256 results about "Design space" patented technology

The invention discloses an aircraft aerodynamic performance analysis method, which comprises the following steps: constructing a multi-dimensional parameterized model integrating aerodynamic / structure / thermal control, and outputting a global design space; based on a global design space, fusing sparse fluid dynamics and engineering data to train an agent model, and verifying the cross-speed domain reliability; decoupling the centroid / lift-drag ratio / thermal load conflict by using the proxy model, and generating a speed domain adaptive configuration library; executing fluid-structure-thermal field strong coupling simulation by utilizing a shock wave-boundary layer self-adaptive grid technology aiming at the speed domain self-adaptive configuration library; based on a fluid-structure-thermal field strong coupling mechanism, utilizing a dynamic sensing technology to predict the aerodynamic performance of the aircraft; and integrating dynamic prediction data and digital simulation, calibrating model parameters, and outputting an aerodynamic performance report and an optimization scheme. According to the method, the problems of insufficient multi-physical field integration, low cross-speed domain reliability, poor configuration self-adaption and low coupling simulation precision in aerodynamic performance analysis of a traditional aircraft are solved.

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 wireless power transmission coil optimization method and a related system, which can realize automation of coil structure parameters and multi-target global optimization by acquiring a coil geometric parameter space, constructing a comprehensive optimization function and performing iterative search in the coil geometric parameter space. The problems that in traditional design, the number of simulation iterations is large, design efficiency is low, local optimum is prone to occurring, and multiple performance indexes are difficult to balance are effectively solved, coil design efficiency and precision are remarkably improved, and dependence on artificial experience is reduced. Therefore, the number of manual intervention and simulation is remarkably reduced, the coil design efficiency is improved, and the prototype development period of the WPT system is shortened. Besides, iterative search is carried out in the parameter space, so that the whole design space can be effectively explored, a locally optimal solution trap can be jumped out, and a globally optimal or approximately globally optimal coil structure parameter combination can be obtained more possibly.

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

The invention discloses a small modular prismatic high-temperature gas cooled reactor core optimization design method and system based on data driving. The method comprises the following steps: constructing a training data set; a data-driven agent model is trained to replace and execute high-cost simulation calculation; and exploring a design space and generating a group of Pareto optimal candidate solutions by using a multi-objective evolution algorithm and taking the proxy model as a fitness function evaluator. The key feature of the method is a closed loop of iterative verification and model updating: verifying the candidate solution through high-fidelity simulation, if the prediction precision does not meet the convergence criterion, expanding the verified new data point to a training data set, and retraining the agent model. According to the method, the calculation cost can be remarkably reduced, a complex design space can be efficiently explored, and a physically reliable reactor design scheme with better performance can be obtained.

The invention discloses a bridge splicing part route optimization design method based on a constraint condition genetic algorithm, and relates to the technical field of bridge engineering design, and the method comprises the steps: building a hard constraint and soft constraint double-layer constraint system based on a standardized data set and a parameterized model in a step 2, and associating the system to fitness calculation of chromosomes; and based on a constraint processing result, integrating multi-objective optimization requirements, and constructing a fitness function. According to the method, a route is abstracted into a third-order cubic B-spline curve and parameterized coding is carried out, iteration is carried out in combination with a genetic algorithm, a design space can be globally explored in an optimizable control point range, and compared with traditional experience design, a better global solution can be found, and the problem of local optimum caused by experience limitation of engineers is avoided. The fitness function realizes multi-target quantitative integration through normalized indexes and adjustable weights, the weights of cost, smoothness and environmental influence can be flexibly adjusted according to project scenes, the problems of multi-target qualitative and difficult comparison in traditional design are solved, and the scheme adaptability is remarkably improved.

