271 results about "Design cycle" patented technology

The invention relates to the technical field of power electronics, in particular to a filter equivalent circuit design simulation system suitable for an energy storage converter, which comprises a main circuit topology unit, a control strategy unit, a parameter optimization and design unit, a simulation engine unit and a performance evaluation unit, wherein the main circuit topology unit is used for building a filter equivalent circuit topology of the energy storage converter and configuring passive element parameters of an inductor, a capacitor and a resistor. According to the method, automatic high-robustness optimization of filter parameters is realized through genetic algorithm-particle swarm hybrid optimization, multi-objective collaborative optimization and digital twinning auxiliary optimization, and a'design-optimization-verification-iteration 'closed loop is formed by combining dynamic working condition evaluation, reliability modeling and artificial intelligence auxiliary analysis, so that the method has the advantages of high robustness and high robustness. The harmonic suppression capability, efficiency and long-term operation reliability of the filter are remarkably improved, the design period is shortened, and the development cost is reduced.

The invention relates to an integrated circuit core particle time sequence optimization method and device, equipment and a medium. Analyzing the time sequence of the core particle according to the total negative time sequence margin of all paths generated by the OpenSTA tool on the establishment time, the total negative time sequence margin of all paths on the retention time, the negative time sequence margin of all paths under the worst establishment time and the negative time sequence margin of all paths under the worst retention time; when a violation occurs, the preliminary core particle division scheme is readjusted to determine an iterative division scheme until the time sequence of the core particles meets the requirement; and when the iteration division scheme meets the time sequence optimization requirement, recording and storing the current iteration division scheme, and continuing to perform regular division on the integrated circuit modules at the same level until all the preliminary core particle division schemes at the level are completely traversed. The design period can be greatly shortened, and automation and flexibility can be remarkably improved.

The invention belongs to the related technical field of composite material additive manufacturing, and discloses a composite material microstructure reverse design method and system based on a generative model, and the method comprises the steps: constructing a sample data set corresponding to a microstructure image-attribute parameter of a composite material; performing conditional embedding enhancement on the unconditional generation model, constructing a conditional embedding generation model, training the conditional embedding generation model by using a sample data set corresponding to a microstructure image-attribute parameter, the attribute parameter being an embedding condition during image generation, and obtaining a trained model as a reverse design model; and generating a design microstructure image by using a reverse design model according to the expected attribute parameters. According to the method, a reverse design process of quickly and accurately generating a corresponding vivid microstructure according to expected attributes is realized on the basis of powerful image generation and conditional embedding capability of the generative model, and the problems of long design period and uncontrollable effect are solved.

The invention discloses a turbine part modular design method, device and equipment combined with machine learning and a storage medium. Comprising the following steps: constructing an agent by utilizing a large language model and an expert knowledge base, and carrying out turbine demand capture and one-dimensional parameter design; performing quick generation and simulation of a two-dimensional blade profile by using an agent model based on a full-connection neural network and an auto-encoder; whether to enter a three-dimensional stage or return optimization is determined through performance judgment; and carrying out rapid generation of a three-dimensional blade profile and viscous flow field simulation by utilizing an attention mechanism-based proxy model, and carrying out performance judgment again to decide that the design is completed or optimization is continued. Through the modularized and intelligent design process, the large language model and various machine learning agent models are integrated, full-process automation and intellectualization of turbine component design are achieved, the design period is remarkably shortened, dependence on artificial experience is reduced, and the design quality is guaranteed.

