Structural material identification of tobacco natural fibre composite panel (TNFCP) using stochastic inverse method

The application of natural fibre composites in structural engineering is significantly explored due to their sustainability, biodegradability, and lower environmental impact compared to synthetic fibres. Understandably, the natural composites are made from plant-based fibres and with combined polymer matrices. The natural composite is increasingly used as an alternative for lightweight and eco-friendly materials in various application industries such as automotive, aerospace, and construction industries. However, natural fibre composites are inherently heterogeneous in nature and critically influence the dynamic characteristics of the structure due to the type of fibres, the matrix material, and the fibre orientation itself. The complex interaction between these parameters of concern results in a challenge to accurately predict the mechanical properties of the composite due to the variability and uncertainty of the composite. This study proposes the structural material identification method of composite materials using a stochastic inverse method that emphasis on the uncertainty and variability of the natural tobacco fibre composite randomly generated using a Latin hypercube sampling (LHS) scheme based on an initial finite element model and experimental results of natural tobacco fibre composite. The stochastic inverse method shows a good improvement from 35.05 per cent of total error to 3.12 per cent. The proposed framework demonstrates the ability to accurately predict a range of possible material property values at a given confidence level, which can be used for structural engineering applications.