301 results about "Field analysis" patented technology

The invention discloses a power distribution equipment on-line monitoring system based on multi-modal data fusion, and relates to the field of power distribution equipment management, and the system comprises a sensing module which is used for collecting an electrical signal, a thermal infrared signal, a mechanical vibration signal and an acoustic signal generated in the operation process of power distribution equipment through a multi-type sensing channel, converting the collected various signals into processable equipment state original data to form an equipment operation state original data set; according to the invention, through accurate acquisition of multi-dimensional signals, combination of space mapping and time delay compensation, data quality is optimized, the reliability of original information is ensured, key features are extracted according to working conditions, subtle state changes are captured by means of temperature field analysis and a variable-resolution spectrum technology, the comprehensiveness, accuracy and response timeliness of equipment operation monitoring are effectively improved, and the real-time performance of equipment operation monitoring is improved. Misjudgment and missed judgment are reduced, and fault risks are avoided in advance.

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.

A micron-sized speckle preparation method for quasi-in-situ OIM-DIC mesoscopic strain field analysis comprises the following steps: (1) polishing the surface of a sample to be detected to obtain a bright and scratch-free mirror surface; (2) preparing Si powder turbid liquid; (3) dipping speckles of a sample to be detected in the Si powder turbid liquid to obtain micron-sized speckles; and (4) observing and shooting speckle morphology, and if Si particles are uniformly distributed and dispersed, applying the Si particles to quasi-in-situ OIM-DIC mesoscopic strain field analysis. The method is simple, convenient and rapid, low in operation and construction cost, high in practicability, good in particle dispersity, high in precision, more suitable for calculation of a quasi-in-situ OIM-DIC mesoscopic strain field, controllable in preparation process, low in cost and free of damage to the surface of a sample, the definition and stability of speckle characteristics are remarkably improved, DIC mesoscopic micron-scale operation under a quasi-in-situ OIM mechanical test can be effectively achieved, and the method is suitable for large-scale industrial production. And the grain and mesoscopic strain field information is successfully coupled.

The invention provides an automatic equipment anomaly monitoring method and system based on image processing, and relates to the technical field of automatic equipment anomaly monitoring, and the method comprises the steps: converting an equipment operation video into a multi-dimensional physical field feature: in a motion field dimension, based on optical flow field analysis, extracting a full-period displacement statistical histogram and a space thermodynamic diagram, the motion instability characteristic of the mechanical transmission system is accurately quantified; in a vibration field dimension, an energy spectrum and a vibration thermodynamic diagram are generated innovatively through time-frequency transformation of a displacement signal of a frequency spectrum monitoring point, and frequency domain feature visualization of a hidden vibration fault is achieved; in the dimension of a structure field, edge gradient analysis and texture feature extraction technologies are fused, a time sequence structure thermodynamic diagram sequence is constructed to capture a progressive damage evolution rule, a three-field abnormal index dynamic weighting fusion mechanism overcomes the limitation of traditional single-point monitoring, connected domain analysis of a fused thermodynamic diagram is combined with an LBP texture and morphological feature decision tree, and the defect of the prior art is overcome. Automatic equipment abnormity monitoring based on image processing is realized.

The invention relates to the technical field of highway engineering safety monitoring, in particular to a highway subgrade three-dimensional deformation monitoring system based on unmanned aerial vehicle oblique photography, and the system comprises an unmanned aerial vehicle oblique photography module which adopts a five-lens synchronous shooting strategy to realize the omni-directional coverage of a subgrade; the three-dimensional point cloud generation engine generates a high-precision three-dimensional point cloud model through feature extraction, registration and triangulation strategies; the deformation field analysis platform models a roadbed surface into a parameterized Riemannian manifold based on a differential geometry theory, captures deformation dynamic characteristics through multi-scale curvature flow analysis, and identifies potential risks by using topological evolution characteristics of deformation singular points; and the risk evaluator evaluates the risk level based on the singular point density, the change rate and the topological stability and generates early warning information. According to the invention, millimeter-level accurate monitoring of roadbed deformation is realized, various deformation modes from micro-cracks to large-scale settlement can be captured, the potential landslide risk is early warned 30-45 days in advance, and the false alarm rate is significantly reduced.

