4856 results about "Design methods" patented technology

The invention discloses an optimal design method and system for foundation pit supporting, and aims to improve the design efficiency and safety of a supporting structure, collect on-site landform and soil physical and mechanical parameters, evaluate the influence of foundation pit excavation on the surrounding environment, analyze geological disaster risks, formulate preventive measures and select a proper supporting structure type. Finite element analysis software is used for simulating the performance of different supporting schemes, monitoring equipment is installed to monitor the state of a foundation pit in real time, a machine learning algorithm is used for establishing a prediction model, a design scheme is adjusted according to monitoring data, the final performance of a supporting system is evaluated, abnormal conditions are recorded, and the design process and the construction method are continuously improved according to project feedback. According to the method, a data acquisition and processing module, a design decision support module, a numerical simulation and optimization module, a monitoring and feedback control module, a construction management module and a later evaluation and feedback module are integrated, a closed-loop optimization design system is formed, key problems in support design are solved, and engineering efficiency and safety are remarkably improved.

The invention is suitable for the technical field of industrial design, and provides a multi-agent cooperative industrial design method and system for complex engineering, and the method comprises the following steps: constructing a large model agent set for a complex engineering design task; dividing a design task into sub-tasks which can be executed by an intelligent agent based on a task decomposition algorithm of a knowledge graph and an intention recognition mechanism; a Prompt-to-Code enhancement model is constructed, and task planning targets and constraints of multiple agents are converted into CAD modeling or CAE simulation design instructions capable of being directly executed by an industrial design tool through Prompt embedding; constructing a design version evolution tree, and designing a causal reasoning graph structure based on the interactive influence of target features; and inputting an asynchronous task planning strategy, a design instruction and a version evolution tree feedback result into a large model agent for iterative adaptive optimization. And the design efficiency and the scheme quality of a complex engineering design task can be obviously improved.

Disclosed in the present invention is a vane pump transient process performance optimization design method, comprising: respectively creating an initial design model of a vane pump, an initial design model of an impeller, and a vane pump starting process full-flow-field simulation model, selecting impeller structure parameters as design variables, and on the basis of the initial design models and the vane pump starting process full-flow-field simulation model, performing starting process transient numerical calculation by using CFD simulation software, wherein starting process transient external characteristics comprise a transient lift and transient efficiency; performing data processing on the starting process transient lift and transient efficiency to respectively obtain a weighted average lift and weighted average efficiency; taking the design variables as input parameters, and taking the weighted average lift and the weighted average efficiency as response values; establishing a transient process performance optimization model on the basis of a response surface function; and optimizing vane pump transient process performance by using the established transient process performance optimization model. The vane pump transient process performance optimization design method of the present invention can ensure the calculation accuracy, accelerate the optimization process and shorten the optimization time.

The invention belongs to the technical field of automobile structure design, and particularly relates to a small sample multi-target integrated optimization design method and system for an automobile body structure, and the method comprises the steps: building an automobile body structure parameterized model, defining design variables, and obtaining a design variable combination; obtaining vehicle body structure performance data by utilizing finite element simulation, and constructing an integrated learning agent model; vehicle body structure design variables are optimized through a multi-objective optimization algorithm, and a Pareto leading edge and a solution set are obtained; and circularly adding a proxy model training data set, and iterating the whole optimization process to a termination condition. The technical problems that in the prior art, simulation calculation is long in time consumption, a single machine learning model is insufficient in prediction precision, and the multi-objective optimization effect is not ideal are solved, and the small sample integration optimization design method of the multi-objective optimization algorithm including the adaptive integration model and the fusion multi-strategy is constructed. And the multi-objective optimization efficiency of the vehicle body structure can be effectively improved.

The invention relates to the technical field of building design and digitization, and discloses an automatic design method for a special-shaped facing structure based on parametric modeling. The method comprises the following steps: firstly, acquiring a geometrical characteristic parameter set of the special-shaped facing structure, wherein the geometrical characteristic parameter set comprises curved surface curvature distribution, boundary constraint conditions and a material attribute threshold value; thirdly, according to the curved surface curvature distribution, generating an initial geometric topological grid by using a dynamic subdivision algorithm, adjusting node positions according to boundary constraint conditions to obtain an optimized structural framework, and performing layered mapping on material attribute thresholds to generate a material distribution map; then, the input parametric modeling engine generates a three-dimensional parametric model, finally, a self-adaptive adjustment strategy graph is constructed through a multi-objective optimization algorithm, and a final design scheme is output. By means of the method, automation of design of the special-shaped facing structure is achieved, design efficiency and accuracy are improved, material utilization is optimized, scheme adaptability is enhanced, and design process collaboration is improved.