The invention provides an end-to-end software development automation platform and method, and the platform comprises an intelligent design module which automatically generates a structured design document through multi-Agent cooperation and builds a traceable link; the intelligent development module is used for analyzing the UI design draft through computer vision to generate a front-end code and automatically generating a rear-end code based on the design document; the intelligent test module automatically generates a test case and drives a test closed loop; the workflow engine configures a flow through a visual interface and monitors a task through an intelligent Agent; and the RAG knowledge base and the Agent base disk are used for dynamically slicing the document and storing the document in a vectorization manner, and support multi-role Agent collaboration. According to the platform, the time consumed by manual design can be reduced by 50%-70%, and the design period is shortened by 67%; the front-end development efficiency is improved by three times; the automatic coverage rate of back-end codes reaches more than 90%, and the labor cost is reduced by 60%; the test case generation efficiency is improved by three times, and the test period is shortened by 50%.

The invention relates to the technical field of diffusion model AI application, and discloses an AI aided design workflow method and system based on a diffusion model, and the method comprises the steps: receiving multi-modal data; vectorizing the sketch, and extracting key set features; analyzing the text into structured semantics; parameter constraints are converted into mathematical expressions or boundary conditions; mapping the multi-modal data to a unified space; selecting a generation path with the minimum loss function from the candidate paths; gaussian noise is gradually added into the submerged space, and noise distribution is predicted; injecting the parameter constraint into a denoising process to generate a path; and the optimized latent vector is converted into a vector graph through a decoder, and a geometric topological relation is reserved. The system comprises a unified multi-modal data module, a path generation module and a user interaction module. According to the method, the actual availability of a design result is improved; the design period is shortened, the process is simplified, and human resource investment is reduced.

The invention provides a tool geometric parameter optimization design method and system based on integrated simulation and a storage medium, and relates to the technical field of tool geometric parameter optimization design. Orthogonal experiment design is combined with parametric modeling, tool geometric parameter combination space is fully covered, and invalid exploration is reduced; establishing a nonlinear relation model by using support vector regression, and accurately mapping parameter and performance association; based on a dynamic weight distribution mechanism of an entropy method and a judgment matrix method, the rough machining cost reduction requirement and the finish machining high-quality requirement are met; an improved simulated annealing algorithm introduces a dynamic cooling strategy and global solution test, global search and local convergence capabilities are balanced, and premature convergence is avoided; and through modeling-simulation-optimization closed-loop iteration, automatic parameter updating and feedback verification are realized, and the design period is remarkably shortened. Therefore, while the machining quality is guaranteed, the tool loss and the trial and error cost are greatly reduced, and a high-stability and high-economical-efficiency solution is provided for machining of complex materials.

The invention discloses a method and system for determining the optimal stress orientation of a concrete special-shaped sheet column, and relates to the technical field of constructional engineering. According to the method, a correlation model of special-shaped contour parameters and load conditions is constructed, a mechanical property key direction set is extracted, the screening range is narrowed, the optimal orientation determination efficiency is greatly improved, the design period is shortened, and the optimal orientation determination efficiency is improved based on multi-dimensional screening of all-circumferential inertia moment distribution, a rigidity curve and a bending moment contribution ratio. Core indexes such as section ultimate bearing capacity and ductility are comprehensively evaluated by combining stress simulation of a concrete nonlinear constitutive relation; through overall structure collaborative checking calculation and node stress analysis, it is ensured that the orientation meets the mechanical requirements of components and adapts to lateral force resistance and stress continuity of the overall structure, in combination with building construction requirements and node compressive strength redundancy optimization, the scheme of optimal mechanics but construction conflicts is eliminated, safety redundancy is reserved, the structure anti-disaster stability is guaranteed, and the construction safety is improved. And meanwhile, the method adapts to complex working conditions and specification requirements and ensures that the scheme can be directly applied.

The invention discloses a brand image creative design system, particularly relates to the technical field of brand image design and management, and comprises a data-driven intelligent creative generation engine, a full-process collaborative design platform and a brand consistency management and control system which are used for presetting brand visual specifications and carrying out compliance detection and approval flow management on a design scheme; and an immersive AR preview module. The data-driven intelligent creativity generation engine comprises a multi-modal data integration unit and an AI creativity generation unit. According to the brand image creative design system, the design precision and innovativeness can be improved, and culture elements are fused with the help of multi-modal data and the AI technology. The cooperation efficiency is improved, and multi-party real-time cooperation and version management are supported. And brand consistency is guaranteed, real-time detection is achieved, and design is standardized. And enhancing design evaluation optimization, and simulating a real scene through AR. And the cost can be reduced, the design period is shortened, and the brand design quality and efficiency are comprehensively improved.

