735 results about "Design systems" patented technology

The invention discloses a low-code platform based on a component library and a form engine, and relates to the field of data processing. The platform comprises a design system, an application system and a service system. The design system is provided with a form designer and a template manager, the form designer can configure a form component to generate a description file, and the template manager supports separate storage of a page template; the application system comprises a form analysis engine, a UI rendering engine and a reusable resource management component, the analysis engine analyzes configuration generation logic, the rendering engine loads a resource rendering page, and the reusable resource management component stores resources and generates configuration; the service system comprises a metadata analysis engine and an SQL assembler, the metadata analysis engine analyzes business rules to generate SQL and filtering strategies, and the SQL assembler generates operation statements adaptive to multiple data sources. Through the modular architecture design and the dynamic analysis mechanism, the problem that a low-code platform is insufficient in flexibility and usability is solved.

The invention discloses a speed reducer gear box lightweight design method based on topological optimization, and relates to the technical field of gear box optimization. A processing end establishes a three-dimensional parameterized geometric model, performs finite element mesh generation on the geometric model, optimizes material distribution of the geometric model based on a topological optimization algorithm, and optimizes the material distribution of the geometric model; a topological optimization result is parameterized into geometric features, a random generation tool is used for generating a plurality of initial variable sets, a genetic algorithm is used for outputting an optimal variable set, a geometric model is reconstructed according to the topological optimization result and a genetic algorithm result, and after dynamic-static simulation is conducted on the reconstructed geometric model, the optimal variable set is obtained. And evaluating whether the performance of the reconstructed geometric model reaches the standard or not, and if not, optimizing genetic algorithm parameters according to an evaluation result and then cyclically reconstructing the geometric model until the performance of the reconstructed geometric model reaches the standard. The design system intelligently optimizes a local high-stress area, so that the lightweight requirement is met, and meanwhile, the strength and rigidity balance of the structure is ensured.

The invention discloses a multi-modal knowledge-based automotive body innovative design system, which comprises a multi-modal data fusion module, a multi-modal data fusion module, a multi-modal data fusion module, a multi-modal data fusion module and a multi-modal data fusion module, wherein the multi-modal data fusion module is used for receiving text data, picture data, a three-dimensional CAD (Computer Aided Design) model file and an engineering symbol expression from an automotive body design process and is used for carrying out feature extraction and semantic alignment on input data of four modals; generating a unified semantic vector representation; the cross-modal knowledge mining and graph construction module is used for extracting multi-level entities and relationships from the unified semantic vector and constructing a dynamically weighted multi-modal knowledge graph; the large-model-driven multi-hop collaborative reasoning module is used for analyzing the multi-modal design requirement of a user, carrying out multi-hop reasoning on a knowledge graph, and outputting design parameter recommendation and an interpretable reasoning chain. The method aims at breaking through the limitation of an existing design system in the aspects of multi-modal processing and shallow semantic understanding, and deep fusion and intelligent application of multi-source heterogeneous design data are achieved.

The invention discloses an automobile wire harness process rule automatic matching method based on a knowledge graph, and the method comprises the following steps: collecting wire harness design data, and carrying out the standardization processing; analyzing the process rule base, extracting key attribute fields and generating a process rule metadata set; semantic modeling and structured fusion are carried out, and a process knowledge graph is constructed; performing semantic association analysis, causal constraint fusion and feasibility judgment processing by utilizing a semantic retrieval enhancement module; carrying out provable retrieval, risk assessment and conflict resolution based on the candidate process rule set; converting the target process rule set into a process instruction, and driving a design system to perform synchronous updating and rule labeling; and updating the process knowledge graph based on system feedback data, and outputting an optimized process verification report and updating a design version. The method is based on the knowledge graph and the semantic causal fusion technology, intelligent matching of the wire harness process rules is achieved, and the method has the advantages of being high in matching precision, high in interpretability and capable of achieving self-adaptive optimization.

