42 results about "Diffusion equation" patented technology

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 discloses a boiler energy efficiency prediction method and system based on sampling flue gas component analysis. The method comprises the following steps: acquiring heat flux density data of a plurality of radial positions, and inverting a temperature distribution profile through a radiation heat flux prediction model; constructing a multi-component concentration layering graph based on the diffusion equation and the component transport equation; constructing a sampling path optimization model by using temperature gradient and concentration fluctuation intensity information, driving a dynamic telescopic sampling probe to arrange a sampling position, and collecting a flue gas sample; the analysis model determines original concentration data, thermal-mass offset correction is executed in combination with temperature distribution, and a concentration correction function is constructed to obtain a corrected concentration value; and fusing boiler operation condition data, and inputting into the energy efficiency prediction model to output a heat efficiency index. According to the method, temperature field inversion driven by heat flux density is constructed, a multi-component concentration layering graph is generated in combination with a diffusion and transport model, and the spatial representativeness of flue gas sampling, the physical authenticity of component data and the accuracy of energy efficiency prediction are remarkably improved.

The application discloses a kind of gas-liquid two-phase flow numerical simulation method considering coalbed gas desorption lag, comprising the following steps: using well logging, indoor experiment means to obtain productivity calculation parameter;Desorption equation of matrix system is defined in combination with desorption lag effect, diffusion equation;Gas-water two-phase percolation equation of fracture system is defined, and desorption equation of matrix system, diffusion equation is combined, and double medium gas-water two-phase coupling flow equation set is formed;The porosity and permeability change of matrix system and fracture system in production process is calculated respectively, and the physical property change equation set of double medium is deduced;Using the numerical solver of COMSOL, the coupling equation set is solved using iterative method, and the gas production and water production are calculated.The application is simple to operate, can more scientific and reasonable assess the influence of coalbed gas desorption lag effect on gas well productivity, while greatly reducing the cost and time of gas well numerical simulation calculation, and also has important inspiration for other unconventional gas reservoir development affected by desorption lag.

The invention relates to the field of operation and maintenance management of Internet of Things equipment, in particular to a periodic maintenance task automatic scheduling system and method, and the method comprises the steps: firstly collecting vibration, current and environment signals, and constructing a three-dimensional digital twin map; obtaining a health index and a remaining available life in a preset window through time sequence alignment convolution and an ordinary differential equation recursive network, generating a risk coefficient through index mapping, and driving a reaction-diffusion equation to form a continuous degradation field; the scheduling optimization unit obtains an initial solution through symplectic gradient Hamiltonian-Monte Carlo sampling, and maintenance scheduling data meeting resource constraints are generated through bose sampling, topological bose evolution and dual gaming; the mixed reality terminal displays a risk hotspot and an operation instruction on site, retest data is recorded after maintenance is completed, and reinforcement learning updates a risk assessment and scheduling model on line according to an execution result to form a closed loop; according to the method, accurate quantification of risks, global optimization of scheduling and adaptive feedback of execution are realized, and the fault rate and the maintenance cost can be remarkably reduced.

The invention discloses an osmotic pressure analysis method and device fusing model optimization and physical inversion and a medium, and the method comprises the steps: calculating correlation coefficients of a specified reservoir water level and osmotic pressure under different time lags based on cross-correlation function analysis, and recognizing a differential nonlinear feature corresponding to the maximum correlation coefficient; aiming at the differentiated nonlinear characteristics of different dam types, constructing a plurality of corresponding diagnosis prediction models in parallel, and establishing a model selection decision rule to select an optimal diagnosis model; according to delay parameters obtained through cross-correlation analysis, a permeability coefficient is reversely deduced through a pore medium heat transfer diffusion theoretical formula; according to the regression slope and the theoretical value attenuation factor of the optimal model, a permeability coefficient is reversely deduced in combination with a correction diffusion equation, credibility evaluation and weighted fusion are performed on the permeability coefficient, and a comprehensive permeability coefficient is calculated; and diagnosing the soil type and the permeability characteristic grade. According to the method, the propagation delay characteristic of reservoir water level change in the pore medium can be accurately quantified, and the inversion precision of the permeability coefficient and the engineering applicability are improved.

