Nehru Chevanan

Bulk density and compaction behavior of knife mill chopped switchgrass, wheat straw, and corn stover.

Bulk density of comminuted biomass significantly increased by vibration during handling and transportation, and by normal pressure during storage. Compaction characteristics affecting the bulk density of switchgrass, wheat straw, and corn stover chopped in a knife mill at different operating conditions and using four different classifying screens were studied. Mean loose-filled bulk densities were 67.5+/-18.4 kg/m(3) for switchgrass, 36.1+/-8.6 kg/m(3) for wheat straw, and 52.1+/-10.8 kg/m(3) for corn stover. Mean tapped bulk densities were 81.8+/-26.2 kg/m(3) for switchgrass, 42.8+/-11.7 kg/m(3) for wheat straw, and 58.9+/-13.4 kg/m(3) for corn stover. Percentage changes in compressibility due to variation in particle size obtained from a knife mill ranged from 64.3 to 173.6 for chopped switchgrass, 22.2-51.5 for chopped wheat straw and 42.1-117.7 for chopped corn stover within the tested consolidation pressure range of 5-120 kPa. Pressure and volume relationship of chopped biomass during compression with application of normal pressure can be characterized by the Walker model and Kawakita and Ludde model. Parameter of Walker model was correlated to the compressibility with Pearson correlation coefficient greater than 0.9. Relationship between volume reduction in chopped biomass with respect to number of tappings studied using Sones model indicated that infinite compressibility was highest for chopped switchgrass followed by chopped wheat straw and corn stover. Degree of difficulty in packing measured using the parameters of Sones model indicated that the chopped wheat straw particles compacted very rapidly by tapping compared to chopped switchgrass and corn stover. These results are very useful for solving obstacles in handling bulk biomass supply logistics issues for a biorefinery.

Effect of DDGS, Moisture Content, and Screw Speed on Physical Properties of Extrudates in Single-Screw Extrusion

ABSTRACT Three isocaloric (3.5 kcal/g) ingredient blends containing 20, 30, and 40% (wb) distillers dried grains with solubles (DDGS) along with soy flour, corn flour, fish meal, and mineral and vitamin mix, with net protein adjusted to 28% (wb) for all blends, were extruded in a single-screw laboratory-scale extruder at screw speeds of 100, 130, and 160 rpm, and 15, 20, and 25% (wb) moisture content. Increasing DDGS content from 20 to 40% resulted in a 37.1, 3.1, and 8.4% decrease in extrudate durability, specific gravity, and porosity, respectively, but a 7.5% increase in bulk density. Increasing screw speed from 100 to 160 rpm resulted in a 20.3 and 8.8% increase in durability and porosity, respectively, but a 12.9% decrease in bulk density. On the other hand, increasing the moisture content from 15 to 25% (wb) resulted in a 28.2% increase in durability, but an 8.3 and 8.5% decrease in specific gravity and porosity, respectively. Furthermore, increasing the screw speed and moisture content of the blend...

Direct measures of mechanical energy for knife mill size reduction of switchgrass, wheat straw, and corn stover.

Lengthy straw/stalk of biomass may not be directly fed into grinders such as hammer mills and disc refiners. Hence, biomass needs to be preprocessed using coarse grinders like a knife mill to allow for efficient feeding in refiner mills without bridging and choking. Size reduction mechanical energy was directly measured for switchgrass (Panicum virgatum L.), wheat straw (Triticum aestivum L.), and corn stover (Zea mays L.) in an instrumented knife mill. Direct power inputs were determined for different knife mill screen openings from 12.7 to 50.8 mm, rotor speeds between 250 and 500 rpm, and mass feed rates from 1 to 11 kg/min. Overall accuracy of power measurement was calculated to be +/-0.003 kW. Total specific energy (kWh/Mg) was defined as size reduction energy to operate mill with biomass. Effective specific energy was defined as the energy that can be assumed to reach the biomass. The difference is parasitic or no-load energy of mill. Total specific energy for switchgrass, wheat straw, and corn stover chopping increased with knife mill speed, whereas, effective specific energy decreased marginally for switchgrass and increased for wheat straw and corn stover. Total and effective specific energy decreased with an increase in screen size for all the crops studied. Total specific energy decreased with increase in mass feed rate, but effective specific energy increased for switchgrass and wheat straw, and decreased for corn stover at increased feed rate. For knife mill screen size of 25.4 mm and optimum speed of 250 rpm, optimum feed rates were 7.6, 5.8, and 4.5 kg/min for switchgrass, wheat straw, and corn stover, respectively, and the corresponding total specific energies were 7.57, 10.53, and 8.87 kWh/Mg and effective specific energies were 1.27, 1.50, and 0.24 kWh/Mg for switchgrass, wheat straw, and corn stover, respectively. Energy utilization ratios were calculated as 16.8%, 14.3%, and 2.8% for switchgrass, wheat straw, and corn stover, respectively. These data will be useful for preparing the feed material for subsequent fine grinding operations and designing new mills.

