495 results about "Grid partition" patented technology

The invention belongs to the field of data analysis, and discloses a data analysis method for engineering consultation digital intelligent management, which comprises the following steps: mapping multi-project heterogeneous data to a unified three-dimensional space-time grid through space-time grid division to form a grid mapping data set; detecting data format and attribute conflicts based on neighborhood correlation analysis, and distributing calibration data through dynamic weight; missing values and abnormal fluctuations are processed by using a time sequence autoregression model and a smoothing technology, and a complete data set with continuous time is constructed by combining linear interpolation and multi-dimensional data fusion; key indexes are extracted to construct a digital mirror image containing spatial positions, time sequences and attribute association, real-time data are synchronized, and outlier grid points are corrected; and multi-scene operation conditions are constructed based on the mirror image data, and a dynamic adjustment scheme is realized. According to the method, heterogeneous data are integrated through space-time grids, digital twinning and multi-scene simulation technologies are combined, and full-period management and risk intelligent decision-making of engineering data are achieved.

The embodiment of the invention provides a low-altitude flight target conflict identification method and device, and the method comprises the steps: obtaining a basic scale of a space grid according to the features of a target airspace and the performance features of an aircraft, carrying out the multi-level grid division of the target airspace according to the difference logic and the basic scale of the space grid, and constructing a distributed grid reference space; performing height reference conversion and time reference synchronization on the flight data in the reference space, and associating the flight data with the reference space to obtain a target airspace index space; performing high layering on target airspace index space, performing secondary fine-grained flight conflict detection on each index space layer according to a preset time period, judging whether a potential flight conflict risk exists or not, if yes, acquiring real-time state data of the flight targets, predicting the minimum distance between the flight targets, judging whether an actual flight conflict risk exists or not, and if not, determining whether the actual flight conflict risk exists or not; the method can support the real-time conflict recognition of large-scale aircrafts, and improves the flight efficiency and safety of low-altitude aircrafts.

The invention provides a KKS code generation method and system based on space grid and three-dimensional data fusion, and the method comprises the steps: obtaining an original three-dimensional space data set covering a target facility region and a basic attribute data set of a corresponding facility, and carrying out the grid division of the original three-dimensional space data set; generating a multi-level spatial grid unit set matched with the spatial range of the target facility region, and performing association mapping on the basic attribute data set and the multi-level spatial grid unit set to generate a fusion data set with a binding relationship between the spatial position and the attribute information, and calling a pre-constructed KKS coding rule model to carry out coding generation on the fusion data set, obtaining a KKS coding sequence corresponding to the facility space position and attribute information, carrying out uniqueness verification, generating a verification result set containing a code passing verification and a code not passing verification, and carrying out adjustment processing to generate an effective KKS code. According to the method, the quality and practicability of KKS coding are remarkably improved.

The invention discloses a low-altitude flight base map construction method for unmanned aerial vehicle path planning, and belongs to the technical field of low-altitude flight base map construction. Screening the building data in the target area, and calculating the actual occupied area of each building after screening; dividing the grid level to which each building belongs according to the actual floor area of each building; performing grid coding on the grid level to which each building belongs; constructing an initial grid; and step-by-step refining is carried out on the initial grid by adopting a method based on building space characteristics to obtain sub-grids, and the building space is represented by utilizing a sub-grid group. According to the method, the low-altitude flight base map of the unmanned aerial vehicle is constructed based on the Beidou grid code, and the method has remarkable advantages in the aspects of data storage and calculation efficiency; through regularized grid division and a refinement strategy, an efficient and lightweight low-altitude flight base map of the unmanned aerial vehicle is constructed, so that the data storage amount of the base map is reduced by more than 95%, and the storage overhead is greatly reduced.

