Ultrasonic-Assisted Pelleting of Sorghum Stalk: Predictive Models for Pellet Density and Durability Using Multiple Response Surface Methodology

Abstract

In the field of renewable energy, feedstock such as cellulosic biomass has been proposed as a renewable source of fuel to produce energy. However, the use of raw biomass as feedstock causes high costs in handling, transportation, and storage. Compressing raw cellulosic biomass into pellets significantly increases the density and durability of cellulosic biomass, reducing the transportation and handling costs of feedstock. To ensure high pellet quality, high pellet density and durability are desired during a compressing process. In this study, ultrasonic vibration-assisted (UV-A) pelleting, as a novel pelleting method, was applied to measure pellet density and durability during experiments. Response surface methodology (RSM) was employed to investigate the effects of pelleting time, ultrasonic power, and pelleting pressure on the pellet density and pellet durability. The model was validated by comparing the predictive results with experimental data and demonstrated a good predictive ability (R 2 > 0.95). By employing a Derringer and Suich's desirability function, our results suggest that the optimal pellet density and durability are 1239 kg/m 3 and 93%, respectively, when the pelleting time was set to 44 s, the ultrasonic power was set to 50%, and pressure was set to 42 psi (289,580 Pa).

Pelletization of Sunflower Seed Husks: Evaluating and Optimizing Energy Consumption and Physical Properties by Response Surface Methodology (RSM)

“…In recent years, some novel pellets made from different biomass residues such as beech sawdust [11], Scenedesmus microalgae [12], canola hull mixed meal [6], corncobs [13,14], wheat straw [15], and coir fibers [16] have been investigated, and those studies focused on how the characteristics and quality of the pellets (bulk density, mechanical durability, energy consumption, and net calorific value [17,18]) can be influenced by various factors related to the raw material (chemical composition, moisture content [16], and production process (pressure, temperature [14]). Response surface methodology (RSM) is one of the most popular methods for parameter optimization of pelletization and has been extensively studied [19,20]. RSM is a mathematical modeling tool for predicting the output relationship under multiple input parameters.…”

“…RSM is a mathematical modeling tool for predicting the output relationship under multiple input parameters. It is an optimization method widely used in the engineering field that provides an approximation technique for optimizing the problem and other subroutines [19]. RSM provides a function called the response surface.…”

“…The response surface is a function of an approximate result that predicts the unknown output value of any suitable input [20]. Zhang et al [19] employed RSM to investigate the effects of pelletization time and pressure on straw pellet density and durability by comparing predictive results with experimental data of single pelletization and demonstrated good predictive ability (R 2 > 0.95). Therefore, the study of the effects of these variables on the quality of the pellets is important, and the RSM method can offer reliable solutions with regard to the development of novel pellet fuel.…”

The Effect of Urea Pretreatment Combined with Ultrasonic Vibration-Assisted Pelleting on Pellet Solid Density and Durability

“…Under the context of carbon peak and carbon neutrality, the increasing demand for low-cost, clean, and renewable energy necessitates a comprehensive utilization of agricultural residues, which are associated with high costs in handling, transportation, and storage [5]. Pelleting, a process that compresses biomass into uniform pellets of consistent shape and size, has been shown to significantly increase the density of cellulosic biomass [6][7][8]. The solid density of biomass could reach 1200 kg/m 3 [9].…”

Effect of vibration frequency on the vibration-assisted densification for alfalfa

“…Song et al (2015) showed that the pelleting density would increase with the increase of the ultrasonic power in the ultrasonic-assisted pelleting process. Zhang et al (2018) put forward predictive models for pellet density and durability in ultrasonic vibration-assisted pelleting using multiple response surface methodology. In order to reduce energy consumption, Song et al (2013Song et al ( , 2014 studied the effect of sieve size, pelleting pressure, ultrasonic power, and pellet weight on energy consumption, and proposed a predictive model for energy consumption in ultrasonic vibration-assisted pelleting of wheat straw using response surface methodology.…”