The invention provides a hydraulic engineering three-dimensional design method, system and equipment and a storage medium, and relates to the field of three-dimensional design. The method comprises the steps of obtaining topographic data, hydrological data and engineering design requirements of an area where a project is located; performing feature extraction on the topographic data and the hydrological data to obtain key feature parameters; determining design constraint conditions according to engineering design requirements, and establishing a three-dimensional design optimization model based on the key feature parameters as design variables and the design constraint conditions; solving the three-dimensional design optimization model through a genetic algorithm to obtain a group of non-inferior solutions as a first candidate design scheme; optimizing the first candidate design scheme through a preset reinforcement learning model to obtain a second candidate design scheme; and performing simulation analysis based on the second candidate design scheme to obtain feedback information, and optimizing the second candidate design scheme based on the feedback information to obtain a target design scheme. Through the scheme, the hydraulic engineering design efficiency and the optimization degree of the design scheme are improved.

The invention discloses a thin-wall structure lightweight design method based on additive manufacturing, and belongs to the technical field of additive manufacturing, and the thin-wall structure lightweight design method comprises the following steps: S100, designing an initial structure based on function and performance mapping; s200, an additive manufacturing process knowledge base is constructed, and the adaptability of the additive manufacturing process is evaluated; s300, carrying out process and structure bidirectional coupling finite element analysis; s400, collaborative optimization of a process and a structure driven by a multi-objective optimization algorithm; s500, feature part manufacturing verification and design and process scheme iterative optimization are carried out; and S600, generating a design and process integrated scheme, wherein the integrated scheme comprises design parameters and manufacturing parameters. The technical problem that in the prior art, the structure optimization target and the manufacturing adaptive capacity are lack of collaboration can be solved.

The invention provides a whole-process engineering consultation management design method, which comprises the following steps of: constructing a unified data exchange standard and protocol, converting heterogeneous data output by design tools of different professions and different units into a standardized data format, realizing seamless joint and real-time sharing of data through data middleware, eliminating data barriers, and improving the data exchange efficiency. The collaborative design efficiency is improved; according to the method, digital technologies such as BIM are adopted, a digital twin model of an engineering project is constructed in a design stage, a design scheme is deepened through virtual construction simulation and optimization, factors such as a construction process, construction procedures and resource allocation are fully considered, and the construction feasibility and economic rationality of design are improved; a collaborative mechanism of a design stage and a construction stage is established, experienced construction managers and technicians are invited to participate in design review, improvement suggestions and suggestions are provided from the construction perspective for a design scheme, a designer is helped to comprehensively understand construction requirements, and the design scheme is optimized.

The invention relates to the technical field of structure optimization design, and particularly discloses a box-type beam structure lightweight design method based on topological optimization, which comprises the following steps: constructing a multi-physics field coupled three-dimensional parameterized model, and performing cross-scale analysis on integrated structure rigidity, thermal deformation, vibration mode and fatigue life to obtain a three-dimensional parameterized model; a variable density method and level set method mixed topological optimization strategy is adopted, and an initial material distribution scheme meeting the structural function integrity is generated by modeling the relationship between density and stress strain; starting a quantum genetic algorithm and deep reinforcement learning fused intelligent optimization engine; according to the method, through the multi-physics field coupled three-dimensional parameterized model, a variable density method and level set method mixed topological optimization strategy is combined, the relation between the structural lightweight target and the additive manufacturing process is effectively balanced, multi-physics field analysis of thermal response, vibration, fatigue and the like is introduced, and the structural lightweight target is obtained. And it is guaranteed that the box-type beam meets the mechanical property and other functional requirements in actual application.

