The application of carbon fiber-reinforced thermoplastics (CFRTPs) for automotive mass production is attracting increasing attention from researchers and engineers in related fields. This article presents recent developments in CFRTPs focusing on the systematic development of lightweight CFRTP applications for automotive mass production. Additionally, a related national project of Japan conducted at the University of Tokyo is also introduced. The basic development demands, the specific requirements of CFRTPs for lightweight applications in automotive mass production, and the current development status and basic scientific outputs are discussed. The development of high-performance CFRTPs (chopped carbon fiber tape-reinforced thermoplastics (CTTs)) and functional CFRTPs (carbon fiber mat-reinforced thermoplastics (CMTs)) is also introduced. The fabrication process control of CTTs is evaluated, which demonstrates the extreme importance of the mechanical performance. The ultralight lattice, toughened structures, and orientation designable components of CMTs provide a flexible multi-material solution for the proposed applications. Moreover, highly efficient carbon fiber recycling technology is discussed, with recycled carbon fibers exhibiting outstanding compatibility with CFRTPs. A cost sensitivity analysis of carbon fiber and CFRTPs is conducted to guarantee the feasibility and affordability of their application. This article also discusses the trends and sustainability of carbon fiber and CFRTPs usage. The importance of the object-oriented optimal development of CFRTPs is emphasized to efficiently exploit their advantages.
1 December 2016 in Composites Science and Technology
The thermal deformation, which is called “deconsolidation” or “springback,” is often observed when the randomly oriented short carbon fiber reinforced thermoplastics are heated. In the present study, the deconsolidation effect of two kinds of randomly oriented short carbon fiber reinforced thermoplastics was studied experimentally and theoretically. The deconsolidation ratios were measured as the thickness ratio of the deformed randomly oriented short carbon fiber reinforced thermoplastics in the experiments. The results indicated that the deconsolidation of the randomly oriented short carbon fiber reinforced thermoplastics is caused by the release of the molding elastic deformation of fibers. Structural and molding factors that can affect the deconsolidation ratio were defined and empirical fitting functions were established. The deconsolidation ratios calculated by the functions were compared with the experimental results and the agreement was found to be satisfactory. At last, the fiber volume fraction effect and molding pressure effect on the deconsolidation ratio were investigated using the equations.
Randomly oriented strands (ROS) exhibit multiscale inhomogeneous and significant stochastic variations even in elastic properties because of their complex internal geometries. To quantify the variations and expand the applicability of ROS in industrial fields, a laminate analogy analytical model was developed in combination with Monte Carlo simulation-based statistical analysis to compute the mean and variance of the elastic modulus of ROS. Two semi-empirical fitting equations were formulated to calculate the mean and variance of the elastic modulus, thus reducing the need for onerous experiments. The effects of strand morphology on the stochasticity of the elastic properties are discussed in detail for the first time. The results of the analytical model showed significant applicability and good agreement with the experimental data under various conditions, and the formulated equations were able to provide satisfactory values for the mean and variance of the elastic modulus with different strand properties and strand/specimen morphologies. The role of the strand morphology (thickness, width, and length) was analyzed from a statistical perspective and the thickness ratio of the strand to the specimen was found to be the most effective factor for reducing the stochasticity of ROS.