769 results about "Numerical computing" patented technology

The present invention belongs to the field of computational mechanics, and provides an adaptive multi-level phase-field method for brittle fracture of elastic materials under thermal shock, thus to provide a new numerical calculation method for efficient fracture study. In the present invention, damage degree of a material is characterized by a phase field, and the multi-level hp-FEM is used as an adaptive strategy to implement dynamic discretization in a process of crack propagation under thermal shock. Compared with previous adaptive phase-field fracture models, the present invention has no hanging nodes, and has simple numerical implementation and high calculation efficiency, which can effectively predict the fracture behavior of a structure. At the same time, three pre-existing crack treatment techniques are developed to initialize the phase field. The temperature, displacement and phase fields are solved by an alternating minimization algorithm, which can stably and effectively solve the multi-field coupling large-scale fracture problems.

The embodiment of the invention discloses a numerical calculation method for water outlet icebreaking of a navigation body and related equipment, and the method comprises the steps: generating a floating ice field geometric model according to a working condition, and constructing a navigation body model of the navigation body; grid division is carried out on the floating ice field geometric model and the navigation body model, and a water outlet icebreaking calculation model is obtained; fluid-solid coupling relation definition is conducted on the effluent icebreaking calculation model, and an optimized effluent icebreaking calculation model is obtained; the optimized water outlet icebreaking calculation model is used for simulating the water outlet icebreaking conditions of the navigation body at different moments, and water outlet icebreaking numerical values of the navigation body at different moments are obtained. The fluid-solid coupling relation definition can more accurately describe the interaction between fluid and solid, and in the water outlet icebreaking process, collision and extrusion between a navigation body and an ice layer and subsequent icebreaking behaviors all relate to a complex fluid-solid coupling phenomenon, so that the fluid-solid coupling relation definition is carried out on the water outlet icebreaking calculation model, and the calculation accuracy is improved. Therefore, an accurate value of water outlet icebreaking of the navigation body is obtained.

The invention relates to a quantum gate simulation and control parameter optimization method based on numerical calculation, and the method sequentially comprises the following three modules: a model Hamiltonian matrix representation module can calculate the matrix representation of a model Hamiltonian according to a specific problem; a time evolution and fidelity calculation module of the system discretely solves a Schrodinger equation by using a Hamiltonian matrix, gives a corresponding time evolution matrix, and calculates gate operation fidelity by using the obtained time evolution matrix; and the control parameter optimization module calls the first two modules, optimizes control parameters and quantum gate operation time by adopting a local optimization algorithm or a global optimization algorithm, and gives optimal control parameters and gate operation time. The problem that the gate fidelity of a current superconducting quantum computing system cannot meet the requirement for reliable operation of a practical quantum algorithm is solved, the detailed process of quantum gate operation can be simulated through a numerical calculation method, and the quantum gate operation fidelity is improved by optimizing control parameters.

The invention provides a stratified rock mass constitutive model construction method and system. The stratified rock mass constitutive model construction method comprises the steps that a basic hypothesis is set according to basic mechanical characteristics of a stratified rock mass; based on the basic assumption, a stratified rock mass constitutive model is constructed in the equivalent continuum frame according to the mechanical property of gradual deterioration of the stratified rock mass; the method further comprises the step of verifying the stratified rock mass constitutive model through theoretical solution comparison, numerical test effect analysis, indoor test result comparison and round tunnel excavation effect simulation. According to the embodiment of the invention, the contribution of the layer in the deformation and failure process of the rock mass is highlighted, the influence of the stress state change on the mechanical parameters of the rock mass is reflected, and the gradual degradation of the mechanical parameters along with the equivalent plastic strain in the deformation and failure process of the layered rock mass is realized; and the reasonability and the accuracy of the numerical calculation simulation result in the stratified rock mass engineering construction process are improved.