The invention relates to an active optimization design method of an axial flow fan blade, which comprises the following steps of: defining a blade profile construction line by adopting seven parameters such as a leading edge radius, and parameterizing and representing two-dimensional blade profile geometric characteristics based on NURBS curve control points; a two-dimensional blade profile and three-dimensional fan coordinate system is constructed, and control point coordinate mapping is achieved through matrix transformation; the method comprises the following steps: acquiring an initial sample based on Latin hypercube sampling, and establishing a Gaussian process proxy model by combining two-dimensional CFD calculation data; a K-RVEA algorithm is applied, maximization of a worst attack angle lift-drag ratio and minimization of a resistance coefficient are taken as double targets, Pareto optimization is carried out in combination with geometry and performance constraints, and iteration is terminated through a hyper-volume convergence criterion; and the optimized two-dimensional blade profile parameters are converted into NURBS description, and stacking is carried out in the spanwise direction to generate a three-dimensional blade entity. The grid sensitive effect in three-dimensional optimization is overcome, the flow field analysis precision is improved, invalid calculation is reduced, the blade profile curvature continuity and the process feasibility are guaranteed, and the design period of the axial flow fan is shortened.

The invention discloses a deep sea ultra-shallow gas layer drilling shaft multiphase flow obstacle risk prediction method, and relates to the technical field of petroleum and natural gas engineering, and the method comprises the following steps: building a shaft-sedimentary layer heat-force-solid-chemical multi-physics field coupling model and a 3D model, setting initial boundary conditions, and dividing grids; model parameters are input, a finite element method is used for solving a multi-physics field coupling numerical value, and the gas invasion amount and the hydrate blocking rate are calculated; analyzing a gas invasion-migration-pressure evolution mode; researching the secondary generation and deposition characteristics of the hydrate; establishing a risk assessment system based on the parameters to divide risk levels; a historical data verification model is selected, and when the deviation rate exceeds 15%, parameters are optimized and solution is carried out again. According to the method, the defects of traditional single-field analysis are overcome, the multi-phase flow obstacle risk prediction accuracy is improved, intervention guidance is provided, model verification guarantees stability, safe and efficient mining of the deep sea ultra-shallow gas layer is assisted, and related development technology progress is promoted.

The invention relates to the field of aero-engine core engine performance monitoring and flow field analysis, and discloses a core engine compression turbine component inlet and outlet flow field reconstruction method based on a fusion neural network, and the method comprises the following steps: S1, obtaining a sparse measurement value, carrying out the interpolation based on the sparse measurement value, and generating an initial interpolation field; s2, generating a first feature vector, an attention weight map and a spatial feature map; s3, weighting to obtain a spatial feature map, and fusing the spatial feature map with the first feature vector to obtain a fused feature vector; and S4, training the full connection branch and the convolution branch through a mixed loss function containing a data fidelity loss item and a physical constraint loss item. A physical constraint loss item is introduced into model training and is combined with a data fidelity loss item, so that a reconstructed flow field is ensured to follow a fluid continuity equation on the basis of conforming to measurement data, and the global physical consistency of a reconstruction result is improved.

The invention belongs to the technical field of computational fluid mechanics and artificial intelligence crossing, and discloses an anisotropic turbulence modeling method and system based on scale adaptive physical convolution. Comprising a physical anchor point expansion layer used for improving a physical constraint coverage range, a physical information neural network basic full-connection layer, a convolution layer comprising a feature scale convolution kernel generation mechanism and a loss calculation process. According to the method, a physical anchor point expansion layer is introduced, additional physical calculation points are generated by setting a physical point expansion coefficient on the basis of training data points of a traditional physical information neural network, and the additional physical calculation points are combined with an original data point set to form a physical constraint calculation point set which is wider in coverage range and more reasonable in distribution; a convolution kernel size self-adaptive generation mechanism based on a turbulence characteristic scale is utilized, the turbulence characteristic scale is obtained through vorticity field analysis and energy spectrum calculation, the size of a convolution kernel is determined according to the turbulence characteristic scale, convolution operation can be matched with multi-scale physical characteristics of turbulence in a self-adaptive mode, and pertinence is higher.

