46 results about "Particle simulation" patented technology

The invention discloses a non-uniform and conformal grid-oriented electromagnetic particle adaptive simulation method and system, and relates to the technical field of electromagnetic particle simulation. The method comprises the following steps: performing non-uniform right-angle mesh generation based on a charged particle average free path, and identifying conformal mesh units; carrying out initialization by adopting macro particles; executing electromagnetic field propulsion, field interpolation, particle propulsion, charge current backfilling and collision simulation in each time step; and accelerated calculation is realized through a CPU and GPU hybrid parallel architecture. Through the method, the numerical simulation precision can be improved, the adaptability of complex geometry is enhanced, the coupling stability of the electromagnetic field and the particles is ensured, the information interaction between the field and the particles is improved, and the large-scale calculation efficiency is improved.

This application relates to a physical special effect rendering method performed by a computer device. The method includes: obtaining physical special effect data of physical special effect particles emitted by a particle emission plug-in in a previous frame; obtaining a first target instance obtained by instantiating a scene management class; invoking, through the first target instance, a scene manager of a particle simulation tool to calculate motion state information of the physical special effect particles in a current frame based on the physical special effect data in the previous frame; and updating the physical special effect data in the previous frame based on the motion state information of the current frame to render a physical special effect in the current frame.

The invention discloses a coal mine methane emission estimation method based on backward Lagrange random particle simulation. The method comprises the following steps: S1, acquiring satellite methane concentration monitoring data, meteorological data, EDGAR emission list data and GFEI global fuel development emission list data of a research area; s2, selecting a pixel as an observation point, obtaining an influence factor of methane emission of a virtual emission point pixel on the methane concentration of the observation point pixel through a backward Lagrangian random particle simulation model by utilizing meteorological data to reversely track the motion trail of particles, and constructing a source receptor matrix according to the influence factor; s3, the Bayesian methane emission estimation model carries out observation and prior constraint based on the objective function to obtain posterior emission data of the research area. According to the method, the source receptor matrix is constructed by using the motion trail of the meteorological data reverse tracking particles, and the Bayesian methane emission estimation model performs observation and prior constraint based on the target function to obtain posterior emission data of the research area, so that high-precision methane emission inversion estimation of the coal mine in the research area is realized.

The invention relates to the technical field of fire safety and simulation training, and discloses a rule-driven fire-fighting real smoke and real fire training simulation system, which comprises a data acquisition and modeling module, a rule driving module, a rendering output module and a training evaluation module. The data acquisition and modeling module is used for acquiring initial fire data and constructing a reference model of smoke diffusion and fire spreading; the rule driving module simulates the non-synchronous evolution process of the fire through a particle simulation algorithm, a time coordination rule and a feedback loop algorithm; the rendering output module is used for integrating the environment rendering data and the multi-factor propulsion mode and generating a training effect evaluation index; and the evaluation optimization module judges whether the simulation precision of the reference model reaches a preset standard or not according to the training effect evaluation index until a simulation result meeting a precision requirement is obtained. According to the invention, the reality and accuracy of fire-fighting simulation training are improved.

The invention relates to the technical field of computer rendering, and discloses a dynamic effect processing method and device, electronic equipment and a program product, and the dynamic effect processing method provided by the invention simulates a flame effect in a virtual scene through combustion bitmaps of multiple cycles, and avoids uncertainty of a diffusion range caused by simulation of flame diffusion through particles. Meanwhile, as the combustion bitmap is used for simulating diffusion, flame diffusion simulation can be carried out without calculating the track and the drop point of each particle through a CPU, and the CPU pressure caused by the fact that a large number of particles in a particle system need to be simulated in the related technology is solved. In the rendering process, a map does not need to be added for each particle, the corresponding position in the virtual scene is directly rendered according to the combustion bitmap, the rendering process and the simulated flame diffusion process are separated, the occurrence of a large number of particles is reduced, and the load of the GPU can be reduced.

