2798 results about "Numerical modeling" patented technology

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.

A federated distributed computational system enables secure biological data analysis and genomic medicine through hybrid simulation capabilities. The system implements a hybrid simulation orchestrator that coordinates classical numerical simulations with machine learning models for biological system analysis, while maintaining secure cross-institutional data exchange. The architecture coordinates multi-scale spatiotemporal synchronization across computational nodes, with each node containing local processing capabilities for biological data analysis and privacy preservation protocols. The system implements cellular machinery assembly analysis, real-time patient data integration, and multi-modal image integration with spatiotemporal health data annotation. Through a distributed graph architecture, the system enables cross-species genetic analysis, environmental response modeling, and multi-scale tensor-based data integration with adaptive dimensionality control. The system implements real-time therapeutic response prediction through multi-modal data analysis, enabling research institutions to collaborate on complex biological analyses while maintaining strict data privacy controls.

The invention discloses a high-temporal-spatial-resolution refined flow field reconstruction method, device and equipment and a medium, and relates to the technical field of ocean current reconstruction, and the method comprises the steps: carrying out the normalization and temporal-spatial alignment of satellite remote sensing, buoy observation and numerical simulation data; based on the alignment data, performing rehearsal on the unstructured nested grid through an FVCOM model, and then dynamically encrypting the grid according to the flow field gradient and generating a background flow field; inputting the background flow field into a PINN-GAN combined framework, and outputting a refined flow field through physical constraint loss and double-discriminator adversarial training; and scheduling a calculation task by adopting a heterogeneous accelerator, verifying the reconstructed refined flow field in real time, and performing feedback optimization. Through generation of the background flow field and refinement reconstruction, the ocean current flow field with high temporal-spatial resolution can be reconstructed efficiently and accurately.

The invention discloses an urban inland inundation water recession process numerical simulation method and system based on physical-data fusion, and belongs to the technical field of urban flood control and intelligent water affairs. A hydraulic model and a data driving model are fused, a prediction result is dynamically weighted through gating attention, and real-time correction is performed by using Kalman filtering; the method comprises the steps of multi-source data fusion and enhancement, wherein data collection and processing are carried out, space-time alignment is achieved, and feature construction is carried out; mechanism and mathematical double-engine collaborative prediction: collaborative prediction is carried out based on a physical model engine and a data driving engine, and adaptive fusion is realized; online reasoning and dynamic correction, including Kalman filtering dynamic correction and extreme scene emergency processing; and performing model evaluation and iteration. According to the method, the problem of high-precision prediction of the recession time and the ponding range in a complex urban environment is solved, the generalization ability of the model in non-seen scenes such as pipeline blockage and rainstorm extrapolation is improved, and a reliable decision basis is provided for urban inland inundation emergency scheduling and drainage facility optimization.

A stability assessment method of roadway surrounding rock includes: obtaining actual stratum rock parameters; establishing a two-dimensional geological model through numerical simulation based on a drill core columnar diagram and the actual stratum rock parameters; changing influencing factors, and recording amounts and acceleration values of deformation of roadway sidewalls, and whether failure occurs to obtain dynamic response characteristics of roadway surrounding rock, combining the changed influencing factors and the dynamic response characteristics as labels to obtain a dataset, and obtaining multiple datasets including the dataset; dividing the multiple datasets into a training set and a validation set, inputting the training set into a PSO-BP neural network and a GA-SVM deep learning model to obtain a preliminary stability assessment model, and adjusting and validating the preliminary stability assessment model by the validation set to obtain an optimized stability assessment model; and using the optimized stability assessment model to assess roadway stability.

The invention discloses an internal wave characteristic field information rapid prediction method based on deep learning, and belongs to the technical field of ocean internal wave detection. According to the method, rapid prediction is carried out on the basis of traditional numerical simulation data by using deep learning, so that the efficiency of inner solitary wave prediction is remarkably improved; through multi-channel coupling learning and an iterative prediction strategy, the inner wave field prediction achieves the effect of high precision and high efficiency. Meanwhile, in combination with high-resolution numerical mode data, the consistency of a model prediction result and a physical process is ensured, and rapid extension period prediction of a solitary wave characteristic field in the ocean is realized while low error and high relevancy are kept. The method is suitable for application scenes of real-time ocean internal wave monitoring and early warning and the like, and can be widely applied to the technical fields of ocean environment monitoring and early warning, intelligent ocean observation, ocean engineering safety and the like.