The invention discloses a mold and formwork design system based on virtual simulation, and particularly relates to the field of mold design, the mold and formwork design system comprises a multi-mode perception fusion module, a digital twin modeling module, a multi-physics field coupling simulation module, a hybrid intelligent optimization module, a digital twin closed loop verification module and a data center module, and each module forms a design closed loop through a data center. The multi-modal sensing fusion module adaptively collects and fuses multi-source signals to generate high-credibility data; the digital twin modeling module constructs and iteratively corrects a model based on the data; the multi-physics field coupling simulation module realizes multi-solver co-simulation under a dynamic boundary; the hybrid intelligent optimization module accelerates to generate an optimal solution through secondary optimization and an agent model; the digital twin closed-loop verification module detects defects and generates a correction instruction; the data center module is responsible for data management, cross-module scheduling and precision control; the system improves the design precision and efficiency of the mold frame, reduces the physical mold testing cost, and is suitable for a high-precision mold development scene.

The invention provides a cell culture medium aided design system and method based on a large oracle model, and belongs to the technical field of artificial intelligence. A plurality of candidate culture medium formula schemes meeting user requirements are generated by obtaining culture medium design parameters and requirements and designing structured cues and inputting the designed structured cues into a large language model; a substance matched with the structured cue word is retrieved by utilizing a retrieval enhancement technology, a replacement substance is recommended for a user to refer, the user selects and purchases a required experimental material according to own requirements, a candidate culture medium formula scheme is fed back and evaluated in an actual experiment, and the system performs iterative optimization based on the feedback and evaluation, so that the accuracy of the experiment is improved. And a more appropriate candidate culture medium formula scheme is provided. According to the cell culture medium aided design system and method, intelligence, scientization and individuation of culture medium formula scheme design are achieved, experiment cost is reduced, repeatability and stability of cell culture experiments are improved at the same time, and therefore wide application of culture medium design in the field of biological manufacturing is promoted.

The invention discloses an optimization design method of a large-model-driven mechanical part, which comprises the following steps of: performing knowledge retrieval according to a design task and a constraint condition, and generating text description of a structure design scheme by fusing the retrieved knowledge through a large-scale language model (LLM); the LLM performs task decomposition and modeling code mapping on the structure design scheme described by the text, and generated modeling codes are directly executed by modeling software to generate a three-dimensional model; the LLM generates a reasoning track and calls a finite element analysis tool set to perform performance analysis on the generated three-dimensional model; and according to optimization requirements and design constraints, the LLM optimizes the three-dimensional model to generate an optimal three-dimensional model. The invention discloses an optimization design system of a large model driven mechanical part. The optimization design system comprises a design scheme generation module, a parametric modeling module, a design scheme verification module and a structure parameter optimization module. The method and the system provided by the invention can save code quantity, reduce manual intervention and improve design efficiency.

The invention relates to the field of intelligent interactive design, and particularly discloses a visual intelligent interactive design system which comprises a three-dimensional structure design module, an intelligent color matching module, a visual rendering module and an interactive feedback analysis module. The three-dimensional structure design module can process imported or custom a three-dimensional model, detect and repair topology errors and construct a three-dimensional scene basic framework; the intelligent color matching module generates a color matching scheme based on the instruction, a rule base or user preference and displays a comparison view; the visual rendering module renders a three-dimensional scene in real time, collects rendering pipeline load parameters and quality indexes, and analyzes balance points to adjust rendering parameters; and the interaction feedback analysis module records interaction data, marks over-limit nodes by comparing a standard and analyzes a root cause. According to the system, efficient three-dimensional scene construction, intelligent color matching, rendering optimization and interaction experience improvement are realized through multi-module cooperation, and the system is suitable for multi-field scenes needing visual intelligent interaction design.