The application provides a heterogeneous cooperative path planning method for a marine floating object target search task. A Parcel v2 particle simulator based on a Lagrange framework is used to predict the future trajectory and position of a plurality of particles according to real sea waves, ocean currents, wind fields and other information, and then a Parzen window method based on a Gaussian kernel function is used to obtain a target probability map. In the traditional GBNN method, the regional centroid and motion constraint are added to improve the external stimulation value of the neuron to plan the cooperative search path of the plurality of unmanned ships, so that the local optimum can be effectively avoided and the search efficiency is improved. A solar unmanned aerial vehicle is used as a communication relay of the plurality of unmanned ships, an optimal communication network connection is obtained by using a minimum spanning tree, and then the path of the unmanned aerial vehicle is planned. The application can improve the method for solving the marine search target of the plurality of unmanned ships, so as to improve the efficiency of the marine search target of the unmanned ships.

The invention discloses a GPU (Graphics Processing Unit) parallel thread block adjustment and kernel function scheduling optimization method and system. The method comprises the following steps: acquiring GPU equipment attributes and kernel function execution attributes; determining a feasible thread block size solution space of each kernel function based on GPU equipment attributes and kernel function execution attributes, and selecting a thread block size which enables the load balance degree evaluation model value to be maximum as optimal execution configuration of the kernel function; on the basis of the determined optimal thread block size of each kernel function, dividing an execution grid of each kernel function into a plurality of kernel function slices, and establishing a concurrent execution relationship between the kernel functions; a CUDA graph is constructed in a mixed mode according to the established concurrent execution relation between the kernel functions and data dependence; and by taking an actual model of particle simulation software as a test object, respectively comparing GPU occupancy rates before and after thread block adaptive adjustment, multi-stream concurrent scheduling and hybrid CUDA graph scheduling optimization, kernel function execution time and overall simulation efficiency, and outputting an optimized particle simulation result.

The invention relates to a preparation and performance optimization method of a heat-conducting silica gel film based on aluminum nitride filler in the technical field of new materials, which comprises the following steps: acquiring an aluminum nitride filler particle image through a scanning electron microscope, and extracting particle size and shape characteristics from the image to obtain initial particle size distribution data; according to the initial particle size distribution data, a particle simulation algorithm is adopted to calculate the distribution mode of the filler in a silica gel matrix, and the position of a potential agglomeration area is determined; acquiring an image of a contact interface between the modified particle sample and a silica gel substrate, and judging an interface bonding strength index; simulating a heat transfer path between the modified particles and a matrix through an interface optimization algorithm to obtain optimized interface bonding parameters; adjusting a filler mixing ratio and stirring conditions according to the optimized interface bonding parameters; integrating the final performance data and the initial particle size distribution data by adopting a data fusion method, and judging a long-term reliability index; and processing the long-term reliability index through iterative circulation to obtain stable heat conduction efficiency configuration.

The application discloses a kind of SPH steady flow processing method and related equipment, method includes the input entrance pressure data is converted into entrance speed data;Entrance speed data is based on setting virtual particle;And the data information of fluid particle is updated by the interaction between virtual particle and the fluid particle to be processed, and fluid particle data is judged based on setting parameter threshold, and the particle field information of output is obtained.The application embodiment can be converted into entrance speed data by the entrance pressure data, and virtual particle is set to simulate fluid particle, reduce the speed shock and data noise caused by particle simulation calculation based on entrance pressure, reduce the accumulation of entrance particle simultaneously, improve the stability of entrance boundary, so as to improve the convergence speed and processing efficiency of steady flow simulation.The application can be widely applied in computer simulation and data processing technical field.

This invention discloses a simulation method for a finite-space gas leakage particle system based on velocity field pre-calculation, comprising the following steps: obtaining physical field pre-calculation results from finite element gas simulation software, the physical field pre-calculation results including non-uniform mesh data; homogenizing the non-uniform mesh data to obtain homogenized mesh data; performing coordinate axis transformation between the leakage source location and the simulation scene location; calculating velocity field data based on the homogenized mesh data, and driving the gas diffusion particles to perform motion simulation based on the velocity field data. This invention, by obtaining pre-calculation results through finite element gas simulation software, homogenizing the non-uniform mesh data, and calculating velocity field data based on the homogenized mesh data to drive the gas diffusion particle simulation, can effectively improve the current situation of gas simulation systems characterized by complex data processing algorithms, large computational load, poor simulation results when the mesh distribution is uneven, and poor data visualization.