The invention discloses a boiler combustion optimization method and device based on CFD numerical simulation and a medium, and belongs to the technical field of boiler combustion simulation. The method comprises the steps of obtaining operation parameters and historical operation data of a boiler combustion system; processing the data based on a three-dimensional modeling algorithm to generate a three-dimensional combustion model of the combustion area of the boiler; the three-dimensional combustion model is processed based on a CFD numerical simulation algorithm, and multi-physical field coupling data of the combustion process is generated; processing the multi-physical field coupling data and the historical operation data based on a multi-objective optimization algorithm to establish a combustion parameter optimization model; adjusting the ratio of the air speed at the inlet of the combustor to the fuel flow to update the model and optimize combustion parameters; verifying whether the optimized combustion parameters meet constraint conditions or not; and when the constraint conditions are met, finally optimized combustion parameters are output. By means of the method, multi-physical-field dynamic coupling optimization in the boiler combustion process is achieved, and the purposes of synchronously improving the combustion efficiency and the pollutant control effect are achieved.

The invention discloses a three-dimensional wind field spatial-temporal feature reconstruction and efficient prediction method, and relates to the field of spatial-temporal feature reconstruction and efficient prediction. Constructing a three-dimensional terrain computational domain based on the digital elevation model of the target mountain region, performing multi-scene numerical simulation by adopting a fluid mechanics method or a mesoscale meteorological model, generating a wind field training data set, and constructing and training a wind field spatial feature mapping model; training a wind speed and wind direction short-time prediction model based on the actually measured data set; inputting the monitoring data obtained in real time into the wind speed and wind direction short-time prediction model to obtain a future wind speed and wind direction prediction value of each monitoring station; and inputting the wind speed and direction predicted values into the wind field spatial feature mapping model to obtain the mountain overall wind field distribution of the target mountain region at the future moment. By constructing an'actual measurement-simulation-modeling-prediction-reconstruction 'integrated technical framework, high-temporal-spatial-resolution short-time prediction from observation of local wind speed and wind direction to the overall three-dimensional wind field of the mountainous region is realized.

The invention discloses a dam break flow rapid prediction method and a dam break flow rapid prediction system adopting a Transform-ResUNet model. Comprising the steps of obtaining actual dam break data or obtaining a data set for model training through numerical simulation; a dam break flow space-time coupling prediction model fusing Transform and ResUNet is constructed, the dam break flow space-time coupling prediction model is an encoder-decoder architecture, an encoder extracts spatial features of a water flow field through a plurality of residual convolutional layers, then feature maps are partitioned and flattened into time sequence features, and the time sequence features are input into a parallel stacked Transform module for time dynamic modeling; the decoder fuses the spatial features and Transform enhanced time sequence features through cross-layer connection, and reconstructs a predicted water flow field at a future moment through bottleneck residual blocks which are up-sampled and stacked step by step; and training the constructed dam break flow space-time coupling prediction model, and realizing rapid prediction of the dam break flow by using the trained prediction model. According to the method, high-fidelity flow field detail reconstruction is realized in flow field prediction based on an improved ResUNet encoder-decoder structure.

The invention relates to the technical field of water pollution traceability, and discloses an underground water pollution traceability system based on simulation data, and the system comprises a data collection module which collects real-time data of an underground water monitoring well, soil sampling points and underground water monitoring equipment, and forms a multi-source heterogeneous database; the three-dimensional modeling module is used for constructing a layered geologic body three-dimensional model based on the drilling data, the geological section and the remote sensing image; and the numerical simulation module is used for solving an underground water seepage equation and a pollutant migration equation by adopting a finite difference method of GPU parallel acceleration on the basis of the constructed layered geologic body three-dimensional model. Multi-source monitoring data are accessed in real time through the data acquisition module, online dynamic calculation of an underground water flow field and pollutant migration is achieved in combination with the GPU accelerated numerical simulation module, and the efficiency is effectively improved compared with traditional offline analysis.