The application provides a geochemical exploration anomaly ore-bearing property evaluation method and device, obtains geochemical exploration information of a target anomaly region to be evaluated in ore-bearing property, obtains reconstruction concentration information of a chemical element at each sampling point according to the geochemical exploration information and a trained physical information neural network model, wherein the trained physical information neural network model comprises a physical simulation layer embedded with a fractional order reaction-diffusion equation; and then the target anomaly region is evaluated in ore-bearing property according to original concentration information and the reconstruction concentration information of the chemical element at each sampling point. The fractional order reaction-diffusion equation describing the ore-forming geochemical process is learned and simulated through the physical information neural network model, so that the reconstruction concentration information is more in line with the ore-forming regularity, and field verification or drilling is performed when the ore-bearing property evaluation grade of the target anomaly region is high, thereby reducing the exploration cost.

The application discloses an image generation method and device based on a heat kernel theory on a Riemannian manifold, wherein a geometric encoder and a geometric decoder are trained by limiting a Riemannian metric, representation of an image in a low-dimensional manifold is learned, target data distribution is mapped to a special distribution on a low-dimensional manifold through a diffusion equation, and a neural network is used to learn an inverse diffusion process, so that the learning precision and the learning efficiency are improved. When performing an image generation task, sampling is performed from the special distribution on the low-dimensional manifold, a target data distribution on the low-dimensional manifold is estimated through a heat kernel generation model on the Riemannian manifold, and the image distribution in a high-dimensional Euclidean space is restored through the geometric decoder.

The application belongs to but is not limited to the technical field of electronic core industry, and discloses a polycrystalline NCM electrode particle cracking and pulverization prediction method and system, which comprises the following steps: constructing an anisotropic polycrystalline fracture phase field model, including a grain boundary phase field equation, a solid mechanics equation, a Li + diffusion equation and a fracture phase field equation; constructing a two-dimensional geometry of a polycrystalline NCM electrode particle, setting required parameters of physical fields, carrying out grid division and setting initial conditions and boundary conditions; using a finite element simulation software to perform numerical solution, and obtaining cracking and pulverization distribution of the polycrystalline NCM electrode particle. + The application considers bidirectional coupling of Li diffusion and mechanical stress, cracking and pulverization and mechanical stress, and uses grain boundary phase field calculation to correct the critical energy release rate, so that the application can accurately reflect the mechanism of cracking and pulverization of the polycrystalline NCM electrode particle, and improve the accuracy of cracking and pulverization prediction.

This invention discloses a method for calculating gas-gas diffusion concentration distribution considering the influence of gravity, relating to the field of oil and gas field development. This method introduces a gravity drift velocity term generated by density difference into the traditional diffusion equation, realizing a unified characterization of molecular diffusion and gravity differentiation. It constructs a dynamic mass transfer model applicable to multi-temperature, multi-pressure, and multi-component conditions, which is used to calculate the concentration distribution and corresponding dynamic diffusion coefficient of injected gas and formation gas during the vertical diffusion process. This provides a more consistent calculation basis for predicting the migration front and distribution pattern of injected gas, optimizing gas injection parameters, and assessing gas channeling risk. It has applicable value for improving the recovery rate and the operational safety of gas storage facilities.