The invention provides a numerical calculation method for double-explosion-source underwater explosion impact cavitation loads, and belongs to the technical field of computer data processing-based explosion impact wave calculation, and the method comprises the following steps: solving a propagation process of far-field underwater double-explosion-source explosion impact waves in a two-dimensional acoustic flow field by using a local discontinuous Galerkin (LDG) method; and the cavitation characteristics of the flow field under the action of the double-explosion-source underwater explosion shock waves are researched. A flow field dynamic pressure result calculated by the method is compared with a result calculated by an acoustic finite element method. The result shows that the flow field dynamic pressure result calculated by the method is well matched with the calculation result data of the acoustic finite element method, and the effectiveness and the accuracy of the method are verified.

The invention discloses a coupling iterative algorithm library and a reactor multi-physical field coupling calculation program construction method. The coupling iterative algorithm library comprises an open source library layer used for integrating a plurality of numerical calculation libraries and providing an input / output interface for a reactor multi-physics field coupling framework and each numerical calculation library; the core algorithm layer is used for integrating a plurality of coupling iteration algorithms and a plurality of acceleration algorithms related to each coupling iteration algorithm; the interface layer is used for providing a data interaction interface between a nuclear reactor multi-physics field coupling calculation program and the core algorithm layer; and the iterative algorithm template layer is used for forming an iterative solution process control template function based on the open source library layer, the core algorithm layer and the interface layer, and the iterative solution process control template function is used for constructing a nuclear reactor multi-physics field coupling calculation program based on the process control parameters set in the input file. According to the coupling iterative algorithm library, the development efficiency and the development quality of a nuclear reactor multi-physics field coupling calculation program can be improved.

The invention discloses an overlapped finite element method-based underwater target low and medium frequency sound scattering field forecasting method, which comprises the following steps of: generating a virtual node in an overlapped finite element, distributing a group of quadratic complete shift polynomial basis functions in a local analysis domain of each field node to construct local field approximation, and multiplying the local field approximation by a unit decomposition function of the overlapped finite element, constructing a high-order overlapping finite element approximation function; the method comprises the following steps: cutting off an infinite fluid domain by using an artificial boundary, and introducing a Dirichlet-to-Neumann mapping technology to realize a non-reflection boundary condition. For the problem of underwater target sound scattering in middle and low frequency bands, an overlapped finite element numerical calculation model of elastic target sound scattering is established. According to the method, high-order field variable approximation is realized by using the standard low-order finite element grid, the numerical dispersion error and the numerical anisotropy are effectively inhibited, and the low and medium frequency sound scattering field of the elastic target in the infinite water area can be accurately forecasted.

The embodiment of the invention discloses a numerical simulation method for water-rich stratum foundation pit engineering settlement. The method comprises the steps that computational grids and soil mass parameters of a water-rich stratum foundation pit engineering numerical model are obtained; carrying out numerical calculation on the computational grid to obtain distribution conditions of stress and a seepage field; calculating a permeability coefficient and a compression coefficient in the current soil body state; calculating dynamic pore water pressure and steady-state pore water pressure; calculating soil deformation according to the compression coefficient, the dynamic pore water pressure and the steady-state pore water pressure; and carrying out consolidation analysis according to the permeability coefficient. According to the embodiment, the consolidation deformation condition of the soil body in the complex construction process can be accurately predicted.

The invention belongs to the technical field of weak compressible large deformation of soft materials, provides a dynamic analysis explicit substance point method for large deformation of weak compressible materials, and provides a brand new numerical calculation method for large deformation research of the weak compressible materials. According to the method, a weak-form control equation is discretized in a total Lagrangian substance point method framework, and challenges caused by grid distortion when a traditional method is used for solving a large deformation problem are avoided. Besides, the invention provides a volume self-locking processing technology based on an F-bar method, the problem of volume locking of the weakly compressible substance in numerical simulation can be simply, conveniently and effectively solved, and the volume self-locking processing technology can be conveniently embedded into an existing substance point method program. Meanwhile, a construction method of a smooth kernel interpolation function is developed, and the problem that the solving precision of a traditional substance point method in a boundary region is reduced can be effectively solved. According to the method, the problem of large deformation of the weak compressible material can be solved in a stable and efficient manner, and a new technical path is provided for research and application in related fields.

