60 results about "Design objective" patented technology

The invention discloses an industrial MBSE model generation and evaluation method based on a large language model, and the method comprises the steps: collecting and sorting an aerodynamic model, assembly design rules and related basic design parameters, and carrying out the formatted expression of the rules applied in MBSE, so as to form a special enhanced knowledge base in the industrial field; the method comprises the following steps: converting a demand described by a natural language of a user into a standard MBSE model code based on a large language model through a cue word engineering technology, selecting an optimization algorithm and a simulation algorithm through a function call technology, performing real-time optimization on the model according to a design target, and applying the generated MBSE model to propulsion device design and verification test. And determining availability and model consistency. Reconstruction and acceleration of digital design are realized through automatic configuration based on requirements and components. The method has remarkable advantages in the aspects of reliability, effectiveness and adaptability.

The invention discloses a large-scale equipment shock resistance optimization design method and device based on multi-objective integration, belongs to the technical field of large-scale equipment shock resistance design and optimization, and particularly relates to a method which comprehensively considers multiple design objectives and carries out optimization design on response of large-scale equipment in a shock environment based on a multi-objective integration method. The problem that an existing impact resistance design method only optimizes a single target and cannot deal with a complex multi-target optimization problem is solved. The method comprises the following steps: scoring the importance of each objective function to form a judgment matrix; calculating the weight of each objective function by using an analytic hierarchy process based on the judgment matrix; and S5, carrying out multi-criterion decision analysis on the optimal solution set by utilizing the weight of the objective function, and selecting an optimal design scheme. The large-scale equipment impact resistance optimization design method and device based on multi-objective integration are suitable for large-scale equipment impact resistance optimization design.

The invention discloses a stepped three-band grating coupler and a reverse optimization method thereof, and belongs to the technical field of photonic devices and integration, and the reverse optimization method comprises the steps: determining a design target of the grating coupler, and defining an initial structure; defining optimization parameters including grating height and grating width according to the grating number; defining an optimization quality factor according to a design target of the grating coupler, and dynamically updating a weight coefficient of the quality factor; optimizing the width and height distribution of all gratings by using an improved direct binary search algorithm; and iterative optimization is continuously carried out until a design target is achieved, and width distribution corresponding to gratings with different heights in the optimized stepped grating structure is obtained. The problem that traditional grating diffraction has inherent wavelength dependence is effectively solved, and efficient coupling of three optical communication wavebands is achieved.

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 provides a design optimization method and device of an MIMO antenna, equipment and a medium, and belongs to the field of antenna design, and the method comprises the steps: obtaining historical design parameters and corresponding performance indexes of the MIMO antenna; preprocessing the historical design parameters and the performance indexes, constructing a mapping relation between the input data and the output data, and training based on the mapping relation to obtain a forward prediction model and a generation model; and receiving target performance index input, generating a candidate design parameter set by utilizing the trained generation model, performing iterative optimization by taking the candidate design parameter set as an initial population and combining a forward prediction model as an agent model and adopting a multi-objective evolutionary algorithm, and outputting a Pareto optimal solution set as a target design parameter set. Therefore, the performance evaluation link is greatly accelerated by means of the agent model, diversified non-inferior solution selection is provided through Pareto frontier analysis, and different design targets can be flexibly balanced according to actual requirements.

Embodiments of the present disclosure provide enhanced systems and methods for predicting optimal design flow parameters for optimized output targets for physical design synthesis of a given IC design. A Variational Autoencoder (VAE) along with a regression network are trained using a dataset comprising synthesis design construction flows from historical IC designs to provide a training data representation of the dataset constrained to a latent space of the VAE. The system generates feature vectors based on the training data representation of the dataset and updates the feature vectors with initial design characteristics of the given IC design. The system iteratively performs an input gradient search of the updated feature vectors to optimize an objective function of the design targets to identify locally optimal design parameters. The system identifies globally optimal design flow parameters for optimized design targets based on locally optimal design parameters.

