288 results about "Modeling and simulation" patented technology

The invention belongs to the technical field of automatic control, and relates to a self-adaptive control method based on multi-physical modeling. According to the method, by collecting multi-source data of a controlled object, a thermal, electric and force coupling relation used for control analysis is established so as to describe dynamic responses under different operation conditions. And calculating stress, motor power, energy consumption and temperature rise change in the operation process based on a coupling relation to obtain system performance data, verifying stability and safety of different control parameter combinations in a simulation environment, and obtaining performance indexes including operation retardation risk, overload safety margin and safety response time limit. And according to a simulation result, under the condition of meeting safety constraints, taking energy consumption and temperature rise as optimization targets, adjusting control parameters, generating optimized control parameter configuration data, and feeding back the optimized control parameter configuration data to a control unit, so that closed-loop adaptive control and performance optimization are realized. According to the invention, through multi-physical coupling modeling and simulation optimization, the adaptability and reliability of the automatic control system are improved.

The invention discloses a cloud data center full life cycle monitoring and early warning system based on digital twinning, and the system comprises a multi-source collection and preprocessing module which is used for collecting and preprocessing multi-source data; the twinborn modeling and simulation module is used for constructing a digital twinborn body and completing virtual-real mapping and mechanism simulation; the time sequence modeling module is used for constructing a state space-Kalman enhancement time sequence evolution twinborn model and carrying out continuous time sequence modeling; the virtual-real residual error self-correction closed loop module is used for generating a virtual-real residual error and updating the digital twinborn body and time sequence evolution twinborn model; and the risk and linkage module is used for executing risk identification, grading and life cycle linkage according to the corrected time sequence characteristic representation. According to the invention, a state space-Kalman enhanced time sequence evolution twinborn method is adopted, virtual-real self-correction and full-life-cycle early warning of the cloud data center are realized, and the method has the advantages of high precision, strong robustness and self-optimization.

The invention discloses a digital twin-driven water and fertilizer real-time dynamic balance transfer system, which comprises a sensing and data acquisition module for monitoring moisture, salinity, pH value, illumination and rainfall meteorological data of soil in real time through various sensors deployed in a farmland; and the digital twinborn modeling and simulation module is used for constructing a digital twinborn model of the farmland based on the real-time data collected by the perception and data acquisition module. According to the invention, by arranging the perception and data acquisition module, the digital twin modeling and simulation module, the intelligent decision-making and regulation module, the execution and feedback module, the historical data tracing and system optimization module, the expansion module, the networking module and the edge-cloud cooperative computing architecture, the farmland environment and the crop growth condition can be monitored in real time; the digital twinborn modeling and simulation module constructs a digital twinborn model of a farmland based on real-time data, simulates a soil environment and crop growth, and optimizes a water and fertilizer proportioning strategy.

The invention belongs to the technical field of engineering simulation data processing, and particularly discloses a finite element grid graph structure construction method and system, a terminal and a medium. Comprising the following steps: analyzing original full-amount grid data exported by finite element simulation, segmenting unstructured grid data into a grid vertex coordinate set and a grid unit mark number set, and constructing a graph edge topological structure corresponding to a grid based on a unit mark number relationship; on the basis, loading physical field data and adopting a tolerance-based coordinate matching algorithm to realize accurate mapping of physical field labels and material attributes with grid nodes; and generating standardized finite element grid graph data which can be directly used for graph neural network processing. By means of the method, high-consistency and high-physical-reliability conversion from the finite element simulation data to the graph structure data is achieved, and the physical field modeling and simulation acceleration capacity based on graph learning is improved.

The invention discloses a low-loss planar transformer design method suitable for an LLC resonant converter, and the method comprises the steps: firstly collecting the index parameters of the LLC resonant converter, setting the target parameters of a planar transformer, selecting a magnetic core model meeting the requirements according to an AP method, and then carrying out the design of a winding structure, finally, modeling and simulation of the planar transformer are completed in finite element software, and if the simulation result does not meet the set parameter and loss requirements, selection of the magnetic core model and design of the winding structure need to be conducted again; and if the set parameters and the loss requirements are met, finishing the design.

