8443 results about "Simulation methods" patented technology

The present invention discloses a method for dynamically assessing slope safety, and the method comprises the following steps: S1, carrying out geologic model generalization to the slope according to slope type, surface elevation, slope structure, stratum characteristics and a deformation failure mode to obtain a slope geologic model, creating a slope geometric model according to the said slope geologic model, carrying out the subdivision of computational grid, and selecting a reasonable numerical simulation method, mechanical constitutive and initial boundary value conditions to form a computational model; and S2, adjusting stratum parameters, structural plane parameters and activating factor strength based on the said computational model, carrying out a large amount of numerical simulation, summarizing results of the said numerical simulation, normalizing input quantities and output quantities to establish machine learning samples.

Disclosed is a microgrid optimal scheduling method taking into consideration a system operation risk and user satisfaction, comprising: generating a power prediction curve of wind power and photovoltaic new energy output in a microgrid, using a Monte Carlo simulation method to obtain a prediction error range to generate a typical scene set, and by means of a data fitting method, acquiring a wind-photovoltaic prediction error probability density distribution function; using value-at-risk and conditional value-at-risk theories to quantify a microgrid operation risk which is increased by slightly high or low output caused by wind power and photovoltaics; obtaining the scheduling cost of an adjustable load in a microgrid system; taking the minimum sum of conditional value-at-risk cost and microgrid system operation cost as an objective function and a user satisfaction level under a demand-side response as a constraint, establishing a microgrid optimal scheduling model taking into consideration the operation risk and the user satisfaction; and using a genetic algorithm to solve the model, and obtaining an optimal result of grid-connected microgrid system optimal scheduling. The safety, economic efficiency, stability and reliability of the microgrid are enhanced.

The invention relates to the technical field of twinborn model simulation, and discloses a twinborn model simulation method and system for hot working of large forgings. The method comprises the following steps: collecting and preprocessing process parameters, quality data and environment information in a multi-source manner, and obtaining hot working characteristic data; performing correlation analysis to construct a process knowledge graph; calculating the distribution of a temperature field, a stress field and an organization field by using a self-sensing multi-field coupling var value neural network; comparing and analyzing to obtain deviation data and correction parameters; adjusting a network parameter optimization prediction result; and executing multi-objective optimization calculation, and generating a whole-process technological parameter and a control instruction. According to the method, full-process multi-physics field coupling calculation from smelting, casting, forging and pressing to heat treatment can be achieved, model parameters are dynamically adjusted according to real-time production data, the optimal process scheme is generated, and therefore the manufacturing quality and efficiency of large forgings are improved.

The invention provides a micro-grid energy-saving scheme generation method and system based on energy storage optimization scheduling, and relates to the technical field of energy storage optimization scheduling, and the method comprises the steps: collecting historical operation data, real-time operation data and external environment data of a micro-grid system, and carrying out the multi-scene prediction through a Monte Carlo simulation method, and generating a multi-scene prediction result; according to a multi-scene prediction result, a fuzzy decision theory and an analytic hierarchy process are adopted, and an optimal microgrid energy-saving scheme is screened out from the solution set; and converting the optimal energy storage scheduling scheme into an intelligent energy-saving operation instruction set, recording a microgrid operation state, an energy storage scheduling result and energy transaction information by using a block chain, calculating a comprehensive performance index based on data recorded by the block chain, and performing distributed evaluation by using a federated learning method according to the comprehensive performance index. And continuously optimizing the micro-grid energy-saving scheme according to the evaluation result of the comprehensive performance index.

