7 results about "Grain orientation" patented technology

The application discloses a kind of second generation nickel-based single crystal superalloy recrystallization defect simulation and control method.The method steps are: according to sample preparation wax mold, after sand blasting, dry baking, manufacture ceramic shell;Through directional solidification preparation second generation nickel-based single crystal superalloy sample, control pulling speed, holding temperature and temperature gradient and other parameters;According to service condition preparation sample, simulate stress loading, in combination with heat treatment simulate actual service environment;Using electron backscattering diffraction and X-CT imaging, characterize recrystallization grain orientation distribution, three-dimensional morphology, content and thickness.Process parameter-defect characteristic mapping relationship is established, the stress distribution characteristics during preparation are clarified, the ceramic shell and preparation process are feedback controlled, and the control of recrystallization defects is realized.The application simulates the actual service environment of high-temperature alloy blade, and restores the performance of recrystallization defect sample in actual service environment.The application provides an experimental reproduction method and effective process control strategy for recrystallization defect research.

The application discloses a kind of grain map neural network's weld ultrasonic beam path correction method, it is related to the field of welding structure nondestructive testing, by obtaining the EBSD data of weld area, extract grain orientation, grain boundary type and spatial distribution characteristics, construct grain map structure, and calculate initial propagation time weight based on anisotropic sound velocity model;Using graph neural network to learn end to end for grain node and grain boundary edge features, output corrected edge propagation time weight;The time of flight from element to imaging pixel is obtained by shortest path search, and the time of flight predicted by neural network surrogate model is fused and corrected;Finally, the corrected time of flight is used to perform full focus imaging, and the weld defect image after optimizing the beam path is obtained.The method combines material microstructure characteristics and machine learning model, solves the problem that the beam path description is not fine enough in existing weld ultrasonic testing, significantly improves the accuracy and reliability of defect detection.

The application relates to the technical field of material performance evaluation, and provides a material strength and plasticity rapid nondestructive evaluation method based on EBSD data, which comprises the following steps: adopting an EBSD technology to characterize a material surface state, obtaining a backscattering diffraction pattern and obtaining original EBSD data and a grain orientation map of the material; based on the reconstructed grain orientation map, microstructure characteristic parameters of each grain in a target region of the sample are extracted respectively; based on the extracted microstructure characteristic parameters, a plasticity sensitivity coefficient of each grain is calculated; based on the slip distribution characteristics of the grains under the plasticity sensitivity coefficient, the target region of the sample is divided into a plasticity deformation dominant area and a strength dominant area, and partition visualization is realized through space mapping and different color filling; and based on the respective microstructure characteristic parameters of the areas, microstructure-mechanical property evaluation models are respectively established, so that the material strength and plasticity are rapidly evaluated.

This invention provides a method for constructing a designable nanograin boundary network on the surface of metal powder, belonging to the fields of powder metallurgy and material surface engineering. The invention includes ultrasonic cavitation pretreatment to construct a high-defect nanoscale layer on the surface, external field-assisted annealing to control the surface grain boundary geometry, and cooling and post-treatment. By introducing a high-defect nanoscale layer on the powder surface and combining it with external field-assisted annealing to achieve selective recrystallization and grain orientation reconstruction, this invention obtains a nanograin boundary network structure with controllable grain boundary type, orientation, and curvature on the powder surface, thereby providing a stable and reproducible microstructural basis for improving powder surface properties.

The application relates to the technical field of material performance evaluation, and provides a material strength and plasticity rapid nondestructive evaluation method based on EBSD data, which comprises the following steps: adopting an EBSD technology to characterize a material surface state, obtaining a backscattering diffraction pattern and obtaining original EBSD data and a grain orientation map of the material; based on the reconstructed grain orientation map, microstructure characteristic parameters of each grain in a target region of the sample are extracted respectively; based on the extracted microstructure characteristic parameters, a plasticity sensitivity coefficient of each grain is calculated; based on the slip distribution characteristics of the grains under the plasticity sensitivity coefficient, the target region of the sample is divided into a plasticity deformation dominant area and a strength dominant area, and partition visualization is realized through space mapping and different color filling; and based on the respective microstructure characteristic parameters of the areas, microstructure-mechanical property evaluation models are respectively established, so that the material strength and plasticity are rapidly evaluated.

The application discloses a kind of based on crystal plasticity welding joint fatigue weak area evaluation method, for the fatigue failure problem caused by the complex microstructure such as the difference of grain orientation and uneven grain size distribution of welding joint, quantitative correlation model of grain orientation and size evolution is established by CPFEM, combined with macro-micro scale analysis method, realize the accurate prediction of local stress concentration and crack initiation behavior of welding joint under real fatigue load condition, to complete the scientific evaluation of fatigue weak area.This method is coupled by load condition restoration and grain characteristics multi-scale, constructs the innovative framework of fatigue weak area evaluation, makes up the oversimplification of traditional method to real load condition, overcome the limitation that traditional model is difficult to couple microstructure and real load, significantly improve the quantitative precision of fatigue weakening, provide high-precision analysis technology for the fatigue resistance design, process optimization and life assessment of engineering welded structure.

The application relates to the technical field of metal material development, in particular to a method for accurately calculating the orientation relationship and the beta-Ti grain orientation before phase change in titanium and its alloy. The method is based on the principle of minimizing the average orientation difference between the theoretical orientation and the measured orientation of all alpha-Ti variants generated by the phase change of the same original beta-Ti grain, and directly determines the optimal solution through mathematical optimization. The application adopts a suitable mathematical calculation method, so that the average value of the deviation angle between the measured orientation and the theoretical orientation of all alpha variants transformed from the same beta-Ti grain is minimized, thereby accurately calculating the beta-Ti grain orientation and the orientation relationship in the phase change process.