![](/ii/tfec2022.jpg)
ISSN Online: 2379-1748
7th Thermal and Fluids Engineering Conference (TFEC)
SJR:
0.152
SNIP:
0.14
CiteScore™::
0.5
Indexed in
CHARACTERIZATION METHODS FOR BIOMASS MATERIALS AND OPTIMIZING HEAT TRANSFER BY USING GENETIC ALGORITHMS
Abstract
This research shows how agricultural waste products can be effectively used as naturally sustainable alternatives to insulation materials. Barley seeds and oak leaves are collected from nature and crashed into powders whose particle size distribution is determined by a sand shaker and microscopy images. The bulk density of the biomass powders is measured by using a density cup. Moisture examinations are performed by
using a relative humidity meter device. The angle of repose and the angle of internal friction are calculated to distinguish the flow behavior of the powders. The biomass powder reinforced composites are manufactured in varying weight ratios. Weight ratios of 10% and 20% are used for oak leaf powders and 10%, 20% and 30% are used for barley grain powders. Density of composite materials are measured with a density analyzer. The thermal conductivity was measured using the transient plane source technique implemented in the TPS 2500S Thermal Constants Analyzer. The properties of composites are compared to those of commercial insulation materials. The properties measured are found to be similar to those of traditional insulation materials such as bakelite, plaster board, anthracite coal, fluorelastomer, neoprene rubber and diatomaceous earth. Furthermore, a numerical optimization framework based on Genetic Algorithms (GA) is discussed to
systematically alter geometric parameters with the goal of maximizing the insulation capacity of a set design.