The invention relates to the technical field of form design, in particular to a business form design method based on a visual component. The method comprises the following steps: constructing a multi-type component resource pool in a business form design system, and presetting a standardized configuration parameter set for each component; realizing a component dragging interaction mechanism on the visual design interface, and generating initial layout data at the same time; constructing a component configuration context environment based on the initial layout data, and generating intermediate state form definition data; an index data association mechanism is achieved in the intermediate state form definition data, mapping binding is conducted on the intermediate state form definition data and form components, and a form data structure containing data flow direction definition is generated; and constructing a cross-platform rendering adaptation engine based on the form data structure to automatically generate a form rendering code so as to realize a form design real-time preview system, and providing an interactive debugging tool set for verifying the functional integrity of the form. According to the invention, efficient design and flexible deployment of the business form can be realized.

The invention relates to the cross technical field of fluid mechanics and machine learning, and discloses a particle fluid two-phase flow simulation and reverse optimization method based on deep learning. The method comprises the following steps: constructing a two-phase flow coupling simulation framework based on a fusion discrete element method and smoothed particle fluid dynamics; the drag force, buoyancy and capillary force between particles and fluid are introduced, and the calculation efficiency is improved through GPU parallel acceleration; a graph neural network is adopted to establish a particle-level dynamic interaction modeling framework, and coding and prediction of solid particles and fluid particles are independently processed; a differentiable reverse design system is further developed, and layout parameters of a flow control structure are dynamically optimized based on a gradient descent method by combining automatic differential characteristics of GNN and surrounding target functions such as flow collapse degree and centroid offset, so that effective suppression of two-phase flow destructive behaviors and system performance optimization are realized. The method has high-precision simulation and efficient optimization capabilities, and is suitable for complex two-phase flow engineering scenes such as dam burst and debris flow prevention and control.

The invention belongs to the technical field of composite material design, and discloses a polyimide-based composite material design method and system based on experiment-machine learning collaborative optimization. The method comprises the following steps: S1, experimental database construction and machine learning performance modeling; S2, machine learning model construction and training; S3, model evaluation and performance index output; and S4, intelligent design of the polyimide-based composite material. The multi-objective performance collaborative optimization design and preparation of the polyimide-based ternary carbon heterostructure composite material are carried out by taking experimental data as a main material and machine learning as an auxiliary material. According to the method, an experiment-model-optimization closed-loop iterative design system is constructed based on an experiment-machine learning collaborative optimization method, the method has the advantages of high prediction precision, high optimization efficiency, good multi-target adaptability and the like, the development efficiency of the polyimide-based composite material is remarkably improved, and the development cost of the polyimide-based composite material is reduced. The method is suitable for intelligent design and large-scale application and popularization of the high-performance heat-conducting electromagnetic shielding material.

The invention relates to a robust distributed photovoltaic power station generation power prediction method and system, and the method comprises the steps: obtaining historical data of a distributed photovoltaic power station, and carrying out the preprocessing; selecting weather characteristic data with strong correlation with photovoltaic output power as input data; obtaining a robust distributed photovoltaic prediction model; training a weight parameter of the distributed photovoltaic prediction model, and selecting an optimal hyper-parameter; and obtaining a real-time prediction result. The method has the beneficial effects that the outliers are considered in the designed system model, so that the interference of noise on a prediction result in photovoltaic output power prediction can be effectively reduced; and the distributed model takes the system as a whole, and a plurality of stations are cooperatively trained, so that the prediction precision can be effectively improved.

The invention discloses an aviation three-dimensional aided design integration method and system based on a large language model. The method comprises the steps of obtaining multi-modal design demand data submitted by a user; analyzing the multi-modal design demand data submitted by the user; and calling a large language model to generate a corresponding modeling command according to the analyzed multi-modal design demand data, calling a computer aided design system by utilizing the modeling command to carry out modeling design, and optimizing the large language model at the same time. The system comprises a user interaction module for receiving multi-modal design demand data input of a user; the data analysis module is used for analyzing the multi-modal design demand data and extracting a design demand; the modeling instruction generation module is used for calling a large language model to generate a modeling instruction according to a design requirement; the modeling execution module is used for calling a computer aided design system API to complete modeling by utilizing the modeling instruction; and the model optimization module is used for feeding back the model data modified by the user to the large language model for optimization.

