206 results about "Grid density" patented technology

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 relates to the technical field of quality detection in material manufacturing and coating processes, in particular to an intelligent color difference analysis and detection method for paint, which comprises the following steps: S1, acquiring a multispectral dynamic compensation image; s2, texture-color coupling separation is carried out; s3, carrying out adaptive chromatic aberration modeling; s4, process correlation visualization is carried out, color difference data is mapped into a scalable thermodynamic diagram, and grid density is dynamically adjusted according to detection precision; and analyzing geometric feature parameters of the abnormal region, matching a process defect mode library to generate an optimization suggestion, and superposing the optimization suggestion on the thermodynamic diagram by a visual identifier. Through real-time data acquisition, texture interference elimination, model adaptive optimization and process defect analysis, the overall detection precision and efficiency are improved, the intelligent adaptive characteristic is achieved, and different production environments and base material types can be adapted, so that the coating production process is optimized, and the consistency of the coating quality is ensured.

The invention discloses a gas tank base stress finite element analysis method and system, electronic equipment and a storage medium, and the method comprises the steps that for a complex geometric structure of an LNG gas tank base, a self-adaptive mesh generation technology is adopted, a stress concentration area and stress gradient changes are comprehensively considered, refined modeling is carried out on the gas tank base, a high-quality finite element mesh model is obtained, and in the mesh generation process, the stress concentration area and the stress gradient changes are comprehensively considered; the grid density of a stress concentration area under the load effect is focused, the grid quality of the area is improved, and the stress gradient change is accurately captured; in an LNG gas tank base finite element model, key load working conditions are identified, characteristic parameters such as types, sizes, directions, frequencies and durations of typical loads such as the self weight, thermal stress and wind load of a gas tank are mainly analyzed, load-time historical curves under different working conditions are obtained through load spectrum testing, and a load combination method is adopted, so that the load-time historical curves under different working conditions are obtained. And the stress distribution rule of the gas tank base under the multi-load coupling effect is researched.

The invention discloses a probe card simulation method and system based on counter-acting force analysis, which are used in the field of wafer simulation test, and the probe card simulation method comprises the following steps: integrating multiple physical field working conditions to construct a probe card geometric model, and importing the probe card geometric model into finite element simulation analysis software; carrying out grid division on the geometric model of the probe card by utilizing the hybrid voxel tree model, adjusting the grid density according to the distribution requirement of the multi-physical field, and setting a simulation boundary condition by utilizing a preset boundary condition template according to the actual simulation requirement; starting a simulation calculation process based on the adjusted grid density and simulated boundary conditions; and providing a visual interface of physical field distribution and a structural stress state in the simulation calculation process, and performing iterative optimization on the performance of the probe card in the simulation process according to a reactive force distribution result. According to the method, the grid density is automatically adjusted to adapt to changes of a physical field, and it is ensured that higher simulation precision is obtained in a key area.

The invention relates to the technical field of underground pipe gallery asset management, and discloses a BIM-driven underground pipe gallery asset dynamic management and emergency decision-making platform, and the platform comprises a dynamic topology mapping module which achieves the dynamic grid density adjustment of a BIM model through monitoring the change rate of environment parameters, and generates a logic topology network synchronized with a physical pipe gallery structure in real time; the asset state reverse derivation unit is used for reversely deducing asset degradation based on environmental data by using a physical rule library dynamically loaded in a time-sharing domain; the logic rule self-triggering engine constructs a multi-level response rule chain containing space-time prediction and optimizes an emergency plan; and the edge-cloud collaborative architecture synchronously realizes real-time decision-making of low bandwidth dependence through intelligent cache and asynchronous increment. When dynamic topological mapping is driven by the change rate of environmental parameters, the real-time state of the underground pipe gallery can be represented more finely, and a high-reliability data basis is provided for subsequent accurate analysis and decision making.

