1308 results about "Physical property" patented technology

The invention discloses an automatic control method and system for secondary granulation of a high-voltage zinc oxide resistor disc, relates to the technical field of intelligent manufacturing of power equipment, and solves the problems of out-of-control particle morphology caused by dynamic coupling parameter identification lag and control instability caused by multi-physical field parameter coupling in an existing method. According to the invention, a dynamic physical property parameter matrix is generated in real time based on multi-band dielectric relaxation spectrum analysis and terahertz wave tomography; predicting a fluidized phase change threshold value and an energy gathering area through multi-physics field coupling modeling; a time sequence attention deep reinforcement learning algorithm is adopted to generate a multi-field cooperative adjustment instruction; positioning a parameter conflict source and triggering decoupling compensation by combining a high-frequency vibration and acoustic emission combined monitoring module; performing closed-loop correction on the control network weight based on the laser spectrum data and a partial least squares regression model; the real-time performance of fluidization parameter identification, the stability of multi-field coupling control and the recovery efficiency of abnormal working conditions are remarkably improved, and meanwhile the batch consistency of the electrical performance of the resistor discs is guaranteed.

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 provides a tunnel disaster source multi-attribute joint inversion method and system based on physical property constraint, and relates to the technical field of tunnel engineering and joint inversion, and the method comprises the steps: constructing a tunnel face three-dimensional geologic model, applying controlled disturbance to surrounding rock physical property parameters, analyzing the change characteristics of earthquake and electromagnetic observation response, and obtaining a tunnel face three-dimensional geologic model; establishing a quantitative mapping relation between the surrounding rock physical property parameter disturbance quantity and the multi-field response signal variable quantity; constructing a multi-dimensional sensitivity evaluation index, and generating a joint sensitivity result; the surrounding rock units are identified and divided, differentiated partition rock physical relationship constraints are constructed, and a physical multi-attribute inversion target of joint inversion is determined based on the partition rock physical relationship constraints; and on the basis of a physical multi-attribute inversion target, a multi-source joint inversion target function is constructed in combination with the joint sensitivity result, joint solving and iterative updating are carried out, and a tunnel face advanced inversion result is output. According to the invention, calamity source fine identification and risk quantitative evaluation in front of the tunnel face during the tunnel construction period are realized.

The invention relates to a plastic part forming process parameter optimization regulation and control system, in particular to the field of plastic part forming, through the synergistic effect of multiple modules, the intelligent level and stability of a forming process are remarkably improved, and the system can quickly respond to the physical property change of a new material or a new batch; intelligently generating high-adaptability initial parameter suggestions based on historical data; by fusing physical simulation and real-time sensor data, dynamic behavior characteristics of a material are accurately captured, and an enhanced characteristic vector is constructed; on the premise of strictly following the thermodynamic safety boundary, the process parameter combination is efficiently optimized to meet the complex rheological constraint; and meanwhile, closed-loop precipitation and self-improvement of process knowledge are realized according to a continuous evolution anti-disturbance control strategy of production data, rapid and accurate regulation and control in a high-frequency switching scene are finally achieved, and the consistency of forming quality and production stability of plastic accessories are greatly improved.

The invention provides a rock mass high-temperature deformation simulation method and system based on deep learning near-field dynamics, and relates to the field of rock mass thermal-mechanical coupling analysis and research, and the method comprises the steps: obtaining the parameter information of a to-be-simulated target rock mass, including the geometric shape of the rock mass and the physical attribute of the rock mass; dispersing the target rock mass into a plurality of material points according to the parameter information, and constructing a thermal-mechanical coupling model of the target rock mass; based on the initialized thermal-mechanical coupling model, time step iterative simulation of a solid mechanical field is conducted, and finally the crack propagation process and temperature distribution of the target rock mass are obtained; according to the method, a solid field near-field dynamics theory based on strain energy density is introduced, a fluid field near-field dynamics equation is combined, temperature distribution in a rock medium is predicted through a physical information neural network, a deep learning near-field dynamics framework of rock mass high-temperature deformation damage is formed, and therefore rock mass high-temperature deformation is efficiently and accurately simulated.