The invention relates to the technical field of electronic design automation, and discloses an EDA layout and wiring optimization method, which comprises the following steps of: firstly, finishing layout and wiring according to initial layout and wiring data of an electronic design layout, and then dividing a whole layout and wiring area into a plurality of relatively independent sub-areas; according to the method, the layout and wiring characteristic parameters of each sub-region are extracted respectively, the processed parameters are analyzed after the parameters are normalized, and each sub-region is optimized according to an analysis result, so that the calculation amount is reduced, the optimization efficiency is improved, and finally, the performance of the whole layout and wiring is evaluated. Global performance degradation caused by local optimization is avoided through real-time performance feedback, and it is ensured that the final scheme meets the design target.

Embodiments of the present disclosure provide enhanced systems and methods for optimal design process parameters for predicting optimal output objectives for physical design synthesis of a given IC design. A variational automatic encoder (VAE) is trained along with a regression network using a dataset that includes an integrated design build stream from a historical IC design to provide a training data representation of the dataset constrained to a potential space of the VAE. The system generates a feature vector based on the training data representation of the dataset and updates the feature vector with initial design characteristics of the given IC design. The system iteratively performs an input gradient search of the updated feature vectors to optimize an objective function of the design objective to identify locally optimized design parameters. The system identifies global optimization design process parameters for optimization design objectives based on the local optimization design parameters.

A model representing a physical object in a shape optimization according to a design objective, and a control point for altering a shape of the physical object are received. The shape is defined by a set of nodes in the model. Sibling models are generated from the model according to a perturbation scheme. The control point is perturbed with respective perturbed values for the sibling models. Each sibling model contains nodal location changes for the nodes. The nodal location changes are determined based on a respective shape function formulated according to a respective perturbed value at the control point and one or more simulated physical behaviors of the model. The model is updated to have an optimal value for the control point. The optimal value is identified from a relationship according to the design objective. The relationship correlates a physical characteristic of the sibling models to the respective perturbed values.

The present invention discloses a method and system for optimizing the layout of communication relay nodes in a cooperative action system. Based on the quantitative description of the attribute information of the cooperative action system, from the perspective of communication connection in the physical layer and information interaction in the logical layer, decision variables are defined, constraint conditions are analyzed, and an objective function is designed to construct a two-layer communication relay node optimization layout model including the physical layer and the logical layer. According to the hierarchical characteristics of the model, based on the artificial bee colony algorithm with high fitness and fast convergence speed, combined with the non-feasible solution forced conversion mechanism, a hierarchical artificial bee colony system for upper and lower layer iterative games is constructed. Through the iterative solution of the hierarchical artificial bee colony system, an optimized layout scheme of communication relay nodes that meets the quality requirements of communication information services is generated, solving the problems of insufficient quantity, lack of optimality, and low adaptability in the existing field of optimizing the layout modeling of communication relay nodes, and being unable to generate an optimized layout of communication relay nodes with relatively high quality and efficiency well.

The present invention relates to an intelligent design optimization method for a lead-bismuth reactor, which includes: establishing a mathematical model of the lead-bismuth reactor to be optimized with a design space, a design objective function, and constraint conditions, conducting Latin hypercube sampling to generate sample points, calculating core characteristic parameters to construct a training data set, and using the BP neural network algorithm to establish a surrogate model S-LFR that can predict the core characteristic parameters of the lead-bismuth reactor; using the niche genetic algorithm Micro-GA to optimize the combination of design parameters predicted by the surrogate model S-LFR, updating the training data set and the surrogate model S-LFR, and repeatedly iterating to approach the target optimization interval until the global optimal solution is obtained. The present invention realizes the collaborative optimization of multi-objective, multi-physics, and multi-variable coupling of the lead-bismuth reactor core, greatly improves the design efficiency while ensuring the calculation accuracy, can automatically search for the optimization interval according to the design objective, and obtain the optimal design scheme.

