349 results about "Mesh generation" patented technology

The invention belongs to the technical field of simulation analysis, and particularly relates to a medium-high voltage switch cabinet internal humidity inversion calculation method based on simulation analysis, which comprises the following steps: establishing a geometric model of a switch cabinet, importing the geometric model into finite element simulation software to obtain a simulation analysis model, adding each physical field and computational domain and boundary conditions thereof, and calculating the internal humidity of a medium-high voltage switch cabinet. All the physical fields are coupled, and mesh generation is carried out; performing numerical solution on the simulation analysis model by using a transient solver to obtain a temperature and humidity distribution condition in the switch cabinet; the simulation analysis model is optimized, a simulation data set is constructed, and a PINN is trained; based on the environment temperature and humidity and the operation current collected in the actual operation of the switch cabinet, the trained PINN is used for prediction, and the steady-state relative humidity of the current transformer is obtained. According to the invention, based on the limited boundary monitoring data, efficient and accurate reconstruction of the humidity field of the key area in the switch cabinet is realized, and a feasible path is provided for equipment state sensing and condensation risk early warning.

The invention discloses an electromagnetic field simulation grid adaptive generation method based on a neural network. The method comprises the following steps: performing mesh generation on a semiconductor device simulation model to obtain original generation data, and constructing node features; an undirected graph is constructed, graph nodes of the undirected graph adopt node features of grid points, and connecting edges adopt Euclidean distances between the grid points and adjacent grid points; inputting the undirected graph into a double-branch neural network, and outputting a predicted node position; and correcting each node of the original subdivision data by using the predicted node position obtained by the double-branch neural network to form new subdivision data for electromagnetic field simulation. According to the method, physical field information can be fused to efficiently adjust the node density, and the geometric boundary and topological structure characteristics of the device can be strictly kept.

The invention relates to the technical field of face verification, and discloses a face identity verification data processing method based on dynamic feature extraction, which comprises the following steps: acquiring a continuous face video frame sequence and calculating a full-pixel instantaneous velocity vector to generate an original dense optical flow field, selecting rigid region anchor points to calculate a rigid affine transformation matrix and construct a theoretical rigid motion field, performing differential stripping on the theoretical rigid motion field from the original dense optical flow field, and extracting a non-rigid micro-motion residual field; mapping the non-rigid micro-motion residual field to a facial muscle topological grid to generate a time sequence feature tensor, and calculating a geodesic line distance between a covariance matrix of the time sequence feature tensor and a reference dynamic feature in a Riemannian manifold space; when the geodesic distance is smaller than a threshold value, verification is passed, through a rigid-non-rigid orthogonal decomposition mechanism, the special viscoelastic micro-motion and cooperation law of biological soft tissue is captured by utilizing a residual field, and the high-simulation mask is effectively defended.

The invention relates to the field of biological modeling, and discloses a shoulder joint stress simulation method and system based on a three-dimensional finite element. The method comprises the following steps: acquiring three-dimensional geometric data of a shoulder joint through scanning equipment, and generating an initial grid model; dividing the preliminary calculation grid to determine an initial stress value, simulating stress transfer distribution, and generating a preliminary stress distribution field; calculating the stress gradient change rate of each grid unit and performing local subdivision to generate a stress gradient change rate distribution diagram; performing density subdivision on the grid units exceeding the change threshold to generate a refined grid model; the calculation grid is divided again, the stress value of each grid unit is calculated, and an updated stress field is generated; calculating a difference vector, judging whether the difference vector meets a convergence condition or not, and obtaining a convergence judgment result; and if not, iteratively subdividing the local grid to generate a final stress distribution field. Through adaptive grid subdivision and iterative convergence optimization, the problem of insufficient simulation precision is solved, and the accuracy is improved.