The invention provides an intelligent product service system concept design method based on cue word engineering. The method comprises the following steps: constructing a knowledge base, including data collection, integration and knowledge graph construction; then, a cue word project is constructed, a reasoning mode is determined, and an optimization cue template is created; and then, gradually designing from a demand layer to a physical layer, enabling LLMs in each layer to play different roles for cooperation, realizing demand collection, arrangement and conversion, function determination and decomposition, behavior and logic architecture construction, physical architecture determination and related detection analysis and the like, integrating various technologies to improve the design quality and efficiency, and meeting the market demand.

The invention relates to the technical field of garment processes, in particular to a garment process modular design method and system based on adjustable parameters. The method comprises the following steps: acquiring a basic process parameter set; defining a process association relationship according to the basic process parameter set to obtain a process association diagram; performing meta-model construction according to the process association diagram to obtain a process meta-model; obtaining a target style parameter set; mapping parameters in the target style parameter set into the process meta-model, and performing process parameter adjustment to obtain an adjusted process parameter set; performing process flow optimization according to the adjusted process parameter set to obtain a parameterized process model; performing process flow analysis on the parameterized process model to obtain a process flow diagram; and performing module boundary division on the process flow diagram to obtain a module boundary. According to the method, the defects of the existing method in the aspects of efficiency and flexibility are overcome, and a more intelligent, efficient and flexible process design system is realized.

The invention belongs to the technical field of material structure optimization, and discloses an enhanced structure design method and system for a three-period minimal curved surface, and the method comprises the steps: modeling a geometric model of the three-period minimal curved surface, and exporting the model; expanding a design domain of the geometric model to obtain a corresponding expanded design space of the three-period minimal curved surface; a design space file is converted into an analysis data structure, a general expression mode is constructed for the three-period minimum curved surface, an equal geometric element stiffness matrix is solved by using a Gaussian integral method and the elastic performance of each point in a design domain and assembled into a global stiffness matrix, and the structural response of the model is solved; constructing a local density distribution function in the Bayesian unit, and assembling all LDDFs to obtain a global density distribution function for presenting structural topology; and constructing a stiffness maximization topological optimization mathematical model for the TPMS, calculating an objective function and analyzing sensitivity, and carrying out iterative updating on design variables in the optimization model based on an optimal criterion method to obtain a reinforced structure configuration.

The invention provides a transformer substation AI aided design method based on LLM and RAG, and the method comprises the steps: carrying out the demand analysis through a large language model LLM, and extracting key information; performing knowledge retrieval by using an RAG technology, wherein the knowledge retrieval comprises transformer substation aided design knowledge base construction, transformer substation aided design knowledge retrieval and knowledge reordering; according to the demand analysis and the knowledge retrieval result, the LLM is utilized to generate a preliminary design scheme of the transformer substation, and the design scheme comprises an electrical main wiring diagram, equipment type selection and layout. By adopting the combination of the LLM, RAG and AI aided design, the comprehensive improvement of the design efficiency, standardization and innovation of the transformer substation can be realized, and the problems of low efficiency, insufficient standardization and lack of innovation in the prior art are solved.

The invention relates to the technical field of mechanical engineering, in particular to a three-dimensional simulation design method and system based on an elevator structure. The method comprises the following steps that an elevator structure drawing is obtained; a three-dimensional elevator assembly is constructed according to the elevator structure drawing; lift car static load simulation is conducted according to the three-dimensional elevator assembly, and lift car static load data are obtained; detecting the structural strength of the lift car based on the lift car static load data; evaluating welding defects based on the structural strength of the lift car, and generating welding defect data; identifying a weld weak area according to the welding defect data; determining the abrasion loss of the car structure based on the weld weak area; according to the lift car structure abrasion loss, the lift car bottom plate fracture risk is predicted; carrying out welding optimization design based on the fracture risk of the bottom plate of the lift car to obtain welding optimization design data; and traction and traction simulation is conducted according to the three-dimensional elevator assembly, and traction and traction data are obtained. Based on the mechanical engineering technology, the safety and stability of the elevator structure are improved, and the design precision and efficiency are remarkably improved.

The invention relates to a spinel multi-objective reverse design method based on machine learning and a Bayesian optimization algorithm, electronic equipment and a storage medium, and the design method comprises the steps: firstly extracting related data of a spinel material from a database, and constructing a balanced data set through preprocessing; feature engineering is carried out, a comprehensive feature set is constructed, and key features are reserved; then training a multi-target prediction model through hyper-parameter optimization by using a multi-task gradient elevator model; and finally, integrating to a Bayesian reverse design framework, expanding a design space through a specific encoder, and combining a Gaussian process proxy function and an expected hyper-volume improvement criterion to screen candidate materials meeting conditions and verify performance, thereby completing reverse design optimization. Compared with the prior art, the intelligent and efficient spinel novel multi-target reverse design method can be used for solving the problem of data scarcity, and development of high-performance spinel solar cell materials is accelerated.

