Abstract
In this paper, considering the strength and geometric discrete distribution characteristics of composite reinforcement, by introducing the discrete distribution function of reinforcement, the secondary development of ABAQUS is realized by using the Python language, the parametric automatic generation method of representative volume elements of particle-reinforced composites is established, and the tensile properties of silicon carbide particle-reinforced aluminum matrix composites are analyzed. The effects of particle strength, particle volume fraction, and particle random distribution on the mechanical properties of SiCp/Al composites are studied. The results show that the random distribution of particles and the change in particle strength have no obvious influence on the stress–strain relationship before the beginning of material damage, but have a great influence on the damage stage, maximum strength, and corresponding failure strain. With the increase in particle volume fraction, the damage intensity of the model increases, and the random distribution of particles has a great influence on the model with a large particle volume fraction. The results can provide a reference for the design, preparation, and characterization of particle-reinforced metal matrix composites.
Highlights
Silicon carbide particle-reinforced aluminum matrix (SiCp/Al) composites are favored in the fields of microelectronic packaging, aircraft, high-speed trains, armor protection, and so on because of their excellent properties, such as high specific strength, high modulus, excellent thermal conductivity, wear resistance, and low coefficient of thermal expansion [1,2,3,4].it is of great engineering value to study the mechanical properties of SiCp/Al composites
Qing et al [12,13,14] studied the effects of particle arrangement and interface strength on the mechanical properties of particle-reinforced metal matrix composites under different loading modes, and developed a program to automatically generate a two-dimensional model with random distribution of particle size and position
In order study the effect of particle strength on the mechanical properties of parti3
Summary
Silicon carbide particle-reinforced aluminum matrix (SiCp/Al) composites are favored in the fields of microelectronic packaging, aircraft, high-speed trains, armor protection, and so on because of their excellent properties, such as high specific strength, high modulus, excellent thermal conductivity, wear resistance, and low coefficient of thermal expansion [1,2,3,4]. Shao et al [11] established a finite element numerical model considering the particle size parameters of reinforcement, and studied the effect of particle size on the mechanical behavior of composites. Qing et al [12,13,14] studied the effects of particle arrangement and interface strength on the mechanical properties of particle-reinforced metal matrix composites under different loading modes (uniaxial and biaxial tension), and developed a program to automatically generate a two-dimensional model with random distribution of particle size and position. In this paper, considering the strength and geometric discrete distribution characteristics of composite reinforcement, by introducing the discrete distribution function of reinforcement, the secondary development of ABAQUS is realized by using the Python language, the parametric automatic generation method of representative volume elements of particle-reinforced composites is established, and the tensile properties of silicon carbide particle-reinforced aluminum matrix composites are analyzed. The effects of particle strength, particle volume fraction, and particle random distribution on the mechanical properties of SiCp/Al composites are studied
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