70 results about "Geometric design" patented technology

A vehicle is controlled for travel on a road having a geometric design defined by one or a combination of a docking line, a cross-section, and a cross-section of the road such that different values of parameters of the geometric design of the road, traffic on the road, traffic rules for traffic flow on the road define different traffic scenarios. By relaxing configuration parameters of a real-world scene and tightening corresponding limiting parameters, a mixed integer non-convex constraint optimization problem for a current real-world traffic scene is converted into a mixed integer convex optimization problem for approximate representation of the real-world traffic scene, so that a carrier is controlled. A mixed integer convex optimization problem for the converted approximate representation of the real-world traffic scene is solved to generate current control commands for controlling one or more actuators of the vehicle.

The invention discloses a physical perception-based generative three-dimensional reverse design method and system, which realize efficient exploration and optimization in a three-dimensional design space by constructing a unified physical-geometric potential representation and combining a two-stage optimization strategy. According to the method, shape and physical field data combined training is utilized to obtain potential representation, so that a geometric structure and physical constraints are compactly represented; on the basis, two stages of physical perception optimization are adopted: in the first stage, global exploration is performed in a potential manifold through a gradient-guided diffusion model, and an initial grid is generated; and in the second stage, the initial grid is locally optimized by utilizing target-driven topology maintenance optimization, so that the initial grid gradually approaches the target performance requirement. According to the method, the high-fidelity three-dimensional geometric design can be directly generated, the target performance and the result diversity of the design are remarkably improved, the method can be widely applied to aerospace, energy equipment and complex engineering structure design, and a new technical approach is provided for efficient implementation of the three-dimensional intelligent design.

The invention provides a finite element analysis method and system for geometric design of a flow regulating valve, and relates to the technical field of data processing.The method comprises the steps that 1, spatial geometric feature analysis is conducted on each data point in a discrete contour coordinate dataset, the principal curvature value of each data point on the sealing surface of a metal diaphragm is solved, and the principal curvature value of each data point is calculated; determining a point with the maximum average curvature value on the sealing surface of the metal diaphragm as a core morphology reference point; step 2, establishing a local coordinate system by taking the core morphology reference point as an original point, screening four sealing state points from the discrete contour coordinate data set, solving a corresponding space plane equation, and calculating a space intersection line between the space plane and the sealing surface of the metal diaphragm; according to the method, through accurate positioning of the core reference point, definition of the analysis sub-domain, grid division, mechanical solution, leakage rate calculation and parameter optimization, the dynamic particulate matter problem is effectively improved, and the sealing performance and the micro flow adjusting precision are improved.

The invention discloses a microwave device multi-physics field optimization method taking electromagnetism as a center based on a feature assistance and proxy model. The method comprises the steps of setting initial values of geometric design variables and multi-physics field design variables; the multi-physical field response with electromagnetism as the core responds at the solution point {xg, xm}, multiple pieces of parallel multi-physical field data are generated, and f represents the frequency; according to the multi-physics field data, constructing a feature-assisted multi-physics field agent model based on a neural network transfer function, and calculating a gradient optimization derivative of the feature-assisted multi-physics field agent model; and on the basis of the gradient optimization derivative and the optimization feature auxiliary multi-physics field agent model, obtaining an optimal solution of the variable. According to the method, the robustness and optimization design efficiency of a microwave device multi-physics field optimization algorithm taking electromagnetism as a core are improved.

The invention relates to a spring stiffness characteristic simulation optimization method and system. The spring stiffness characteristic simulation optimization method comprises the steps of obtaining first stiffness characteristic curve data of a spring through multi-physical field simulation, and extracting and obtaining a first physical morphological characteristic of the spring based on the first stiffness characteristic curve data; establishing a prediction model between the spring input parameters and the first physical morphological characteristics; in robust design optimization iteration, according to the geometric design parameters and the uncertainty parameters and on the basis of the prediction model, corresponding second physical morphological characteristics are obtained, and on the basis of the second physical morphological characteristics, second rigidity characteristic curve data of the spring are obtained through reconstruction; and on the basis of statistical analysis of the second stiffness characteristic curve data, a robust performance evaluation result of the design scheme under the influence of uncertainty is obtained, and according to the robust performance evaluation result, the geometric design parameters are iteratively adjusted until the spring design scheme meeting the robust requirement is obtained.