The invention provides a photovoltaic station intelligent operation and maintenance simulation method and system based on digital twinning, and relates to the technical field of photovoltaic station operation and maintenance, and the method comprises the steps: constructing a digital twinning hierarchical structure through multi-modal detection signals through discrete wavelet packet transformation, tensor decomposition and a graph neural network, and determining structured data; extracting fault features by using a dynamic neural network, predicting a fault probability based on a Markov model, and triggering maintenance early warning; inputting the early warning signal into a maintenance strategy model based on multi-agent reinforcement learning, and generating a candidate maintenance time window set; the maintenance scheduling module optimizes sorting to obtain an optimal time window sequence, and the resource allocation module generates a personnel material allocation scheme by adopting a genetic algorithm; and iteratively optimizing the strategy parameters based on the maintenance cost, and outputting a final operation and maintenance implementation scheme.

The present invention provides a digital twin simulation method and system for an industrial simulation platform, the method comprising: collecting the operation data of the industrial training production line through a sensor array to obtain a real-time mapping data stream; constructing a digital twin model according to the real-time mapping data stream, using a semantic ontology library and a graph neural network to perform correlation analysis on the multimodal data of the physical space and the digital twin model, and obtaining a twin knowledge graph of the physical-digital dual space; according to the twin knowledge graph and a preset expert knowledge base, using a reinforcement learning method to perform collaborative learning on the operation conditions of the physical-digital dual space to obtain an elastic fault-tolerant boundary; according to the twin knowledge graph and the elastic fault-tolerant boundary, the deviation between the real-time action of the operator in the physical space and the standard action in the digital space is graded and judged, and corresponding feedback and warning information are output. The present invention overcomes the limitations of the existing fixed standard action model and provides personalized guidance for operators with different proficiency levels.

The invention provides a twin power station collision visual simulation method and system based on physical simulation, and relates to the technical field of data processing, and the method comprises the steps: obtaining a three-dimensional geometric model of a twin power station, carrying out space division, extracting geometric parameters, obtaining material data, constructing a material correlation model and a mechanical model, and carrying out fusion to obtain a physical simulation model; acquiring initial collision condition parameters as boundary conditions, performing local grid encryption, constructing a nonlinear kinetic equation of a collision process, performing time domain solution, determining equivalent stress distribution and equivalent plastic strain distribution, and generating a collision result; judging whether plastic deformation or fracture failure occurs, generating full collision process physical field data, generating a collision animation frame sequence, generating a stress distribution cloud picture and a plastic strain cloud picture, constructing a fracture special effect, and comprehensively generating a collision visual scene.

The invention discloses a target echo signal simulation method and system with unmanned aerial vehicle rotor frequency spectrum characteristics, and the method comprises the steps: obtaining an original radar echo signal, carrying out the preprocessing and feature enhancement, and obtaining an enhanced rotor feature signal; sequentially performing dynamic component decomposition, nonlinear phase coupling analysis, adaptive parameter estimation and trajectory prediction to generate probability distribution of a feature trajectory; probability feature space mapping and dynamic feature fusion are carried out to obtain a fusion feature vector; constructing a nonlinear dynamic model, and performing adaptive signal synthesis to generate a synthesized signal; performing quality evaluation on the composite signal to generate a quality evaluation report and an optimization parameter set; based on the quality evaluation report and the optimization parameter set, performing multi-target parameter optimization and monitoring system performance to obtain a performance evaluation result; system parameters are updated, stability analysis is carried out, and a system stability report and regulation and control suggestions are generated. According to the invention, the calculation efficiency and the simulation precision are both improved.

The invention provides a power distribution network reliability cooperative control method and system under distributed power supply access, relates to the technical field of electric power, and designs a power distribution network reliability index system considering a distributed power supply based on a load demand uncertainty model, and adopts a Monte Carlo simulation method. Evaluating the reliability of the power distribution network in combination with the power distribution network reliability index system, and formulating a cooperative control strategy including distributed power supply output control, load demand response management and network topology reconstruction according to an evaluation result; a multi-target cooperative control optimization model with reliability improvement, economical efficiency optimization and environmental benefit maximization as targets is established, the multi-target cooperative control optimization model is solved by adopting an improved particle swarm algorithm, and an optimal cooperative control strategy is generated; and based on the optimal cooperative control strategy, issuing and executing a control instruction to each control object.

