385 results about "Field simulation" patented technology

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 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 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 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 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 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 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 discloses an aero-engine hot end component temperature field reconstruction method based on multi-source data fusion, and belongs to the technical field of aero-engine thermal analysis and data driving modeling. The method comprises the following steps: carrying out temperature field simulation and local temperature point test, and respectively obtaining a simulation data set and a test data set of a part; fusion of simulation data and test data is realized by using a data fusion technology, and a high-quality temperature database with precision and mass advantages is constructed. Establishing a temperature field reconstruction model based on a machine learning technology, and training the temperature field reconstruction model through data of a multi-source database; and the trained model is utilized to realize rapid reconstruction and visual output of the component temperature field under multiple working conditions. According to the method, the continuity of simulation data and the authenticity of test data are fully fused, and the precision and stability of temperature field reconstruction are improved.

The invention discloses a centrifugal pump blade damage suppression design and optimization method based on multi-physics field coupling, which comprises the following steps: constructing a fluid grid model of a centrifugal pump and carrying out transient flow field numerical simulation comprising a cavitation model and a dispersed phase model to obtain transient flow field simulation results of a cavitation field and a dispersed phase motion field; according to the transient flow field simulation result of the cavitation field, cavitation collapse wall surface energy is calculated, and a first correlation model of the blade geometric parameters and cavitation collapse energy is established; according to a transient flow field simulation result of the dispersed phase motion field, calculating particle impact wall surface energy, and establishing a second correlation model of the geometric blade parameters and the particle impact wall surface energy; and according to the first correlation model and the second correlation model, the cavitation collapse energy and the particle impact energy are controlled to suppress damage generated by multiple physical fields coupled with cavitation and particle impact, and multi-objective optimization is carried out in a mode of minimizing the cavitation collapse energy and minimizing the particle impact energy, so that optimal blade parameters are determined.

The invention discloses a low-carbon and energy-saving fattening pig house air conditioner control method which comprises the following steps: S1, constructing a grid digital twinborn model of a pig house, and initializing the grid digital twinborn model by using sensor data; s2, based on the gridding digital twin model, physical flow field simulation is executed, and temperature field distribution in the hog house is obtained; s3, temperature field distribution is analyzed, a temperature anomaly region needing to be regulated and controlled is recognized, and the attribute of the temperature anomaly region is quantified; s4, determining a target regulation and control unit and calculating regulation and control parameters of the target regulation and control unit based on the attribute of the temperature abnormal region; and S5, executing regulation and control and updating the digital twin model based on feedback data to form predictive closed-loop control based on physical simulation. By eliminating a local hot / cold stress area, the uniformity and stability of the hog house hot environment are greatly improved, meanwhile, a precise on-demand regulation and control mechanism is achieved, global excessive air supply is avoided, and substantive low-carbon and energy-saving effects in the operation process are achieved.

The invention relates to the technical field of fire risk assessment, in particular to a fire risk assessment method and device for an energy storage power station, electronic equipment and a computer readable storage medium, and the method comprises the steps: obtaining the structure information and equipment information of the energy storage power station, and constructing a three-dimensional simulation model; a three-dimensional simulation model is used for conducting simulation analysis through multiple physical fields, and disaster diffusion trends under various emergencies are obtained; the method comprises the following steps: simulating an emergency response plan in a multi-physics field simulation process based on disaster diffusion trends under various emergencies, fire-fighting equipment deployed by an energy storage power station and the corresponding emergency response plan, and performing fire-fighting risk assessment on a simulation result to obtain an assessment result. Modeling is carried out by utilizing physical characteristics and fire dynamics, so that the fire extinguishing design efficiency and accuracy are improved, the design cost and time investment are remarkably reduced, and a powerful guarantee is provided for the fire safety of the energy storage power station.

The invention discloses a stake car wind resistance dynamic optimization method and system based on airflow simulation, and belongs to the field of automobile pneumatic optimization. A stake car three-dimensional structure model is constructed, and spatial distribution parameters and surface roughness parameters of a stake component are extracted; establishing a multi-working-condition external flow field simulation model, and obtaining a unit area wind resistance coefficient distribution diagram; constructing a wind resistance sensitivity matrix, and identifying a high-sensitivity component; performing disturbance modeling on the high-sensitivity component, generating a local deformation configuration sample and establishing a simulation model set; parallel simulation calculation is carried out, and wind resistance coefficient and aerodynamic stress data are extracted; based on a multi-objective optimization algorithm, determining an optimal disturbance configuration; outputting a structure adjustment suggestion for guiding dynamic design optimization; according to the method, collaborative optimization of wind resistance reduction and structure safety can be achieved, and the pneumatic performance and the energy-saving level of the whole stake car are improved.