The invention discloses a front subframe lightweight design method and device based on RMNN, a medium and a program product, and the method comprises the steps: (1) constructing three simulation models of weight, stress and modal of a front subframe, and deducing a lightweight design model containing stress and modal constraints; (2) generating a population based on a uniform experimental design and a correlation criterion, performing simulation evaluation on the population, and constructing a database; (3) constructing a network architecture and training an RMNN; (4) generating a candidate frame set according to a random preferential strategy and the RMNN; and (5) establishing a radial basis function model, screening an optimal frame, performing simulation evaluation, updating the database and the population, returning to the step (3) until the optimization target reaches the standard, and outputting an optimal solution of the optimization parameter. According to the method, the feasible region is quickly searched through the RMNN, the problems that the high-dimensional design space search efficiency is low and the feasible region is difficult to recognize under multiple constraints are further solved in combination with the radial basis function model, and quick optimization can be carried out for the lightweight design of the front subframe.

The invention discloses a variant reconstruction AUV (Autonomous Underwater Vehicle) shape optimization method based on proxy-assisted multi-starting-point space reduction. The variant reconstruction AUV shape optimization method comprises the following steps: establishing a parameterized model of a variant reconstruction AUV; constructing a variant reconstruction AUV shape modeling-grid division-performance simulation automation framework, realizing input of design variables, and automatically performing variant reconstruction AUV shape modeling and watershed grid division; a variant reconstruction AUV shape hydrodynamic force simulation calculation framework is built, and assessment of variant reconstruction AUV hydrodynamic force performance is achieved; generating a plurality of groups of initial samples for a design space of design variables, calculating target function values corresponding to the samples by utilizing the simulation automation framework and the simulation calculation framework, and importing the samples and corresponding sailing resistance into a sample library; and performing optimization in the design space of the design variables by utilizing an agent-assisted multi-starting-point space reduction method to obtain an optimal solution of the variant reconstruction AUV shape design problem. According to the method, the reliability of an optimization result and the design efficiency can be improved, and the optimization time is shortened.

Disclosed are a neuromorphic chip compiling method and compiling system. The compiling method comprises: acquiring a pre-trained model and a data set of a neuromorphic application; generating an initial neuromorphic chip architecture and a network spiking input; performing an optimization and adjustment operation, performing simulation, and evaluating performance; and determining whether an optimization objective is satisfied, and performing loop optimization until an optimal neuromorphic chip architecture is obtained. In the method, by means of iterative optimization and effective evaluation, an optimal neuromorphic chip architecture is efficiently explored in a vast design space, thereby improving design quality and efficiency. The present application further provides a corresponding compiling system, comprising a generator, a simulator, and a compiler, thereby achieving automated compilation and deployment, and providing support for the design of large-scale multi-core neuromorphic chips.

The invention discloses a digital circuit design method and device, equipment and a medium, and relates to the technical field of digital circuits, and the method comprises the steps: determining a target type of a to-be-designed digital circuit, and collecting a first training set corresponding to the target type; each training sample in the first training set comprises an input feature item used for designing a target type of historical digital circuit and the actual result quality of the historical digital circuit, and the input feature item comprises a high-level language source code and an HLS constraint parameter; constructing an initial prediction model based on the multi-layer perceptron mixed structure, training the initial prediction model by using the first training set, and searching and optimizing the model architecture based on the network structure to obtain a target prediction model; and predicting the actual result quality corresponding to each parameter combination in a target design space of a to-be-designed digital circuit by using the model, and designing the digital circuit by using the parameter combination of which the quality meets the Pareto frontier. And predicting an accurate actual quality result by utilizing a prediction model without intermediate representation so as to carry out digital circuit design.

The invention discloses an accelerator architecture design method and electronic equipment, relates to the technical field of computers, and performs dynamic fractal space coding on a design parameter matrix of an accelerator to obtain an analog coding vector. And performing meta-learning dynamic weight entropy search on the analog coding vector by using a historical task data set to determine a new design scheme. And when the difference between the sensitivity parameters in the new design scheme and the sensitivity parameters in the neighbor set meets a difference condition, performing multi-objective optimization simulation on the new design scheme. And when the difference does not meet the difference condition, multiplexing the simulation result of the neighbor set. And performing iterative search according to Bayesian optimization, and determining a final accelerator architecture design scheme in the selected design scheme and the simulation result thereof. Dimension reduction is performed on a high-dimensional discrete space, and a search direction is guided by means of an efficient meta-learning dynamic weight entropy acquisition function. And rapid exploration of an accelerator architecture design space under multi-objective optimization is realized.