The invention discloses a power equipment operation state prediction and anomaly simulation method based on digital twinning, and relates to the technical field of power grid operation. According to the method, through establishment of a digital twinborn model of the power equipment and real-time data analysis, prediction and anomaly simulation of the operation state of the power equipment are realized. The method comprises the following steps of: analyzing a physical structure, operation characteristics and load distribution of power equipment, constructing a digital twin model, performing multi-dimensional analysis on real-time data by utilizing edge calculation, extracting electrical characteristics and behavior patterns, generating an equipment state data set, and constructing an abnormal causal chain model based on the model and the data set. The method comprises the steps of identifying a fault mode caused by uneven load or overload, evaluating the influence of an abnormal state on the stability and efficiency of a power system through virtual simulation and fault propagation analysis, and obtaining an abnormal influence index of power equipment. The accuracy of power equipment fault prediction is improved, the stability and efficiency of a power system are optimized, and support is provided for intelligent operation and maintenance and fault early warning.

The invention discloses a wind field wind resource fine simulation method, system and device based on WRF-CFD medium and micro-scale coupling and a storage medium, and belongs to the technical field of wind energy resource evaluation.The method comprises the steps that mesoscale meteorological analysis data is collected and calculated through a mesoscale WRF numerical simulation technology; performing fitting processing to obtain a fitting function between the wind speed component and the height; extracting wind speed contour information at a micro-scale modeling boundary based on the mesoscale meteorological analysis data and the fitting function, and determining a boundary condition of a micro-scale CFD model; performing directional calculation and correction on the wind speed of each sector by using a virtual anemometer tower; performing grid division on the wind power plant area to generate a refined grid corresponding to the wind power plant area; and driving numerical simulation of the micro-scale CFD model, and carrying out wind power plant regional range stroke resource evaluation. According to the method, the complex characteristics of the wind field can be comprehensively reflected, the wind resource evaluation precision and the calculation efficiency are remarkably improved, and the resource utilization is optimized.

The invention provides an intelligent networked automobile chassis drive-by-wire simulation method and system based on multi-domain modeling, and relates to the technical field of adaptive control, and the method comprises the steps: obtaining structural parameters and kinetic parameters of an intelligent networked automobile chassis, constructing a finite element grid, building a multi-flexible-body kinetic model corresponding to the intelligent networked automobile chassis, and constructing a multi-flexible-body dynamic model corresponding to the intelligent networked automobile chassis; introducing a coupling coordination equation, establishing a multi-flexible-body kinetic equation, and solving to obtain vibration response and stress-strain distribution under different working conditions; generating a plurality of finite element models, performing multi-physical field fusion and multi-error source fusion models, performing online error identification and active compensation, performing all-condition drive-by-wire chassis closed-loop control, and generating a drive-by-wire chassis closed-loop integrated simulation model; constructing a road three-dimensional parameterized model, generating a vehicle-road coupling model, generating a simulation test case, identifying a performance short board, constructing a knowledge graph and an optimization rule base, and generating an optimal control strategy.

The invention relates to the technical field of virtual simulation and human-computer interaction, in particular to a semantic association modeling and self-adaptive simulation method based on multilayer correction, which comprises the following steps of: acquiring characteristic data from a three-dimensional simulation model and an electrical schematic diagram, and generating situation dynamic model data through data cleaning and standardization processing; constructing a semantic incidence matrix based on the situation dynamic model data, generating a geometric layer model, a logic layer model and a cross-domain layer model, and generating dynamic state and logic state data through distributed cellular automaton simulation; and in combination with simulation data, optimizing a semantic incidence matrix and a dynamic modeling rule by utilizing a causal path inference algorithm and a multi-layer correction mechanism, and realizing state linkage and user interaction feedback of the three-dimensional simulation model and the electrical schematic diagram. The state synchronization accuracy and interaction efficiency of the complex system are remarkably improved, and the method is suitable for the fields of industrial design, simulation verification and teaching training.