The invention discloses a mechanical product multi-field simulation and prediction system based on digital twinning, and relates to the technical field of thermal error digital twinning. A main shaft load current, a rotating speed, a bearing temperature, a workpiece surface temperature and a cooling liquid parameter are obtained in real time; rapidly predicting a first thermal error according to the load current and the rotating speed by using a preset multi-layer feed-forward neural network, dynamically calculating a thermal inertia time coefficient in combination with the cooling liquid efficiency and the thermal state of a workpiece, and filtering and extracting a slowly-changing thermal state from the temperature of a main shaft bearing according to the thermal inertia time coefficient, thereby obtaining second thermal error prediction; a fusion weight is generated according to the load current change rate and the thermal inertia time coefficient, weighted fusion is carried out on the two predicted values, and a compensation instruction is output; and by monitoring the stability of the fusion weight, the thermal inertia time is reversely and dynamically adjusted to suppress oscillation. According to the method, high-robustness and self-adaptive accurate compensation of complex thermal errors is realized in field processing with changeable environments and working conditions, and the long-term stability of processing precision is remarkably improved.

The invention relates to the technical field of state monitoring and fault diagnosis of wind power generation equipment, and discloses a fault diagnosis system and method for a vertical axis wind power generator based on digital twinning, and the system comprises a physical sensing unit, a digital twinning body, an intelligent diagnosis engine, and a predictive maintenance platform. The physical sensing unit deploys a multi-source sensor to collect real-time data; the digital twin body is a high-fidelity virtual model fusing high-precision geometry, multi-physics field simulation and a data-driven degradation model; and the intelligent diagnosis engine realizes fault identification, positioning and mechanism traceability by comparing measured data with simulation data and combining fault mode library matching and virtual fault injection simulation. According to the method, the digital twin which dynamically interacts with the physical entity in real time and is continuously evolved and updated is constructed, the conversion from threshold alarm to mechanism simulation prediction is realized, and the technical problems that in the prior art, multi-source data is isolated, a diagnosis model lacks physical mechanism support, and dynamic simulation and predictive maintenance cannot be carried out are solved.

The invention discloses an acoustic metamaterial parameter optimization method based on a KAN network and particle swarm optimization, the acoustic metamaterial is of a cylindrical double-layer structure, the upper layer is a porous material layer, and the lower layer is a parallel cavity layer, and the method comprises the following steps: constructing initial structure parameters of the acoustic metamaterial by using a multi-physics field simulation platform, inputting the sound absorption coefficients into a pre-trained KAN proxy model to obtain a plurality of sound absorption coefficients at fixed intervals in middle and low frequency bands; optimizing the plurality of sound absorption coefficients by using a particle swarm optimization algorithm to obtain an optimal structure parameter combination; and verifying the optimal structure parameter combination by using a multi-physics field simulation platform, and obtaining a final optimal structure parameter combination. According to the method, the interpretable KAN proxy model and the particle swarm optimization algorithm are deeply coordinated, and the parameter sensitivity analysis and gradient information provided by the KAN proxy model are utilized to guide the search direction of the particle swarm optimization algorithm, so that the particle swarm optimization algorithm can find the real optimal parameter combination of the acoustic metamaterial.

The invention relates to the technical field of simulation optimization, and discloses a charging module heat dissipation optimization method based on temperature field simulation, and the method comprises the steps: firstly discretizing a heat dissipation space into voxel units, and collecting flow heat data; calculating the flow resistance sensitivity according to the relationship between the flow velocity vector and the main wind direction; calculating an effective convection potential energy density and a gradient vector thereof by combining a Reynolds number and a temperature difference; then, generating a chasing cold source driving vector based on the heat flux demand of the component; establishing a thermal wake flow cone projection model, and calculating a thermal wake flow rejection vector; generating a flow resistance avoidance vector in combination with the regional flow velocity direction; and finally, performing weighted synthesis on the three vectors to obtain optimized displacement, and updating coordinates of the component. According to the technical scheme, through multi-physics field coupling analysis, while a driving component finds a high cooling potential area, flow channel smoothness and thermal wake avoidance are effectively considered, and deterministic optimization of the charging module layout is realized.

