388 results about "Numerical computing" patented technology

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 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 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 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 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 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.

The invention provides a method and a device for dynamically metering computing power based on computing power operation tasks of an intelligent computing center cloud platform, and relates to the technical field of intelligent computing centers, intelligent computing centers, computing power infrastructures and intelligent computing cloud. The method for dynamically metering the computing power of the intelligent computing center cloud platform based on the computing power operation task comprises the following steps: S1, acquiring a parameter value of first operation data of a first GPU in a first time period, wherein the first GPU is a GPU for operating a first computing power operation task; s2, determining a first task type of the first computing power operation task based on a parameter value of the first operation data; s3, determining a weighting coefficient corresponding to the first task type; and S4, based on the weighting coefficient and the parameter value of the first operation data, calculating to obtain the calculation power value of the first calculation power operation task in the first time period. According to the method, the computing power metering accuracy of the computing power operation task in the intelligent computing center cloud platform can be greatly improved.

The present invention relates to the technical field of fluid mechanics. Disclosed is a variable-density low-speed flow mesoscopic numerical calculation method, comprising: determining a computational domain, and dividing or reading grid information, fluid parameters and control parameters in the computational domain; on the basis of the read information, allocating arrays, initializing corresponding parameters of the computational domain, and entering a time step loop upon completion; setting boundary conditions, and assigning all boundary macroscopic quantities in a flow field; under a finite volume framework, deriving a numerical flux of the flow field by means of a BGK equation to solve a Navier-Stokes equation of the flow field; calculating pressure and velocity fluxes at cell interfaces of the flow field, and updating boundary macroscopic quantity information on the basis of flux information; determining whether there is an external force, and if so, applying the external force by means of splitting, and updating the boundary macroscopic quantities; determining whether a time step meets a loop condition; if so, re-entering setting boundary conditions, and assigning all boundary macroscopic quantities in the flow field; and if not, outputting flow field data, and ending simulation. The present invention has the advantages of high algorithm accuracy and simple programming.

The invention relates to a numerical calculation method and device for simulating slippage of a duct piece and a built-in steel bar. The numerical calculation method for simulating slippage of the duct piece and the built-in steel bar comprises the following steps: performing grid division on a three-dimensional shield duct piece according to reinforcement information, endowing the grid three-dimensional shield duct piece with basic physical parameters of concrete, and constructing cable units arranged along actual reinforcement positions, coupling with the concrete model in combination with the calibrated bonding parameters to obtain a concrete model with slippage characteristics; a load path conforming to an engineering scene is applied to the concrete model with the slippage characteristic, nonlinear increment iteration solving is adopted, and simulation time history data is obtained; and finally, performing index calculation and evaluation on the simulation time history data. According to the numerical calculation method for simulating slippage of the duct piece and the built-in steel bar, the problem of overestimation of rigidity and bearing capacity caused by assumption of complete bonding is effectively avoided.

The invention discloses a flood storage and detention area flood diversion process simulation method and device based on a hydrodynamic model, and the method comprises the steps: obtaining the landform, river section, dike engineering parameters, and real-time hydrological and meteorological data of a flood storage and detention area, constructing a basic parameter library, and storing the basic parameter library in a data input module; constructing a hydrodynamic model calculation module by taking a hydrodynamic equation as a theoretical basis on the basis of the basic database, and combining a finite element volume method; receiving a numerical calculation result, analyzing real-time parameters through a dynamic simulation module so as to match actual hydrological parameters, and performing comparison under multiple scenes; and transmitting the hydrological parameters and the comparison data to a result output module, and outputting key parameters of the flood diversion process and a risk assessment result. The method has the advantages that high-frequency coupling of a hydrodynamic model, multi-source dynamic data, a cross-domain model and an engineering control system is achieved, and the problems of data lag, model isolation and control disjunction in traditional simulation are solved.

The embodiment of the invention provides a spectrum red shift measurement method, device and equipment and a medium, which can be applied to the fields of astronomical information technology and high-performance computing technology, and the method comprises the following steps: receiving N observation spectrum data to be measured; determining a processing mode of the observed spectrum data; in response to the processing mode being a first processing mode, processing the observation spectral data through a first calculation path, the first calculation path performing red shift measurement calculation based on a first numerical calculation library by matching the observation spectral data with a set of template spectral data to obtain a calculation result, the calculation result of the first numerical calculation library is consistent with the calculation result of a reference algorithm within a preset precision range; in response to the processing mode being a second processing mode, the observed spectral data is processed through a second computational path that reconstructs the redshift measurement calculations into a tensor parallel model based on a second library of numerical calculations and performs on parallel computing hardware, the second library of numerical calculations supporting tensor calculations.