According to the technical scheme, the large-scale logic optimization multiplier verification method is characterized in that a four-stage pipeline processing mode is adopted, the first stage is a partial adder tree recovery stage, and the second stage is a partial adder tree recovery stage; the second stage is an architecture generation stage; the third stage is a function verification stage; and the fourth stage is an equivalence checking stage. The verification capability is improved in a breakthrough manner and is far better than that of an existing method; the innovative three-stage decomposition strategy significantly reduces the calculation complexity, the ILP algorithm optimizes resource allocation, the multi-stage scheduling balances the calculation load, and the QACO algorithm efficiently explores the design space, so that the RefSCAT-2.0 framework provided by the invention becomes the most effective solution for verifying a large-scale logic optimization multiplier at present. From the perspective of practice, the technical blank of large-scale logic optimization multiplier verification is filled up, and important tool support is provided for reliability guarantee of key computing systems such as artificial intelligence chips, high-performance CPUs and GPUs.

The invention relates to the technical field of electric power engineering, in particular to an electric power construction acceptance method and system based on an image processing technology, and the method comprises the steps: receiving an electric power construction drawing, recognizing an electric power equipment mark and an association mark through a deep neural network, and generating a design parameter set; a multi-view depth image of a construction site is collected, point cloud data and topology rules are fused to construct a live-action three-dimensional model, and an actual measurement parameter set is extracted; carrying out space coordinate system alignment on the design space coordinates and the actually measured space coordinates, calculating size and angle deviations and forming a comprehensive deviation data set; and performing compliance judgment according to a safety threshold value of the power equipment, marking a standard exceeding position, generating a deviation thermodynamic diagram, generating a dynamic rectification scheme in combination with a historical acceptance database and construction environment information, and finally outputting a power acceptance report containing the thermodynamic diagram and rectification suggestions. According to the invention, automatic identification and intelligent rectification of the power construction deviation can be realized, and the acceptance efficiency and the quality traceability are improved.

Methods, systems, and apparatus, including medium-encoded computer program products, for computer aided design of physical structures using three-dimensional model synthesis processes. A method includes: obtaining a build angle, a manufacturing direction, a design space, and one or more design criteria for use in a shape synthesis process, the build angle and the manufacturing direction being for an additive manufacturing process; performing the shape synthesis process including applying a build-angle filter to a boundary-based computer-data representation of an intermediate version of the shape of the modeled object during multiple iterations, including removing a portion of material from the intermediate version of the shape in accordance with the build angle and the manufacturing direction to make the intermediate version of the shape self-supporting in a vicinity of the portion of material; and providing the shape of the modeled object for use in manufacturing using the additive manufacturing process.

The invention discloses an organic Rankine cycle optimal configuration search method and device based on PINN and multi-objective optimization, and the method comprises the steps: firstly constructing a thermodynamic model of an organic Rankine cycle system, constructing a training data set and physical constraints based on the thermodynamic model, and then training a PINN pair network through the training data set, thereby obtaining the optimal configuration of the organic Rankine cycle system. Embedding a physical constraint in the loss function; the method comprises the following steps: training a PINN (Plural Index Neural Network), predicting a to-be-predicted design parameter by using the trained PINN to obtain a predicted cycle state parameter, finally calculating a plurality of organic Rankine cycle evaluation indexes according to the predicted cycle state parameter, constructing a target function, and carrying out multi-target optimization search by minimizing the target function to obtain final optimal configuration. According to the method, the calculation efficiency of system performance evaluation is remarkably improved, the optimal performance configuration of the ORC system under various working medium and operation conditions can be efficiently obtained by searching in a wide design space, and unification of optimization efficiency and prediction accuracy is achieved.

The invention discloses a micro-channel heat exchanger topological optimization design method, which comprises the following specific steps of: 1, executing key working condition parameter sampling in a design space, constructing a topological optimization mathematical model, carrying out iterative computation, and establishing a topological optimization database comprising a topological field and corresponding temperature field, flow field and pressure field data; 2, realizing unified order reduction of a topological field and each physical field by adopting intrinsic orthogonal decomposition, and converting a complex high-dimensional structure into low-dimensional modal representation; 3, constructing a multi-task learning neural network, taking the multi-target constraint parameters as input, taking the topological field modal coefficient and each physical field modal coefficient as output, and adopting a PyTorch deep learning framework to train a topological structure generation model; and 4, a model is generated based on the trained topological structure, the high-resolution topological structure can be predicted within second-level time, and the thermal-fluid performance of the high-resolution topological structure can be synchronously fed back. The method has a remarkable calculation speed-up ratio and good engineering mobility, and an efficient solution is provided for micro-channel heat dissipation design of a high-power electronic device and a new energy system.