The invention discloses a digital typesetting design system and method for a clean workshop enclosure structure based on a BIM technology. The digital typesetting design system comprises a room processing unit which comprises a room generating unit, a room merging unit and a room separating unit; the typesetting area division unit is used for distinguishing room practice, cutting ceilings, combining the ceilings, typesetting partitions and cancelling the partitions; the typesetting unit comprises typesetting configuration and one-key typesetting; the top plate typesetting and adjusting unit comprises ceiling typesetting, top plate adjusting, top plate dividing and top plate combining; the wallboard typesetting and adjusting unit comprises wallboard typesetting, wallboard adjustment, wallboard segmentation and wallboard combination; the optimization typesetting unit is used for optimizing non-standard boards of the wallboards; the plate coding unit comprises coding rule definition, automatic coding and non-standard combination; and the typesetting result output unit is used for generating a plate purchase list, a profile purchase list and a typesetting drawing. According to the method, rapid and refined generation, three-dimensional intelligent typesetting, non-standard plate optimization and numbering drawing of the building envelope model can be realized, the building envelope typesetting efficiency and quality are improved, and the problems of low typesetting efficiency and insufficient optimization in an existing method are solved.

The invention discloses an intelligent creative design system based on a diffusion model. The system comprises sketch generation, sketch optimization, style migration and high-quality rendering. According to the method, the design efficiency and innovativeness are improved through an intelligent technology, and meanwhile, the personalized requirements of users are met. According to the system, firstly, diversified design sketches are generated through a diffusion model, an initial sketch is generated through Gaussian noise step-by-step iteration, and keywords or style labels input by a user are introduced in combination with a conditional diffusion model so as to control the generation direction; performing feature extraction on the sketch by using a convolutional neural network, and optimizing lines and structures of the sketch through a multi-layer perceptron; then, in combination with a style migration technology, migrating an artistic style specified by a user into the sketch, and meanwhile, introducing an attention mechanism to ensure local detail consistency of style migration; and finally, performing high-quality rendering on the design by using a GAN, optimizing detail performance through adversarial training of a discriminator and a generator, and improving the image resolution by using a super-resolution technology.

The invention relates to the technical field of packaging image processing, and provides a customizable cultural and creative packaging design system based on AIGC, and the system comprises the following modules: a data input module which is used for receiving cultural and creative themes, cultural element preferences and packaging specification parameters inputted by a user; the culture element database is used for storing multi-dimensional culture symbol data including patterns, color pedigree, historical allusions and semantic association rules; and the AIGC generation engine is used for extracting features from the culture element database according to the input parameters based on a generative adversarial network (GAN) and a Transform model, and generating an initial design draft. 10 versions of high-quality design schemes can be generated within 5 minutes through an AIGC engine, the speed is increased by 8 times compared with a traditional process, meanwhile, the modification feedback period is shortened to 2 hours through AR real-time preview, the user satisfaction degree reaches 94%, the pattern semantic matching accuracy is improved to 89%, the historical allusion misuse rate is reduced to 3% or below, and the design efficiency is improved. And the material waste rate of the automatically generated printing file is reduced to 12%, and the delivery cycle is shortened by 40%.

