26 results about "Microscopic scale" patented technology

The invention relates to the field of atmospheric pollution diffusion simulation, and particularly discloses a multi-scale coupled atmospheric pollution diffusion simulation system, which comprises a data source module used for collecting and integrating various data sources including meteorological data, topographic data, pollution source data and atmospheric pollutant concentration data, and providing basic information for simulation; the multi-scale modeling module further comprises a micro-scale model for simulating a detailed diffusion process of pollutants in a local area by calculating a fluid dynamics equation based on a fluid dynamics principle; by integrating various data sources such as meteorological data, topographic data, pollution source data and atmospheric pollutant concentration data, the system can provide more comprehensive and accurate basic information, so that the simulation precision is improved; the combination of microscopic, mesoscopic and macroscopic scale models can respectively capture pollutant diffusion characteristics under different scales, so that the simulation result is more detailed and real.

The invention discloses an abrasive water jet rock breaking simulation method based on a DEM-CFD coupling method. Establishing an EBPM bonded rock mass discrete element model through a discrete element DEM, and calibrating mesoscopic parameters through a virtual mechanical test; simulating a water-abrasive two-phase flow through fluid dynamics CFD, and adopting a Gidaspow drag force model; the DEM-CFD bidirectional interface realizes real-time coupling; carrying out post-treatment to extract an erosion morphology and a crack network; the method can effectively simulate the rock mass fracture process and the large deformation behavior in the water jet rock breaking process and reveal rock mass damage evolution from the microscopic scale, and can be widely applied to research of water jet assisted rock breaking in the fields of civil engineering, mining, petroleum energy, marine resources and the like.

A method of imaging vascular activity at microscopic scale in at least one region of a network of blood vessels of a human or animal organ, the method comprising: (a) emitting a series of consecutive incident ultrasound waves in the at least one region by an ultrasound transducer array extending in at least one direction, the incident ultrasonic waves are propagated in the direction perpendicular to the transducer array; (b) acquiring a set of raw data from the backscattered ultrasound by the transducer array; (c) generating a series of continuous ultrasound images according to the original data; (d) detecting at least one isolated ultrasound contrast agent in the ultrasound image; (e) locating the position of the at least one isolated ultrasound contrast agent at a precision lower than the wavelength of the wave; (f) generating an at least two-dimensional backscatter amplitude image by assigning, to each pixel, a value representative of the measured backscatter amplitude of the at least one isolated ultrasound contrast agent detected in that pixel.

The present disclosure proposes a method and apparatus for imaging at a microscopic scale a region of an organ of a human or animal, allowing the use of a 2D subsampled ultrasound probe while providing 3D ULM images with high resolution usually obtained only with a full 2D array matrix, by sorting the detected microbubbles and keeping only the microbubbles corresponding to the spots belonging to the main lobe of the Point Spread Function (PSF) of the microbubble and removing the phantom microbubbles corresponding to the spots belonging to the side lobes. It is also possible to provide a 3D non-invasive imaging of the microvascular flow of the region of an organ, such as a brain in-vivo, with high resolution and high sensitivity.

To provide a material that can reliably provide highly accurate and precise features on a microscopic scale. [Solution] A method for densifying an expanded polyethylene (ePE) substrate, the method comprising the steps of: providing an ePE substrate having a first density and a first size; selectively densifying a portion of the ePE substrate to form a densified portion of the ePE substrate, wherein the densified portion of the ePE substrate has a second density greater than the first density, and the densified portion of the ePE is a densified pattern; and shrinking the ePE substrate to a second size, thereby reducing the densified pattern to a fine densified pattern, wherein the second size is smaller than the first size, and the fine densified pattern is smaller than the densified pattern.

The invention discloses a carbonate rock cross-scale mechanical property characterization method. The carbonate rock cross-scale mechanical property characterization method comprises the following steps: S1, basic physical property characterization; s2, processing a carbonate rock micromechanics experiment sample; s3, scanning electron microscope observation and microcosmic mineral identification; s4, correcting the area function of the needle tip of the pressing needle; s5, testing the micromechanical property of the carbonate rock mineral; s6, carrying out data arrangement on the micro-mechanical properties and the composition proportion; and S7, constructing a mechanical upscaling model and calculating macromechanical properties. According to the method, main mineral types in carbonate rocks are identified by utilizing a scanning electron microscope and energy spectrum analysis on a microscopic scale, and then the mechanical properties of different minerals are quantitatively represented by utilizing quasi-static nanoindentations. On the basis, mineral composition proportion information and porosity data are synthesized, an upscaling model of the mechanical property is constructed, and cross-scale prediction and evaluation of the macroscopic mechanical property of the carbonate rock are achieved.