The invention discloses a street building group automatic layout and iterative optimization method based on a TFM architecture, and the method comprises the steps: constructing a structured learnable graph attention matrix through high-precision point cloud data, and coding a building unit space topological relation and economic indexes through combining a historical case library; the method comprises the following steps: dynamically modeling a space function association relationship of a building group by utilizing a multi-head graph attention Transform module, and integrating space and function constraint conditions through a hierarchical constraint injection mechanism; an autoregression graph generation model is adopted to generate a preliminary layout scheme based on land parcel features and global constraints, and multi-target iterative optimization is carried out through a genetic algorithm in combination with a fitness function; and finally outputting a three-dimensional layout scheme meeting multi-dimensional indexes such as the plot ratio, the building density and the greening rate. According to the method, the traditional artificial experience driving limitation is broken through, adaptive learning and optimization under the multi-constraint condition are supported, the design period is shortened from several weeks to several hours, and the scientificity and feasibility of the scheme are remarkably improved.

The invention relates to the technical field of building data processing, and discloses a collaborative design method and platform for building engineering three-dimensional modeling based on BIM, and the collaborative design method for building engineering three-dimensional modeling based on BIM comprises the following steps: S101, constructing a cross-professional boundary edge set; step S102, constructing a boundary merging unit; step S103, constructing an overall cost; step S104, generating an initial solution set; step S105, outputting an optimal merging sequence, publishing time and object batch assignment; and step S106, generating a batch merging list and issuing a Gantt plan on the subject side. According to the method, computable indexes such as cross-professional asymmetry degree are constructed, the time deviation degree of cross-professional boundary object parameter updating and connection relation changing is accurately quantified, and a previous decision mode depending on experience is eliminated; therefore, the cross-professional collaboration efficiency is effectively improved, the design period is shortened, the engineering design cost is reduced, and the modeling collaboration quality is guaranteed.

The present invention relates to a method and system for compensating a composite structural component mold, and relates to the field of composite structural component molding. The method comprises obtaining a three-dimensional model of the composite structural component and determining a mold surface based on the three-dimensional model; performing a curing deformation simulation on the three-dimensional model according to a curing process curve during the actual molding process to obtain a simulation calculation result; extracting nodes from the mold surface based on the simulation calculation result to obtain the initial coordinates and deformation amounts of all nodes; performing compensation based on the initial coordinates and deformation amounts of all nodes using the mirror compensation principle to obtain a compensated mold surface; and comparing the compensated mold surface with the three-dimensional model to determine the composite structural component mold surface. By combining numerical simulation and mirror compensation, the present invention improves the design cycle of the mold surface and saves molding costs.

The invention provides a turbine blade wall thickness forward design method and system. The method comprises the steps that 1, the type of a turbine blade, the front edge radius and the tail edge radius of the turbine blade, the internal cooling mode of the turbine blade, the initial wall thickness of the front edge of the turbine blade, the initial wall thickness of the middle chord of the turbine blade and the initial wall thickness of the tail edge of the turbine blade are obtained; 2, pneumatic evaluation is conducted on the turbine blade, whether the type meets the design requirement or not is judged, if yes, the step 3 is executed, and if not, the type of the turbine blade is updated, and the step 1 is executed again; 3, performance evaluation is conducted on the turbine blade, whether evaluation results are qualified or not is judged, if yes, the step 4 is executed, and if not, the initial wall thickness of the turbine blade is adjusted, and the step 1 is executed again; and 4, the initial wall thickness of the front edge, the initial wall thickness of the middle chord and the initial wall thickness of the tail edge of the turbine blade serve as the design wall thicknesses. According to the technical scheme provided by the invention, the design period is effectively shortened.