The invention relates to the technical field of fracture network fracture water channel identification, and discloses an identification method for analyzing a dominant flow channel in a three-dimensional fracture network based on a topological network. According to the method, probability distribution parameters such as geometric occurrence, gap width and density of a rock mass multi-scale fracture system in a target area are obtained through field surveying and mapping and three-dimensional scanning, and a spatial topological structure of the three-dimensional fracture system is reconstructed by adopting Monte Carlo method simulation and discrete fracture network modeling technology; secondly, abstracting the fracture network into a three-dimensional topological graph model based on a graph theory principle, defining fracture center points and cross points as graph nodes, and converting fracture sections into weighted edges; the method breaks through the continuous medium hypothesis limitation of traditional seepage analysis, and has important engineering application value in the fields of deep geological energy storage reservoir seepage risk assessment, shale gas fracture network optimization design, rock slope stability analysis and the like; compared with a traditional numerical simulation method, the method has the technical advantages of being high in calculation efficiency, good in prediction precision, high in multi-scale applicability and the like.

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 discloses an intelligent construction method, system, equipment and medium based on a digital twin tunnel, and aims to construct a high-precision physical entity model by fusing dynamic and static data in real time through multiple types of sensors so as to improve data acquisition comprehensiveness; based on tunnel-level, soil-level and ground building-level multi-level modeling and finite element analysis, fine mechanical stability simulation is realized; multi-dimensional data features are extracted by combining a convolutional neural network algorithm, security risks are evaluated, and a reinforcement scheme is optimized through dynamic iteration; a closed-loop regulation and control mechanism of data monitoring, numerical simulation and dynamic feedback is formed by utilizing a collaborative architecture of a sensing layer, a simulation layer and a display layer, so that environmental disturbance is effectively reduced, and construction safety is guaranteed; according to the method, digital twinning, BIM, finite element analysis and deep learning are fused, real-time monitoring and intelligent optimization of the whole construction process are achieved, efficiency and safety are remarkably improved, and influences on the surrounding environment are reduced.

The invention discloses a numerical simulation prediction method and system for typhoon binocular wall structure reconstruction judgment and maintenance duration after terrain interference and a medium, and relates to the technical field of typhoon fine structure evolution description and numerical simulation. According to the method, the binocular wall typhoon is identified through multi-source data fusion, a high-resolution numerical simulation system is constructed, and a typhoon structure is divided into four quadrants for differential diagnosis according to the wind shear direction based on vertical wind shear phase limit analysis. And the distribution characteristics of the rapid vortex silking area are captured by calculating vortex silking time parameters. And establishing a ditch sinking airflow detection mechanism, and quantitatively evaluating the contribution of radial advection, tangential advection, vertical advection and friction force items to tangential wind evolution by using tangential wind income and expenditure diagnostic analysis. And calculating an energy growth rate, and predicting a double-eye wall maintaining time length. According to the method, the outer eye wall re-formation judgment is output, the outer eye wall radius zone, the maintenance duration interval and the uncertainty are predicted, and the method is suitable for real-time business and research.

According to the intelligent grotto excavation stability analysis system based on the BIM, through deep fusion of the BIM model and multi-source monitoring data, whole-process dynamic control over the grotto excavation stability is achieved. The system adopts a lightweight model processing technology to remarkably improve the calculation efficiency, and an intelligent inverse algorithm effectively solves the subjectivity problem of traditional parameter determination. A three-dimensional numerical simulation and real-time monitoring data interactive verification mechanism greatly improves the reliability of an analysis result, and a dynamic risk assessment system realizes the accuracy of risk early warning through multi-index fusion analysis. A final support scheme optimization module combines engineering experience with an intelligent algorithm, safety is ensured, economical efficiency is taken into account, and an intelligent solution capable of being self-adaptive to engineering condition changes is formed. According to the whole system, seamless connection of all links is achieved through modular design, and full-chain technical support from data to decision making is provided for safety construction of underground engineering.

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 discloses a numerical simulation-based roadway surrounding rock deformation monitoring method and device. The method comprises the following steps of: constructing a three-dimensional geologic model of a roadway area; based on the three-dimensional geologic model, establishing a numerical model of heat conduction, stress action and seepage multi-physics field coupling, and based on elastic-plastic characteristics of rocks in the roadway area, simulating simulation data of surrounding rocks in the roadway area under the multi-physics field action by the numerical model; acquiring real-time monitoring data of various types of sensors arranged in a risk monitoring area of surrounding rock deformation corresponding to the simulation data; denoising, filtering and abnormal value processing are carried out on the real-time monitoring data, and then multi-source data fusion is carried out to calibrate the numerical model; and predicting the deformation trend of the surrounding rock based on the calibrated target numerical model and the real-time monitoring data. Therefore, by means of geological modeling, numerical model simulation, sensor arrangement optimization, numerical model optimization and surrounding rock deformation trend prediction, roadway surrounding rock monitoring precision is improved, and safe operation of a roadway is guaranteed.

