Abstract: Graphene (Gr) is widely used as the reinforcing phase of metal-based materials due to its excellent properties, but the mechanism of the microscopic effect of graphene on the wear resistance of copper-tungsten alloy (CuW) is still unclear. In this paper, based on the molecular dynamics simulation method, the particle swarm algorithm is applied to establish the composite models of CuW80 and different mass fractions of graphene-doped CuW80Gr for the characteristics of CuW "pseudo-alloys". According to the models, the elastic moduli in the temperature range of 300~3000K are calculated via LAMMPS, the hardness of the models is calculated by nanoindentation simulations, and the enhancement mechanism of graphene on the mechanical abrasion resistance of CuW80Gr composite models is analyzed from the dynamic evolution of microscopic dislocations. The results show that the elastic modulus and hardness of CuW80Gr model are higher than those of CuW80, and they both show a tendency to decrease with the increase of graphene mass fraction. The addition of graphene contributes to solve the problem of mechanical property degradation caused by high temperature during the opening and closing of the circuit breaker, and the strengthening mechanism of graphene on CuW composites is barrier effect and dislocation strengthening. This study can provide theoretical guidance and technical support for the doping optimization design, selection, and performance control of copper-tungsten alloy composites.