664 results about "Field simulation" patented technology

The invention relates to the technical field of press monitoring, in particular to a digital twinning-based three-dimensional monitoring system for a precision servo press, which comprises a physical layer sensing module for acquiring real-time operating parameters, environment variables and workpiece processing data of the press; the dynamic twin construction module constructs a total-factor digital twin, and simulates a force-heat-deformation coupling effect by using finite element analysis and a multi-body dynamics algorithm based on physical attributes and process parameters; the intelligent analysis center identifies a potential fault mode of the press machine and locates an abnormal source through multi-physics field simulation data in combination with an improved CNN-LSTM model; the three-dimensional visual interaction unit constructs an interactive immersive three-dimensional virtual scene, renders a running state and a processing process in real time, and generates a maintenance strategy; and the self-adaptive regulation and control unit predicts the residual life of the key component and dynamically adjusts parameters according to a maintenance strategy and real-time monitoring data. Therefore, the problems of single monitoring dimension, disjunction of maintenance strategies and the like in the prior art are solved.

The invention relates to the technical field of image classification, in particular to a training method and system of a cervical pathological image classification model based on multiple modes. The method comprises the following steps: acquiring a cervical tissue image and carrying out tissue structure segmentation, forming a nucleus-interstitial-epithelium three-distribution framework, collecting development historical data, confirming a prediction trend of each layer, carrying out environment field simulation through the image, generating a simulated cervical environment field, and carrying out hierarchical evolution prediction on the framework. Evolution mapping images are generated according to the evolution data and classified, finally, a visual basic model is obtained through combined modeling training, image-text fusion is achieved, and a cross-center deployment model system is generated. According to the method, vision-language combined modeling is realized, and the stability and controllability of the whole model structure in image space deformation modeling, semantic cross-modal alignment construction and task-level response flow scheduling are improved.

The invention discloses an intelligent management system and method applied to a radio frequency energy output device, and belongs to the technical field of intelligent management of the radio frequency energy output device.An integrated sensor array is deployed on a radio frequency host and a hand tool electrode, and load voltage, output current, electrode temperature and tissue impedance are synchronously collected; a dynamic thermal impedance collaborative analysis model is constructed after time synchronization alignment, a three-dimensional thermal field simulation map is generated, and a thermal accumulation trend is predicted; a double-layer control framework is constructed, a first control layer generates a dynamic power adjustment rule base based on a preset treatment target and a safety threshold value and outputs an instruction, a second control layer receives the instruction and adjusts output parameters in real time, and a strategy is adjusted by combining a model prediction result in the execution process; meanwhile, the operation state is continuously monitored, a fault classification model is constructed for anomaly detection, a fault source is positioned, and a visual report is generated; and finally, constructing a mapping relation based on historical data, and generating an energy control scheme adapted to individualized requirements through iterative optimization.

The invention discloses a laser processing parameter autonomous generation system and method based on digital twinning, and relates to the field of digital twinning, and the method comprises the steps: collecting and preprocessing processing data in real time through a multi-source sensor; processing and analyzing the task instruction by using a natural language, extracting a constraint condition and forming a structured demand; a processing parameter candidate set is generated through a Transform model in combination with historical data transfer learning, and virtual processing is performed by means of multi-physics field simulation; an improved non-dominated sorting genetic algorithm is adopted to dynamically optimize the parameter weight, and a global optimal parameter combination is obtained through digital twin iteration verification; and after full-process virtual processing verification and task demand comparison, parameters are adaptively corrected, and model parameters are continuously optimized according to physical and simulation data deviation after actual processing. The method has the advantages that the digital twin is used as a core, multi-source real-time data, the AI algorithm and multi-physical field simulation are fused, and autonomous generation, multi-target optimization and virtual-real closed-loop iteration of laser processing parameters are achieved.

