Response Surface Methodology for the Synthesis and Characterization of Bio-Oil Extracted from Biomass Waste and Upgradation Using the Rice Husk Ash Catalyst

Optimization of Operational Parameters Using Artificial Neural Network and Support Vector Machine for Bio-oil Extracted from Rice Husk

Bio-oil production from rice husk, an abundant agricultural residue, has gained significant attention as a sustainable and renewable energy source. The current research aims to employ artificial neural network (ANN) and support vector machine (SVM) modeling techniques for the optimization of operating parameters for bio-oil extracted from rice husk ash (RHA) through pyrolysis. ANN and SVM methods are employed to model and optimize the operational conditions, including temperature, heating rate, and feedstock particle size, to enhance the yield and quality of bio-oil. Additionally, ANN modeling is utilized to create a predictive model for bio-oil properties, allowing for the efficient optimization of pyrolysis conditions. This research provides valuable insights into the production and properties of bio-oil from RHA. By harnessing the capabilities of ANN and SVM, this research not only aids in understanding the intricate relationships between process variables and bio-oil properties but also provides a means to systematically enhance the production process. The predictive results obtained from the ANN were found to be good when compared with the SVM. Several models with different numbers of neurons have been trained with different transfer functions. R values for the training, validation, and test phases are around 1.0, i.e., 0.9981, 0.9976, and 0.9978, respectively. The overall R-value was 0.9960 for the proposed network. The findings were considered acceptable, as the overall R-value was close to 1.0. The optimized operational parameters contribute to the efficient conversion of RHA into bio-oil, thereby promoting the use of this sustainable resource for renewable energy production. This approach aligns with the growing emphasis on reducing the environmental impact of traditional fossil fuels and advancing the utilization of alternative and environmentally friendly energy sources.

Upgrading Pyrolysis Bio-Oil through Esterification Process and Assessing the Performance and Emissions of Diesel-Biodiesel-Esterified Pyrolysis Bio-Oil Blends in Direct Injection Diesel Engines

This research aimed to evaluate the performance and emissions of direct injection diesel engines using blends of diesel-biodiesel-esterified pyrolysis bio-oil (D-B-EPB). The pyrolysis process was employed to produce pyrolysis bio-oil (PBO) from solid biomass obtained from fresh palm fruits. Furthermore, a simple and effective esterification process was used to upgrade the PBO. The methyl ester (ME) purity of EPB production was studied to optimize three independent variables: methanol (14.8-65.2 wt %), sulfuric acid (1.6-18.4 wt %), and reaction time (16-84 min) using the response surface methodology. The actual experiment yielded a ME purity of 72.73 wt % under the recommended conditions of 40.3 wt % methanol, 13.0 wt % sulfuric acid, 50 min reaction time, 60 °C reaction temperature, and 300 rpm stirrer speed. Additionally, the stability and phase behaviors of D-B-EPB blends were analyzed by using a ternary phase diagram to determine the potential blending proportion. The results revealed that a fuel blend consisting of 30 wt % diesel, 60 wt % biodiesel, and 10 wt % EPB (D30B60EPB10) met the density and viscosity requirements of diesel standards. This D30B60EPB10 blend was subjected to performance and emission tests in diesel engines at various speeds ranging from 1100 to 2300 rpm and different engine loads of 25, 50, and 75%. In terms of performance analysis, the brake thermal efficiencies of biodiesel and D30B60EPB10 were 7.19 and 3.88% higher than that of diesel, respectively. However, the brake-specific fuel consumption of the D30B60EPB10 blend was 6.60% higher than that of diesel due to its higher density and viscosity and lower heating value compared with that of diesel. In the emission analysis, the D30B60EPB10 blend exhibited performance comparable to diesel while being more environmentally friendly, reducing carbon monoxide, carbon dioxide, nitrogen oxide, and smoke opacity by 8.73, 30.13, 37.55, and 59.75%, respectively. The results of this study suggest that the D-B-EPB blend has the potential to serve as a viable biofuel option, reducing the proportion of diesel in blended fuel and benefiting farmers and rural communities..