112 results about "Design cycle" patented technology

The invention discloses a method and system for determining the optimal stress orientation of a concrete special-shaped sheet column, and relates to the technical field of constructional engineering. According to the method, a correlation model of special-shaped contour parameters and load conditions is constructed, a mechanical property key direction set is extracted, the screening range is narrowed, the optimal orientation determination efficiency is greatly improved, the design period is shortened, and the optimal orientation determination efficiency is improved based on multi-dimensional screening of all-circumferential inertia moment distribution, a rigidity curve and a bending moment contribution ratio. Core indexes such as section ultimate bearing capacity and ductility are comprehensively evaluated by combining stress simulation of a concrete nonlinear constitutive relation; through overall structure collaborative checking calculation and node stress analysis, it is ensured that the orientation meets the mechanical requirements of components and adapts to lateral force resistance and stress continuity of the overall structure, in combination with building construction requirements and node compressive strength redundancy optimization, the scheme of optimal mechanics but construction conflicts is eliminated, safety redundancy is reserved, the structure anti-disaster stability is guaranteed, and the construction safety is improved. And meanwhile, the method adapts to complex working conditions and specification requirements and ensures that the scheme can be directly applied.

The invention relates to a full-parameterization automatic closed-loop pressure pulsation optimization method for a spaceflight high-pressure corrugated pipe. The method comprises the following steps that S1, geometric parameters and optimization instructions of the corrugated pipe are input into a text command interface; s2, the parametric modeling module generates a corrugated pipe geometric model; s3, an automatic simulation analysis module performs grid division and computational fluid dynamics simulation on the generated geometric model, and automatically extracts an index value representing the pressure pulsation intensity from a simulation result; s4, an optimization decision module automatically adjusts the geometric parameters, generated in the step S2, of the corrugated pipe, a new geometric parameter combination is generated with the purpose of minimizing the index value representing the pressure pulsation intensity, the new geometric parameter combination is fed back to a parameterization modeling module for next iteration, and a closed-loop optimization process is formed till a termination condition is met; and S5, outputting the optimal geometric parameter combination by a result output module. According to the method, the operation efficiency is improved, the design period is shortened, and the optimization quality and reliability are fundamentally improved.

The application discloses a kind of based on RAG's few-sample processor design PPA prediction method.The technical scheme is: the processor design paradigm, EDA tool module, RAG module, the input module of processor design to be measured and PPA prediction module are formed based on RAG's few-sample processor design PPA prediction system.RAG module carries out sampling to the design space of processor design paradigm, obtains processor design sample, the feature vector coding of sample, utilizes EDA tool module to obtain the PPA value of design sample, constructs the knowledge base required for PPA prediction;RAG module detects the knowledge matched with the processor design code of the PPA value to be predicted in knowledge base, generates prompt word based on the matched knowledge.PPA prediction module and prompt word interaction, obtain the PPA prediction value of the PPA value processor design to be predicted.The application can be based on a few samples to carry out accurate PPA prediction, shortens design cycle.

The invention provides an optimization design evaluation method for a labyrinth welding drum based on a parameterized model, and belongs to the technical field of aero-engines, and the method comprises the steps: building a drum parameterized mathematical model, and determining a drum stress expression; determining a dangerous part of the drum at the maximum working rotating speed, and determining the section average stress of the dangerous part based on the stress expression; aiming at the welding part, determining the residual strength reserve coefficient of the drum based on the initial defect, and determining the stress reserve coefficient of the welding part; for the maximum stress part, the ratio of the minimum self-sustaining radius of the two wheel discs connected with the drum to the pitch diameter of the drum is obtained; when the ratio does not meet the preset condition, the stress reserve coefficient of the maximum stress part is determined; and carrying out optimization design on the structural parameters of the drum by taking the lightest weight of the drum as an objective function and taking the condition that the residual strength reserve coefficient and the stress reserve coefficient do not exceed the material performance as a constraint condition. A complete evaluation system is established, the design period is shortened, and the evaluation accuracy is improved.