The invention discloses a thin-wall structure layered body grid generation method based on surface grid alignment, which comprises the following steps of: reading an integral surface grid with a thin-wall structure characteristic and a mapping relation, and pairing a source surface grid and a target surface grid in the integral surface grid according to the mapping relation; aligning the source surface grid and the target surface grid which are paired, updating the target surface grid, and extracting triangular mapping information of an aligned region; according to the mapping information, advancing a source surface grid to a target surface grid layer by layer to obtain a layered body grid; extracting the outer surface of the stratified body mesh, combining the outer surface of the stratified body mesh with the overall surface mesh to obtain a combined surface mesh, and performing mesh point classification; normalizing the unit normal direction of the combined surface grid, calculating the normal direction at grid points needing to be propelled according to the grid point classification, and interpolating points according to distances in the normal direction to form a constraint point set; and generating a cavity area body grid by taking the constraint point set and the combined surface grid as constraints, and combining the cavity area body grid with the layered body grid to obtain the layered body grid of the overall thin-wall structure.

The invention discloses a polygonal and quadrilateral mesh automatic subdivision method based on deep reinforcement learning, relates to the field of computational geometry and mesh generation, and constructs an automatic subdivision framework fusing geometric priori knowledge and a data driving strategy. According to the method, nine basic topology filling templates covering triangles to hexagons are predefined as discrete action spaces, and continuous geometric segmentation is converted into a sequence decision problem; learning a mapping relation between the polygon state characteristics and the optimal template selection strategy by using a deep Q network, and balancing exploration and utilization through a dynamic epsilon-greedy mechanism; and in combination with a vertex number priority scheduling strategy and a multi-dimensional quality award function, guiding an intelligent agent to adaptively generate a high-quality quadrilateral grid. According to the method, full-automatic and high-robustness subdivision of the complex polygon area is achieved, the grid orthogonality and the length-width ratio quality are remarkably improved, manual intervention is avoided, and the method is suitable for engineering scenes such as finite element analysis.

The invention discloses a multi-field coupling concrete dam parameter intelligent inversion method, system and device based on deep learning and a medium, and belongs to the technical field of dam engineering safety monitoring and computational mechanics crossing. The geometry and boundary modeling unit is used for uniformly expressing a dam body-dam foundation geometric region and a boundary type; simultaneously representing a state field and a parameter field by utilizing PINN inversion, calculating a physical residual error, and implementing parameter physical feasibility constraint and prior regularization; the organization optimizer, residual drive sampling and weight self-adaption are used for training scheduling, and result review, visualization and data export are carried out through the verification and output unit. According to the method, end-to-end parameter field inversion is realized on the premise of not depending on frequent mesh generation, the calculation cost of multiple forward modeling is reduced, the non-uniqueness of inversion is inhibited, and the method has higher recognition capability for engineering concerned areas such as permeation channels and degraded zones.

The invention provides a well-ground frequency domain electromagnetic detection method and device and electronic equipment, and the method comprises the steps: setting a perfect matching layer based on stretching coordinate transformation at the outer side of a model based on a three-dimensional geologic model, constructing an overall computational domain, facing the overall computational domain, and implementing adaptive mesh generation according to posterior error estimation. And generating an unstructured tetrahedral mesh which is locally refined in a target area, and on the tetrahedral mesh, performing spatial discretization and solution on a frequency domain Maxwell equation by adopting a first-order or second-order vector finite element in an H (curl) space to realize well-ground frequency domain electromagnetic forward modeling calculation. According to the method, through cooperation of the adaptive grids and the vector finite elements under the microframework, both precision and efficiency are considered, forward modeling stability and imaging resolution are improved, and a scientific basis is provided for efficiency improvement and cost saving of mineral resource exploration and development.

The invention provides a dynamic grid updating and scheduling method and system for watershed scale ecological restoration. The system comprises a data fusion access module, a dynamic grid generation module and a central cooperative controller. The data fusion access module is used for receiving multi-source heterogeneous data, the dynamic grid generation module is used for constructing an initial watershed grid by adopting a quadtree space division algorithm based on the multi-source heterogeneous data, and the central cooperative controller is used for periodically scanning a full-watershed grid set. Comprehensively judging information value density and updating urgency of each grid according to a multi-dimensional index; by adopting the above technical scheme, the autonomous evolution and precise adaptation of the watershed spatial discretization unit can be realized, the global monitoring breadth and the local description precision are dynamically balanced, and the response sensitivity to an emergent ecological event is improved.