The invention discloses a connector structure drawing generation method and device, computer equipment and a storage medium, and relates to the technical field of high-speed electronic signal transmission. And screening a target parameter combination according to the target attribute information, and obtaining a target structure parameter of the to-be-produced connector from the target parameter combination. And finally, according to the target attribute information and the target structure parameters, generating a structure drawing of the connector to be produced. The problem that the design period for determining the structure parameters of the connector is too long, and consequently time consumed for generating the structure drawing is long can be solved. According to the method, the optimal structure parameters of the connector to be produced can be quickly determined, and the period of generating the connector structure drawing is greatly shortened. Moreover, the structural parameters in the parameter combination are subjected to simulation verification, so that the accuracy of the structural parameters can be ensured.

The application relates to the field of power electronics, in particular to a filter equivalent circuit design simulation system suitable for an energy storage converter, which comprises a main circuit topology unit, a control strategy unit, a parameter optimization and design unit, a simulation engine unit and a performance evaluation unit, wherein: the main circuit topology unit is used for building a filter equivalent circuit topology of the energy storage converter and configuring passive element parameters of inductance, capacitance and resistance; the filter parameters are automatically and highly robustly optimized through genetic algorithm-particle swarm hybrid optimization, multi-objective collaborative optimization and digital twin auxiliary optimization; dynamic working condition evaluation, reliability modeling and artificial intelligence auxiliary analysis are combined to form a "design-optimization-verification-iteration" closed loop; the harmonic suppression capacity, the efficiency and the long-term operation reliability of the filter are significantly improved; the design cycle is shortened and the development cost is reduced.

The invention discloses an industrial design component library management and automatic matching method and system, and relates to the technical field of XXX industrial design, and the method comprises the following steps: obtaining the dimension attribute of a component, and carrying out the fusion modeling of the dimension attribute of the component; obtaining design requirements, extracting keywords according to the design requirements, matching the keywords with semantic tags in the component library, and obtaining semantic similarity based on a cosine similarity algorithm; constructing a matching model according to the semantic similarity in combination with the dimension attributes of the components, and comprehensively evaluating the dimension attributes of the components by using a weighted multi-dimensional data fusion technology to obtain matching degree scores of the components and the design requirements; and comparing the matching degree score with a preset matching threshold value, evaluating an automatic matching effect according to a comparison result, and dynamically updating the attribute weight of the component according to the automatic matching effect. According to the method, the problem of separation of semantic understanding and attribute matching is solved, rapid matching of components and design requirements is realized, the design period is remarkably shortened, and the design efficiency is improved.

The invention provides an industrial steam turbine exhaust optimization system and method, and belongs to the technical field of steam turbine design, and the method comprises the steps: obtaining a flow field data set representing the full working condition operation of a steam turbine; based on the flow field data set, processing last-stage blade outlet section flow field information so as to determine rotational flow strength factors corresponding to all the operation working conditions; converting the three-dimensional solid geometry of the exhaust hood diffuser into a candidate three-dimensional geometric configuration parameterized model controlled by preset geometric parameters; coupling the candidate three-dimensional geometric configuration parameterized model with the corresponding rotational flow intensity factor according to each operation condition, and determining a pressure recovery coefficient and a flow stability coefficient through computational fluid dynamics simulation; and in combination with the preset performance weight coefficient and the preset working condition weight, the pressure recovery coefficients and the flow stability coefficients of all the operation working conditions are subjected to weighted calculation, so that the design points of the unit and the comprehensive operation efficiency, the full-working-condition adaptability and the operation safety under the variable working conditions are remarkably improved, and the design period is greatly shortened.