Neural Network and Regression Modeling of Extrusion Processing Parameters and Properties of Extrudates containing DDGS

Two extrusion experiments using a single screw extruder were conducted with an ingredient blend containing 40% DDGS, along with soy flour, corn flour, fish meal, vitamin mix, and mineral mix, with the net protein content adjusted to 28%. The variables controlled in the first experiment included 7 levels of die size, 3 levels of moisture content, 3 levels of temperature gradient in the barrel, and one screw speed. The variables altered in the second experiment included 3 levels of moisture content, 3 levels of temperature gradient in the barrel, 5 levels of screw speed, and one die size. Regression models and Neural Network (NN) models were then developed using the data pooled from the two experiments to predict extrudate properties and extrusion processing parameters. In general, both regression and NN models predicted the extrusion processing parameters with better accuracy than the extrudate properties. With the regression modeling, even though increasing the number of input variables from 3 to 6 resulted in better R2 values, there was no significant decrease in the coefficient of variation between the measured and predicted variables. On the other hand, the NN models developed with 3 input variables (L/D ratio of die, moisture content and temperature gradient) predicted the extrusion processing parameters and extrudate properties with better accuracy than the regression models developed with the same 3 input variables. Furthermore, increasing the number of input variables resulted in better accuracy of prediction for both extrudate properties and extrusion processing parameters, and the standard error and coefficient of variation were also found to decrease. The highest accuracy of prediction was observed for the NN models developed to predict the extrusion processing parameters with 6 input variables (D, L, L/D ratio of die, moisture content, temperature gradient and screw speed). Because of its ability to account for variation, NN modeling has great potential for developing robust models for extrusion processing.

Comminution Properties of Biomass in Hammer Mill and its Particle Size Characterization

Biomass particle size impacts handling, storage, conversion, and dust control systems. Size reduction mechanical energy was directly measured for switchgrass (Panicum virgatum L.), wheat straw (Triticum aestivum L.), and corn stover (Zea mays L.) in an instrumented hammer mill. Direct power inputs were determined for different operating speeds from 2000 to 3600 rpm for 3.175 mm integral classifying screen and mass input rate of 2.5 kg/min with 90o and 30o edges on hammers. Overall accuracy of power measurement was calculated to be ±0.003 kW. Particle sizes were examined for hammer mill operating factors using ISO sieve sizes from 4.75 to 0.02 mm in conjunction with Ro-tap sieve analyzer. A total specific energy (kWh/Mg) was defined as size reduction energy expended for a particular mill design. Effective specific energy was defined as the energy that can be assumed to reach the biomass. The difference is parasitic or idle energy. Total specific energy for switchgrass, wheat straw, and corn stover grinding increased with hammer mill speed for both 90o and 30o hammers. Effective specific energy decreased marginally for switchgrass and considerably for wheat straw and it increased for corn stover with 90o hammers. However, effective specific energy increased with speed to certain extent and then decreased for 30o hammers. Rosin-Rammler equation fitted the switchgrass, wheat straw, and corn stover grind size distribution data with R2 > 0.995. Mass relative span was greater than 1, which indicated a wide distribution of particle sizes. Uniformity coefficient was less than 4.0 for wheat straw, which indicated uniform mix of particles, and it was about 4.0 for switchgrass and corn stover, which indicated a large assortment of particles and also represented a well graded particle size distribution. Geometric mean diameter had strong correlations with Rosin-Rammler size parameter, median diameter, and effective size. Distribution related parameters, namely, mass relative span, Rosin-Rammler distribution parameter, inclusive graphic skewness, graphic kurtosis, uniformity index, uniformity coefficient, coefficient of gradation and distribution geometric standard deviation had strong correlation among themselves and a weak correlation with mill speed. Results of this extensive analysis of specific energy and particle sizes can be applied to selection of hammer mill operating parameters to produce a particular size of switchgrass, wheat straw, and corn stover grind.

Neural Network and Regression Modeling of Extrusion Processing Parameters and Properties of Extrudates Containing DDGS

Two sets of experiments using a single-screw extruder were conducted with an ingredient blend containing 40% DDGS (distillers dried grains with solubles), along with soy flour, corn flour, fish meal, vitamin mix, and mineral mix, with the net protein content adjusted to 28%. The variables controlled in the first experiment included seven levels of die size, three levels of moisture content, three levels of temperature gradient in the barrel, and one screw speed. The variables altered in the second experiment included three levels of moisture content, three levels of temperature gradient in the barrel, five levels of screw speed, and one die size. Regression models and neural network (NN) models were then developed using the data pooled from the two experiments to predict extrudate properties and extrusion processing parameters. In general, both regression and NN models predicted the extrusion processing parameters with better accuracy than the extrudate properties. Similarly, lower R2 values for the regression results corresponded to lower R2 values in the NN modeling. The regression models predicted the extrusion processing parameters using three and six input variables with R2 values of 0.56 to 0.97 and 0.75 to 0.97, respectively. The NN models predicted the extrusion processing parameters using three, five, and six input variables with R2 values (between measured and predicted values) of 0.819 to 0.984, 0.860 to 0.988, and 0.901 to 0.991, respectively. With the regression modeling, even though increasing the number of input variables from three to six resulted in better R2 values, there was no decrease in the coefficient of variation (CV) between the measured and predicted variables. On the other hand, the NN models developed with six input variables resulted in more accurate predictions with reduced CV and standard error. Because of its ability to produce accurate result with reduced variation and standard error, NN modeling has greater potential for developing robust models for extrusion processing.