The invention relates to the technical field of construction surrounding rock stability evaluation, discloses a tunnel surrounding rock stability evaluation method and system based on multi-physics field parameter inversion, and aims to solve the problems that an existing method is insufficient in data collaboration, high in parameter inversion multiplicity and poor in surrounding rock stability evaluation accuracy and timeliness. According to the scheme, the method mainly comprises the steps that an acousto-optic electromagnetic vibration drill multi-mode sensing array is arranged, and time-space synchronization is implemented; establishing a mutual interference entropy spectral density model to realize multi-physics field collaborative excitation and acquisition; a unified feature vector is obtained through data correction, feature extraction and weighted fusion; a joint inversion objective function embedded with rock physical constraints is constructed, a three-dimensional physical property parameter field is obtained through inversion, and a dynamic permeability field is calculated in combination with acoustic emission energy; and finally, dynamically updating the model by utilizing ensemble Kalman filtering, and obtaining a final risk probability based on updated parameters and seepage-uncertainty coupling correction. According to the method, the accuracy, the real-time performance and the reliability of the stability evaluation of the surrounding rock of the deep-buried tunnel are improved.

The invention discloses a deep resource fluidized mining disturbance effect evaluation model under a multi-field coupling effect, and the method specifically comprises the following steps: constructing a multi-field coupling parameter system: collecting geologic body basic parameters, covering rock mass mechanical parameters, thermal physical parameters, fluid parameters and chemical parameters in deep three-high, high ground stress, high ground temperature and high karst water pressure environments, and establishing a multi-field coupling parameter system; the method comprises the following steps: establishing a dynamic parameter database, realizing real-time updating of parameters along with a mining process, establishing a heat-flow-force-chemical full-coupling mathematical model, introducing the influence of a rock plastic damage correction term quantification temperature on heat conduction efficiency, associating a dynamic mapping relation between mineral reaction and rock physical property parameters, and establishing a dynamic parameter database. Simplification errors of a traditional model on multi-field effects are thoroughly eliminated, chained interaction of temperature, fluid, stress and chemical processes in a deep three-high environment is accurately described, a model prediction result better fits an actual mining working condition, and prediction deviation is greatly reduced.

The invention discloses a deep learning and machine learning fused soil moisture inversion construction method, and relates to the technical field of measurement of physical properties of materials, and the method comprises the steps: capturing complementary information and spatial context of multi-source data through a multi-source heterogeneous data space-time adaptive fusion step by using a cross-modal attention mechanism and a graph neural network; through a deep learning and machine learning dual-path collaborative inversion step, advantage complementation is realized by combining data-driven nonlinear modeling and a physical constraint interpretable model; according to the method, the defects of single data source, insufficient model generalization ability and incomplete physical mechanism consideration in the prior art are overcome, the inversion precision is improved by 12%-18% under the complex earth surface condition, and the method has the advantages that the method is suitable for large-scale popularization and application. And a high-precision, strong-generalization and reliable technical means is provided for precise monitoring of soil moisture.

The invention belongs to the technical field of geometric pretreatment in computer aided engineering (CAE), and particularly relates to a dirty geometry restoration method for a complex three-dimensional geometric model, which comprises a dirty geometry detection and restoration module based on heuristic rules and geometric topology analysis. By means of a multi-model collaborative alignment and bonding mechanism, high-precision assembly between parts is achieved through geometric feature matching and adjacent domain self-adaptive adsorption; acquiring material attributes provided by the simulation platform, and performing accurate cutting and boundary reconstruction on an intersection domain based on an intersection domain intelligent segmentation algorithm of the material attributes to ensure correct mapping of boundary conditions of a physical field; a geometric Boolean processing engine iterative learning mechanism of a general merging algorithm is integrated, and a high-quality model for simulating a grid is generated through multi-round iterative optimization. According to the method, double challenges of internal dirty geometry of a single model and derivative dirty geometry of intersection / adjacent areas among multiple bodies are solved, and key physical attributes and topological continuity of electromagnetic signal links are ensured and are completely reserved during repair.

The invention relates to the technical field of multi-source data fusion, in particular to a multi-source geological data processing method and system of a three-dimensional geological model.The method comprises the following steps that mountain landform and river valley images are obtained, gray frequency characteristics are extracted, a frequency energy gradient layer is constructed, a frequency continuous response area is screened to generate a structure boundary set, and a structure boundary set is constructed; the method comprises the following steps of: extracting a boundary normal vector by utilizing principal component analysis, identifying boundary sections with consistent directions, estimating a physical property parameter gradient direction, judging an included angle screening blocking region, generating a space attribute limiting layer, carrying out space alignment analysis on an overlapping region vector included angle, updating a boundary label, and generating an available attribute path structure set in three-dimensional geological modeling through a Dijkstra algorithm. According to the method, a conduction model is constructed through frequency domain decomposition and logarithmic transformation enhanced recognition, frequency window analysis noise reduction, principal component extraction vector analysis direction and center difference estimation, dynamic matching is promoted through alignment, a Dijkstra algorithm optimizes a path, and the geological model bedding characterization and conduction simulation precision is improved through cooperation of a multi-dimensional technology.

