Construction method of multi-degree-of-freedom lattice model of real concrete test piece

Abstract

The invention relates to a method for constructing a multi-degree-of-freedom lattice model of a real concrete test piece, which comprises the following steps of: scanning a concrete sample to be simulated by using CT equipment to obtain a high-resolution two-dimensional image stack; performing three-dimensional geometric reconstruction on the two-dimensional image stack obtained by scanning; performing structural component subdivision on a geometric reconstruction result of the three-dimensional real concrete test piece; converting the geometric reconstruction model of the subdivided structurecomponents into a corresponding finite element entity unit model and combining the finite element entity unit models; and performing optimization processing on the merged finite element entity unit model and converting the finite element entity unit model into a multi-degree-of-freedom lattice model. According to the method, the concrete test piece is subjected to multi-degree-of-freedom latticemodel reconstruction, so that the problems of low calculation efficiency and poor model reduction degree in a three-dimensional reconstruction numerical model based on a real concrete test piece can be solved, and the calculation efficiency can be greatly improved while the internal microstructure characteristics of the concrete are reserved to a great extent; and the authenticity and reliabilityof simulation are improved.

Description

technical field [0001] The invention relates to the technical field of concrete numerical simulation research, in particular to a method for constructing a multi-degree-of-freedom lattice model of a real concrete test piece. Background technique [0002] Concrete is a commonly used building material, and its mechanical and durability properties are closely related to the microstructure inside the concrete. Due to the multi-scale and porous characteristics of concrete, its internal aggregates, pores and microcracks cause structural heterogeneity and complexity. Traditional concrete numerical models, such as the random aggregate delivery model, have the disadvantage that the expression of the concrete structure is too simple to reflect the real stress and cracking state of the concrete, which objectively results in high-precision, high-reduction numerical values ​​of concrete. Simulation difficulties. [0003] With the emergence and development of concrete reconstruction tec...

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Problems solved by technology

The geometric method is mainly based on the microstructure of scanned entities such as aggregates and pores, and adopts image second-order moment, rotation invariant and other technical processing methods to identify the boundary point characteristics of the entity, adopts a bottom-up modeling method, and generates Points, lines, surfaces, and bodies are meshed to form a finite element model; and the mathematical method is to directly generate regular finite element elements based on the pixel characteristics of the 3D image, and assign corresponding material properties to form an overall solid finite element model; The finite element models generated by the two reconstruction methods are all solid elements. During the calculation process, the degree of freedom of the elements is relatively high, and the number of elements is large, which consumes a large amount of computing resources. Generally, personal computers cannot bear it. The solution to this problem is usually to reduce the The resolution of the image is reconstructed with fewer geometric features, and the reconstructed model has a certain degree of distortion and loses important microstructures such as microcracks, so the simulation results are relatively inaccurate

Therefore, there has always been a problem in concrete reconstruction technology that needs to be solved: the contradiction between model calculation efficiency and the authenticity of the reconstruction model. At present, there is no good solution to this contradiction, and it is impossible to solve the problem without sacrificing the authenticity of the model. , to improve the computational efficiency of the numerical simulation

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