The invention discloses an efficient Transform model reasoning accelerator deployment method based on Versaal ACAP, and belongs to the field of software and hardware collaborative acceleration numerical calculation. Firstly, load analysis is carried out on the model, and meanwhile, according to hardware performance, the types and scales of operators needing to be borne by hardware of all parts are determined; then, hardware is equipped with a data transmitter, a data receiver, a nonlinear operator and other modules; then, the modules are reasonably deployed and connected in hardware, pipeline parallelization is completed, and calculation of a multi-head attention stage and a feedforward neural network stage is achieved; and finally, integrating the two stages to realize accelerated calculation of the whole encoder / decoder layer so as to accelerate the reasoning speed of the upper layer model. Experiments prove that the throughout of the model is effectively improved, the reasoning delay is reduced, meanwhile, the accelerator has huge advantages in the aspect of batch reasoning, and the accelerator has wide application prospects in the aspects of reducing the model reasoning cost and improving the model reasoning speed.

The invention relates to the field of reactor data processing, and particularly discloses a numerical calculation method for solving a neutron transport equation. The method comprises the following steps: 1, describing the geometry of a reactor core of a nuclear reactor by utilizing a construction entity geometric modeling method, and subdividing a curved surface grid along a curved surface structure; 2, directly expanding a neutron flux distribution function in each curved surface grid by using a multivariate polynomial; 3, deriving a neutron transport equation and an integral residual equation of a boundary condition under each curved surface grid; 4, solving geometric integral parameters of each curved surface grid; step 5, establishing an adaptive linear system; and step 6, iteratively calculating and solving a maximum characteristic value and an unknown expansion coefficient.

The invention relates to the field of theoretical calculation and numerical simulation of ship structure protection and cavitation, in particular to a bubble pulsation initial condition inversion method and system based on a bubble energy loss target. Inputting characteristic parameters and energy parameters of the bubbles, and determining a target variable value of inversion calculation; taking a bubble maximum volume moment as an initial calculation moment, randomly giving a bubble internal pressure value at the bubble maximum volume moment, and determining a bubble initial condition in inversion calculation; reversely carrying out time integration on the basis of a compressible spherical bubble pulsation equation to obtain bubble characteristic parameters at zero moment; calculating a time calendar evolution process of a bubble radius by taking a bubble characteristic parameter obtained by reverse time integration as a bubble pulsation initial condition, and judging whether the energy loss of the bubble reaches a target value or not; and adjusting the bubble internal pressure value at the moment of the maximum volume of the bubbles for re-calculation, solving a bubble radius time calendar process, and recording bubble characteristic parameters after reaching an expected target as a new bubble pulsation initial condition. The method is used for solving the problem that the initial bubble pulsation condition is difficult to determine in the existing bubble dynamics theory and numerical calculation.

The invention discloses a plasma sheath electromagnetic characteristic simulation method and system for a hypersonic flight vehicle, and the method comprises the steps: carrying out the fluid simulation according to the geometric shape and flight parameters of the hypersonic flight vehicle, so as to obtain the information of a flow field containing a plasma sheath region; according to the flow field information, simulation parameters of all positions of the plasma sheath space are determined, and the simulation parameters at least comprise electron density distribution and electron collision frequency distribution; based on the simulation parameters, a three-dimensional model of the plasma sheath is established, the three-dimensional model is layered according to electron density distribution, a layered three-dimensional model composed of a plurality of plasma layers is formed, and each plasma layer has the electron density within a preset range; based on the layered three-dimensional model, establishing a non-uniformly distributed electromagnetic simulation model of the plasma sheath; and carrying out grid division on the non-uniformly distributed electromagnetic simulation model, and carrying out numerical calculation by adopting a numerical solver so as to obtain the electromagnetic characteristics of the plasma sheath. According to the method, the problem of deviation between a simulation result and an actual situation of a traditional simulation model can be solved.