The invention relates to the technical field of urban planning, in particular to a charging facility planning method and device based on machine learning and a medium, and the method comprises the following steps: carrying out the grid division of a planning region, which comprises a plurality of charging service grids; carrying out vehicle ownership prediction and charging facility demand prediction to obtain a charging demand quantity; adopting a clustering algorithm to obtain a plurality of charging block areas with balanced charging demand quantity; and constructing an objective function by maximizing the station revenue of each charging block area, constructing constraint conditions by full coverage of charging demands, calling an aurora optimization algorithm to obtain an optimal planning scheme of the charging facilities, and completing the planning of the charging facilities by adopting the optimal planning scheme of the charging facilities. According to the method, the problems of incomplete analysis and unreasonable partition optimization in the prior art can be solved, and various influence factors of charging facility layout are comprehensively considered, so that efficient layout and resource allocation of a charging network are realized, and the overall quality of charging services and the user satisfaction are remarkably improved.

The invention discloses a layout generation method for load effect compensation and a related device, which are applied to the technical field of photoetching and comprise the following steps: acquiring photomask data; carrying out grid division on the mask graph according to the photomask data, and determining layout density in each grid; comparing the layout density of each grid with a target density, and determining a density difference value corresponding to each grid; determining a virtual graph corresponding to each grid according to the density difference value; and adding a corresponding virtual graph in a layout area corresponding to the grid to form a compensated mask plate graph. By performing grid division on the mask plate graph, calculating the specific layout density in each grid and adding the corresponding virtual graph to the layout area corresponding to the grid according to the difference value between the layout density and the target density, the graph density of the layout area in each grid can be effectively compensated, so that the load effect of each area in the layout is balanced, and the performance of the mask plate is improved. And the etching uniformity is improved.

The invention discloses a fluid internal particle motion simulation method based on CFD-DEM coupling. Comprising the following steps: constructing a three-dimensional model, and exporting the three-dimensional model as a. Step file; grid division is carried out on the solid and the grid between the solid and the drainage basin, and a. Msh file is generated; a dynamic grid motion control file is generated, and a. Model file is reserved; the. Msh file is imported into DEM simulation software, and a. Case file with the initial time being 0 is exported; and performing fluid mechanics and discrete phase calculation on the. Model file in CFD simulation software, and exporting a particle motion track and a variable change curve. According to the method, control over the moving part is more accurate, the movement trend of particles in the three-dimensional model can be accurately simulated, and particle movement simulation animation and variable data of more real points are output; the obtained simulation coupling result not only can judge the movement condition of the abrasive particles, but also can improve the structure according to a fluid mechanics (CFD) calculation result, optimize work and design parameters, reduce power loss and improve transmission performance.

The invention discloses a seepage field adaptive analysis method and device based on a flexible polygon unit, and the method comprises the steps: dividing the polygon unit into a plurality of sub-regions, and constructing an internal water head field of each sub-region; recognizing a free water surface according to water head features extracted from the internal water head field of each sub-region; if the free water surface is recognized for the first time at present, or the error of the positions of the free water surfaces recognized by two adjacent rounds of iteration does not meet a preset condition, quadtree decomposition is carried out on the free water surface to obtain new sub-regions; returning to the step of extracting the water head features according to the internal water head field of each sub-region until the error of the positions of the free water surfaces identified by two adjacent rounds of iteration meets a preset condition, and obtaining a grid division result of the polygon unit; and performing seepage field analysis on the polygon units based on a grid division result to obtain a seepage field analysis result. According to the method, the complex seepage field is accurately simulated, and the optimal balance between high-precision discretization near the free water surface and the overall calculation efficiency is realized.