The invention relates to a fractional order partial grey model short-time traffic flow prediction method based on a two-dimensional advection diffusion equation, and belongs to the technical field of intelligent traffic. The method comprises the following steps: constructing original traffic flow data into traffic flow data in a matrix sequence form; processing the original matrix sequence, and calculating an accumulation generation sequence and a mean value sequence and a partial derivative sequence corresponding to the accumulation generation sequence; establishing a fractional order partial grey short-time traffic flow prediction model AD-FPGM (2, 1) based on a two-dimensional advection diffusion equation; constructing matrixes B and Y to estimate model system parameters, and searching a fractional order accumulation order r and a parameter lambda in a time response formula by adopting a particle swarm algorithm; calculating a simulation value and a reduction value of the AD-FPGM (2, 1) model; and carrying out error test according to each evaluation index of the comparison model, if the error test is passed, predicting a future trend by using an AD-FPGM (2, 1) model, otherwise, reconstructing traffic flow data to carry out model optimization. The prediction result can provide reliable information for a traffic management system, and the research method of traffic flow prediction is enriched.

The invention relates to the field of roadway surrounding rock strengthening control, in particular to a long-term water immersion roadway surrounding rock strengthening control method and system based on fracture feature classification, and the system comprises a multi-dimensional sensor network module, a graph nerve-random differential prediction module, an optimal control module and a chaotic hyper-parameter self-evolution module. A Bayesian digital twin base is established for the multi-dimensional sensor network, and multiple parameters are acquired after a sensor is self-checked; the graph neural random differential prediction module is used for voxelizing a coal bunker, calculating a concentration deterministic trend by using a Fick diffusion equation, and generating a probability trajectory by stacking random differential terms; an optimal control module constructs a Wasserstein fuzzy set to solve a worst case expectation, converts a hard limit into a barrier function constraint, and solves convex quadratic programming to output an optimal control sequence in combination with a Lyapunov constraint; the chaotic hyper-parameter self-evolution module performs quantum coding on hyper-parameters, and the parameters are optimized by taking a safety and energy consumption Nash equilibrium value as fitness and by means of Chebyshev mapping. According to the method, accurate gas prediction, robust control and parameter self-optimization are realized, the over-limit risk is reduced, and the energy consumption is reduced.

The application discloses a method for obtaining C / C composite ablation morphology based on physical information neural network, and relates to the field of aerospace, comprising the following steps: taking the coordinate data of a C / C composite three-dimensional space model under a Cartesian coordinate system, an ablation time, a dimensionless parameter Sh and a dimensionless parameter A as inputs of a pre-trained multilayer perceptron network, outputting oxygen molar concentration and solid volume fraction through the pre-trained multilayer perceptron network; solving a gas phase diffusion equation and a solid phase evolution equation through the oxygen molar concentration and the solid volume fraction output by the multilayer perceptron network to obtain the C / C composite ablation morphology. The method can efficiently and accurately solve the gas-solid coupling equation, overcome the limitations of traditional numerical methods, accurately obtain the ablation morphology of the C / C composite under the gas-solid coupling effect at a low calculation cost, and provide strong theoretical support and technical support for the application of the C / C composite in the field of aerospace and the like.

The application provides a kind of fast solver of radiation diffusion equation based on meshless discrete, it is related to the technical field of numerical simulation and calculation of radiation diffusion problem.It includes: a computing node configuration module for determining the solution threshold of radiation diffusion, and constructing a set of configuration points, a set of center points and a set of evaluation points within the solution region; a compactly supported kernel function definition module for configuring a radial basis function with a fixed support radius for each center point as a compactly supported kernel function; a solver execution module for rigidly decomposing the solution problem to obtain rigid sub-problem partial differential equations and non-rigid sub-problem partial differential equations; discretizing the rigid and non-rigid sub-problem partial differential equations using implicit and explicit formats respectively, solving the two partial differential equations using the radial basis function collocation method to obtain the coefficient vector of the radial basis function; and calculating the numerical solution of the evaluation point set using the coefficient vector.The scheme can achieve fast solution of the radiation diffusion partial differential equation using a meshless method.

