33 results about "Iterative design" patented technology

Digital model platform that enables the streamlined creation and management of digital twins and physical twins by leveraging external feedback and artificial intelligence (AI) is disclosed. Methods and systems for a model collaboration platform that facilitate the integration of external feedback, whether from physical, virtual, or human sources, into the streamlined design, validation, verification, certification, assembly, operations, and maintenance processes of complex systems. Updated results are output to those external sources, including physical twins, other digital twins or models and simulations, and / or human users. External feedback includes feedback data from physical prototypes and their environment, virtual prototypes, simulations, and subject-matter experts. Embodiments are directed to integrating external feedback into the assembly and system-level assessment of digital twins, physical twins, digital threads, and the iterative design of constituting digital engineering models, including constructing, maintaining, and improving digital engineering models for the design, validation, verification, certification, operations, and maintenance of complex systems.

The invention discloses a truss type load-bearing structure time domain dynamics topological optimization method and system based on an intrinsic orthogonal decomposition method, and relates to the technical field of truss type load-bearing structure topological optimization. The method is provided for solving the problems of high calculation power and the like caused by large-scale space-time response iteration of original transient problems and intensive calculation of dual problem sensitivity analysis in the prior art. According to the method, a local geometric control strategy for the cross interference problem of rod piece units is introduced, and a transient dynamics full-order topological optimization model of the truss structure is established through an equal geometric stiffness diffusion method. Based on an intrinsic orthogonal decomposition method, a transient dynamics reduced-order model of a truss structure is constructed, a reduced-order model base is updated in real time through an incremental singular value decomposition method, and then efficient solving of a transient dynamics equation and an adjoint equation in sensitivity analysis is achieved. And updating an iterative design variable by adopting a penalty function method, and seeking the optimal layout design of the truss structure. The invention provides a time-domain dynamics topological optimization method of the truss type load-bearing structure based on an intrinsic orthogonal decomposition method, and the method can be used for efficiently solving the dynamics layout optimization problem of the truss structure under the action of a transient load.

One embodiment of a computer-implemented method includes receiving the plurality of design constraints defining properties of a machine assembly, receiving a first selection of a first part in a user interface, the first part selected from a virtual parts inventory, identifying, using a generative machine learning model, a second part from the virtual parts inventory connectable to the first part based on the plurality of design constraints and a second selection of a first location within the first part, and displaying the first part and the second part in a user interface, wherein the first part and the second part comprise a first portion of the machine assembly.

An optimization method for a fuel control device structure based on additive manufacturing includes: performing a basic arrangement analysis and a selection of the fuel control device structure; performing an arrangement design of a basic component / interface feature structure according to the basic configuration structure; performing an optimization design for a flow channel structure on the basis of determining structural features of all cores, components and interfaces; performing the optimization design for an outer envelope structure on the basis of the flow channel structure; and checking a calculation and optimizing an iterative design of the fuel control device structure through a finite element tool, and determining a structural scheme of the optimal fuel control device. The optimization method gives full play to the technological advantages of additive manufacturing and determines the optimal structural arrangement and flow channel design scheme to meet the product requirements through pure forward design ideas.

The invention provides a train airtightness iterative design method, system and equipment based on a simulation model and a medium. The train airtightness iterative design method comprises the following steps that an initial empirical relational expression and an initial simulation model are obtained according to a first train of airtight trains; according to the related theoretical relational expression and the initial simulation model, obtaining a whole vehicle air tightness index; according to the initial empirical relational expression and a related theoretical formula, the whole vehicle air tightness index is converted into a part air tightness index; according to the airtightness indexes of the parts, the whole newly-manufactured train is installed and manufactured, and the newly-manufactured train is used as the first airtight train of the next airtightness iteration; according to the method, the static sealing index of each key airtight component is obtained through decomposition based on a simulation analysis method, the problems and defects existing in existing train air tightness optimization design can be solved, and train air tightness meeting the requirements is obtained according to simulation and test data of an existing train combination line and used for guiding and optimizing subsequent product air tightness design. The system also has the same beneficial effects.