The invention discloses a method for quantitatively characterizing three-dimensional parameters of surface particles of a polymer-based nanoparticle composite material. Comprising the following steps: acquiring a scanning electron microscope backscattered electron image of a sample; generating particle simulation back scattering electron images with different three-dimensional sizes and different depths on the surface layer of the material; respectively extracting image data of particles in the scanning electron microscope back scattering electron image and the Monte Carlo simulation back scattering electron image; respectively constructing numerical models of particle back scattering electron image data simulated by the Monte Carlo method and particle three-dimensional size and depth; predicting to obtain the three-dimensional size and depth data of the particles; and combining the predicted particle depth data with the two-dimensional coordinates of the particles in the scanning electron microscope back scattering electron image to obtain the three-dimensional space positions of the particles. The method is suitable for providing reliable data support for uniformity evaluation of surface particles of the polymer-based nanoparticle composite material, material performance optimization and industrial quality control.

This invention provides a method, apparatus, electronic device, and medium for determining contact force in particle motion simulation, belonging to the field of particle simulation. The method includes: acquiring a particle model to be simulated, the particle model including multiple nodes; performing surface reconstruction processing on the surface of the particle model to obtain a reconstructed surface; setting multiple background points on the reconstructed surface; for a target particle model, determining the contact force generated by other particle models on the target particle model based on the background points of the reconstructed surface of the target particle model and the nodes of other particle models; and performing particle motion simulation on the target particle model based on the contact force. This invention improves computational efficiency while ensuring the accuracy of particle simulation by performing surface reconstruction on the mesh surface of the particle model to obtain a smooth reconstructed surface, and then setting multiple background points on the reconstructed surface. The contact force is solved by the relationship between the background points and nodes.

The application discloses an implicit particle simulation analysis method for atmospheric pressure micro-scale arc discharge dynamics characteristics, and specifically comprises the following steps: step 1, uniformly dividing a calculation region into grids, and placing a plurality of charged simulation particles with initial positions and velocities in each grid; step 2, calculating charge density and current density on each grid node; step 3, calculating potential and electric field distribution on each grid node; step 4, calculating force on the charged simulation particles and updating coordinates and velocities of the charged simulation particles; step 5, calculating new velocities after collision based on collision theory; and step 6, taking the updated coordinates and velocities as the coordinates and velocities in step 2, and repeating steps 2-6 in a time step until a set iteration number is reached. The application solves the problem that in the prior art simulation technology, time and space steps must be small enough to distinguish Debye length and oscillation period of electrons, thereby significantly increasing simulation time.

The invention discloses a low-pressure plasma particle simulation method based on a variational auto-encoder, and the method comprises the following steps: firstly, building a plasma particle model which is used for generating a data set needed by neural network training; constructing a neural network framework based on a variational auto-encoder to reconstruct a source field of the model and derive a corresponding solution field; designing a loss function according to a closure relationship of the neural network, and optimizing hyper-parameters of the neural network; and training the network until the loss function converges to a predetermined threshold. According to the method, the source field of the plasma particle model can be accurately reconstructed, and the solution field can be accurately solved. Compared with a traditional particle simulation method based on a neural network, the problems that a complex source field is difficult to express and the equation solving precision is insufficient are effectively solved, and the accurate mapping relation can be efficiently trained through limited sample data.

According to the model and the simulation method for emitting the microscopic hot electrons to the macroscopic electromagnetic pulse, particle simulation and three-dimensional electromagnetic field simulation are innovatively coupled, and full-chain integrated simulation from microscopic particle dynamics to macroscopic electromagnetic radiation is realized; the technical problem that a micromechanism and macroscopic performance are disjointed in a traditional simulation method is effectively solved; meanwhile, the method has good universality and adaptability, and influences of multiple factors such as laser parameters, target material characteristics and experimental environments can be fully considered. By adjusting simulation parameters, electromagnetic pulse characteristics under different experiment conditions can be accurately predicted, and reliable theoretical guidance is provided for optimizing an experiment design scheme. The method is not only suitable for performance evaluation of an existing laser device, but also can provide technical support for electromagnetic pulse management of a higher-power laser device in the future.

