Multi-objective optimization and modeling of a natural fiber hybrid reinforced composite (P_xG_yE^z) for wind turbine blade development using grey relational analysis and regression analysis

Abstract

Due to the increasing demand for clean and sustainable energy, wind turbine technology has also witnessed significant developments in terms of its output capacity which is proportional to its size (length of wind turbine blades). The only limitation to this scaling is the availability of applicable materials with expected strength and low weight which can support a longer span wind turbine blade. Although studies have been carried out on alternate materials for the development of wind turbine blades, the use of Grey Relational Analysis for the optimization of natural fiber-reinforced composites for this application is rare. Also, pineapple leaf fiber, having considerable mechanical properties and low density has not been optimally considered as reinforcement in this regard. This is a robust study concerned with developing more eco-friendly materials for application in the manufacture of wind turbine blades. In this study, a material P_xG_yE^z, a natural fiber/synthetic fiber polymer composite was developed and optimized based on the major criteria for selecting materials for wind turbine blades which are high tensile strength, high flexural strength, and low density. Grey relational analysis coupled with the Taguchi robust optimization technique was used for the optimization process and statistical analysis was employed to know the percentage contribution of each of the variable parameters (PALF volume percentage, glass fiber volume percentage, and fiber length) to the grey relational grades. The material P₁₀G₂₀E¹⁵ was the optimum having a grey relational grade of 0.7977 at experimentation and tensile strength of 95.3144 MPa, a flexural strength of 92.818 MPa, and a density of 1.3274 g/cm³. SEM analysis showed microstructural formations that explained the mechanical and physical behavior of the optimized hybrid composite. Simulation of an NREL 5 MW wind turbine blade developed with the optimized material P₁₀G₂₀E¹⁵ proved reliable for service with a 64% reduction in weight.

Graphical Abstract

Keywords:

• Natural fibers
• polymer matrix composites
• optimization
• grey relational analysis
• Taguchi
• wind turbine blades

Disclosure statement

On behalf of all authors, the corresponding author states that there is no conflict of interest.

Acknowledgment

The strong contribution of the Materials Research Laboratory, Steelagon Engineering Limited (MRL-SEL) (financially and intellectually) to this study under the GreEnergy Program is greatly appreciated.

Additional information

Funding

This work was partly funded by the Steelagon Engineering Limited GreEnergy Program.

Notes on contributors

Bassey Okon Samuel

Bassey Okon Samuel received his Bachelor of Engineering with Honors from the Department of Mechanical Engineering, Ahmadu Bello University Zaria where he also obtained his post-graduate degree. He is currently the principal investigator with the Material Research Laboratory at Steelagon Engineering Limited (MRL-SEL). His expertise includes Composite Materials, Nanomaterials, Renewable Energy, Computational Materials, Theoretical And Computational Modeling, Artificial Intelligence/Machine Learning, Optimization, System Design, Production Management, Steel Design, and Project Conceptualization. He serves as a first and supporting consultant to numerous projects in the energy, construction, and manufacturing industry. Bassey has authored and coauthored numerous scholarly articles in high-impact journals.

Malachy Sumaila

Sumaila Malachy is a Professor at the Department of Mechanical Engineering, Ahmadu Bello University, Zaria. An MIT research fellow with expertise in Materials and Production, Professor Sumaila Malachy has authored numerous highly valuable research articles that have been published in various national and international journals of repute. He graduated from the University of Maiduguri where he obtained his Bachelor of Engineering and the University of Benin where he obtained his Ph.D. He is the author of various outstanding research publications. He is also a recipient of various grants.

Bashar Dan-Asabe

Bashar Dan-Asabe is an Associate Professor with the Department of Mechanical Engineering, Ahmadu Bello University, Zaria. He obtained his first degree (B. Eng.) in Mechanical Engineering from Ahmadu Bello University, Zaria, and later obtained his MSc in Mechanical Engineering from the University of Hertfordshire, United Kingdom. He was awarded a Ph.D. from Ahmadu Bello University, Zaria, Nigeria. He is a COREN registered Engineer with an extensive research profile. Bashar Dan-Asabe has more than 34 publications comprising 20 journal papers and 14 conference proceedings. He is an expert in Composite Material Development & Characterization, Corrosion inhibition, Statistical Modeling, and Machine Design and Stress Analysis.