The invention relates to a nonlinear damping element based on a Modelica language, and relates to the field of mechanical system modeling and simulation. According to the technical scheme, a novel damping element is designed based on the Modelica language, corresponding damping coefficients can be defined according to different movement speeds of the element, and the limitation of the prior art is effectively broken through; specifically, according to the technical scheme, the element types of the Modelica mechanical library are enriched, the blank of nonlinear damping elements in the library is filled up, and the application range of the library is expanded; moreover, simulation requirements of a nonlinear damping system can be accurately matched, so that the modeling process better fits nonlinear characteristics of a damping coefficient in an actual working condition; besides, free switching between non-linear damping and linear damping can be flexibly realized depending on a speed-damping force two-dimensional number table, the adaptability of the element to different modeling scenes is greatly enhanced, and powerful support is provided for precise modeling of a mechanical system based on Modelica.

The invention discloses a machine learning driven vehicle frame lightweight design method, which comprises the following steps: (1) performing vehicle frame parametric modeling in CATIA, constructing a vehicle frame modal analysis model and a stiffness analysis model in ABAQUS, and deducing a mathematical model of vehicle frame lightweight design; (2) performing Latin hypercube sampling and discrete Gaussian sampling on continuous and discrete parameters to generate a frame population, and establishing a database; (3) designing a variable type driven hybrid variation mechanism to obtain a candidate frame population; (4) constructing a radial basis function machine learning model, and deducing a comprehensive minimum statistical lower limit function to screen an optimal candidate frame; and (5) performing parametric modeling and simulation analysis on the optimal candidate frame, updating the frame population and the database, returning to the step (3) until the optimal frame meets the design requirement, and outputting the optimal frame. According to the method, adaptive variation strategies and screening functions are designed according to the vehicle frame parameter characteristics, and the vehicle frame lightweight design effect is good.

The invention discloses a recycled concrete permeability detection system and method, and relates to the technical field of material science, and the system comprises an electric field auxiliary module which applies a preset voltage gradient through an electric field auxiliary device, obtains initial ion concentration distribution data and a current change signal from a recycled concrete sample, and obtains a reference parameter of a permeation process; the modeling and simulation module is used for constructing a pore structure model by adopting a finite element simulation method according to the reference parameters, fusing an ion migration rate and a non-uniform distribution characteristic, and determining a dynamic regulation and control scheme under the action of an electric field; according to the recycled concrete permeability detection system and method, dynamic regulation and control and real-time monitoring of ion permeability behaviors are achieved, the barrier property evaluation precision of recycled concrete is remarkably improved, and efficient technical support is provided for durability optimization of engineering materials.

The invention relates to the technical field of power system modeling and simulation, in particular to a load model identification error analysis method, device and equipment and a storage medium, and the method comprises the steps: obtaining the prediction output and the measurement output of a preset load model, and building a target function based on the error between the prediction output and the measurement output; decomposing the measurement output to obtain an actual output and a noise component of a preset load model; and based on the objective function and the actual output, establishing a linear model between the identification error of the preset load model and the noise component through a first-order approximation method, and performing linear regression according to the linear model to obtain an analysis result of the identification error. Therefore, by constructing the theoretical model of the load model identification error, the problems that the identification error is difficult to predict, the data processing strategy selection lacks theoretical guidance and the like in related technologies are solved, and a theoretical basis is provided for selecting an optimal load modeling data processing strategy.

The invention provides a management, modeling and simulation method and system for heterogeneous computing task scheduling, and the method comprises the steps: generating a global logic task identifier set according to the input parameters of a computing problem, and dividing the set into a plurality of logic task blocks based on the internal attributes of logic task identifiers; mapping each logic task block into an atomic computing unit, and packaging a computing attribute for each atomic computing unit; based on a preset screening rule and the resource constraint information, the atomic computing units are recombined, and schedulable task instances are formed; and allocating the schedulable task instances to the computing resources for execution, and monitoring performance data of the execution to update the quantifiable computing attributes of the atomic computing units by using the performance data. According to the method, the problems that the utilization efficiency of heterogeneous computing resources is low and simulation prediction is distorted due to the fact that a traditional task scheduling scheme lacks a quantifiable task abstraction and dynamic recombination mechanism across hardware platforms are solved.