The invention discloses a testing device and method for simulating coupling ignition of forest fire heat radiation and flying fire particles in a boundary region to ignite liquid fuel. Comprising a flying fire particle simulation system, a heating sheet loading system, a heat radiation generation system, a fuel pool loading system, an environmental wind simulation system, a water bath heating / cooling system, a thermal characteristic parameter measurement system, an image data measurement system, a high-speed infrared measurement system and the like. According to the method, the physical process of igniting the combustible liquid by coupling the flying fire particles and thermal radiation in the forest-town boundary fire can be accurately reproduced; the dynamic characteristics, including critical evaporation rate and ignition heat flow of liquid fuel under the coupling action of different flying fire particles and thermal radiation, and ignition delay time, ignition temperature and other key parameters when the ignition heat flow is greater than a critical threshold value, of the combustible liquid storage tank in a boundary region can be quantitatively studied; and basic data support is provided for risk assessment and prevention and control strategies of the forest fire ignition liquid storage tank in the boundary region.

The invention discloses a network fault troubleshooting method, device and equipment, a storage medium and a computer program product, and the method comprises the steps: constructing a multi-layer circular ring map model, receiving abnormal data, and positioning an abnormal point; identifying a specific fragmentation behavior of a circle layer where the abnormal point is located, and determining a troubleshooting direction through behavior force analysis; monitoring an interaction path between a control plane and a resource plane in the target circle layer, and determining a troubleshooting strategy; and screening the target node, and migrating the fault task to the target node. According to the method, abnormal points are positioned to corresponding ring layers in a multi-layer ring structure by using same-entropy representation space mapping, the troubleshooting path and direction of a fault are determined by identifying the propagation trend of specific fragmentation behaviors of each layer, on this basis, an anti-fragility load mechanism is introduced, and on the basis of disturbance particle simulation and anti-fragility index evaluation, the fault detection accuracy is improved. And optimal embedding points are selected to deploy task twin bodies, particle hedging takeover of fault tasks is achieved, finally, the closed-loop condition is judged and repaired through state consistency hash, and the stability of the system is ensured.

The application discloses a low-pressure plasma particle simulation method and system based on operator learning, and relates to the technical field of low-pressure plasma. The application comprises the following steps: constructing a plasma particle model, giving a training task set and a task target set of the plasma particle model; constructing an operator neural network based on operator learning based on a field equation of the plasma particle model, designing corresponding constraint conditions and a loss function, and selecting appropriate neural network parameters; training the constructed operator neural network, ending the training after the loss function value gradually converges to a set value; and taking the trained operator neural network as a field equation solver of the plasma particle model to calculate and output simulation results of the plasma particle model. The application can significantly improve the simulation efficiency of the particle model under the condition of the same model structure and different parameters, and overcomes the defects of the traditional particle simulation method, such as dependence on a large number of iterations for field equation solving and high calculation cost.

The application relates to the technical field of reactor physics calculation, and discloses a particle simulation transport system and method for simplifying an input process, the system comprising: a front-end modeling system configured to introduce a WebGL-based Three.js library as a 3D engine, perform three-dimensional modeling, and generate a particle simulation model; wherein the particle simulation model at least comprises a geometric body, a radiation source and a detector; a front-end parameter setting system configured to set MCNP parameters of the particle simulation model; and a back-end calculation system configured to introduce a Django framework to constitute a network server, convert the particle simulation model and the MCNP parameters into an MCNP input file by using the Django framework, and perform simulation calculation according to the MCNP input file. The application models the particle simulation model in the Three.js library, sets parameters for the model, converts the particle simulation model and the corresponding parameters into the MCNP input file, simply generates the MCNP input file, and thus can perform MCNP simulation calculation.

The invention provides a particle simulation method and device, electronic equipment, a storage medium and a program product, and the method comprises the steps: determining a particle distance between a first particle and a second particle according to the first position information of the first particle and the second position information of the second particle, the first particle and the second particle are any two of a plurality of simulation particles to be analyzed in a simulation task; according to a preset truncation radius interval and the particle distance, determining an interaction weight between the first particle and the second particle; determining an acting force between the first particle and the second particle based on the interaction weight; and executing the simulation task according to the acting force among the plurality of simulation particles to obtain a simulation result of the simulation task. According to the embodiment of the invention, the accuracy of acting force between particles can be ensured, and the accuracy of a particle simulation task is improved.

