201 results about "Design cycle" patented technology

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 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 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 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 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 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.

This application relates to the field of window design technology, and particularly to a method, system, and device for designing inward-opening and tilt-and-turn windows. The method includes: detecting an adjustment command; if a target parameter exists within a preset constraint dataset, not extracting design data from the target parameter set; if the target parameter set does not exist within the preset constraint dataset, extracting design data from the target parameter set to determine window opening angle data; and if the window opening angle data does not exist within the target constraint dataset, using the window opening angle data to design the inward-opening and tilt-and-turn window. The inward-opening and tilt-and-turn window design method provided by this application can solve the problem that in the process of designing inward-opening and tilt-and-turn windows, the design system may repeatedly use inappropriate opening angles, leading to the inability to obtain the correct design solution in a timely manner, thus causing a prolonged design cycle.

The present application belongs to the technical field of photonic device design, and specifically relates to a micro-ring resonator reverse design optimization method based on deep learning. The present application comprises: obtaining different micro-ring resonator structure parameters and corresponding free spectral range and quality factor, and processing and dividing the data set; building a cascade neural network model, wherein the reverse network takes the target performance index as the input to predict the structure parameter, the forward network inputs the structure parameter and outputs the performance index, and is used to constrain and correct the reverse prediction result; after training, the test set is evaluated to measure the reverse effect by the average absolute percentage error index, the weight in the loss function is changed, and multiple rounds of training are performed to determine the optimal weight configuration and final model of the reverse design. The present application has the advantages of high calculation efficiency, excellent design precision and strong physical realizability, can reduce the dependence on large-scale simulation and multiple iteration optimization, effectively shorten the device design cycle, and has high application value.

This invention relates to a rapid prediction system and method for combustion characteristics of pure hydrogen micro-mixed combustors based on CNN. The invention addresses the problem of long design cycles for micro-mixed pure hydrogen combustors. By constructing a dataset representing the relationship between "inlet conditions and combustion characteristics," this invention enables rapid prediction of the combustion characteristics of pure hydrogen micro-mixed combustors based solely on the inlet conditions, significantly accelerating the variable operating condition design cycle. The prediction system includes a data acquisition module, a data preprocessing module, a dataset partitioning module, a prediction model construction module, a combustion characteristic prediction module, and a model update and optimization module. This invention belongs to the field of micro-mixed combustion technology.

The application relates to a parallel multi-objective optimization method and system for engineering product CAE simulation, and belongs to the technical field of simulation optimization. The method solves the problems that the simulation-driven design cycle is long and it is difficult to obtain a high-quality multi-objective trade-off optimization scheme. The method comprises the following steps: based on multiple objective functions and constraint conditions, initial sample data is obtained through two-stage collaborative optimization and is put into a sample library; a joint surrogate model is constructed and trained, and a hierarchical error compensation mechanism is initialized; multiple rounds of iterative optimization are performed until a preset optimization termination condition is met; each round of iterative optimization comprises the following steps: based on the current joint surrogate model and the hierarchical error compensation mechanism, multiple candidate design points are generated in parallel, and then the multiple candidate design points are distributed to multiple computing nodes for parallel simulation calculation to obtain new sample data which is put into the sample library; the joint surrogate model and the hierarchical error compensation mechanism are updated; and a multi-objective optimization design scheme set of a product to be optimized is obtained from the final sample library. The optimization efficiency is improved.

The invention discloses a wave rider shape approximate optimization method based on an agent model. According to the method, the parameterized shape of the waverider is established and passivated by adopting the CST method, the three-dimensional viscous effect and the front edge passivation effect of the shape of the waverider are considered, and the flight surface grid local parameters are generated by adopting the Jacobian conversion method, so that automatic updating of the waverider space grid in the optimization process is realized; then, the aerodynamic / thermal characteristics of the waverider are calculated based on a Reynolds average Navier-Stokes equation (RANS); the method comprises the following steps: constructing a waverider shape optimization problem by taking the maximum lift-drag ratio as an optimization target, solving the optimization problem by adopting an agent model assisted constraint optimization algorithm, and circularly selecting new sample points to update an agent model based on a certain point adding criterion in the solving process until approximate optimization convergence. According to the method, the optimization efficiency can be effectively improved, the design period is shortened, and optimization and modification of the wave rider shape scheme can be rapidly achieved in the overall design stage.

