Evaluation of engine performance and emission of <scp>African pear seed oil</scp> (<scp>APO</scp>) biodiesel and its prediction via multi‐input‐multi‐output artificial neural network (<scp>ANN</scp>) and sensitivity analysis

Neto

Biofuels Bioprod Bioref

et al. 2023

Due to the growth in global demand for biodiesel, there is a tendency for the volume of its main by‐product, glycerol, available on the market to increase. This has led to a search for new uses for this by‐product and the development of new processes that use glycerol as a raw material because it has wide industrial applications. However, to be used in many of these processes, the glycerol must go through a purification stage before reaching the purity required for the application (which can reach 99.7% w/w). Taking this into account, the optimization of the parameters for the main glycerol purification stage (vacuum distillation) is essential to reduce the cost of this stage as much as possible. In this article, optimization of the vacuum distillation column was carried out using an artificial neural network (ANN) and a genetic algorithm (GA) together. With the optimization, it was found that four theoretical stages of equilibrium (separation) is the optimal value, in economics terms, for the distillation column on an industrial scale, leading to better performance (in terms of glycerol purity) than patents that used a smaller number of theoretical stages and an equal performance in relation to the patents that used a greater number of stages, which in this case reduces the cost with the size of the column. This result helps to increase the financially viability of using glycerol as a raw material, which can make several processes cheaper, thus generating greater added value to this sustainable by‐product.

Section: Methodsmentioning

confidence: 99%

Section: Artificial Neural Networkmentioning

confidence: 99%

Optimized conditions for the design and operation of a vacuum distillation column for the purification of crude glycerol from biodiesel production

Neto

Biofuels Bioprod Bioref

et al. 2023

“…Therefore, this study focused on the optimization and deep learning prediction of fuel yield and properties of FAME derived from BSO (inedible seed oil) via KOH-activated waste banana bunch stalk biochar. 41 were used in the extraction of oil from the baobab seeds. The seeds were first dehusked, and to thoroughly remove moisture, the sample was dried at 105 °C for 12 h. The sample was powdered after drying.…”

Section: Introductionmentioning

confidence: 99%

Optimization and Deep Learning Modeling of the Yield and Properties of Baobab-Derived Biodiesel Catalyzed by Waste Banana Bunch Stalk Biochar

Elendu,

Liu,

Aleem

et al. 2024

ACS Omega

The integration of optimization techniques and deep learning models, which offer a promising avenue for improving the efficiency and sustainability of biodiesel production processes from baobab seed oil (BSO), is rare. This study utilized a multi-input-multioutput (MIMO) deep learning technique and the most recent central composite design (CCD) optimization tool to model and optimize the yield and properties of biodiesel produced from BSO. First, the baobab seed oil was extracted using a solvent extraction method. BSO was subsequently analyzed and converted to biodiesel by reacting CH3OH catalyzed by waste banana bunch stalk biochar activated by KOH. Multiobjective optimization and prediction of the biodiesel yield (Y) and several key fuel properties, including the cetane number (CN), kinematic viscosity (VS), and purity (P), were achieved. With better correlation coefficients of 0.9709, 0.9464, and 0.9714 for response training, response testing, and response validation, respectively, and a root-mean-square error of 0.00755, the MIMO model on the logsig transfer function accurately predicted the biodiesel yield and properties more than did the MISO and response surface methodology models. The optimum Y (96 wt %), CN (48), VS (3.3 mm2/s), and P (98.3%) were concurrently accomplished at a reaction temperature of 56 °C, a reaction time of 115 min, a CH3OH/BSO molar ratio of 15:1, a catalyst dosage of 6 wt %, and a stirring speed of 400 rpm with 98% optimal validation accuracy. CCD sensitivity analysis revealed that the CH3OH/BSO ratio was the most sensitive (50.9%) input predictor among the other input variables studied.

Mater Renew Sustain Energy

“…Research investigations continue to indicate that biodiesel fuels made from a variety of seed oils (rubber seed oil, date seed oil, hemp seed oil, cotton seed oil, African pear seed oil, watermelon seed oil, etc.) have fuel qualities comparable to diesel fuel while emitting less hazardous pollutants [12][13][14][15][16][17]. The utilization of biodiesel produced from seed oils has become increasingly popular as a diesel fuel substitute due to its many characteristics that might enhance the proper functioning of a diesel engine.…”

Section: Introductionmentioning

confidence: 99%

Performance and emission analysis of a CI engine fueled with parsley biodiesel–diesel blend

Bitire

Jen

2022

Pollution-induced environmental deterioration is one of the serious aspects that must be solved. As a result, biodiesel was made from a novel material (Parsley seed oil) through an alkali-induced transesterification reaction. The efficiency, as well as exhaust emission tests, were performed by running the prepared parsley biodiesel blends (mixture of biodiesel and diesel fuel in different proportions) in an engine. The ideal blend for enhancing engine performance was discovered to be B20, which displayed steady performance attributes without requiring any modifications to the diesel engine. The B20 parsley biodiesel blend had fewer emissions than diesel, notably hydrocarbons, and carbon monoxide except for nitrogen oxides and carbon dioxide. B20 Parsley blends were also shown to emit less pollution than other blends (B5 and B10). A high reduction in CO, CO2 and HC emissions for B20 was recorded at 33.9%, 29.73%, and 11.38% relative to diesel except for NOx. Brake-specific energy consumption decreases and thermal efficiency of the engine increases for all biodiesel blends. In addition, from the performance results, BTE and BSFC of B20 are relatively close to those of pure diesel fuel (B0). The use of parsley biodiesel as a diesel engine fuel was shown to be a promising strategy to promote the use of green fuels (biofuels from renewable materials) while simultaneously mitigating the release of toxic greenhouse gases from the combustion of fossil fuel.