The invention discloses a traffic safety risk early warning method and system based on intersection traffic flow information, and relates to the technical field of traffic safety monitoring, and the method comprises the steps: dividing an intersection region into space-time grids, generating a pixel-level optical flow field through a minimization energy function, converting the pixel-level optical flow field into a physical optical flow field, and carrying out the early warning of the traffic safety risk based on the physical optical flow field. Mapping the physical optical flow field to a space-time grid, and fusing the average optical flow vector and the velocity vector through a least square method to generate a fused velocity vector; predicting the future trajectory of each vehicle based on a kinematic equation, generating a grid risk by integrating the traffic flow density, the normalized grid confusion degree and the optimized strategy probability vector, and calculating the overall risk of the intersection through weighted average; and carrying out risk early warning on the overall risk of the intersection. According to the method, optical flow field analysis is combined with velocity vector fusion, the representation precision of the motion state of the vehicle is improved, kinematics prediction is combined with trajectory intersection analysis, and the capability of finding potential collision risks in advance is improved.

The invention relates to the technical field of a multi-field coupling simulation shield pump pressure-bearing component service life prediction method, particularly discloses a multi-field coupling simulation shield pump pressure-bearing component service life prediction method, and aims to solve the problem of service life prediction distortion caused by difficult accurate modeling of a nonlinear coupling effect in traditional single field domain analysis. The method comprises the following steps: constructing a three-dimensional self-adaptive grid model covering a pressure-bearing shell, a flange and a bearing seat; defining multi-physical field boundary conditions containing temperature gradient, pressure pulsation, electromagnetic excitation and time-varying creep parameters; and executing thermal electromagnetic full-coupling transient simulation to obtain a stress-strain evolution field. According to the method, through strong coupling modeling, time-varying constitutive embedding and data closed-loop correction, crack dynamic tracking and life rolling prediction under extreme working conditions are realized, and failure early warning perspectiveness and engineering decision reliability are remarkably improved.

The invention discloses a pollutant monitoring system and method guided by turbulence degree of a flow field of a clean room, and aims to solve the problem that the existing monitoring technology lacks self-adaption and active tracking capability. The invention provides an innovative solution aiming at the defects that a fixed point position sensor has a blind area and a robot cannot deal with the change of a dynamic flow field during fixed inspection. The system comprises a mobile robot and a set of calculation and control system with a hierarchical data processing architecture. The remote computer is responsible for complex flow field analysis and decision making, the local industrial personal computer processes original data and executes bottom layer control, the load of the robot is effectively reduced, and efficient, stable and intelligent data transmission is achieved. The core of the method is an intelligent collaborative algorithm guided by the turbulence degree of the flow field. When the system detects that the flow field is disordered, the robot can start headwind search for rapid positioning, then seamlessly switches to disorder degree gradient tracking for accurate tracking, and finally the pollution source is locked. According to the cooperative mechanism of rough positioning and accurate tracking, the hysteresis problem of a traditional method is effectively solved, monitoring is changed from a passive mode to an active mode, and the real-time performance and the accuracy of clean room pollutant monitoring are greatly improved.

The invention discloses a composite insulator large cluster parachute heating defect judgment interference suppression method. The system comprises an infrared image acquisition and preprocessing module, a composite insulator target detection and positioning module, a composite insulator temperature field analysis module, a large umbrella group reflection area identification module, a composite insulator central axis reconstruction module and a heating defect intelligent diagnosis and interference suppression module. Complex infrared image analysis is converted into refined analysis of a temperature field and geometric features, and meanwhile, a strategy of combining deep learning and morphology is introduced to improve the precision of target detection and segmentation and ensure the robustness of central axis reconstruction and interference suppression. The method has the beneficial effects that the false alarm rate can be obviously reduced, the detection accuracy of the real heating defect is improved, the result is highly consistent with the interpretation result of an artificial expert, the processing efficiency is high, and the method is suitable for a large-scale unmanned aerial vehicle inspection scene.