The embodiment of the invention provides an estuary region storm surge disaster assessment method and device. The assessment method comprises the steps of obtaining basic geographic data, meteorological data, tide and wave data and disaster-bearing body data of a preset region of an estuary region; constructing a discrete grid according to the basic geographic data; according to the tide and wave data, constructing a storm surge and wave numerical simulation model in a discrete grid; simulating different typhoon scenes in a numerical simulation model of the storm surge and the waves according to the meteorological data to obtain simulation results; evaluating according to the simulation result to obtain the danger level of each area; evaluating according to the disaster-bearing body data to obtain the vulnerability level of each region; and determining the comprehensive risk level of each area according to the danger level and the vulnerability level. According to the embodiment of the invention, the evolution process of storm surge disasters can be simulated more accurately, and then the comprehensive risk level of each area of the estuary region is determined.

The invention provides a CO2 sequestration simulation method based on transfer learning and a physical information neural network, which aims at a geological carbon dioxide sequestration process by combining the transfer learning and the physical information neural network, and comprises the following steps of: simulating and generating data by using a Matlab oil reservoir simulation tool box, and constructing a neural network basic model; the physical law of carbon dioxide migration in the porous medium is trained and learned through coarse resolution, then fine tuning is performed on the generated actual geological model data by adopting a migration learning strategy to adapt to different geological structures and injection conditions, and a neural network loss function is embedded in combination with a Darwest equation and a mass conservation equation to obtain a carbon dioxide migration model. Compared with a traditional numerical simulation method, the method has the advantages that the calculation efficiency is remarkably improved while the prediction precision is kept, and the method is suitable for carbon dioxide sequestration optimization and environmental risk assessment under complex geological conditions and has good industrial popularization value and environmental benefits.

The invention discloses a metro shield tunnel crack width refined numerical simulation method under surface loading, and the method comprises the following specific steps: describing the overall stress deformation characteristics of a soil body-shield tunnel structure based on a stratum-structure method, and simulating a macroscopic equivalent model by adopting a continuous medium model, and the equivalent stiffness reduction effect caused by the influence of longitudinal seams and circular seams is fully considered, the most unfavorable section position along the shield tunnel is determined, so that the key section is replaced with a refined model considering local hand hole weakening, multi-contact and built-in steel bars, and the shield tunnel crack evolution characteristics are described by adopting a total strain crack model. And obtaining the millimeter-scale crack width of the target tunnel structure based on a load-structure method. According to the analysis method, the millimeter-scale crack width of the shield tunnel under the action of ground surface loading can be accurately obtained, the structure safety state can be rapidly evaluated in combination with current specifications, and an important basis is provided for operation and maintenance of the subway shield tunnel.

The invention relates to the technical field of wind energy resource evaluation, in particular to a method and a system for calculating a hydrodynamics wind field numerical value based on high-precision landform, and the method comprises the steps: generating a three-dimensional unstructured grid for CFD wind field simulation based on high-precision landform data; analyzing an atmospheric boundary layer structure, and establishing a turbulence calculation model; according to the turbulence calculation model, the influence of atmospheric stability on the mountain flowing wind acceleration factor is researched, and a mountain flowing model is developed; performing CFD wind field simulation according to the three-dimensional unstructured grid and the mountain flow model, and correcting parameters of the mountain flow model; a refined grid is made through terrain elevation data; and according to the refined grid, driving the corrected mountain flow model to carry out numerical simulation, and carrying out wind power plant wind resource evaluation. Through the method, the complex characteristics of the wind field can be reflected more comprehensively, the precision and the calculation efficiency of wind resource evaluation are remarkably improved, and the efficiency and the accuracy of numerical simulation of the complex terrain wind field are improved.