The invention relates to a numerical simulation method for multiphase fluid stratum seepage, which belongs to the technical field of numerical simulation and comprises the following steps: S1, generating an unstructured grid by adopting a mode of combining a leading edge propulsion method and Delaunay triangulation; s2, performing dynamic adjustment through an adaptive grid encryption technology according to the change of the seepage physical quantity; s3, establishing a dynamic phase change model, and obtaining a function of representing the phase change rate as temperature, pressure and concentration of each phase; s4, the mass and energy change of each phase in the phase change process is calculated in real time through a kinetic equation; s5, processing dynamic evolution of a phase interface by adopting a phase field method, and describing distribution conditions of different phases through phase field variables; and S6, coupling the grid system obtained by dividing the multi-scale unstructured grid with the dynamic phase change model through a numerical solution algorithm. According to the method, the complex geometrical shape of the stratum can be better fitted through multi-scale unstructured grid division, and then the change of the phase change process along with time and space can be tracked in real time through the dynamic phase change model.

The invention relates to the technical field of city updating simulation, and discloses a city updating multi-scene simulation evaluation system based on digital twinning. The system comprises a multi-source data acquisition module, a space grid division module, a scene simulation engine and a dynamic evaluation module. The multi-source data acquisition module acquires real-time monitoring data and historical city update project data of a city physical space, and the real-time monitoring data covers environmental parameters, infrastructure operation data and people flow dynamic data, so that a digital twinborn body is constructed. The space grid division module divides the digital twin into space grid units according to the urban functional area type and the updating target and gives attribute tags to the space grid units. And the scene simulation engine generates a simulation parameter combination based on the attribute tag, and drives the digital twin to carry out multi-scene dynamic simulation. And the dynamic evaluation module outputs a state evaluation value of each space grid unit according to a simulation result, the state evaluation value comprises an infrastructure load state and a people flow distribution state, and orderly promotion of city updating work is assisted.

The invention discloses a reservoir dam leakage intelligent detection device, and the device comprises a soil hardness detection module which is used for determining a detection point according to the axis of a dam and the type of a dam body filling material; the grid division module is used for dividing the corresponding region into grid structures with associated sizes through the soil hardness mean value of the same region; the detection strategy matching module is used for determining a leakage detection strategy corresponding to the grid structure according to the soil hardness; the leakage detection module is used for detecting the leakage flow velocity of each grid in the grid structure according to the determined leakage detection strategy and determining the leakage state of each grid according to the leakage flow velocity; and the prediction module is used for predicting the leakage state of the grid according to the historical leakage data to obtain the duration required for deterioration of the leakage state of the corresponding region. According to the method, grids are reasonably divided according to the hardness of soil, so that detection is more detailed and comprehensive, potential leakage points can be accurately found, and the precision and reliability of leakage detection are improved.

The invention discloses a regional grid safety evaluation method and device based on smart gas and a medium, belongs to the technical field of gas safety supervision, and aims to solve the technical problem of how to overcome the defects of insufficient matching between grid division and gas facility characteristics and lagging leakage risk prediction in the prior art. In order to realize full-process intelligence from risk identification to closed-loop management and improve supervision efficiency and early warning precision, the technical scheme adopted by the invention is as follows: dividing a pressure sensitive grid: performing optimization division on a regional grid based on a gas pipeline pressure grade and facility distribution characteristics, and realizing accurate division of the regional grid where a pipe network is located by combining a GIS and an improved DBSCAN algorithm; acquiring three-level Internet of Things data: integrating sensor data of an unmanned aerial vehicle, a pipe network pressure device and a leakage monitoring device, and covering a full-link data system of a terminal sensing layer, an edge computing layer and a cloud storage layer; constructing a double-engine evaluation model; carrying out digital twinborn visualization; and scheduling the capability matrix.