The invention provides a double-pulse high-frequency switching power supply control method and system for precise electroplating, and relates to the field of electroplating, and the method comprises the steps: collecting area surface data through a three-dimensional scanner, and obtaining a three-dimensional model; extracting a high-curvature area grid according to the three-dimensional model, and calculating to obtain a surface concave-convex degree index; performing current field simulation, and calculating current density vector distribution; when the deviation of the current density vector distribution exceeds a preset deviation threshold value, pulse parameters are optimized through a genetic algorithm; selecting a pulse parameter which is most matched with the surface concave-convex degree index, and carrying out iterative calculation to obtain updated current density vector distribution; based on the difference between the updated current density vector distribution and the initial distribution, predicting a coating thickness value, and determining a preliminary evaluation index; and optimizing pulse parameters to obtain a final control scheme of uniform current distribution. According to the method, pulse parameters can be dynamically optimized according to the geometrical shape of the workpiece, and uniform current distribution and stable plating quality are realized.

A multi-physics computation method and system for digital twin online simulation, relating to the technical field of physics simulation. A multi-physics coupling simulation computation model of a simulated object is established, and the multi-physics coupling simulation computation model is simplified, and the order of a temperature field simulation model is reduced, thereby greatly reducing the amount of computation, and improving computational efficiency; a low-precision dataset is obtained by means of temperature field analysis, so that the data size required for a model is reduced by means of low-precision data, thus reducing modeling costs; and a basic data-driven model is constructed by means of the low-precision dataset and a sample space corresponding to the low-precision dataset, so that a temperature field distribution result can be rapidly outputted, further improving computational efficiency and reducing computational errors.

The invention relates to the technical field of torque converters, in particular to a hydrodynamic transmission power chain optimization method and system.The method comprises the steps that a hydrodynamic torque converter parameterized geometric model is built, and a pump impeller blade outflow angle, a guide wheel runner input / output angle, turbine blade geometric parameters and the relative position of a pump impeller and a turbine are set as design variables; based on CFD three-dimensional flow field simulation, a k-epsilon model is adopted for rapid analysis, an SST model is adopted for transient simulation, and simulation data under different variable combinations are obtained; training a BP neural network by using the simulation data, inputting each design variable, and constructing a multi-target optimization model with maximization of efficiency and minimization of noise as targets; a design variable combination is selected in the Pareto optimal solution set, a model is reconstructed, and an optimized hydraulic torque converter is obtained; according to the method, the problems that the design optimization efficiency of the hydraulic torque converter is low, the parameter adjusting period is long, and good compromise between the transmission efficiency and noise suppression is difficult to obtain can be solved.

The invention relates to the technical field of bridge engineering intelligent construction, discloses a digital twinborn and multi-physics field simulation-based lattice pier assembly error intelligent prediction method, and aims to construct a lattice pier assembly error prediction model. The lattice pier assembly error prediction model is composed of a channel independent feature extraction module of multi-physics field data, a self-adaptive space-time coupling and multi-factor dynamic fusion module and a training lattice pier assembly error prediction model, the multi-physical field data channel independent feature extraction module maps data of each physical field to a high-dimensional feature space through calculation, and according to a state space model, the adaptive space-time coupling and multi-factor dynamic fusion module introduces a plurality of factors to dynamically adjust weights of the physical fields in different time steps. Carrying out adaptive fusion on the processed physical field data through a space-time coupling function to obtain coupled physical field data; and finally, taking the output of the two as the input, and combining a regression model to predict the lattice pier assembly error.

The invention discloses a PINN-based transformer convective heat transfer coefficient acquisition method, system and device and a medium, and relates to the technical field of transformers, and the method comprises the steps: building a three-dimensional thermal field simulation model based on transformer structure parameters, obtaining temperature field data through multi-physics field coupling simulation, building a sample set, training a physical information neural network model, and obtaining the convective heat transfer coefficient of a transformer. A loss function is defined, through weight adjustment and optimization algorithm training, loss change is dynamically monitored, convective heat transfer coefficient distribution is inversed, an inversion coefficient is substituted into a thermal model for forward calculation, iterative optimization is performed through comparison with independent measurement data, and accuracy and applicability are verified through actually measured temperature data. According to the method, the dependence on experimental data is reduced, the high-precision and high-efficiency acquisition of the convective heat transfer coefficient of the spatial change of the transformer is realized, and a reliable technical means is provided for thermal design and state evaluation of the transformer.

