scholarly journals Selectively Enhanced 3D Printing Process and Performance Analysis of Continuous Carbon Fiber Composite Material

Materials ◽  
2019 ◽  
Vol 12 (21) ◽  
pp. 3529 ◽  
Author(s):  
Huiyan Luo ◽  
Yuegang Tan ◽  
Fan Zhang ◽  
Jun Zhang ◽  
Yiwen Tu ◽  
...  

Aiming at the limited mechanical properties of general thermoplastic 3D printed models, a 3D printing process method for selective enhancement of continuous carbon fiber composite material is proposed. Firstly, the selective enhanced double nozzle working mechanism and crafts planning process are put forward. Then, based on the double nozzle carbon fiber 3D printing device, test samples are printed by polylactic acid (PLA) and carbon fiber material, and the test samples are enhanced by inserting layers of continuous carbon fiber material. The performance test of the samples is carried out. Experiment results show that when the volume fraction of continuous carbon fiber material increases gradually from 5% to 40%, the tensile strength increases from 51.22 MPa to 143.11 MPa. The performance improvement curve is fitted through experimental data. Finally, field scanning electron microscopy is used to observe the microscopic distribution of continuous fibers in the samples. The results of the research lay the foundation for the performance planning of 3D printed models.

Materials ◽  
2019 ◽  
Vol 12 (19) ◽  
pp. 3164 ◽  
Author(s):  
Huili Yu ◽  
Hui Zhao ◽  
Fangyuan Shi

Unidirectional carbon fiber composite material is one of the most common types of composites employed in vehicles, and its bending performance plays an important role in crash safety, especially in side pole impact. This study aimed to redesign one of the most important components of the side structure of a vehicle, the rocker panel, with unidirectional carbon fiber composite material. Our results show that it is not easy to acquire the same bending performance as that of a steel rocker panel by merely replacing it with carbon fiber material and increasing the wall thickness. Therefore, reinforcements were employed to improve the bending performance of the carbon fiber rocker panel, and a polypropylene reinforcement method achieved a weight reduction of 40.7% compared with high-strength steel.


2020 ◽  
Vol 34 (07n09) ◽  
pp. 2040017
Author(s):  
Yung-Lan Yeh

This study investigates the possibility analysis of UAV propeller made by commercial 3D printing machine. The primary experimental facility is 3D printer based on Fused Deposition Modeling method (FDM). The main methodology of this work is to construct standard test piece according to ASTM standard and use for standard test. The Polylactic Acid (PLA) and carbon fiber composite material are the main two printing materials in this work. Experimental results reveal that the strength and bending of these two materials are enough to be the propeller of middle size UAV, especially the carbon fiber composite material. This study not only confirms the application possibility of UAV propeller made by 3D printing, but also carries out the real flight test to identify performance enhancement and future application.


2015 ◽  
Vol 2015.21 (0) ◽  
pp. _20312-1_-_20312-2_
Author(s):  
Keisuke Horiguchi ◽  
Ryosuke Matsuzaki ◽  
Akira Todoroki ◽  
Masato Ueda ◽  
Yoshiyasu Hirano ◽  
...  

2018 ◽  
Vol 83 (2) ◽  
pp. 20901 ◽  
Author(s):  
Ahmed Chaouki Lahrech ◽  
Bachir Abdelhadi ◽  
Mouloud Feliachi ◽  
Abdelhalim Zaoui ◽  
Mohammed Naїdjate

This paper proposes a contactless method for the identification of the electrical conductivity tensor of a carbon fiber composite materials plate using a rotating magnetic field and multi-coil eddy current sensor. This sensor consists of identical rectangular multi-coil, excited by two-phase sinusoidal current source in order to generate a rotating magnetic field and to avoid the mechanical rotation of the sensor. The fibers orientations, the longitudinal and transverse conductivities in each ply of carbon fiber composite material plate were directly determined with analysis of the impedance variation of each coil as function of its angular position. The inversion process is based on the use of artificial neural networks. The direct calculation associated with artificial neural networks makes use of 3D time-harmonic finite element method based on the A, V–A formulation.


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