785 results about "Control equation" patented technology

The invention relates to the technical field of tunnel engineering, and discloses a tunnel multi-field coupling nonlinear deformation analysis method and system.The method comprises the steps that geological environment information of a tunnel area is collected, a multi-source physical field boundary condition model is built based on collected data, and a heat-seepage-stress-time four-field coupling control model is built based on the collected data; specifying a nonlinear response model for the geological medium to truly reflect the stress-strain behavior of the geotechnical material; solving a coupling equation set, and optimizing the four-field coupling control model; introducing measured data to correct the model; the system comprises a geological data acquisition module, a boundary condition modeling module, a coupling model establishment module, a numerical solution module, a measured data correction module and a visual output and control interface module. According to the method, high-fidelity prediction and evolution analysis of the deformation behavior of the tunnel under the complex geological condition are realized based on comprehensive acquisition of the geological environment, multi-field boundary modeling, control equation construction and numerical calculation.

The invention relates to the technical field of coast engineering, and discloses a multi-source data-based beach restoration decision-making method and system, and the method comprises the following steps: obtaining multi-source data of beach monitoring, carrying out the data fusion processing, and generating a feature tensor with a unified temporal-spatial resolution; performing symbol regression analysis based on the feature tensor, and automatically discovering a control equation of beach evolution; and inputting the evolution equation into a decision optimization framework to generate a beach restoration decision scheme. According to the method, through organic combination of multi-source data fusion, symbolic regression analysis and a decision optimization framework, accurate description of a beach evolution process and intelligent generation of a repair decision are realized; according to the scheme, information of various monitoring data can be fully utilized, a control equation of beach evolution and time-varying characteristics of the control equation can be automatically found, and a physical rule is directly converted into a specific engineering decision suggestion, so that prediction precision and decision efficiency of beach repair are improved.

The invention discloses a PINN-based high-precision hydrodynamic numerical simulation method and system, and the method comprises the steps: firstly building a computational domain, setting reasonable geometric parameters and boundary conditions, and constructing a dimensionless Navier-Stokes control equation set; then designing a deep neural network architecture with space-time coordinate input and flow field variable output, and adopting a loss function combining physical constraint and data driving; the core innovation lies in providing a timing sequence sensing RAR-D adaptive sampling strategy, dividing a time domain into a plurality of time frames, performing residual error evaluation in each frame, constructing a probability density function related to residual errors, and balancing priority sampling and overall coverage of a high residual error region; adam and L-BFGS optimizers are adopted to carry out network training, the weight of a loss function is dynamically adjusted, and a sampling point set is periodically updated; and finally, the solution precision is verified through multi-dimensional flow field visualization analysis. Therefore, the prediction precision of the complex flow field is effectively improved, and the calculation efficiency is remarkably improved.

The invention belongs to the related technical field of heat dissipation of electronic equipment, and discloses a liquid cooling device and a preparation method and application thereof, and the method comprises the steps: S1, enabling a control equation of the liquid cooling device to be equivalent to a continuity equation, an N-S equation and a heat transfer equation based on equivalent parameters; s2, taking the minimum average temperature and energy dissipation of the whole design domain of the liquid cooling device as a target function, taking the volume fraction of the fluid domain as a constraint condition, and constructing a topological optimization model based on a continuity equation, an N-S equation and a heat transfer equation; s3, an optimization solver is adopted to carry out iterative solution on the topological optimization model, whether a result meets a convergence condition or not is judged, if yes, a topological structure is output, and the step S4 is executed; otherwise, updating the design variable of the topological optimization model, and turning to the step S1; and S4, the three-dimensional model of the liquid cooling device is corrected based on the obtained topological structure, and then blowing forming is carried out based on the corrected three-dimensional model to obtain the liquid cooling device. According to the invention, the cost is reduced.

