Abstract
Biomass is a renewable and sustainable green energy material. It is made up of lignin, cellulose, and hemicellulose with considerable amount of water, extractives, and inorganic chemical compounds. The use of biomass materials and other biogenic wastes for energy recovery represents an eco-friendly way. Biomass material selection is one of the most significant aspects for any energy conversion process, and it is a common outsourcing problem that includes material preparation, reactor performance, economic assessment, and calorific value of the products. Fuzzy systems can be quite useful in high-performance computing during the selection of biomass materials. In each engineering process, material selection is a crucial step since each material is having its own set of characteristics. This study presents the application of type-1 fuzzy set for the selection of suitable biomass material for yielding maximum bio-oil. This study focuses on seven locally available materials such as rice straw (M-1), sunflower shell (M-2), hardwood (M-3), wheat straw (M-4), sugarcane bagasse (M-5), corn cop (M-6), and palm shell (M-7). The study evaluated seven important properties of the materials such as lignin (P-1), cellulose (P-2), hemicellulose (P-3), volatile matter (P-4), fixed carbon (P-5), moisture content (P-6), and ash content (P-7). The findings demonstrated that sugarcane bagasse (M-5) is the best option for maximum bio-oil yield. Furthermore, the potential of nanoscale catalysts in improving the yield of bio-oil through real-time experiments was studied. The findings of this work add to our understanding of the application of fuzzy-based systems for energy applications.
Highlights
In recent years, the use of biomass materials for the production of valuable chemicals and biofuels has gained popularity as a way to minimise emissions of greenhouse gases emitted by the combustion of fossil diesel fuels [1]
Biomass material selection is mainly concerned with the biomass to biofuel conversion techniques in order to yield the maximum biofuels such as crude bio-oil, char, and gas to fulfil the future energy needs
Cellulose is a linear long-chain polymer that encircles mostly crystalline structures with tiny amorphous regions. They are structured in fibrils and grouped together to form cellulose fibres, which are aware of the fibrous character of biomass cell walls
Summary
The use of biomass materials for the production of valuable chemicals and biofuels has gained popularity as a way to minimise emissions of greenhouse gases emitted by the combustion of fossil diesel fuels [1] It is an organic substance with a lot of chemical energy. The main idea behind this study is to evaluate the biomass materials in order to get higher quantity and rich biofuel by evaluating the yield parameters This can be attained with the aid of fuzzy logic and fuzzy inference systems, which have been shown to be useful tools. This research focused on the use of fuzzy AHP to select suitable biomass materials for thermochemical conversion processes, pyrolysis. The prediction is validated with experimental study conducted by using specified set of input through thermal as well as catalytic pyrolysis
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