This invention discloses a product packaging iterative design system and method based on data analysis, relating to the field of product packaging technology. The invention acquires a simulated packaging process of the product being placed into a packaging shell, marks primary damage risk points, generates a static matching degree map in the static state after simulated packaging, applies environmental load parameters simulating the transportation environment to the static matching degree map, analyzes the relative displacement and internal stress redistribution between the product and the packaging shell, assesses their impact on the deterioration of primary damage risk and static matching degree, identifies points that exacerbate damage risk, adjusts the design scheme of the packaging shell, conducts iterative simulation analysis, and selects the packaging shell with the best overall performance as the final design scheme. This solves common quality problems in cross-regional transportation of cold chain food, such as high-altitude bag swelling and extrusion, and high-temperature softening providing space for extrusion, improving the accuracy and efficiency of packaging scheme determination.

The application provides a heavy-duty gas turbine compressor design method, system and medium suitable for multiple working conditions. The method comprises the following steps: in the two-dimensional through-flow inverse problem design stage, through a plurality of set blade profile geometric parameters and a preset artificial neural network proxy model, through-flow loss and lag angle are calculated; based on a positive problem analysis file generated by a positive and inverse problem coupling design, two-dimensional through-flow positive problem analysis is carried out, including judging whether the compressor working margin meets the requirements by calculating a stall factor; for the deviation between the matching parameters of each stage of the compressor and the expected values of the through-flow design, the adjustment amount of the blade profile geometric parameters corresponding to the deviation is predicted through through-flow analysis; and the VGVs control law of the compressor under variable load working conditions is optimized and designed by using the positive problem analysis file and a particle swarm optimization algorithm. The method fully utilizes the positive problem analysis file generated in the positive and inverse problem coupling mode, can reduce the number of iterative designs, and improves the aerodynamic design efficiency.

The invention discloses a process control method and device for rear-end design of a digital chip and EDA tool software, and the method comprises the steps: firstly, carrying out RC automatic calibration on a pre-wiring database according to a design database, a reference database, a reference parasitic parameter information file and / or a preset time sequence calibration target, and then obtaining a parameter configuration file, the parameter configuration file comprises calibration configuration parameters for parasitic parameter extraction and / or time sequence values; and then loading the parameter configuration file in a logic synthesis stage, a layout stage, a clock tree synthesis stage, a wiring stage and / or an ECO stage of physical perception in a digital chip back-end design for RC extraction. According to the calibration configuration parameters, RC extraction or a time sequence value of a certain stage is used as a reference value to guide an RC engine of another stage, and then an optimized RC estimation model is used for iterative design again, so that a calibrated RC estimation or extraction model can be applied in different stages, the RC estimation and extraction precision is improved, and the design process efficiency is further improved.

The application relates to a dynamic response analysis method of a gas turbine cylinder elastic support structure, wherein the method comprises the following steps: generating a finite element simulation result of the gas turbine cylinder elastic support structure based on at least one of an isotropic loss factor, a structure size, an elastic modulus and an acting load of the gas turbine cylinder elastic support structure; constructing a firefly optimization algorithm-back propagation FA-BP neural network model; training the FA-BP neural network model by using a training set; evaluating the trained FA-BP neural network model, and generating a dynamic response result of the gas turbine cylinder elastic support structure after the evaluation result meets a preset condition. The embodiment of the application can realize training and prediction of a dynamic analysis model of an elastic support structure, provide a fast iteration method for design optimization, improve the calculation efficiency of elastic support dynamic simulation in the iteration design process, and realize a dynamic simulation method with high efficiency and precision.

One embodiment of a computer-implemented method includes receiving the plurality of design constraints defining properties of a machine assembly, receiving a first selection of a first part in a user interface, the first part selected from a virtual parts inventory, identifying, using a generative machine learning model, a second part from the virtual parts inventory connectable to the first part based on the plurality of design constraints and a second selection of a first location within the first part, and displaying the first part and the second part in a user interface, wherein the first part and the second part comprise a first portion of the machine assembly.