The application relates to the field of building information model application technology and engineering project management technology, and discloses a building engineering progress intelligent prediction system based on BIM, which firstly analyzes BIM and progress data, constructs a semantic constraint topological graph containing logical dependence and spatial proximity relationship, then discretizes the building space, constructs an anisotropic diffusion tensor based on component semantics, realizes physical tensorization of geometric constraints, on the basis of which, the system performs multi-physical field coupling calculation, solves the distribution of material flow resistance coefficient field and risk field by using a potential field method and a diffusion equation respectively, finally, the environmental resistance factor in the process operation space is calculated to correct the process prediction duration, and iterative control is performed based on a field-graph closed loop feedback mechanism. The application can quantize the spatial congestion effect and risk non-uniform conduction under a complex building environment, solves the problem of logical plan and physical constraint separation, and significantly improves the accuracy of construction progress prediction.

The invention discloses a blasting process simulation method and system based on bidirectional fluid-solid coupling, and relates to the technical field of rock blasting. The method comprises the following steps: firstly, modeling a solid computational domain by adopting a discrete element method, and modeling a fluid computational domain by adopting a finite volume method; and then applying a dynamic load to simulate an initial crack in a shock wave stage, mapping crack information to a fluid computational domain grid, dynamically updating local permeability, solving a compressible gas diffusion equation, applying a pressure field to the surface of a solid computational domain particle through an interpolation method, and driving the crack to continuously expand. A fluid-solid two-way feedback mechanism covering detonation gas and rock is established, through closed-loop coupling of crack-permeability-gas pressure-new crack, the driving effect of gas at the tip of the crack is accurately captured, the experimental crack form can be accurately reproduced, and the experiment precision is improved. And the influence of the initial air pressure on the crushing range, the crack number and the damage mode can be quantitatively analyzed, and the method is suitable for blasting optimization design under the condition of high-gas-yield explosives.

The application discloses a coupling algorithm for studying the influence of microplastics on fish based on an unstructured grid, and aims to deeply understand the influence of microplastics on the ecology of fish in the ocean. The method combines a Lagrangian advection model and a diffusion equation to simulate the transmission and diffusion process of microplastic particles, calculates the spatial position of each particle and tracks the trajectory of each particle by introducing real ocean current data. The GMRES method is used to solve the large-scale sparse linear system generated in the simulation process to ensure the efficiency and stability of the calculation. The Crank-Nicolson method is also used for time stepping to improve the numerical stability. The Lagrangian advection and diffusion processes are coupled by staggered time steps to truly reflect the spatial distribution of microplastics. Considering the specific behavior of the fish population, the density change rate is determined by the inherent motion, diffusion and microplastic concentration gradient, so as to evaluate the potential influence of microplastics on the marine fish ecology.

The invention relates to a method and device for evaluating an electrolytic bath pole plate structure, a storage medium and electronic equipment, and the method comprises the steps: constructing a multi-physics field model based on an alkaline electrolytic bath, and carrying out finite element grid division to obtain a multi-physics field finite element model; when the multi-physics field finite element model is used for calculating the volume distribution of the bubbles in the small chamber, the bubbles are equivalent to particles, homogeneous flow is adopted, and the radial speed in the running speed is ignored; on the basis of enabling bubbles to be equivalent to particles and adopting homogeneous flow, setting a single-phase flow model equation for describing electrolyte flow by using single-phase flow in each finite element grid in a multi-physics field finite element model, and describing a convection-diffusion equation for describing bubble movement by using convection-diffusion; and iteratively operating the multi-physics field finite element model step by step, obtaining a multi-physics field distribution result of the to-be-evaluated electrolytic bath pole plate, and evaluating the structure of the to-be-evaluated electrolytic bath pole plate based on the multi-physics field distribution result. The structural design evaluation efficiency can be improved.