The invention discloses a stratospheric airship structure optimization design method and a stratospheric airship structure optimization design system based on joint simulation, and aims to solve the problems of long design period, low efficiency and the like caused by consideration of optimal aerodynamic performance due to size or volume limitation in existing airship design. According to the method, the shape of a capsule body is set through Python with a Bezier curve method, the shape of an empennage is set through parameterized design, constraint conditions are output, and three-dimensional CAD software is driven to automatically generate an airship shape model; computational fluid dynamics software is used for completing pneumatic simulation and exporting a report, after Python format conversion, engineering simulation optimization software is imported to build an optimization platform, optimization design is carried out with optimal pneumatic performance as a target in combination with constraint conditions, and finally, optimal structure parameters are verified and output. According to the method, full-process automation from parametric modeling, pneumatic simulation to optimization verification is achieved, the design period is shortened, the efficiency and precision of stratospheric airship structure optimization are improved, and it is ensured that a shape scheme with the optimal pneumatic performance is obtained.

The invention discloses a BIM (Building Information Modeling) technology-based pipeline hole reserving design system and method. The method comprises the following steps of defining hole occupation data for storing hole parameters; according to each hole occupation data read from the storage of the project file, creating a corresponding hole volume in the BIM software as a BIM model component; calculating the geometric dimension of the volume of each hole; combining the masses of the adjacent holes; and updating corresponding hole occupation data according to the combined hole volume, and generating a hole instance of the multi-view BIM hole according to the updated hole occupation data, thereby realizing synchronization of the BIM hole and the two-dimensional drawing. According to the method, automatic circulation of pipeline hole reserving from data to models and drawings is realized; the problems that omissions are easy to occur in manual marking and no professional discrimination is available for plug-in hole opening are solved, the design quality is guaranteed, the design period is shortened, and information mistakes and omissions are reduced; and multiple views are synchronously generated, so that inconsistency of manual labeling is avoided, and construction application is directly supported.

The invention discloses a CVM-based airfoil profile multi-objective optimization method, equipment, a medium and a program product. The method comprises the following steps: (1) respectively constructing an airfoil profile lift coefficient simulation model, an airfoil profile resistance coefficient simulation model and an airfoil profile rigidity simulation model in SU2 and Ansys; (2) establishing a population and a database by using Latin hypercube sampling and Pearson product-moment correlation coefficients; (3) constructing a global radial basis function prediction model; (4) generating candidate offspring individuals for each sub-problem by using elite-guided co-evolution operation, and constructing a sub-population; (5) evolving the sub-population in the characteristic space after covariance matrix mapping; and (6) based on a Chebyshev fitness function, screening an airfoil node parameter vector solution set, updating a population and a database, and turning to the step (3) until a design cycle is reached. According to the method, the comprehensive performance of the airfoil structure is improved through elite-guided co-evolution and characteristic space efficient evolution after covariance matrix mapping.

The invention discloses a ducted fan design method with flow as a key variable, and belongs to the field of ducted fan design. The method comprises the specific steps that the flow needed by a duct is determined; the rotor inlet area and the throat area are calculated according to the flow; determining radial positions of rotor / stator inlet and outlet equidistant control points; constructing a speed triangle based on the set rotating speed and the calculated torque speed and axial speed; geometric feature determination of the rotor and the stator is completed; and exporting geometric data to turbine simulation software to complete three-dimensional modeling of the rotor and the stator. According to the method, the problems that traditional design depends on experience and is low in efficiency are solved, the design period is remarkably shortened while the precision is guaranteed, and the reliability and aerodynamic performance of the ducted fan are improved.