The invention discloses a fabricated wall BIM model multi-objective optimization method based on acoustic parameter analysis, and relates to the technical field of building information models. The method comprises the following steps: constructing an acoustic parameter analysis-prediction coupling model based on an auto-encoder and a deep network, and generating a lightweight performance prediction proxy model through a knowledge distillation technology; the performance prediction agent model, a cost calculation module and a weight calculation module are jointly packaged into an acoustic parameter analysis-model optimization plug-in conforming to BIM platform interface specifications; and realizing automatic multi-target optimization of the target fabricated wall in the BIM platform through the plug-in. According to the method, real-time prediction of high-precision acoustic performance and collaborative optimization of a multi-dimensional design target are achieved, interactive target and constraint setting of a user in a BIM environment is supported, the technical problems that in a traditional method, performance analysis efficiency is low, the optimization process is split, and multiple targets are difficult to balance are solved, and the method is suitable for popularization and application. And the scientificity, efficiency and engineering practicability of the assembly type wall body design are improved.

The invention discloses a bridge protection device optimization design method and system and a computer program product, and belongs to the technical field of bridge protection device performance optimization, and the method comprises the following steps: determining design parameters and design targets; designing an initial structure of the protection device; a ship, a protection device and a bridge are respectively simplified into a corresponding ship macroscopic module, a protection device macroscopic module and a bridge macroscopic module, and a ship-protection device-bridge simplified dynamic model is established; calculating the impact force borne by the bridge by using the ship-protection device-bridge simplified dynamic model; judging whether the impact force borne by the bridge meets a design target or not, if not, modifying the structure of the protection device, and if yes, outputting a final parameter combination to complete optimization design. The dynamics calculation process is simplified, parameterization analysis is optimized, calculation time consumption and hardware requirements are reduced, and design efficiency is improved.

The invention relates to a microstrip network layout optimization method based on Fourier series, and belongs to the technical field of radio frequency circuit design. The method aims at solving the problems of topology dependence, boundary discontinuity and low efficiency caused by sharp increase of optimization parameters along with the area in a traditional rectangular spliced microstrip network. The core of the technical scheme is that a microstrip network boundary is modeled into a plane closed curve, the curve is represented through Fourier series decomposition, and a Fourier coefficient is optimized by taking circuit performance as a target drive, so that a microstrip layout with any shape and a continuous and smooth boundary is generated. According to the method, automatic design rule checking and port adding processes are integrated, and finally electromagnetic simulation iteration is carried out until a design target is met. The method can break through the limitation of the traditional topology, effectively improves the electromagnetic performance and design efficiency, and is widely applied to the microstrip network design of broadband matching, multi-band matching, harmonic control and the like.

To provide a system and method for generative design of an energy storage device.SOLUTION: A method automatically builds at least one model of an energy storage device. The building is based on a design parameter space and employs a machine learning process. The method automatically performs a simulation of the energy storage device using the design parameter space, a design evaluation space, and the at least one model built. The performing produces at least one prediction. The method automatically evolves at least one of the design parameter space and the design evaluation space. In an event the at least one prediction indicates that a product design objective or model design objective has been achieved, the method automatically converges on the design parameter space evolved, thereby completing a generative design of the energy storage device and, otherwise, repeats the building, performing, and evolving.SELECTED DRAWING: Figure 1A

The present invention realizes an update support system capable of optimizing a QoS during an update of a system. An update support system according to the present invention comprises: a design unit that designs an updated concrete configuration of a target system providing a service by repeatedly executing, with respect to a service requirement, a concretization procedure in which a plurality of concretization rules defining a method for concretizing an abstract configuration of the target system are referred to, and one or more of the concretization rules corresponding to the abstract configuration are specified and applied to generate one or more abstract configurations or concrete configurations, and generates an operation model of the target system corresponding to the updated concrete configuration; a generation unit that generates a QoS evaluation function for evaluating, when updating the abstract configuration of the target system to the concrete configuration designed by the design unit, a quality of service (QoS) of the configuration of the target system in the middle of the update; and a planning unit that plans, by using the operation model and the QoS evaluation function, an update procedure satisfying a QoS-based criterion.

