General practices to enhance bast fiber composite properties for state of art applications – a review

Composite materials are revolutionizing to realize the demanding needs of aeronautical, automobile, construction, chemical, and biomedical applications. The natural fiber composite is chosen as one of the best choices among composites due to its sustainable goods like eco-friendly nature, better properties and Greenhouse gas (GHG) balance. Furthermore, the bast fiber composites are identified as promising industrial composites based on the availability, strength-to-weight ratio, manufacturing ease, and economics for commercialization. However, product quality and production volume significantly influence commercial adoption of the bast fiber composites. Especially the product quality primarily suffer due to climatic conditions, damage while harvesting, extraction method, retting issues, and extraction location. Consequently, this review aims to provide an overview of the bast fibers & their composites, properties enhancement techniques, overall mechanical behaviours and thermal stability with suitable applications.

An Unconventional Approach for Analyzing the Mechanical Properties of Natural Fiber Composite Using Convolutional Neural Network

Over the past few years, natural fiber composites have been a strategy of rapid growth. The computational methods have become a significant tool for many researchers to design and analyze the mechanical properties of these composites. The mechanical properties such as rigidity, effects, bending, and tensile testing are carried out on natural fiber composites. The natural fiber composites were modeled by using some of the computation techniques. The developed convolutional neural network (CNN) is used to accurately predict the mechanical properties of these composites. The ground-truth information is used for the training process attained from the finite element analyses below the plane stress statement. After completion of the training process, the developed design is authorized using the invisible data through the training. The optimum microstructural model is identified by a developed model embedded with a genetic algorithm (GA) optimizer. The optimizer converges to conformations with highly enhanced properties. The GA optimizer is used to improve the mechanical properties to have the soft elements in the area adjacent to the tip of the crack.

Fiber length – the persuadable factor in making natural fiber composite: a review

Purpose The study aims to review the literatures on the effect of fiber length on the mechanical response of natural fiber composite will help the researchers to know about the perspective of the various natural fibers in making of composite concerning fiber length. The review summarized the work of the other researchers, thereby unambiguously précised suitability of a specific natural fiber for a matrix in use. Thus, one can identify the use of the same fibers–matrix combination to obtain composites with different properties with the control of fiber/matrix interface. Design/methodology/approach The review work proposes a new kind of diagrammatic representation that expresses the influence of fiber length. This work has not been explored before in this specific format. The chronology of work may help to select natural fibers for use in composites for a specific matrix. Findings The length of the fiber perception in terms of “critical” length decides the need for pre-treatment process of natural fiber to improve shear stress at the interface for various matrices. Originality/value The current review paper attempts to shed light on the association between the fiber length of natural fiber and the mechanical response of natural fiber composite. Moreover, it probes the concepts of critical fiber length as a persuadable factor.