The invention provides a transformer substation flood control optimization design modeling method and system based on grid division, and relates to the technical field of transformer substation flood control optimizing.The method comprises the steps that grid division is conducted on a transformer substation area according to multiple sets of schemes, and the optimal grid scheme is determined with the purpose of minimizing the area of a non-grid area; analyzing the stability of each grid foundation based on the foundation parameters, and dividing N stability grades; classifying the equipment in the station according to an electrical rule, determining the priority, and determining a storable grid according to the lowest stability requirement of the equipment; then, calculating dynamic stability indexes of all feasible storage schemes of each device according to a priority sequence, and selecting an optimal scheme for device arrangement; and finally, traversing all the devices to complete flood control optimization layout, and constructing a layout model of the devices according to the final scheme. According to the method, the foundation stability, the influence of adjacent grids and the priority of the equipment are comprehensively considered, and the flood control scientific layout of the substation equipment is realized through gridding partition and an intelligent optimization algorithm.

The invention relates to the technical field of refrigeration house energy-saving control, and provides a refrigeration house energy-saving control method based on deep reinforcement learning, which comprises the following steps: dividing a refrigeration house according to a multi-scale grid, collecting data in real time, weighting and aggregating according to spatial characteristics, calculating spatial semantic codes and confidence indexes of each grid, and obtaining a standardized and traceable state vector; real-time energy consumption, grid temperature space gradient, long-term exposure economic loss, event condition triggering and weighted summation form a reward function, and a deep strategy network is adopted to train parameters in an accumulated reward mode; constructing a grey box and residual dynamic prediction model, shrinking the original temperature and humidity constraint, solving the prediction model through scenario under the shrinkage constraint, and carrying out weighted fusion on the depth strategy obtained by training and the solution of the prediction model according to confidence; and calculating a statistical value in the sliding window, constructing confidence distribution of strategy return, triggering a hierarchical response according to a detection result, and inputting all triggers into an audit log for threshold self-calibration.

The invention relates to a reinforcement learning-based intelligent grid division method from GIS data to GEOSOT, and relates to the technical field of reinforcement learning, and the method comprises the steps: obtaining a plurality of grid division samples which comprise sample GIS data and a sample optimal grid scale; determining a plurality of grid division influence factors based on the plurality of grid division samples; establishing an intelligent grid division model based on a reinforcement learning algorithm, and training the intelligent grid division model based on the plurality of grid division samples; obtaining to-be-divided GIS data; determining feature data of the to-be-divided GIS data based on the plurality of grid division influence factors; determining an optimal grid scale based on the feature data of the to-be-divided GIS data through the intelligent grid division model; according to the optimal grid scale, the GIS data to be divided are converted into the GeoSOT format, and the method has the advantages that the precision and efficiency of the GIS data in the gridding process are improved, and data redundancy is reduced.

The invention discloses a multi-scalar multiplication acceleration method based on resource estimation and a pre-calculation strategy, and provides a systematic solution for the problems of insufficient resource estimation, pre-calculation factor stiffness and low sorting efficiency of a Pippenger algorithm in zero-knowledge proof. A multi-resolution point multiplication table is dynamically generated through a hierarchical displacement pre-calculation strategy, and global memory access delay is remarkably reduced by combining memory layout optimization and asynchronous flow task scheduling of window inner barrel continuous storage. A dynamic resource adaptation mechanism is designed, thread block topology, grid division and sorting algorithm selection are adjusted in real time based on GPU hardware features, and load balancing and cache utilization rate maximization are achieved. Iterative reduction and double temporary bucket strategies are introduced, and data scale is compressed and boundary processing is optimized through multi-round reduction. In the large-scale MSM operation in the block chain and privacy computing field, the computing efficiency and the resource utilization rate can be remarkably improved, and the method is suitable for an elliptic curve cryptography acceleration task.

The invention discloses a photovoltaic cluster dynamic grid division method and device based on spatial-temporal characteristics, and the method comprises the steps: obtaining the historical characteristic data of a photovoltaic cluster, and constructing a spatial-temporal characteristic matrix and a data incidence matrix; wherein the historical feature data at least comprises historical meteorological data and historical output power, and the data incidence matrix is an incidence matrix of the historical meteorological data and the historical output power; performing similarity analysis on the spatial-temporal characteristic matrix, and dividing a photovoltaic cluster to obtain an initial grid; giving a reference output mode matched with the current day of the photovoltaic cluster based on the data incidence matrix, and dividing the initial grid to obtain a secondary grid; and carrying out dynamic optimization on the secondary grid, and giving a final grid division result. According to the invention, accurate clustering and dynamic division of photovoltaic sites can be realized.