The application discloses a creative design method, system, device and medium based on creative samples, changes the randomness of traditional design depending on inspiration, establishes a standardized process from demand to landing, improves based on the closest existing technology sample, avoids blind exploration from zero, greatly shortens the design cycle, introduces verification and prototype iteration steps, and ensures that the creativity not only stays on paper, but also can be converted into a final scheme with technical feasibility.

This application discloses a method, apparatus, equipment, and medium for flutter analysis of UAV wings during the design phase, relating to the field of aircraft design. The method includes: generating a first component by calling a corresponding structural component simulation model from a finite element structure module library based on the shape parameters of the wing to be analyzed; constructing a skin finite element mesh model based on the first component; determining the installation position of a second component at the node positions of the skin finite element mesh model; generating the second component by calling a corresponding structural component simulation model from the finite element structure module library; installing the second component at the corresponding node positions of the skin finite element mesh model based on the installation position to obtain a target wing model; performing aerodynamic modeling using the skin finite element mesh model to obtain a flutter calculation file; performing flutter analysis based on the flutter calculation file and the target wing model; and optimizing the wing to be analyzed that has a flutter risk based on the flutter analysis results. This application shortens the UAV design cycle.

The application belongs to the technical field of transformer three-dimensional design, and discloses a transformer three-dimensional parameterized design method based on Autodesk Inventor, which is realized based on an iLogic programming platform embedded in Autodesk Inventor, and the design steps are as follows: step one, establishing a standard component template; step two, parameterized design; step three, three-dimensional model generation; step four, two-dimensional drawing generation; and step five, version management and updating. The sub-modules are set as the standard component template, and the parameterized mode is used, so that the designer only needs to input design data in the input interface of the parameterized standard component template during design, then calls the program to calculate, and the transformer three-dimensional model and two-dimensional drawing can be obtained, thereby greatly reducing the workload and shortening the design cycle, and more importantly, the algorithm of the parameterized standard component template eliminates the quality problems caused by human factors and controls the design quality at a high level.

The invention relates to a simulation method for optimizing a high-speed wiring transition position. The method comprises the following steps: establishing a simulation model; adjusting the initial position of the reference plane of the fine line, and setting a variable for the moving distance of the reference plane of the fine line; traversing different values of the variables, and simulating to obtain TDR impedance results corresponding to different variable values; and according to a preset TDR impedance optimization target, a variable value conforming to the target is screened out from the TDR impedance result, and optimization of the high-speed wiring transition position is completed. By adjusting the initial position of the fine line reference plane and setting the displacement distance variable, the dynamic simulation analysis of the spatial position of the fine line reference plane is realized, and the impedance change rule of the transition area under different reference plane positions can be accurately captured; according to the method, the initial position parameter and the variable value range can be flexibly adjusted according to the difference requirements of different items on the length of the transition line; according to the method, the design period of the high-speed PCB is effectively shortened, and the design efficiency is improved.

The invention discloses a catalytic material element ratio optimization method and system, and the method comprises the steps: obtaining a data set of a catalytic material in a catalytic reaction, carrying out the preprocessing and standardization processing of the data set, and dividing the data set into a training set and a test set; training and evaluating the multiple candidate machine learning models based on the training set and the test set, and screening out a model with the best performance as a catalytic material performance prediction model; determining an element optimization object of the catalytic material, taking the catalytic material performance prediction model as a target function, and constructing an element ratio optimization model by using a heuristic optimization algorithm; optimizing calculation is carried out according to the element ratio optimization model, the optimal element ratio under the target performance is output, and the technical problems that when the high-performance carbon-based catalytic material is developed, the design period is long, the cost is high, and rational optimization of the multi-element ratio is difficult to achieve are solved.