The invention discloses a smart park platform planning and designing system, and belongs to the technical field of smart city construction. Multi-source static and dynamic data are integrated through the data acquisition and integration module, and the space function planning module and the dynamic resource allocation optimization module construct an optimization model based on core function requirements and resource requirements, so that scientific planning of space layout and resource allocation is realized; the simulation evaluation display module dynamically evaluates the traffic flow, the environmental influence and the resource efficiency by using a three-dimensional digital park model and a multi-dimensional simulation technology, provides a visual and quantitative evaluation result for a planning scheme, effectively reduces the design risk, combines the planning intelligent auxiliary decision-making module and the user participation feedback module, and improves the design efficiency. Through a rule engine and a multi-dimensional comparison model, an optimal design strategy is recommended for the dimensions of cost, efficiency, environment and the like, meanwhile, user requirements are collected and converted into optimization suggestions, a closed-loop optimization process is formed, and the applicability of a planning scheme and the user satisfaction degree are improved.

The invention discloses a garment customization design system and method based on AI body shape data analysis, and relates to the technical field of data processing, user customization circumference basic evaluation is carried out based on user circumference body shape data, and garment design schemes of all parts of a user in all scenes are generated according to user customization circumference basic evaluation results; adjusting and evaluating the costume design scheme based on the muscle change condition data of each part and the activity condition data of each part; and judging whether the costume design scheme needs to be adjusted based on the costume design scheme adjustment evaluation result, outputting each part, needing to be adjusted, of the user in each scene according to the costume design scheme adjustment evaluation judgment result of each part of the user in each scene, and performing costume customization design according to different conditions of each part of the user in each scene. Different scenes and requirements are met, a user can show the personal style, meanwhile, it can be ensured that the clothes cannot limit movement, and the wearing comfort and the long-term use experience of the user are improved.

Systems and methods for generating an editable design using an auto-regressive pre-trained large language model (LLM) are disclosed. The method includes: receiving a prompt to generate the editable design; sequentially generating a set of tokens of model representation data for the editable design, each token in the set of tokens defining an attribute of the editable design; for each token in the set of tokens, determining whether the token is a predicted special token associated with a design asset or a non-special token; upon determining that the token is a non-special token, providing the non-special token as an input to the LLM to generate a next token in the set of tokens; upon determining that the token is a predicted special token: replacing the predicted special token with a replacement special token associated with a design asset stored in a design asset library; and providing the replacement special token as the input to the LLM to generate the next token in the set of tokens.

The invention discloses a low-code platform design system based on modularization and a dynamic extension component, and relates to the technical field of low-code development, and the system comprises a form module which is used for standardly defining a data model and dynamically rendering a user interface, realizing unification of form configuration through a structured metadata specification, and establishing a form module; bidirectional binding of the view and the data model is realized; the process module is used for realizing modeling, execution and state management of a business process, supporting automatic task scheduling and multi-instance management based on standardized process elements, and keeping consistency of a process state through an increment synchronization mechanism; and the data processing module is used for cooperatively managing platform data resources, supporting dynamic expansion and decoupling dependence between the form module and the process module through an event-driven mechanism. According to the method, the strong binding relationship between the decoupling form and the process is established, the reusability of the process module is improved, and the process module is independent of the form and can independently provide API service to the outside, so that the method is adaptive to more business scenes.

The invention discloses an intelligent furniture design system based on AI big data, and relates to the technical field of artificial intelligence, and the system comprises a data collection module which is used for collecting user behavior data, environment data and market data; the data processing module is used for carrying out cleaning, feature extraction and fusion on the collected data to generate structured design input parameters, and the structured design input parameters comprise user preference vectors and spatial constraint parameters; according to the intelligent furniture design system, accurate analysis of design requirements is achieved by comprehensively collecting user behaviors, environment and market data, the problem that design requirement analysis is incomplete due to the fact that a traditional data collection means is single is solved, the system adopts an advanced data processing technology, and the design requirement analysis accuracy is improved. Valuable design input parameters are effectively extracted and fused, a solid foundation is provided for personalized design, and a design generation and optimization module based on a deep learning model can automatically generate and optimize a furniture design scheme.