The invention discloses a truss-like structure cross-scale topological optimization method based on data driving, and belongs to the technical field of structure topological optimization design. The method comprises the following steps: firstly, constructing a truss-like unit cell topological structure database with high bearing efficiency through a self-evolution sampling strategy; then, a topological decoder neural network is constructed, a high-dimensional discrete topological space is mapped into a low-dimensional continuous and differentiable design space, and direct control over a unit cell boundary connection mode is achieved; meanwhile, constructing a unit cell equivalent mechanical performance predictor by utilizing a graph convolutional network to replace time-consuming numerical value homogenization analysis; and finally, integrating the components into a gradient-based multi-material topological optimization framework to realize synchronous concurrent optimization of a macroscopic topological layout and various microcosmic unit cell geometric structures. According to the method, the problems that the design space is discrete, the boundary connection compatibility is difficult to guarantee and the calculation efficiency is low are solved, the optimization precision is guaranteed, and the efficiency of multi-scale topological optimization and the global optimization capability are remarkably improved.

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 discloses an intelligent part assembling method, system and equipment, and relates to the technical field of intelligent part assembling. The method comprises the steps that multi-modal data of multiple to-be-assembled parts is acquired; the multi-modal data comprises texts, CAD drawings and process parameters; the text is a natural language instruction or a design requirement; generating a model based on the multi-modal data of each to-be-assembled part and a two-dimensional part graph, and obtaining a two-dimensional part graph of each to-be-assembled part; the two-dimensional part graph generation model is obtained by training an initial network model by adopting a training set; performing design space optimization and multi-objective optimization on the two-dimensional part drawing of each to-be-assembled part to obtain an optimal three-dimensional part drawing of each to-be-assembled part; preset modeling software is adopted, the multiple to-be-assembled parts are automatically assembled on the basis of a preset assembly instruction and the optimal three-dimensional part drawings of the multiple to-be-assembled parts, and an assembly drawing containing all the parts is obtained. According to the invention, efficient and automatic generation and accurate and intelligent assembly of the part model are realized.

This invention belongs to the field of artificial intelligence hardware architecture design and discloses a method, system, device, and medium for cross-layer optimization of multi-core packaging and optical interconnect clusters for large language model training. The method includes: constructing a design space, including a core hardware architecture layer, an optical interconnect network layer, and a training parallel strategy layer; performing an outer-layer search to search for the architecture parameters of the multi-core modules within the core hardware architecture layer; for each outer-layer search sampling point, performing an inner-layer search to collaboratively optimize the optical interconnect network topology and training parallel strategy within the optical interconnect network layer and the training parallel strategy layer; and outputting the Pareto optimal design point on the training performance and cluster cost plane. The technical solution described in this invention can guide the design of related training clusters, thereby fully leveraging the advantages and potential of core technology and optical interconnect technology in large language model training.

The application discloses a landscape bridge skin parameterization generation method based on computer design plug-ins, relates to the technical field of landscape bridge design, and popularizes the concept of skin from the field of civil buildings to bridge buildings according to the demand of landscape bridge design; the skin design idea and core algorithm suitable for the landscape bridge in different design spaces are obtained from three dimensions of observer vision, design space and design demand; the functions needed in the landscape bridge skin parameterization design are written into an operator by using a Visual Studio platform and a C# language; the skin parameterization auxiliary operator in the scheme stage is written according to the scheme, the plane skin parameterization generation logic is combined, the skin parameterization generation core logic is adjusted and optimized, and the space curved surface skin parameterization generation is carried out; the parameterization generation method can quickly realize the parameterization simulation generation of the bridge skin and has good operability and economy.