The invention belongs to the technical field of underwater propeller design, and discloses an annular propeller modeling and hydrodynamic performance evaluation method and system. The method comprises the following steps: defining a distribution rule of blade parameters along a wheelbase based on a segmented cubic Hermite interpolation method, and realizing parametric modeling; automatically generating a propeller three-dimensional geometric model and a flow field computational domain; carrying out discretization processing on the rotating domain and the outer watershed by adopting a hybrid grid technology; hydrodynamic performance data are obtained through numerical simulation calculation, and thrust, torque and efficiency coefficients are obtained through processing; and completing multi-working-condition performance calculation and drawing an open water curve by automatically and cyclically updating a speed coefficient, and finally storing design variables and performance response data into a database. According to the method, full-process automation from modeling, grid division, simulation calculation to post-processing is achieved, the efficiency of annular propeller design and hydrodynamic performance analysis is remarkably improved, and the labor cost and the time cost are greatly reduced.

The invention discloses an aircraft surface structure grid generation method based on semantic tags and sequence constraints, and relates to the field of computational fluid mechanics pretreatment and grid generation, and the method comprises the steps: carrying out the part semantic recognition of an aircraft CAD model, and obtaining a part set with semantic tags and key geometric feature lines; generating a topological structure block composed of quadrilateral logic units for each component; determining a component generation sequence of the whole machine surface grid based on component semantics; inputting the topological structure block, the semantic tag and the working condition parameters of the first part into a graph neural network GNN, predicting a size distribution function of a topological edge by the GNN, and outputting initial node distribution; sequentially generating all component grids according to the determined sequence; and finally, post-processing is carried out to output a complete and closed complete machine surface structure grid. According to the method, the end-to-end automatic generation from the CAD model to the high-quality surface structure grid is realized, the natural matching of the grids among the parts is ensured, and the grid generation efficiency and quality are remarkably improved.

The invention discloses a ship bollard identification method and system based on adaptive multi-scale multi-grid division, and belongs to the technical field of computer vision and image processing. The system divides an image foreground region and a background region through a visual saliency calculation module, carries out dense sampling in the foreground region and sparse sampling in the background region by adopting a non-uniform grid generation module, screens candidate grids in combination with gradient direction consistency and texture features, fuses candidate frames of different scales through a multi-scale image pyramid, and finally obtains a multi-scale image. And accurate positioning of the bollard is realized through the fine grid accurate positioning module. The method solves the problem that the prior art is insufficient in adaptability to ship size, shooting distance and resolution change, improves the precision and generalization ability of bollard positioning in a complex scene, and is suitable for bollard detection scenes of various ship images.

The invention discloses a battery microstructure three-dimensional reconstruction simulation method and system based on an electrochemical model and computer equipment. The method comprises the following steps: acquiring a lithium ion battery electrode scanning sequence image, and acquiring a three-dimensional voxel model and an electrode grid chart; s2, acquiring key microstructure parameters of the electrode; s3, performing mesh generation on three-phase voxels in the electrode mesh chart to obtain a mesh file for finite element calculation; and S4, comparing the experimental data of the battery with the simulation data of the three-dimensional microstructure electrochemical model, adjusting the precision of the three-dimensional microstructure electrochemical model, and optimizing related parameters. According to the invention, three-phase accurate segmentation is carried out by using filtering and denoising, image enhancement and connectivity and a watershed segmentation algorithm, and a three-dimensional voxel model containing real particle morphology, cracks and pores and an electrode grid chart are reconstructed; the problems that in the prior art, a lithium ion battery microstructure simulation model is large in idealization deviation and inconsistent with a real structure, and consequently performance prediction is inaccurate are solved.

The invention discloses a building design modeling method and system based on a parameter entity and a Boolean relationship thereof, and the method comprises the steps: converting a plurality of building components into geometric body data based on a structure shape, and abstracting a single geometric body into a whole model according to the Boolean relationship between the building components required by the design; the method specifically comprises the steps that firstly, building design related component data given by a user is preprocessed, a two-stage structure is adopted to redefine a geometry, the geometry is stored, and the Boolean relation between components is represented through a tree structure; the preprocessed data are transmitted into a grid generation solver, and a final three-dimensional model and affiliated topological information are obtained through background grid and contour surface construction, topological information integration and grid post-processing. The method can ensure that the building design modeling process has good robustness and calculation efficiency.