The invention discloses a reservoir-shaft integrated prediction method for geothermal exploitation, which belongs to the technical field of geothermal exploitation, and comprises the following steps: S1, constructing a cross-scale reservoir model, S2, establishing a reservoir-shaft coupling model, S3, establishing a heat-fluid-solid coupling control equation, S4, solving the coupling control equation, S5, simulating multiphase flow in a shaft, and S6, learning and optimizing a machine. S7, dynamically updating prediction; by constructing a cross-scale reservoir model and a wellbore-reservoir coupling model, accurate mapping from micro pores to macroscopic thermal storage and dynamic coupling of a reservoir and a wellbore are realized, and numerical solution and multiphase flow accurate simulation of a thermal-fluid-solid multi-field coupling control equation are combined. Rock heterogeneity, multi-physical field interaction and complex flow characteristics in the shaft are comprehensively considered, the prediction accuracy and comprehensiveness are greatly improved, and the defects that in a traditional method, reservoir and shaft analysis is split, and the model precision is limited are overcome.

The invention is applicable to the technical field of coal bed gas development and geological sequestration, and provides a THMC multi-field coupling simulation method and system for a process of displacing CH4 by coal bed CO2, and the method comprises the following steps: collecting multi-source parameter information of a target coal bed; according to the multi-source parameter information, constructing a coal seam structure model comprising a matrix and a crack system; constructing a control equation system based on the coal seam structure model, and introducing a multi-field coupling mechanism to obtain a fully-coupled mathematical model; performing numerical solution on the fully-coupled mathematical model to obtain a spatio-temporal evolution result of the key field variables; and according to the spatio-temporal evolution result of the key field variable, evaluating the index of the target coal seam. According to the invention, a heat-force-gas-chemical multi-physical field full-coupling simulation system is constructed, so that the CH4 recovery rate and the CO2 storage stability can be accurately predicted. The method is suitable for gas injection-storage coupling optimization of a multi-coal-rank and low-permeability coal seam, and has high precision, high adaptability and remarkable engineering guidance value.

The invention provides a deep energy reservoir multi-scale heat-fluid-solid coupling simulation method and system, and belongs to the field of deep energy reservoir numerical simulation. Acquiring spatial distribution characteristics and physical property parameters of different lithologic reservoir media under a micro-scale, and constructing a digital structure model of the reservoir media; a micro-observation action mechanism and a flow mechanism are embedded in the model to obtain a micro-observation numerical model; establishing a mapping relation by solving model structure parameters and physical property parameters of the microscopic numerical model under different thermal-fluid-solid coupling conditions; and on the basis of the mapping relationship, in combination with the macrogeological and engineering data of the target reservoir, establishing a macroscale heat-fluid-solid multi-field coupling control equation and solving, and outputting the multi-physics field response of the target reservoir under the given working condition. According to the method, fine simulation of physical property parameter dynamic transmission and a multi-field coupling evolution process from a micro view to a macro view is realized, and the accuracy and reliability of deep complex reservoir engineering behavior prediction are remarkably improved.

The invention provides a flow field solving method based on a time sequence physical information neural network, and belongs to a partial differential equation calculation method. The method comprises the following steps: firstly, determining a flow field motion law and a flow field computational domain based on a fluid motion control equation, configuring data points for training and performing data fusion operation; secondly, constructing a physical constraint residual equation, taking the training data set as input data of a neural network, calculating a data residual term, weighting a calculation result of the physical constraint residual equation and a calculation result of the data residual term, and constructing a data-physical mixed loss function; and finally, constructing a time sequence-based physical information neural network, performing training optimization on parameters of the time sequence-based physical information neural network, completing training and obtaining simulated flow field features. By introducing the time sequence module, the accuracy of flow field dynamic simulation based on the time sequence physical information neural network is improved, the requirement for the model solving speed can be met, and the feasibility and accuracy of the model are guaranteed.

The invention provides an optical element surface type simulation method based on a physical information neural network, and relates to the technical field of element design and simulation, and the method comprises the steps: constructing a feedforward neural network; generating a deformation control equation model library; constructing a three-dimensional simulation database; forming a machine learning parameter library; training the PINN deformation simulation model in combination with a deformation control equation model library, a three-dimensional simulation database and a machine learning parameter library, and screening out a target PINN deformation simulation model meeting a preset condition; inputting the design parameters, the support structure parameters and the given external load parameters of different combinations into the target PINN model to obtain a key performance prediction result of the optical element; according to the method, the key performance of the element under various parameter combinations can be rapidly evaluated, the design iteration period is shortened, the trial and error cost is reduced, direct data support is provided for supporting structure optimization design, and the bottleneck problem that a traditional method restricts the research and development efficiency of a high-precision optical system is effectively solved.