The invention discloses a cutting slope reliability assessment method considering fracture spatial variability. The method comprises the following steps: step 1, generating a three-dimensional slope model with soil parameter spatial variability by using a Latin hypercube sampling method; 2, averagely selecting M two-dimensional sections from the three-dimensional slope model constructed in the step 1, calculating 2DFS, and reconstructing a plurality of 2DFS signals from sparse 2DFS data by using a BCS method; step 3, taking the plurality of 2DFS signals obtained in the step 2 as machine learning model input, taking the 3DFS as output, and training machine learning models of the 2DFS and the 3DFS; 4, generating 2DFS random field simulation data by adopting a KL series expansion method; and 5, predicting the 3DFS of the random field data by using a machine learning model, and calculating the reliability. According to the method, only a small number of three-dimensional slope samples and sparse two-dimensional sections need to be calculated, and the efficiency of three-dimensional reliability analysis is greatly improved.

The invention discloses a multi-scale analysis-based gas-water seepage field simulation method, which specifically comprises the following steps of: based on a digital rock core reconstructed by a CT (Computed Tomography) scanning image of a typical rock sample of a target reservoir, adopting a microcosmic pore network flow simulation technology; the change rule of the stratum seepage capacity in different stratum pressure gradients and water drive processes, the use degree of a pore network and the water drive process in a pore are calculated, and then a correlation chart with the rock permeability and the pressure gradients is established and used for rapid measurement and calculation of the actual reserve use degree and the recovery degree of the water-invaded sandstone gas reservoir. The method starts from a rock microcosmic pore channel, the scale is amplified to a macroscopic oil reservoir during application, the method has the cross-scale characteristic, and the method is used for rapidly measuring, calculating and evaluating the reserve utilization degree and the recovery degree of the actual water-invaded sandstone gas reservoir and is beneficial to rapid development of the gas reservoir engineering scheme design in a mine field.

The invention discloses an intelligent package visual effect dynamic simulation and preview system, and relates to the technical field of intelligent simulation, and the system comprises a demand analysis calibration module which receives user input, arranges demands, and transmits the demands to a visual scheme generation module; the multi-field saliency simulation module calls a database and outputs multiple groups of schemes to the multi-field saliency simulation module through a linkage generation technology; the module simulates a dynamic effect, marks flaws and transmits the flaws to the preview feedback acquisition module; the module supports multi-terminal preview, displays flaws and collects and feeds back the flaws to the optimization cost accounting module; the module generates an optimization scheme, quantizes the value, measures and calculates the cost and then returns the value; according to the method, through accurate adaptation of requirements and material structures, potential problems are recognized in advance through multi-field simulation, the period is shortened, and the reliability is improved; the two-dimensional defect algorithm is used for accurate classification, the feedback efficiency is improved through multi-terminal adaptation, cost performance evaluation is formed through cost quantification optimization, the balance between the design effect and the economical efficiency is achieved, and an efficient solution is provided for packaging design.

The invention relates to the technical field of metal plastic processing, and discloses a special-shaped steel bar drawing forming parameter optimization method and system. The method comprises the following steps: extracting geometrical characteristics of a special-shaped section and performing flow field simulation to generate a flow velocity distribution diagram; identifying a potential eddy current region through velocity gradient analysis and determining an influence range of the potential eddy current region; a material flowing path is tracked in the influence range, and a vortex intensity distribution diagram is generated; performing correlation analysis on the vortex intensity distribution diagram and the wall thickness deviation data, and adjusting lubrication process parameters to generate a lubrication condition distribution diagram; superposing and mapping the lubrication condition distribution diagram and the flow velocity distribution diagram, analyzing the influence of shear extrusion stress on the wall thickness evolution, and determining a drawing velocity compensation field; the simulation parameters are updated according to the drawing speed compensation field, and a wall thickness prediction distribution diagram is generated; and by taking the wall thickness uniformity as a target function, iteratively calculating a drawing speed compensation field through an optimization algorithm, and generating drawing forming control parameters. According to the method, the wall thickness uniformity and the machining precision of the special-shaped steel bar are improved.