The invention discloses a batch modeling method for slope excavation support discontinuous numerical calculation. The batch modeling method comprises the steps that a lithologic model reflecting material partitions is established according to terrain and stratum lithologic characters contained in a slope design result; according to the fracture and joint distribution characteristics, a fracture model and a joint model are established in combination with the calculation purpose, and the inheritance relation among the fracture model, the joint model and the fracture model is established; selecting one of the three models as a parent model, setting an excavation sequence of each bench according to a design result, and constructing a step-by-step excavation model; according to the relative relation between the supporting opportunity and the excavation sequence, corresponding supporting models are created on the basis of the excavation models of all the stair flights in sequence; and according to the inheritance relationship, automatically generating general command stream files containing excavation information, support information and parent model information in batches, and converting the general command stream files into command stream files meeting calculation requirements, so as to establish slope excavation support discontinuous numerical calculation models in batches.

The embodiment of the invention discloses an abnormal bidding behavior recognition method and device, electronic equipment and a storage medium, and relates to the technical field of computers, and the method comprises the steps: determining a bidding enterprise of a target bidding project; calculating historical bidding anomalies of the bidding enterprise, wherein the historical bidding anomalies comprise a huddling risk parameter value, an accompanying bidding risk parameter value and a bidding behavior mutation parameter value; calculating bidding document tamper-resistant similarity of the bidding enterprises; and determining an abnormal bidding behavior identification result of the bidding enterprise according to the historical bidding abnormality and the bidding document tamper-resistant similarity. According to the technical scheme provided by the embodiment of the invention, the problems of low manual auditing efficiency, poor identification accuracy and insufficient multi-dimensional analysis in the prior art can be solved.

The invention relates to the technical field of computational simulation, in particular to a modeling method for constructing any chemical short-range ordered multi-principal element alloy structure, which comprises the following steps: setting target values and convergence conditions of chemical short-range ordered parameters; calculating parameter values of chemical short-range order parameters of the initial configuration; calculating an initial difference value; judging whether the initial difference value meets a convergence condition or not; if yes, outputting an atomic configuration; if not, carrying out iterative operation; the iterative operation process comprises the following steps of: randomly exchanging two atomic positions to obtain a new configuration; calculating a difference value between a parameter value number of the chemical short-range order parameter of the new configuration and a target value to obtain an exchanged difference value; judging whether the difference value after exchange is smaller than the difference value before exchange or not; if yes, current exchange is accepted; and after the convergence condition is met, outputting the atomic configuration. According to the method, the function of directly generating a specific structure from structural features is achieved, and atom configuration of any chemical short-range ordered feature can be customized in a wide component space.

The invention discloses a high-precision adaptive numerical simulation method and system for solving a nonlinear integral-differential equation, and relates to the technical field of computer simulation and numerical calculation. Comprising the steps of setting simulation conditions; constructing a grid space based on the computational domain; constructing a global cubic spline interpolation function based on the solutions on the grid points; if the updated grid point location exists, calculating a right-end integral item by using an adaptive numerical simulation integral algorithm; calculating a heuristic solution and an error estimation value; dynamically adjusting the tentative step length and updating the time according to the estimated value and the ODE tolerance; checking gradient and curvature distribution of solutions, encrypting grids for areas with violent solution changes, and sparse grids for areas with smooth solution changes; using a global cubic spline interpolation function to demap the old grid space to the adjusted new grid space; and iteratively executing the steps, and outputting an integral solution in the computational domain. And finally, collaborative improvement of integral simulation calculation in precision, efficiency and stability is realized.

The invention discloses a meter and valve integrated structure optimization and flow calculation method based on computational fluid mechanics, and belongs to the technical field of intelligent measurement and control valve simulation, and the optimization method comprises the following steps: S1, carrying out Boolean operation on a three-dimensional model of a typical opening degree of meter and valve integrated, and obtaining an accurate flow field model; s2, performing grid division on the accurate flow field model; s3, establishing a numerical model after grid division; s4, performing numerical calculation on the flow field model after mesh division by using a numerical model; s5, determining the position of a pressure measuring point according to a numerical calculation result, and obtaining a final optimization model of the meter-valve integrated structure. By adopting the method, the meter-valve integrated complex flow field structure can be captured at high precision, the flow field calculation precision is remarkably improved, rapid iterative optimization of the valve structure is supported, and pressure difference and flow data of the pressure measuring point can be accurately output. And an efficient and reliable numerical simulation means is provided for the optimization design of a meter and valve integrated structure, flow field regulation and control and flow characteristic analysis.