The invention belongs to the technical field related to casting, and discloses a rapid tracking and predicting method and system for involved bubble movement in the casting and mold filling process. The method comprises the following steps: (1) carrying out grid division on a three-dimensional geometric model for casting and mold filling; (2) calculating the filling rate, the speed and the pressure intensity of each grid in a casting mold filling cavity at the moment i in the mold filling process; identifying bubbles in the cavity and grids contained in each bubble; and (3) repeating the step (2) until updating of the filling rates, the filling speeds and the pressure intensities of the grids in the bubbles at all moments is completed, so that tracking and prediction of bubble movement in the casting and mold filling process are realized. By means of the method, tracking and calculation of involved bubbles in the mold filling process are achieved, and the solving accuracy of casting numerical simulation software is enhanced.

The invention relates to the technical field of switch cabinet simulation, in particular to a switch cabinet mechanism model construction method, system and device and a medium, and the method comprises the steps: generating a three-dimensional model corresponding to a switch cabinet, carrying out the preprocessing of the three-dimensional model to obtain a simulation model, applying a target parameter in an actual use scene to the simulation model to complete the parameter loading, and obtaining a parameterized model, determining a target relational expression of the switch cabinet, unifying an expression structure and modeling requirements of the switch cabinet, combining the target relational expression with the parameterized model, and generating a mechanism model through modeling processing; simulation adaptability and calculation efficiency are improved through structure simplification and grid division, actual operation parameters are loaded to reflect different working condition characteristics, an electromagnetic field, temperature field and electromagnetic loss multi-physical relational expression is constructed to achieve unified modeling, a mechanism model capable of being used for multiple operation conditions is formed, and the method is suitable for large-scale popularization and application. The method is suitable for application scenes such as switch cabinet design verification, operation maintenance and fault pre-judgment.

The invention relates to a method for synchronously playing multiple channels of videos at a browser end, which comprises the following steps of: (1) acquiring input of multiple channels of video streams, and uniformly decoding the multiple channels of video streams into video objects with a uniform format; step (2), according to the number of input paths of the multi-path video streams and the uniformly decoded video objects, generating a dynamic grid arrangement scheme meeting a preset target at a browser end in real time by adopting a self-adaptive dynamic grid division algorithm; (3) distributing a corresponding video memory block for each path of video stream according to the path number of the plurality of paths of video streams and the generated dynamic grid arrangement scheme; and step (4), based on a video memory multiplexing mechanism, adopting WebGL, and based on the dynamic grid arrangement scheme, synthesizing and rendering video frame textures of multiple paths of video streams on a single canvas to obtain a display picture.

The invention relates to the technical field of robustness artificial intelligence, and discloses an intelligent monitoring method and system for the flow state of a gas pipeline, and the method comprises the following steps: carrying out the grid division of a pipeline according to a construction layout diagram of the gas pipeline, and carrying out the leakage danger grade marking of the gas pipeline in each grid unit; for local gas pipelines in the grid units with different danger levels, the intensities of the installed sensor assemblies are different; the sensor assembly is used for collecting gas in the gas pipeline and equipment operation data; sensor data are collected, processed and transmitted through data acquisition and transmission equipment; determining geographical location information of an accident site by using positioning equipment; geographic information data support and path planning are provided by means of a geographic information system device. The system can be suitable for various installation environments and is high in monitoring accuracy.

