Metal-polymer hybrid (MPH) materials can integrate the excellent mechanical properties of metal and complex geometry formability of polymer into a single component, which has become an effective way of reducing the weight of automotive semi-structural components. For example, the hybrid steel/thermoplastic polymer has been applied in automotive front-end modules, bumper cross-beams and B-pillars due to its light weight, excellent strength and stiffness, good corrosion resistance and recycling, high integration and reasonable cost. These components are usually subjected to impact or crash loads and the strain rate effect should be taken into account.
This paper aims to experimentally and numerically study the dynamic behavior of MPH materials at different strain rates and provide an accurate and efficient numerical model for crash simulation of vehicles with MPH components.
Firstly, MPH specimens with high strength steel (HSS) and glass fiber-reinforced thermoplastic polymer (GFRTP) were fabricated by direct injection molding adhesion (DIMA) process. Then, the dynamic mechanical properties of MPH specimens under strain rates from 800 s−1 to 2000 s−1 were investigated by Split Hopkinson Pressure Bar (SHPB) experiments. Finally, a strain rate-dependent numerical model was established in ABAQUS software to simulate the dynamic behavior of MPH specimens and validated by experimental results. Three numerical approaches for modeling the interface between the two discrete material phases were considered and compared to examine the level of interaction between two constitute materials. Cohesive zone modeling technique at the interface which saved modeling and characterization time and showed adequate predictive capability proved to be generally applicable to the evaluation of structural concepts in an early vehicle development stage.
This study provides a foundation for the future engineering application of HSS/GFRP hybrid materials and numerical models for automotive crash simulation.
It is reported that carbon nanotube (CNT)-based conductive polymer composites have potential application prospect in structural health monitoring and flexible sensors. However, the current price of CNTs is relatively high compared with other fillers. To reduce the materials cost and ensure the sensing characteristics of this type of materials, the most economic and least amount of CNTs needed should be found, this balance value is called as electrical percolation threshold (EPT) in this study. First, a large number of numerical models containing CNTs with three-dimensional random distribution and epoxy resin matrix are established by Monte Carlo method. Then, the construct of conductive network is observed using these models, and the influence of electron tunneling between two adjacent CNTs on the EPT is investigated. Furthermore, the influence of length-diameter ratio (L/D) of CNTs, length variation and angle distribution of CNTs on EPT is investigated. This research provides useful information on how to produce conductive composites more economically.
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