The invention relates to the technical field of virtual modeling, in particular to a lamp arrangement method and system based on virtual modeling and a medium. The method comprises the following steps: obtaining dynamic monitoring data of a target space, wherein the dynamic monitoring data comprises real-time illumination intensity data, people flow density data and ambient light change data; performing prediction modeling on the illumination demand of the target space according to the dynamic monitoring data to obtain illumination demand prediction data including expected illumination requirements and light distribution characteristics in different time periods; the adaptive light propagation grid is constructed in the digital twinborn space based on the illumination demand prediction data, grid division data are obtained, and the adaptive light propagation grid has high grid density in a region with severe illumination change and low grid density in a region with smooth illumination change. According to the method, comprehensive illumination analysis and evaluation can be carried out in the initial stage of design, and blindness and low efficiency in a traditional design method are avoided.

The invention relates to a pollutant concentration diffusion simulation method based on grid optimization and self-regulation. The method comprises the following steps: carrying out basic grid division on a simulation area to obtain a basic grid; calculating a pollutant concentration field of the simulation area according to the spatial position and the pollutant concentration value of the monitoring station; generating a concentration distribution matrix according to the pollutant concentration field of the simulation area, and then dynamically adjusting the grid density of the basic grid; calculating the calculation complexity of each grid region by using the grid density of the adjusted basic grid, carrying out pollutant concentration calculation task allocation according to a cloud platform and a weighted polling algorithm, and forming a pollutant concentration distribution prediction result of the simulation region by a pollutant concentration prediction result of each grid; and dynamically adjusting a pollutant concentration distribution prediction result according to the Kalman filtering and the obtained real-time environment data to obtain a final pollutant concentration prediction value. By adopting the method, the precision and the real-time performance of pollution diffusion simulation can be improved.

The invention relates to the technical field of point cloud de-noising, and discloses a substation equipment laser radar point cloud de-noising method based on space grid density, comprising the following steps: S1, acquiring point cloud data, and preprocessing the point cloud data; s2, analyzing point cloud features, and performing point cloud type division by utilizing the features of equipment and ground point cloud on elevation distribution; and S3, removing noise points through a density difference method by using the relative distribution characteristics of the equipment point cloud and the ground point cloud with the noise. The multi-dimensional subspace grid density difference segmentation method based on the three-dimensional laser point cloud suitable for the extra-high voltage transformer substation is provided for overcoming the defects that an existing method is too high in dependence degree on a big data technology, and the method can efficiently and accurately remove noisy three-dimensional point cloud data according to different scanning modes and different data types, so that the accuracy of the three-dimensional subspace grid density difference segmentation method based on the three-dimensional laser point cloud is improved. And on the basis of noise processing of massive three-dimensional point cloud data, automatic extraction of the extra-high voltage substation equipment can be completed more accurately and efficiently.

The present invention relates to the technical field of natural ventilation in buildings, and in particular to a computationally assisted decision-making method and system for climate-adaptive building cavity design. The method comprises: using a Delaunay triangulation method to generate an initial mesh, using a Laplace operator-based mesh refinement method to adaptively refine the initial mesh, so as to obtain an adaptive mesh system, wherein the adaptive mesh system is used for dynamically adjusting the mesh density of conditional PINNs; constructing a multi-task learning framework within the conditional PINNs, wherein the multi-task learning framework is used for jointly predicting a plurality of physical field variables within the conditional PINNs; and iteratively training the conditional PINNs, and using a gradient descent algorithm to minimize a loss function until a predetermined number of training iterations or loss convergence is reached, thereby generating a key physical field variable prediction model in building cavity design. The present invention can implement efficient and accurate prediction of key physical quantities in building cavity design, and can be adapted to different building layouts and functional space characteristics.