This invention relates to the field of electronic digital data processing technology and discloses a method for generating structural parameters of a static mixer. The method includes: selecting the inclination angle of the crossbars and the aspect ratio of the mixer as structural parameters to be optimized, with the optimization objectives being minimizing the relative standard deviation of the concentrations of each component at the outlet section and minimizing the pressure drop; constructing a three-dimensional geometric model of the static mixer based on the structural parameters and setting the inlet and outlet positions; solving the flow field based on the Navier-Stokes equations and the continuity equation, and solving the concentration field of each component based on the convection-diffusion equation; obtaining the concentration distribution and pressure drop data of each component at the mixer outlet section under different structural parameters through multiphysics simulation, and calculating the relative standard deviation of each component concentration; screening structural parameter combinations with relative standard deviations less than a threshold, and selecting the one with the smallest pressure drop as the optimal structural parameter. This method solves the problems of reliance on trial and error and long cycles, achieving the goals of high accuracy, high efficiency, and low cost.

The invention belongs to the technical field of oil reservoir development dynamic monitoring data interpretation and analysis, and particularly relates to a well testing analysis and interpretation method for a single-medium different-boundary oil reservoir inclined shaft. A well testing analysis and interpretation method for a single-medium different-boundary oil reservoir inclined shaft comprises the following steps that according to the characteristics of a single-medium oil reservoir, an instantaneous point source diffusion equation of the single-medium oil reservoir is listed in combination with different types of boundary conditions; according to a mirror image reflection rule, carrying out infinite multiple times of symmetry along top and bottom boundaries through a LordKelvin basic solution, and superposing sources to obtain a single-medium oil reservoir instantaneous point source function basic solution under different types of boundary conditions; and integrating along the track of the mirror image inclined shaft in combination with the track of the mirror image inclined shaft, and obtaining the bottom hole pressure response of the inclined shaft in the single medium oil reservoir under different types of boundary conditions through dimensionless. Compared with a conventional vertical shaft theory for explaining inclined shaft data, the method has the advantage that the adaptability and precision of analysis and explanation can be greatly improved.

The application relates to a two-phase flow heat transfer numerical simulation method and system, which comprises the following steps: S01, according to simulation content, setting physical parameters, grid parameters and calculation parameters of the simulation content, and initializing a grid; S02, initializing a two-phase parameter field, a velocity field and a temperature field, and giving a boundary condition; S03, using a two-phase flow model to calculate time evolution conditions of the two-phase parameter field, the velocity field and a pressure field; S04, based on the time evolution conditions of the obtained velocity field, calculating the time evolution conditions of the temperature field through a convection-diffusion equation; and S05, combining the time evolution conditions of the obtained two-phase parameter field, velocity field, pressure field and temperature field, and outputting required simulation data. On the basis of an adaptive grid, the temperature field is added into the flow field as a passive scalar, so that the application range of the numerical simulation method is improved, the reliability of simulation results is improved, and the convenience of analyzing problems is improved.

The invention provides a method for analyzing the influence of leakage diffusion of a directly-buried gas pipeline to an adjacent cable trench under the action of multiple factors, and relates to the technical field of gas pipeline safety monitoring, and the method comprises the following steps: screening key factors influencing leakage diffusion of the directly-buried gas pipeline to the adjacent cable trench; comprise pipeline operation parameters, soil characteristic parameters, environment parameters and cable trench structure parameters, and parameter values corresponding to all factors are obtained through field detection, laboratory tests and literature investigation; on the basis of a computational fluid dynamics method, a porous medium seepage theory and a gas diffusion equation are combined, and a three-dimensional coupling diffusion model is constructed; the three-dimensional coupling diffusion model is constructed by integrating four types of influence factors including pipeline operation parameters, soil characteristic parameters, environment parameters and cable trench structure parameters, the defect that only a single factor or a simplified model is considered in the prior art is overcome, the dynamic rule of diffusion of gas to the cable trench under the multi-factor coupling effect can be accurately described, and the method is suitable for popularization and application. And the prediction precision is obviously improved.

