19 results about "Particle method" patented technology

The invention discloses a numerical simulation method, system, equipment and medium for the complete closing process of a ball valve, and belongs to the technical field of valve control. The method comprises the steps that a geometric model of a ball valve pipeline is established, and pressure and speed monitoring points are arranged; carrying out particle discretization and relaxation on the valve pipeline geometric model through a meshless particle method discrete modeling technology; setting pressure inlet and outlet boundary conditions, and controlling a valve core to rotate so as to simulate the complete closing process of the valve from full opening to full closing; solving a transient closing process, and obtaining a pipeline velocity field and a pressure field under different opening degrees; the change rule of the inlet and outlet pressure difference, the flow coefficient and the flow resistance coefficient along with the opening degree is analyzed, and transient simulation of the ball valve closing process is achieved. According to the method, the problems of grid distortion and numerical instability are avoided through the meshless particle method, high-precision simulation of the complete closing process of the ball valve is achieved, the flow evolution mechanism in the closing process of the valve is revealed, and a theoretical basis is provided for analyzing the flow characteristics of the valve under the small opening degree.

The application discloses a complex geometric model particle discrete method and system and electronic equipment, belongs to the field of fluid mechanics, proposes a kind of efficient, accurate method for constructing model geometry surface narrowband area LSDF, and carry out particle compensation, to avoid the problem that particle spacing increases after particle relaxation;According to the above method, by inputting the geometric model and the particle spacing after discretization, the complex geometric model can be discretized into uniform, adaptive particles with specified spacing. The method solves the problem of inaccurate and inefficient LSDF in the prior art, and the volume error of the model after being discretized into particles is large. By inputting the STL geometric model file and the particle spacing, the model can be automatically discretized into a particle model. The particle model can be applied to numerical calculation of the particle method. The accuracy and universality of the method and device in the application are verified by particle discretization of various complex geometries.

The method for analyzing the formation and evolution characteristics of a core melt debris bed based on a particle method mainly comprises the following steps: 1, selecting a particle size to adapt to geometric modeling and coolant modeling; 2, selecting a melt material and a coolant material, setting initial parameters, and starting calculation; 3, calculating melt column fragmentation by using a moving particle semi-implicit method basic model; 4, calculating melt particle solidification and combination by using a melting and solidification model; 5, calculating melt debris collision and settlement to form a debris bed by using a discrete element model; 6, calculating debris bed cooling or remelting by using a decay heat model and a boiling heat transfer model; 7, judging whether the end time is reached, if not, advancing by a time step, and if yes, outputting a calculation result; and the method can predict the melt fragmentation form, debris size distribution, debris bed accumulation form, debris bed coolability and debris bed remelting risk probability after a core melt accident.

Aspects herein describe new methods of determining optimal actions to achieve high-level objectives based on an optimized chosen statistic. At least one high-level objective, along with various observational data about the world, is identified by a computational unit. The computational unit determines, through a particle method, an optimal course of action. The particle method is doubly-exponentially accelerated based on one or more acceleration methods. The doubly-exponentially accelerated particle method comprises alternating backward and forward sweeps of a coupled induction loop to optimize a selection policy and test for convergence to determine said optimal course of action. The doubly-exponentially accelerated particle method may be applied in multiple different time scales.

The invention relates to an underground reservoir coal pillar protective layer fracture water inrush large deformation prediction method and system. The method comprises the steps that a particle model containing a coal pillar protective layer, reservoir water flow and a support boundary is generated based on preset particle precision; based on a particle model, a response process of a coal pillar protection layer under a water storage-excavation coupling working condition is simulated through a meshless particle method, and the method comprises the following steps: dynamically updating particle distribution of an excavation area by adopting a particle inactivation algorithm, and simulating a thickness change of the coal pillar protection layer; based on a fluid-structure interaction contact algorithm, calculating the interaction force between the reservoir water flow and the coal pillar protection layer; the number of damaged particles is counted in real time according to the stress state of the coal pillar protective layer particles, and the crack expansion, penetration and fracture processes are identified; and generating a critical protective layer thickness, water inrush outburst time and a fracture influence range based on the damage evolution data, and outputting visual data. Through model construction, dynamic simulation, damage identification and parameter prediction, the technical bottleneck of a traditional grid method in large deformation simulation can be broken through.

