11 results about "Nanoindentation" patented technology

This invention discloses a discrete element method, system, medium, and equipment for simulating equivalent crystalline materials, relating to the field of numerical simulation of rock mechanics. The method includes: converting granite images into binary images using a binarization method to identify various minerals within the binary images; determining the size data of various minerals in the binary images based on a particle size statistical algorithm; extracting micromechanical parameters using nanoindentation experiments combined with a trial-and-error method, and constructing multiple sets of equivalent crystalline models based on the mineral size data; dividing each set of equivalent crystalline models into multiple regions using a Brazilian splitting experiment; determining the optimal magnification for each region of each set of equivalent crystalline models by magnifying from non-critical regions to critical regions using a magnification algorithm, obtaining differentiated equivalent crystalline models; and performing Brazilian splitting numerical simulation using these differentiated equivalent crystalline models to obtain simulation results.

The C content in the chemical composition of an electric resistance welded steel pipe (1) according to the present disclosure is 0.19-0.35 mass%, and the tensile strength of the electric resistance welded steel pipe (1) is 1700 MPa or more. In a cross-section perpendicular to the pipe axis direction of a metal flow rising portion (3), a metal flow angle (AN), which is an angle between the outer circumferential surface of the metal flow rising portion (3) and a metal flow on the outer circumferential surface side, is 35-80°. In the cross-section, the hardness ratio RH of the average hardness (GPa) in a band-shaped region having a hardness of 8.5 GPa or more, obtained by a nanoindentation method, to the average hardness (GPa) in a band-shaped region having a hardness of 7.5 GPa or less is 1.8 or less. The FN value defined by equation (1) using the metal flow angle (AN) and the hardness ratio RH is 130 or less.　(1): FN = ANRH

The application provides a method for evaluating sand production risk of deep reservoir by using nanoindentation data, which comprises the following steps: step 1, performing nanoindentation test, and performing indentation feature observation and data analysis; step 2, performing indentation depth-load curve and data analysis; step 3, calculating macro mechanical parameters based on a weak cementation surface model and nanoindentation data; and step 4, performing sand production risk evaluation based on nanoindentation test data. The method for evaluating sand production risk of deep reservoir by using nanoindentation data adopts drilling cuttings, and the sample is easy to obtain; the test adopts a common nanoindentation experiment, the process is simple, and the repeatability is strong; the sand production risk evaluation can be obtained by simple calculation, the quantitative evaluation of the sand production risk evaluation coefficient is obtained, the comparison is convenient and quantitative, and the result is intuitive and clear.

The invention discloses a method for evaluating anisotropy and hydration compressive strength of shale based on rock debris, and relates to the technical field of exploration and development of petroleum and natural gas. According to the method, a nano-indentation experiment is adopted for testing the relation between indentation loads and displacement of the surface of a shale sample subjected to hydration treatment at different bedding angles; calculating to obtain the elastic modulus and hardness of the shale subjected to hydration treatment at different bedding angles; based on the elastic modulus and hardness parameters of the shale, establishing a uniaxial compressive strength calculation model by using a multivariate nonlinear multivariate fitting method; and finally, based on a modified Hoek-Brown strength criterion formula considering the anisotropy characteristics of the shale, calculating the compressive strength of the shale considering the anisotropy and the hydration effect. By adopting the method, the limitation of the size and shape of the shale sample can be broken through, the experiment cost and the test time consumption are reduced, the accurate and efficient evaluation of the shale compressive strength by considering anisotropy and hydration is realized, and the problem of testing the rock mechanical parameters of the underground deep shale of an oil-gas well is solved.

The method for predicting Vickers hardness by nanoindentation hardness through a deep learning neural network, in order to solve the problem that the existing Vickers hardness test method is destructive, time-consuming and low in test efficiency.The method for predicting Vickers hardness: I, the sample is treated by carburizing and plasma nitriding; II, the nanoindentation hardness and Vickers hardness of the sample are detected respectively; III, a depth-hardness DNN model is established, the depth-hardness DNN model includes three hidden layers, and the hardness data is expanded and trained through the depth-hardness DNN model; IV, a nanoindentation-Vickers hardness DNN model is established; V, the nanoindentation-Vickers hardness DNN model is trained by using the expanded data set; VI, the Vickers hardness is predicted.The present application constructs a multi-layer deep neural network to process the nonlinear relationship between the nanoindentation hardness and the Vickers hardness, and can accurately predict the Vickers hardness in the range of 400-1000 HV.