A time domain integral solving method for transient seepage of a dam containing a three-dimensional heterogeneous semi-infinite domain comprises the steps that a novel semi-analytical method of a proportion boundary finite element method (SBFEM) based on a proportion surface is constructed, and the problem of three-dimensional unsteady seepage in a heterogeneous semi-infinite domain foundation is researched. A new coordinate transformation technology is introduced for accurately describing irregular and discontinuous material areas. Based on a three-dimensional diffusion equation, a transient hydraulic head control equation is deduced by using an energy functional and variation principle system, and physical consistency modeling of an unsteady seepage process in a heterogeneous medium is ensured. In order to process boundary conditions at infinity, an unsteady-state seepage matrix is constructed through a weighted residual value method, and the unsteady-state seepage matrix is efficiently solved through a continued fraction expansion method. The time integral of the hydraulic response is realized by combining an improved fine time history integral method (MPTSIM) with a four-order Runge-Kutta method, and has higher stability and precision in a long time interval.

The invention discloses an irregular half-day tide estuary brine invasion unsteady state analysis method considering a time effect, and the method comprises the steps: firstly constructing a flow velocity expression considering different tidal partial effects, carrying out the Fourier series expansion of salinity, substituting the flow velocity and the salinity into a convection diffusion equation, and simplifying the flow velocity and the salinity; then referring to a salinity spatial change expression under a saline intrusion steady-state analysis model, assuming that the average salinity of a tidal period is substituted into simplification calculation to obtain saline intrusion time-space process unsteady-state analysis; and replacing the data parameters which are difficult to obtain in the analytic expression with the data parameters which are easy to obtain. According to the method, Fourier series expansion is adopted, a salinity spatial change expression under a saline intrusion steady-state analytical model is adopted as a basis to assume the average salinity of an unsteady-state tidal period, and the like, so that the problem of non-linear solution difficulty brought to a convection diffusion equation by a time item is ingeniously solved, and a series of physical parameters which are easy to obtain in production and life are introduced; and theoretical support is provided for predicting and preventing salt tide disasters.

The invention discloses an SAR image noise reduction method based on a non-divergence diffusion equation of adversarial attack priori, and the method comprises the steps: randomly generating initial adversarial disturbance, and constructing an initial adversarial attack sample; obtaining a denoised SAR image through a neural network denoising model, carrying out adversarial attack through a projection gradient descent algorithm, and carrying out multiple iterations; the multiple iterations comprise the steps of calculating a loss value of adversarial disturbance introduced by the iterations, and calculating a gradient direction; updating the disturbance noise, and keeping the disturbance noise in a defined space through projection operation; after multiple iterations, obtaining the final confrontation disturbance; and generating a final confrontation attack sample according to the final confrontation disturbance. According to the method, an adversarial attack sample adaptive to SAR image characteristics can be generated, the deep learning adversarial disturbance proportion is used as prior information, spatial modulation of a diffusion coefficient is guided, speckle noise is effectively removed, and meanwhile, the robustness of the model in an adversarial disturbance environment is improved.

The invention discloses a method for acquiring ablation morphology of a C / C composite material based on a physical information neural network, and relates to the field of aerospace. Comprising the following steps: taking coordinate data, ablation time, a dimensionless parameter Sh and a dimensionless parameter A of a C / C composite material three-dimensional space model under a Cartesian coordinate system as inputs of a pre-trained multilayer perceptron network, and outputting an oxygen molar concentration and a solid volume fraction through the pre-trained multilayer perceptron network; and solving a gas phase diffusion equation and a solid phase evolution equation through the oxygen molar concentration and the solid volume fraction output by the multi-layer perceptron network to obtain the ablation morphology of the C / C composite material. According to the method, the gas-solid coupling equation can be efficiently and accurately solved, the limitation of a traditional numerical method is overcome, the ablation morphology of the C / C composite material under the gas-solid coupling effect is accurately obtained with low calculation cost, and powerful theoretical support and technical guarantee are provided for application of the C / C composite material in the fields of aerospace and the like.