The invention discloses an industrial-grade printed circuit board heat exchanger design optimization method based on structured grid division and an artificial neural network, and the method comprises the steps: S1, carrying out the modeling of a heat exchanger based on a structured grid division method, and segmenting an end socket of the heat exchanger into a plurality of hexahedron structures, a flow channel of the heat exchanger is built into an agent flow channel model in the axial direction; s2, key parameters of a heat exchanger runner are extracted through a proxy runner model, and flowing and pressure drop characteristics of fluid in the runner are calculated; S3, based on the computational fluid mechanics simulation technology, a velocity field, a pressure field and flow distribution of the fluid in a heat exchanger end socket are obtained; s4, dividing control bodies for the heat exchanger based on a finite volume method, establishing a heat exchange amount and efficiency calculation program of the heat exchanger, and obtaining the efficiency of the heat exchanger; and S5, an artificial neural network training model is introduced, a multi-objective optimization algorithm is applied, the thermal hydraulic performance of the heat exchanger is optimized, a Pareto leading edge is generated, and multiple design selections are provided for designers to refer to.

The invention relates to an SPH pollutant transport simulation method based on background grid division particle dormancy. The method comprises the following steps: initializing parallel computing parameters and initializing particle information; copying the to-be-processed data from the CPU end to the GPU end; parallel computing of the SPH method is carried out, wherein the parallel computing comprises the steps of background grid division, particle sorting, background grid state updating, background grid classification, particle searching and computing, dynamic updating grid classification, particle interaction computing solution diffusion, particle position updating, boundary condition processing and repeated iteration; and copying the result data back to the CPU end from the GPU end, and exporting the result data for subsequent analysis and visualization.

The invention relates to the technical field of power sensing equipment fault prediction, in particular to a power sensing equipment fault prediction method and system and a storage medium. The method comprises the following steps of performing geometric model construction on power sensing equipment to obtain grid division model data; carrying out material attribute endowing based on association of microscopic characteristics and macroscopic attributes on the grid division model data to obtain material attribute grid model data; performing model parameter calibration on the material attribute grid model data to obtain a calibrated equipment twinborn body; carrying out environmental parameter loading on the calibrated twin of the equipment, and carrying out multi-physical field coupling simulation in the equipment to obtain stress field distribution data in the equipment; key point identification is carried out on the stress field distribution data in the equipment, and key point positions and stress data are obtained. The reliability of the power sensing equipment is improved through the power sensing equipment fault prediction technology, and the operation and maintenance cost is reduced.

The invention provides a position sensing monitoring method and device based on dynamic error compensation, and relates to the technical field of error compensation, and the method comprises the steps: constructing an initial three-dimensional model based on a target pipe network, and carrying out the division to obtain a grid division result; dynamically monitoring the first pipe network node through the distributed sensing equipment group to obtain first operation information; introducing a predetermined dynamic error compensation adjustment function to adjust and analyze the first operation information, obtaining first target operation information as analysis data of the leakage discriminator, and obtaining a first discrimination result of the leakage discriminator; and when the first discrimination result accords with a predetermined discrimination constraint, carrying out leakage emergency early warning on a first position corresponding to the first grid. According to the method and the device, the technical targets of multi-sensor cooperative monitoring, dynamic error compensation analysis and intelligent leakage judgment can be realized, and the technical effects of improving the leakage detection precision, reducing the false alarm rate, enhancing the environmental adaptability and optimizing the operation and maintenance efficiency and the safety of a pipe network are achieved.

The invention belongs to the technical field of flying probe machines, and particularly relates to a dynamic self-adaptive adjustment method, system and equipment for the needle inserting height of a flying probe machine based on grid division and a medium. A PCB board is simplified into small plane grids through the grid division technology, and the needle inserting height of each grid bonding pad is calculated in combination with a space plane equation; and the self-adaptive adjustment of the bonding pads with different heights is realized. The system is especially suitable for detecting complex plate surfaces such as warped plates, can accurately identify and adapt to plate surface deformation, and ensures the needle inserting precision. Meanwhile, the system acquires height information in real time by using the needle tip sensor, plans the test speed in advance, and realizes high-speed and accurate flying probe test. According to the invention, the test cost is reduced, the test efficiency and universality are improved, and a powerful guarantee is provided for the quality control and production efficiency of the electronic manufacturing industry.