The invention discloses a wind turbine blade semi-coupling aeroelastic modeling method considering nonlinear deformation, and belongs to the technical field of fan simulation calculation. In combination with calculation parameters used by three-party software, establishing a blade structured load model and a blade correction aerodynamic model, calculating an aerodynamic load and a structural load, and superposing: superposing the aerodynamic load, the gravity load and the centrifugal force load of the blade as an external load of a nonlinear structure control equation of the blade, and taking the external load as a calculation parameter; according to the method, the blade nonlinear structure model and the semi-coupling simulation process of the three-party wind turbine simulation software are constructed, and under the same simulation environment and load conditions, the blade nonlinear structure model and the three-party wind turbine simulation software can be subjected to semi-coupling simulation, so that the blade nonlinear structure model and the three-party wind turbine simulation software can be subjected to semi-coupling simulation calculation. The higher-precision non-linear motion response characteristics of the super-long flexible wind turbine blade are calculated, and a good effect can be achieved in the aspects of initial structure design and response evaluation of the large wind turbine blade.

The invention discloses a fluid distribution dynamic regulation and control method and device based on a shale reservoir microstructure, and relates to the technical field of oil and gas exploitation. The method comprises the steps that microstructure parameters of a target shale reservoir are obtained through a core experiment, and a multi-scale model is constructed based on the microstructure parameters; determining control equations of different physical fields of the multi-scale model; coupling the control equations of different physical fields, and resolving through a finite element method; performing a numerical simulation experiment based on the multi-scale model and the resolving result to determine regulation and control parameters; the regulation and control parameters are input into the multi-scale optimization model to optimize the regulation and control parameters, and a regulation and control strategy is obtained. The problems that an existing displacement experiment is single, the complex interaction process under the actual mining environment is not comprehensively considered, and the guiding effect on mining work is limited are solved. Business personnel can be guided to formulate a development scheme more scientifically and accurately, the mining efficiency and the success rate are improved, the development cost can be reduced, and meanwhile economic benefits are improved.

The invention discloses a CFD (computational fluid dynamics) simulation-based road construction environmental emission calculation method, and particularly relates to the technical field of environmental engineering and numerical simulation. The method comprises the following steps: establishing a three-dimensional physical model of a road construction environment emission system and determining a flow field computational domain; performing grid division on the three-dimensional physical model in a flow field calculation domain and establishing a grid structure internal association relationship; applying a mass conservation equation set, a momentum conservation equation set and an energy conservation equation set to the simulation model, and constructing a control equation system in combination with the turbulence model and the gas-solid two-phase flow model; setting boundary conditions such as an inlet, an outlet and a wall surface, and constructing an environmental emission simulation calculation model; actual data such as airflow velocity, temperature and particulate matter concentration of a road construction site emission source are collected and input into a simulation model for simulation calculation, a simulation result is compared with actually measured data through a relative error method, model verification is completed, and visual modeling and quantitative measurement and calculation of the road construction environment emission process are achieved.

The invention provides an insulating material surface arc ablation resistance simulation method based on magnetohydrodynamics, and belongs to the field of insulating material performance detection. The method comprises the following steps: establishing an insulating material surface arc ablation resistance model; constructing a magnetohydrodynamic control equation set; setting boundary conditions of the model; and iteratively solving the magnetohydrodynamic control equation set through finite element simulation software to obtain a temperature distribution diagram of the insulating material under different arc ablation times, and comparing the temperature distribution diagram with a TGA curve of the insulating material to judge the arc ablation resistance of the insulating material. According to the invention, the power-frequency alternating-current high-voltage arc and the insulating material are used as simulation objects, engineering practice is better met, the surface arc ablation resistance process of any insulating material can be simulated by changing the physical characteristic parameters of the insulating material, and the TGA curve of the material is introduced to judge the arc ablation resistance of the insulating material. And technical support is provided for high-voltage switch equipment insulating material type selection.