The invention belongs to the technical field of tunnel engineering, and provides a multi-physics field real-time assimilation simulation and regulation method and system in a tunnel grouting process in order to solve the problem that real-time dynamic simulation and automatic regulation are lacked in existing tunnel construction, and the real-time assimilation simulation and regulation method and system in the tunnel grouting process are provided by utilizing ensemble Kalman filtering and combining real-time monitoring data in the tunnel grouting process. Dynamically correcting parameters of the multi-physical model; time correlation in the slurry condensation process is considered, a time-varying condensation model depicting physical property changes of slurry evolving along with time is integrated, the time-varying condensation model serves as an external function in the time step length to be embedded into the multi-physical field model in correction, and the slurry flowing state is adjusted in a self-adaptive mode through numerical simulation; and generating control parameters of tunnel grouting according to a dynamic simulation result, and realizing closed-loop regulation and control of tunnel grouting. Synchronous linkage of numerical simulation and on-site working conditions is realized.

The invention discloses an electronic device parasitic parameter network analysis method based on point cloud deep learning and a related device, and the method comprises the steps: obtaining physical characteristic data in a laser-induced quartz material process, and the physical characteristic data comprises laser wavelength, pulse width, photon energy and material characteristics; and inputting the physical characteristic data into the trained neural network model, and predicting the damage threshold of the laser-induced quartz material. According to the machine learning method fusing physical information, unification of data efficiency and physical consistency is achieved, prediction precision and model expandability are remarkably improved, and the method is used for accurately predicting the damage threshold value of the quartz material under the specific laser condition, so that the laser processing technology is optimized, and the processing precision and efficiency of the quartz material are improved.

The invention discloses a vacuum sealing leakage rate prediction method and device, equipment and a medium. The method comprises the following steps: constructing a three-dimensional microstructure model of a flange sealing surface according to a processing mode of the flange sealing surface; based on the three-dimensional microstructure model, establishing leakage micro-channels between the sealed contact interfaces in different contact states, analyzing channel characteristics, and determining flow characteristics of leakage media in the leakage micro-channels in different contact states; constructing a first leakage rate prediction model represented by the microscopic characteristic parameters according to the working environment parameters and the physical attributes and flow characteristics of the leakage medium; and constructing a mapping relation between the macroscopic design parameters and the microscopic characteristic parameters through characteristic multi-scale coupling, and substituting the mapping relation into the first leakage rate prediction model to obtain a second leakage rate prediction model driven by the macroscopic design parameters so as to predict the vacuum sealing leakage rate. The method has the advantages of high precision, strong adaptability and good engineering practicability.

The invention relates to the field of digital core modeling, in particular to a stomatal basalt three-dimensional digital core reconstruction method, which comprises the following steps: extracting target characteristic parameters from CT (Computed Tomography) scanning gray volume data of a stomatal basalt sample, the target characteristic parameters comprising porosity, cluster number, cluster size statistics, spatial uniformity index and simplified compactness; generating an initial three-dimensional digital core model according to the target characteristic parameters; carrying out iterative optimization on the initial three-dimensional digital core model by utilizing a self-adaptive Markov chain-Monte Carlo algorithm so as to enable cluster features of the optimized three-dimensional digital core model to approach target feature parameters; and performing curvature smoothing post-processing on the optimized three-dimensional digital core model to obtain the pore basalt three-dimensional digital core model. The model not only is highly matched with real pore basalt in the aspect of macroscopic statistical characteristics, but also shows natural and smooth curved surface characteristics in the aspect of microscopic pore boundary morphology, and provides a reliable digital basis for subsequent rock physical property analysis.