The invention discloses a comprehensive intelligent monitoring decision-making system and method for an overlapping shield tunnel system. The system comprises an information acquisition system, an iterative optimization state real-time evaluation system and an intelligent maintenance decision-making system. Firstly, a preset model is trained through data such as numerical calculation; operating measured data to train a feedback model, and weighting output results of the two models to obtain a tunnel deformation predicted value; then establishing an experience overlapping tunnel safety evaluation system and an iterative optimization evaluation system, performing deep association on the tunnel state, damage and maintenance decision through association degree intelligent real-time analysis, realizing tunnel state real-time monitoring, tunnel damage real-time capturing and tunnel maintenance decision real-time updating, performing intelligent matching on maintenance measures, and performing real-time monitoring on the tunnel state, the tunnel damage and the maintenance decision. And the prediction model and the safety evaluation system are iteratively optimized according to operation effect feedback. According to the invention, real-time perception, intelligent diagnosis and maintenance of the whole life cycle overall service performance of the overlapping shield system are realized, and the long-term service quality of the overlapping shield tunnel structure is improved.

The invention provides a computing power metering method and device of an intelligent computing center cloud platform based on a multi-dimensional performance index, and relates to the technical field of intelligent computing centers, intelligent computing centers, computing power infrastructures and intelligent computing clouds, and the method comprises the steps: S1, obtaining a first task type of a first computing power operation task; s2, determining a plurality of resource indexes corresponding to the first task type and a weight coefficient corresponding to each resource index; s3, collecting a parameter value corresponding to each resource index in each of the N periods; s4, calculating a computing power value corresponding to the first computing power operation task based on the weight coefficient corresponding to each resource index and the parameter value corresponding to each resource index in N periods; and S5, generating a first verification data packet based on the first task identifier of the first computing power operation task, the weight coefficient corresponding to each resource index and the parameter value corresponding to each resource index in N periods. The computing power credibility of the intelligent computing center cloud platform can be greatly improved.

The invention relates to the technical field of underground engineering safety monitoring and disaster simulation, in particular to a digital twinborn deduction platform for underground engineering disaster chain evolution simulation, which comprises a multi-disaster coupling numerical simulation module used for acquiring multi-source data including design drawing data, geological data and engineering monitoring data, and based on the multi-source data, establishing an initial stress field model by using a numerical calculation method combining a finite element and a finite difference, and carrying out leakage-settlement-structure failure multi-disaster coupling numerical simulation. According to the method, the partial differential equation for describing the evolution law of the underground engineering is used as a constraint term to be embedded into the deduction model, and online identification and dynamic extrapolation of parameters are executed by fusing real-time monitoring data, so that the accuracy of disaster evolution simulation under complex working conditions is remarkably improved; and the problem that the traditional numerical calculation method is difficult to meet the real-time requirement of digital twinning is solved.

The invention discloses a heat flow real-time inversion method and device based on an annealing gradient algorithm, and relates to the technical field of numerical calculation, and the method comprises the steps: carrying out the numerical calculation based on an external surface heat flow initial value, obtaining a temperature field, selecting a temperature value of a measurement point position, constructing an objective function, randomly generating a new solution, comparing the objective function constructed by the new solution and an old solution, and obtaining a heat flow real-time inversion result; if yes, the new solution serves as a candidate solution, if not, the new solution serves as the candidate solution according to the Monte Carlo judgment criterion by means of probability decision, and local iterative optimization is carried out by means of the gradient information optimization search process till the target function value reaches a predefined threshold value or the temperature parameter is reduced to the lower temperature limit; and ending under the condition that an end condition is met to obtain a final thermal flow vector. Through the randomness of the annealing algorithm and the Monte Carlo judgment criterion, local optimum is avoided, the multi-peak problem of nonlinear heat flow boundary condition identification can be solved, and an accurate identification result of the heat flow on the surface of the thermal protection structure is obtained.