The application discloses an OTR tire pattern heat dissipation hole parameter design and heat dissipation strengthening method, and belongs to the tire structure design field.The method firstly establishes a tire parameterized model containing a heat dissipation hole, determines the length, width, depth and inclination angle of the heat dissipation hole as key design variables; subsequently, sample points are generated in the design space by using Latin hypercube sampling, and the average convective heat transfer coefficient corresponding to each sample is calculated through numerical simulation; then, a radial basis function proxy model with the design variables as input and the heat transfer coefficient as response is constructed, and the accuracy thereof is verified; thereafter, the design variables are globally optimized by using an adaptive simulated annealing algorithm with the maximization of the average convective heat transfer coefficient as the target, and the optimal structure parameters are obtained; finally, the optimization scheme is modeled and numerically verified.The application significantly improves the heat dissipation efficiency of the OTR tire through multi-parameter collaborative optimization, has the advantages of short design cycle, strong optimization ability and good versatility, and is helpful to prolong the tire life.

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

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

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

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

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

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

The invention discloses a self-locking nut elliptical closing tool design method based on contact curvature matching, which comprises a design method for obtaining the radius R of an arc opening of a closing tool on the basis of the arc curvature of a closing table of a self-locking nut. The radius R of the arc opening of the closing-in tool is calculated on the basis of the arc curvature of the closing-in table of the self-locking nut, and the problem that the design period of the closing-in tool is long due to the fact that the closing-in tool is usually determined according to the experience of workers is solved.

The invention relates to the technical field of industrial design, and discloses a lightweight assembly type mobile equipment industrial design generation method based on artificial intelligence, and the method comprises the following steps: S1, constructing and training a dual-stage AI model which comprises a concept generation module and an industrial conversion module; s2, receiving multi-modal design demand information input by a user; s3, generating at least one visual concept design scheme through the concept generation module; and S4, in response to a selection instruction of a user for the visual concept design scheme, the selected concept scheme is converted into an industrial-grade design scheme through the industrial conversion module, and the industrial-grade design scheme comprises at least one of a bill of material, a technical drawing and a manufacturing instruction. Through the two-stage AI model, full-automatic generation from fuzzy text originality to an accurate industrial-grade manufacturing scheme is realized for the first time, the design period is shortened from several weeks to several hours, and the design cost is reduced.

The invention provides a water turbine inlet seating angle design method and system based on an analytical model, and belongs to the technical field of hydraulic machinery design. The method can at least partially solve the technical problems that in the prior art, water turbine blade inlet setting angle design depends on an empirical formula, the calculation precision is low, repeated trial and error are needed, and the design period is long. According to the method, a performance analysis model for the normal outlet working condition of the water turbine is constructed, and the model represents a continuous function mapping relation between a water flow angle and unit parameters, efficiency and geometric parameters under the design working condition; according to the water head, the flow and the rotating speed required by the design, directly calculating a theoretical inlet water flow angle by using an analytical model; and in combination with a preset inlet attack angle correction strategy, determining an initial value of a blade inlet setting angle, and performing closed-loop verification and iterative optimization through fluid simulation. According to the method, the blade inlet setting angle can be quickly and accurately determined, and the hydraulic design efficiency of the turbine runner and the operation performance of the design point are remarkably improved.

The application discloses a kind of circulator insertion loss quadratic response surface optimization methods.The method includes: obtaining the target performance of circulator, and determining the adjustable factor set of circulator according to target performance;Adopt experimental design method in adjustable factor set Significant factor is screened;According to significant factor, a quadratic response surface proxy model is constructed, and the minimum insertion loss is used as the optimization target to train the model;The trained model is used to execute multi-objective optimization with constraints, and the optimal parameter combination is obtained;After verifying the optimal parameter combination, the final design parameters are output.The application filters significant factors and constructs a quadratic response surface proxy model to minimize IL within the constraint space for fast optimization.The total amount of experiments is reduced by 70%, the verification error is less than 5%, the design cycle is significantly shortened, and the insertion loss is reduced, which is suitable for precise determination of low-loss process window for any-band self-biased circulator.