The invention discloses a training data acquisition method and device applied to electromagnetic device design, a medium and equipment, and relates to the technical field of electromagnetic device design. According to the method, the inverse mapping relation between the electromagnetic response curve and the topological distribution of the frequency selective surface structure is utilized, topological modeling and full-wave simulation are firstly carried out, a topological structure is expressed by utilizing a binary matrix, in iteration of a target function, the topological binary matrix and the electromagnetic response reserved in each iteration are used as a training data set, and the frequency selective surface structure is obtained. According to the method, more useful design information can be reserved, the electromagnetic response and the design target have more similar characteristics, misleading information is less, and the quality of training data in electromagnetic device design is improved.

The present application provides a cross-platform collaborative parametric modeling design method, device and equipment for hyperbolic curtain walls. The method includes determining file parameter information corresponding to the hyperbolic curtain wall according to the parametric modeling software and structural modeling software corresponding to the hyperbolic curtain wall modeling; obtaining the design objective corresponding to the hyperbolic curtain wall to be modeled, and dividing the hyperbolic curtain wall model to be modeled into multiple modules in the parametric modeling software according to the design objective; setting the design parameters corresponding to each module in the parametric modeling software, and the design parameters at least include curvature and size; generating a cross-platform design file in the parametric modeling software according to the file parameter information and the design parameters corresponding to each module; in the structural modeling software, performing detailed design and structural analysis on the hyperbolic curtain wall model corresponding to the cross-platform design file; setting the material corresponding to each module in the structural modeling software according to the analysis result corresponding to the structural analysis and updating the design parameters.

The invention discloses an automatic optimization method based on a CAD model, and relates to the technical field of engineering design automation and computer aided design optimization. The method does not depend on manual predefined parameter dimensions any more, directly takes topology and geometric features of the CATIA model as core input, constructs a complete geometric optimization link through automatic extraction, structure mapping and optimization algorithm cooperative processing, ensures synchronous evolution of geometric features and design targets in the optimization iteration process, and improves the optimization efficiency of the CATIA model. And the optimization efficiency and stability are obviously improved. A reinforcement learning or evolutionary algorithm is built in the system to perform efficient search and multi-round adaptive iteration on geometric feature vectors, and global optimization of a complex structure can be completed without manual intervention. According to the method, automatic model generation of an optimization result is realized through a CATIA API and a macro command interface, and manual geometry reconstruction by an engineer is not needed. CATIA can be written back through one key according to optimized feature information, the closed-loop automatic process of input, optimization and output is achieved, the design period is remarkably shortened, and the iteration response efficiency is improved.

The invention discloses an III type composite material hydrogen storage container liner-composite layer integrated design method based on deep learning. The method comprises the following steps: firstly, determining a design target, design parameters and a value range and constraint conditions thereof according to design requirements, and generating an initial sample data set by adopting Latin hypercube sampling; performance parameters corresponding to all samples are obtained through numerical simulation, and design parameters are input into a Transform model in a structured matrix form for feature extraction and correlation modeling; performing data enhancement by using the trained model to generate an extended sample set; and finally, inputting the samples into a conditional constraint enhanced generative adversarial network, and generating a design scheme which meets various design constraints and achieves optimal balance on various performance indexes through adversarial training. According to the method, all design parameters of the inner container and the composite layer are fully considered, the generated design scheme ensures the optimal balance of the strength performance, the fatigue performance and the material cost of the container, and the design efficiency of similar products is remarkably improved.

The application discloses a micro-architecture design space exploration method based on deep learning, comprising: obtaining target processor micro-architecture parameters, constituting a design space, obtaining performance indicators of different design points in the design space, and dividing key modules based on the design points; creating a directed acyclic graph according to the key modules, constructing a prediction model using a graph attention network to obtain a parameter optimal solution in the directed acyclic graph that meets a design target; splicing the directed acyclic graph into a global graph to obtain interconnection parameters of the key modules, introducing federal learning to train a global prediction model, and predicting and evaluating performance data of the parameter optimal solution based on the global graph; and when the performance evaluation result meets a preset performance standard, outputting target configuration parameters of the target processor under each configuration dimension. The application performs micro-architecture design space exploration in a graph embedding space, provides decision support for chip design, and improves design efficiency and flexibility by taking the idea of coordination between different design stages and design modes.