The invention relates to the technical field of unmanned aerial vehicle path planning methods, in particular to an unmanned aerial vehicle path planning method based on an improved leapfrog algorithm. According to the method, dynamic weight adjustment information is obtained by carrying out dynamic adaptation matching analysis on flight stage information and environment threat information, a flight stage weight mapping matrix is established, and fitness function weights are dynamically adjusted according to core targets in take-off, cruise and landing stages; weight correction is carried out in combination with environmental data such as obstacle grid density and a meteorological threat coefficient, so that the algorithm focuses on core constraints in the current stage, and target conflicts caused by global unified weight are avoided; according to the method, environmental threats are sensed in real time by means of multi-sensor fusion, when abnormal states such as over-high obstacle density and strong wind are detected, an algorithm is triggered to be suddenly stopped and restarted, a population is reconstructed according to the current position, threat avoidance weight is enhanced, the defect that an existing mechanism can be updated only after the current iteration period is completed is overcome, and the method is suitable for large-scale popularization and application. And the response time to an abnormal environment is shortened.

The invention discloses a self-adaptive Monte Carlo macro particle simulation method and system based on parallel computing, and relates to the technical field of particle simulation, and the method comprises the steps: initializing parameters, if the current step number is not the maximum step number, storing node data, balancing particle loading, and calculating charge density and battery density; using macro particles to represent a group of real particles, updating the positions and speeds of all the particles in parallel, and calculating new charge distribution; setting adaptive grid configuration, and dynamically adjusting grid density according to electric field intensity and local density of charge distribution; and based on the updated particle position and speed, evaluating and processing a collision event, storing collision data, re-calculating surface charge density data, adding 1 to the current step number, and circularly executing to finish simulation when the maximum step number is reached. According to the method, the accuracy of a simulation result is improved through the improved collision model, electrical discharge behaviors under different conditions are better predicted, and more reliable data support is provided for design and safety evaluation of high-voltage equipment.

The invention relates to the field of vacuum circuit breakers, in particular to a vacuum circuit breaker opening and closing dynamic characteristic calculation method, device and equipment and a medium. Establishing a three-dimensional geometric model of the pole-mounted vacuum circuit breaker arc extinguish chamber and the moving and static contacts; setting material attributes for each part in the three-dimensional geometric model; constructing a multi-physics field coupling system; the area where the moving contact is located is divided into movable grids, and the grid density of the moving contact and the grid density of the static contact dynamically change along with time; and performing multi-field coupling transient solution according to the three-dimensional geometric model, the multi-physical field coupling system and the movable grid to obtain the dynamic characteristics of the vacuum circuit breaker. The electromagnetic field, the thermal field, the fluid field, the structure field and the circuit are subjected to full coupling analysis, multi-physical field strong coupling dynamic simulation of the whole opening and closing process is achieved, and the dynamic characteristics of the whole opening and closing process can be accurately calculated.

The invention provides a grid clustering method and device, equipment and a storage medium, and the method comprises the steps: carrying out the layer-by-layer grid division of a target region represented by a target image according to each resolution corresponding to the target image, and obtaining N target grids corresponding to the target region; counting the grid density corresponding to each target grid to obtain N grid densities; sorting the N target grids according to the sequence of the corresponding grid densities from high to low to form a grid sequence; and clustering the N target grids according to the sequence of the N target grids in the grid sequence and the grid density corresponding to each target grid to obtain M clusters. In the embodiment of the invention, the target area is subjected to grid division through the hexagonal grid, so that the deviation and error of the clustering result can be reduced; in this way, the curvature and the non-rectangular terrain of the target area are adapted through a hexagonal grid clustering method, and the accuracy of a clustering result is improved.

The invention relates to the technical field of image reconstruction, in particular to a lung puncture three-dimensional image reconstruction positioning system and method. The method comprises the following steps that CT scanning sequence data and chest wall multi-point infrared mark data of a patient are obtained, wherein the chest wall multi-point infrared mark data comprise respiration reference position data, real-time angular velocity data of a chest wall motion state and real-time acceleration data of each point of the chest wall; and inputting the real-time angular velocity data and the real-time acceleration data into a lung tissue nonlinear viscoelasticity prediction model based on a Maxwell model according to the chest wall multi-point infrared marking data to carry out iterative calculation so as to obtain lung tissue stress-strain relation data. According to the method, the non-feature region can be simplified while the grid density of the feature region is kept, the calculation burden is greatly reduced, and the detail and global consistency of reconstruction is ensured.