The application provides a floor grinding machine gear box guide plate structure parameter optimization design method, which is used for determining the optimal values of three radial clearances between the guide plate and the gear tooth top. Firstly, a parameterized gear box model containing clearance as a variable is constructed, and a gear oil stirring loss theoretical model is established based on the boundary layer theory and the fluid resistance theory; taking the maximum lubrication efficiency as the target and the oil stirring power loss not exceeding the set threshold as the constraint condition, a central composite design method is used to select representative sample points in the design space; through computational fluid dynamics simulation, a moving particle semi-implicit method is used for splash lubrication transient analysis to obtain performance data of each point; based on the simulation data, a high-precision proxy model is constructed; finally, under the condition of meeting the oil stirring power loss constraint condition, the maximum lubrication efficiency is taken as the target for optimization solving to obtain the optimal clearance combination. The method realizes the quantitative design from parameters to performance, and effectively replaces the traditional trial and error method.

This disclosure relates to a Python-based method, system, and medium for optimizing the design of a reflector. The method includes: determining the shape and material of the reflector; using UG software to draw the reflector's reinforcing ribs, support holes, and outer edge frame to complete the design of a parametric template for the reflector's sketch; performing parametric feature curve stretching, solid merging, and solid trimming operations based on the reflector's parametric template to obtain a parametric model of the reflector's back structure; performing parametric modeling of the mirror surface to obtain a parametric model of the mirror surface; obtaining the reflector's settable parameters to form a settable parameter set; and updating the reflector structure by modifying the parameters in the parameter set to optimize the reflector structure design. This disclosure shortens the design iteration cycle, improves design efficiency, reduces the reflector's R&D cost, significantly reduces the probability of model errors or update failures, and facilitates full exploration of the design space, thus improving the reflector's design effectiveness.

The application provides a kind of mixed laminar flow control tail optimization design method of comprehensive multi-condition and multi-constraint, comprising the following steps: according to the optimization target and constraint condition of multiple actual conditions of vertical tail, the optimization mathematical model of vertical tail is established;Design variables are constructed;The design variables include vertical tail geometric parameter design variables and vertical tail suction coefficient design variables;Based on the vertical tail reference configuration, the optimization design space of each design variable is determined;Optimization design is carried out.The application has good multi-condition and multi-constraint processing capability, can consider the balance of friction resistance and pressure difference resistance in optimization design, while ensuring that the stall characteristics of vertical tail do not deteriorate during take-off and landing stage, and the laminar flow range of airfoil does not change abruptly under small side slip state, and can consider various complex engineering constraints, thereby effectively improving the drag reduction effect of mixed laminar flow control tail, and making the design result more in line with actual engineering needs.

The application provides a design method and system of a porous balanced flowmeter with a center hole, and belongs to the field of fluid metering instrument design and numerical simulation. The method parameterizes the geometric configuration of a 1+N type balanced flowmeter, constructs a dimensionless parameter system, generates parameter sample points in a design space satisfying constraints, constructs a CFD simulation model, drives a CFD solver to perform flow field simulation calculation, and obtains a massive simulation data set; collects physical calibration experiment data of a standard flowmeter, compares the simulation data with the simulation data of the same standard, and obtains a correction factor; the correction factor is used to correct the simulation data set to obtain a training data set; a design proxy model is constructed, the optimization target of the design proxy model is set based on specific working conditions, and the optimized design proxy model is optimized to obtain optimal dimensionless parameters. The application improves the rationality of the distribution of the center hole and the peripheral hole, and improves the design rationality and efficiency of the flowmeter.

The utility model discloses an electric leakage test detection loop and a release, and belongs to the technical field of low-voltage electric appliances. The electric leakage test detection loop comprises a first connecting piece and a first torsion spring, wherein the first torsion spring is connected with the first connecting piece; a first breakpoint is formed between the second torsional spring and the first connecting piece, and the second torsional spring can abut against the first connecting piece; the first torsional spring and the second connecting piece are second breakpoints, and the first torsional spring can abut against the second connecting piece; one end, deviating from the first connector, of the second torsion spring is connected with the third connector; one end of the second connecting piece away from the first torsion spring is connected with the circuit board. One end of the third connecting piece away from the second torsion spring is connected with the circuit board. The first torsion spring and the second torsion spring are arranged on the outer side of the release shell, so that the space in the release shell is saved, the purpose of reducing the design space of the electric leakage release is achieved, and the dielectric property of a product is improved. And by arranging the two breakpoints, mistaken touch of an operator is avoided, and high stability and reliability are achieved.