The application discloses a symbolic controller design method based on chino polyhedron under linear temporal logic specification, belongs to the technical field of nonlinear system control, and solves the linear temporal logic (LTL) task controller synthesis problem of a nonlinear control system. First, an accepted path is generated for a preset LTL task. Second, a chino polyhedron and a constrained chino polyhedron are used to divide a state space, the divided regions are defined as 'units', adjacent units are allowed to intersect, a unit topology graph is constructed based on the unit intersection relationship, and the realizability of the LTL accepted path is verified. Finally, if the accepted path is realizable, the global LTL task is decomposed into a plurality of local subtasks, a local symbolic model is constructed for each unit, a local symbolic controller is iteratively designed through a 'local to global' control strategy, and combination is completed, so that a symbolic controller satisfying the global LTL specification is obtained. The application supports different units to adopt a differentiated local equivalence relationship, reduces the conservativeness of a single equivalence relationship, reduces the calculation complexity of global approximation, and improves the efficiency and practicability of controller synthesis.

Digital model platform that enables the streamlined creation and management of digital twins and physical twins by leveraging external feedback and artificial intelligence (AI) is disclosed. Methods and systems for a model collaboration platform that facilitate the integration of external feedback, whether from physical, virtual, or human sources, into the streamlined design, validation, verification, certification, assembly, operations, and maintenance processes of complex systems. Updated results are output to those external sources, including physical twins, other digital twins or models and simulations, and / or human users. External feedback includes feedback data from physical prototypes and their environment, virtual prototypes, simulations, and subject-matter experts. Embodiments are directed to integrating external feedback into the assembly and system-level assessment of digital twins, physical twins, digital threads, and the iterative design of constituting digital engineering models, including constructing, maintaining, and improving digital engineering models for the design, validation, verification, certification, operations, and maintenance of complex systems.

This invention discloses a Python-based parametric modeling method for wind turbine blades, relating to the field of finite element analysis technology. By combining Python with an Abaqus scripting interface, this invention automates the entire process of geometric modeling, model segmentation, mesh generation, material property assignment, assembly arraying, and contact and boundary condition setting for the blade root segment, blade root bolts, flanges, bearings, hub, and hub bolts. The final result is the generation of a semi-model (CAE and INP) file of the blade root. This invention significantly reduces the finite element modeling time for blade roots, decreasing the modeling efficiency from tens of hours using traditional manual methods to minutes. It effectively reduces human error and provides a simple and intuitive interactive interface, offering a reliable technical means for the rapid iterative design and analysis of blade root structures.

The invention provides an instruction set design method for matrix online parallel general calculation, which analyzes several common large-scale matrix calculation operators in a deep learning algorithm and extracts a general calculation mode. And configuring an instruction type demand model and a behavior model according to a general calculation mode by taking universality and calculation performance as optimization targets. And performing iterative design on the deep learning instruction set according to the constructed instruction type demand model and behavior model, so that the deep learning processor gives consideration to calculation performance and universality.

The invention provides a drug design digital twinning method and platform based on a pre-training knowledge graph, and the method comprises the steps: constructing the pre-training knowledge graph focusing on drugs, target spots and mechanism paths, and generating a drug structure embedding vector and a mechanism path embedding vector through a graph neural network; a mechanism path is utilized to embed and guide a conditional graph to generate a network, and candidate molecules matched with a target mechanism are generated from a public skeleton; performing conditional graph attention propagation on the candidate molecules in combination with mechanism semantics in the mechanism sub-graph, and simulating multi-dimensional behavior performance of the candidate molecules under a mechanism path; and performing comprehensive scoring based on behavior performance, screening an optimal structure, generating a standardized execution object which can be directly issued to an experimental platform, and extracting a mechanism-structure optimization mode for subsequent iterative design. Closed-loop cooperation of knowledge representation, structure generation, mechanism simulation and experiment execution in drug design is realized, and research and development efficiency, prediction interpretability and result feasibility are improved.