The invention discloses an underground water flow field simulation method, an underground water flow field simulation device, underground water flow field simulation equipment and a computer readable storage medium, and the method comprises the steps: carrying out the collection of multi-source geological data based on drilling basic information, a digital elevation model and a hydrogeological map, and obtaining the multi-source geological data; constructing a three-dimensional geological model based on the multi-source geological data to obtain a three-dimensional geological entity model; performing aquifer recognition based on the profile information of the three-dimensional geological entity model to obtain aquifer spatial distribution; performing groundwater flow field analysis based on the aquifer spatial distribution to obtain groundwater flow field data; and performing model construction based on the groundwater flow field data to obtain a groundwater flow field model. The integrated simulation method for fine description of stratums, automatic identification of aquifers, flow field feature analysis and comprehensive evaluation of thermal reservoirs is realized, so that the precision and efficiency of geothermal resource exploration evaluation are improved.

The invention discloses a signal integrity simulation analysis method for a digital radio frequency hybrid microsystem, and belongs to the field of advanced packaging of integrated circuits. According to the method, a complete analysis process accompanied with product research and development is established, systematic work of qualitative simulation evaluation, rule design and quantitative analysis verification is sequentially carried out in various stages of project approval demonstration, scheme design, design verification and the like of product design, and process conditions, material characteristics and rationality and feasibility of system layout are rapidly evaluated; qualitative support is provided for agile design of the scheme; designing rules and optimization ranges of structures such as a radio frequency link, a digital link and a coupling shield are formulated according to process and material rules, and accurate initial input is provided for comprehensive design of a product; according to the layout wiring form, digital, radio frequency and coupling areas are formed through division, time domain analysis, frequency domain analysis and near field analysis are carried out in a targeted mode, quantitative reference is provided for judging design reasonability, and an effective basis is provided for optimizing design content.

The invention relates to the technical field of zero-point positioning mother board pressure compensation, and discloses a pneumatic type zero-point positioning mother board pressure adaptive compensation system which performs multi-source fusion processing on initial pressure field data and covers a compensation sequence of static reference features, a feedback sequence of dynamic deformation features and a calibration sequence of axial offset features. And the pressure compensation module carries out dynamic fluctuation suppression on the real-time deformation data flow, realizes pressure field balance identification through a multi-field coupling layer and generates a compensation instruction. The pressure standardization module performs space grid division, anomaly filtering and data calibration, and a pressure field analysis layer, a zero point self-adaption layer and a compensation trigger layer of the field intensity reconstruction module sequentially complete feature fusion, dynamic correlation modeling and multi-dimensional field intensity fusion. According to the system, through algorithms such as deformation segmentation, virtual interpolation and dynamic clustering, the pressure field balancing capability and positioning precision of the mother board under complex working conditions are improved, and the system is suitable for high-precision positioning requirements in the field of industrial automation.

The invention discloses a parachute flight performance prediction method based on follow-up coupling flow field analysis, and the method is suitable for a parafoil and a traditional round parachute. Parachute flight flow field aerodynamic characteristics and flight dynamic characteristics are coupled by using a body-attached dynamic grid and a self-adaptive flow field boundary technology, real-time changes of a parachute streaming flow field along with body motion are accurately reflected, and the attitude, the speed and the flight trajectory of the parachute are automatically solved and obtained. According to the method, on one hand, real-time aerodynamic characteristics and motion characteristics of the parafoil are coupled, the coupling influence of flight attitude speed change on aerodynamic force and aerodynamic torque of the parafoil is reflected, and the calculation precision is guaranteed; and meanwhile, the change of the streaming flow field of the parachute system is decoupled into the change of the relative incoming flow and the change of the posture, so that the redundancy of flow field grids and the complex grid reconstruction are avoided, and the simulation calculation efficiency is improved.