This invention discloses a design method and apparatus for refractory high-entropy alloys based on a large model, relating to the field of alloy material design technology. The method includes: First, by generating and collecting data, pre-trained surrogate models for thermodynamics (covering phase diagrams, solidification processes, etc.) and mechanical properties are constructed, and calculation models for physical parameters such as valence electron concentration and density are established. Then, these models are integrated into a single ensemble model, and a large language model is introduced as the core of intelligent scheduling. The large model is responsible for parsing the design task, intelligently planning and calling the interfaces of each model based on a knowledge base and rule base. Finally, based on the set design objectives, a multi-objective genetic algorithm is initiated for iterative optimization and adaptive adjustment, efficiently outputting a final alloy design scheme that meets multiple performance requirements. This invention enables intelligent multi-objective design of refractory high-entropy alloys, solving the problem of high dependence on manual intervention.

This invention discloses a design method for a silicon-based mode divider. Based on a silicon-on-insulator (SiI) platform, it defines a bus waveguide, branch waveguides, and a functional region located between the bus and branch waveguides. The number of branch waveguides is n, determined by a linear combination of the input modes and bandwidths of the bus waveguides. The initial structures of the bus waveguides, branch waveguides, and functional regions are defined. Using an FDTD solver, each iteration requires m forward simulations and m adjoint simulations. The gradient field is calculated, and the dielectric constant parameters of the functional region are optimized using the gradient descent method based on the gradient field calculation results, updating the structure. Iteration continues until the design target is reached or further optimization is impossible, at which point it stops. The discrete dielectric constants are binarized, transforming the dielectric constants of the functional regions into a structure defined only by the functional regions. The final structure diagram is output. This invention also discloses a silicon-based mode divider designed using the above method.

This invention provides a base station design device and method for determining the placement of base stations in an environment where terminal usage fluctuates over time, by performing robust base station design with minimal computational effort. [Solution] The method using the station placement design device of the present disclosure involves arranging multiple base station installation candidates within a design target area, calculating the radio quality between each terminal and each base station installation candidate at each time step based on the movement prediction of multiple terminals within the design target area, creating a weighted directed graph for each time step with each terminal as a node, the connection between each terminal and each base station installation candidate as an edge, and each radio quality as the weight of each edge, obtaining a set of graphs, compressing the set of graphs in the time direction to obtain a compressed set of graphs, and selecting the placement location of a base station from multiple base station installation candidates based on the compressed set of graphs such that the sum of the probabilities of the existence of terminals whose radio quality is equal to or greater than the quality target value is equal to or greater than the design target value.

This invention discloses a multi-domain adaptive design rule method based on EMC data assets. It includes: acquiring the target application scenario identifier, functional type, IC combination, and design objectives; retrieving matching typical basic products and their derivative product cases to obtain their feature sets and mapping relationships; constructing an initial design concept by combining IC-level and system-level data assets; retrieving the standard essential characteristics of the target application scenario; constructing an EMC domain adaptation model, establishing an adaptive mapping based on verified mapping relationships, and quantitatively correcting and generating design rule parameters; outputting design rules containing constraint objects, types, target values, source metadata, and protection layer priorities; and structurally storing and assigning multi-dimensional tags. This invention establishes cross-application scenario mappings through typical basic products and derivative products, achieving quantitative adaptive generation of design rules, supporting cross-domain reuse, test prediction, rule self-evolution, and automatic generation of design documents, shifting EMC design from experience-based to data-driven.