The invention discloses a deep and far sea wind power time-varying impedance model grid connection analysis method based on a time domain residual error method, relates to the technical field of power system modeling simulation, and can efficiently and accurately analyze deep and far sea wind power grid connection. The method comprises the following steps: establishing a differential algebraic equation set containing high-capacity submarine cable impedance and a plurality of nonlinear links, and constructing a recursive coefficient matrix; dividing a preset global time domain into a plurality of time domain subintervals, and solving the recursion coefficient matrix in each time domain subinterval by referring to a universal analytic solution represented by a power series explicit operator to generate a global time domain explicit solution corresponding to the preset global time domain; performing discrete Fourier transform on the global time domain explicit solution to obtain a time-frequency domain spectrum result; and constructing a time-varying impedance model according to the differential algebraic equation, setting the time-varying impedance model by adopting a time-frequency domain spectrum result, and analyzing the deep and far sea wind power grid-connected control system by utilizing the set time-varying impedance model.

Disclosed is a joint modeling and simulation method and system for ocean engineering installation operation, belongs to the technical field of ship and ocean engineering, and particularly relates to joint modeling and simulation for ocean engineering installation operation. The problems of low simulation efficiency, incapability of satisfying real-time requirements of engineering drills, and high time cost caused by repeated development due to difficulty in reuse of a simulation model in the ocean engineering equipment installation operation at present are solved. The method includes the following steps: step S1: acquiring an equipment independent motion simulation model; and step S2: acquiring joint simulation real-time data through motion transmission simulation and load transmission simulation. The joint modeling and simulation method and system for ocean engineering installation operation are applicable to the joint modeling and simulation for ocean engineering installation operation.

The invention discloses a stay cable tensioning system and method. The stay cable tensioning system comprises a data acquisition module, a modeling and simulation module, a multi-source data fusion module, a cable force value prediction module, a disease diagnosis and maintenance module and a tensioning control module. According to the stay cable tensioning system, through full-process digitization of data acquisition, modeling analysis, intelligent control and maintenance rehearsal, the change from experience driving to data driving is achieved. The method has the core advantages that the deep fusion of multi-source data, the precise simulation of the digital twin model and the efficient decision of the intelligent algorithm significantly improve the construction precision of the stay cable, the safety of the structure and the maintenance efficiency. The method has the advantages that the prediction error of the cable force value in the construction stage is reduced from + / -5% to + / -1.2%, the stability of the cable force value after bridge forming is improved by 60%, and the vibration amplitude is reduced by 85%.

The invention relates to the technical field of mechanical part design, and discloses a flange bolt connection layout optimization design method and related equipment.The method comprises the steps that flange basic parameters are obtained, and a rigidity calculation model is constructed based on the flange basic parameters; bolt margin parameters are determined through sealing surface pressure distribution based on a rigidity calculation model; bolt spacing parameters are determined through pressure distribution changes based on a rigidity calculation model; and performing parametric modeling and simulation checking on the determined bolt edge distance parameters and bolt spacing parameters by taking the pressure distribution change rate as a checking parameter to obtain a design result, and completing flange bolt connection layout optimization design through the design result. According to the method, discrete experience is upgraded into a continuous scientific model, the design reliability is remarkably improved, static strength design of a traditional empirical formula is replaced, and therefore the sealing reliability is remarkably improved, the method adapts to complex working conditions, and the design period is greatly shortened.

The invention relates to the technical field of data processing, in particular to a water source heat pump air conditioning system emission reduction data evaluation method and system, and the method comprises the steps of data acquisition and processing, data complementation, reference scene modeling and simulation, actual emission calculation, emission reduction calculation and analysis, full life cycle emission calculation and result output. According to a traditional full-life-cycle evaluation method, specific resource conditions, environment cost, policy intensity and other regional factors of a project location are ignored, so that an evaluation result is lack of regional guiding significance; according to the method, a regional influence weight adjustment model constructed based on a multi-layer perceptron neural network is introduced, differential parameters such as underground water recharge cost, pollution control cost, recovery industry level and carbon policy intensity of a project location are taken as input, and weight coefficients of all life cycle stages are dynamically calculated; the evaluation result can dynamically reflect where emission reduction is implemented, the value is higher, and a more accurate scientific basis is provided for differentiated decisions of different areas.

