Browsing by Author "Enweremadu, Christopher C"

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Comparison of the Techno-Economic and Environmental Assessment of Hydrodynamic Cavitation and Mechanical Stirring Reactors for the Production of Sustainable Hevea brasiliensis Ethyl Ester
(MDPI AG, 2023-12) Samuel, Olusegun David; Aigba, Peter A; Tran, Thien Khanh; Fayaz, H; Pastore, Carlo; Der, Oguzhan; Erçetin, Ali; Enweremadu, Christopher C; Mustafa, Ahmad
Even though the hydrodynamic cavitation reactor (HCR) performs better than the mechanical stirring reactor (MSR) at producing biodiesel, and the ethylic process of biodiesel production is entirely bio-based and environmentally friendly, non-homogeneous ethanol with the triglyceride of underutilized oil, despite the many technical advantages, has discouraged the biodiesel industry and stakeholders from producing ethylic biodiesel in HCRs. This study examines the generation of biodiesel from rubber seed oil (RSO) by comparing the ethyl-based HCR and MSR. Despite ethyl’s technical advantages and environmental friendliness, a lack of scalable protocols for various feedstocks hinders its global adoption. The research employs Aspen HYSYS simulations to investigate the ethanolysis process for RSO in both HCRs and MSRs. The HCR proves more productive, converting 99.01% of RSO compared to the MSR’s 94.85%. The HCR’s exergetic efficiency is 89.56% vs. the MSR’s 54.92%, with significantly lower energy usage. Removing catalytic and glycerin purification stages impacts both processes, with HC showing lower exergy destruction. Economic analysis reveals the HCR’s lower investment cost and higher net present value (USD 57.2 million) and return on investment (176%) compared to the MSR’s. The HCR also has a much smaller carbon footprint, emitting 7.2 t CO2 eq./year, while the MSR emits 172 t CO2 eq./year. This study provides database information for quickly scaling up the production of ethanolic biodiesel from non-edible and third-generation feedstocks in the HCR and MSR.
Neem-castor seed oil esterification modelling: Comparison of RSM and ANFIS
(Elsevier Ltd., 2023-02) Samuel, Olusegun D; Emajuwa, James; Kaveh, Mohammad; Emagbetere, Eyere; Abam, F.I; Elumalai, P.V; Enweremadu, Christopher C; Reddy, P. Srinivas; Eseoghene, Ivrogbo Daniel; Mustafa, Ahmad
ven though the desirable fuel properties and enhanced engine characteristics of an IC engine have led to the adoption of hybrid second generational oily feedstock (HSGOF) over a mono-oily feedstock, the high FFA associated with the HSGOF remains a challenge. The Response Surface Methodology (RSM) and Adaptive-Network-based Fuzzy Inference System (ANFIS) were used to model the esterification of neem and seed crude oils (NCSO) with a high free fatty acid content (FFA). The RSM and ANFIS were used to model and optimize input: esterification variables such as NCSO ratio (20–40), catalyst dosage (1.0– 2.0 wt%), retention time (1.5–2.5 h), and NCSO/methanol molar ratio (4.5–5.5) to achieve the lowest FFA for the NCSO esterification process and produce composite biodiesel. Optimum acid value (AV) of 2.1 mg KOH/g was attained at NCSO ratio of 20, catalyst dosage of 2 wt%, retention time of 2.0 h, and molar ratio of 4.5. A contrast of the developed models was accomplished by statistical norms such as coefficient of determination (R2 ), root mean square error (RMSE) with standard Error of Prediction (SEP). The R2 of 0.82522, RMSE of 0.68099, and SEP of 0.21729 for the RSM model (RM) related to the R2 of 0.9982, RMSE of 0.02434, and 0.01992 for the ANFIS model (AM). The AM seems more consistent than the RM in pre-treating and rendering high NCSO for composite biodiesel production. The key fuel properties of the neem-castor oil methyl ester (NCSOME) certified with those of biodiesel international standards. Copyright 2023 Elsevier Ltd. All rights reserved. Selection and peer-review under responsibility of the scientific committee of the International Confer- ence & Exposition on Mechanical, Material and Manufacturing Technology.