The invention discloses an intelligent air cooler design method based on knowledge engineering and multi-physics field coupling analysis. The intelligent air cooler design method comprises the steps that an instance library containing multiple pieces of historical air cooler product complete data is constructed; constructing a subjective and objective weight coefficient mixed model by adopting an optimization method based on the main indexes of the air cooler required by the order, calculating the similarity with historical products, and performing instance reuse, instance modification or new product design according to the similarity; for a scheme needing to be modified or newly designed, the modeling and installation parameters are adjusted, and an assembly body and a flow field geometric model are automatically generated; establishing a multi-physics field coupling mechanical calculation model, calling a corresponding sub-model for calculation according to a checking requirement, and automatically obtaining performance data and finishing checking; aiming at new product design, starting a calculation model to carry out iterative design and statistical optimization; and finally, storing the design scheme and the process scheme which pass the engineering verification into an instance library as new instances. Intelligent and automatic design of the air cooler is achieved.

The application discloses an ice wind tunnel cloud mist nozzle design method, device, equipment and medium, the method comprises the steps that S1, according to the cross-sectional size of the position of the spray rake in the ice wind tunnel, the layout of the spray rake and the number of nozzles are preliminarily determined;S2, according to the existing supercooled large water droplet frozen drizzle condition, determine the cloud mist requirement;S3, according to the liquid water content LWC and the wind tunnel test section speed requirement, the water supply demand of the nozzle and the water supply demand of the single nozzle are analyzed;S4, according to the water supply flow and the water supply parameter, the nozzle combination mode of the spray system is preliminarily designed;S5, the nozzle combination mode is simulated in the ice wind tunnel cloud mist-air two-way coupled heat transfer;S6, analyze the simulation result, evaluate whether to meet the particle size requirement of the frozen drizzle cloud mist, if yes, the cloud mist nozzle design is completed, if not, return to step S4, optimize the nozzle spacing and combination, and carry out iterative design. The application shortens the design iteration cycle and reduces the test cost.

This invention belongs to the field of CAD / CAE integrated design and structural reanalysis technology, specifically involving a rapid reanalysis method for CAD and CAE integration based on volume subdivision. It deeply integrates volume subdivision technology with reanalysis technology, using volume subdivision as a unified geometric-analysis representation framework for CAD / CAE. Local feature editing, discretization updates, and finite element reanalysis are integrated into the same data structure, constructing a rapid reanalysis framework suitable for adding or deleting local features, geometric deformation, and topological changes. This invention can efficiently handle reanalysis scenarios involving feature modifications in complex equipment, significantly improving computational efficiency while ensuring analysis accuracy. It completely solves the pain points of traditional methods, such as local feature modifications triggering global reconstruction and high computational costs. It is suitable for high-frequency feature iteration design requirements and has strong engineering application value.

The invention discloses a three-element collaborative design method for a bamboo-like sandwich spar driven by a modular neural network, and relates to the technical field of aircraft design, and the method comprises the following steps: constructing a linear bearing performance sub-neural network; constructing a nonlinear effector neural network; constructing a defect reduction effect sub-neural network; fusing the linear bearing performance sub-neural network, the nonlinear effector sub-neural network and the defect reduction effector sub-neural network to obtain a modular neural network; inputting the input parameters into a modular neural network, and obtaining output parameters through the modular neural network; iteration is carried out through a spar parameter iteration design module, and spar optimization design is completed. According to the three-element collaborative design method for the bamboo-like sandwich spar driven by the modular neural network, the bamboo-like sandwich spar designed by the method is generally suitable for wings with high aspect ratio and low wing load, the prediction precision of the structural damage boundary is high, and the method has the advantages of excellent precision, high efficiency and good robustness.