The invention belongs to the technical field of circuit design, and discloses a method for impedance matching design based on a large language model, which comprises the following steps of: 1, collecting impedance matching design demand information for preprocessing, and outputting demand data; 2, semantic understanding, field extraction and structured mapping are carried out, a rule verification mechanism is adopted to carry out conversion unit unification, parameter range verification and missing information complementation, and standard structured design task description is generated; 3, judging a matching task type, selecting a corresponding design according to the matching task type, and generating a topological structure and parameters; 4, converting into a netlist file, performing S parameter simulation, analyzing key performance and indexes, judging initial structure performance, and generating a report and storing the report into an RAG knowledge base when a design target is met; 5, if not, parameter optimization is carried out, a report is generated and stored in an RAG knowledge base after optimization succeeds, modification suggestions are generated if the optimization succeeds for many times, and then redesign is carried out. According to the method, the matching structure design efficiency and accuracy of the large language model are improved.

The present invention provides a radar scanning mechanism design method, a terminal, and a storage medium. The method includes: establishing a parameter vector, where the parameter vector includes multiple design parameters of the radar scanning mechanism; obtaining a candidate motor parameter table, which includes motors of multiple models; establishing multiple objective functions according to the multiple design parameters and the motor parameters of each model of motor in the candidate motor parameter table, where the first objective function represents the total weight of the radar scanning mechanism, the second objective function represents the motor torque of the radar scanning mechanism, and the third objective function represents the size of the radar scanning mechanism; performing optimization according to the optimization objectives to determine the values of each design parameter in the parameter vector and determine the model of the target motor in the candidate motor parameter table, where the optimization objectives include minimizing the values of the first objective function and the third objective function and maximizing the value of the second objective function. The present invention can optimize the multiple design objectives of the radar scanning mechanism as a whole.

This invention discloses a passive component selection method based on EMC data assets. It includes: acquiring the application scenario, design objectives, housing structure, and EMC standard requirements of the target product; acquiring port and PCB interconnect information to determine the protection priorities of emission suppression, immunity enhancement, and transient protection; retrieving IC-level and system-level EMC data assets to identify interference source pins and sensitive pins; searching historical design cases to extract successful solution characteristics and failure modes; calculating the required emission suppression, immunity enhancement, transient protection level, housing shielding effectiveness, and common-mode suppression requirements; establishing an inside-out forward design method to determine IC-level, PCB-level, and system-level three-layer protection and dynamically allocate weights; establishing a weighted scoring model, introducing a multi-dimensional labeling system for filter topology, generating and ranking candidate solutions; and integrating selection records into a closed-loop protection selection data asset. This invention achieves quantitative selection of passive components.

The present invention relates to a bolt structure optimization design method, comprising: selecting a bolt connection structure comprising a connecting member and a connected member, and performing reliability analysis on the bolt connection structure to obtain a plurality of reliability analysis results; if there is a result item that does not meet a pre-designed target value in the reliability analysis result, determining that the bolt structure needs to be optimized, and screening and determining at least one key parameter in the bolt structure that affects the result item that does not meet the pre-designed target value; taking the result item that does not meet the pre-designed target value as a response and the key parameter as a factor, and performing a DOE experimental design on each response, comprising: setting a response target value, selecting factors associated with the response, and setting corresponding factor levels; and performing a DOE experiment in combination with all responses, all response target values, all selected factors, and all set factor levels to obtain an optimal solution for each factor when the response is the pre-designed target value.

This invention belongs to the field of flowmeter technology and discloses a method for optimizing the impeller of a turbine flowmeter. The method includes: S1: collecting data on the physical properties, operating range, and performance indicators of the medium through a system to establish clear design constraint data; S2: integrating streamlined and multi-lead design concepts, and determining the blade structural parameters through mathematical modeling and simulation analysis; S3: ensuring precise matching between the processing process and design objectives through parameter modeling, accuracy threshold setting, process coordination, and data linkage; S4: manufacturing an impeller prototype based on the processing technology, and calibrating the blade size and angle parameters using equipment; S5: verifying linearity and starting flow rate indicators through data acquisition and analysis, and iteratively optimizing design and processing parameters; S6: establishing a large-scale batch production process based on the optimized final parameters. This invention solves the problems of large starting flow rate, poor linearity, and insufficient consistency of metering accuracy in turbine flowmeters under low Reynolds number conditions.