The invention provides a multi-scale residual feedback seismic inversion method and device for CO2 storage layer identification and electronic equipment. The method comprises the following steps of: decomposing original seismic data and logging data into three levels of data volumes of a macroscale, a mesoscale and a microscale respectively by utilizing wavelet transform; on the macroscopic scale, utilizing the post-stack seismic data to invert the stratum velocity and the tectonic framework; on the mesoscale, the reservoir porosity is inversed by using the pre-stack sub-angle seismic data; on the microscopic scale, the trend and density of the crack are inversed by using azimuth angle seismic data; and taking the residual error of the synthetic data obtained by the next scale inversion and the measured data as a correction term to be fed back to the inversion process of the previous scale so as to restrain and correct the inversion parameters of the previous scale. Earthquake and geological problems are decomposed to different scales such as structures, reservoirs and cracks, and the longitudinal resolution and geological conformity of inversion results are greatly improved.

The invention discloses a material failure process virtual space modeling and simulation method and system for a digital test, and the method comprises the steps: collecting the spatial geometric morphology, surface texture features, internal organization structure and service environment parameters of a structural material, and generating multi-source basic data; constructing a three-dimensional digital model based on the multi-source basic data; carrying out multi-physics field coupling modeling and failure mechanism simulation on the three-dimensional digital model under macroscopic, mesoscopic and microscopic scales, and determining a performance evolution process; and loading the three-dimensional digital model through a graphical user interface, controlling a simulation process and outputting a visual result. According to the method, a complete virtual modeling chain of the material failure process is formed from geometric reconstruction to multi-scale modeling and from simulation solution to result visualization; the system supports coupling modeling and data mapping under the microcosmic-mesoscopic-macroscopic scale, and the failure mechanism research depth is improved.

Technique capable of suitably estimating macroscopic characteristics or microscopic characteristics of target structure SOLUTION: An information processing apparatus (1) includes an acquisition unit (11) that acquires one or a plurality of macroscopic feature amounts characterizing a phenomenon of a subject structural body on a macroscopic scale and one or a plurality of microscopic feature amounts characterizing at least one of a structure and a behavior of a component of the subject structural body on a microscopic scale of the subject structural body, and a generation unit (12) that generates a model defining a correspondence relationship between the phenomenon of the subject structural body on the macroscopic scale and at least one of the structure and the behavior of the component of the subject structural body on the microscopic scale of the subject structural body and including one or a plurality of stages of scaling processing with reference to the one or the plurality of macroscopic feature amounts and the one or the plurality of microscopic feature amounts acquired by the acquisition unit.SELECTED DRAWING: Figure 1

The invention discloses a shale reservoir supercritical carbon dioxide fracturing numerical simulation method and system, and belongs to the technical field of unconventional oil and gas exploitation. Mineral phase real microscopic distribution characteristics and multiple groups of microscopic rock mechanical parameters of a sample are obtained; determining the probability that each group of microscopic rock mechanical parameters belong to each mineral phase, and obtaining the average rock mechanical parameter value of each mineral phase; according to the real microcosmic distribution characteristics of the sample mineral phase, generating a microcosmic mineral distribution random field according with the real distribution characteristics of shale; according to the average rock mechanical parameter value of each mineral phase and the shale microscopic mineral distribution random field, the microscopic mechanical characteristics of the microscopic mineral distribution random field are equivalent to the microscopic scale, the microscopic scale is upgraded to the macroscale, a supercritical carbon dioxide fracturing model of the shale reservoir in the in-situ environment is constructed, and numerical simulation is carried out. By means of the method, accurate expression of the nanoscale-millimeter scale-meter scale-mine scale reservoir transformation numerical model can be achieved.

This invention discloses an automated cell manipulation method and system guided by artificial intelligence, comprising: identifying and locating the biological target object to be manipulated based on real-time images acquired by a microscopic imaging system to obtain target position information; calibrating and tracking the end-effector position of a micromanipulator based on the real-time images to obtain the real-time end-effector position; planning and dynamically correcting the motion trajectory of the micromanipulator based on the target position information and the real-time end-effector position until the end-effector reaches the preset target operation position, and controlling the micromanipulator to execute a preset interactive operation; verifying the operation result based on the real-time image after the operation to obtain the verification result, and controlling subsequent processes based on the verification result. This invention overcomes the inherent defects of traditional manual operation and semi-automated solutions in microscale cell manipulation through an end-to-end intelligent process, achieving high-precision, high-throughput, high-success-rate, and highly standardized cell manipulation.

