Sieve analysis of biomass: accurate method for determination of particle size distribution
2016
Chaloupkova, V., Czech Univ. of Life Sciences, Prague (Czech Republic) | Ivanova, T., Czech Univ. of Life Sciences, Prague (Czech Republic) | Havrland, B., Czech Univ. of Life Sciences, Prague (Czech Republic)
Increasing interest in biofuels made of agricultural organic waste and energy crops is accompanied by general need for better and more comprehensive knowledge of biomass material properties. Particle size and particle size distribution (PSD) are important physical characteristics playing essential roles in flow ability, bulk density, compressibility of bulk solid material and durability of densified products. Sieve analysis is considered as a traditional and standard method to assess dimensional and morphological features of particulate materials. The aim of the present paper was to determine PSD of different grinded biomass sources such as industrial hemp (fibrous annual plant), miscanthus (perspective perennial energy crop) and pine sawdust (wooden biomass) via the sieve analysis. Horizontal vibrating sieve shaker comprising seven sieves with opening sizes of 0.63, 1.5, 3.15, 4.5, 6.7, 8 and 10 mm were used for the analysis of the biomass materials with initial fractional size of 12 mm. Data were processed using MS Excel and the obtained results were tabulated and graphically plotted. Size distribution of pine sawdust particles was quite uniform; the particles’ spherical shape decreased screen opening size resulted in really decreased particle sizes. Contrarily, analysis of hemp and miscanthus did not yield absolutely reliable results of real PSD. In case of hemp it was due to its fibrous nature – more than half of the material stayed on the first sieve (i.e. 10 mm); in case of miscanthus it was caused by needle-like shape of its particles, since this method did not obviate a “falling-through” effect of longer particles through smaller sieve apertures. Due to these limitations, utilization of more accurate method for determination of PSD – machine vision and image analysis is discussed. Even though the method of the sieve analysis was not so accurate and consistent, the results generally contributed to better knowledge of input material for solid biofuel production.
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