The invention relates to the technical field of artificial intelligence, in particular to a non-deterministic boundary thermal convection flow field intelligent analysis method based on deep learning, which comprises the following steps: acquiring sparsely distributed training data in a thermal convection system, constructing a physical information neural network and designing a composite loss function comprising a prediction error, a physical constraint error and a boundary condition error; and dynamically adjusting a weight coefficient by using a quasi-Newton optimization algorithm to carry out network training, and finally realizing prediction of full-field physical quantity distribution and inversion of missing boundary conditions. According to the method, a fluid mechanics control equation is used as a physical constraint to be embedded into a deep learning framework, the dependence of an existing calculation method on accurate boundary conditions is overcome, and the problems of flow field analysis and parameter inversion caused by unknown boundary conditions or difficulty in direct measurement are effectively solved; the method has important application value in engineering scenes such as aero-engine thermal management.

The invention discloses a green building energy consumption adaptive regulation and control system based on dynamic environment parameters, and relates to the technical field of building energy consumption regulation and control, and the system comprises a multi-source environment sensing module which comprises a plurality of environment parameter collection devices which are arranged at different spatial positions of a building atrium area and are used for collecting various kinds of environment parameter information, generating a structured data packet; and the control analysis module is used for receiving the structured environment data packet, performing field analysis, generating a control intention set based on a preset atrium environment control rule, identifying an environment parameter conflict relationship caused by vertical spatial characteristics of the atrium, and outputting the control intention set with a conflict identifier. According to the invention, multi-point synchronous acquisition of parameters such as temperature, humidity, air quality and illumination intensity in a building atrium area is realized through environment parameter acquisition devices arranged at different spatial levels, and a comprehensive credibility weight is generated in combination with personnel quantity information to construct a structured data packet.

The invention discloses an asphalt paving construction control system and method based on temperature field analysis, and relates to the technical field of road engineering construction, and the system comprises a temperature field monitoring module which is used for obtaining the temperature information of different positions of an asphalt paving surface, and constructing a three-dimensional temperature field with absolute position information; the multi-source environment information acquisition module is used for acquiring current environment information; the temperature field processing and temperature drop prediction module is used for dividing the three-dimensional temperature field into a plurality of grid units, predicting the future temperature of each grid unit in combination with the current environment information, and predicting the residual effective rolling time required for reducing the temperature to the critical temperature; the segregation risk intelligent diagnosis module is used for carrying out risk judgment according to the gridded temperature field; and the rolling strategy dynamic decision module is used for calculating a rolling scheme for each grid according to the current temperature, the remaining effective rolling time and the risk judgment result of each grid. According to the invention, real-time quality diagnosis, prediction and closed-loop dynamic control of asphalt paving construction can be realized.

The invention discloses a shape memory alloy multi-physics field analysis method based on an expansion depth operator network, belongs to the technical field of material science and engineering calculation, solves the problem of phase field dynamics analysis of multi-physics field coupling under various initial conditions, and comprises the following steps: S1, constructing the expansion depth operator network, the expansion depth operator network comprises a branch network and a backbone network; and S2, determining the total error of the neural network according to the data information error and the physical information error, optimizing the parameters of the neural network by adopting an AdamW optimizer and a Minibatch technology, training the neural network, and completing the shape memory alloy multi-physical field analysis based on the extended depth operator network. According to the method, the expansion depth operator network is used for replacing a finite element method, the solving process of the multi-physical field phase field equation is accelerated, field quantity distribution continuous in time and space is obtained, the solving process is accelerated, and continuous field distribution is obtained.