Provided are a method for estimating a flow rate distribution of an injected material, a method for estimating a temperature distribution of an object, a method for designing a spray nozzle, and a method for creating a learned model, which are capable of accurately estimating a flow rate distribution of an injected material injected from a spray nozzle on an injection surface while using a particle method having a track record as a numerical simulation method even for a gas-liquid multiphase fluid.SOLUTION: An inflow particle arrangement interval d ' obtained from a filling rate α of the liquid phase and an initial inter-particle distance d is defined as a particle interval in the particle inflow region, a function of a probability that particles are generated in the particle inflow region is defined as a particle generation rate function P, and coordinates of the injected material in the particle inflow region are represented by the inflow particle arrangement interval d ' and the particle generation rate function P, the particle generation rate function P is calculated in advance by using a flow rate distribution on a test ejection surface measured in advance by using a test spray nozzle having the same shape as the spray nozzle.SELECTED DRAWING: Figure 1

A data processing method suitable for multi-resolution particle methods includes the following steps: reading initial data and establishing an original model array to start calculation; detecting and judging all particles separately to determine whether particles split or merge, with the judgment condition being whether particles of different sizes flow across precisions; marking and recording the corresponding number of particles that split or merge; constructing two intermediate arrays to store particle information after splitting and merging; updating particle information in conjunction with time nodes, and updating the final particle data and corresponding particle information to the original model array for subsequent calculations, thereby improving overall computational efficiency.

The invention provides a liquid film oscillation mechanism and fluctuation stability calculation method and device based on a particle method. The method provided by the invention comprises the following steps: firstly, constructing a calculation model by arranging five types of particles, namely, sole, fluid, wall, dummy and ghost; secondly, applying a net heat flow boundary considering wall enthalpy correction, radiation heat dissipation and a gas injection factor based on a virtual particle method to realize heat transfer and phase change calculation; then solving a viscosity item and a shear force by adopting a fully implicit method, and updating a particle motion state by combining a non-Newton flow power law model; then, a potent model is introduced to calculate surface tension and overload influence; solving a pressure field through a pressure Poisson equation and iteratively updating particle positions; and finally, dynamically marking ghost particles at the outlet to optimize the calculation efficiency. According to the method, the oscillation phenomenon of the liquid film can be accurately simulated, the generation mechanism and stability influence factors of the liquid film can be revealed, theoretical support and technical means are provided for thermal protection design of the silicon-based material, and the technical problem that the three-dimensional dynamic ablation morphology cannot be analyzed through a traditional method is solved.

This invention relates to the field of geological disaster prevention and control, specifically to a method for improving the accuracy of landslide disaster chain simulation using the smooth particle method. The method comprises the following steps: Step 1: Collecting survey data on the target landslide and its impact range to be simulated, and based on this data, clarifying the geological conditions, topography, landslide body physical and mechanical parameters, and water body physical and mechanical parameters of the target landslide and its impact range; Step 2: Constructing a numerical analysis model for landslide disaster chain numerical simulation based on the smooth particle method; Step 3: Setting initial calculation parameters based on the numerical analysis model constructed in Step 2; Step 4: Starting the simulation calculation, updating the effective radius of any calculation time step according to a preset rule, and continuing the calculation for the next time step until all calculations are completed, obtaining the numerical simulation result of the landslide disaster chain. This invention can significantly improve the accuracy of landslide disaster chain simulation using the smooth particle method.