The application discloses a rail transit line design system and method based on scheme management. Through the system and method, a designer can surround rail transit line design, establish a line scheme management mechanism, and perform tag management on technical standards, line design data and interface data of other specialties. When the designer operates a line, a station and other tagged entities, the designer can query the relationship between objects through the scheme management mechanism, use corresponding operation tools and complete various operations. Meanwhile, the system forms a data package with a single scheme as a unit, manages and interacts from the time axis angle around the scheme, and meets the needs of repeated iteration of a scheme in a design process. The system and method not only optimize a line design process and tools, but also provide a solution for data management and iteration of a design scheme. From the whole design cycle angle, the system and method greatly improve the working efficiency and accuracy of rail transit line design.

The application belongs to the technical field of printing, and particularly relates to a printing jig design method based on ultra-thin circuit board printing technology. The application aims to solve the problems that the existing jig design is difficult to adapt to the ultra-thin circuit board, the printing precision and yield are low, the design cycle is long and the like due to the fact that the ultra-thin circuit board is extremely thin and easy to deform and warp. The method comprises the following steps: obtaining geometric and mechanical parameters of the ultra-thin circuit board; establishing an accurate deformation mechanical model of the ultra-thin circuit board under printing composite load; predicting the deformation behavior based on model simulation; optimizing the jig structure layout, support scheme and material selection according to the simulation result; and optimizing the jig design. Through the above technology, the application can effectively prevent the deformation and warping of the ultra-thin circuit board, significantly improve the printing precision and yield, shorten the design cycle, reduce the production cost, and promote large-scale and efficient production.

This invention discloses a diffuser design method based on variable variable gradient, relating to the field of diffuser design. The method includes: establishing a one-dimensional flow analysis model containing mass, momentum, and energy conservation equations; specifying a variable variable gradient objective function along the flow direction, defined as the spatial rate of change of fluid momentum along the flow direction; coupling the objective function with the mass conservation equation, and iteratively solving the closed equation set in conjunction with boundary conditions to obtain the variation law of the diffuser cross-sectional area along the flow direction; generating the profile curve accordingly, and iteratively optimizing it through three-dimensional numerical simulation. This invention directly couples the flow field control objective to the geometric profile design process, realizing active control of boundary layer growth and pressure distribution, effectively suppressing flow separation, improving the pressure recovery coefficient and outlet flow field uniformity, and has a short design cycle and wide applicability.

The invention provides a flexible gripper structure design method based on machine learning, and belongs to the technical field of machine learning. Double frames of a forward prediction model and a reverse design model are constructed through machine learning, and two-way accurate mapping of eight core structure design parameters of the flexible gripper and characteristic curve coordinate points after the gripper is inflated and deformed is achieved. According to the method, the function that corresponding structure optimization parameters can be obtained through the design method when any target curve characteristic parameter is input is achieved. According to the method, a machine learning algorithm is introduced to construct a mapping model of the structural parameters and the grabbing efficiency of the flexible gripper. Intelligent optimization selection of structural parameters is achieved, the design period is shortened, the universality and adaptation efficiency of structural design are improved, the optimization potential of an intelligent algorithm is fully played, indexes of all aspects of the flexible gripper are improved, and the flexible gripper can adapt to multiple scenes.

The invention relates to the technical field of process package generation, in particular to a gear hobbing process package rapid generation method and system, and the method comprises the steps: receiving gear basic parameters inputted by a user; verifying the validity of the basic parameters of the gear; the hob type is matched based on the verified parameters, and the hob diameter is calculated through a piecewise linear formula; the cutting speed range of the material is obtained based on the verified parameters, and core process parameters are calculated in combination with the cutting speed range, the verified parameters, the hob type and the hob diameter; on the basis of the gear basic parameters and the core process parameters, a machining program code is generated according to a preset rule, and a gear hobbing program is obtained; and the core process parameters and the gear hobbing program are displayed on a user interface in a centralized mode, and a numerical control machining program capable of being copied is generated. According to the method, the process design period can be greatly shortened, the machining efficiency is remarkably improved, and parameter consistency and program accuracy are guaranteed.