The invention discloses an explosive shock wave intelligent mixed numerical simulation method, device and equipment, and relates to the field of numerical simulation, and the method comprises the steps: determining a computational domain range, grid node information and simulation termination time of an explosive shock wave simulation problem, and constructing a tetrahedral grid; initializing a physical flow field based on a computational domain range, and constructing a flow field analysis model based on the tetrahedral mesh; using a mean total variation bounded discontinuous detection method to identify a discontinuous region and a smooth region in a computational domain range; for the discontinuous region, reconstructing physical parameters in the flow field analytical model by adopting a non-structural multi-resolution weighted essential oscillation-free reconstruction method, and for the smooth region, reconstructing physical parameters in the flow field analytical model by adopting a linear windward reconstruction method; and performing spatial discretization on the physical flow field based on the flow field analysis model, then performing time discretization, and obtaining a numerical simulation result until the calculation time exceeds the simulation termination time. According to the invention, optimal balance of precision and efficiency is realized.

This invention relates to a method, device, electronic device, and computer storage medium for compensating for thermal errors in lead screws, belonging to the field of machine tool processing technology. The thermal error compensation method for lead screws is applicable to lead screw feed systems with fixed ends. It includes: acquiring real-time temperatures at key temperature points in the lead screw feed system and the positioning error at those real-time temperatures based on a preset experimental platform; constructing a three-dimensional model of the lead screw feed system based on the thermal deformation effects and complexity of each structure; performing transient temperature-structure coupled field analysis on the lead screw feed system based on the three-dimensional model to determine the correlation between the lead screw pre-tension and the thermal deformation under thermal steady-state conditions; constructing a quantitative mapping model between lead screw temperature and thermal deformation based on this correlation; and performing thermal error compensation on the lead screw based on the quantitative mapping model. This invention can accurately achieve thermal error compensation for lead screws.

The present application relates to the technical field of medical image processing, in particular to a pain assessment system for neonatal facial expression image analysis, comprising a data acquisition module, a facial expression manifold construction module, a curvature field analysis module, a spatiotemporal feature hierarchical analysis module and a pain assessment and alarm module, the facial expression manifold construction module maps discrete facial feature points to a Riemann manifold space to construct an individualized expression manifold model; the curvature field analysis module calculates a facial expression dynamic curvature field and extracts micro-motion curvature features; the spatiotemporal feature hierarchical analysis module performs multi-scale decomposition on the curvature features to identify pain-related micro-motion units; the pain assessment and alarm module calculates a pain score and performs early warning, the present application significantly improves micro-expression capture sensitivity, is robust to changes in shooting conditions, improves the ability to distinguish different types of pain, realizes objective quantitative assessment and multi-level early warning of the pain state of neonates, and provides reliable technical support for clinical pain management.

The invention discloses a field line analysis method for sensitive frequency points of an unmanned aerial vehicle. The method comprises the following steps: building an unmanned aerial vehicle full wave field-line-line joint simulation model comprising a field analysis model, a line analysis model and a line analysis model based on the unmanned aerial vehicle; simulation waveforms, frequency bands, cable coupling types and waveform detection points are set through simulation software, the unmanned aerial vehicle full wave field-line-circuit joint simulation model is simulated, and a simulation analysis result is obtained. The unmanned aerial vehicle full wave field-line-path joint simulation model is established according to an actual unmanned aerial vehicle structure, has the advantages of being wide in frequency band, accurate in position, large in number of analysis systems and the like, and has important significance in actual engineering application such as unmanned aerial vehicle high-power electromagnetic radiation protection.

The invention discloses a mine equipment intelligent monitoring method and device based on knowledge retrieval enhancement generation, and relates to the technical field of mine safety intellectualization, and the method comprises the steps: obtaining equipment real-time data through a mine equipment monitoring special intelligent agent communication protocol, and generating a standardized message based on an equipment type and a risk level; determining a collaborative target AI node type and a collaborative method by using a three-dimensional decision tree algorithm, and matching a cross-domain collaborative strategy according to the current AI node type, the equipment type and the risk level; an improved RendezvousHash algorithm is combined with a load balancing strategy, and an optimal target node is selected from AI nodes for equipment distribution; sending a collaborative analysis request to the selected AI node through an asynchronous calling mechanism, and receiving and integrating analysis results of the AI nodes in each field; and performing semantic fusion on multi-field analysis results based on a large language model to generate a comprehensive disposal scheme conforming to coal mine safety regulations. According to the invention, the scientificity and response efficiency of equipment exception handling are improved.

