Ultrasonic vibration-assisted pelleting of wheat straw: a predictive model for energy consumption using response surface methodology

Optimisation of biomass catalytic depolymerisation conditions by using response surface methodology

The aim of this study is to present the optimum operating conditions for reducing energy consumption in the process of obtaining bio-oil from the mixture of sawdust, waste lubricating oil, lime, and commercial catalyst. In the study where the catalytic pressureless depolymerisation (also called Katalytische Drucklose Verölung - KDV) was applied, the operating conditions were analysed with response surface methodology. According to the analysis of variance results, a mathematical model was obtained for specific product yield (bio-oil amount/energy consumption g kW_e^-1). Effects of temperature (260°C-290°C), catalyst rate (1-2 wt.%) and reaction time (0.5-1 h) were investigated. The optimum conditions for the three independent variables (temperature, catalyst rate, reaction time) were 279 ± 2°C, 2 wt.% and 0.5 h, respectively. Maximum specific product yield was obtained as 970.17 g kW_e^-1. While the reaction time was the most effective regarding the amount of bio-oil obtained at 1 kW_e energy consumption, the temperature was found to be the least effective. In addition to these, bio-oil obtained under optimum conditions were characterised and compared with standard diesel specifications.

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

Pelletization is a significant approach for the efficient utilization of biomass energy. Sunflower seed husk is a common solid waste in the process of oil production. The novelty of this study was to determine the parameters during production of a novel pellet made from sunflower seed husk. The energy consumption (W) and physical properties (bulk density (BD) and mechanical durability (DU)) of the novel pellet were evaluated and optimized at the laboratory by using a pelletizer and response surface methodology (RSM) under a controlled moisture content (4%–14%), compression pressure (100–200 MPa), and die temperature (70–170 °C). The results show that the variables of temperature, pressure, and moisture content of raw material are positively correlated with BD and DU. Increasing the temperature and moisture content of raw materials can effectively reduce W, while increasing the pressure has an adverse effect on W. The optimum conditions of temperature (150 °C), pressure (180 MPa), and moisture content (12%) led to a BD of 1117.44 kg/m3, DU of 98.8%, and W of 25.3 kJ/kg in the lab. Overall, although the nitrogen content was slightly high, the novel manufactured pellets had excellent performance based on ISO 17225 (International Organization for Standardization of 17225, Geneva, Switzerland, 2016). Thus, sunflower seed husk could be considered as a potential feedstock for biomass pelletization.

Ultrasonic vibration-assisted (UV-A) pelleting of wheat straw: a constitutive model for pellet density

Ultrasonic vibration-assisted (UV-A) pelleting can increase cellulosic biomass density and reduce biomass handling and transportation costs in cellulosic biofuel manufacturing. Effects of input variables on pellet density in UV-A pelleting have been studied experimentally. However, there are no reports on modeling of pellet density in UV-A pelleting. Furthermore, in the literature, most reported density models in other pelleting methods of biomass are empirical. This paper presents a constitutive model to predict pellet density in UV-A pelleting. With the predictive model, relations between input variables (ultrasonic power and pelleting pressure) and pellet density are predicted. The predicted relations are compared with those determined experimentally in the literature. Model predictions agree well with reported experimental results.