The invention relates to the technical field of aero-engines, and discloses an automatic design method for aero-engine turbine blades, which analyzes design requirements through a language large model, combines a retrieval enhancement technology and a turbine blade expert knowledge base, performs interdisciplinary coupling verification by utilizing a step-by-step reasoning template, and generates and optimizes part design schemes and parameters. And then calling parametric modeling and an AI simulation agent model to carry out multi-physics field prediction, comparing a result with a requirement, if the result meets the requirement, outputting design, otherwise, automatically iterating and adjusting parameters until the parameters reach the standard or reach the maximum number of iterations. According to the method, end-to-end intelligent closed-loop design from design requirements to design results can be realized, manual intervention is reduced, a design scheme meeting performance requirements can be quickly generated, the design efficiency can be improved, the design cost can be reduced, and the design quality can be improved.

The invention discloses a hydraulic engineering digital design method based on digital twinning, and relates to the technical field of hydraulic engineering design. According to the digital twin-based hydraulic engineering digital design method, design demand information of a to-be-designed diversion tunnel is obtained and input into a pre-trained building recognition model for comprehensive analysis, a spatial layout map of the to-be-designed diversion tunnel is obtained, and a tunnel design digital twin model is constructed; simulation data of the tunnel design digital twinborn model are obtained, simulation analysis is carried out respectively, a tunnel construction risk index and a hydraulic action risk comprehensive index of the tunnel design digital twinborn model are obtained, comprehensive analysis is carried out, and a tunnel feasibility index of the tunnel design digital twinborn model is obtained; according to the method, the tunnel design digital twin model is subjected to design optimization based on the feasibility index, so that a lagging mode of re-evaluation after building is effectively avoided, later frequent reinforcement and reworking are prevented, and the engineering safety coefficient is improved.

The invention relates to an optimization method for improving a whale algorithm based on chaos multi-strategy fusion, and belongs to the technical field of mechanical engineering. The method comprises the following steps: firstly, constructing a tension / compression spring design problem model, secondly, fusing multiple improvement strategies to improve a whale optimization algorithm, then, optimizing a mathematical model by using the improved whale optimization algorithm, and finally, outputting an optimal variable combination and an optimal target value of a tension / compression spring model. According to the whale optimization algorithm, multiple improvement strategies are fused, the initial population quality and population diversity of the whale optimization algorithm are improved, the convergence speed and exploration capacity are improved, the situation that a stretching / compression spring design method is caught in local optimum is avoided, and the algorithm has better optimization accuracy when solving the stretching / compression spring design problem.

The invention provides a lightweight potential diffusion model design method and system based on evolutionary neural architecture search, and the method employs a super-network technology to train a plurality of network architectures at the same time, combines an evolutionary genetic algorithm in an architecture search process, and trains a multi-layer perceptron as a score predictor, so as to improve the performance of the model. According to the method, the optimal architecture is efficiently screened out in a large-scale search space through the assisted evolution genetic algorithm, and the resource consumption and the calculation cost needed in the traditional architecture design process are remarkably reduced. According to the method, the pre-trained teacher model is introduced in combination with the knowledge distillation technology to supervise the training of the student model, and the potential diffusion model can be lightened while the stable performance of the potential diffusion model is ensured. Through the method, an efficient neural network architecture can be automatically designed, efficient deployment of the potential diffusion model can be realized, and a brand-new and low-cost solution is provided for optimization of the diffusion model.