The invention discloses an automobile front-end structure multi-task optimization design method and system oriented to different material scenes. Due to the fact that automobile front-end structure design under different material scenes has certain similarity, the method considers that the automobile front-end structure design under each material scene is regarded as an optimization task, and a multi-task optimization problem is formed for optimization. The method mainly comprises the following steps: constructing a multi-task optimization model and initializing each task database; identifying an optimization task with high similarity with the current optimization task as a source task; establishing an agent model of each optimization target of the current task and the source task; multi-task evolutionary optimization is executed, and current task optimization is accelerated by migrating source task valuable knowledge; and iterating until a termination condition is met, and outputting an optimal design scheme set under various materials. Compared with a single-task design method, the method provided by the invention can meet the diversified design requirements of users on automobiles, shortens the optimization design period by 50% +, and improves the solution set multi-target comprehensive index by 15% +.

This application discloses a method, system, device, and storage medium for determining the feasibility of parameters, relating to the field of microfluidics. The method includes: acquiring design parameters to be determined, wherein the design parameters include liquid physical properties, nozzle structural parameters, and driving parameters for driving the liquid ejection; calculating state determination values ​​related to the atomization process based on the design parameters; comparing the state determination values ​​with preset state determination thresholds to determine the atomization state corresponding to the design parameters; and determining that the design parameters pass the feasibility judgment when both the atomization state corresponding to the design parameters and the driving parameters in the design parameters meet their respective preset feasibility judgment conditions. This application eliminates the need to fabricate physical samples of the design parameters and verify the atomization effect through actual testing, avoiding the time and resource consumption caused by repeatedly fabricating samples and conducting repeated tests, thereby shortening the design cycle and reducing development costs.

This invention provides a method for generating process routes, an electronic device, and a storage medium, relating to the field of computer-aided design and manufacturing technology. The method for generating process routes includes configuring the product type of the target product and the factory information for manufacturing the target product; obtaining a 3D model of the part to be processed and a preset process database; parsing the 3D model based on geometric topological relationships to obtain feature information of the part to be processed; obtaining processing instructions for the part to be processed in response to received process type instructions; matching and obtaining corresponding process data from the process database based on the feature information and processing instructions; determining an initial process route based on the process data and product type; adjusting the initial process route according to processing constraints and received editing instructions to obtain a transitional process route; and instantiating the transitional process route according to factory information to obtain a deployment process route. This invention shortens the design cycle of process routes.

The application discloses a data-synteny river channel management engineering three-dimensional positive design drawing method, and relates to the technical field of hydraulic engineering.The technical scheme comprises the following steps: S1, constructing an enterprise-level design resource library;S2, constructing a parameterized cross section template system;S3, configuring automatic drawing rules;S4, importing basic data and defining design parameters;S5, axis segmentation, template matching, model generation and review;S6, automatic achievement output;S7, data adjustment or design change.The application changes the generation of plane, vertical section, cross section drawings and engineering quantity report from manual drawing of each drawing to batch automatic output by constructing a parameterized section template library and an automatic drawing environment, and greatly reduces repetitive labor.For long-distance linear engineering, the design cycle is shortened from several weeks to several days, and the project labor cost and time cost are significantly reduced.

The invention discloses a static parameter modeling and optimization design method for a vertical frame type gravity energy storage system. The method comprises the following steps: S1, constructing a'capacity-power-space 'three-dimensional coupling parameter model of the vertical frame type gravity energy storage system; s2, based on the three-dimensional coupling parameter model, determining the minimum height Hmax and other geometric static parameters of the system; s3, constructing a motion parameter model of the system; s4, based on the rated power P of the system and the geometric static parameters; and S5, based on the three-dimensional coupling parameter model and the motion parameter model, developing a parameter derivation engine. Through the parameter coupling model, the design period is shortened from several days to the minute level, meanwhile, the material redundancy is reduced by 10%-15%, and the construction cost is reduced; moreover, the design of a megawatt power station is supported, and the system is suitable for deserts, cities, abandoned pits and other scenes.