The invention provides an intelligent grid size field prediction method, which comprises the steps of inputting geometric data, material parameters and boundary conditions of a to-be-processed CAE model, automatically extracting an input feature set, inputting the input feature set into a trained hybrid model, and outputting an initial grid size field; and performing post-processing on the initial grid size field, including performing smoothing processing by adopting Gaussian filtering to ensure that the size difference of adjacent patches does not exceed 20%, executing constraint verification to ensure that the grid size is within a preset range, and performing multi-physical field adaptation to take the minimum value of the size required by each physical field. And generating a CAE (Computer Aided Engineering) grid based on a post-processing grid size field driving grid generation algorithm, feeding back the grid quality in real time in a grid generation process, and if the grid distortion rate exceeds 5%, predicting and adjusting the size again. According to the method, the grid generation efficiency is remarkably improved, the manual intervention cost is reduced, the simulation precision and stability are ensured, and the method is suitable for complex engineering analysis scenes in the industries of aerospace, automobiles and the like.

Described is a system for generating meshes by receiving a prompt from a developer, accessing a default head mesh rigged to facial features of a default head, modifying the default head mesh by inputting the prompt into a stable diffusion model, retrieving gradients from the stable diffusion model, and adjusting a plurality of vertices on the default head mesh according to the gradients, accessing a camera feed from a camera system of a user, the camera feed including a head of the user, and applying a first content augmentation corresponding to the modified head mesh to the head of the user in the camera feed.

A stratum reinforcement modeling and analysis method for a shield tunnel crossing an existing structure is provided. Geological information and an engineering structure condition of the existing structure are acquired. Physical parameters of different soil mass layers are determined based on a laboratory test. A three-dimensional (3D) model is constructed. Mesh generation is performed on the 3D model defining a constraint for the 3D model. Model parameters are selected for the 3D model. A soil mass constitutive model is selected for the 3D model. Synchronous grouting simulation, construction load simulation and shield tunneling construction simulation are performed on the 3D model. Stratum parameters are changed to achieve stratum reinforcement modeling. Data analysis is performed by adopting different reinforcement schemes to achieve stratum reinforcement modeling and numerical analysis of the process of the shield tunnel crossing the existing structure.

A method of generating an iso-surface mesh for a three-dimensional (3D) model is provided. In the method a plurality of voxels is generated in a bounding box of an input mesh, where a size of each of the plurality of voxels is based on a size of the bounding box of the input mesh and an iso-value. One or more iso-surfaces in each of the plurality of voxels are determined based on an unsigned distance function and the iso-value. One or more feature points in each of the plurality of voxels are determined based on the one or more iso-surfaces in the respective voxel and a constraint function. A feature mesh is generated based on the determined one or more feature points, and an edge flip operation is performed on each of a plurality of edges of the feature mesh to generate the iso-surface mesh.

The invention relates to a geomechanical data visualization method, device and equipment and a medium thereof. The method comprises the following steps: acquiring original data containing rock mass structural characteristics and temperature and humidity environmental parameters, and completing grid division and load and displacement constraint boundary condition setting by adopting finite element analysis to obtain a rock mass stress distribution model; core mechanical parameter evolution of rock mass at different time nodes is simulated based on the model, and a dynamic stress distribution sequence is generated; identifying and marking stress overrun potential event association points through a threshold value, extracting a key time-space change trend, and inputting the key time-space change trend into the time-space dynamic model to obtain a risk prediction distribution diagram containing a risk level, a coverage range and an occurrence probability; and constructing a three-dimensional dynamic view by adopting visual rendering, analyzing a mechanical parameter full-cycle evolution path and geological event association mode, and outputting a three-dimensional dynamic result integrating multi-dimensional information. According to the method, the problems of static data presentation and event association deficiency in the traditional technology can be solved, and the scientificity and the high efficiency of geological engineering analysis are improved.