The invention discloses a design method and system for a wind turbine blade, and belongs to the field of wind power generation. Adopting a Latin hypercube design method to generate initial sample points of a design scheme in a design space of the wind turbine blade model; according to the initial sample points, constructing a Kriging agent model; an improved multi-target mantis algorithm is adopted to carry out iterative solution on the Kriging proxy model, and a Pareto leading edge solution set is obtained; and selecting an optimal solution as a design scheme of the wind turbine blade from the Pareto leading edge solution set according to constraint conditions of the wind turbine blade. Aiming at low wind turbine blade design optimization efficiency in the prior art, a wind turbine blade mathematical optimization model is constructed, then a Kriging proxy model is constructed according to sampling points, hyper-parameters of the Kriging proxy model are optimized, and on this basis, an improved multi-target mantis optimization algorithm and a multi-dimensional point adding strategy are introduced to carry out adaptive updating optimization solution and the like on the proxy model. And the optimization efficiency is improved.

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.

Disclosed in the present invention is a design method for a low-code-based coal mining industrial Internet of Things development platform. The method comprises: constructing a low-code component toolkit; constructing a technical system of a low-code-based coal mining industrial Internet of Things development platform; and constructing an architecture of the coal mining industrial Internet of Things development platform. The present invention can be suitable for situations with high service scene complexity, and a delivery application can be rapidly developed by defining a relationship between data and a service processing logic and constructing a human-machine interface (HMI) by means of a visual modeling technique, so as to conveniently and flexibly realize data fusion.

The invention relates to the technical field of plate shell structures, in particular to a plate shell curve reinforced structure design method and a plate shell curve reinforced structure. According to the method, based on given design parameters, an implicit curved surface and a cross section of the curve reinforced structure are selected, then section parameters of the curve reinforced structure are optimized through layout optimization of the curve reinforced structure and establishment of an agent model, and finally the optimal curve reinforced structure design is obtained. The implicit curved surface in the method can be given by any general curved surface form, and has great degree of freedom. The application agent model is high in calculation efficiency and can explicitly process constraints, and the calculation amount is reduced. According to the design method, the E-AMS method is combined, high-precision reduction of the implicit curve can be achieved while explicit is achieved, and accurate modeling of the curve reinforcement structure is achieved. The plate shell curve reinforced structure provided by the invention is obtained by adopting the plate shell curve reinforced structure design method, the design cost is lower, the efficiency is higher, and the structure has better anti-buckling bearing capacity and bearing characteristic.

The invention relates to an aircraft concept scheme design method and system based on generative artificial intelligence. The method comprises the following steps: selecting a large language model as a system basic model; constructing an aircraft collaborative design cloud platform; driving the large language model to generate a design scheme in a local calling mode, wherein the design scheme comprises model type selection and cue word selection; weight, pneumatic, performance and modeling professional analysis tools are packaged into a capability unit of a design system, and related modeling, evaluation and verification links comprise appearance, power, pneumatic, weight, RCS and flight performance parts and are deployed and operated in a distributed mode. On the basis of a design project in a collaborative design cloud platform, an aircraft CATIA model, overall parameters, aerodynamic parameters, weight parameters and performance data formed by a design scheme are extracted, and elements therein are displayed. According to the system, the aircraft design efficiency is remarkably improved, and the design cost is reduced.

The invention discloses a building facade optimization method and system based on sustainable analysis, and relates to the technical field of data processing. According to the method, parametric modeling is carried out on the external facade of a target building, and a design space is defined; training a machine learning model integrating energy consumption, carbon emission, cost and lighting prediction functions by using historical data; building an optimization problem by taking external facade parameters as decision variables and taking minimization of energy consumption, carbon emission and cost and maximization of lighting as targets, and automatically generating an optimal scheme set by adopting a multi-target optimization algorithm; a decision maker is assisted to select a final scheme through a visual interface, and a corresponding BIM model is output; the method effectively solves the problems that a traditional design method is difficult to coordinate multi-target conflicts, depends on experience and is low in efficiency, and can automatically and intelligently generate an optimal design scheme which is energy-saving, low-carbon, low-cost and good in lighting performance.

The invention discloses a lightweight design method for a thin-wall structure containing a flow channel based on additive manufacturing, and belongs to the technical field of additive manufacturing, and the lightweight design method comprises the following steps: S100, analyzing functional requirements, and constructing a functional requirement model containing the flow channel; s200, a printing direction and additive manufacturing constraint conditions are set, topological optimization is executed on the function demand model, and a preliminary topological structure is obtained; s300, carrying out geometric reconstruction on a topological optimization result to obtain a three-dimensional model suitable for additive manufacturing; s400, carrying out parameter optimization design; s500, the section shape and size of the runner are optimized based on fluid performance requirements; and S600, additive manufacturing manufacturability inspection is conducted on the structure with the section shape and size optimized. And S700, the model obtained after additive manufacturing manufacturability optimization is analyzed and checked. The technical problems that in the prior art, the design requirement of a thin-wall structure containing a runner cannot be met, and the forming quality and the section shape of the inner surface of the runner are difficult to accurately control can be solved.