The invention discloses an overhead working truck bed-shaped arm section optimization method and system considering stability and rigidity. The method comprises the steps that geometric design parameters of all polygonal sections of the box-shaped arm are set, and the geometric design parameters of all the polygonal sections jointly form an adjustable geometric design space; establishing a three-dimensional finite element analysis model of the box-shaped arm, and endowing the three-dimensional finite element analysis model with material attributes; according to the actual use requirement of the box-shaped arm, the analysis working condition of the three-dimensional finite element sub-model is defined as the most stringent working condition combination; and setting an optimization target, executing a multi-target optimization algorithm and solving to obtain geometric design parameters of each polygon section after optimization. According to the method, through scientific multi-objective optimization simulation, the coupling and restricting relation between two core performance indexes of local stability and deflection (rigidity) in boom design is systematically solved, so that the section shape with the optimal comprehensive performance under the given working condition is obtained.

The invention belongs to the technical field of data processing, and provides a design parameter extraction method and system based on geometric features, a geometric model is disassembled in combination with the geometric features, all components in the model and the mutual relation of the components can be more accurately understood and analyzed, and the accuracy of data processing is improved; the geometric design parameters are set according to the geometric feature types, so that the accuracy, reliability and scientificity of the design parameters are ensured, and meanwhile, the efficiency of setting the design parameters can be remarkably improved; the integrity of the geometric model is verified, so that the reasonability of the constructed design parameters can be ensured, and geometric loss cannot be caused; by optimizing the design parameters, the total quantity of the design parameters of the complete geometric model can be effectively reduced, the complexity and the data volume of the model can be remarkably reduced, the maintainability and the expandability of the relevant performance corresponding to the design parameters can be improved, and the cost required for performance evaluation in the later period can be further reduced.

The invention discloses a design method and device for an air conditioner heat exchanger of an electric vertical take-off and landing aircraft and a storage medium, and the method comprises the steps: firstly determining multiple types of geometric design parameters and parameter ranges of the heat exchanger, and building a heat exchanger weight calculation model and a heat exchanger heat exchange amount calculation model; sampling parameter ranges of various geometric design parameters to obtain N sample point sets; then, a multi-objective evaluation function of a genetic algorithm is constructed based on the heat exchanger weight calculation model and the heat exchanger heat exchange calculation model, and the genetic algorithm is adopted to carry out multi-time iterative optimization solution based on the multi-objective evaluation function by taking the N sample point sets as populations to obtain multiple groups of heat exchanger geometric design parameter optimization solution sets; and finally, verifying the thermodynamic properties under each group of heat exchanger geometric design parameter optimal solution set, so as to determine the heat exchanger geometric design parameter optimal solution set. The device and the storage medium are used for implementing the method. According to the method, the rapid iteration and design type selection requirements of the thermal management system can be met.

The embodiment of the invention provides a heat exchange equipment optimization design method and system, a medium and equipment, and the method comprises the steps that according to the design working condition of heat exchange equipment, thermodynamic parameters and geometric design parameters are determined; determining a pipe side heat transfer film coefficient and a shell side heat transfer film coefficient according to the geometric design parameters; according to the pipe side heat transfer film coefficient, the shell side heat transfer film coefficient, the heat exchanger pipeline outer side area, the heat exchanger pipeline inner side area and the pipe wall thickness, the total heat exchange coefficient is determined; according to the thermodynamic parameters and the total heat exchange coefficient, the total heat exchange area of the heat exchange equipment is determined; and the total heat exchange area is substituted into the evaluation model, and geometric design parameters corresponding to the total heat exchange area meeting preset conditions serve as target design parameters and are applied to design of the heat exchange equipment. Through the method, a heat exchange equipment design scheme considering both design flexibility and engineering feasibility can be obtained.

The invention discloses a curve adjustment method and device based on feature control points, equipment, a medium and a product, and relates to the field of computer-aided geometric design, the method comprises the following steps: introducing a shape parameter a, and constructing a planar cubic Bezier curve with the shape parameter; according to design requirements, performing interpolation processing on feature points of the planar cubic Bezier curve, and determining curve segments with the feature points; based on a continuity constraint condition, splicing all curve segments with feature points; initializing adjustment parameters according to the curve type, the feature point type and the interpolation position of the planar cubic Bezier curve; according to the initialized adjustment parameters, control points of the curve segments with the feature points are calculated, and a linear equation set is constructed; the control parameters are optimized according to the linear equation set, the curve shape is adjusted according to the optimized control parameters, curve continuity can be improved, and the type of the insertion point can be controlled.