The invention provides a digital twinborn simulation method for an automatic verification system of an electric energy meter, and belongs to the technical field of electric energy meters, and the method comprises the steps: S1, collecting the multi-modal data of the electric energy meter in real time; s2, based on a multi-scale convolutional neural network, deep features of the multi-modal signal data are extracted, and a digital twinborn model is constructed; s3, operating the digital twin model in the virtual environment, simulating the verification process of the electric energy meter, and monitoring the equipment state in real time; and S4, inputting the implicit state representation into the graph convolutional network, constructing a fault relation network of the electric energy meter verification system, analyzing fault causes through the graph convolutional network, obtaining a comprehensive analysis report based on output of fault prediction and diagnosis, and optimizing an electric energy meter verification process by using a multi-arm tiger machine model. The digital twinning technology is fully utilized, the actual operation state of the electric energy meter is simulated in the virtual environment, real-time synchronization of the physical entity and the virtual model is achieved, and the intelligent level and the management efficiency of the system are effectively improved.

The invention discloses an urban inland inundation water recession process numerical simulation method and system based on physical-data fusion, and belongs to the technical field of urban flood control and intelligent water affairs. A hydraulic model and a data driving model are fused, a prediction result is dynamically weighted through gating attention, and real-time correction is performed by using Kalman filtering; the method comprises the steps of multi-source data fusion and enhancement, wherein data collection and processing are carried out, space-time alignment is achieved, and feature construction is carried out; mechanism and mathematical double-engine collaborative prediction: collaborative prediction is carried out based on a physical model engine and a data driving engine, and adaptive fusion is realized; online reasoning and dynamic correction, including Kalman filtering dynamic correction and extreme scene emergency processing; and performing model evaluation and iteration. According to the method, the problem of high-precision prediction of the recession time and the ponding range in a complex urban environment is solved, the generalization ability of the model in non-seen scenes such as pipeline blockage and rainstorm extrapolation is improved, and a reliable decision basis is provided for urban inland inundation emergency scheduling and drainage facility optimization.

The invention discloses an enterprise operation global analog simulation method based on digital twinning. The method comprises the following steps: S1, collecting and preprocessing multi-source heterogeneous data; s2, constructing an enterprise operation digital twinning model, and defining an optimization objective function and constraint conditions; s3, optimizing the model by adopting a sea elephant optimization algorithm, and dynamically adjusting structural parameters, control variables and strategy configuration; s4, multi-scene simulation drilling is carried out based on the optimization model, and enterprise operation prediction results under different strategies are obtained; s5, evaluating and comparing key performance indexes corresponding to the strategies, and determining an optimal service configuration scheme; and S6, deploying an optimal service configuration scheme, collecting feedback data, and dynamically updating the model. According to the method, the enterprise operation digital twin model which can be optimized, simulated and fed back is constructed, so that operation simulation and optimal business scheme output under multi-strategy configuration are realized, and the enterprise decision-making intelligence level and the operation efficiency are improved.

The invention provides a numerical simulation method suitable for a three-dimensional spherical flame, and belongs to the field of electrical data processing, and the method comprises the steps: building a computational domain model according to the requirements of a computational scene, dividing a grid unit, and obtaining the node information of the required grid unit; establishing a Navier-Stokes equation set of a coupling chemical reaction and diffusion process model; estimating convection and diffusion term variable gradients in the conservation equation; calculating a time step length according to a set Kulang number, and carrying out time advancing; estimating an expected value of a velocity field, and solving a predicted velocity; the divergence of the velocity field and the correction value of the pressure field are calculated; obtaining a corrected velocity field; a self-adaptive grid means is introduced to dynamically adjust the grid resolution; performing iterative correction for multiple times until the velocity field and the pressure field converge to convergence conditions; performing spherical flame numerical simulation, and monitoring the convergence of the solution. According to the invention, the flame dynamics and cellular instability of the premixed spherical expansion flame can be reproduced.