The invention relates to a splicing seam repairing method and device, electronic equipment and a readable medium, and the method comprises the steps: obtaining an original DR image collected by DR equipment, and determining a first candidate region corresponding to the position of a grid of the DR equipment on the original DR image; performing multi-algorithm joint calculation on the original DR image based on the first candidate region to determine a splicing seam region in the first candidate region; performing local statistics on the splicing seam region and the neighborhood thereof to obtain local gray feature information, and taking the local gray feature information as a dynamic threshold constraint; and under the constraint of a dynamic threshold value, a weighted diffusion equation is constructed based on the main structure direction and the diffusion weight determined by a structure tensor, iterative repair is carried out on the splicing seam area according to the weighted diffusion equation, and the structure tensor is obtained by calculating gradient information of the splicing seam area and a neighborhood of the splicing seam area. The problem of how to ensure the structure continuity and the detail integrity while repairing the splicing seam of the DR image is solved.

The application provides a kind of GIL loss fast calculation method considering electromagnetic space distribution, relate to high voltage gas insulated transmission technology field, solve the problem that existing GIL loss calculation method is difficult to consider physical rigor and calculation efficiency.The method, the coaxial hollow cylindrical structure electromagnetic field model of GIL is established, and then the diffusion equation of time-harmonic electromagnetic field is constructed and the boundary condition is set;Solving time adopts the linear combination of first kind Bessel function and second kind Bessel function as the general solution form, determines the undetermined coefficient, obtains the magnetic field intensity and electric field intensity distribution expression in the conductor region and shell region;Finally, based on the Poynting theorem, the analytical expression of unit length conductor ohmic loss and shell eddy current loss is calculated and derived, and the conductivity parameter is embedded in the form of explicit function of temperature, that is, the GIL loss calculation is completed.The calculation realized by the application can provide a clear, differentiable and traceable heat source coupling interface for the heat network model.

This invention discloses a numerical simulation method and apparatus for Microcystis blooms coupled with multiple hydrodynamic effects, comprising the following steps: S1, collecting basic data required for constructing a Microcystis bloom model; S2, establishing a fluid dynamics model based on a preset turbulence model, and solving the fluid dynamics model based on preset boundary conditions; S3, constructing a Microcystis dynamics model based on the response relationship between hydrodynamic elements and Microcystis population migration, buoyancy transport, growth, death, population size, and cell density, with governing equations including convection-diffusion equations, Microcystis vertical migration equations, Microcystis growth rate equations, Microcystis death rate equations, population diameter dynamic equations, and cell density dynamic equations; S4, coupling the fluid dynamics model and the Microcystis dynamics model, and obtaining the simulated concentration distribution results of Microcystis through parameter calibration and verification; This invention can fully reflect the key role of hydrodynamic elements in the bloom process, providing reliable support for bloom prediction and forecasting.

The application discloses a SAR image denoising method based on a non-divergence diffusion equation of an adversarial attack prior, randomly generates an initial adversarial disturbance, and constructs an initial adversarial attack sample; a denoised SAR image is obtained through a neural network denoising model, an adversarial attack is carried out through a projection gradient descent algorithm, and multiple iterations are carried out; the multiple iterations comprise calculating a loss value of an adversarial disturbance introduced in iteration, calculating a gradient direction; updating disturbance noise, and maintaining the disturbance noise in a defined space through a projection operation; after multiple iterations, a final adversarial disturbance is obtained; and a final adversarial attack sample is generated according to the final adversarial disturbance. The method can generate an adversarial attack sample suitable for the characteristics of a SAR image, uses a deep learning adversarial disturbance ratio as prior information, guides the spatial modulation of a diffusion coefficient, effectively removes speckle noise, and improves the robustness of a model in an adversarial disturbance environment.