The application discloses a multi-objective optimization design method and related device for clamping a metal wedge-shaped anchoring joint of a composite structure, and relates to the technical field of anchoring of marine engineering composite material structures. The method comprises constructing a mechanical-bonding composite three-dimensional finite element model based on the geometric components of the metal wedge-shaped anchoring joint. Numerical simulation is performed on the multiple geometric design variables through experimental design, and key design variables affecting anchoring strength, clamping stress and joint weight are screened through variance analysis. The steepest ascent method is used to determine the optimization direction, and a quantitative mapping relationship between the design variables and the optimization objectives is constructed in the optimization region using the response surface method to establish a high-precision surrogate model. The maximum anchoring strength, the minimum clamping stress and the minimum joint weight are taken as the objectives, the surrogate model is used as an objective function evaluator, a multi-objective genetic algorithm is applied for collaborative optimization, an optimal solution set is obtained, and the optimal geometric structure parameter combination of the metal wedge-shaped anchoring joint is determined according to requirements.

The present application relates to the technical field of nuclear power plant containment structure deformation measurement, and discloses a pressure deformation measurement method for a nuclear power plant containment and related devices. The method comprises obtaining the outer curved surface geometric design parameters and correction parameters of the outer dome at the outer monitoring point, and the inner curved surface geometric design parameters of the inner dome at the inner monitoring point; obtaining the strain measurement value of the outer monitoring point of the outer dome under the action of the environmental load in the state that the inner shell bears the internal pressure; determining the free displacement estimation value of the outer shell at the outer monitoring point; determining the actual displacement value of the outer shell in the environment; determining the relative displacement change between the inner monitoring point and the outer monitoring point; and determining the deformation displacement of the inner shell at the inner monitoring point under the loaded state. The present application does not need to set up components such as metal wires inside the inner shell which are easily affected by temperature, but calculates the deformation displacement of the inner shell by the strain measurement value, the relative displacement measurement value, and the geometric design parameters and correction parameters, so as to weaken the interference of temperature on the measurement result.

The application provides a building structure material quantity prediction method and device based on a knowledge embedding neural network, electronic equipment and a storage medium, wherein the method comprises the following steps: obtaining design conditions of a target building structure, the design conditions comprising seismic design conditions, wind resistance design conditions and overall geometric design conditions of the structure; obtaining a structure design scheme of the target building structure, the structure design scheme comprising the spatial positions and geometric sizes of walls, columns, beams, plates and supports; inputting the design conditions and the structure design scheme into a pre-trained material quantity prediction model to obtain the material quantities of various materials in the target building structure. The method embeds prior knowledge into the material quantity prediction model, overcomes the defects of the prior art that the material quantity prediction value violates the basic common sense of engineering and has low prediction accuracy due to the inability to consider the prior knowledge in the field related to building structures, and realizes accurate and efficient prediction of the material quantity of the target building structure.

This invention relates to the field of earthwork trenching technology, specifically to a method and system for excavating slope trenches for prefabricated quick-assembly grid beams. In this invention, by collecting high-density discrete coordinates of the slope and constructing a reference straight-line vector connecting the beginning and end, the geometric correction depth of each surface point relative to the ideal flat bottom surface is calculated. This eliminates nonlinear errors caused by the original slope undulations, ensuring that the bottom surface of the trench accurately adapts to the straight-line configuration of the prefabricated components. The resistance gradient change characteristics during the excavation process are combined with a clustering algorithm to dynamically lock the interface between soft and hard geological layers. The excavation depth required by the geometric design is fused and compared with the measured depth of the geotechnical boundary in the same coordinate system. Based on the comparison results, differentiated cutting or stripping commands are intelligently generated. When encountering hard rock layers higher than the designed bottom surface, a fuzzy PID algorithm is activated to enhance hydraulic driving force and ensure cutting efficiency. In soft soil operating areas, standard pressure is maintained to reduce energy consumption.

