slope and acceleration by a dynamic sliding window, generating a time sequence change matrix, judging an abnormal spectrum, screening and analyzing unexpected signals, realizing accurate identification of known and new unexpected signals, and reversely deducing molecular configuration parameters through a characteristic peak position interval. Calculating a matching degree difference value between the pore size and the molecular configuration, and carrying out matching analysis to ensure the suitability analysis accuracy of the pore characteristics and the pollutant molecules; according to the matching degree difference value, porosity gradient regulation and control are carried out, real-time monitoring is carried out to verify the regulation and control effect, self-evolution is achieved, and the regulation and control efficiency and precision are continuously improved.

The utility model discloses a system for large-range high-efficiency detection of a building facade. The system comprises a wall-climbing robot and a remote controller, the wall-climbing robot comprises a robot body, a climbing module, a propeller propelling module, a detection module and a control module, the control module is in communication connection with the remote controller; and the control module is suitable for controlling the climbing module to drive the wall-climbing robot to climb or descend along the rope, controlling the propeller propelling module to propel the wall-climbing robot to be tightly attached to the building facade and controlling the detection module to carry out large-range damage detection on the building facade in the climbing or descending process of the wall-climbing robot under an instruction of the remote controller. According to the utility model, the wall-climbing robot is controlled to climb up and down stably on the vertical facade through the remote controller, and the large-range detection of the crack damage of the building facade is realized.

The invention discloses a mine water recharge reservoir scaling trend prediction, scale removal and permeation enhancement method, and the trend prediction method comprises the steps: carrying out the conventional physicochemical index analysis of the water quality of mine water and a monitoring well according to the hydrogeological information of a recharge reservoir, and calculating the scaling trend of the mine water recharge reservoir based on a Retino index method and the relative saturation R.S. The scaling conditions of carbonate, sulfate and silicate are rapidly judged respectively; when scaling occurs, the ion concentration change on a path is revealed through a Transport module and an Equilibrium Phases module in the PHREEQC software, and verification is carried out through a measured value of a monitoring well; and then according to the mineral dissolution precipitation reaction and the percentage of the reservoir rock sample composition, calculating the reaction dose and the void ratio so as to formulate a mine water recharge reservoir permeation enhancement optimization scheme. According to the method, the scaling trend of the mine water recharge reservoir can be effectively predicted, the recharge process is monitored, and continuous operation of deep well recharge sealing work of mine water is facilitated.

The invention provides a multi-dimensional adsorbent performance evaluation method, and belongs to the technical field of performance evaluation, and the method comprises the following steps: carrying out a first test on an adsorbent, recording the mass change of the adsorbent after each cycle, and evaluating the adsorption performance of the adsorbent to obtain a first test result; and carrying out a second test on the adsorbent to determine the anti-sintering capability and the cycling stability of the adsorbent so as to obtain a second test result. Microscopic form change, influence condition and crystal structure of the adsorbent before and after the test are observed, and microscopic characterization of the adsorbent is obtained. And performing multi-scale simulation on the adsorbent according to the microscopic representation, and performing life cycle evaluation on the adsorbent by using a simulation result to obtain a life cycle evaluation result. And an optimization direction is provided for comprehensive performance evaluation of the adsorbent. The invention aims to realize an efficient and low-cost carbon capture technology and promote effective utilization of solid waste resources, and provides a systematic evaluation method to promote the development of the carbon capture technology.

The invention provides a method for determining a carbon dioxide-water two-phase seepage relative permeability curve and a method for determining reservoir porosity and permeability evolution under the action of carbon dioxide. The method for determining the relative permeability curve of the carbon dioxide-water two-phase seepage comprises the following steps: acquiring the dry weight of a rock core and the mass of the rock core saturated with formation water; under the simulated formation temperature and pressure condition, constant-speed injection of different kinds of fluid composed of saturated carbon dioxide formation water and gas-phase carbon dioxide with different flow ratios is sequentially carried out into a saturated water core; the pressure difference between the two ends of the rock core, the gas-phase carbon dioxide flow and the saturated carbon dioxide formation water flow after the injection pressure is stable in the injection process of various fluids are obtained; then the rock core is blow-dried with CO2, and the mass of the rock core blow-dried with CO2 is obtained; based on the obtained data, the water-phase relative permeability, the gas-phase relative permeability and the water saturation of the rock core are determined respectively when various kinds of fluid are injected, and then the carbon dioxide-water two-phase seepage relative permeability curve of the rock core is determined.

The invention relates to the technical field of alpine sand soil moisture leakage estimation technologies, and particularly discloses an alpine sand soil moisture leakage estimation method which comprises the following steps: S1, multi-source data acquisition: acquiring 0-110cm layered soil moisture content and temperature data by using a cold-resistant soil hydrothermal sensor array, and calculating the moisture content and temperature data of the layered soil; synchronously acquiring Sentinel-2 remote sensing data to extract vegetation coverage and land surface temperature, and recording regional freezing and thawing cycle times and biological crust coverage types; s2, key parameter inversion: calculating a permeability coefficient correction factor kFTC = alpha * N (1 / 2) through a multi-expression programming model based on the freezing and thawing cycle number N. According to the method for estimating the soil moisture leakage amount of the high and cold sand land, the limitation of a traditional model based on steady-state water flow and empirical parameters is broken through by quantifying the dynamic effect of freezing and thawing cycles on the porosity of a 30-80 mm soil layer and the water blocking effect of 23.41%-30.39% when the biological crust coverage degree exceeds 30%; and the influence of the low-temperature freezing and thawing cycle and the biological crust on the leakage mechanism of the high and cold sand land is accurately depicted.

A while-drilling multi-element signal sensing and early warning method for coal rock dynamic disasters comprises the steps that in the early stage of coal seam recovery, bedding gas extraction drilling is utilized, while-drilling signals generated in the drilling period of each drill rod are collected in real time through a multi-parameter sensing system integrated with a drilling machine, and while-drilling data are obtained based on the while-drilling signals; constructing a mechanical parameter inversion model, and calculating the compressive strength of the coal rock mass; a gas parameter inversion model is constructed, and gas pressure and coal rock mass permeability are obtained through decoupling; according to the method, coal rock mass compressive strength, gas pressure and coal rock mass permeability are used as core indexes, a spatial interpolation method is adopted to realize continuous representation of disaster risk distribution of a whole area, and a comprehensive risk index is established accordingly; and according to the value range of the comprehensive risk index, further quantifying the risk level of the coal and rock mass dynamic disaster based on the comprehensive risk index. According to the method, real-time sensing, accurate inversion and active prevention and control of coal rock dynamic disasters can be realized, and the problems of low detection accuracy, poor real-time performance, insufficient overall performance and the like in the traditional technology can be effectively solved.