The invention provides a curved surface grid generation method based on discrete grid parameterization, and belongs to the technical field of computer aided engineering (CAE) and computational geometry. Aiming at the problems of tedious geometric operation, parameter space fusion distortion, insufficient grid fitness and the like in grid subdivision of a complex curved surface formed by a plurality of sub-curved surfaces, the invention provides the following technical scheme: firstly, carrying out triangular grid pre-subdivision on an original curved surface, and constructing a virtual topological structure for inhibiting non-key features; the discrete grids are mapped to a low-distortion two-dimensional parameter space by adopting least square conformal mapping (LSCM), and seamless combination of multiple sub-surface parameter domains is realized; dynamically calculating a parameter space size field, and controlling grid density distribution; after a parameter space adaptive grid is generated through Delaunay triangulation, grid points are accurately attached to an original geometric surface by using a dual projection correction mechanism. According to the method, complex CAD geometric operation is avoided, the automation degree is remarkably improved, meanwhile, physical space grid uniformity and strict fitness are guaranteed, and the method is suitable for efficient and high-precision grid generation of complex curved surfaces in the fields of aerospace, automobiles, ships and the like.

The invention discloses a hydraulic engineering operation and maintenance data monitoring method and system based on digital twinning, relates to the technical field of data analysis, and comprises the steps of defining multi-physics field coupling related to a three-dimensional structure region model, and providing a basis for subsequent model grid density setting. And performing clustering analysis on the region according to the geological features and the structural features on the three-dimensional structural region model. The grid density grade of each type of region is evaluated based on the grid attribute, the multi-physics field coupling strength and the uncertainty parameter, a flexible grid density grade determination mode is carried out on different regions, the reliability and precision of model gridding processing are improved, and the uncertainty condition can be captured more accurately. The operation and maintenance event and the event state of the water conservancy project are monitored through the multi-physics-field multi-grid digital model, current time monitoring and future time prediction of the operation and maintenance event are achieved, the accuracy and adaptability of water conservancy project operation and maintenance monitoring are improved, and the complex and changeable monitoring requirements of the water conservancy project are met.

The invention provides a river flow velocity intelligent monitoring method and system based on multi-scale optical tracking velocity measurement. A plurality of detectors with different characteristics are organically combined, and dynamic grid density adjustment based on flow velocity gradient is realized through adaptive grid adjustment; establishing a multi-dimensional track quality evaluation system through intelligent track evaluation; the real-time performance optimization realizes the performance optimization of multi-thread parallel processing, integrates an intelligent grid optical flow detection and dynamic density adjustment mechanism, and optimizes the detection precision and performance in real time according to the flow velocity gradient and the flow field complexity; a multi-track quality evaluation system is utilized, tracks are screened and fused from three dimensions of motion consistency, physical constraint and time stability, and the accuracy and reliability of data are remarkably improved. The method overcomes the problems that a traditional speed measurement method is complex in operation, limited in environment, insufficient in precision and the like, supports real-time processing, can be widely applied to the fields of water conservancy projects, environment monitoring, flood prevention early warning, scientific research and education and the like, and has remarkable advancement and practical value.