The disclosure provides computing apparatus, computer-implemented methods and software for autonomously generating a geometric design for a mechanical part optimised to perform an intended function by interacting with a fluid and / or particulate matter in an operating environment. The method includes iteratively generating a plurality of CAD models for the mechanical part using a CAD kernel program based on a search distribution across a parameter space of free parameters defining geometric features of the designs, generating a simulation of the performance of the modelled mechanical part for each of the plurality of generated CAD models, analysing the simulation of each CAD model for the mechanical part over time, selecting a subset of the generated CAD models having a better performance, and proceeding to the next epoch to generate, simulate and analyse evolved CAD models having candidate geometries with features based on combinations of free parameters synthesised across an updated search distribution.

The invention discloses a neural network electromagnetic performance prediction method with causality and passivity constraints, and the method comprises the steps: obtaining geometric design variables of a TSV structure to be detected, inputting the geometric design variables into a trained electromagnetic performance prediction model, and obtaining the prediction values of a plurality of scattering coefficients of the TSV structure to be detected; wherein the electromagnetic performance prediction model comprises a polar point sub-network, a residue sub-network and a prediction sub-network, and the polar point sub-network and the residue sub-network are respectively used for determining a to-be-detected polar point vector and a to-be-detected residue vector corresponding to each scattering coefficient according to geometric design variables of a to-be-detected TSV structure; the prediction sub-network is used for determining a prediction value of a scattering coefficient of a corresponding type according to a to-be-measured pole vector and a to-be-measured residue vector; the electromagnetic performance prediction model is trained through a sample pole vector and a sample residue vector, and the sample pole vector and the sample residue vector are obtained by processing a sample scattering coefficient based on a vector fitting technology. The method is low in implementation cost and good in adaptability.

The application relates to a spring stiffness characteristic simulation optimization method and system. The spring stiffness characteristic simulation optimization method comprises the following steps: obtaining first stiffness characteristic curve data of a spring through multi-physical field simulation, and extracting first physical form features of the spring based on the first stiffness characteristic curve data; a prediction model between spring input parameters and the first physical form features is established; in the robust design optimization iteration, corresponding second physical form features are obtained according to the geometric design parameters and the uncertainty parameters and based on the prediction model, and second stiffness characteristic curve data of the spring is reconstructed based on the second physical form features; the robust performance evaluation result of the design scheme under the influence of uncertainty is obtained through statistical analysis based on the second stiffness characteristic curve data, and the geometric design parameters are iteratively adjusted according to the robust performance evaluation result until a spring design scheme meeting the robustness requirement is obtained.

The present invention relates to a globally consistent geometric design method for blade-like surfaces based on PHT splines, which uses Polynomial Splines over Hierarchical T-meshes (PHT-splines) surfaces to fit complex blade-like surfaces and their geometric features with high precision. The main technical solution includes: through a boundary-consistent reparameterization process, the splicing and cutting parameter domain is a globally consistent complete single parameter domain, which serves as the definition domain of the PHT spline; comprehensively considering the geometric features and boundary information, rationally sampling to obtain the set of data points to be fitted and calculating the corresponding high-order geometric information; by controlling the hierarchical subdivision of the grid, blade-like surfaces represented by PHT splines are obtained with high precision fitting. The present invention solves the discontinuity problem caused by cutting and splicing in traditional design methods, ensures the global consistency of the overall design, and improves the design accuracy and efficiency.

This invention belongs to the field of road traffic noise control and acoustic computation technology, and relates to a physical information neural network-driven method for sound barrier shape optimization based on the isogeometric singular boundary method. The method includes: NURBS parameterization and boundary discretization based on the sound barrier's geometric design requirements; constructing an acoustic analysis model based on acoustic control equations and boundary conditions; calculating the average sound pressure level within the observation area using the isogeometric singular boundary method and using it as the objective function; constructing a physical information neural network, constraining the control point update range through a coordinate mapping layer and bounded activation functions, and iteratively optimizing using the average sound pressure level of the observation area as the loss function; and outputting the optimized sound barrier geometry after network convergence and evaluating the noise reduction effect. This invention combines the isogeometric singular boundary method with a physical information neural network, eliminating the need for mesh reconstruction and sensitivity analysis, achieving efficient adaptive optimization of the sound barrier geometry, and effectively improving the noise reduction performance of the sound barrier.

