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In this paper, an intelligent self‐healing carbon fiber composite based on core‐shell nanofiber for structural applications was introduced. The self‐healing epoxy resin and curing agent were encapsulated in polyacrylonitrile by coaxial electrospinning to form two‐component core‐shell nanofibers. The core‐shell nanofibers were distributed between the carbon fiber layers, and the mechanical strength of the composites was improved by changing the interlaminar distribution of the core‐shell nanofibers. The bending test showed that the bending strength could be increased by 5.96%. The best self‐healing conditions were determined by curing kinetic analysis and bending test. The results showed that the healing efficiency could reach 110.12% after self‐healing at 120°C for 1 h. The release of self‐healing agent and the filling of microcracks were clearly observed by scanning electron microscope. The addition of core‐shell nanofibers can prolong the service life and improve the mechanical strength of the composites, which has a potential application prospect in structural applications.

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Purpose As the transmission component of a locomotive, the traction gear pair system has a direct effect on the stability and reliability of the whole machine. This paper aims to provide a detailed dynamic analysis for the traction system under internal and external excitations by numerical simulation. Design/methodology/approach A non-linear dynamic model of locomotive traction gear pair system is proposed, where the comprehensive time-varying meshing stiffness is obtained through the Ishikawa formula method and verified by the energy method, and then the sliding friction excitation is analyzed based on the location of the contact line. Meantime, the adhesion torque is constructed as a function of the adhesion-slip feature between wheelset and rail. Through Runge–Kutta numerical method, the system responses are studied with varying bifurcation parameters consisting of exciting frequency, load fluctuation, gear backlash, error fluctuation and friction coefficient. The dynamic behaviors of the system are analyzed and discussed from bifurcation diagram, time history, spectrum plot, phase portrait, Poincaré map and three-dimensional frequency spectrum. Findings The analysis results reveal that as control parameters vary the system experiences complex transition among a diverse range of motion states such as one-periodic, multi-periodic and chaotic motions. Specifically, the significant difference in system bifurcation characteristics can be observed under different adhesion conditions. The suitable gear backlash and error fluctuation can avoid the chaotic motion, and thus, reduce the vibration amplitude of the system. Similarly, the increasing friction coefficient can also suppress the unstable state and improve the stability of the system. Originality/value The numerical results may provide a systemic understanding of dynamic characteristics and present some available information to design and optimize the transmission performance of the locomotive traction system.