The invention relates to the technical field of mechanical part design, and discloses a flange bolt connection layout optimization design method and related equipment.The method comprises the steps that flange basic parameters are obtained, and a rigidity calculation model is constructed based on the flange basic parameters; bolt margin parameters are determined through sealing surface pressure distribution based on a rigidity calculation model; bolt spacing parameters are determined through pressure distribution changes based on a rigidity calculation model; and performing parametric modeling and simulation checking on the determined bolt edge distance parameters and bolt spacing parameters by taking the pressure distribution change rate as a checking parameter to obtain a design result, and completing flange bolt connection layout optimization design through the design result. According to the method, discrete experience is upgraded into a continuous scientific model, the design reliability is remarkably improved, static strength design of a traditional empirical formula is replaced, and therefore the sealing reliability is remarkably improved, the method adapts to complex working conditions, and the design period is greatly shortened.

The invention relates to a full-parameterization automatic closed-loop pressure pulsation optimization method for a spaceflight high-pressure corrugated pipe. The method comprises the following steps that S1, geometric parameters and optimization instructions of the corrugated pipe are input into a text command interface; s2, the parametric modeling module generates a corrugated pipe geometric model; s3, an automatic simulation analysis module performs grid division and computational fluid dynamics simulation on the generated geometric model, and automatically extracts an index value representing the pressure pulsation intensity from a simulation result; s4, an optimization decision module automatically adjusts the geometric parameters, generated in the step S2, of the corrugated pipe, a new geometric parameter combination is generated with the purpose of minimizing the index value representing the pressure pulsation intensity, the new geometric parameter combination is fed back to a parameterization modeling module for next iteration, and a closed-loop optimization process is formed till a termination condition is met; and S5, outputting the optimal geometric parameter combination by a result output module. According to the method, the operation efficiency is improved, the design period is shortened, and the optimization quality and reliability are fundamentally improved.

The invention discloses a multi-objective optimization design method for a high-voltage nanosecond pulse adder, and aims to solve the problem that the prior art depends on experience trial and error and is difficult to consider multiple objectives such as fast leading edge, high efficiency, portability and reliability. The method comprises the following steps: firstly, building a simulation and experiment platform, and acquiring output waveform data for changing topological parameters; constructing a physical model of the influence rule of the parasitic parameters on the pulse rising edge time and the voltage gain, and establishing a power supply efficiency prediction model based on a deep neural network; taking the minimization of the pulse rising edge time and the maximization of the voltage gain and the energy efficiency as targets, constructing a particle swarm optimization multi-target optimization model in combination with the model, and obtaining a Pareto optimal solution set under the constraints of portability and parasitic parameters; and finally, carrying out experimental verification iteration to obtain an optimal scheme. According to the invention, the design period is obviously shortened, the multi-target conflict is effectively balanced, the rising edge time is shortened, the energy efficiency is improved, the voltage gain is improved, the portability is enhanced through the modular design, and the wearable application is compatible.

The invention relates to the technical field of buildings, in particular to a style and feature fusion design method for a building roof photovoltaic system. The method aims at overcoming the defects that in the design process of an existing roof photovoltaic system, multi-dimensional requirements such as style, appearance, economy and safety cannot be quantified and unified, and the design period is long and the landing difficulty is large due to the fact that design and modeling links are disjointed and separated. According to the method, traditional fuzzy requirements of building style and appearance coordination, visual influence, landscape sensitivity and the like depending on subjective experience are converted into calculable parameters based on objective data, a scientific and unified evaluation criterion is provided for a design scheme, dependence on artificial experience is reduced, and standardization and efficiency of an approval process are improved; the invention aims to shorten the design period and guarantee the technical feasibility, economic rationality and style compliance of an existing building roof photovoltaic installation project in a complex urban and rural environment, especially in a style sensitive area.

The application discloses a kind of based on RAG's few-sample processor design PPA prediction method.The technical scheme is: the processor design paradigm, EDA tool module, RAG module, the input module of processor design to be measured and PPA prediction module are formed based on RAG's few-sample processor design PPA prediction system.RAG module carries out sampling to the design space of processor design paradigm, obtains processor design sample, the feature vector coding of sample, utilizes EDA tool module to obtain the PPA value of design sample, constructs the knowledge base required for PPA prediction;RAG module detects the knowledge matched with the processor design code of the PPA value to be predicted in knowledge base, generates prompt word based on the matched knowledge.PPA prediction module and prompt word interaction, obtain the PPA prediction value of the PPA value processor design to be predicted.The application can be based on a few samples to carry out accurate PPA prediction, shortens design cycle.