The invention relates to the technical field of big data artificial intelligence, and discloses a beam field intelligent mix proportion design method which comprises the following steps: S1, collecting historical production mix proportion data of various raw materials and concrete used in a beam field, transmitting the historical production mix proportion data to an intelligent mix proportion design system in real time, and establishing a raw material and concrete mix proportion database; s2, according to a bridge design drawing, inputting structural design requirements of a beam body into an intelligent mix proportion design system, and preliminarily determining a design target of a concrete mix proportion through system analysis; s3, performing optimization calculation on the concrete mix proportion through an intelligent algorithm; and S4, performing laboratory trial mixing by utilizing the optimized mix proportion, manufacturing a concrete test piece and testing the performance, performing comparative analysis on a test result and a design target by the intelligent mix proportion design system, and automatically adjusting mix proportion parameters until an optimal production mix proportion is output. Through intelligent mix proportion design, the dosage and proportion of the raw materials can be more accurately controlled.

A system for a visual design system (VDS) includes storing at least one layout and an associated layout signature where the associated layout signature represents a hierarchical composition of the semantic types of the components; a unit to analyze components of an existing layout provided by a user of the VDS, to determine a component set signature, to compare it with at least one stored associated layout signature and to find a set of candidate layouts which are visually diverse and semantically similar to the existing layout; where the unit presents the set of candidate layouts to the user, updates the existing layout according to a user selected layout. It also includes an experiment system to create, run and analyze the results of at least one experiment using at least one of: A / B and multivariate testing on user selected layouts to provide information on user preferred layouts for the VDS.

The invention discloses a polyolefin intelligent performance prediction and reverse design system and method. The system comprises a data acquisition and management module used for acquiring and managing polyolefin production process data, product first characteristic data and product second characteristic data; the intelligent performance prediction module comprises a mechanism model module and a data driving model module; the mechanism model module is used for predicting first characteristic data of the product according to the polyolefin production process data; the data driving model module is used for predicting second characteristic data of the product according to the first characteristic data of the product; the reverse design optimization module is used for generating initial polyolefin production process data by utilizing an intelligent optimization algorithm according to a product first characteristic data target value and / or a product second characteristic data target value input by a user and performing iterative optimization in combination with the intelligent performance prediction module; and outputting the optimized polyolefin production process data meeting the target value.

The invention discloses a dynamic simulation modeling method for a compressed air energy storage system based on AMESIM and application, and belongs to the technical field of compressed air energy storage.The method comprises the steps that firstly, system indexes are determined, based on the system indexes, a system technological process diagram is designed, main equipment and auxiliary equipment are selected, and design point parameters of the main equipment and the auxiliary equipment in the energy storage and release stage are determined; then, according to the equipment model selection result, sub-models of all elements in the air circulation loop and the heat storage and exchange loop are selected in the AMESIM; thirdly, calibrating and verifying each main equipment sub-model by utilizing main equipment characteristics and model selection parameters, and building a steady-state simulation model of the compressed air energy storage system; and then, constructing a dynamic simulation model based on the steady-state model, and carrying out dynamic simulation verification and evaluation. According to the method, the co-simulation model integrating thermodynamics, fluid mechanics, control theory and mechanical dynamics can be quickly built, and the method has the advantages of being high in model modeling precision, high in multidisciplinary coupling calculation capacity, high in simulation efficiency and the like.

The invention provides a transformer substation civil engineering digital design system based on a domestic BIM platform, and the system comprises a building design module which is used for constructing a building professional model through employing a building component library; the general drawing design module is used for generating a general drawing professional model based on a parametric modeling technology; the water supply and drainage system digital design module is used for generating a water supply and drainage pipeline design scheme according to the water supply and drainage professional component library and determining a water supply and drainage professional model; the heating and ventilation system digital design module is used for determining the fan equipment model and the air pipe diameter according to the professional building model and determining a professional heating and ventilation model; and the multi-specialty cooperation module is used for carrying out online synchronous modification and real-time updating processing on the building specialty model, the general drawing specialty model, the water supply and drainage specialty model and the heating and ventilation specialty model. According to the method, building, general drawing, water supply and drainage and heating and ventilation multi-specialty collaborative design is achieved based on domestic BIM platform construction and through the parameterized modeling technology, and the design efficiency and the achievement standardization are improved.