To provide a simulation device capable of analyzing a flow of a liquid containing bubbles without dividing an analysis space into lattices.SOLUTION: To analyze the motion of a liquid containing a plurality of bubbles by using a particle method. Simulation conditions are input to the input unit. The processing unit performs calculation based on the simulation condition input to the input unit. The processing unit has a function of discretizing a liquid using a plurality of computational particles based on an input simulation condition, a function of representing each of air bubbles by one computational particle based on the input simulation condition, a function of calculating an interaction between a computational particle of the liquid and a computational particle of the air bubble based on the input simulation condition, a function of solving a governing equation of the discretized liquid in consideration of the interaction, and a function of solving a governing equation of the air bubble in consideration of the interaction.SELECTED DRAWING: Figure 4

A method for evaluating melt fragmentation in a sodium-cooled fast reactor (SFR), in which a high-order accurate particle method is adopted to discretely solve a corresponding model and calculate the melt fragmentation process in the SFR. A least-squares moving particle semi-implicit method with high-order accuracy for gradient and Laplace models is used, and a particle-shifting technique is used to maintain a more uniform particle distribution. A geometry-based free surface identification technique is adopted. An equation-of-state model is introduced to enable acquisition of more realistic physical parameters. The solid-liquid coupling model and the phase transition model are combined to carry out the high-order accurate discretization. An evaluation system is also provided. The melt fragmentation data can be updated to the system in real time, and a real-time dynamic graph of the melt fragmentation process is automatically generated, and real-time dynamic cloud graphs of different influencing factors are automatically generated.

The invention discloses a multiphase composite structure dynamic fracture prediction method based on deep learning. The method comprises the following steps: generating fracture evolution data of a multiphase composite structure under dynamic loading as sample data by adopting a GPU accelerated finite mass point method and combining with a rate-related cohesive zone model; the method comprises the following steps of: constructing a multi-dimensional feature system comprising static space features and dynamic time features by taking a bonding unit of a potential cracking region of a multi-phase composite structure as a description object, and carrying out standardization processing on different types of features; constructing a space-time cooperative encoder-decoder deep learning framework; the structure of the framework is as follows: starting from an input layer, a graph attention network space encoder, a feature fusion layer, a gating cycle unit time decoder and a double-branch output layer are connected in sequence; training and verifying the space-time collaborative encoder-decoder deep learning framework for training to obtain a final deep learning framework; and inputting the characteristic data of the test set or the to-be-predicted multi-phase composite structure into the final deep learning framework to complete the rapid prediction of the dynamic fracture evolution of the multi-phase composite structure. According to the method, efficient prediction of dynamic fracture evolution of the multiphase composite structure can be realized, calculation is simple, convenient and efficient, and the defects of the content in current research are overcome.

The invention discloses a high-speed moving solid turbulent boundary layer characteristic analysis method based on a particle method. The method mainly comprises the following steps: 1, selecting particle sizes to model a geometric container, a high-speed moving solid and a fluid; 2, selecting high-speed moving solid and fluid materials, setting initial speed, temperature and temperature boundary conditions, and starting calculation; 3, calculating the Reynolds number of the maximum relative speed of the high-speed moving solid and fluid; 4, turbulent boundary layer parameters of the near wall surface fluid are calculated; 5, calculating motion and heat transfer by adopting a basic model of a particle method; 6, updating the position, the speed and the temperature of the high-speed moving solid, calculating the force and the torque of the fluid to the high-speed moving solid, and counting extra loss required for maintaining the movement of the high-speed moving solid; 7, judging whether the end time is reached or not, if not, repeating the steps 3-6, and if yes, outputting a calculation result; based on the method, the turbulent boundary layer characteristics of the near-wall surface of the high-speed moving solid can be obtained.

This invention discloses a blowout prevention system and method for auger excavators based on SPH-DEM coupling, belonging to the field of tunnel engineering construction technology. The system integrates an SPH fluid simulation module, a DEM particle simulation module, a bidirectional coupling interface, a parametric model of the auger excavator, and a blowout early warning module. It uses the Lagrange particle method to discretize the fluid, Hertz-Mindlin theory to solve for particle contact forces, and GPU parallel computing to achieve bidirectional exchange of forces between the fluid and particles. It also integrates multiple key physical quantities to construct a blowout risk criterion. The method includes multi-scale model construction, coupling calculation parameter setting, bidirectional coupling calculation, blowout feature extraction, risk early warning, and parameter optimization steps. This invention simulates the particle migration and blowout mechanism caused by water pressure disturbance in water-rich strata, improving the accuracy of blowout risk identification and early warning capabilities, and providing a scientific basis for the structural design and construction parameter control of auger excavators.