The invention discloses a scene preprocessing method for fire simulation, and relates to the technical field of building fire simulation, and the method comprises the steps: calculating a three-dimensional thermal weight through employing a fire propagation dynamics model, and generating a fire dangerous region thermal diagram; through a tensor field generation algorithm, fire behavior main diffusion direction and each axial anisotropic parameter are extracted, and fire behavior grid parameters are generated; through a hybrid grid generator, performing hexahedron dominant grid construction and increasing the grid density of a fire behavior dangerous area to obtain a fire behavior optimization hybrid grid; performing Reynolds number verification and boundary layer matching on the fire behavior optimization hybrid grid through a fire behavior feature adaptive algorithm, and performing iterative correction to generate a fire simulation correction grid; according to the invention, through the hybrid grid generator, the self-adaptive distribution of the grid density of the fire hazard area and the smooth connection of the transition area are realized, so that the grid distribution of the fire hazard area is accurately matched with the fire spreading characteristics.

The invention provides an image processing method and device, equipment and a storage medium, and the method comprises the steps: determining the grid density information of a to-be-rendered model according to the vertex data of the to-be-rendered model, and determining the screen space proportion information of the to-be-rendered model according to the position information of the to-be-rendered model, and determining sampling weight information corresponding to the to-be-rendered model according to the grid density information and the current screen space proportion information, and sampling a map corresponding to the to-be-rendered model according to the sampling weight information to render the to-be-rendered model. According to the method, the UV coordinates of the to-be-rendered model do not need to be manually created, so that the workload is reduced, and the problem of UV seams is avoided. And the three-dimensional model with a larger area ratio in the screen can obtain higher rendering precision during rendering, and the three-dimensional model with a small area ratio can obtain lower rendering precision during rendering, so that the consumption of computing resources is reduced, and the rendering efficiency is further improved on the premise of ensuring the rendering effect.

The invention discloses a multi-point shape-preserving multi-scale optimization design method for variable stiffness of a fiber reinforced composite material, and relates to the field of variable stiffness design of the fiber reinforced composite material. Based on a normal distribution fiber optimization interpolation format, a multi-point shape-preserving design and an artificial weak unit concept are introduced; a fiber reinforced composite material multi-point shape-preserving multi-scale variable stiffness optimization design research is developed, and the analysis sensitivity of a design variable to multi-point shape-preserving constraint is deduced through an adjoint vector method. The method solves the following difficulties in the prior art: (1) the calculation time consumption is huge due to the increase of the design variables along with the grid density and the number of alternative fiber laying angles; (2) adopting the minimum displacement of all nodes in a local area as a design target to cause an unfavorable fixed area with a pure rigid shape and a fixed position; (3) the perforated structure does not have actual physical elements for calculating the local deformation energy of the structure; and (4) after the artificial weak unit concept is introduced, the analysis sensitivity derivation is difficult.

The invention belongs to the technical field of engineering mechanical structure health monitoring, and particularly relates to a dynamic prediction method for multi-working-condition stress of a tower crane based on a constraint space Kriging agent model. Comprising the steps of system parameter acquisition and constraint space construction, physical constraint sample generation, efficient stress sample calculation, agent model training and real-time stress distribution prediction. According to the method, the Kriging agent model and the variable grid density optimization strategy are organically combined, the calculation efficiency is high, the efficient dynamic prediction capability is achieved, and the real-time prediction requirement under the dynamic working condition is met; a Latin hypercube sampling method in a physical constraint space is adopted, and a simulated annealing optimization technology is combined, so that invalid sample points are effectively eliminated, and the utilization rate of a sample space is improved; a nonlinear mapping relation between multiple parameters of hoisting weight-amplitude-speed and full-beam long stress distribution is established through a Kriging agent model, the limitation that a traditional method only supports fixed working conditions is broken through, and an accurate and rapid response model is provided for structural health monitoring under complex working conditions.

The invention provides a gas detection system and device, and relates to the technical field of gas detection, and the system comprises a configuration module which is used for carrying out the type selection configuration of a monitoring sensor according to the monitored gas; the reference construction module is used for constructing reference grid density based on the minimum coverage area of the monitoring sensor; the monitoring node establishment module is used for performing region importance calculation on the to-be-monitored region and configuring monitoring nodes; the collaborative analysis module is used for acquiring and establishing a monitoring sensor array and establishing an associated collaborative coefficient; and the detection module is used for calling a decision fusion network to carry out abnormal decision making on the monitoring data based on the association cooperation coefficient, and generating a gas detection result. By means of the gas detection method and device, the technical problem that in the prior art, due to the fact that selection and configuration of the sensors are not adjusted according to actual requirements, the gas detection precision is low can be solved, the sensors are reasonably configured according to the gas type and the region importance, and the gas detection precision is improved.

