RT info:eu-repo/semantics/article
T1 Biofuels as a sustainable energy solution: Density measurement and modeling of waste cooking oil and DBE blend
A1 Yatim, Fatima Ezzahra
A1 Samadi, Khaoula
A1 Abala, Ilham
A1 Lifi, Mohamed
A1 Muñoz Rujas, Natalia
A1 Aguilar Romero, Fernando
A1 Alaoui, Fatima E. M.
K1 Biofuel blends
K1 Waste cooking oil
K1 Dibutyl ether
K1 Density
K1 PC-Saft model
K1 Artificial neural network
K1 Ingeniería Química
K1 Chemical engineering
K1 Termodinámica
K1 Thermodynamics
AB Bioenergy and biofuels are at a critical stage of development. Their role in decarbonising the transport sector, particularly in reducing emissions from shipping and aviation, is widely recognized. Waste Cooking Oil Biodiesel (WCOB) is a promising biofuel, due to its economic viability and sustainability. Additionally, oxygenated additives, such as Dibutyl Ether (DBE), enhance the properties of biofuel blends by improving combustion efficiency and reducing emissions. In this study, the density of WCOB and DBE, was systematically investigated under controlled temperature and pressure conditions. Four mixtures with mass fractions of 0.3500, 0.4998, 0.6750, and 0.8492 were prepared. Density measurements were performed over a temperature range of 298.15 K–393.15 K and a pressure range of 1–140 MPa. The Tait equation was used to correlate the experimental density data, which were subsequently used to determine the derived thermodynamic properties of isobaric expansion and isothermal compressibility. The blend density was also predicted using the PC-SAFT equation of state and artificial neural networks (ANN). Models accuracy was evaluated and discussed using a statistical metrics. The ANN model provided the best accuracy for the complete dataset, with AAD = 0.1246 %, MD = 2.3046 % and RMSE = 1.84.10−3, demonstrating its effectiveness in predicting blend densities.
PB Elsevier
SN 0960-1481
YR 2025
FD 2025-09
LK https://hdl.handle.net/10259/11258
UL https://hdl.handle.net/10259/11258
LA eng
NO This research was supported by a grant from National Center for Scientific and Technical Research (CNRST), Morocco (Grant number: 11UCD2020).
DS Repositorio Institucional de la Universidad de Burgos
RD 07-may-2026