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

The invention relates to the technical field of glass hot working control, and discloses a rapid prototyping control system and a rapid prototyping control method for tempered glass production. Comprising a thermal coupling module, a temperature control decision module, a flow field solving module, a photoelastic stress analysis module, a quantum annealing optimization module and a time domain synchronous control module. According to the system, a three-dimensional thermal-stress field is constructed on the basis of physical properties and thermal boundaries of glass, heating power is predicted through reinforcement learning, flow field simulation and stress image analysis are combined, control parameter self-adaptive adjustment is achieved through quantum annealing optimization, beats of all subsystems are coordinated through a synchronization module, and an efficient closed-loop control structure is formed. By introducing the quantum annealing optimization module, parameter adjustment in the control system is optimized, the technical effect of improving the precision of complex control decisions is achieved, and the optimization speed and the decision quality of the system are improved.

The invention belongs to the technical field of helicopters, and relates to a helicopter rotor blade-vortex interference noise suppression effect analysis method and system. The method comprises the following steps: establishing a CFD model for solving a helicopter rotor paddle-vortex interference flow field; establishing a CSD model for solving the helicopter rotor paddle-vortex interference flow field; establishing a coupling model; carrying out helicopter rotor paddle-vortex interference flow field simulation; establishing an FW-H model, and performing BVI noise calculation on the rotor blade; establishing an HHC numerical calculation model; and evaluating the inhibition effect of the HHC numerical calculation model on the BVI noise. According to the method, the unsteady effect of the blade can be fully considered, the unsteady air load on the surface of the rotor blade can be accurately simulated, the blade elastic deformation and the aeroelastic coupling effect caused by the HHC numerical calculation model are further deeply considered, the actual dynamic behavior of the blade is simulated, and then the prediction precision of the HHC numerical calculation model on the BVI noise suppression effect is enhanced.

The invention provides a large aqueduct intelligent temperature control system and method based on a digital twinning technology, and relates to the technical field of aqueduct temperature monitoring. A three-dimensional digital model of an aqueduct is constructed, and geometric parameters of the three-dimensional digital model are corrected through three-dimensional point cloud data of the aqueduct, so that the temperature of the aqueduct can be accurately controlled. Thermodynamic simulation calculation is carried out based on the three-dimensional digital model to obtain a simulation result, the aqueduct concrete temperature field simulation result is compared with the collected aqueduct temperature to obtain temperature deviation, parameters of thermodynamic simulation calculation are corrected according to the temperature deviation, and therefore the simulation result is updated, and the accuracy of the simulation result is improved. According to simulation results obtained after geometric parameters of the three-dimensional digital model and parameters obtained after thermodynamic simulation calculation are corrected, the water flow of the corresponding water pipe is controlled for cooling, local targeted cooling is achieved, and the problem that targeted cooling cannot be achieved for too high local hydration heat in the prior art is solved; the method is suitable for intelligent temperature control in the hydration heat process of the large aqueduct.

The invention relates to the technical field of power system intelligent monitoring, and discloses a construction method and system of a digital twinborn model of a cable tunnel, and the method comprises the steps: collecting the skin temperature data and physical geometric data of a high-voltage cable in the cable tunnel through a sensing layer, and constructing a physical geometric model of the cable tunnel; based on the physical geometric data and the temperature data, establishing a cable temperature field simulation model in a network layer, and generating cable temperature field distribution data through multi-physical field coupling simulation; temperature field distribution data and real-time monitoring data are integrated in an application layer, a visual temperature monitoring platform is constructed, and the temperature change trend of the cable is analyzed and predicted through time sequence data. According to the method, the operation state of cable equipment in a cable tunnel is simulated by using a digital twinning technology, and cable holographic temperature sensing is realized. By monitoring and analyzing the temperature of the cable in real time, the load can be reasonably adjusted, the overload and loss of the cable can be reduced, the energy efficiency of a power system can be improved, and the purposes of energy conservation and emission reduction can be achieved.