Provided are a grouting subgrade water-vapor-heat coupling simulation method and system, a device and a medium, including: constructing a subgrade water-vapor-heat coupling geometric model; acquiring a partial differential equation of a subgrade water-vapor-heat coupling process, and establishing a relationship between physical fields; setting a temperature and water boundary condition; performing mapping and free triangle mesh generation on the subgrade water-vapor-heat coupling geometric model to obtain a meshing model; selecting initial data, and performing a simulation solution on the meshing model to obtain a water-vapor-heat coupling simulation result; and analyzing the impact of a double-layer polyurethane grouting thermal insulation structure on a temperature distribution, a freeze-thaw cycle depth, and water migration of a subgrade.

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 feature-preserved curvature-adaptive triangular mesh generation method. The method comprises the following steps: acquiring a geometric adaptive size field according to a curved surface set based on a geometric size field construction strategy; based on the geometric adaptive size field, performing curve discretization processing on the curve set according to the geometric adaptive size field to obtain a discrete curve grid with reserved curve features; taking the discrete curve grid as a rigid boundary constraint condition, and performing curved surface discretization processing on the parameterized curved surface patches according to a geometric adaptive size field through a leading edge propulsion method and a triangulation coupling strategy to obtain discrete curved surface grids of all the parameterized curved surface patches; and carrying out local grid merging and optimization on the discrete curved surface grid to obtain a uniform curved surface grid with geometric continuity, namely a curvature self-adaptive triangular grid with reserved features. According to the method, the technical problems that the quality of the boundary grid cannot be ensured, the efficiency is low and the convergence is poor in the existing method are solved.

The invention discloses an unstructured high-order grid generation method based on a Loop subdivision format, and the method comprises the steps: firstly reading a linear triangular grid as a basic topological structure, and reading sampling point set data of a target model; secondly, initializing each triangular patch in the basic topological structure into a quartic triangular Bezier surface patch based on a Loop subdivision rule, establishing a mapping relation, and splicing all the surface patches into an initial high-order surface; establishing a sampling point-patch association index through a k-d tree acceleration structure, and updating the global control point based on the mapping relation to obtain a preliminarily optimized global control point; and finally, applying continuous coplanar constraint to the global control points, forming a final parameter curved surface, generating a triangular mesh model and outputting the triangular mesh model. According to the method, the rough linear triangular mesh can be efficiently converted into the continuous high-order curved surface capable of approaching the target sampling data, and the obtained curved surface is high in smoothness and small in fitting error.

The present disclosure is directed toward systems, methods, and non-transitory computer readable media that provide a differentiable tiling system that generates aesthetically plausible, periodic, and tile-able non-square imagery using machine learning and a text-guided, fully automatic generative approach. Namely, given a textual description of the object and a symmetry pattern of the 2D plane, the system produces a textured 2D mesh which visually resembles the textual description, adheres to the geometric rules which ensure it can be used to tile the plane, and contains only the foreground object. Indeed, the disclosed systems generate a plausible textured 2D triangular mesh that visually matches the textual input and optimizes both the texture and the shape of the mesh and satisfy an overlap condition and a tile-able condition. Using the described methods, the differentiable tiling system generates the mesh such that the edges and the vertices align between repeatable instances of the mesh.

The invention discloses a variable grid method grid automatic division method and device based on vector field guidance. The method comprises the following steps: extracting boundary feature points according to geometric features of an input model boundary so as to construct a feature polygon of a model, and dispersing the feature polygon into a triangular mesh model; constructing a vector field based on a Laplacian operator by using the triangular mesh model; starting from the geometric center of the model, setting an initial quadrilateral grid as an initial paving layer, paving the quadrilateral grid outwards layer by layer, and if the paving layer exceeds the boundary of the model, stopping paving; when each layer of quadrilateral grid deforms, uniform transition is achieved through a size transition template; and finally, generating a boundary quadrilateral mesh of the model by adopting a mapping method, mapping discrete points on the boundary of the feature polygon back to the boundary of the input model, and outputting a generated quadrilateral mesh model. According to the method, full-automatic generation of the quadrilateral mesh can be realized, and the method is particularly suitable for mesh generation in finite element simulation pretreatment.