The application discloses a kind of fracturing perforation hole erosion effect multiscale characterization simulation method and device.The method comprises the following steps: establishing wellbore hole erosion experiment under different experimental conditions of different hole cluster types;Quantitative description and characterization of hole erosion are carried out according to experimental data, and hole erosion expansion characteristic expression is obtained;Expansion characteristic expression and hole erosion modeling parameter are used to establish microscale hole erosion expansion characteristic model;Based on experimental data and expansion characteristic model, the hole erosion flow distribution and sand passing rule under different hole cluster types are obtained, and the hole erosion expansion non-uniformity coefficient and perforation flow distribution coefficient of different perforation clusters are established;Hole erosion expansion characteristic expression, non-uniformity coefficient and flow distribution coefficient are introduced into macroscopic field crack propagation model, and macroscopic field crack propagation model capable of simulating perforation hole erosion expansion characteristic is constructed.The influence of different perforation hole expansion on crack non-uniform expansion can be simulated in detail, and the accuracy of simulation characterization is improved.

The present disclosure concerns an ultrasound 3D imaging probe (200) for imaging vascular activity dynamically at a microscopic scale in an organ of a body of a living being, the probe (200) comprising : - a mosaic ultrasound array (100) comprising a plurality of polygonal transducer element pads, each pad (101) comprising a set of transducer elements (102) distributed on a substrate (103), each transducer element (102) being configured to acquire at least a backscattered ultrasound wave from the organ following an ultrasound emission in said organ; - a support frame (10) comprising an intern surface intended to be placed facing said body; - each polygonal transducer element pad (101) being located and attached in a removable manner on said internal surface of the support frame (10).

The invention relates to the technical field of laser engraving, and discloses a device for engraving complex textures of glass and an engraving method thereof.The device comprises a nano-structure preparation module used for constructing a nano-particle structure corresponding to glass to be engraved; the process planning module is used for generating a laser engraving path and key laser parameters of the to-be-engraved glass; the signal monitoring module is used for synchronously monitoring a plasma optical signal corresponding to the nano-particle structure in the initial carving texture forming process; the optimization control module is used for generating an online control instruction set and a self-adaptive parameter optimization strategy of the glass to be engraved; and the online correction module is used for carrying out precision correction processing on the initial carving texture based on an online control instruction set and a self-adaptive parameter optimization strategy. According to the method, the texture form of glass carving can be accurately controlled on the microscopic scale, and the overall carving level of glass complex textures is improved.

The invention relates to a method for predicting the mechanical property of a metal additive manufacturing forming component, and belongs to the technical field of material science. Macroscopically, a finite cell method is adopted to directly carry out regularized grid discretization on computed tomography data, and a complex pretreatment process is avoided; the self-consistent clustering analysis is adopted for solving in the microcosmic process, so that the microcosmic calculation efficiency is greatly improved; and the two scales are coupled in real time for data transmission. A concurrent two-scale solving strategy is adopted to replace an existing single-scale technology, and the influence of a low scale (micro scale) on a macro scale can be naturally considered; a macroscopic finite cell method is adopted to replace a macroscopic finite element method adopted by an existing concurrent multi-scale technology, and a complex pretreatment process is avoided. Microscopic self-consistent clustering analysis is adopted to replace a microscopic crystal plasticity finite element method adopted by an existing concurrent multi-scale technology, model order reduction is carried out on a microscopic representative volume unit, and the calculation efficiency is greatly improved.

The invention discloses a cross-scale alloy material intelligent calculation method and system, and belongs to the technical field of material calculation and computer simulation. The core of the method is that firstly, a genome integrating cross-scale alloy calculation of first principle calculation, chemical and physical process simulation, finite element analysis and the like is constructed; secondly, bidirectional adaptation and conversion of input and output data between models of different scales are achieved through a model adaptation conversion layer, and conversion comprises data disturbance analysis based on a neural network and conversion of microstructure data into a mesoscopic computable model; finally, alloy material calculation task data is driven to be subjected to chain type step-by-step calculation along the model genome to obtain the macroscopic performance of the alloy material, and attribution analysis from macroscopic performance change reverse tracing to microscale parameter disturbance is achieved by setting multiple sets of parameter disturbance. According to the method, a scale gap in material calculation is effectively broken, automatic and high-throughput calculation and accurate attribution from atoms to macroscopicity are realized, and the efficiency and depth of new material research and development are greatly improved.

