Method for establishing concrete in-situ mesoscopic finite element model based on CT (Computed Tomography) scanning technology

By using CT scanning technology and Python programs to process images, combined with direct thresholding and local image segmentation, the problem of accurately reflecting fiber distribution and porosity effects in existing modeling methods was solved, and an efficient and accurate micro-finite element model of steel fiber reinforced concrete was constructed.

CN121744748APending Publication Date: 2026-03-27NINGXIA UNIVERSITY
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Patent Information

Application Number
CN202511768691.4
Authority / Receiving Office
CN · China
Patent Type
Applications(China)
Current Assignee / Owner
Filing Date
2025-11-28
Publication Date
2026-03-27

AI Technical Summary

Technical Problem

Existing microscopic modeling methods for steel fiber reinforced concrete cannot accurately reflect the true spatial distribution of fibers and the influence of porosity, and the image segmentation effect is poor, resulting in large model deviations.

Method used

CT scanning technology was used for image preprocessing and three-phase separation. Porous phase and fiber phase were separated by combining direct thresholding and local image segmentation. The matrix finite element mesh and fiber beam element model were generated by Python program to construct a complete micro-finite element model of steel fiber reinforced concrete.

Benefits of technology

It improves modeling accuracy and efficiency, accurately reflects the internal structural characteristics of steel fiber reinforced concrete, overcomes the problems of over-segmentation or under-segmentation, and generates efficient and accurate finite element models.

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Abstract

The invention discloses a method for establishing a concrete in-situ mesoscopic finite element model based on a CT (Computed Tomography) scanning technology, which is applied to the technical field of mesoscopic simulation of a concrete structure. The method comprises the following steps: firstly, performing XCT scanning on a steel fiber ultra-high performance concrete test piece to obtain a two-dimensional sequence image of an internal structure of the steel fiber ultra-high performance concrete test piece; then, image processing is carried out through Avizo software, and three-dimensional space distribution information of a base body, steel fibers and pores is segmented and extracted; on the basis of the three-dimensional information, a Python program is utilized to generate a finite element mesh, an eight-node hexahedron unit is adopted in a model, and the established model can accurately reflect real mesoscopic characteristics such as fiber orientation, distribution and pore defects.
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