The invention provides a remote sensing monitoring multi-scale space grid index construction method and device, and belongs to the technical field of remote sensing monitoring, and the method comprises the steps: dividing uniform basic grids based on the geographic boundary of a monitoring region; calculating a service importance score fusing the supervision priority, the geographic complexity and the historical change frequency for each basic grid; according to the score, a preset threshold value and a dynamic decision, refinement, maintenance or aggregation operation is executed on the basic grid, and a service-adaptive multi-scale grid structure is formed; unified codes based on a Z-order curve are generated for all the grids; establishing association mapping between the water conservancy business object and the grid and determining a main grid; and finally outputting a spatial grid index fusing geometry, coding, hierarchy, attribute and association relationship. According to the method, the AI interpretation efficiency of the mass remote sensing data can be remarkably improved, the allocation of computing resources is optimized, and the accuracy of monitoring and early warning is improved through deep fusion with business rules such as river and lake supervision.

Systems and methods for classifying an aortic condition include capturing aorta image data, applying a mesh generation process, and determining an intrinsic coordinate system for the resulting mesh structure, including a plurality of vertices. The mesh structure is mapped to a reference coordinate system for generating, from the vertices, mapped vertices, which are embedded into the mesh structure to create an embedded mesh structure. The embedded mesh structure is compared to reference mesh structures including at least one normal aortic mesh structure and at least one pathology aortic mesh structure, and a similarity score is generated, and the aortic condition is classified.

Apparatuses, systems, and techniques to generate a 3D mesh using one or more neural networks. In at least one embodiment, tokens of a sequence of tokens that represents a sequence of coordinates of vertices of polygons of a polygon mesh are generated autoregressively using one or more neural networks based on a 3D representation of an object and one or more attributes. In at least one embodiment, the sequence of tokens includes start-of-part and end-of-part tokens that separate vertex coordinates corresponding to a part of the 3D representation of the object. In at least one embodiment, the one or more neural networks are trained via a progressive training technique that employs iterative vocabulary expansion and fine-tuning.

The invention discloses a skin riveting quality monitoring method and system based on machine vision, and relates to the technical field of aerospace manufacturing engineering quality inspection, and the method comprises the steps: comprehensively obtaining the form, texture and temperature information of a rivet region through multi-modal data synchronous collection of a coaxial structured light three-dimensional sensor, an industrial camera and a thermal infrared imager; projecting the three-dimensional point cloud data to a radial grid by adopting a polar coordinate system, generating a height measurement function and calculating a morphology difference function; extracting morphology energy characteristics by combining a weighted p-norm integration method, extracting fractal dimensions, texture characteristics and temperature rise indexes of rivet contours at the same time, constructing a rivet distribution diagram structure, and defining adjacent weights through Euclidean distances between nodes and stress transfer paths; and outputting a riveting defect analysis result by dynamically adjusting an adjacent weight based on a graph convolutional network containing a morphology gating mechanism. Therefore, the accuracy of riveting defect detection is improved.

The invention discloses an aero-engine complete machine full-three-dimensional performance simulation method and device and a storage medium. The method comprises the steps that firstly, a complete machine full-three-dimensional geometric model of all main watershed components from an inlet to an outlet of the aero-engine is constructed under a unified coordinate system and processed, and a single-channel model is formed through periodic simplification; grid division is carried out by adopting a hybrid grid strategy, structured grids are divided for the rotating part, and unstructured grids are divided for the complex structure; secondly, in a single universal CFD solver, specific turbulence and combustion models are configured, a Stage interface is adopted to carry out data transmission between components, high-precision numerical simulation is executed, and solving is carried out based on a strict convergence criterion; and finally, extracting performance parameters from a simulation result for evaluation. According to the method, the integral high-precision simulation of the whole machine in a single solver environment is realized, the problem of low parameter transmission precision among parts in a traditional method is effectively solved, and the engineering-level simulation precision can be achieved.