The invention discloses a data center temperature field and flow field rapid order reduction simulation method and system, and the method comprises the following steps: S1, carrying out the CFD numerical calculation of a data center, and obtaining a CFD data set; s2, performing dimensionality reduction on the CFD data set by adopting a weighted intrinsic orthogonal decomposition (POD) method to obtain a low-dimensional mode; s3, optimizing the low-dimensional mode by adopting a machine learning model to obtain a reduced-order model; s4, performing error evaluation and physical constraint processing on the reduced-order model, and performing verification; and S5, generating a temperature cloud chart and a streamline chart by adopting a reduced-order model, and performing hotspot optimization based on a visualization result. Temperature field and flow field simulation is carried out under the guidance of the thermodynamic theory, and the actual requirement for efficient heat management of the data center is met.

The invention relates to the field of numerical calculation of fractional order partial differential equations (groups), and discloses a novel fractional order physical information convolutional recurrent neural network solver, which comprises the following steps of: 1, determining the fractional order partial differential equations (groups) and initial conditions satisfied by a calculation region, 2, a neural network is constructed according to a self-defined coding-convolution LSTM-decoding layer structure, the input of the neural network is an initial condition, and the output of the neural network is a prediction solution of a fractional order partial differential equation (group); 3, calculating the loss of the control equation to obtain a loss function; and 4, obtaining an optimal loss function weight and parameters by using an optimization algorithm, obtaining a solved fractional order partial differential equation (group) solving model, and solving the fractional order partial differential equation (group). Compared with a fractional order physical information neural network (fPINNs), the fractional order partial differential equation (group) solving method based on the physical information convolutional recurrent neural network has remarkable advantages in extrapolation and expansibility, and the problems that in practical application, the fPINNs network is large in parameter quantity and poor in extrapolation and generalization ability are solved.

The invention belongs to the field of computational explosion mechanics, and particularly relates to a rapid calculation method for a shock wave and detonation wave propagation process in a non-uniform medium, and the rapid calculation method comprises the following steps: 1, initializing a calculation program; step 2, estimating and calculating step length in each time step; step 3, carrying out integration on the ordinary differential equation by adopting an explicit three-order TVD Runge-Kutta format; 4, solving a Mach number through an A-M relation; 5, data correction is carried out, wherein the data correction comprises regularization and smoothing processing of grids; and step 6, checking whether termination time is reached or not, if so, ending all processes to complete operation, and if not, returning to the step 2 to continue to circularly solve. According to the rapid calculation method, rapid numerical calculation of propagation of shock waves and detonation waves in a non-uniform medium is achieved, wherein the phenomena comprise refraction, transmission, Mach reflection and the like.

The invention discloses a grid mapping method and device for reactor core multi-physics field coupling, relates to the technical field of numerical calculation, and aims at improving the mapping efficiency and the mapping precision by performing abstraction processing on a grid field and only performing space mapping of a minimum grid set. And the requirements of application scenes with relatively high requirements on the mapping precision are met. The method comprises the following steps: determining a target grid field and a source grid field participating in grid mapping; identifying minimum grids forming the grid fields, constructing a first basic grid set of the target grid field, and constructing a second basic grid set of the source grid field; constructing a basic grid mapping relation pair, and calculating a volume weight coefficient of each second basic grid; setting a volume weight coefficient for each grid according to the volume weight coefficient of each second basic grid; and calculating the grid field parameter by using the volume weight coefficient of each grid to obtain a mapping result of the grid field parameter in the target grid field.

The invention discloses a flow field prediction-oriented full-process automatic joint reduced-order modeling method, which comprises the following steps of: specifying a target physical field parameter space, and randomly generating a sample space according to a Latin hypercube sampling method; constructing a full-process automatic simulation tool chain, driving target physical field numerical calculation and generating a training data set; carrying out singular value decomposition-based intrinsic orthogonal decomposition on the output physical field data, and only retaining first r main feature components to construct a reduced-order data set; constructing a multi-input multi-output full-connection feedforward neural network, and modeling and training a nonlinear mapping relation between input parameters and reduced-order features; new working condition parameters are input, reduced-order features are predicted through the trained neural network, distribution of a target physical field is reconstructed according to a singular value decomposition reduction matrix, and more flexible and reliable technical support is provided for reducing the training cost of a reduced-order model and improving simulation efficiency.