This invention discloses a full-process physical simulation method and platform for a charged particle waveform acquisition system, used to provide waveform datasets of charged particles. The method includes: using the high-energy physics simulation software Geant4 for particle simulation and energy deposition calculation, outputting energy deposition data including different depth positions; based on the energy deposition data, using the silicon microstrip detector simulation software WeightField2 for carrier generation and transport simulation, outputting a detector induced current map; and based on the detector induced current map, using LTSpice software to simulate the preamplifier circuit, outputting the complete output waveform of the charged particles. This invention provides a low-cost, high-efficiency solution, enabling particle identification algorithms to be optimized and trained with richer waveform data. It effectively overcomes the problems of insufficient sample size and high experimental costs in existing technologies, improving the accuracy and practicality of charged particle identification.

The application relates to the technical field of particle simulation, and discloses a particle collision method, device and equipment based on physical simulation and a storage medium, the method comprises the following steps: determining current parameters of each particle in a particle system based on initial parameters and external force parameters of each particle; detecting collision information between each particle and / or collision information between the particle and other objects in the particle system through a collision detection algorithm; and updating target collision parameters of each particle based on a collision model, the current parameters and the collision information. In the foregoing manner, the initial parameters and the external force parameters of the particles are considered to more accurately simulate the motion state of the particles under the action of force, a preset collision detection algorithm is used to detect the collision information between the particles and between the particles and other objects in the system, the simulation effect is more realistic, powerful technical support is provided for simulating complex physical phenomena, and the accuracy of the particle collision effect is improved.

The invention relates to the technical field of particle simulation in a flash copper smelting process, in particular to a coalescence and separation criterion method for high-temperature viscous-elastic particles in flash copper smelting and a particle size prediction method. The correlation between force balance and speed during contact and separation of the particles is considered, and a mathematical criterion for coalescence and separation of the viscous-elastic particles after collision is established. Besides, on the basis of the characteristic that the phase state of the particles changes along with the temperature, the particles are divided into three stages of elasticity, viscosity-elasticity and viscosity, a CFD-PBM simulation method is utilized, and the established mathematical criterion of particle coalescence and separation is introduced, so that numerical simulation of particle temperature rise phase change-collision coalescence in the flash copper smelting process is achieved; the result shows that the model can effectively predict the evolution rule of the particle size of the particles in the flash furnace.

The invention relates to the technical field of meteorological particle simulation, in particular to a Beidou grid-based local micrometeorological particle simulation system, which comprises a Beidou grid positioning module used for performing regular grid division on a ground space of a preset local area according to a Beidou satellite navigation system; the multi-source data acquisition module is used for acquiring meteorological data of the target area according to preset meteorological data acquisition equipment to obtain multi-source meteorological data; the data preprocessing module is used for preprocessing the multi-source meteorological data in a data processing center; the meteorological particle model construction module is used for constructing a meteorological particle model; and the micrometeorological particle simulation module is used for carrying out dynamic simulation analysis on meteorological elements in each three-dimensional grid unit in the meteorological particle model. According to the method, the requirement of local micrometeorological simulation for spatial scale fineness can be accurately adapted, accurate conversion from meteorological data to particle attributes is realized, and the accuracy of local micrometeorological dynamic evolution simulation is improved.

The application provides a splash behavior simulation method and device of a laser selective melting process, and a medium, and belongs to the field of metal material additive technology. The method comprises the following steps: forming a simulation flow field by simulating the flow field in a forming cavity used in a fluid dynamics simulation experiment; determining particle parameters of an experimental splash according to a splash experiment image, and determining initial conditions of particle simulation spraying according to the particle parameters; setting a spraying area in the simulation flow field, and controlling a particle spraying simulation source to emit particles meeting the initial conditions; tracking each splash particle in the simulation flow field by using a discrete phase model, and obtaining a splash trajectory of the splash particle according to the initial conditions; setting a capture boundary condition, and determining a removal rate of the splash particle according to the splash trajectory and the capture boundary condition; setting a region of interest, and statistically analyzing a distribution trend of the splash particle in the region of interest according to the splash trajectory. The splash behavior in an LPBF processing process is simulated and analyzed, so that the influence of the splash on the quality of a formed part is reduced.