The invention discloses an antenna polarization simulation method based on phase and amplitude calibration, and the method comprises the steps: collecting original data, carrying out the preprocessing, and obtaining the preprocessed original data; constructing an initial calibration model, and generating a calibrated lookup table; obtaining a target polarization parameter, and calculating a Stokes parameter; constructing a Mueller matrix, and determining an ideal polarization state; constructing a closed-loop control system to obtain a monitoring result; constructing a polarization parameter adjustment strategy, executing multi-objective optimization, and generating an optimized polarization parameter; acquiring position information of each antenna, and constructing a multi-antenna system model; a distributed optimization algorithm is used to obtain a coordination result, a space diversity strategy is realized, and polarization control parameters are generated; and generating a final polarization control parameter by using a beam forming technology. According to the invention, the universality of the system is improved, the precision and reliability of polarization simulation are improved, the adaptability and stability of the system are enhanced, the complexity of real-time calculation is reduced, and the response speed of the system is improved.

Disclosed in the present invention is a non-autoregressive Transformer-based modeling method for a 4-level pulse amplitude modulation high-speed transmitter. The method involves establishing a deep learning model having an encoder-decoder architecture to predict the behavior of a 4-level pulse amplitude modulation transmitter. An encoder processes unordered non-sequential inputs, including an input signal parameter and link parameters, to generate a context vector and then transmit same to a decoder. The decoder uses both the context vector generated by the encoder and a transmitter output signal sequence to generate a categorical probability distribution for each point in the sequence one by one. The model is trained using a random masking strategy, and inference is performed by means of non-autoregressive decoding and filtering, so that the model can perform parallel prediction on an output sequence, and perform a filtering process to predict an output signal. Compared to traditional simulation methods, the present invention achieves a significant acceleration effect, particularly when processing multi-link systems.

The invention provides an AI flood real-time simulation method for urban hydrological multi-physics field decoupling supervision, and the method comprises the steps: constructing an intelligent physical prediction model of urban flood, carrying out the layered decoupling of an urban hydrological hydrodynamic system, separating a one-dimensional drainage pipe network submodule from a two-dimensional surface flood module, designing a multi-scale physical constraint loss function for different links, and carrying out the real-time simulation of the AI flood. Microcosmic, mesoscopic and macroscopic multi-scale physical constraint fusion is realized, and residual constraints of the Saint-Venant equation are embedded in a neural network agent of a drainage system in a microcosmic level; in the mid-level, embedding the residual constraint of the shallow water equation in the surface flood routing system; in the macroscopic level, the water balance constraint of the whole system is realized; urban hydrology and hydrodynamic force are decoupled, and multi-scale physical field supervision constraint is achieved.

The invention relates to the technical field of artificial intelligence, and discloses a multi-agent social network simulation method and system based on a cognitive inference chain, and the method comprises the steps: initializing a multi-agent system comprising a social environment engine, a user portrait engine and a cognitive inference engine, executing a multi-agent social network simulation cycle of a preset round of iteration, in each iteration round, the social environment engine pushes social information to the intelligent agent as external stimulation and activates the intelligent agent to execute an independent decision, the cognitive state of each dimension in the cognitive reasoning chain is updated through large language model reasoning, corresponding social behaviors are generated, and the social behaviors and corresponding cognitive state tracks are recorded; and periodically analyzing historical records to optimize influence coefficients among all cognitive dimensions of the cognitive inference chain, and adjusting an inference strategy of a preset large language model. The simulation of the cognitive process of the intelligent agent is a transparent and traceable evolutionary process, and the complete and understandable simulation of the'observation-cognition-behavior 'cycle is realized.