The invention discloses a suspension type oven flow field optimization method based on CFD dynamic simulation. The invention relates to the technical field of data processing, and the method comprises the steps: constructing a three-dimensional model of a suspension type oven flow field, and splitting the three-dimensional model into a plurality of geometric subdomains according to functions; dividing a corresponding grid sub-domain based on each geometric sub-domain; the grid subarea at least comprises a suspension area; judging whether the quality of the grid subdomains reaches the standard or not, and if not, optimizing division of the grid subdomains; if yes, setting a boundary condition and a physical model for the grid sub-domain; performing flow field simulation analysis on the grid sub-domain to obtain simulation data; comparing and analyzing the simulation data and the multi-dimensional target data to judge whether the model parameters of the oven flow field need to be corrected or not; whether the dynamic key indexes of the oven flow field reach the standard or not is monitored, and if the dynamic key indexes all reach the standard, optimization parameters of the oven flow field are output; and if any dynamic key index does not reach the standard, correcting the model parameters of the oven flow field, thereby improving the suspension stability of the material and realizing the optimization of the oven flow field.

The invention relates to the technical field of data processing, and discloses a cable joint arc multi-physical field simulation method and system. The method comprises the following steps: establishing a defect-containing geometric model, judging according to a temperature gradient change rate and a current rising rate to obtain an adaptive time step length, and carrying out bidirectional coupling iteration on an arc temperature field and a material dielectric parameter based on the time step length to obtain an accumulated damage factor; arranging a virtual temperature detection point to convert the simulation temperature field into a virtual monitoring signal, extracting temperature characteristic parameters and ultrasonic spectrum characteristic parameters, and projecting the temperature characteristic parameters and the ultrasonic spectrum characteristic parameters to a two-dimensional characteristic space to obtain a fault mode fingerprint spectrum. According to the method, adaptive adjustment of the time step length is realized by establishing an arc evolution phase discrimination mechanism, and the problems of low calculation efficiency and insufficient transient characteristic capture caused by a fixed time step length are solved.

The invention relates to the technical field of material thermal performance testing, and discloses a material heat conductivity coefficient automatic testing method based on a heat flow gradient method. The method comprises the following steps: firstly, constructing a test environment topology network, collecting three-dimensional structure parameters and environment thermodynamic parameters of a tested material, and inputting the parameters into a thermal field simulation system to generate an internal heat flow distribution model; and analyzing internal cavity distribution characteristics according to the three-dimensional structure parameters, matching the internal cavity distribution characteristics with a cavity characteristic-heat source layout mapping table to determine a steady-state heat source layout scheme, and activating a heat flow gradient analysis device when multiple heat sources are needed. A heat conduction parameter database is called, heat source power parameters and temperature acquisition parameters are extracted based on environmental thermodynamic parameters, the heat source power parameters comprise spacing, axial angles and the like, and the temperature acquisition parameters comprise thermocouple types and acquisition frequencies; and finally, simulating temperature field evolution through a heat flow gradient analysis device, outputting and analyzing related data, and generating a parameter optimization instruction to adjust heat source configuration. According to the method, multiple links are coordinated, material structures and environmental factors are integrated, and automation of the testing process is achieved.

The invention discloses a temperature field simulation method, device and equipment for an outdoor high-voltage isolation switch and a storage medium, belongs to the technical field of power transmission and transformation, and solves the problems that a calculation result is disjointed from an actual operation and maintenance environment and the application range is narrow due to the adoption of an existing power equipment temperature distribution method. The invention discloses a temperature field simulation method for an outdoor high-voltage isolating switch. The method comprises the following steps: establishing a multi-physical field coupling finite element model according to a geometric structure, air material parameters and rated current of a target outdoor high-voltage isolating switch; and calculating a three-dimensional temperature field of the target outdoor high-voltage isolation switch according with an actual operation state based on the multi-physics field coupling finite element model by taking a variable field distribution value meeting a convergence condition under a pre-calculated forced wind speed as an initial condition and combining the boundary condition. According to the invention, the real position and the temperature rise amplitude of the internal hot spot of the outdoor high-voltage isolation switch can be directly quantified, the result is more accurate and reliable, and misjudgment caused by environmental interference is not easy to occur.

