3451 results about "Numerical modeling" patented technology

The invention discloses a fluid mechanics equation solving method based on a physical information neural network, and relates to the technical field of fluid mechanics. The problems that in the prior art, a large amount of training data is needed, physical information is not embedded, prediction does not conform to physical laws, generalization is difficult, and sample generation consumes resources are solved. The fluid mechanics equation is solved through the physical information neural network, physical consistency and prediction precision of model training are ensured, mathematical descriptions of fluid motion and heat transmission are determined, accurate input is provided for the neural network, definition of a loss function is combined with a basic physical law of fluid mechanics, and the prediction precision is improved. The reliability of model output is guaranteed, the training and optimization process effectively guides the learning of the neural network and improves the solving efficiency, the numerical verification and prediction step combines the prediction capability of high-precision numerical simulation and the neural network, the solving precision is guaranteed, the prediction efficiency in an unsampled area is improved, and the prediction efficiency of the neural network is improved. And an efficient and accurate tool is provided for fluid mechanics research.

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

The invention discloses a freezing and thawing stratum grouting numerical analysis modeling method and system, particularly relates to the technical field of hydraulic engineering numerical simulation, and is used for solving the problem of grouting parameter prediction inaccuracy caused by neglecting the dynamic coupling relationship between the thermodynamic behavior of a phase-change material and a seepage field and a damage field in an existing grouting model. A dynamic correlation system of phase change energy storage performance parameters and seepage field-damage evolution is established, a slurry diffusion path priority channel weight is corrected based on a freeze-thaw interface migration track, a bidirectional iteration equation of a seepage field and a diffusion migration field is coupled, and multi-physical field spatial-temporal scale cooperative solution is realized through a separated iteration algorithm; through multi-dimensional coupling of thermodynamic characteristics of the phase-change material, heterogeneous evolution of seepage paths and damage mechanical response, the prediction precision of the mechanical characteristics of the grouting stone body and the slurry diffusion range under the action of freeze-thaw cycle is remarkably improved, and the leakage and structural instability risks are effectively reduced.

The invention discloses a large-diameter shield tunneling parameter optimization method and system based on digital twinning, and relates to the technical field of shield tunnel numerical simulation, machine learning and digital twinning, and the method comprises the steps: obtaining shield tunnel construction site data, and constructing a virtual digital twinning body; building a training sample set based on virtual numerical twinborn generation data; training an agent model by using the training sample set; during construction, actual stratum response data and tunneling parameter data are obtained in real time, the real-time data are input into the soil mass parameter inversion agent model, and the optimal value of the soil mass parameter is rapidly output; the optimal value is input into the virtual digital twin, and dynamic real-time updating of numerical simulation is carried out; and on the basis of the updated soil parameter data and the tunneling parameter data in the next construction step, stratum response prediction data are obtained through the stratum response prediction agent model, so that the tunneling parameter data are adjusted and optimized. According to the invention, more accurate numerical simulation and safe and efficient tunneling of the shield tunnel can be realized.

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 provides a numerical simulation method suitable for a three-dimensional spherical flame, and belongs to the field of electrical data processing, and the method comprises the steps: building a computational domain model according to the requirements of a computational scene, dividing a grid unit, and obtaining the node information of the required grid unit; establishing a Navier-Stokes equation set of a coupling chemical reaction and diffusion process model; estimating convection and diffusion term variable gradients in the conservation equation; calculating a time step length according to a set Kulang number, and carrying out time advancing; estimating an expected value of a velocity field, and solving a predicted velocity; the divergence of the velocity field and the correction value of the pressure field are calculated; obtaining a corrected velocity field; a self-adaptive grid means is introduced to dynamically adjust the grid resolution; performing iterative correction for multiple times until the velocity field and the pressure field converge to convergence conditions; performing spherical flame numerical simulation, and monitoring the convergence of the solution. According to the invention, the flame dynamics and cellular instability of the premixed spherical expansion flame can be reproduced.

The invention discloses a method and system for intelligently constructing a two-dimensional hydrodynamic model based on a large language model, and relates to the technical field of artificial intelligence and hydraulic numerical simulation, and the system comprises an intelligent region block division module which is used for analyzing geographic information data through the large language model LLM, recognizing topographic features and engineering facilities, and dividing region blocks; the self-adaptive grid generation module is used for setting different grid types and dynamically setting grid density according to different partitions; the terrain interpolation optimization module is used for selecting an interpolation algorithm to calculate a grid unit terrain and solve an optimal grid terrain based on a water level-reservoir capacity relationship verification result, and checking and marking an elevation abnormal mutation grid unit; and the two-dimensional hydrodynamic model construction module is used for outputting the grid and the time sequence data to a configuration file according to the format requirement of the target two-dimensional hydrodynamic model, and constructing the two-dimensional hydrodynamic model. According to the method, the problems of dependence on artificial experience, long time consumption of grid division and tedious adjustment are effectively solved, and integrated intelligent modeling is realized.