An artificial intelligence system for military planning and decision support is disclosed. The system comprises a central coordination agent, multiple specialized agents focused on specific military domains, and a dynamic learning module. The system analyzes inputs, activates relevant specialized agents, coordinates information exchange, and synthesizes outputs into cohesive solutions. It incorporates security and ethics verification, multi-modal interfaces, and can operate in both local and remote configurations. Advanced capabilities include multi-lingual operation, predictive maintenance, and generation of multiple courses of action with sophisticated modeling and simulation. The system is not limited to this architecture, and may instead comprise of a single AI system consolidating these functions. The system continuously learns and adapts to new scenarios while maintaining alignment with military doctrine and objectives.

The invention relates to a Janus type heterojunction material as well as a calculation method and application of the Janus type heterojunction material in photocatalytic water decomposition, and belongs to the technical field of heterojunction materials. The upper layer of the material is a 1T-phase GeSe single layer, the lower layer of the material is a 1T-phase SnSSe single layer, and the material is divided into two configurations of GeSe / SSnSe and GeSe / SeSnS according to interface atom arrangement. Modeling and simulation calculation are carried out through VESTA and VASP software, and the result shows that the material has the direct Z-type heterojunction characteristic, photon-generated carrier separation can be effectively promoted, the light absorption range is widened, the photocatalytic oxidation reduction capacity and the solar energy-hydrogen energy conversion efficiency are remarkably improved, and a new strategy is provided for developing efficient photocatalysts.

The invention discloses an intelligent diagnosis method for wear of a high-speed bearing of an emulsifying machine, and the method comprises the steps: collecting multi-working-condition vibration and environmental noise signals through an experimental design system, and building a structured and standardized multi-channel data set; injecting various typical abnormal multi-scale signals by utilizing a physical modeling and simulation algorithm; adopting a working condition gating multi-branch time-frequency feature extraction network to obtain adaptive features; according to the method, high-confidence anomaly discrimination is realized in combination with a multi-discrimination sub-model and ensemble learning, and anomaly traceability and model self-learning are realized through a back projection and dynamic update algorithm. The method is suitable for intelligent monitoring and health management of emulsifying machine bearings under complex variable working conditions.

The invention discloses a method and system for simulating the operating environment of a hydrogen energy reaction kettle, and the method comprises the steps: building a multi-scale simulation frame based on the hydrogen energy reaction kettle, and carrying out the modeling of a micro scale, a mesoscale and a macro scale of the hydrogen energy reaction kettle; performing multi-physical field coupling simulation on the hydrogen energy reaction kettle, including coupling calculation of a flow field, a temperature field, a concentration field and a stress field in an operation environment of the hydrogen energy reaction kettle; performing intelligent optimization simulation based on a multi-scale simulation framework and multi-physics field coupling simulation, wherein the intelligent optimization simulation comprises adaptive grid optimization, non-uniform inlet simulation and two-phase flow simulation; and constructing a digital twin platform, and carrying out system-level dynamic simulation and intelligent control on the hydrogen energy reaction kettle based on the digital twin platform. According to the method, all-around modeling and simulation from a micro scale to a macro scale are realized through a plurality of methods such as a density functional theory, molecular dynamics, a lattice Boltzmann method and computational fluid dynamics.

The invention discloses a multi-scale modeling and simulation prediction method and device for a two-phase composite material, and the method comprises the following steps: S1, carrying out the molecular dynamics simulation of the penetration process of a solution in the composite material based on molecular dynamics, extracting the microscopic information in the simulation process, and obtaining a microstructure model of the composite material; s2, mapping the microstructure model to a finite element grid, and reserving structures between particles and interfaces to obtain a finite element model; s3, inserting a cohesive zone unit into an interface of the finite element model, and modeling an interface adhesion and separation phenomenon between a matrix and particles of the composite material based on the cohesive zone unit; and S4, carrying out analogue simulation on the whole damage evolution process based on the finite element model to realize mechanical simulation analysis and prediction. According to the method, composite material modeling is carried out based on a real microstructure, and more accurate mechanical simulation analysis is carried out based on the modeling.