The invention relates to the technical field of numerical simulation of additive manufacturing nickel-based superalloy, and discloses a temperature field and phase field coupling simulation method of SLM forming nickel-based superalloy, which comprises the following steps: establishing a three-dimensional model of a forming part and a substrate for processing to obtain a temperature field basic model; simulating an SLM forming process on the temperature field basic model according to preset parameters to obtain temperature field data, and importing the temperature field data into a phase field simulation module to serve as predefined temperature field data; coupling the gamma ' / gamma mismatch degree and temperature correlation data to the basic phase field model to obtain a gamma' phase change model, correcting the gamma 'phase change model in combination with predefined temperature field data, and adding a nucleation model based on a Poisson seed method; and based on the gamma'phase change model and the nucleation model, growth and coarsening behaviors of the gamma 'phase in the SLM material increasing process are obtained, and a simulation report is formed. According to the method, the vacancy of gamma'phase structure evolution of the existing nickel-based superalloy with high (Al + Ti) content under the SLM complex thermal history condition is solved, and important help is provided for regulating and controlling the structure to obtain the required mechanical property.

The application discloses an aero-engine ice wind tunnel test section modeling simulation optimization integrated platform, comprising a geometric parameterization modeling module, a mesh division and boundary condition setting module, an aero-engine performance calculation agent model module, a CFD simulation module, an iterative optimization module, a visualization and data analysis module, the application realizes deep coupling of geometric parameterization modeling, CFD simulation, aero-engine performance calculation and multidisciplinary optimization technology, and constructs an automatic closed-loop process of the aero-engine ice wind tunnel test section from geometric modeling to flow field simulation analysis and then to aerodynamic layout optimization, so that the high efficiency of calculation is ensured, the accuracy of simulation results is improved, a fast, accurate and scalable technical tool is provided for accurate flow field simulation and efficient aerodynamic layout optimization of the aero-engine ice wind tunnel test section, and the technical problems of long design period, low efficiency and high cost of the aero-engine ice wind tunnel test section are solved.

The invention relates to the technical field of vapor deposition coating, in particular to a coating device airflow field optimization method and system, electronic equipment and a computer readable storage medium, and the method comprises the steps that a first coating device simulation model is established based on original structure parameters of an entity coating device, and the original structure parameters comprise to-be-adjusted parameters; configuring simulation parameters and simulation boundary conditions of the first coating device simulation model according to preset process conditions of the entity coating device to obtain a second coating device simulation model; performing airflow field simulation based on the second coating device simulation model to obtain a simulation result; judging whether the simulation result meets a preset condition or not; and when it is determined that the simulation result meets a preset condition, setting an entity coating device according to the corresponding numerical value of the to-be-adjusted parameter in the second coating device simulation model, and finally improving the film thickness consistency of coating of the coating device.

The present invention relates to the field of die-casting optimization technology, and discloses a die-casting process parameter optimization method and system based on digital twin. The method includes: arranging sensors to collect die-casting equipment operation parameters and die-casting part quality data in real time to form multi-source die-casting production data. According to the multi-source die-casting production data, establish a multi-physics field simulation model and construct a digital twin model. Compare the virtual prediction results with the measured quality data, and construct a virtual-real difference compensation network to correct the parameters of the digital twin model. Based on the compensated digital twin model, perform a multi-objective reinforcement learning method to generate the optimal die-casting process parameters. Apply the optimal die-casting process parameters to the die-casting equipment for verification, and update the virtual-real difference compensation network according to the verification results. This application realizes the intelligent optimization and continuous self-evolution of die-casting process parameters, and improves the casting forming accuracy, energy efficiency utilization rate and production stability.

The invention discloses a COMSOL physical model parameter optimization method based on a hybrid intelligent algorithm, and the method comprises the steps: firstly configuring a file definition optimization problem, employing fusion chaotic mapping to initialize a population, and carrying out the initial fitness evaluation; then, entering an iterative loop, and alternately executing a weighted chimpanzee optimization algorithm and a self-adaptive differential evolution algorithm; the chimpanzee optimization algorithm simulates chimpanzee social hunting behaviors to perform global exploration and preliminary development, and the adaptive differential evolution algorithm performs local fine search and diversity maintenance through adaptive differential variation; performing performance evaluation in each iteration process; and finally, adaptively adjusting algorithm parameters and strategy probability according to an evaluation result. And finally outputting a global optimal parameter combination and optimization process data. The improved weighted chimpanzee optimization algorithm is combined with the adaptive differential evolution algorithm, and is deeply integrated with the multi-physics field simulation engine, so that the full-automatic parameter optimization process is realized, and the optimization efficiency and the result quality are remarkably improved.