The invention discloses a valve processing and manufacturing method based on digital twinning, which comprises the following steps: S1, constructing a valve digital twinning model, creating a valve geometric model by using three-dimensional modeling software, and endowing the valve geometric model with physical attributes and material characteristics through finite element analysis software, carrying out design optimization through fluid mechanics simulation and stress analysis; s2, establishing a processing technology digital twin model, performing digital modeling on the device, integrating processing technology parameters, and simulating a material processing process; s3, the machining process is monitored in real time, multiple types of sensors are deployed on machining equipment, and operation data of the machining equipment are collected in real time; s4, dynamic simulation and comparative analysis are conducted, specifically, the digital twin model dynamically simulates the actual machining process according to real-time collected data, and a simulation result and design requirements are compared and analyzed; and S5, feedback control optimization: when the processing deviation exceeds a preset threshold value, automatically generating a process parameter adjustment scheme and feeding back the process parameter adjustment scheme to a processing equipment control system.

The invention relates to the field of dirt removal, and discloses a method and system for evaluating the dirt removal effect of a mold cleaning agent, and the method comprises the steps: obtaining the three-dimensional shape data and characteristic spectrum data of an uncleaned mold, and constructing a dirt distribution model to obtain the dirt type and position distribution; according to the initial dirt classification result, chemical composition and physical characteristics of dirt are judged, and cleaning parameters are obtained; based on the three-dimensional shape data, geometrical characteristics of the special-shaped structure area are extracted, a flow track of the cleaning agent in the special-shaped structure area is analyzed, and action range distribution of the cleaning agent is obtained; optimizing the cleaning parameters based on the action range distribution of the cleaning agent to obtain optimized cleaning parameters; and the optimized cleaning parameters are executed to clean the mold. The method has the advantages that directional cleaning and effect evaluation are achieved, and the cleaning efficiency and quality are improved.

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

The invention discloses a skarn type deposit three-dimensional metallogenic prediction method, system and equipment and a medium, and relates to the technical field of mineral exploration. The method comprises the following steps: collecting and sorting geological information of a to-be-studied area and a surrounding area; according to the collected information, performing gravity-magnetic three-dimensional physical property inversion and lithology mapping; carrying out gravity-magnetic three-dimensional comprehensive geological modeling by adopting a discrete body inversion method; on the basis of the constructed model, performing three-dimensional metallogenic favorable contrast prediction; constructing a three-dimensional mineralization comprehensive prediction model based on the mineralization favorable degree value; and carrying out target region delineation and verification by using the three-dimensional metallogenic comprehensive prediction model to complete three-dimensional metallogenic prediction under the support of regional gravity and magnetic data. The method has the advantages of wider prediction range, high prediction reliability and the like.

The invention discloses a tunnel dew formation and icing rapid monitoring method and system based on a space-time phase change cooperation mechanism, and relates to the technical field of tunnel engineering safety monitoring and freeze injury prevention and control. Establishing a tunnel geometric model and a heat-humidity-turbulence multi-field coupling physical model; synchronously acquiring heat and humidity physical property parameters and outdoor hourly meteorological parameters; taking the outdoor hourly meteorological parameters as Dirichlet boundary conditions and initial conditions of a heat-humidity-turbulence multi-field coupling physical model; determining a heat and humidity exchange coupling process of the tunnel wall surface and the internal environment, and defining heat and humidity transfer parameters under an unsteady state boundary; performing discretization processing on the tunnel geometric model by adopting a grid division strategy; by setting a dew point temperature threshold value and an icing temperature threshold value, a condensation risk area is judged, dynamic changes of the thickness of an ice layer are quantified, and monitoring of tunnel condensation and icing is achieved. The method can effectively reflect the distribution rule of multiple physical fields on the surface and in the tunnel in any time, accurately judge the risk area and quantify the thickness of the ice layer.

The invention belongs to the technical field of mechanical property testing, and particularly discloses and provides a coal rock sample mechanical property intelligent testing system and method.The coal rock sample mechanical property intelligent testing system comprises a consistency verification module, a test piece dividing module, a density testing module, a triaxial testing module and a report generating module; standardized screening is carried out on the size, morphology and structural integrity of the test piece, physical characteristics are ensured to be unified, individual difference interference is avoided, then density and triaxial testing are integrated, density, triaxial compressive strength and shear strength parameters are synchronously obtained, a multi-dimensional data system is constructed, the problem that in the prior art, parameters are single is solved, and the test efficiency is improved. The method comprehensively supports comprehensive evaluation of coal rock mechanical properties, and meanwhile, by outputting a structured report containing a measured value, an adaptive threshold value, a judgment result and an unqualified item and clearly marking the unqualified item, the limitation that manual secondary processing is needed in the prior art is solved, seamless connection of testing, evaluation and engineering application is achieved, and the engineering application value is improved.