The application discloses a modular neural network driven three-element collaborative design method for a bamboo-imitating sandwich wing spar, relates to the technical field of aircraft design, and comprises the following steps: constructing a linear bearing performance sub neural network; constructing a nonlinear effect sub neural network; constructing a defect reduction effect sub neural network; fusing the linear bearing performance sub neural network, the nonlinear effect sub neural network and the defect reduction effect sub neural network to obtain a modular neural network; inputting input parameters into the modular neural network to obtain output parameters through the modular neural network; and iteratively designing a spar parameter through a spar parameter iterative design module to complete the optimization design of the spar. The modular neural network driven three-element collaborative design method for the bamboo-imitating sandwich wing spar is adopted, the bamboo-imitating sandwich wing spar designed by the method is generally applicable to a large-aspect-ratio low-wing load wing, the prediction accuracy of a structural damage boundary is high, and the method has the advantages of high accuracy, high efficiency and good robustness.

A method for iterative design using a computer numerical control (CNC) machine for automated changing of a CNC computer design program controlling the CNC machine may install an executable application to the CNC computer design program. The executable application may have a plurality of instructions, when executed by a processor, may cause the processor to display a customer tab on a home screen of the CNC computer design program, wherein the customer tab displays a plurality of icons. The plurality of instructions, when executed by a processor, may cause the processor to synchronize settings of the CNC computer design program to settings on the CNC machine so the settings on the CNC computer design program mirror the settings on the CNC machine when an import icon of the plurality of icons is selected is selected.

This invention discloses a method for defuzzification optimization of a planar arbitrary configuration interferometer, belonging to the field of passive direction finding and positioning technology. The method involves: first, determining the initial configuration of the planar interferometer and its corresponding direction finding baseline; then, performing fuzzy number set analysis corresponding to the arrival fuzzy offset vector within the field of view; subsequently, determining the minimum effective non-redundant phase difference observation set and constructing a phase residual cost function; combining the layout structure and neighborhood range to generate neighborhood optimization cost constraints and geometric constraints; finally, iteratively obtaining the optimal configuration correction vector within the neighborhood under the constraints to complete the configuration optimization. This method has no special requirements for the interferometer layout, has strong applicability, can effectively improve the system's defuzzification performance, and has high configuration optimization efficiency, making it suitable for rapid iterative design.

The embodiment of the invention discloses a method for constructing a radar servo system model based on a meta-model. In one specific embodiment, the method comprises the following steps: establishing a meta-model library of the radar servo system; establishing a general model library of the radar servo system according to the meta-model library of the radar servo system; and establishing a corresponding radar servo system model based on the general model library of the radar servo system according to project requirements. The implementation mode can be suitable for model construction processes of radar systems and subsystems in different fields, and a more standard and more convenient modeling method is provided for rapid iterative design of the radar system model.

The invention relates to a rocket engine valve motor assembly, in particular to a rocket engine valve motor assembly capable of achieving three-direction vibration reduction and a design method of the rocket engine valve motor assembly, and solves the technical problems that an existing valve motor assembly and a design method of the existing valve motor assembly are difficult to meet the requirements for three-direction vibration reduction, low cost and rapid design of a rocket engine. According to the shock absorber, the shock absorber-valve connecting bolts and the shock absorber-motor connecting bolts which are evenly distributed in the circumferential direction are connected with the valve and the motor correspondingly, the good assembling characteristic is achieved, and the good rigidity characteristic, the good connecting characteristic and the good three-direction shock absorption effect can be provided. Meanwhile, vibration reduction characteristics and structural characteristics can be accurately estimated through simulation, adjustment of parameters of the vibration damper can be rapidly completed according to design requirements, therefore, adjustment and optimization of rigidity and vibration reduction performance are conducted, the range of adjustment frequency and the range of the vibration reduction effect are large, and the high-cost requirement for iterative design through tests in a traditional vibration reduction scheme is avoided.