The invention discloses an intelligent optimization method for a multi-type well seam joint control fine injection-production mode, and relates to the technical field of oil-gas field development. The method comprises the following steps: setting a well seam joint control fine injection-production mode, establishing an oil reservoir numerical simulation model in oil reservoir numerical simulation software, obtaining multiple groups of oil reservoir injection-production schemes based on a Latin hypercube sampling method, performing simulation according to each group of oil reservoir injection-production schemes by utilizing the oil reservoir numerical simulation model, generating multiple pieces of sample data, and establishing a sample database; a deep learning agent model is established, after the sample database is utilized to train and train the deep learning agent model, a particle swarm optimization algorithm is adopted to carry out single-target pre-search global optimization to obtain a preferred reference strategy, a reinforcement learning dynamic decision model is established, and a reinforcement learning agent is obtained through training based on a PPO near-end strategy optimization algorithm; and the optimal injection-production development scheme of the oil reservoir is obtained by utilizing the reinforcement learning agent, so that rapid optimization and decision support of the oil reservoir injection-production scheme in a new multi-type well seam joint control mode are realized.

The invention belongs to the technical field of tunnel engineering, and provides a multi-physics field real-time assimilation simulation and regulation method and system in a tunnel grouting process in order to solve the problem that real-time dynamic simulation and automatic regulation are lacked in existing tunnel construction, and the real-time assimilation simulation and regulation method and system in the tunnel grouting process are provided by utilizing ensemble Kalman filtering and combining real-time monitoring data in the tunnel grouting process. Dynamically correcting parameters of the multi-physical model; time correlation in the slurry condensation process is considered, a time-varying condensation model depicting physical property changes of slurry evolving along with time is integrated, the time-varying condensation model serves as an external function in the time step length to be embedded into the multi-physical field model in correction, and the slurry flowing state is adjusted in a self-adaptive mode through numerical simulation; and generating control parameters of tunnel grouting according to a dynamic simulation result, and realizing closed-loop regulation and control of tunnel grouting. Synchronous linkage of numerical simulation and on-site working conditions is realized.

The invention discloses a numerical simulation method for an avalanche impact protection structure based on bidirectional coupling, and relates to the technical field of mountain disaster protection, and the method comprises the steps: modeling and initializing an avalanche material source: employing a discrete element theory to simulate an avalanche process, and achieving the whole-process dynamic simulation and reproduction of an avalanche disaster from the starting to the movement to the impact protection structure; protection structure modeling and parameter setting: modeling an avalanche protection structure based on a universal finite element simulation platform; discrete element-finite element contact coupling setting: solving unit stress and strain data; numerical simulation control and solution; impact response extraction and result analysis: performing systematic analysis on the structure response and impact characteristics to evaluate the dynamic performance and safety margin of the structure under the action of avalanche impact; the method can be used for predicting the impact effect of the avalanche disaster on the downstream structure, and provides a theoretical basis and technical support for design and performance evaluation of a protection structure.

The invention discloses a wind wave-seabed-pile foundation-photovoltaic array multi-physics field coupling calculation system for an ocean photovoltaic power station. The system comprises a wave model construction module, a photovoltaic array wind load numerical simulation module and a multi-physics field coupling numerical model integration module. The wave model construction module is used for extracting wave elements and constructing a wave model; the photovoltaic array wind load numerical simulation module is used for performing photovoltaic array wind load numerical simulation based on the extracted wave elements and the constructed wave model; and the multi-physics field coupling numerical model integration module is used for carrying out multi-physics field coupling numerical model integration, solving and verification based on a numerical simulation structure. According to the method, the wind wave load, the seabed seepage field, the pile foundation stress field and the photovoltaic array wind field are cooperatively calculated by building the multi-field dynamic coupling model, and therefore the accuracy and reliability of offshore photovoltaic power station pile foundation bearing performance evaluation are improved.

The invention provides an automatic history fitting method for gas drive numerical reservoir simulation, which comprises the following steps of: 1, establishing a gas drive numerical simulation mathematical model, and correcting the gas drive numerical simulation mathematical model by using a gas drive PVT phase state fitting experiment; 2, solving the corrected gas drive numerical simulation mathematical model obtained in the step 1, performing parameter analysis, and screening main control factors influencing accumulated oil production; 3, generating a numerical simulation training sample set based on an orthogonal experiment, and obtaining the main control factor parameter initial value constraint screened out in the step 2 through a machine learning algorithm; step 4, establishing a multi-parameter fitting objective function for realizing historical fitting; and step 5, using the main control factor parameter initial value constraint obtained in the step 3, performing iterative calculation through a projection gradient method, fitting the target function established in the step 4, and terminating when a convergence condition is satisfied. According to the method provided by the invention, the constraint parameter values can be adaptively calculated, automatic historical fitting is completed, and the definition of the fitting parameter range does not depend on empirical and experimental determination any more.