The invention relates to the technical field of nuclear engineering mechanical simulation, and particularly discloses a rapid grid generation method for nuclear engineering typical components, which comprises the following steps: acquiring a geometric model and grid generation control parameters of a nuclear engineering typical component to be processed input by a user in a command stream mode; carrying out region identification according to the topological structure and the geometric features of the geometric model, and determining a grid division strategy of the geometric model according to a region identification result and grid generation control parameters, the grid division strategy at least comprises a region identification result of the geometric model and a grid division adaptation mode adapted to the region identification result of the geometric model, and the grid division adaptation mode at least comprises a grid division preselection mode; and according to a grid division strategy, performing grid division on a region identification result of the geometric model to obtain a grid generation result of the nuclear engineering typical component. According to the grid rapid generation method for the nuclear engineering typical component, the grid generation efficiency can be improved.

The invention provides a temperature control adjusting method and system for printing curing equipment. The temperature control adjusting method of the printing curing equipment comprises the steps that printing data information corresponding to a current printing task is uploaded to a database; the first grid setting factor and the second grid setting factor are used for carrying out grid division on a substrate surface irradiation area of the UV curing equipment, and a plurality of grid areas are obtained; performing target grid screening according to the real-time temperature change characteristic parameters of the grid region to obtain a target characteristic grid; and temperature compensation is carried out according to the adjustment target temperature obtained in the temperature control process of the UV curing equipment according to the temperature change characteristic parameters of the target characteristic grid, the compensated adjustment target temperature is obtained, and temperature regulation and control are carried out on the UV curing equipment according to the compensated adjustment target temperature. The system comprises modules corresponding to the steps of the method.

The invention provides a CAE modeling and grid dividing method and system based on natural language driving, and the method comprises the steps: constructing a triple language model, defining an action-object-adversity triple structure, receiving a natural language instruction, carrying out the standardization processing of the instruction, recognizing and extracting the action, object and adversity components in the instruction, and carrying out the recognition and extraction of the action, object and adversity components in the instruction. The missing necessary parameters are prompted and complemented; based on a predefined analysis rule, extracting a triple conforming to the triple structure from the processed instruction; mapping the triad passing the verification into a corresponding CAE operation instruction through a mapping rule base, and generating an instruction sequence according to a logic sequence of a CAE modeling process; and automatically executing the instruction sequence, completing CAE modeling and grid division operations, and finally outputting a CAE model file. According to the method, the user operation complexity and the professional threshold are remarkably reduced, the modeling efficiency and the model quality are improved, an efficient and intelligent auxiliary tool is provided for engineering design, and the wide application value is achieved.

The invention discloses a layout parameterization hierarchical parallel mesh generation method based on Net. The method comprises the following steps: inputting a layout design file, analyzing hierarchical structure identification ports, generating a port set P and creating an accessed port set V (initial V =); a graph G = (VG, EG) is constructed, VG comprises key vertexes or geometric centers of ports and conductor fragments, an electrically independent Net is generated through traversal of a breadth-first search algorithm or a depth-first search algorithm, and iteration is performed until V is completely equal to P; configuring independent subdivision parameters such as a grid size and a grid algorithm for each Net; net is used as an independent task, grids are divided through parallel computing frameworks such as multithreading, and a complete grid file for subsequent simulation is generated after merging. According to the method, Net automatic identification is realized through graph theory analysis; different Net precision requirements are adapted by differential subdivision parameters, so that waste of computing resources is avoided; through parallel processing, the time consumption of layout grid division is shortened to the time consumption of processing the maximum Net, and the efficiency and the flexibility of simulation pre-processing are remarkably improved.