This invention discloses a method, device, and medium for simulating biomagnetic field measurement results. The method includes: determining a corresponding theoretical model based on the properties of the biomagnetic field to be simulated; simulating the biomagnetic field using the theoretical model to obtain a simulated biomagnetic field; acquiring the index parameters of a measuring instrument; and simulating the biomagnetic field based on the index parameters of the measuring instrument to obtain simulated measurement results. This invention solves the problem that traditional biomagnetic field simulations do not consider the influence of the performance and technical specifications of the measuring instrument itself on the biomagnetic field measurement results. It can more realistically and directly simulate the results of measuring biomagnetic fields using different measuring instruments, considering the influence of the technical specifications of the measuring instrument on the biomagnetic field measurement results from multiple dimensions.

The invention discloses a temperature control method and device for laser cladding, electronic equipment and a storage medium. The temperature control method comprises the steps that laser parameters of laser heating conducted by laser equipment on a laser cladding area on a machined part are obtained; the laser parameters are input into a preset temperature field simulation model to conduct temperature field simulation on the laser cladding area, and temperature field data in the laser cladding area are obtained; based on the temperature field data, cladding state parameters in the laser cladding area are determined, and the cladding state parameters comprise at least one of the cladding temperature and cladding state characteristics; and target laser parameters are determined based on the cladding state parameters, so that laser equipment conducts laser heating in the laser cladding area according to the target laser parameters. According to the method, the temperature control accuracy of laser cladding can be improved.

This invention belongs to the field of fracture characterization and reservoir hydraulic fracturing simulation technology. It discloses a method and related equipment for characterizing natural fractures and simulating reservoir damage evolution using a phase-field model. By distinguishing primary and secondary natural fractures based on a discrete fracture network and constructing a model, it achieves accurate characterization of the different sizes and spatial heterogeneity of primary / secondary natural fractures in the model. Natural fractures are characterized as mechanically weak surfaces with differentiated parameters. Hydraulic fractures can capture and interact with natural fractures. Combining a phase-field damage model and a rock mechanics constitutive model, it can accurately simulate key behaviors such as activation and deflection during natural fracture propagation without pre-setting fracture paths, avoiding numerical instability and low computational efficiency. Through dynamic coupling analysis of the entire fluid-solid-damage process, it takes into account the influence of multiple factors such as geostress and fluid pressure, improving the accuracy of phase-field simulation, reducing simulation distortion, providing reliable support for fracturing design optimization, helping to improve reservoir stimulation effects and production benefits, and ensuring the smooth implementation of fracturing processes.

The invention belongs to the field of hydroelectric generation control engineering and fluid mechanical dynamics, and particularly discloses a starting-up optimization control method of a large hydroelectric generating set based on full-view simulation and dynamic verification. Comprising the steps of multi-dimensional real machine test database construction and benchmark evaluation, one-dimensional system simulation and macroscopic boundary definition, three-dimensional high-fidelity transient flow field simulation and microscopic mechanism insight, startup law dynamic optimization based on simulation insight and'simulation-test 'technology closed loop and iterative refining. Compared with the prior art, one-dimensional system simulation and three-dimensional high-fidelity flow field simulation are organically combined for the first time, the problem of comprehensive analysis from the macroscopic hydraulic transition process to the microcosmic complex flow mechanism is solved, the'full-transparency 'insight of the starting process is achieved, multiple performance indexes such as vibration, throw, stress and temperature can be considered at the same time, and the method is suitable for large-scale popularization and application. And the overall stability of the unit is synergistically improved.

This invention belongs to the field of petroleum exploration and discloses a quantitative characterization method for structural fracture parameters based on the coupling of the minimum energy consumption and minimum action principle. To overcome the shortcomings of existing technologies in achieving quantitative prediction of structural fractures from qualitative description, this invention first calculates the energy consumption of fracture rupture through rock mechanics experiments; then, it couples the minimum energy consumption principle and the minimum action principle to establish a rock fracture criterion; based on this, it derives and establishes quantitative characterization models for fracture aperture, volumetric density, and linear density; subsequently, it constructs a heterogeneous mechanical parameter volumetric model and performs elastoplastic geostress field simulation; finally, it achieves batch prediction of structural fracture parameters through programming, and verifies the reliability of the prediction results using core, imaging logging, and production dynamic data. This invention, starting from the physical essence of energy distribution and path selection, provides a unified theoretical framework for rock fracture and significantly improves the prediction accuracy of fracture "sweet spots."