The invention discloses a rock nanoindentation numerical simulation method based on PFC discrete elements, and relates to an unconventional natural gas reservoir fracturing technology. Comprising the following steps: dynamically loading an iterative matching load-displacement curve based on XRD-SEM-EDS mineral spatial distribution of a rock sample and single mineral nanoindentation experimental data microscopic parameters; in combination with mineral space distribution data, constructing a multi-mineral heterogeneous model by stages, and dynamically loading simulation; based on crack number development, force chain distribution and particle displacement vector characteristics, a regulation and control mechanism of a mineral interface coupling effect and pore stress concentration on a crack propagation path is quantitatively analyzed. According to the invention, a heterogeneity evolution mechanism of force chain development and crack propagation in each stage of loading, load holding and unloading can be analyzed, and a dynamic mechanism that mineral components and pore structures cooperatively regulate and control a crack propagation path and nonlinear load response is disclosed; and a solution path is provided for rock microscopic damage mechanism prediction and heterogeneous material discrete element numerical simulation modeling.

The invention provides a method and a device for evaluating and measuring microscopic mechanical properties of TC4 alloy, relates to the technical field of microscopic mechanical properties, and realizes accurate evaluation of material properties through combination of multi-scale characterization and numerical simulation. Firstly, a standard sample is prepared through selective laser melting, and residual stress field distribution is obtained through X-ray diffraction; dividing a stress field into sub-regions, and establishing a quantitative relationship between microscopic structure parameters and residual stress by combining SEM and EBSD analysis; the method comprises the following steps: acquiring local mechanical properties through a nanoindentation test, and constructing a stress-performance correlation model; and finally, establishing a finite element model, transmitting stress and tissue parameters by adopting trilinear interpolation and an inverse distance weighting method, verifying data reliability through a stress difference criterion, and calculating mechanical properties of each unit. According to the method, multi-scale correlation from microstructure characteristics to macroscopic mechanical properties is innovatively realized, so that the mechanical property distribution of the material is accurately evaluated.

The invention relates to the technical field of investment casting, and particularly provides an investment casting automatic wax pattern welding equipment control method which comprises the following steps: extracting a peak value and duration from heating curve data, and judging a uniformity numerical value of interface temperature distribution through a numerical simulation method; according to the fusion depth change trend and the interface temperature distribution data, the quantized value of the quality index is calculated, and an evaluation result of the welding effect is obtained; if the quality index quantized value is lower than a preset threshold value, historical test data are extracted from a data analysis module, and the adjustment range of the process variable is determined; according to the process variable adjustment range, optimizing the parameter combination of the heating curve and the pressure curve, and generating new control strategy data through an iterative algorithm; new control strategy data is adopted to drive equipment to operate, and dynamic feedback values of the interface temperature and the fusion depth are obtained through a real-time monitoring system; and extracting abnormal fluctuation data from the dynamic feedback value, and judging the influence degree of the solidification rate change on the quality index in combination with a data analysis result.

The invention discloses a tropical region offshore marine meteorological fusion analysis method. The method comprises the following steps: step 1, data collection and preprocessing: collecting offshore multi-platform collaborative networking observation data of a tropical region; 2, data quality control: checking the data, and analyzing error characteristics of marine meteorological observation data; 3, data fusion processing: establishing a tropical region offshore multi-source data fusion analysis system, performing intelligent fusion on the multi-source observation data subjected to quality control, and constructing a marine meteorological fusion analysis data set; 4, constructing a coupling analysis model: performing coupling analysis on marine meteorological elements by combining a physical model and a numerical simulation technology, and discovering an evolution rule and influence factors of a marine meteorological system by simulating and predicting an interaction process between the ocean and the atmosphere; and 5, dynamic application and evaluation: through real-time analysis of key meteorological elements, potential marine meteorological disaster risk affairs are discovered and early warned.