The invention discloses a rock fracture prediction method and system based on a resistivity data assimilation algorithm, and the method comprises the steps: building a numerical model for simulating the asymptotic fracture process of a rock mass under the load effect according to the boundary conditions and initial conditions of the rock mass; simulating the stress damage process of the rock mass by using a numerical calculation method to obtain prediction data of stress field and fracture damage field distribution of the rock mass; monitoring the damage process of the rock mass sample in real time by using a high-density electrical method to obtain observation data; rock mass fracture damage distribution is obtained based on observation data; an assimilation algorithm is adopted, information of observation data and information of prediction data are combined, and initial conditions or parameters of the numerical model are corrected; and then corrected rock fracture prediction data is obtained. Through the data assimilation algorithm, different data and model simulation results are fused in the power frame of rock fracture, the model track is automatically adjusted continuously depending on observation, the analysis result with higher precision and more consistency is obtained, and the prediction precision and predictability of the model are improved.

The invention provides a sparse approximate inverse Shenwei parallel preprocessing method and system for electromagnetic scattering, and relates to the technical field of processor parallel computing, and the method comprises the steps: carrying out the performance hotspot analysis of a sparse approximate inverse preprocessor in an electromagnetic scattering simulation process, and determining a hotspot function of the sparse approximate inverse preprocessor; extracting a sparse matrix vector multiplication operation of a hotspot function, performing master-slave core parallel calculation on the sparse matrix vector multiplication operation, migrating the sparse matrix vector multiplication operation to slave core calculation, and accelerating hotspot calculation by using a heterogeneous parallel sparse approximate inverse algorithm; parallel computing of master-slave core intensive numerical computing tasks is achieved; in the parallel computing process, the slave cores communicate with the master core in a direct memory access mode, and during the period, the master core is in a waiting state to ensure data consistency and communication synchronization until all the slave cores compute distributed tasks.

The invention discloses a navigation body water entry load and motion trail prediction and optimization method based on artificial intelligence, and relates to the field of cross-medium water entry and exit of navigation bodies. The problems that an existing real-scale navigation body cross-medium water entry test is huge in cost, a small-scale mechanical test and other methods are adopted for the cross-medium water entry problem, but large-scale development is difficult due to high cost, and the numerical simulation calculation efficiency is low are solved. The invention discloses a deep learning-based slamming load and motion track prediction method when a navigation body enters water at a high speed, and the method comprises the steps: building a navigation body water entry slamming acceleration and motion attitude database through finite element, meshless and other numerical calculation results or existing test results; and predicting the underwater slamming load characteristics and motion trails of the navigation body under different section shape parameters and underwater parameters, and on the basis, introducing a genetic algorithm to perform reverse optimization design on the shape parameters and underwater parameters of the navigation body by combining the established model, so as to obtain the underwater slamming load characteristics and motion trails of the navigation body. And optimal shape parameters and water entry parameters with strong ballistic stability and small slamming acceleration can be quickly given.

The invention discloses a Neper-DEM-based apparent crystal rock modeling and calculation method with a bedding structure, relates to the field of numerical calculation of a tunnel engineering technology, and solves the problem that a simulation and calculation method for apparent crystal rocks with transverse isotropy such as gneiss and granite gneiss is lacked in the prior art. The method comprises the following steps: constructing a polycrystal structure with crystal characteristics in Neper, and generating a geometric parameter text of crystal grains from the polycrystal structure; constructing a discrete element rock sample model in the DEM; performing a numerical simulation test on the discrete element rock sample model to obtain a stress-strain curve and a sample failure mode, wherein the numerical simulation is realized by adopting a Brazilian splitting test and a triaxial test; according to a numerical simulation result, discrete element sample calculation parameters are calibrated, and the effectiveness of the modeling and calculation method of the discrete element rock sample model is verified; according to the modeling method, construction and assignment of the crystal structure and the bedding structure are achieved at the same time, so that the rock structure is closer to a real rock structure.