The phase structure evolution phase field analysis method in the annealing and crystallization process of the amorphous hafnium oxide-based ferroelectric film comprises the following steps: S1, setting a sequence parameter xi according to the evolution process from an amorphous phase to a crystal phase in the annealing process, and setting a sequence parameter eta according to the process of the crystal phase and the crystal phase; s2, a phase field theoretical model is established, the total free energy is the sum of the free energy of the sequence parameter xi and the free energy of the sequence parameter eta, and the free density in the free energy of the sequence parameter eta is obtained through coupling of the sequence parameter xi and the sequence parameter eta; s3, deducing a weak form of the control equation; and S4, compiling the weak form equation into COMSOL finite element software, solving and analyzing the phase structure in the annealing crystallization process of the thin film. According to the method, the sequence parameter xi representing the transformation process from the amorphous phase to the crystalline phase is introduced and coupled with the sequence parameter eta to construct a new free energy equation and a new control equation, the weak form of the control equation is deduced, and the phase structure and the evolution rule of the hafnium oxide-based ferroelectric film at different annealing moments can be dynamically reproduced.

This invention belongs to the field of oil and gas development and exploitation engineering technology, specifically relating to a method for determining the initiation zone and sequence of fractures during multi-layer fracturing and filling operations in loose sandstone reservoirs. Based on the basic physical properties and pumping parameters of each sub-layer, this invention establishes the time-varying process of fluid absorption and wellbore pressure at each sub-layer during multi-layer fracturing and filling operations, enabling rapid identification of sub-layers that have initiated fractures and those that have not. Furthermore, based on the fractured sub-layers, this invention iteratively corrects the fluid absorption capacity of each sub-layer and calculates the changes in fluid pressure at the wellbore of the un-fractured sub-layers, thus determining the sub-layers that will subsequently initiate fractures at each stage. This provides the order and timing of fracture initiation for construction design and on-site analysis, offering a basis for construction design and field analysis.

The invention discloses an analytic wake flow model parameter increment correction method based on working condition scene driving, and mainly relates to the field of wind power plant wake flow engineering modeling. Comprising the following steps: S1, establishing a wind power plant whole wake flow model; the method specifically comprises the steps that modeling of a whole-field analysis wake flow model of the wind power plant is achieved through a single-machine wake flow model, a yaw wake flow model and a wake flow superposition model in sequence; s2, generating a wind power plant working condition scene; s3, on-line acquisition and processing of SCADA data are carried out; and S4, adaptively correcting parameters of the analysis wake flow model. The method has the advantages that adaptive correction of the analysis wake flow model in different working condition scenes can be achieved, the depiction deviation of the model on the wake flow diffusion characteristic and the wind speed loss rule in different operation scenes is effectively reduced, the analysis wake flow model can reflect complex and changeable actual working conditions more accurately, and the prediction precision is remarkably improved.

The application discloses a kind of deep melting interlayer development area rigid pile composite foundation structure design method, it is related to rigid pile composite foundation field, including the following steps: step one, in the existing rigid pile bearing capacity calculation process, front-end increase subgrade-ground temperature field analysis;Step two, increase groundwater analysis;Step three, determine the compression modulus of the soil layer of seasonal freeze-thaw layer, (water-rich) melting interlayer, permafrost layer, bearing capacity characteristic value, check the single pile bearing capacity characteristic value of different positions in the cross section of roadbed using different pile length, pile diameter, pile body stiffness material;Step four, carry out zoned unequal design, adjust pile length, pile diameter, pile body stiffness, so that the range of all pile single pile bearing capacity characteristic values in cross section is lower than design allowable value.The application effectively optimizes pile foundation design, reduces material waste, reduces engineering cost, while ensuring the safety and stability of structure.