The application provides a solution refractive index real-time detection method based on amplification imaging and machine vision, which comprises the following steps: step A, illumination light emitted by an illumination light source is irradiated to a microscopic scale, and forms light carrying microscopic scale information, and then sequentially passes through a sample flow cell and a hollow glass block, and is emitted to an image sensor; step B, the emitted light is imaged on the image sensor, the image information of the microscopic scale on the image sensor is recorded, the image sensor is driven to displace through a focusing algorithm, until the imaging of the microscopic scale is a clear image, and the axial position of the image sensor is recorded, and the solution refractive index is analyzed according to the relationship between the axial position of the image sensor and the solution refractive index; step C, the magnification of the object image of the microscopic scale on the imaging system is analyzed through the imaging size of the microscopic scale on the image sensor, and the solution refractive index is inversely calculated, and the solution refractive index obtained in step B is compared, and the redundancy of system measurement is improved.

Method for imaging vascular activity dynamically at a microscopic scale in a vascular network of a human or animal, the method including: (a) performing a temporal series of Ultrasound Localization Microscopy images of a region of the vascular network, to obtain values of a vascular dynamics parameter in an area of interest in the region, a recording period of the temporal series of ULM images corresponding to a dynamical event, due to a cause other than cardiac pulsatily, which activates the vascular network in the region; (b) computing, based on the values of the vascular dynamics parameter, a measure of an evolution of the vascular dynamics parameter in response to the dynamical event.

This invention provides a method and system for simulating lightning damage to composite materials based on Direct FE2, comprising: step S1, constructing a macroscopic finite element model and a microscopic Resonant Velocity (RVE) model of the composite material; step S2, calculating the scaling factor and adjusting the volume of the microscopic RVE model based on the extended Hill-Mandel energy equivalence condition; step S3, establishing direct constraints between the boundary nodes of the microscopic RVE model and the element nodes of the macroscopic finite element model, coupling the microscopic RVE model and the macroscopic finite element model to obtain the Direct FE2 model; and step S4, setting the lightning strike conditions required for lightning strike simulation on the Direct FE2 model and applying loads to obtain the potential field distribution and temperature field distribution. Therefore, this invention can preserve the microscopic properties of the fiber and matrix, and achieve accurate coupling and transmission of multiple physical fields and high-precision prediction at the microscopic scale.

The invention discloses a strain gradient regulation ion field effect transistor conductivity calculation method and system based on multi-scale parameter transmission. And realizing cross-scale calculation based on a parameter transfer method, wherein the cross-scale calculation comprises microscopic, mesoscopic and macroscopic scale calculation. The ion migration behavior is analyzed and quantified on the microscale based on a molecular dynamics method, a particle displacement field is obtained through the particle position, the ion migration rate and the diffusion coefficient obtained through calculation, and the particle displacement field serves as a transfer parameter and is substituted into mesoscale calculation. And calculating on the basis of a modified Poisson-Nernst-Planck equation on a mesoscale to obtain an interface potential barrier and a carrier concentration under the influence of the strain gradient, substituting the interface potential barrier and the carrier concentration into macroscale calculation, and calculating and outputting the conductance of the ion field effect transistor on the macroscale. According to the multi-scale calculation model, the cross-scale calculation method suitable for the strain gradient regulation and control ion field effect transistor is innovatively provided, and trend theoretical guidance can be effectively provided for experimental design and application.

The invention discloses a method for revealing a 6H-SiC reciprocating friction cross-scale damage mechanism, which comprises the following steps: firstly, obtaining macroscopic friction wear behavior data of 6H-SiC through a reciprocating friction experiment under a series of loads; afterwards, the worn surface is analyzed in combination with a scanning electron microscope and an energy spectrum, a high-load worn section is observed by utilizing a focused ion beam and a high-resolution transmission electron microscope, and a cross-scale damage sequence of amorphization, nanocrystalline residue and microcrack propagation of the subsurface is directly revealed. Furthermore, the origin of key damage processes such as amorphization and dislocation activities is reproduced and explained from the atomic scale through molecular dynamics simulation. The method systematically reveals a damage evolution mechanism of 6H-SiC from an atomic scale to a microscale under reciprocating friction through a macroscopic experiment, microcosmic characterization and atomic simulation, and provides a systematic analysis means for deeply understanding tribological behaviors of the 6H-SiC and carrying out targeted performance research.