The application discloses a non-uniform and conformal grid-oriented electromagnetic particle adaptive simulation method and system, and relates to the technical field of electromagnetic particle simulation. The method comprises the following steps: performing non-uniform right-angle grid division based on the average free path of charged particles, and identifying conformal grid units; adopting macro particles for initialization; performing electromagnetic field propulsion, field interpolation, particle propulsion, charge and current backfilling and collision simulation in each time step; and realizing accelerated calculation through a CPU and GPU hybrid parallel architecture. Through the application, the numerical simulation precision can be improved, the adaptability of complex geometry can be enhanced, the stability of electromagnetic field and particle coupling can be ensured, the information interaction between the field and the particles can be improved, and the large-scale calculation efficiency can be improved.

The application discloses a programmable logic device, a bonding force calculation method and a verification platform. The programmable logic device comprises: a block random memory configured to store a plurality of boxes, the plurality of boxes corresponding to a plurality of unit spaces divided by a three-dimensional space occupied by a simulated organic compound, and the box comprising a plurality of simulation particles, the simulation particles being used to represent particles of the organic compound in the corresponding unit space; a logic controller configured to traverse the boxes in the block random memory, and obtain simulation particle information of each simulation particle contained in the current box from a current box currently traversed; a bonding force calculator configured to obtain each simulation particle from the logic controller, and calculate each bonding force of the corresponding simulation particle according to the simulation particle information of each simulation particle; and a write-back device configured to write back the total bonding force corresponding to each simulation particle to the corresponding simulation particle in the block random memory according to the identification of each simulation particle.

The application relates to the technical field of meteorological particle simulation, in particular to a local micro-meteorological particle simulation system based on a Beidou grid, which comprises a Beidou grid positioning module, a multi-source data acquisition module, a data preprocessing module and a micro-meteorological particle simulation module. The Beidou grid positioning module is used for regularly dividing the ground space of a preset local area into grids according to a Beidou satellite navigation system. The multi-source data acquisition module is used for collecting meteorological data of a target area according to a preset meteorological data acquisition device to obtain multi-source meteorological data. The data preprocessing module is used for preprocessing the multi-source meteorological data in a data processing center. The meteorological particle model construction module is used for constructing a meteorological particle model. The micro-meteorological particle simulation module is used for dynamically simulating and analyzing meteorological elements in each three-dimensional grid unit in the meteorological particle model. The application can accurately adapt to the demand of local micro-meteorological simulation for spatial scale fineness, accurately convert meteorological data into particle properties, and improve the accuracy of local micro-meteorological dynamic evolution simulation.

The invention relates to the field of computational physics and particle simulation, and particularly provides an inverse transformation sampling energy spectrum incidence method. The method comprises the following steps: firstly, obtaining discrete energy spectrum data of beta decay based on theoretical calculation, constructing energy-probability density function mapping, and further generating a normalized cumulative distribution function; and then, performing inverse transformation operation on the uniformly distributed random numbers in the [0, 1] interval to generate energy distribution data conforming to the target energy spectrum. By taking beta decay of 63Ni as an example, whole-process modeling and simulation are realized through MATLAB and Geant4 platforms, results show that the method can effectively reconstruct a theoretical energy spectrum, is high in goodness of fit, has relatively high universality and accuracy, is applicable to most standard energy spectrums when being used for energy spectrum incidence simulation of beta decay type particles, has universality, and can be widely applied to the field of energy spectrum incidence simulation of beta decay type particles. The method can effectively process a complex spectrum pattern without closed expression, and is widely applied to researches such as radiation detection, nuclear reaction simulation, particle transport and high-energy physics.

The invention discloses a low-pressure plasma particle simulation method and system based on operator learning, and relates to the technical field of low-pressure plasma. The method comprises the following steps: constructing a plasma particle model, and giving a training task set and a task target set of the plasma particle model; constructing an operator neural network based on operator learning based on a field equation of the plasma particle model, designing corresponding constraint conditions and loss functions, and selecting proper neural network parameters; training the constructed operator neural network, and ending training after a loss function value is gradually converged to a set value; and taking the trained operator neural network as a field equation solver of the plasma particle model, and calculating and outputting a simulation result of the plasma particle model. According to the method, the simulation efficiency of the particle model can be remarkably improved under the conditions of the same model structure and different parameters, and compared with a traditional particle simulation method, the defects that field equation solving depends on a large number of iterations, and the calculation cost is high are overcome.