The invention relates to the technical field of distributed simulation based on containerized deployment and elastic expansion and contraction, and discloses a distributed simulation method and system based on containerized deployment and elastic expansion and contraction. According to the distributed simulation method and system based on containerized deployment and elastic expansion, real-time resource monitoring and historical load trend data of a simulation task are collected, and unified load evaluation is carried out in combination with a simulation calculation complexity parameter and an I / O density parameter; the refined modeling and resource demand pre-judgment of the simulation task are realized, and the accuracy of task scheduling and allocation is improved; modularized deployment of simulation tasks is achieved through subtask segmentation based on minimum executable units and a standard containerization packaging mechanism in cooperation with a container arrangement platform, and then concurrent execution and elastic scheduling in a multi-node environment are supported.

The invention discloses a UE5-based dynamic simulation method for digital twin flood inundation of small and medium-sized watersheds. The method comprises the following steps: 1, constructing a two-dimensional hydrodynamic numerical model; step 2, creating a flood inundation simulation UE5 plug-in project; step 3, creating a flood role class; 4, constructing a method for drawing triangular mesh primitives of the flood model; 5, constructing a flood hydrological feature and flood flow state rendering method; and 6, realizing a dynamic simulation process of digital twinborn flood submerging. According to the invention, dynamic rendering and high-fidelity visualization of an ultra-large data volume flood model in a small and medium-sized basin digital twinning three-dimensional scene are realized, and multi-dimensional flood inundation numerical simulation results of water level, water depth, flow velocity, flow direction and the like and complex flood flow states of backflow, convergent flow, bifurcated flow, overflat flow, turbulent flow and the like are expressed; the authenticity and accuracy of flood inundation simulation are improved, and the flood risk assessment and flood control plan decision support capability of small and medium-sized drainage basins can be enhanced.

The invention discloses an establishment method of a rock multi-field coupling model and the model thereof, and belongs to the technical field of engineering geological survey. Through comprehensive application of multi-scale modeling, a nondestructive testing technology, a machine learning algorithm and intelligent optimization, the problems that existing multi-physical field coupling analysis is not deep enough, the precision of an observation method is poor, and a device is prone to being damaged are solved, the advantages of various observations are combined, the building and analysis precision of a rock multi-field coupling model is improved, and the rock multi-field coupling analysis precision is improved. The method has the advantages that the method is simple and convenient to operate, the intelligence and automation level of the model is enhanced, microstructure data and macroscopic response are combined, deeper understanding of rock behaviors is provided, meanwhile, more accurate and efficient decision support can be provided for rock engineering design and construction, and the method is worthy of popularization and application. And a novel analysis and simulation method is provided for the field of rock mechanics research. Through the comprehensive scheme, behaviors of rocks under complex geological conditions can be better predicted and managed, so that the safety and economical efficiency of engineering are improved.

The invention provides a tunnel grouting dynamic adaptive simulation method and system based on multi-physics field coupling, and belongs to the technical field of grouting simulation, and the method comprises the steps: obtaining original geological information, constructing a three-dimensional geological geometric model and a fracture network, constructing a multi-physics field coupling mechanism, and carrying out discrete solution; further predicting slurry diffusion and crack filling to obtain an isobaric envelope diagram and an early warning area, and simulating a grouting process; acquiring real-time sensor data, inputting the isobaric envelope diagram, the early warning area and the real-time sensor data into an adaptive parameter prediction model, dynamically updating the weight of the adaptive parameter prediction model according to the change of the real-time sensor data by adopting rolling training to obtain a prediction index, and constructing a feedback control chain based on the prediction index. Determining an optimal grouting parameter combination by adopting a particle swarm optimization algorithm; and the optimal grouting parameters are fed back to the simulated grouting process for automatic parameter adjustment, and the optimized grouting strategy is executed. The intelligent numerical values of the grouting parameters can be dynamically and adaptively adjusted.