The invention belongs to the technical field of ship intelligent digital optimization design, and particularly relates to a ship global deformation and optimization method, program and equipment considering drainage volume precision control and deformation rationality and a storage medium. The analytical expression of the drainage volume variation about the global deformation parameter is obtained based on the numerical integration and the recursion formula, the reasonable deformation parameter range of the ship body is determined based on the global deformation modification function and the regular design space, the ship body does not need to be actually deformed, the corresponding volume variation can be directly predicted according to the design parameter, and the calculation accuracy is improved. Accurate feedforward control of volume constraint and direct judgment of rationality of the deformed ship are realized. On the basis, rapid optimization of any ship type structure under the constraint of reasonable deformation and accurate volume control is realized in combination with an agent model. According to the method, a traditional'design-verification-adjustment 'experience iteration process is converted into deterministic one-step calculation, and subsequent optimization can be directly carried out in a pre-verified reasonable design space.

A laminate cooling structure performance optimization method adaptive to uncertainty analysis comprises the following steps: firstly, establishing a parameterized finite element model of a flame tube laminate cooling structure, and realizing flow heat exchange mechanism analysis of the laminate cooling structure by adopting a solid-thermal coupling mode; carrying out a DOE experiment by using Latin hypercube sampling LHS, generating a parameter set, importing the parameter set into a parameterized finite element model, obtaining a data set of a training proxy model BP-NN by combining a laminate cooling structure solid-heat coupling heat exchange method, and carrying out uncertainty quantification in a design space of the parameters of the laminate cooling structure by using an MC simulation method; using a Sobol sensitivity analysis method to analyze the uncertainty of the laminate cooling structure; the training agent model is combined with a multi-target particle swarm optimization algorithm to carry out multi-target optimization on the laminate cooling structure parameterization, and a laminate cooling ideal structure is found in the Pareto frontier; according to the method, the calculation cost and time of uncertainty analysis are reduced, and the calculation cost of laminate cooling uncertainty analysis is greatly reduced.

The invention relates to the technical field of aero-engine overall design, and discloses an aero-engine generation design method and system based on fusion implicit empirical reasoning, and the method comprises the steps: generating an initial thermal scheme population at a thermal parameter space sampling boundary, and carrying out the optimization through a multi-objective evolutionary algorithm, decision feature vectors including multi-dimensional physical and engineering attributes such as thermal load, cost and service life are constructed, and a related engineering knowledge base is retrieved in combination with an RAG technology, so that downstream structure design is not blind trial and error any more, but can actively adapt to upstream top layer decisions, and the engineering rationality of a design scheme is greatly improved; besides, standard actions of'positive and negative experience focusing / protocol + multi-target optimization 'are introduced into a performance layer and a structure layer, and invalid spaces are greatly eliminated in the initial stage of design, so that the problem of'dimensionality disaster' in a high-dimensional design space is solved, and the generation efficiency is remarkably improved.

This invention discloses a linear guide rail SOMC design method, equipment, medium, and program product, including: (1) constructing a simulation model and SOMC design model with static stiffness as the target and weight and maximum contact stress as constraints based on the structural characteristics and static load analysis of the linear guide rail; (2) constructing a design space, generating an initial population and establishing a database, and obtaining a set of high-influence continuous variables and a set of high-influence discrete variables through SRC and CEA sensitivity analysis methods; (3) generating corresponding candidate sets based on the two sets of variables, and obtaining a complete set of candidate guide rails through individual pairing; (4) establishing a random forest prediction model, screening excellent subsets and selecting the best offspring guide rails; (5) updating the database and prediction model after simulation evaluation, returning to step (3) until the indicators meet the standards, and outputting the optimal parameter values. This invention can effectively balance the SOMC process with stiffness as the optimization target and weight and maximum contact stress as constraints, achieving higher accuracy and better overall performance.