The invention discloses a CFD calculation method and system based on a neural network and adaptive parameter optimization, and belongs to the technical field of computational fluid dynamics. Initializing a flow field by reading calculation parameters and a grid file; solving the N-S equation, recording solving parameters and outputting an intermediate flow field; inputting the intermediate flow field into a pre-trained physical constraint neural network, sequentially applying boundary condition hard constraint and soft constraint based on control equation residual error, and outputting a corrected flow field; based on the convergence dynamic characteristics and the solving parameters, outputting a parameter adjustment amount through a strategy network of reinforcement learning training, and dynamically optimizing the solving parameters; and taking the corrected flow field as an initial flow field of the next iteration step, updating solving parameters, and circularly executing until convergence. According to the method, the physical prior is embedded into the neural network, intelligent self-adaptive regulation and control of solving parameters are realized through reinforcement learning, and the prediction precision and convergence efficiency of complex flow simulation are remarkably improved.

The invention provides a real-time prediction method and system for milling deformation of a thin-wall part and electronic equipment. The method comprises the steps that a partial differential equation set used for reflecting the deflection and stress coupling relation in the milling machining process of the thin-walled workpiece is constructed based on a von Karman control equation set; constructing a deformation prediction model based on a depth operator network; according to the partial differential equation set, constructing a loss function comprising a partial differential equation residual term and a boundary condition term; training the deformation prediction model according to the loss function and two-dimensional coordinate points and load function sampling points used for training the deformation prediction model; and deploying the trained model in a machine tool system, inputting real-time load data and real-time coordinate data of the thin-wall part in the milling process, predicting deformation response of the thin-wall part in the milling process, and obtaining a target prediction result. The method can quickly and accurately predict the deformation response of the thin-wall part under the complex load working condition, and improves the machining quality and efficiency of the thin-wall part.

The invention discloses a method for predicting fluid excitation characteristics of a propeller, and relates to the field of propeller simulation. The method comprises the following steps: modeling a propeller flow field according to attribute information corresponding to the propeller flow field to obtain a propeller flow field grid model; determining a propeller flow field control equation corresponding to the propeller flow field grid model, and discretizing the propeller flow field control equation by adopting a finite volume method to obtain a discretized propeller flow field control equation; performing propeller hydrodynamic numerical simulation on the discrete propeller flow field control equation based on a delay separation vortex simulation method to obtain speed spatial-temporal distribution and pressure spatial-temporal distribution, and performing decoupling processing on the speed spatial-temporal distribution and the pressure spatial-temporal distribution; and according to the whirling vibration data, the vortex motion data, the decoupled pressure field and the decoupled speed field, the exciting force of the propeller flow field is obtained. The method can accurately reflect the influence of different vortex motions on the excitation characteristics of the propeller and the fluctuation of the velocity field of the propeller.

The invention discloses a stress corrosion crack propagation simulation and prediction method and system based on a phase field method. The method comprises the following steps: constructing a stress corrosion dynamic evolution model based on the phase field method; the stress corrosion dynamic evolution model is a control equation set for coupling a displacement field, a material concentration field and a crack phase field to carry out stress corrosion cracking evolution; establishing a discrete numerical value format for analyzing the stress corrosion dynamic evolution model, and performing simulation program development of the stress corrosion dynamic evolution model based on an ABAQUS platform according to the discrete numerical value format; and acquiring a specific load working condition, and performing stress corrosion crack growth rate simulation prediction on the nuclear reactor primary circuit 690 alloy material under different working conditions based on a developed simulation program to obtain the crack growth rate. According to the invention, the phase-field function is introduced to describe the crack morphology to simulate the stress corrosion crack propagation, and the rule of the stress corrosion crack propagation of the primary loop 690 alloy under different working conditions is accurately simulated.