The invention relates to the technical field of building structure engineering, in particular to a partition wall structure integrated refined modeling and simulation method based on physical reality. A complete and closed technical chain from refined physical modeling to connection and failure linkage algorithm definition and then to whole-process nonlinear simulation to finally realize automatic multi-target parameter optimization is constructed, and'work-damage-failure-influence 'full-life-cycle behaviors of a partition wall subsystem are subjected to full-process nonlinear simulation, so that the whole-life-cycle behavior of the partition wall subsystem is optimized. A rigorous mathematical model and a numerical algorithm are integrated into the performance design of the whole structure, a special design system which is highly innovative, computable and verifiable is formed, and therefore quantitative and performance design of the damping connection structure is completed. By introducing a series of mathematical models, criteria and linkage algorithms with clear physical significance, the black box experience of traditional'cycle reduction coefficient 'is improved.

The invention provides a corresponding method for solid engine digital twin modeling and design optimization aiming at the problems of lack of an integrated parametric modeling framework, weak proxy model mapping capability, lack of a cross-working-condition / cross-model migration mechanism and the like in the background technology. The invention provides a digital twin modeling and optimizing method for a solid engine. The method comprises the following steps: step 1, setting parameters and inputting a model; 2, parametric modeling and simulation calculation are carried out; 3, configuring input and output of the proxy model; 4, extracting hidden variable features; 5, training a mixed structure agent model; step 6, parameter optimization based on a calibration mechanism; and 7, optimizing a result and analyzing.

This invention proposes a simulation method and system for the current response of distribution networks based on multi-frequency coupling effects, belonging to the field of power system modeling and simulation technology. The method includes: obtaining the frequency domain admittance matrix of the distribution network; extracting the same-frequency admittance vector and coupled admittance vector; converting each admittance vector into a transfer function, and then converting the transfer function into a discrete state-space model; preprocessing the voltage input signal using dq transform to reconstruct components at specified frequencies; substituting the preprocessed voltage signal into the discrete state-space model to obtain the current response of each frequency component; solving for the optimal weighting coefficients using an adaptive weighting strategy, and linearly superimposing the current responses to obtain the real-time simulated total current response.

The invention provides a training method for aero-engine modeling driven by mechanism and data fusion, and relates to the technical field of aero-engine modeling simulation, and the method comprises the steps: decomposing a simulation model of an aero-engine into a plurality of assemblies containing to-be-identified unknown parameters, and employing an assembly integration algorithm to associate the plurality of assemblies, an end-to-end differentiable complete simulation model is formed; based on hierarchical division of the simulation model, performing parameter pre-estimation by adopting a top-down layer-by-layer progressive strategy to obtain an initial estimation value of the unknown parameter; the strategy comprises the following steps: firstly, estimating unknown parameters of components in a highest level according to actually measured output data, and generating a training target of a next lower level based on a calculation result of an estimated level so as to complete estimation of unknown parameters of the lower level in sequence; and performing gradient back propagation in the complete simulation model by taking the initial estimation value as a starting point to optimize and update unknown parameters.

The invention discloses a hydropower station unit operation optimization system and method. The system comprises a data acquisition module, a modeling and simulation module, a power toggle analysis module, an intelligent control module, an operation optimization execution module and a remote monitoring and prediction module. According to the invention, by constructing a hydropower station unit operation optimization system which covers data acquisition, modeling simulation, power fluctuation analysis, intelligent control and remote monitoring prediction, accurate modeling and real-time correction of dynamic characteristics of an impact type unit in primary frequency modulation and jet needle throwing and withdrawing processes can be realized; fFT and big data analysis are utilized to effectively identify and suppress abnormal frequency fluctuation, and a speed regulation parameter and a spray needle control strategy are dynamically adjusted in combination with intelligent optimization means such as a genetic algorithm, so that the power fluctuation amplitude is remarkably reduced, the frequency modulation response time is shortened, and the control precision and stability are improved.