A methods comprises: receiving, by a pseudo random number generator module, an instruction to generate pseudo random numbers from a security application; determining, by the pseudo random number generator module, at least one algebraic input parameter value for a transcendental equation from a randomness library in memory of the device, wherein the transcendental equation comprises a transcendental function that is capable of generating transcendental number outputs from algebraic number inputs; calculating, by the pseudo random number generator module, a solution to the transcendental equation based on the at least one algebraic input parameter value; determining, by the pseudo random number generator module, pseudo random number(s) based on the solution; and storing, by the pseudo random number generator module, the pseudo random number(s) in a randomness library for use as seeds for keys by the security application and as subsequent input parameter values for the pseudo random number generator module.

The invention discloses a damage three-dimensional reconstruction and full-time-history quantitative analysis method based on a two-dimensional axisymmetric finite element model, and the method comprises the steps: constructing the axisymmetric finite element model, importing the axisymmetric finite element model into LS-Dyna software, carrying out the numerical calculation, analyzing a K file, and extracting key information. And screening a specified unit, preprocessing data, calculating the centroid position and volume, and realizing accurate mapping from two dimensions to three dimensions. Mechanical response parameter time history data are extracted, binarization processing and peak value extraction are carried out, damage parameters are calculated, damage time history data are subjected to visualization processing, and a high-resolution image is output. The method solves the problems of lack of spatial-temporal evolution analysis capability, blank extraction of damaged geometric parameters, insufficient cloud picture resolution and the like in the prior art, has wide applicability and practical application value, and can provide powerful support for explosion impact dynamics and penetration damage evaluation.

The invention discloses an extreme rainfall prediction method based on deep learning and numerical calculation, and the method comprises the following steps: employing a random forest classification method to process a rainfall data sequence and multi-element physical quantity data, employing a long-short-term memory network to optimize the processed data, and obtaining an optimized multi-element association sequence; performing feature recognition on the optimized multi-element association sequence, and performing dynamic association modeling and iterative parameter updating on multi-element expression to obtain prediction model input of comprehensive expression; performing regression and deviation correction on the spatial-temporal distribution data of the extreme rainfall event based on prediction model input of comprehensive expression, and performing multi-element dynamic association integration on the residual error part of the multi-scale characteristics by adopting a feedback cycle mechanism to obtain a final rainstorm event judgment basis; and based on a final rainstorm event judgment basis, carrying out evolution process simulation on real-time environmental factor updating data, and determining an accurate output sequence of extreme rainfall prediction.

The invention discloses a surface flood rapid calculation method based on a Fourier neural operator, and provides an urban flood modeling and numerical calculation method fusing a two-dimensional hydrodynamic model and a physical constraint Fourier neural operator. According to the method, a multi-scale feature mapping and physical constraint mechanism is introduced under a framework of solving a surface flood evolution process by a traditional shallow water equation, and nonlinear mapping from a low-resolution simulation result and multi-source environment driving data to a high-resolution flood response field is realized, so that a high-resolution flood response field is obtained on the premise of ensuring physical rule constraints. According to the invention, high-precision and rapid prediction of the urban flood process is realized.

The invention discloses a collaborative reasoning method and system for adaptive model segmentation in a heterogeneous computing power environment. The method comprises the following steps: establishing a numerical calculation precision difference model between a source computing device and a target computing device; at a source equipment end, carrying out sensitivity analysis on a state tensor to be migrated according to the difference model, and asymmetrically dividing the state tensor into a core sensitive part and an edge part; performing dimension reduction processing on the edge part to generate a low-precision basic tensor, extracting precise residual information from the core part, compressing to generate a residual compensation vector packet, and sending the two to target equipment; and at a target equipment end, main calculation is carried out by using the low-precision basic tensor, a residual error compensation vector packet is decompressed in a bypass manner, and recovered residual error information is injected into an intermediate result of a main calculation stream to complete precision compensation. The problems of reasoning state semantic drift and error accumulation caused by dynamic migration between heterogeneous devices are solved, and the robustness and efficiency of a collaborative reasoning system are improved while the model reasoning accuracy is guaranteed.