The invention provides a three-dimensional modeling method and device, electronic equipment and a storage medium. The method comprises the steps of obtaining multi-source data of a to-be-constructed model; dividing the initial grid based on the geometric feature density of the to-be-constructed model to obtain an initial grid frame of the to-be-constructed model; optimizing the grid density of the initial grid frame based on the curvatures of different positions of the to-be-constructed model; fusing the multi-source data to the optimized grid vertexes to obtain a grid model after each vertex is fused with the multi-source data; carrying out iterative optimization on a grid topological structure of the grid model; and outputting the three-dimensional model obtained by final iteration through a preset format. According to the invention, by dynamically adjusting the grid density and fusing the multi-source data, the precision and efficiency of three-dimensional modeling are improved.

The invention provides a gallium nitride device-oriented three-dimensional electromagnetic-thermal co-simulation method, which relates to the technical field of gallium nitride devices, and comprises the steps of generating a training sample set by collecting device parameters, obtaining electromagnetic field and temperature field feature vectors to establish a control equation set, carrying out grid division by adopting a self-adaptive hierarchical subdivision method, and obtaining a three-dimensional electromagnetic-thermal co-simulation result. Grid density distribution is determined based on the temperature gradient and the material interface characteristics, and a multi-level grid structure is generated; solving the electromagnetic field equation to obtain loss power density, and establishing a temperature field heat source item to calculate temperature distribution; and judging the thermal stability state according to the temperature change rate, updating the material parameters and optimizing the grid structure. According to the method, high-precision simulation of electromagnetic-thermal coupling analysis is realized, and the calculation efficiency is improved.

The invention provides a grid generation method and device for a nuclear power fuel assembly and a computer readable medium, and the method comprises the steps: receiving a geometric file of the nuclear power fuel assembly, and generating a hybrid grid of the nuclear power fuel assembly according to a grid generation strategy and the geometric file, the grid generation strategy comprises the steps that a structured grid is used in a boundary layer of the nuclear power fuel assembly, and an unstructured grid is used in an area outside the boundary layer; the generated hybrid grid is subjected to self-adaptive refinement processing, the self-adaptive refinement processing comprises the steps of recognizing a high-gradient area and increasing the grid density in the high-gradient area, and the high-gradient area refers to the area where the change rate of fluid parameters in space is larger than a preset threshold value when fluid flows along the wall face of the nuclear power fuel assembly. According to the method, the grid density is only increased in a high-gradient region, and relatively thick grids are kept in other regions, so that the resolution of a key region is ensured, and the waste of computing resources is effectively reduced.

The invention relates to a BIM (Building Information Modeling)-based building structure modeling method, device, equipment and medium, and the method comprises the steps: aiming at a curvature-mechanics semantic fault problem existing in a process of converting a special-shaped curved surface structure from a BIM geometric model to finite element analysis, generating a curvature tensor field with parameter coordinates by analyzing an NURBS curved surface; integrating along the maximum curvature change direction to construct an internal force flow function, and forming a guide field for controlling the grid density; shell / beam units are divided based on the guide field gradient, space coordinates are marked, and a curvature-stiffness matrix and an internal force flow driving variable cross-section are combined for calculation to generate a structural analysis model; the gradient distribution of the guide field is dynamically corrected through displacement error feedback, and lossless transmission of geometric topology and mechanical properties is achieved. According to the method, the distortion risk of special-shaped structure analysis is remarkably reduced, artificial experience correction is avoided, and high-precision automatic modeling support is provided for a complex building structure.