The invention provides an energy-controllable turbulence simulation method and device based on continuous convolution, and relates to the technical field of computer graphics fluid simulation. The method comprises the following steps: generating particle method physical turbulence data through various physical solvers, sampling and calculating particle speed to obtain various model data sets; training the continuous convolution network model to obtain a plurality of continuous convolution approximation model units, and performing particle displacement prediction according to the model units; and inputting the particle displacement prediction result into an energy interpolation network to obtain an interpolation proportionality coefficient, and carrying out hybrid interpolation on the particle displacement prediction results of the plurality of continuous convolution approximation model units according to the interpolation proportionality coefficient to obtain a final simulation result. The turbulence energy change level generated by the method keeps positive correlation with the control parameters, the effectiveness of the energy intensity coefficient on turbulence energy control is proved, and the obvious trend of transition from laminar flow to turbulence is presented in the visual effect.

Method of determining a physical quantity (QP) of a particle (2) comprising the following steps: Directing the particle (2) to a test mass unit (3), wherein an impact of the particle (2) causes a test mass (4) to deflect, Controlling a physical quantity (QT) of the test mass unit (3) according to a reference value (R) by means of a feedback-control-loop (18), the feedback-control-loop (18) comprising a measurement unit (6) which outputs a measurement signal (y(t) ) related to a measurement quantity (QM) of the test mass unit (3), a feedback-controller unit (7) which outputs a controller output signal (u(t) ) for controlling the physical quantity (QT) of the test mass unit (3) and an actuator unit (5) which actuates the test mass unit (3) based on the controller output signal (u (t) ); and Determining the physical quantity (QP) of the particle (2) on the basis of a feedback-loop signal (19) of the feedback-control-loop (18). The invention further relates to a system (1) for determining a physical quantity (QP) of a particle (2).

The invention belongs to the field of corrosion science and engineering, and provides a galvanic corrosion simulation solving method, system and device and a storage medium, the method comprises the following steps: constructing a boundary response model and a material domain flux conservation model, the material domain flux conservation model being constructed by introducing a galvanic corrosion reaction current; generating a boundary and material domain interface based on the boundary response model and the material domain flux conservation model; and generating a galvanic corrosion result by applying continuity condition coupling on the interface and iteratively converging the boundary response model and the material domain flux conservation model. A boundary element method is adopted to establish a boundary response model of a corrosive medium, a finite volume method is used for establishing an engine material domain flux conservation model, the boundary response model and the finite volume method are coupled on an interface, and the boundary processing efficiency and the volume solving precision are both achieved. And the current conservation of the motivation material domain is more strictly ensured.

Aspects herein describe new methods of determining optimal actions to achieve high-level objectives based on an optimized chosen statistic. At least one high-level objective, along with various observational data about the world, is identified by a computational unit. The computational unit determines, through a particle method, an optimal course of action. The particle method is doubly-exponentially accelerated based on one or more acceleration methods. The doubly-exponentially accelerated particle method comprises alternating backward and forward sweeps of a coupled induction loop to optimize a selection policy and test for convergence to determine said optimal course of action. The doubly-exponentially accelerated particle method may be applied to a meta-control problem to determine an optimal course of action for achieving the goals of a plurality of different control systems having respective computational units.

The application discloses a reactor core meltdown collector design optimization method based on a least square particle method, which is based on a least square moving particle method in a Lagrange method, has higher simulation accuracy and no space consistency limitation, adds a fluid-solid coupling model (PMS model) for calculating the interaction between a coolant and solid melt, and finally calculates the force between solid particles of the melt in the flow field and between the solid particles of the melt and a solid wall through a solid collision model (DEM method). In addition, an optimized particle slip model is used to relieve the particle particle aggregation effect, the calculation density and dynamic viscosity are processed to improve the calculation stability, and the accuracy of particle type determination is improved through a double detection method of algebraic calculation and geometric calculation. The method is a method with the ability of simulating the fluid-solid coupling problem and the solid collision problem in the reactor core meltdown collector and is used for the design optimization of the reactor core meltdown collector.