The invention discloses a flexible sunlight greenhouse temperature control method, system and device and a storage medium, and relates to the technical field of greenhouse environment, the method comprises the following steps: calling a heat transfer model to carry out temperature field simulation calculation according to greenhouse internal thermal field distribution data to obtain a first predicted temperature value; calling a greenhouse temperature prediction model to perform time sequence analysis on the external environment temperature historical time sequence data to obtain a second predicted temperature value; performing data fusion according to the first predicted temperature value and the second predicted temperature value to obtain a comprehensive predicted temperature value; and according to a deviation value between the comprehensive prediction temperature value and a preset greenhouse air temperature target value, adjusting operation parameters of the greenhouse equipment. By simulating thermal field distribution in a greenhouse and processing time sequence data of an external environment, a deterministic rule and random fluctuation are covered, a deviation value with a target value is calculated according to an obtained comprehensive prediction value, and equipment is dynamically adjusted based on prediction deviation, so that ineffective energy consumption and equipment loss are reduced.

The invention discloses a CFD (computational fluid dynamics) boundary processing acceleration method based on GPU (graphics processing unit) parallelism, and belongs to the technical field of fluid mechanics related calculation. The problem that in the prior art, a traditional CFD boundary processing acceleration method is low in calculation efficiency is solved. The method comprises the following steps: generating a computational grid required for simulating a flow field, and reading grid information and boundary condition information of computational simulation; initializing a flow field according to the calculation parameters, copying flow field data and flow field boundary information from a main memory to a video memory, establishing a boundary pointer array in the video memory, and instantiating a boundary pointed by each pointer; according to the boundary pointer array, the flow field data and the flow field boundary information, time step cycle calculation is carried out by utilizing a GPU, and physical quantity updating of a boundary virtual unit corresponding to the thread is realized; and after time step cycle calculation convergence, video memory flow field data are copied to a main memory, and flow field simulation calculation is completed. The method effectively improves the calculation efficiency, and can be applied to CFD boundary processing.

The invention relates to the technical field of welding cooling, and provides a liquid nitrogen spraying welded plate cooling device and a design method thereof.The cooling device comprises a liquid nitrogen source used for providing liquid nitrogen; the input end of the spraying module is connected with a liquid nitrogen source through a main pipeline, the output end of the spraying module is provided with a plurality of spraying holes corresponding to the surface of the welded plate, and the main pipeline is provided with a flow regulating valve; the temperature acquisition module comprises a plurality of temperature sensors which are arranged at temperature measuring points of a welding plate; the control module is electrically connected with the temperature acquisition module and the flow regulating valve respectively; the structure of the spraying device is optimized through flow field simulation, it is ensured that liquid nitrogen is evenly distributed to the surface of a welded plate, local supercooling or superheating is avoided, and uniform cooling of the welded plate is achieved; data are collected through the temperature sensor, closed-loop control is formed in cooperation with the PID controller and the multiple adjusting valves, the liquid nitrogen flow, the spraying area and the spraying time can be accurately regulated and controlled, the inter-channel temperature is effectively controlled, the temperature is prevented from being too high, and it is guaranteed that the welding process is continuously and stably carried out.

The invention discloses a heat pump drying experiment method based on 1D-3D joint simulation, particularly relates to the crossing field of heat energy engineering and simulation modeling, and aims to solve the problem of insufficient precision caused by disconnection of a heat pump system and cavity flow field simulation in a heat pump drying process in washing equipment such as a dish-washing machine. The method comprises the following steps: establishing a heat pump system one-dimensional dynamic model and a cavity three-dimensional flow field model, dynamically setting one-dimensionally output air supply temperature and humidity parameters as a three-dimensional inlet boundary, and meanwhile, feeding back three-dimensional air return parameters to a one-dimensional evaporator adjusting boundary to form closed-loop coupling iteration, so as to obtain a three-dimensional flow field model; dynamic high-precision simulation of the whole drying process is achieved, the structure optimization efficiency and the energy consumption evaluation reliability are effectively improved, part of physical tests are replaced, and the development cost is reduced.