The invention discloses a parallel simulation method for guided wave focusing imaging of a piezoelectric array of a composite structure, belongs to the technical field of nondestructive testing, and aims at solving the problems that the sound field control precision of a current multi-array-element piezoelectric structure in a composite material plate is insufficient, and a traditional finite element method is large in calculation time consumption, low in convergence speed and high in reliability in the guided wave propagation simulation process. In order to solve the problem that effective convergence cannot be realized under the excitation condition of a high-frequency multi-channel array and even under the excitation condition of a high-frequency multi-channel array, the invention provides an efficient guided wave focusing simulation strategy combining spectral element high-order precision and GPU parallel computing, and the method comprises the following steps: establishing a system control equation considering a piezoelectric-structure coupling effect on the basis of a delay superposition principle; energy focusing and sidelobe suppression of a guided wave signal in a specific direction are realized by adjusting spatial arrangement and excitation time sequence of a piezoelectric array sensor, Gauss-Labatto-Legendre integral nodes are introduced to construct a high-order spectral element unit, unit-level parallel solution is realized under a CUDA architecture, and dynamic simulation capability and overall calculation efficiency of focusing field distribution are remarkably improved.

The invention discloses a fluid-structure interaction numerical simulation method, device and equipment and a medium, and the method comprises the steps: selecting a fluid-structure interaction computational domain, generating a computational grid, and marking the computational domain according to fluid and solid distribution information; determining a solving time step length and a discrete format, and selecting a control equation set for solving, the control equation set comprising a continuity equation, a fluid dynamics equation, a solid dynamics equation and a phase transfer equation; and analyzing and displaying a solving result. According to the efficient fluid-solid coupling numerical simulation method, global unified calculation is achieved, explicit fluid-solid decoupling is not needed, a global fluid-solid coupling body kinetic equation is adopted, errors caused by fluid-solid decoupling processing in a traditional split-phase solving method are avoided, and the method does not need to depend on and repeatedly generate a complex body-fitted grid; the control equation is based on each phase conservation equation on a physical continuous domain and realizes interphase accurate association through an interface continuity condition, and the fluid-solid coupling problem can be accurately and quickly solved.

The invention discloses a GIS equipment shell vibration fault identification method and system based on a physical information neural network, and relates to the technical field of GIS fault diagnosis, and the method comprises the steps: collecting a vibration acceleration signal of the surface of a GIS shell; establishing a simplified physical model of the vibration system, and determining a control equation, initial conditions and boundary conditions of the vibration system; based on the HFT-MPINN or the RL-PINN, constructing a parameter inversion model; fusing physical constraint loss, experimental data loss and multi-parameter coupling loss of the vibration system to construct a composite loss function; training a parameter inversion model by using the vibration acceleration signal to obtain key physical parameters of the vibration system; time-frequency domain analysis and finite element simulation verification are combined, and the mechanical fault type and degree of the GIS equipment shell are recognized. According to the method, the modeling precision, the noise robustness and the multi-working-condition adaptability of the high-frequency vibration signals are improved, and reliable technical support is provided for intelligent fault diagnosis of GIS equipment.

The invention relates to a CFD (Computational Fluid Dynamics) method for nearly continuous hypersonic high-temperature thermochemical unbalanced flow numerical simulation, which comprises the following steps of: 1, introducing a Park double-temperature model into an NS equation to describe a thermochemical unbalanced effect at high temperature, and closing a shear stress tensor, a heat flow vector and a mass diffusion flux by adopting an equivalent constitutive model to obtain a closed shear stress model; capturing speed slippage and temperature jump phenomena on the wall surface by adopting corresponding slippage boundary conditions to obtain a macroscopic control equation and boundary conditions suitable for near-continuous hypersonic high-temperature thermochemical non-equilibrium flow; 2, discretely solving the macroscopic control equation and the boundary conditions given in the step 1 by adopting a finite volume method; and step 3, performing post-processing on a solution result obtained in the step 2 to obtain a streaming flow field, a wall surface aerodynamic force and a wall surface heat flow of the calculated appearance.