The invention relates to the technical field of tunnel deformation prediction, in particular to a BPNN parameter inversion and LSTM tunnel deformation prediction method. On the basis of the orthogonal test design principle, multiple parameter combinations are designed for the M-C constitutive model and the HSS constitutive model, numerical calculation is carried out, and vertical displacement data of the tunnel measuring points are obtained through numerical calculation; constructing a BPNN model, and training the BPNN model by taking the vertical displacement data as input and the corresponding constitutive model parameters as output; inputting field actual measurement tunnel settlement data into the trained BPNN model, and performing inversion to obtain optimal constitutive parameters of M-C and HSS constitutive models; performing forward numerical simulation on the whole process of pipe jacking construction by adopting the optimal constitutive parameters obtained by inversion to obtain a tunnel vertical displacement evolution rule; and inputting a vertical displacement monitoring value of the measuring point of the downlink tunnel based on the long-short term memory neural network to obtain a prediction result of future settlement of the tunnel. The accuracy of the predicted value is improved.

The invention belongs to the technical field of computational electromagnetics, and discloses a numerical calculation method for simulating electromagnetic wave propagation characteristics in time-varying plasma, which is a three-dimensional Newton-HIE-FDTD method for efficiently simulating propagation of electromagnetic waves in time-varying plasma based on a hybrid explicit-implicit finite difference time domain method and Newton's second law of motion. The method inherits the advantages of the Newton-ADE-FDTD method, the time-varying electron density is accurately represented through the time derivative, and the abundant dynamic characteristics of the time-varying plasma can be accurately captured. On the basis, the method also fuses the advantages of an HIE-FDTD method, so that the time step length of the algorithm is only restricted by the sizes of grids in two directions, and compared with other simulation methods based on time-varying plasma, the method provided by the invention is more excellent in calculation efficiency and is more suitable for large-scale popularization and application. The method is especially suitable for analysis and simulation of electromagnetic wave propagation characteristics in time-varying plasma.

The invention relates to the field of multiphase numerical simulation, and discloses a large-scale particle flow numerical calculation method based on multi-ball filling, and the method comprises the steps: obtaining a fluid domain grid size, a fluid density and a large particle radius; calculating the radius of the small filling ball according to the size of the fluid domain grid; based on golden angle spiral distribution and minimum distance coverage judgment, determining the number and the positions of small filling balls, and generating a large particle model of multi-ball filling; obtaining the background flow field speed of the large particles and the filling small balls in the current time step, and calculating the background flow field speed and drag force of the large particles; updating through iterative calculation to obtain the speed and the position of the large particles and the small filling balls in the next time step; and adding drag force as a source item into a momentum equation to solve fluid motion, and obtaining a fluid computational domain grid speed in the next time step. Accurate numerical simulation of large-scale particles is realized.

The invention belongs to the technical field of nuclear reactor physical numerical calculation, and particularly relates to a method for improving precision and convergence of solving a diffusion equation based on a PINN, and the method comprises the following steps: S1, building a neural network algorithm model combining a physical information neural network PINN and source iteration; s2, aiming at a multi-region smooth transition neutron diffusion problem with small cross section difference between materials, optimizing the neural network algorithm model by adopting an optimization strategy of a training level; and S3, aiming at the multi-region neutron diffusion problem of large neutron flux gradient at the boundary due to large cross section difference between materials, improving the neural network algorithm model by adopting a domain-divided neural network architecture. According to the method, the problem that the calculation cost is exponentially increased in a high-dimensional or complex geometric scene due to the fact that a traditional finite difference method and a finite element method depend on grid division is avoided.