The invention discloses a macroscopic progressive damage intelligent evaluation method driven by multi-scale microscopic damage observation, and the method comprises the steps: selecting a plurality of representative materials to carry out a microscopic mechanical test, and observing the damage evolution process under different loading conditions through MicroCT to obtain a microscopic mechanical test result; simulating a crack state based on a micro-mechanical model to reproduce a micro-mechanical test result, and performing material parameter correction of simulation calculation by taking test data as a constraint to obtain a micro-numerical modeling calculation result; and determining a representative volume element (RVE) scale based on a microscopic numerical modeling calculation result, and describing a macroscopic damage behavior by utilizing a continuous damage mechanical model so as to obtain evolution relation data of a macroscopic damage variable, stress and strain. According to the method, the damage behaviors of metal and composite material structures under complex working conditions can be accurately predicted, and the safety and reliability of aircraft structures can be improved.

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 provides a pre-stressed anchor cable construction arrangement quality evaluation method, and relates to the field of underground engineering, and the method comprises the following steps: S1, model construction: building three-dimensional numerical models of different anchor rod arrangement schemes; s2, simulation calculation and result evaluation, wherein excavation simulation calculation is executed according to the three-dimensional numerical models of different anchor rod arrangement schemes, and numerical simulation calculation results of surrounding rock deformation, stress distribution, damage and fracture area distribution and supporting structure stress are obtained; evaluating numerical simulation calculation results of different anchor rod arrangement schemes to obtain evaluation indexes, and determining an optimal scheme according to the evaluation indexes. Through the cooperation of the above structures, the method has the following beneficial effects: 1, the evaluation accuracy can be comprehensively improved, and the data is converted into a visual and quantitative evaluation result by constructing a comprehensive evaluation system and applying a data analysis model and algorithm; and secondly, by establishing an error correction model, the deviation between numerical simulation and on-site monitoring data can be accurately calibrated.

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 relates to the field of oil and gas field exploration and development, in particular to an oil and gas reservoir four-dimensional stress field quantitative prediction and integrated modeling method. Establishing finite element geological geometric models in different periods by recovering a paleostructure form in a key structure transformation period; predicting three-dimensional distribution of rock mechanics parameters by combining a rock mechanics experiment and adopting a well-seismic combination method; burial depth changes of rocks in different periods are determined through ancient and modern structure fusion, three-dimensional distribution of mechanical parameters of the ancient rocks is predicted, geomechanical heterogeneous models of oil and gas reservoirs in different periods are established, and numerical simulation of four-dimensional stress fields in different periods is achieved; and a multi-period stress unit cyclic coupling algorithm is adopted to realize coupling of multi-period stress field prediction data into one model. The invention provides a quantitative prediction and integrated modeling method for a four-dimensional stress field of an oil and gas reservoir. The method has practical significance in multiple aspects of ancient stress field numerical simulation, tectonic fracture distribution prediction, 'geology and engineering dessert 'evaluation and the like.

The invention discloses an AI-NWP three-dimensional closed-loop bidirectional dynamic feedback coupling method for extreme rainfall event area simulation and a program product, and belongs to the technical field of meteorological numerical simulation and artificial intelligence fusion. According to the method, a mid-term forecast field is generated based on an AI global weather prediction model, an analysis field is constructed by assimilating multi-source observation data, and a high-resolution NWP region mode is driven to perform rolling simulation. Furthermore, a space-time residual field is constructed by using the difference between an NWP region simulation result and live data, a residual learning model is trained, an AI model prediction structure is fed back and corrected, and dynamic weight adjustment updating of the AI prediction model is realized. A closed-loop two-way feedback system among AI output, NWP simulation and residual evaluation is integrally formed, the space structure reduction capability and the area positioning precision of a medium-term heavy rainfall event are effectively improved, the continuous predictability and the simulation credibility of an extreme weather process are remarkably enhanced, and the method has good stability, universality and engineering expansion value.