The application is based on a parallel flow passage heat exchanger flow distribution simulation method of a general flow resistance model: one, single channel general flow resistance model construction stage: create a general flow resistance model; single channel fine modeling and simulation; obtain pressure drop-flow rate data; fitting to determine the flow resistance coefficient; two, whole machine flow distribution simulation stage: build the whole machine simulation model: establish the three-dimensional geometric model of the macro flow channel system of the target heat exchanger and carry out grid division to obtain the macro flow channel CFD model, abstract all parallel microchannels of the core heat exchange section of the target heat exchanger into a parallel flow resistance network composed of a large number of flow resistance elements, each flow resistance element is endowed with the general flow resistance model with a specific flow resistance coefficient which has been determined in stage one; coupling solution, establish an iteration process, make the error between the driving pressure difference of each flow resistance element and the pressure drop calculated according to the general flow resistance model less than a preset threshold, and the iteration converges; output the flow distribution results of all parallel flow passages of the target heat exchanger.

The invention discloses an equal-length matching optimization method for differential pair transmission paths of a high-speed printed circuit board, and belongs to the technical field of signal integrity modeling and simulation. Comprising the following steps: constructing a multi-conductor transmission line model containing a reference conductor, extracting a parameter matrix per unit length, judging the uniformity and symmetry of a structure, and introducing a local modal substrate and a continuous modal coupling term which change along with space for describing modal conversion caused by gradual change of the structure, the propagation delay inequality of the two signal paths is calculated, a phase calibration operator is constructed, modal conversion and the delay mismatch effect are brought into a unified propagation equation to be solved, the phase calibration operator is applied at a recoupling reference plane to carry out alignment processing on voltage and current, and finally equivalent differential mode impedance is obtained through calculation. According to the method, integrated modeling is carried out by integrating the joint effect of mode conversion and time delay mismatch, and the impedance simulation precision of the difference pair snake-shaped compensation structure recoupling region is remarkably improved.

The application discloses an energy balance-based asymmetric temperature control system simulation modeling method, and belongs to the technical field of industrial temperature control system modeling and simulation. Firstly, a temperature rising step experiment and a temperature falling step experiment are performed, steady-state data is acquired, a balance point power function is derived, equivalent verification is performed, a temperature rising curve and a temperature falling curve are derived, and identification parameters are derived. A net power deviation is defined, the identification parameters are subjected to smooth transition, gain parameters are acquired, a first-order linear differential model is established, a first-order backward difference method is adopted for discretization, recursion is performed based on a set simulation step, and a recursion model is acquired. A plurality of recursion models are derived based on repetition of the simulation step, a temperature response curve of the temperature control system is established, and simulation modeling is completed. The method only needs two step experiments, real-time parameters are calculated through the net power deviation, real smooth and continuous dynamic simulation is realized, and a reliable simulation method is provided for temperature digital twinning and temperature controller design.

The application discloses a modeling simulation method of a backup power supply device and a storage medium, and comprises the following steps: step 1, predefining an obtained backup power supply device script; step 2, judging whether the backup power supply device is charged, if yes, entering step 3, otherwise, entering step 4; step 3, judging whether the pre-defined backup power supply device script of the backup power supply device meets a set action condition, if yes, adding the start information of the backup power supply device to a start queue or pushing a start queue simulation clock, entering step 4, otherwise, removing the start information of the backup power supply device from the start queue, and entering step 4; step 4, judging whether the start queue reaches a time limit, if yes, the backup power supply device sends a tripping instruction; step 5, judging whether a tripping switch is open, if yes, the backup power supply device sends a closing instruction, entering step 1 or ending operation, if not, entering step 1.

The invention provides a terahertz metamaterial resonance enhanced trace thiabendazole detection method and system, and the method comprises the steps: constructing parameter information of a metamaterial sensor based on a single periodic structure and the characteristic peak frequency of thiabendazole, and carrying out modeling simulation according to the parameter information to obtain a terahertz metamaterial with an L-shaped composite double-peak structure; preparing a thiabendazole sample, and performing spectrum acquisition on the thiabendazole sample by using a terahertz metamaterial to obtain corresponding spectrum data; constructing a support vector regression model, fusing a weighted vector average optimization algorithm, and performing hyper-parameter global optimization to construct a corresponding optimization model; and constructing a corresponding detection model according to the spectral data and the optimization model, and realizing nondestructive detection of trace thiabendazole by using the detection model. According to the method, high-sensitivity quantitative analysis on trace amount of thiabendazole residues is realized, and the feasibility and superiority of the INFO optimization algorithm in the field of spectrum detection are also verified.