The invention discloses a direct coal liquefaction pump thermal wear prediction method considering a high temperature effect, and belongs to the technical field of fluid machinery and reliability engineering.The method comprises the steps that the high temperature effect is considered, a liquid phase control equation and a solid particle dynamic model are subjected to coupling iteration, and a solid-liquid two-phase flow numerical model is obtained; the method comprises the following steps: performing full flow field modeling on a fluid domain formed by flow passage components of a pump for direct coal liquefaction, and performing grid division on the fluid domain; constructing a heat-flow-solid multi-field coupling calculation system, and solving the solid-liquid two-phase flow numerical model by adopting a large eddy simulation method based on temperature correction and a discrete element method coupling method to obtain information of flow fields and particle fields at all positions in the pump; operation condition parameters are obtained, the thermal wear rate is obtained through a thermal wear rate calculation formula on the basis of flow field and particle field information of all positions in the pump, and the predicted wear amount of the flow passage component is obtained; and the prediction precision and applicability of the wear model are improved.

The invention discloses a PINN-based grinding temperature prediction method and a transfer learning model, and belongs to the field of slow feed grinding and the technical field of neural networks. The method comprises the following steps: establishing an unsteady state heat conduction control equation, and defining a composite boundary condition; calculating the heat flux density of a heat source based on set grinding process parameters and workpiece material characteristics; constructing a PINN temperature prediction model; based on sparse temperature measurement data, a gradient optimization algorithm is adopted to dynamically invert and correct a heat conduction coefficient and a convective heat transfer coefficient; establishing a transfer learning mechanism, and accelerating solution of a PINN temperature prediction model under a new working condition; high-risk regions exceeding the critical damage temperature of the material are identified based on the predicted temperature field, and processing parameters are optimized to prevent grinding burns. According to the method, the unsteady heat conduction equation is embedded into the neural network, empirical formula constraint is replaced, and the physical consistency of the dynamic process is ensured; meanwhile, the method can achieve the inversion of key physical parameters based on a very small number of temperature measurement points, and solves a problem of boundary condition uncertainty.

The invention discloses a dynamic submarine cable response extremum prediction method and device fusing a physical mechanism and a dynamic time sequence characteristic, and the method comprises the steps: deeply fusing a dynamic submarine cable control equation and data driving training through a physical information neural network, and converting the mechanical mechanism of a dynamic submarine cable into a residual constraint term; the defect of poor generalization of a pure data driving method is overcome; amplitude characteristics of six-degree-of-freedom motion of the floating body are extracted through an LSTM time sequence prediction model, and a long time sequence dynamic coupling effect is compressed into physical interpretable characteristics; a structure type judgment module is designed, so that two types of mainstream submarine cable structures can be covered without reconstructing the model, and the engineering applicability is greatly enhanced; dynamically balancing data fitting loss, physical residual loss and motion prediction loss by adopting a time-varying weight strategy, accelerating convergence and ensuring that a prediction result accords with a physical rule; dynamic submarine cable strength failure early warning is provided for offshore wind power by outputting key node response extreme values and motion amplitude characteristics in real time, and the operation and maintenance cost of the offshore wind power is greatly reduced.

The invention relates to the field of oil and gas reservoir drilling, and provides a borehole wall stability analysis method for a deepwater shallow long horizontal well, which comprises the following steps: carrying out mechanical parameter test on a weakly cemented rock sample to obtain basic mechanical characteristic parameters; performing time-varying strength modeling on the weak cementation constitutive structure to obtain a damage evolution model; performing three-dimensional finite element modeling on the stratum around the borehole to obtain a numerical calculation model; establishing a control equation set, and discretely solving the control equation set through the numerical calculation model to obtain a field variable solving result; and well wall stability analysis is carried out based on the field variable solving result, and an analysis result is obtained. According to the method, the well wall stability prediction precision of the deep-water shallow-layer long horizontal well is improved, and the safety of well drilling is improved.