The invention provides an optimization design evaluation method for a labyrinth welding drum based on a parameterized model, and belongs to the technical field of aero-engines, and the method comprises the steps: building a drum parameterized mathematical model, and determining a drum stress expression; determining a dangerous part of the drum at the maximum working rotating speed, and determining the section average stress of the dangerous part based on the stress expression; aiming at the welding part, determining the residual strength reserve coefficient of the drum based on the initial defect, and determining the stress reserve coefficient of the welding part; for the maximum stress part, the ratio of the minimum self-sustaining radius of the two wheel discs connected with the drum to the pitch diameter of the drum is obtained; when the ratio does not meet the preset condition, the stress reserve coefficient of the maximum stress part is determined; and carrying out optimization design on the structural parameters of the drum by taking the lightest weight of the drum as an objective function and taking the condition that the residual strength reserve coefficient and the stress reserve coefficient do not exceed the material performance as a constraint condition. A complete evaluation system is established, the design period is shortened, and the evaluation accuracy is improved.

The application discloses a kind of uncertainty quantification driven MEMS sensor intelligent design method and system, the method is first obtained by finite element simulation MEMS sensor experimental data;Then construct and train uncertainty quantification model, obtain the positive mapping relationship from sensor physical structure to performance parameter, and output corresponding uncertainty quantification result;Then construct and train generative model CDDPM, for realizing by expected performance and expected variance to structure parameter inverse design;Finally, construct multi-solution generative model, and efficiently generate multiple sets of structure parameters that meet performance requirements and variance constraints simultaneously.The application does not need to carry out time-consuming multi-physical field simulation and artificial parameter adjustment, with the characteristics of fast speed, high precision and intelligence, which helps to shorten the design cycle and realize rapid iterative design;The application realizes the efficient output of diversified design scheme while giving quantifiable confidence information, significantly improves the reliability of MEMS sensor intelligent design method.

The invention relates to the technical field of jewelry design, in particular to a jewelry design system and method. A user interaction module receives a demand and feeds back; the intelligent design module combines a deep learning model and a knowledge base for preliminary design; the material and color selection module recommends material and color schemes according to styles, crowds and the like; the virtual display and rendering module generates a three-dimensional display model; the design optimization module performs multi-aspect evaluation and provides suggestions; and the data management module stores and manages design data. The design sketch is quickly generated through the intelligent design module, and automatic material and color recommendation, virtual display and rendering functions are combined, so that the jewelry design period is greatly shortened, and market requirements can be quickly responded. According to the method, the personalized requirements of the user are fully considered, and the user can autonomously select and adjust each link in the design process, so that the design result better fits the expectation of the user.

The application discloses an OTR tire pattern heat dissipation hole parameter design and heat dissipation strengthening method, and belongs to the tire structure design field.The method firstly establishes a tire parameterized model containing a heat dissipation hole, determines the length, width, depth and inclination angle of the heat dissipation hole as key design variables; subsequently, sample points are generated in the design space by using Latin hypercube sampling, and the average convective heat transfer coefficient corresponding to each sample is calculated through numerical simulation; then, a radial basis function proxy model with the design variables as input and the heat transfer coefficient as response is constructed, and the accuracy thereof is verified; thereafter, the design variables are globally optimized by using an adaptive simulated annealing algorithm with the maximization of the average convective heat transfer coefficient as the target, and the optimal structure parameters are obtained; finally, the optimization scheme is modeled and numerically verified.The application significantly improves the heat dissipation efficiency of the OTR tire through multi-parameter collaborative optimization, has the advantages of short design cycle, strong optimization ability and good versatility, and is helpful to prolong the tire life.