This invention discloses a method for optimizing hydraulic fracturing parameters based on nanoindentation spatial heterogeneity maps, relating to the field of coalbed methane extraction. The method includes: sampling and nanoindentation testing of the target coal seam to obtain load-displacement curves at each measuring point; analyzing and calculating the load-displacement curves at each measuring point to plot the heterogeneity map of the sampling points and the micromechanical spatial heterogeneity map of the entire coal seam; identifying the micromechanical spatial heterogeneity map of the entire coal seam; constructing a hydraulic fracturing design scheme based on the distribution information of the easily proliferating advantageous paths and difficult-to-proliferate disadvantageous paths of the fracturing fractures in the coal seam; and monitoring the fracture propagation range using resistivity tomography to dynamically adjust the fracturing parameters of the hydraulic fracturing design scheme. This invention generates micromechanical spatial heterogeneity maps using a nanoindentation instrument, characterizing the mechanical heterogeneity within coal and rock, saving trial-and-error costs in fracturing design, and reducing the blindness of fracturing.

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.

This invention relates to the field of springback control for high-strength steel, and discloses a method and application for predicting springback of manganese steel in a gradient microstructure considering the evolution of elastic modulus and microstructure distribution characteristics. The method includes: S1, extracting the gradient microstructure distribution characteristics of manganese steel along the thickness direction using image recognition technology to construct a representative volume element model; S2, measuring the evolution curves of the elastic modulus of each component phase in different regions as a function of strain using digital image correlation technology and nanoindentation technology; S3, importing the representative volume element model and the elastic modulus evolution curve data of each phase into a finite element simulation model, assigning elastic modulus properties as a function of strain to different component phases, performing bending springback simulation, and achieving accurate springback prediction. This invention effectively solves the problem of large and difficult-to-accurate springback in manganese steel forming in gradient microstructures by identifying gradient microstructure distribution characteristics and introducing the evolution law of elastic modulus of each phase, achieving an average relative error of less than 5% in springback angle prediction.

The present application belongs to the technical field of shale mechanics analysis, and particularly relates to a hard and brittle shale micro-mechanics performance analysis method and system based on nano-indentation. The analysis method provided by the present application is performed by combining micro-multiple scale experimental characterization and atomic scale molecular dynamics simulation. Experimental data is obtained through nano-indentation array experiments and multi-source micro-characterization, a heterogeneous molecular dynamics model is constructed, room temperature nano-indentation simulation is performed, gradient temperature is set for high temperature nano-indentation simulation and temperature effect is analyzed, and a corresponding prediction model is constructed, thereby providing micro-basis and a theoretical model for mechanical performance evaluation and prediction of deep shale under a thermal coupling environment.

This invention provides a method for obtaining the elastic modulus and hardness of a sample and a gas-phase hydrogen charging device. The method includes dividing the sample into hydrogen-charged and non-hydrogen-charged samples; embedding conductive powder into the bottom of the hydrogen-charged and non-hydrogen-charged samples, and polishing the test surfaces of the hydrogen-charged and non-hydrogen-charged samples to obtain hydrogen-charged and non-hydrogen-charged samples; performing nanoindentation tests on the test surfaces to obtain load-depth curves of the hydrogen-charged and non-hydrogen-charged samples; calculating the elastic modulus and hardness of the hydrogen-charged and non-hydrogen-charged samples based on the load-depth curves; the nanoindentation tests include standard nanoindentation tests, micro-load nanoindentation tests, and variable-rate nanoindentation tests. This method can more comprehensively characterize the hydrogen embrittlement of materials and analyze the mechanism of hydrogen embrittlement.