Optimisation of biomass catalytic depolymerisation conditions by using response surface methodology

Abstract

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 kWe−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 kWe−1. While the reaction time was the most effective regarding the amount of bio-oil obtained at 1 kWe 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.

Comparison of an Artificial Neural Network and a Response Surface Model during the Extraction of Selenium-Containing Protein from Selenium-Enriched Brassica napus L.

“…The effect of the interaction of four factors (A, B, C, and D) on Y was intuitively reflected by observing the steepness, contour density, and contour presentation shape of the 3D surface map [ 27 ]. Figure 4 shows that Y tended to increase and then decrease with increasing factor levels when A, B, C, and D interacted with any two factors.…”

“…A portion of the data were used to train the BP-ANN model and the remaining portion was used for testing and validating the model [ 27 ]. The relationship of the regression fit between the actual and predicted values are shown in Figure 5 .…”

Extraction of High-Purity Native State Gutta-Percha from Enzymatic Hydrolyzed Eucommia ulmoides Pericarps by Ultrasound Treatment and Surfactant Aqueous Phase Dispersion

“…To visualize the effect of the interaction between the ultrasonic factors on Y, the 3D surface charts were drawn (Figure 4) [18]. The steeper surface and the higher slope indicate a stronger influence of the interaction between two factors on gutta-percha purity [19]. It could be observed that the interaction between frequency (X 1 ) and temperature (X 4 ) and that between power (X 2 ) and temperature (X 4 ) had greater impacts on the removal of plant tissue fragments.…”