The invention discloses an ultra-high voltage reactor shell convective heat transfer coefficient iterative calculation method and device, and the method comprises the steps: building a control equation of a temperature fluid field of an ultra-high voltage reactor, and building a function expression for obtaining a comprehensive convective heat transfer coefficient; the comprehensive convective heat transfer coefficient comprises a convective heat transfer coefficient under a natural convection condition and an equivalent radiation heat transfer coefficient, the comprehensive convective heat transfer coefficient is corrected step by step through multiple iterations based on a control equation of a temperature fluid field until the comprehensive convective heat transfer coefficient converges, the temperature difference between the wall surface and the external fluid is obtained, and the temperature difference between the wall surface and the external fluid is obtained. And taking the converged comprehensive convective heat transfer coefficient as a final convective heat transfer coefficient. According to the method, the equivalent radiation convective heat transfer coefficient is provided, the comprehensive convective heat transfer coefficient is obtained by combining the convective heat transfer coefficient under the natural convective heat transfer condition, and the accurate temperature difference between the wall surface and the external fluid is obtained through multiple times of iterative calculation.

The invention discloses a mass concrete construction temperature control anti-cracking integrated system and method, and the system comprises a construction module which is used for constructing a cooling water pipe fine model based on concrete thermodynamic parameters and construction conditions, solving a heat flow coupling control equation through a heat flow coupling algorithm, and determining a concrete internal temperature field and stress field distribution cloud chart; the monitoring module is used for collecting attribute data of concrete; the comparison module is used for comparing the attribute data with the concrete internal temperature field and stress field distribution cloud atlas, correcting model parameters of the heat flow coupling model according to a comparison result, generating a regulation and control instruction and sending the regulation and control instruction to the execution module; the execution module is used for receiving and executing the regulation and control instruction; the regulation and control instruction comprises at least one of temperature regulation and pouring time sequence optimization. A temperature field and a stress field are accurately predicted, complex construction working conditions are matched, mechanical and thermal state changes of the whole life cycle of concrete are captured in real time, temperature control adjustment is effectively conducted, and the construction quality is improved.

The invention discloses a split type three-box girder nonlinear vortex vibration steady-state amplitude intelligent prediction method, belongs to the field of bridge vortex-induced vibration control, and aims to solve the problem of low accuracy of three-box girder vortex vibration nonlinear modeling and amplitude prediction. The method comprises the following steps: acquiring displacement time sequence data through a reduced scale model wind tunnel test, preprocessing to obtain displacement, speed and acceleration dimensionless data, and dividing a data set; constructing a candidate function library containing high-order polynomial terms of the primary function; performing nonlinear system sparse recognition by taking acceleration data as a target item and combining an improved algorithm to obtain a preliminary feature set; a final feature set is obtained through energy-statistics-self-adaption three-stage screening; and finally, constructing a control equation to predict the steady-state amplitude. The method can accurately predict amplitude, coincide test and real bridge observation results, and is less in computing resource occupation and high in numerical value precision.

Provided is a three-dimensional thermal-hydraulic analysis method and system for a reactor core. The method includes: analyzing a type of a reactor core, dividing an outer-layer mesh and a computational mesh, and establishing a conservative mapping relationship and a set of transport equations; decomposing a coolant viscosity-induced frictional effect, and representing a turbulent mixing-induced exchange of a physical quantity through a source term; establishing a three-dimensional set of governing equations including mass, momentum, and energy conservation equations to describe a flow and heat transfer phenomenon within coolant channels, and forming a fully assembled matrix system based on the set of transport equations; setting a boundary condition and an initial condition for a physical field of the reactor core, and setting an initial field; and iteratively solving the fully assembled matrix system, and obtaining a thermal-hydraulic parameter.

The invention discloses an intelligent well site comprehensive management system based on digital twinning and AI analysis, and belongs to the technical field of digital twinning. Uniformly representing the multi-physical field data as a tensor data structure including a space dimension, a time dimension and a physical quantity dimension; performing data fusion on the tensor data structure and the three-dimensional geometric model of the well site, and establishing a spatial association relationship of multi-physical field data at grid nodes; establishing physical field control equations based on the fused data, and correlating the equations through a coupling operator to form a multi-physical field coupling equation; solving the coupling equation to obtain a numerical solution of each physical field distribution; generating a control instruction sequence for adjusting the operation parameters of the well site equipment according to the numerical solution; according to the invention, accurate sensing and intelligent regulation and control of the operation state of the well site equipment are realized, and the intelligent level of well site management is obviously improved.