The invention provides a computer-aided slide-resistant pile and anchor cable build-in depth design method, and relates to the technical field of slide-resistant pile and anchor cable design, and the method comprises the following steps: collecting drilling data of an engineering site, and establishing a three-dimensional geologic model containing spatial distribution of each soil layer; determining a feasible range of design parameters; according to the soil layer space distribution and parameters, a slope stability analysis model considering the supporting effect of the slide-resistant piles and the anchor cables is established and used for calculating the slope stability safety coefficient under the given design parameters; and taking the minimum construction cost as a target function, determining an optimization constraint condition according to the slope stability analysis model, carrying out iterative optimization on the design parameters in a feasible range by adopting an optimization algorithm until an optimization convergence condition is met, and outputting an optimal design parameter. The problems that a traditional design method excessively depends on experience, multiple influence factors are difficult to consider, and the calculation efficiency is low can be solved, and the design level of the built-in depth of the slide-resistant pile and the anchor cable is improved.

The invention discloses an inclined shaft formwork design method based on digital modeling and sliding mode optimization, and the method comprises the steps: drawing a complete three-dimensional digital model of an inclined shaft through employing a geographic information system and a building information model, obtaining the high-precision inclined shaft data through combining with the technologies of laser scanning, an unmanned aerial vehicle and the like, and guaranteeing the accuracy of the model; an included angle between a tangent line and a normal line of each segment is calculated through an inclined shaft curve equation, and a precise geometric basis is provided for optimization design of the formwork based on the divided pouring areas and bin division starting and ending points; the optimal scheme of sliding mode segmentation is calculated by adopting an optimization algorithm, the structural deformation of the template is emphatically optimized, and the rationality of the position, angle and transition part of each segment is ensured; finally, through the accurate three-dimensional inclined shaft model and optimal design, the overall construction formwork is constructed, the precision and stability of inclined shaft formwork design are improved, it is ensured that in the construction process, stress of the formwork is uniform, deformation is minimized, and the construction efficiency and safety are remarkably improved.

The invention relates to the technical field of green low carbon and the technical field of structural design, and discloses a design method and device of a prefabricated composite wall, electronic equipment and a storage medium, and the method comprises the following steps: obtaining mechanical data, construction data and cost data of the prefabricated composite wall; according to the mechanical data and a preset mechanical evaluation model, the flexural capacity of the prefabricated composite wall is generated; according to the construction data and a preset carbon emission evaluation model, the total carbon emission amount of the prefabricated composite wall is generated; according to the cost data and a preset cost evaluation model, the total cost of the prefabricated composite wall is generated; and when the flexural capacity of the prefabricated laminated wall is greater than the flexural capacity demand value, generating a collaborative efficiency coefficient of the design data of the prefabricated laminated wall according to the flexural capacity of the prefabricated laminated wall, the total cost of the prefabricated laminated wall, the total carbon emission amount of the prefabricated laminated wall and a preset collaborative efficiency model. According to the method, the collaborative effect of the prefabricated laminated wall design data can be quantified.

The invention discloses an assembly type composite floor slab cast-in-place section span beam joint design method based on digital twinning, and relates to the technical field of intelligent construction, the method comprises the following steps: adopting a least square optimization algorithm to obtain a material performance correction parameter and a geometric compensation parameter; based on the historical material performance correction parameters and the geometric compensation parameters, training the structure model through a genetic algorithm to generate a digital twin reference model; inputting the material performance correction parameters and the geometric compensation parameters into the digital twin reference model, performing multi-scale finite element analysis, and outputting a multi-scale node performance evaluation report; identifying a multi-scale node performance influence factor and a sensitive area by adopting a response surface method, outputting a design parameter sensitivity analysis result, and converting the multi-scale node performance influence factor into a preliminary node design scheme through a design parameter conversion algorithm; according to the method, the real-time accuracy of node design is remarkably improved through least square dynamic parameter correction.