The application discloses a complex part contour optimization design method based on multi-field node feature weighted aggregation. First, according to the complex part contour geometry design variables, temperature and contact surface friction coefficient to be optimized, a batch of finite element simulations are carried out to obtain a training data set. Then, a deep map sampling aggregation neural network fusing space and temperature attention is constructed, and then the deep map sampling aggregation neural network fusing space and temperature attention is trained by using the training data set. After the training is completed, a stress prediction model is obtained. Finally, combined with the stress prediction model, an iterative optimization is carried out to minimize the maximum equivalent stress of the complex part as an optimization objective, and the optimal geometric parameters of the current complex part contour in the target temperature interval are obtained. The application realizes the rapid reconstruction of the stress distribution state of the complex part, improves the optimization speed while fully guaranteeing the accuracy of the optimization result, and greatly saves the calculation resources.

The invention relates to the field of precious metal recovery, and discloses a method for recovering precious metal from a solution containing precious metal ions, which comprises the following steps: establishing a mathematical physical model of an electrolysis process, the mathematical physical model comprising ion diffusion and migration, electrode reaction kinetics and current distribution simulation; according to the mathematical physical model, a multi-objective optimization problem is constructed, and by optimizing current density distribution, the geometric design of an electrolytic bath and electrode reaction conditions, the recovery efficiency of precious metal is maximized, and energy consumption in the electrolysis process is minimized; and a particle swarm optimization algorithm is adopted to optimize the current density distribution, and the current density in the electrolysis process is adjusted. By optimizing current density distribution, electrolytic bath design and electrode reaction conditions and combining a real-time monitoring and dynamic adjustment mechanism, the precious metal recovery efficiency is remarkably improved, energy consumption is reduced, and meanwhile the stability and adaptability of the electrolysis process are improved.

This invention discloses a method for generating two-dimensional closed curves using NUBRS interpolation, belonging to the field of computer-aided geometric design. The method first obtains parameter values ​​and a knot array using the interpolation points passed by the closed path curve and the order of the closed path curve. The coordinates of all control points of the closed path curve are then solved using a system of simultaneous equations. Finally, the parameter values ​​are constrained according to the NUBRS generation formula to generate a closed NUBRS curve. Based on NUBRS curves, the method accurately represents various complex free-form closed path curves.

The invention relates to a storage system (10) for a motor vehicle (200), comprising a plurality of system receptacles (12) and a plurality of system inserts (14); wherein the system inserts (14) have a unified external geometric design; wherein each system receptacle (12) has a receiving space (16) corresponding to the external geometry of the system insert (14), such that each system insert (14) can be positioned in either system receptacle (12). According to the invention, at least two system inserts of the plurality of system inserts (14) have different insert spatial divisions (ER) within a unified outer geometric design. The invention further relates to a motor vehicle (200) having such a storage system (10).

The application discloses a kind of robust optimization design method of double pressure angle asymmetric gear modification parameters considering uncertain working condition, steps include: defining the torque value range of gear service condition uncertainty and geometric design requirement;Gear pair meshing performance simulation model is constructed and simulation test design is carried out;Establish the multi-objective optimization model of modification parameter with the target of comprehensive service performance index and comprehensive robustness index;Pareto solution set is obtained by using intelligent optimization algorithm;Select the best scheme and export gear three-dimensional model.The application will load spectrum fluctuation into asymmetric gear modification optimization, through the combination of proxy model and multi-objective optimization, realize the gear modification parameter design with strong robustness to uncertain working condition, significantly improve the transmission stability and reliability of gear under variable load condition, while greatly reduce the calculation cost and time in optimization design process.