The invention relates to the technical field of data analysis, and discloses a parameterization analysis method and system based on a sea wave spectrum mode. The method comprises the following steps: carrying out abnormal value detection and missing data filling on multi-source ocean data by adopting a 3 sigma criterion and Kriging interpolation, and unifying to a 0.1-degree grid to obtain a standardized data set; decomposing a sea wave energy balance equation source item into three modules for numerical calculation; configuring ST2, ST4 and ST6 schemes for the numerical solutions, and carrying out statistical analysis to obtain performance evaluation indexes; based on the evaluation indexes, a genetic algorithm is combined with particle swarm optimization to carry out parameter optimization; dividing the offshore China into four sub-regions for differential adjustment according to the optimization parameters; and carrying out trend checking and parameter increment updating by adopting a sliding window technology based on region configuration. The technical problems that a sea wave spectrum mode parameterization scheme lacks a systematic comparison and optimization mechanism, parameter configuration cannot adapt to regional marine environment differences, and parameters lacks real-time monitoring and dynamic adjustment capabilities are solved.

The invention relates to the technical field of atmospheric science and numerical calculation, discloses an atmospheric numerical simulation method based on multiphase state water substance conservation constraint and application, and aims at evolution calculation of all phase state water substances under the conditions of discrete grids and discrete time steps for atmospheric numerical mode cloud microphysical parameterization. The method comprises the following steps: acquiring the density and velocity field of each component in a grid unit, and constructing a mass ratio variable normalized by wet air density; defining a growth rate per unit volume and per unit time, and representing a phase change source sink by using a component continuity equation; and establishing a coupling discrete updating rule according to the mass ratio accurate evolution equation, calculating a total water substance growth rate residual error and a ratio residual error corresponding to the equivalent conservation expression, and obtaining a corrected growth rate meeting conservation constraint through consistency correction so as to write back and update the mass ratio field. The method can inhibit the income and expenditure drift of water substances, reduces the phase distribution error under the condition of mixed phase cloud, and is suitable for numerical weather forecast and regional numerical simulation.

A system and method include learning a topological order of a DAG by setting an initial index value of a first index, setting an initial score value of a score, setting an initial order list, computing an initial SSCP matrix, sweeping the initial SSCP matrix based on the first index, incrementing the first index to obtain an updated index value of the first index, determining an index value of a second index, computing an updated SSCP matrix, computing an updated score value as a sum of an initial score value and a value identified from the updated SSCP matrix, and computing an updated order list from an initial order list based on the updated index value of the first index and the index value of the second index.

The application discloses a method for realizing a conservative charge-controlled memcapacitive hyperchaotic circuit with multiple coexisting attractors. First, a six-dimensional conservative memcapacitive circuit model is constructed by a charge-controlled memcapacitive device, and the memcapacitive characteristics are verified. Then, the balance point and dissipation are used to verify the conservativeness. By changing the system parameters and initial conditions, a larger Lyapunov exponent can be obtained, and it is found that the internal parameter e of the circuit can not only cause the circuit to exhibit complex transient chaotic phenomena, but also has large-scale range chaotic characteristics. The attractor basin, coexisting attractors and complexity reflect the extreme multistability and complex nonlinear dynamic behavior of the circuit. In addition, the initial offset boosting behavior is also found. The application combines the FPGA technology to design a digital conservative charge-controlled memcapacitive hyperchaotic circuit model, and the hardware simulation result is consistent with the numerical calculation result, thereby providing a new idea for the digital realization of a nonlinear storage system.

The invention relates to the field of multiphase numerical simulation, and discloses a cross-scale particle flow calculation method based on feature point arrangement, and the method comprises the steps: obtaining the position coordinates, speed, radius and augmentation coefficient of particles in a current time step, and the position coordinates, volume and speed of all fluid domain grids; determining position coordinates of the feature points according to the grid volume, the particle radius and the augmentation coefficient; dividing grids where the feature points are located into internal grids, boundary grids and external grids on the basis of the position relationship between the feature points and the particles, calculating the voidage of each grid in different modes, and calculating the background voidage of the particles; the background flow field speed of the particles is calculated according to the grid voidage, the volume and the speed; according to the background voidage, the speed and the background flow field speed of the particles, the drag force borne by the particles is calculated, and therefore numerical calculation of the cross-scale particles is achieved.