The invention discloses a rock unconventional reservoir carbon dioxide fracturing temperature field simulation method and system, and belongs to the technical field of oil and gas exploitation. Rock unconventional reservoir parameters and wellbore parameters are obtained, fluid physical property parameters of carbon dioxide fracturing fluid flowing in a wellbore are determined, and a multi-dimensional physical partition model is constructed; the unconventional reservoir is divided into a plurality of physical areas including a fluid flowing area, a static fluid area, a solid area and a porous medium area; thermal boundary conditions of all physical areas are coupled through an energy conservation equation, stratum elasticity modulus and Poisson's ratio are added to the thermal boundary conditions, a thermal-force coupling equation is constructed, carbon dioxide fracturing construction parameters obtained in real time are estimated, temperature field distribution nephograms of carbon dioxide fracturing fluid at different moments in the shaft flowing process are obtained, and the temperature field distribution nephograms of the carbon dioxide fracturing fluid at different moments are calculated. According to the method, the temperature distribution rule of different fracturing stages in the shaft-crack direction can be truly reflected.

The invention particularly relates to a spatial analysis method based on large model agent driving. According to the spatial analysis method based on large model agent driving, syntactic analysis and intention recognition are carried out on a spatial problem described by a natural language through a large model, and spatial-temporal clustering, network analysis and a field simulation algorithm module are dynamically matched; packaging a heterogeneous algorithm into a standardized service component based on a model context protocol (MCP), and automatically constructing an analysis process chain; and integrating a GIS engine and a visual template library, generating a dynamic thematic map according to the processed spatio-temporal data through the visual engine, and superposing multi-dimensional analysis annotations. According to the spatial analysis method based on large model agent driving, the full-chain intelligent capability from data processing to decision support is constructed, the efficiency and precision of spatio-temporal evolution modeling are remarkably improved, meanwhile, the system integration and maintenance cost is reduced, the method is suitable for high-complexity scenes needing real-time spatio-temporal data analysis, and the method is suitable for popularization and application. And the method has remarkable technical innovation and industrial application value.

The invention provides a fishery breeding risk area division method and related equipment, and relates to the technical field of breeding area planning. The method comprises the steps of simulating a disturbance effect of a fan group on a water flow field based on a geometric model of the fan group in combination with marine environment data of a target sea area where the fan group is located, and obtaining a water flow field simulation result; determining a risk area in the target water area based on the water flow field simulation result; inputting the flow velocity data of the risk area at each moment in the first time period into a pre-established water flow prediction model to obtain flow velocity data of the risk area at each moment in a second time period; and respectively mapping the flow velocity data of the risk area at each moment in the second time period into risk levels, and dynamically dividing the risk area in the target water area based on the risk levels. According to the method, the water flow field near the fan group can be simulated, and the preliminary risk area is determined. And through the water flow prediction model, predicting the water flow change trend at each moment in the future, and dynamically adjusting the risk area.

The invention relates to the field of underwater pressurization, and discloses an underwater contra-rotating compressor blade tip leakage flow vibration prediction method and system based on fluid-solid coupling simulation, and the method comprises the steps: carrying out the division of flow field grids and the division of solid domain grids based on a constructed underwater contra-rotating compressor impeller three-dimensional model; establishing a blade flow field CFD model and a blade solid domain FEA model; aNSYS Fluent software is used for conducting underwater contra-rotating compressor three-dimensional unsteady blade flow field simulation so as to obtain unsteady blade tip leakage flow characteristics of a concerned flow field area; an external data module in ANSYS Workbench software is used for loading the aerodynamic force, obtained through unsteady flow simulation, of the surface of the blade to the surface of a blade solid domain FEA model, transmission of the aerodynamic force load between different blade surface grids is achieved, and one-way fluid-solid coupling is achieved; aNSYS Workbench software is used for conducting underwater counter-rotating compressor blade vibration simulation, vibration response of the blade under the combined action of aerodynamic force and centrifugal force is obtained, and the fatigue life of the blade is predicted based on a fatigue model.