The invention discloses a disc-shaped granulating block and a dynamic meshing clearance analysis method thereof, the disc-shaped granulating block comprises a left granulating block and a right granulating block, the shape contour of the granulating block is composed of two concentric arcs which are in circumferential symmetry and a transition arc which is arranged between the two concentric arcs and is in circumferential symmetry; the circle center of the transition arc is arranged on the perpendicular bisector where the centers of the two concentric arcs are connected. According to the method, the thread inner diameter d1, the thread outer diameter D1 and the double-screw gap e1 of the front-section conveying double screws of the continuous wet granulator are used as geometric design bases, the outer contour of the rear-section disc-shaped granulation block is designed, on the basis, meshing of the two granulation blocks is constructed, the working dynamic gap S12 generated when the two granulation blocks rotate by one circle is analyzed, and the working dynamic gap S12 of the two granulation blocks rotating by one circle is analyzed. According to the method, the gap value of the granulation block at any moment can be accurately calculated, a basis is provided for the particle size of the granulation block, the geometric parameters of the contour of the granulation block can be adjusted according to the application requirement of the actual particle size, and the purpose of adjusting the particle size of the granulation block and the distribution of the granulation block is achieved.

The invention provides a 3D printing buffer structure based on multi-material cavity filling and an additive manufacturing method of the 3D printing buffer structure, and relates to the technical field of 3D printing. The at least one cavity unit is embedded into the main body structure; the cavity unit comprises a closed geometry which is formed by rotating a curve AB around an axis n by 360 degrees; or stretching the geometry: stretching an area enclosed by the curves AB and BA along a space curve PQ; or the composite geometry is composed of a stretching geometry and an end rotating body Boolean union set; a filler is arranged in the cavity unit, and the filler is at least one of airtight gas, a foamed polymer or a lattice structure; the adjacent cavity units can be spatially nested to form a plurality of airtight protective layers. Through geometric design and material combination, the buffering performance, rebound resilience and comfort of the 3D printing product are remarkably improved, and the high-performance requirements in different application scenes are met.

1. Name of this design product: Apple Cut (Simple Geometric). 2. Purpose of this design: For cutting apples. 3. The key design feature of this product is its shape. 4. The image or photograph that best illustrates the design's key points: 3D view 1.

The present disclosure provides a dynamic toolpath optimization system for an additive manufacturing machine. The system comprises an input reception unit to receive user-provided information comprising three-dimensional (3D) geometric design data of an object and material composition details; a design analysis component utilizing a first artificial intelligence technique to determine an effective toolpath for each layer; a monitoring unit that monitors quality control metrics and current manufacturing conditions and a machine learning analysis unit that accesses a historical database to generate one or more artificial intelligence (AI) models. The system further comprises a toolpath optimization unit utilizes the generated AI models to process monitored quality control metrics and current manufacturing conditions to identify flaws and determine a toolpath optimization strategy and a control unit dynamically regulates the additive manufacturing machine based on the determined toolpath optimization strategy.

The invention discloses a worm gear and worm dynamic transmission error analysis method based on rigid-flexible body joint simulation, and compared with the prior art, high-precision analysis of the dynamic transmission error of a worm gear and worm transmission system is realized through the technical scheme of rigid-flexible body joint simulation. According to the method, the contribution of geometric errors (including manufacturing errors, assembly errors and modification errors) to transmission errors can be independently analyzed, and a theoretical basis is provided for geometric design optimization of a transmission system; through a difference value calculation method, a dynamic comprehensive meshing error and a dynamic transmission error are respectively obtained, an elastic dynamic transmission error is further obtained, contribution of elastic deformation is separated from a total transmission error, and although the nonlinear coupling influence of a geometric error and the elastic deformation error cannot be completely eliminated, the dynamic transmission error cannot be completely eliminated. However, the contribution of elastic deformation to the transmission precision can be approximately quantitatively evaluated.

Method (100) for optimizing the placement of weld spots during resistance spot welding comprises several steps that enable precise analysis and adjustment of the welding parameters. First, welding process data is acquired (102). This data is used to monitor and optimize the welding process. In step (104), geometric design data is extracted from a CAD model, including the weld spot location, material thickness combinations (MCT), and geometric features such as edge distances. This data is necessary to analyze the weld spot placement. In step (106), a two-dimensional analysis is performed, calculating distances between weld spots and component features. In step (108), a three-dimensional analysis is carried out, taking into account the spot location in relation to the geometric properties of the surroundings.Step (110) links the geometric design data with the welding process data, including the quality score, enabling a detailed analysis. In step (112), correlations between the geometric location of the weld spots and the weld quality are determined. In step (114), alternative spot locations and / or material thickness combinations are identified to improve the weld quality. Finally, in step (116), optimization recommendations for the design are generated to increase the weld quality by adjusting the spot location or material thickness combination.