The invention discloses a road protection multi-scene coupling simulation method and system based on digital twinning, and relates to the field of electric digital data processing, and the method comprises the steps: collecting dynamic response data (strain, acceleration and displacement) of a traffic protection facility through multiple sensors, and building a scene feature library containing vehicle collision, wind load and seismic waves; and projecting response data to a unified time axis, identifying a multi-scene overlapping interval, and determining an action sequence and duration. Primary and secondary scenes are judged according to scene action parameters, and mechanical correction values and standard response parameters are extracted. And establishing a digital twinborn model for coupling simulation to obtain a stress distribution condition, evaluating a structural damage level and generating a safety performance report. By implementing the method, the deviation between the mechanical property simulation result of the protection facility and the actual working condition can be reduced.

Provided in the present invention is a thermal stress simulation method for a laminated structure. The simulation method comprises: importing a simulation model; creating a heat dissipation simulation process; completing relevant settings of a model heat source device; setting a thermal analysis simulation environment; activating a thermal stress analysis option, and selecting the type of fixed support; completing thermal-stress coupling simulation analysis; checking a post-processing result; and modifying a layout design according to the post-processing result. A potential structural risk of an electronic product can be predicted by means of thermal stress simulation, the situations of a temperature field, a stress field and a deformation field of an analysis object are obtained by means of finite element analysis, and theoretical research and an experimental test are effectively verified and supplemented, thereby rapidly implementing the verification and iteration of a product.

The invention discloses an HIL simulation method for an underground mining whole process, and relates to the field of automatic driving simulation testing, and the method comprises the steps: collecting point cloud data of an underground scene, and generating a simulation scene in a CARLA format; compiling and importing the generated simulation scene in the CARLA format through a Unreal engine, building a vehicle model and a laser radar sensor model in a Carla simulator, and collecting a point cloud data packet of the simulation scene; according to the point cloud data packet, mapping is carried out through an SLAM algorithm, and a point cloud map in a PCD format is generated; constructing a map of the simulation scene according to the PCD point cloud map; building a hardware-in-the-loop HIL simulation platform comprising an upper computer, a lower computer and an execution mechanism; and loading the constructed map of the simulation scene to the constructed hardware-in-the-loop HIL simulation platform, simulating a real well working condition scene through the simulation platform, and verifying a well working condition unmanned driving algorithm. In order to solve the problem that unmanned driving tests are difficult to comprehensively evaluate in the prior art, the coverage rate of the tests is increased through a hardware integrated full-process closed loop and the like.

The invention belongs to the technical field of pollutant diffusion simulation, and particularly relates to a pollutant diffusion simulation system and method based on a time effect. The system comprises a meteorological data acquisition module, a pollutant diffusion module, a time effect conversion module and a simulation analysis module, the meteorological data acquisition module is used for acquiring meteorological data and preprocessing the acquired data; the pollutant diffusion module is used for acquiring a three-dimensional Gaussian diffusion model changing along with time based on the Gaussian diffusion model of the continuous point source; the time effect conversion module is used for establishing a coordinate system by taking the current downwind direction as an x axis when the wind direction and the wind speed in the meteorological data are changed, acquiring a conversion relation between a reference coordinate system and a coordinate system at the current calculation moment, and performing conversion of a three-dimensional Gaussian diffusion model by utilizing the conversion relation; and the simulation analysis module is used for calculating the concentration of the pollutants according to the converted three-dimensional Gaussian diffusion model so as to realize a pollutant diffusion simulation system.

The invention discloses an interactive simulation method for calculating aging parameters of a superconducting cable and a superconducting cable system.The system comprises the steps that a cable body electromagnetic transient model, a cooling system transient thermal model and a three-dimensional multi-field finite element model are built, and cable material characteristics, environment parameters and operation condition data are input; a model interaction interface is constructed through a simulation platform, data interaction and coupling among multiple models are realized, simulation parameters are dynamically adjusted, accurate matching of model step length and dynamic characteristics of the system is ensured, and aging parameters of the superconducting cable system under complex working conditions are calculated. According to the method, the operation state of the superconducting cable is evaluated by analyzing the mixed data, aging analysis of the superconducting cable system under multiple working conditions is carried out, and decision support is provided for system maintenance.