The invention relates to the field of environmental pollution simulation and control, and discloses a radioactive consequence diffusion simulation system in an environment, which comprises an input and preprocessing module used for receiving simulation input data, including pollution source position, release intensity, terrain and environmental parameters, and initializing calculation conditions and a concentration field; the multi-medium coupling module is used for realizing material flux coupling among atmosphere, water and soil through interface conditions; the self-adaptive grid module is used for dynamically adjusting the grid density according to the concentration gradient and error estimation in the diffusion result so as to optimize the calculation precision of the hot spot region; and the solving and control module is used for solving the high-dimensional nonlinear partial differential equation set of the multi-medium coupling model and dynamically adjusting the time step. Diffusion behaviors in atmosphere, water and soil are processed by modules, and cross-medium dynamic flux coupling is realized through interface conditions, so that the technical effect of accurately predicting diffusion paths of pollutants in a complex environment is achieved.

The invention relates to the technical field of three-dimensional modeling, in particular to a three-dimensional rapid modeling method and system for a gantry crane. The method comprises the following steps: obtaining structural parameter template data and installation site wind condition data of the gantry crane; establishing a parameterized geometric model template according to the structural parameter template data, and determining a wind load sensitive part distribution diagram in combination with the wind regime data of the installation site; dividing structural modeling precision grades according to the wind load sensitive part distribution diagram, and generating a differentiated grid density distribution scheme; constructing multi-precision hybrid modeling framework data according to the differentiated grid density distribution scheme and the parameterized geometric model template; key geometric feature parameters are extracted based on multi-precision hybrid modeling framework data, and a parameter adaptive adjustment rule is established according to a wind load sensitive part distribution diagram; according to the method, geometric weak points are positioned through wind load pre-evaluation, local grid encryption and geometric optimization are automatically executed, and the reliability of model safety evaluation is improved.

The invention discloses a springback compensation control system for a metal stamping part, and belongs to the technical field of metal plate forming. The system comprises a stress memory prediction module, a fractal compensation analysis module, a phase change compensation regulation and control module, a compensation decision fusion module and an execution feedback optimization module. The stress memory prediction module extracts stress evolution characteristics of the stamping process through a multi-scale memory network and a time decay attention mechanism; the fractal compensation analysis module adaptively adjusts the compensation grid density based on the fractal dimension to realize optimal configuration of computing resources; the phase change compensation regulation and control module predicts the phase change behavior of the material through the thermal-mechanical coupling constitutive model and calculates the compensation correction amount caused by phase change; the compensation decision fusion module intelligently fuses three compensation strategies by adopting Bayesian reasoning and a spatial modulation function; and the execution feedback optimization module realizes continuous optimization of the system through online learning. According to the method, the influence of three dimensions of stress history, geometric complexity and material phase change is comprehensively considered, accurate prediction and compensation of the springback behavior are achieved, and the forming precision and production efficiency of the metal stamping part are remarkably improved.

The invention provides a construction method of a fiber concrete fiber bridging numerical analysis model, and belongs to the technical field of fiber concrete. The method comprises the following steps: firstly, establishing a nonlinear slippage constitutive relation of a fiber-matrix interface; secondly, adopting a probability density function to describe anisotropic distribution of a three-dimensional fiber direction angle, simulating randomness of fiber embedding length in combination with logarithmic normal distribution, and introducing a correction factor to quantify interaction between fibers; secondly, mapping a debonding behavior of a microscopic interface to a macroscopic fracture surface through a heterogeneous data transfer protocol to realize seamless coupling of a multi-scale mechanical state; meanwhile, the grid density of the crack tip area is dynamically optimized by combining posterior error estimation and an unstructured hexahedral grid local subdivision technology. By the adoption of the method, the limitation of a traditional model in the aspects of interface behavior characterization, fiber distribution idealized assumption and grid rigid division is effectively solved, and the precision and reliability of fiber bridging effect simulation are remarkably improved.