The invention relates to the technical field of electronic component testing for investigating or analyzing internal microstructures and physical properties of materials by utilizing an electrical means, and discloses an online testing and analyzing method for physical properties of electronic component materials, which comprises the following steps of: constructing a composite excitation signal formed by linearly superposing a main carrier voltage and a perturbation wave voltage; applying the signal to a to-be-tested electronic component and acquiring response current; and extracting an intermodulation current amplitude at an intermodulation frequency point in the frequency spectrum of which the linear response interval is excluded, calculating a nonlinear response coefficient of the material in combination with the excitation amplitude, and comparing the nonlinear response coefficient with a preset degradation threshold so as to judge whether the nonlinear response coefficient is qualified or not. By extracting intermodulation components which cannot be generated by linear contact resistance, physical isolation of external contact noise in a frequency domain is realized, and the problem that contact resistance fluctuation and material intrinsic aging cannot be distinguished in a traditional linear impedance test is solved.

The invention provides a power equipment three-dimensional dynamic updating method and system for virtual reality training, and the method comprises the steps: collecting the working state data of power equipment in real time through a sensor; processing the working state data based on a preset function model, and calculating the physical state change of the power equipment; according to the physical state change, adjusting physical attributes of the three-dimensional model of the power equipment in real time so as to simulate physical effects of thermal expansion, stress concentration or structural deformation; loading the adjusted three-dimensional model into a virtual reality environment, and performing real-time display through a virtual reality rendering platform; and after the user executes the interactive operation through the virtual reality equipment, the working state of the power equipment is updated, and the influence of the operation on the three-dimensional model of the equipment is dynamically fed back, so that a virtual-real linkage closed-loop training process is formed. The virtual model can change in real time along with the collected data, and the technical verisimilitude and operability of virtual training are remarkably improved.

The invention discloses a physical attribute inversion and three-dimensional reconstruction method based on Gaussian splashing and micro-rendering, and belongs to the technical field of computer vision, and the method comprises the steps: generating a sparse point cloud based on a multi-view image to initialize a Gaussian ball; determining a Gaussian pivot point based on a Gaussian ball, constructing a self-adaptive tetrahedral mesh in combination with gradient optimization, extracting an explicit surface from the self-adaptive tetrahedral mesh, and sampling to obtain geometric information; predicting the physical attribute of each sampling point through an implicit texture network, and providing ambient light through an HDR ambient light map; geometric information, physical attributes and ambient light are used as input, a differentiable PBR renderer is adopted to generate a physical rendering image, multi-term loss function reverse optimization is constructed, and collaborative optimization and inversion of three-dimensional geometry and surface physical attributes are realized. According to the method, the problems of texture dislocation, thin-wall structure disappearance and high rendering calculation cost under dynamic topology are effectively solved, and a digital model with fine geometry and a realistic material can be efficiently recovered from a multi-view image.

The invention discloses an underground physical characteristic prediction method and system combining seismic waves and drilling data, and relates to the technical field of geophysical exploration, and the method comprises the steps: collecting original seismic records, carrying out the preprocessing, obtaining a three-dimensional seismic data body, carrying out the complex channel analysis of the three-dimensional seismic data body, extracting the instantaneous amplitude, instantaneous phase and instantaneous frequency attributes, and carrying out the calculation of the instantaneous amplitude, instantaneous phase and instantaneous frequency attributes. Fault features are identified through a coherent body algorithm, an earthquake feature matrix is obtained, depth alignment and correction are carried out on density logging, interval transit time and neutron porosity curves of drill holes, and a standardized drill hole data table is generated; and based on the seismic feature matrix and the standardized drilling data table. According to the method, deep complementation of the earthquake macroscopic information and the borehole local truth value is realized through the geometric perception multi-modal graph neural network and the dynamic gating fusion mechanism, the problems of insufficient cross-modal feature fusion and misalignment of physical rules in the prior art are solved, and the prediction precision and reliability under complex geological conditions are remarkably improved.