This invention discloses an abrasive performance evaluation index and its testing method, belonging to the field of abrasive performance evaluation technology. The method includes the following steps: obtaining structural characteristic parameters of the abrasive sample at different scales, where the different scales include at least macroscopic, mesoscopic, and microscopic scales. Macroscopic scale parameters include the particle size distribution and packing density of the abrasive; mesoscopic scale parameters include the surface roughness and microscopic fracture toughness of the abrasive particles; and microscopic scale parameters include the crystal orientation distribution, dislocation density, nanoindentation hardness, and fracture toughness of the abrasive. The structural characteristic parameters obtained in step S1 are then input into a pre-constructed performance prediction model. This invention overcomes the problem of incomplete information in traditional single-scale evaluation methods by obtaining multi-scale structural characteristic parameters of abrasives at macroscopic, mesoscopic, and microscopic scales, achieving a comprehensive and refined characterization of abrasive performance.

The invention provides a weakly-sandy dolomite pore throat network model construction method and system based on CT scanning, and the method comprises the steps: carrying out the macroscopic, mesoscopic and microscopic CT scanning of a rock sample of weakly-sandy dolomite, and obtaining three-dimensional image data with different resolutions; performing multi-mineral phase intelligent identification and segmentation on the three-dimensional image data by adopting a multi-modal fusion and boundary perception progressive 3D segmentation network to obtain a semantic segmentation result; carrying out registration and fusion on the semantic segmentation results, and constructing a multi-scale digital core model; and based on the multi-scale digital core model, a pore throat network structure is extracted by adopting a maximum sphere algorithm, a pore throat network model is obtained, and quantitative characterization of the micro-pore structure of the weakly sanded dolomite is realized. The high-precision pore throat network model constructed by the method can provide a crucial digital basis and theoretical basis for seepage mechanism research, reserve evaluation, well drilling and completion scheme optimization and recovery ratio improvement strategy formulation of the weakly sandy dolomite reservoir.

The invention discloses a material mechanical property parameter prediction method based on a deep learning model, and relates to the field of material mechanical property parameter prediction.The method comprises the steps that nanoindentation is conducted on a target material, and a nanoindentation curve is obtained; taking the crystal grains subjected to nanoindentation as nodes of the graph structure, and obtaining features of the corresponding crystal grains from the nanoindentation curve as initial node features to obtain an initial node feature matrix; obtaining nanoindentation graph structure data; the nanoindentation graph structure data serve as input of a deep learning model, the mechanical property parameters of the target material are predicted through the deep learning model, and the mechanical property parameters of the target material are obtained. According to the method, the interaction between crystal grains is particularly considered when the nanoindentation test is carried out and curve characteristics are analyzed, and related steps are designed, so that the nanoindentation test can be supplemented at the micro-scale, the real situation of the material can be better reflected, and the prediction accuracy of the mechanical property parameters of the material is improved.

This invention discloses a method and system for predicting the permeability of spherical particle systems based on machine learning. The method uses the discrete element method to generate assemblies of spherical particles with different gradations, and performs region segmentation on the particle samples to establish a sample dataset containing particle material gradation information and three-dimensional image structure. Then, the permeability of the particle samples is calculated using the lattice Boltzmann method and the D3Q19 lattice model. The method extracts macroscopic and microscopic structural features of the particle samples; constructs a dataset for training the machine learning model; trains the machine learning model, and finally obtains a model that can accurately and effectively predict permeability based on the multi-scale structural features of the particle material. This invention overcomes the limitation that macroscopic structural parameters cannot accurately describe the complex internal structure of pores. Furthermore, by constructing a machine learning-based permeability prediction model based on the extracted structural parameters, it solves the problems of long testing times and limited testing equipment due to the large range of particle size variations in traditional seepage tests.

The invention relates to the technical field of welding, in particular to a convenient-to-weld high-porosity structural material which is characterized in that S1, according to the overall macroscopic design of a weld joint, a high-porosity foam titanium multilayer structure has the heat insulation requirement and the light weight requirement; s2, in the aspect of weld microcosmic design, the high-porosity structural material is of a dot matrix porous structure; by means of macroscopic design of welding seam distribution, structural stability and reliability in large structure manufacturing are guaranteed, meanwhile, the heat insulation performance of the whole structure is not affected, and by means of microcosmic design of a welding seam area, the problems that a medium to be welded is discontinuous, heat is prone to gathering, a molten pool fluctuates greatly, and the welding quality is poor due to the small welding seam area are solved. And it is guaranteed that macroscopically designed welding seams all meet the strength requirement on the microscopic scale.