The invention discloses a PINNs high Reynolds number flow field solving method based on regulatory factor optimization, and the scheme comprises the steps: firstly building a physical model, on one hand, building a geometric model according to the actual condition of a reactor core rod bundle channel, and on the other hand, building a fluid mechanics model containing continuity, momentum conservation and energy conservation equations; a data set is obtained, and experimental data is preprocessed and then integrated with simulated data through experimental measurement and numerical simulation; and then training a physical information neural network, designing a neural network model of specific input and output, introducing a regulatory factor to balance the difference between a physical equation and data, constructing a comprehensive loss function containing internal data points, boundary data points and equation loss, and training the network by using a training data set until convergence. And finally, solving a flow field by using the trained neural network, outputting predicted values of a velocity field, a pressure field and a temperature field, and solving the high Reynolds number flow field of the reactor core.

The invention relates to the technical field of layered surrounding rock inversion analysis, and discloses a layered surrounding rock three-dimensional crustal stress field inversion intelligent analysis system and method, and the system comprises a dimensional geological value module, an intelligent inversion analysis module and an inversion result verification module. The method comprises the steps of collecting geological data in target layered surrounding rock; carrying out normalization processing on the geological data, and carrying out sensitivity analysis; constructing a three-dimensional geologic model, and performing numerical simulation; a crustal stress field inversion intelligent analysis model is generated based on the three-dimensional geologic model; training the crustal stress field inversion intelligent analysis model by using the training sample; inputting the real-time geological data into the crustal stress field inversion intelligent analysis model to obtain a crustal stress inversion analysis result; carrying out visual output on the ground stress analysis result; and adjusting the crustal stress field inversion intelligent analysis model according to the actually measured data. Scientific ground stress field analysis basis can be provided for complex projects such as tunnel engineering, underground engineering and hydropower stations.

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 relates to the technical field of dredge pump performance analysis, and discloses a numerical simulation and model test-based dredge pump performance analysis method, which comprises the following steps of: planning an analysis process, and determining numerical simulation (dredge pump internal flow field simulation) and model test contents (actually measured performance data under different working conditions); determining working condition types according to design parameters and working conditions; generating a performance analysis process set and determining an execution sequence; generating a simulation parameter setting list and a test scheme list of each working condition; and associating the data to generate an overall scheme. The method further relates to working condition analysis boundary determination, working condition type subdivision, dynamic adjustment of the process, test rule optimization, database construction and the like. According to the method, comprehensive and accurate analysis of the dredge pump performance is achieved through multi-dimensional data integration and a dynamic mechanism, the analysis efficiency and reliability are improved, and the method is suitable for evaluation and optimization of the dredge pump performance.

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.

The invention discloses a computer numerical simulation method, system and equipment for a composite material, particularly relates to the technical field of analog simulation, and is used for solving the problem of simulation distortion caused by neglecting the randomness of a microstructure in the prior art. The method comprises the following steps: acquiring microstructure image data of a composite material, extracting fiber arrangement direction and pore distribution parameters, and generating a fiber direction probability density function and a pore topological relation; constructing a non-uniform grid model constrained by a local coordinate system according to the fiber direction probability density function; identifying a weak connection area based on a pore topological relation and marking nodes; applying dynamic decoupling constraint to the weak connection area, wherein the dynamic decoupling constraint comprises initial rigidity and rigidity attenuation rate; applying an external load to the model and calculating a real-time stress coefficient of the weak connection area; dynamically adjusting the constraint parameter through threshold judgment and iterative correction until the stress coefficient is converged; and finally, outputting a corrected macroscopic mechanical property result.

The invention relates to the technical field of mountainous river fish habitat habitat restoration, and relates to a mountainous river fish habitat restoration method based on numerical simulation optimization, comprising: acquiring habitat data of a mountainous river fish habitat, and performing preliminary ecological restoration measures on the mountainous river fish habitat; constructing a numerical simulation model to predict the erosion and deposition evolution result of the fish habitat in the mountain river after the preliminary ecological restoration in a set period, and identifying an area of which the erosion and deposition evolution degree meets a preset threshold value in the set period; and carrying out riverbed substrate transformation on the identified area based on the target fish, evaluating the habitat improvement effect under the combined action of the preliminary ecological restoration measure and the riverbed substrate transformation through a habitat suitability model, and completing the restoration of the fish habitat in the mountain river based on the evaluation result. According to the method, dredging, spur dike and substrate transformation are combined, and numerical simulation optimization is combined, so that the effectiveness, continuity and scientificity of restoration of the fish habitat in the mountain river are improved.

The present invention provides systems, methods, and devices for electroporation-based therapies (EBTs). Embodiments provide patient-specific treatment protocols derived by the numerical modeling of 3D reconstructions of target tissue from images taken of the tissue, and optionally accounting for one or more of physical constraints or dynamic tissue properties. The present invention further relates to systems, methods, and devices for delivering bipolar electric pulses for irreversible electroporation exhibiting reduced or no damage to tissue typically associated with an EBT-induced excessive charge delivered to the tissue.

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.