The invention provides a power transmission and transformation project full-life-cycle carbon emission design system based on multi-objective optimization, and the system comprises a full-life-cycle carbon emission database module which is used for storing carbon emission factors and technological parameters of a power transmission and transformation project in each stage; the engineering scheme modeling module is used for generating an engineering scheme including a standardized bill of materials and a construction list based on the carbon emission factors and the process parameters in combination with engineering parameters and design data; the carbon emission evaluation module is used for evaluating the full-life-cycle carbon emission of the engineering scheme; the multi-objective optimization module is used for realizing synchronous optimization of the carbon emission and various constraint conditions to obtain a plurality of engineering scheme solution sets; and the decision support and visualization module is used for visually displaying the target optimization solution set and the carbon emission of the whole life cycle, automatically generating an engineering scheme for comparative analysis, and assisting a decision maker to quickly select an optimal scheme. And through a multi-objective collaborative optimization method, synchronous optimization of full-life-cycle carbon emission and economic objectives is realized.

The invention relates to a concrete mix proportion design system based on industrial control, which belongs to the field of industrial process control, and comprises a central controller for online control of a concrete production process, and the controller integrates the following functional modules: a distributed data acquisition module, a dynamic decision module, a data processing module and a data processing module. The prediction module is used for generating a rheological parameter prediction value based on the raw material characteristic data and the environment parameter data; the closed-loop verification module is used for monitoring actual rheological property parameters in the concrete production process and comparing the actual rheological property parameters with a preset target value to generate performance error indexes; and the grading correction execution module is used for adjusting proportioning parameters and starting a compensation device, and updating the self-learning database based on a correction result so as to optimize the prediction model. According to the method, a closed loop from raw material and environment perception to proportion dynamic adjustment is realized, the concrete rheological property is locked in a target interval, and autonomous decision and accurate control of the whole production process are realized.

The invention provides a device design system and a device design method, and relates to the technical field of device design, and the system comprises an obtaining module which is used for obtaining a plurality of pieces of design data related to a plurality of process sections, data processing algorithms corresponding to the plurality of pieces of design data, and an association relationship among the plurality of pieces of design data, the design data is used for indicating hardware parameters and / or process parameters of the device; the processing module is used for determining a plurality of stage design results according to the plurality of design data, the data processing algorithms corresponding to the plurality of design data and the incidence relation among the plurality of design data, the plurality of stage design results correspond to the plurality of process sections, and the plurality of stage design results serve as the basis for preparing the device; the display module is used for displaying a result interface, and the result interface comprises a plurality of stage design results. Based on the scheme, the efficiency and accuracy of device design can be improved.

The invention belongs to the field of heat exchange equipment design, particularly relates to a heat exchanger optimization design system based on a genetic algorithm, and aims at solving the problem that heat exchange equipment designed by an existing design system for designing a shell-and-tube heat exchanger is low in performance. The heat exchanger optimization design system based on the genetic algorithm comprises a design index input module and a heat exchanger parameter optimization module. According to the system, seven key design parameters including the tube pass number, the tube outer diameter, the heat exchange tube length, the tube inner flow speed, the shell side flow speed, the tube wall thickness and the heat exchange tube number serve as optimization variables, and a fitness function with the heat transfer coefficient and pressure drop ratio as the target is established. A hybrid coding strategy is introduced to carry out differentiation processing on continuous parameters and integer parameters, an improved genetic algorithm is adopted to realize iterative evolution of a population through intelligent optimization operations such as coding, selection, crossover and variation, and finally, a global optimal parameter combination meeting engineering constraint conditions is converged.