LOOSE-FILLED AND TAPPED DENSITIES OF CHOPPED SWITCHGRASS, CORN STOVER AND WHEAT STRAW

Bulk density is one of the important engineering property of biomass having significant impact on the supply logistics and processing in ethanol production facilities using lignocellulosic materials. Bulk density of most of the comminuted biomass significantly increased by tapping. Switchgrass, wheat straw and corn stover were chopped in a knife mill at different operating conditions including four different screens having 50, 25, 19, 12 mm diameter. Mean loose-filled bulk densities were 67.5 ± 18.4 kg/m3 for switchgrass, 36.1 ± 8.6 kg/m3 for wheat straw, and 52.1± 10.8 kg/m3 for corn stover. Mean tapped bulk densities were 81.8 ± 26.2 kg/m3 for switchgrass, 42.8 ± 11.7 kg/m3 for wheat straw, and 58.9 ± 13.4 kg/m3 for corn stover. The maximum volume reduction ratio observed for switchgrass, wheat straw and corn stover was 0.159, 0.165, and 0.154, respectively for fine-chopped samples and 0.107, 0.117, and 0.098, respectively for coarse-chopped samples. By tapping, the infinite compressibility was highest for chopped switchgrass followed by chopped wheat straw and corn stover as indicated by the ‘a’ values in Sone’s model. Degree of difficulty in packing was minimum for chopped wheat straw followed by chopped switchgrass and corn stover. This indicated that the chopped wheat straw particle compacts very rapidly by tapping compared to chopped switchgrass and corn stover. Hausner ratio, a measure of internal friction, determined after 50 taps ranged from 1.114 to 1.321 for chopped switchgrass, 1.105 to 1.309 for chopped wheat straw and 1.060 to 1.239 for chopped corn stover.

Physical Properties of Extrudates Containing Distillers Grains Extruded in a Twin Screw Extruder

Extrusion trials were conducted with varying levels of DDGS along with soy flour, corn flour, fish meal, vitamin mix, mineral mix and net protein content adjusted to 28% in a Wenger TX-52 twin screw extruder. The properties of extrudates obtained with experiments conducted in full factorial design with 3 levels of DDGS content, 2 levels of moisture content and 2 levels of screw speed were studied. Increasing the DDGS content from 20% to 60%, resulted in 36.7% decrease in the radial expansion leading to 159%, 61.4% increase in the unit density and bulk density of the extrudates. Increasing the DDGS content resulted in significant increase in the water absorption index (WAI) and significant decrease in the water solubility index (WSI) of the extrudates. Changing the screw speed and moisture content had no effect on the radial expansion ratio, but resulted in significant difference in the bulk density of the extrudates and might be due to longitudinal expansion. Even though changing the moisture content and screw speed had no effect on the WSI of the extrudates, significant difference in the WAI of the extrudates was observed. Color changes in the extrudates was mostly due to color changes in the ingredient components and moisture content of the extrudates and screw speed had least effect on the color of the extrudates.

Flowability Parameters for Chopped Switchgrass, Wheat straw and Corn stover

A direct shear cell to measure the shear strength and flow properties of chopped switchgrass, wheat straw and corn stover was designed, fabricated, and tested. The shear strength measured at various normal stresses was found to be significantly different. Shear strength for all three chopped biomass types measured at a particular normal stress was not significantly different. The R2 value of the experimental yield loci was found to be more than 0.99 for all three chopped biomass, indicating that the chopped biomass followed the Mohr-Coulomb theory for critical state of friction. The experimental yield loci developed at a preconsolidation pressure of 4.92 kPa showed that the cohesive strength of chopped corn stover was the highest. The effect of changing the particle size had a profound effect on the angle of internal friction of chopped switchgrass compared to chopped wheat straw and chopped corn stover. The friction coefficients measured at different normal pressures were always more than 1 for chopped corn stover. But for chopped switchgrass and wheat straw, the friction coefficient was found to be less than 1 for a normal stress of above 2.55 kPa. These results indicate that changing the particle size of chopped biomass will have a profound effect on the flowability of chopped switchgrass compared to chopped wheat straw and corn stover. These results are useful for development of handling, storage and transportation equipments for biomass in biorefineries.