The application discloses a non-iterative design method of a non-uniform continuous distribution composite pupil function, solves the problem that the design method of an existing pupil function is relatively complex, including expansion of the pupil function, matrix calculation and a calculation process of solving a high-resolution gain expression, the non-uniform continuous distribution composite pupil function is composed of a Sonine polynomial, a Zernike polynomial and a Fourier-Bessel series, numerical mapping relationships between the Sonine polynomial, the Zernike polynomial, the Fourier-Bessel series and an imaging complex amplitude distribution at a radial focal plane are respectively constructed, coefficients of the Sonine polynomial, the Zernike polynomial and the Fourier-Bessel series are solved, a function formula of the composite pupil function is finally determined, and the mapping relationship is relatively simple and operable.

The application discloses a turbine blade profile simulation piece design method and a simulation piece test piece, and belongs to the technical field of aerospace engines. According to the method, the turbine blade is divided into sections, the temperature and stress of each section dangerous point are obtained, and the strength reserve coefficient is calculated. The section corresponding to the minimum strength reserve coefficient is selected as the dangerous section. The selected dangerous section is the weakest section in the section division, so that the designed simulation piece can fail under the same physical mechanism as the real blade. Therefore, the creep life and fracture data obtained from the simulation piece test can truly reflect the creep performance of the turbine blade, greatly improving the accuracy of life prediction. Meanwhile, the worst "strength-stress" matching section can be directly pointed out, and targeted measures can be taken in the subsequent iterative design process.

The invention relates to the technical field of mechanical arm control, in particular to a flexible tracking control method for randomly switching a mechanical arm system with unmodeled dynamics, which comprises the following steps of: constructing a mechanical arm kinetic equation, considering the unmodeled dynamics, obtaining state space representation, and establishing a nonlinear system state equation with output constraint; flexible preset performance is designed based on the mechanical arm system, error transformation is carried out, and a tracking error model is established; using a radial basis function neural network to approach an unknown physical nonlinear term corresponding to the mechanical arm system, and designing an adaptive law; introducing coordinate transformation and separation variables according to a nonlinear system state equation with output constraint, and iteratively designing a controller by adopting a backstepping method through a tracking error model; flexible pre-setting performance, flexible pre-setting performance, a self-adaptive law and a controller are integrated, an average residence time switching law is designed to restrain system mode switching, and a self-adaptive closed-loop control mechanical arm system capable of stably running under unmodeled dynamic and random switching is jointly established.

The invention discloses an oil cylinder fixing structure, a joint size determination method and an aerial work platform, and belongs to the technical field of aerial work engineering machinery and computer aided modeling. The oil cylinder fixing structure comprises an oil cylinder, a check block, a fixing bolt and an arm support connecting plate, a limiting groove is formed in the middle of a mounting connector at the end of the oil cylinder, longitudinal limiting is achieved through matching of a stepped structure and the arm support connecting plate, axial limiting is achieved through the check block inserted into the limiting groove, and the rotating rigidity of the connector is remarkably improved. Meanwhile, according to the method, a finite element model of the oil cylinder connector is established, a linear equivalent algorithm is adopted for rapid iterative design, then a nonlinear equivalent algorithm is adopted for accurate verification, an efficient and reliable design closed loop is formed, and connector size parameters capable of achieving the design load are determined. According to the method, the buckling instability resistance of the oil cylinder is effectively improved, the safety and reliability of the long arm frame of the aerial work platform are guaranteed, and a standardized tool is provided for performance prediction and reliability evaluation.

An automatic compilation method and framework for generating a layout for an integrated memory-compute circuit design is provided. The automatic compilation method comprises: constructing a design database with at least one basic design library and a collection of referencing architecture templates; receiving a user specification associated with the integrated memory-compute circuit design; selecting a referencing architecture template from the design database and parameterizing the selected architecture template according to the received user specification to generate an architecture for the integrated memory-compute circuit design; generating a physical layout based on the generated architecture according to one or more placement-and-routing algorithms; iterating a design exploration loop on the generated layout with one or more expertise experience-based optimization schemes to obtain one or more explored physical layouts; and evaluating hardware metrics of the one or more explored physical layouts to determine an optimal physical layout.