The invention discloses a method for predicting shock waves through a multi-region conservation enhanced physical information neural network, and belongs to the field of flow field prediction of shock waves and strong nonlinear physical phenomena in high-speed flow, and the method comprises the steps: S1, carrying out numerical simulation through fluid dynamics software to obtain a reference flow field solution of a to-be-solved N-S control equation, the verification module is used for verifying a model solving result; s2, constructing a neural network comprising an integral layer, a micro-layer and a loss function error layer; s3, constructing a physical information neural network; s4, training is carried out after physical information neural network training parameters are set, and whether a convergence standard is met or not is determined by constructing a joint loss function corresponding to the physical information neural network; and S5, applying the trained neural network model to shock wave prediction of high-speed flow field simulation under different working conditions. Through the multi-region local conservation constraint, the width of the shock wave transition region is effectively compressed, so that the relative error of the physical quantity is obviously reduced compared with the existing method.

The invention discloses an intelligent energy-saving regulation and control system and method for a silicon single crystal thermal field. The system comprises a multi-physical field acquisition unit, a thermal field simulation calculation module, a gradient thermal insulation assembly, an AI regulation and control module, a feedback execution control module and an energy consumption evaluation module. The system constructs a coupling temperature field / flow field model by collecting temperature, flow velocity and pressure data in a furnace in real time, generates a dynamic control strategy by using an AI algorithm, and drives a heater, a cooling system and an adjustable graphite felt assembly to cooperatively respond; the gradient heat insulation assembly adapts to heat flow distribution through the axial heat conductivity decreasing design, and heat loss is reduced. The method comprises the steps of data acquisition, simulation modeling, AI strategy generation, execution control, quality evaluation and model correction, and closed-loop optimization is formed. The method realizes intelligent dynamic regulation and control of thermal field distribution, remarkably improves crystal growth quality and energy efficiency, and is suitable for the field of semiconductor silicon single crystal preparation.

The invention belongs to the technical field of geological energy storage, and particularly provides an underground chamber surrounding rock thermal-mechanical coupling fatigue phase field simulation method and system, and the method comprises the steps: building a phase field evolution equation through a phase field fracture model and a fatigue degradation function; on the basis of the calculation model, according to the air temperature and pressure in the cavern, the Newton heat exchange law is adopted to calculate cavern wall heat exchange, and a cavern wall heat conduction equation is constructed; on the basis of the calculation model, utilizing rock mass displacement and surrounding rock strain to construct a rock mass deformation equation; performing numerical discretization on the phase field evolution equation, the cave wall heat conduction equation and the rock mass deformation equation on a finite element grid unit, and performing thermal-mechanical coupling solution on all discretized equations through an iterative method to obtain evolution results of a temperature field, a stress field, a displacement field and a crack phase field of the underground chamber surrounding rock target area. According to the method, the phase field method is applied to thermal-mechanical coupling simulation of the underground gas storage chamber surrounding rock crack propagation condition, and the authenticity of chamber crack simulation is reflected to the maximum extent.

The invention relates to the cross technical field of industrial intelligent simulation and computational material science, in particular to a phase field simulation method and device based on physical constraint deep learning and electronic equipment, and the method comprises the steps: obtaining phase field parameters of a to-be-predicted material, including an initial phase field value, an initial material mobility tensor and an initial free energy density coefficient, the phase field parameters are input into a pre-trained prediction model, so that a phase field simulation result of the to-be-predicted material is obtained, and the pre-trained prediction model is used for predicting the phase field of the to-be-predicted material based on the improved LSTM network, a preset hybrid forward propagation strategy and a preset parameter coupling mechanism. And training a preset neural network by using a mixed loss function and a sub-path gradient back propagation strategy. Therefore, the problems of low phase field simulation calculation efficiency, physics non-conservation of a data driving model and the like in the related technology are solved, physical equation constraints are embedded into the neural network through a hybrid model architecture, and efficient and accurate prediction of material microstructure evolution is realized.