A Review on Natural Fiber Composite Material in Automotive Applications

2021 ◽  
Author(s):  
Venkatesh Naik ◽  
◽  
Mohan Kumar ◽  
Vijayananda Kaup ◽  
◽  
...  
Keyword(s):  
Composite Material ◽  
Natural Fiber ◽  
Fiber Composite ◽  
Automotive Applications ◽  
Fiber Composite Material ◽  
Natural Fiber Composite

Sustainable development of natural fiber composite material

2020 ◽  
Author(s):  
M. Balachandar ◽  
E. Vetre Selvan ◽  
A. Ponshanmugakumar ◽  
S. Magesh ◽  
N. Ramanan
Keyword(s):  
Sustainable Development ◽  
Composite Material ◽  
Natural Fiber ◽  
Fiber Composite ◽  
Fiber Composite Material ◽  
Natural Fiber Composite

scholarly journals Effect of Alkaline Treatment on The Mechanical Properties of Pineapple Leaf Fiber Composite Material

2020 ◽  
Vol 2 (3) ◽  
pp. 43-50
Author(s):  
M Febriyan Baruna Putra ◽  
Delima Yanti Sari ◽  
Hendri Nurdin ◽  
Rodesri Mulyadi
Keyword(s):  
Mechanical Properties ◽  
Composite Material ◽  
Energy Efficient ◽  
Natural Fiber ◽  
Fiber Composite ◽  
Alkaline Treatment ◽  
Fiber Composite Material ◽  
Pineapple Leaf Fiber ◽  
Alternative Material ◽  
Leaf Fiber

Utilization of natural fiber waste, especially pineapple dau fiber, is a major concern and continues to be developed to utilize and optimize plantation waste as a material that is more environmentally friendly, energy efficient and inexpensive. The purpose of this study was to determine the effect of alkaline treatment on the mechanical properties of pineapple leaf fiber composite material as an appropriate alternative material. The method in this research is the experimental method, where the research was carried out by giving variations in the percentage of alkaline 10% and 20%. The results of the research on the composite material of pineapple leaf fiber using tensile testing showed that giving alkaline treatment with a percentage of 20% made the fiber stronger but brittle. In addition, the orientation direction and immersion time also affect the tensile strength of the fibers. Pemanfaatan limbah serat alam khususnya serat dau nanas menjadi bahan alternatif menjadi perhatian utama serta terus dikembangkan guna memanfaatkan dan mengoptimalkan limbah perkebunan sebagai bahan material yang lebih ramah lingkungan, hemat energi, dan murah. Tujuan penelitian ini untuk mengetahui pengaruh perlakuan alkali terhadap sifat mekanik material komposit serat daun nanas sebagai bahan alternatif tepat guna. Metode dalam penelitian ini yaitu metode eksperimen, dimana penelitian dilakukan dengan pemberian variasi persentase alkali 10% dan 20%. Hasil penelitian material komposit serat daun nanas dengan menggunakan pengujian tarik menunjukkan bahwa pemberian perlakuan alkali dengan persentase 20% membuat serat menjadi lebih kuat namun bersifat getas. Selain itu, arah orientasi dan waktu perendaman juga mempengaruhi kekuatan tarik serat.

Electrical conductivity identification of a carbon fiber composite material plate using a rotating magnetic field and multi-coil eddy current sensor

2018 ◽  
Vol 83 (2) ◽  
pp. 20901 ◽  
Author(s):  
Ahmed Chaouki Lahrech ◽  
Bachir Abdelhadi ◽  
Mouloud Feliachi ◽  
Abdelhalim Zaoui ◽  
Mohammed Naїdjate
Keyword(s):  
Magnetic Field ◽  
Neural Networks ◽  
Electrical Conductivity ◽  
Composite Material ◽  
Carbon Fiber ◽  
Fiber Composite ◽  
Rotating Magnetic Field ◽  
Current Sensor ◽  
Carbon Fiber Composite ◽  
Fiber Composite Material

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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