The invention relates to the technical field of intelligent control, in particular to a breeding feed mixing control method and mixing equipment, and solves the technical problem of poor mixing quality caused by physical property difference of raw materials in the prior art. The method comprises the following steps: monitoring component composition and particle physical form of a mixed material in a mixing process and stirring parameters of mixing equipment; the mixing process comprises the following steps: stirring the dry materials in the mixing equipment, and adding liquid by spraying; the components are obtained through near infrared spectroscopic analysis; the physical form of the particulate matter is obtained through image analysis; analyzing the influence of the stirring parameters on the mixing quality based on the component composition, and determining a correction coefficient of the operation parameters of the mixing equipment in combination with the physical form of the particles; and regulating and controlling the current operation parameter of the mixing equipment according to the correction coefficient, so that the mixing equipment operates according to the regulated and controlled target operation parameter.

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

The invention discloses a gravity-magnetoelectricity three-dimensional joint inversion method based on reweighting, and belongs to the technical field of geophysics. According to the method, the resolution and physical property difference characteristics of data of geophysical gravity, a magnetic method and an electromagnetic method are fully utilized, and a more reliable underground structure model is obtained in a joint inversion mode; according to the method, gravity, magnetic and electric multi-field data are processed at the same time, and the method is suitable for mineral resource exploration, oil and gas reservoir exploration, deep structure research and other scenes under complex geological conditions, and especially has remarkable advantages in hidden ore body boundary recognition, lithologic contact zone positioning and the like; by integrating reweighting, cross gradient and efficient iteration technologies, the manual intervention and parameter debugging cost is greatly reduced, the automatic inversion process from data input to model output is realized, and the engineering application efficiency of geophysical exploration is improved.

Provided are computer-implemented methods and quantum computing systems for preparing computational states representing quantum states of a physical system, including performing a computational evolution of the state and then determining physical properties of the system using the time-evolved computational state. Hamiltonian dynamics of observables are computed on a quantum computer to provide information about the physical system represented by the Hamiltonian. Low energy electronic structure states of a physical system are prepared using adiabatic evolution. The energy of an equilibrium quantum state of a physical system is determined using a time-evolution operator. The energy of an eigenstate of a physical system is indirectly determined by evaluating expectation values of a time-evolution operator averaged across multiple shots for randomly-generated quantum circuits. Example methods enable calculation of the energy of an evolved computational state with chemical accuracy, due to avoiding discretization errors, with a smaller circuit depth than known alternatives.

The invention relates to a method and system for determining the water content of a safe shutdown boundary of a submarine mixed transportation pipeline, and the method comprises the steps: carrying out a physical property parameter test, and taking the physical property parameter as a multiphase flow simulation input parameter; carrying out submarine pipeline shutdown simulation on the basis of the physical property parameter test data, and obtaining oil section temperatures and spatial distribution characteristics at different water depth positions in the pipeline; carrying out an oil-water layering characteristic experiment under a temperature control condition to obtain an oil-water emulsion layering characteristic; sampling oil sections with different layer heights in the oil-water layering characteristic experiment, and testing the water content and simulating the yield / slip characteristic at the oil section temperature based on the temperature distribution of the oil sections; according to the yield / slip stress of the oil sections with different layer heights, carrying out segmented calculation and weighted accumulation to obtain an overall starting stress; on the basis of the overall starting stress, the safe shutdown boundary moisture content is determined in combination with pressure boundary conditions. The method can effectively guide the safe transportation stopping and restarting of the submarine pipeline, optimizes the replacement operation after the transportation stopping of the submarine pipeline, and improves the operation safety and economy.

The invention discloses a method for characterizing physical properties of a single-layer graphene / semiconductor heterojunction. The method comprises the following steps: providing a physical property model about a single-layer graphene-semiconductor heterojunction, wherein influence factors comprise the change of Fermi level of single-layer graphene after the heterojunction is formed and the influence of an interface state on a formation position of a contact potential difference; extracting heterojunction electrical characteristics by using a Kelvin probe force microscope; the interface layer spacing is obtained; and importing the heterojunction electrical characteristics and the interface interlayer spacing into a physical characteristic model, and analyzing to obtain physical characteristics. According to the new theoretical model and the method for realizing the nondestructive characterization of the physical characteristics of the heterojunction by using the Kelvin probe microscope based on the theoretical model, the influence of the change of the Fermi level of the single-layer graphene and the interface state on the formation position of the contact potential difference is fully considered; key interface physical properties, especially built-in potential and depletion region characteristics which are crucial to device performance, can be accurately analyzed.