The application provides a digital integrated circuit TMR reinforcement decision method based on multi-target parameter optimization. Original data of a designed circuit is acquired, a complex nonlinear relationship between a replacement decision and circuit parameters is accurately captured through a feedforward neural network, network parameters are optimized in combination with a genetic algorithm, the prediction accuracy and convergence speed of the feedforward neural network are significantly improved to obtain four cost functions, minimization of the four cost functions is taken as an optimization target, a multi-target evolutionary algorithm NSGA-II is used to solve the optimization target to obtain a Pareto solution set, the limitation of traditional single-target optimization is overcome, and a Pareto solution with the minimum comprehensive evaluation value is selected from the Pareto solution set to finally determine a final replacement scheme. The application predicts a replacement time-consuming simulation through a cost function, automatically searches an optimal solution in combination with an optimization algorithm, greatly shortens a design cycle, reduces manual intervention, and in addition, an optimization direction can be flexibly adjusted through a weight adjustment mechanism, so that diversified design requirements are met.

The invention provides a design method of a self-locking nut, and belongs to the field of nuts. The design method of the self-locking nut specifically comprises the steps that at least two specific numerical values are set for one of the length of a closing-in area and the pressure reduction amount according to the use requirement, and then the corresponding numerical value of the other one of the length of the closing-in area and the pressure reduction amount is calculated according to the relational expression between the length of the closing-in area and the pressure reduction amount; according to the obtained parameters, a group of trial-manufactured workpieces are machined for testing, finally, the trial-manufactured workpieces meeting the requirements are selected, and the size parameters of the trial-manufactured workpieces serve as final design parameters; the relational expression between the length of the closing-in area and the closing-in amount is shown in the specification. According to the method, the design parameters of the size of the closing-in area of the self-locking nut can be determined only by machining and testing a group of trial-manufactured workpieces, the number of trial and error times can be effectively reduced, the design cost is reduced, and the design period is shortened.

The invention provides a design method for a combined compression system tester for simulating a complete machine environment, and belongs to the technical field of aero-engine tests, and the method comprises the steps: determining the function requirements of a tester for a compression system test; determining key performance indexes of the tester based on the functional requirements of the tester; the structural design of the tester is carried out according to the functional requirements of the tester, and the structural forms of an air inlet system, an exhaust system, a transmission system and a power system in the tester are determined; determining materials and processing technologies of an air inlet system and an exhaust system in the tester according to the key performance indexes of the tester; and optimizing an air inlet system, an exhaust system, a transmission system and a power system in the tester. According to the design method of the combined compression system tester for simulating the whole machine environment, the structural design difficulty of the tester can be reduced, the argumentation and design period of a technical route and a scheme can be shortened, and the design and development efficiency can be improved.

The application discloses a high-end numerical control machine tool basic large piece sand mold casting core bone intelligent manufacturing method, and belongs to the technical field of deep integration of high-end equipment manufacturing and intelligent casting. The method balances the weight and strength of the core bone by constructing a sand core digital model and a multi-physical field constraint system, and adopting an improved genetic algorithm and finite element coupling for topology optimization. The method identifies weak areas based on a U-Net deep learning network, and adaptively enhances the bionic structure or heat dissipation channel. The method realizes accurate production through digital twin technology linkage of a robot welding and an additive manufacturing process. Finally, a full life cycle database is constructed, and a reinforcement learning model is used to realize continuous optimization. The application reduces the weight of the core bone, controls the sand core deformation within 0.1mm, shortens the design cycle, improves the casting qualification rate, and can meet the precision casting requirements of high-end numerical control machine tool basic large pieces, and has significant technical and economic value.