Related Experiment Video
Updated: Mar 22, 2026

Improving the Combustion Performance of a Hybrid Rocket Engine using a Novel Fuel Grain with a Nested Helical Structure
Published on: January 18, 2021
Photothermal solar assisted Madhuca diethyl ether fuel processing for LHR engines with AI-based performance and yield
Rakesh Dubey1, Ajeet Kumar Prajapati2,3, Shruti Bharadwaj4
1Department of Mechanical Engineering, SITRC, Nashik, Maharashtra, India.
None:
This study investigates the combustion, performance, and emission characteristics of biodiesel blends derived from Madhuca longifolia oil with diethyl ether (DEE) as an oxygenated additive in a diesel engine. Prior to fuel preparation, Fourier Transform Infrared (FTIR) analysis was conducted to verify the chemical composition of the extracted oil, confirming the presence of triglyceride structures and long-chain fatty acids characteristic of Madhuca longifolia oil. A solar-assisted preheating mechanism was incorporated during oil extraction to reduce energy consumption and improve yield consistency. The system was further integrated with a 250 Wp solar photovoltaic (PV) panel (efficiency ~ 17%, Voc = 37 V, Isc = 8.5 A, MPPT = 30 V/8 A) to power auxiliary loads such as the fuel metering unit, sensors, and control panel. This renewable integration enabled 100% solar contribution for auxiliary components, saving approximately 1.04 kWh/day of grid electricity and achieving an estimated reduction of about 151 kg of CO2 emissions annually. Four fuel types were evaluated: Diesel, MB100 (pure biodiesel), MB20D80 (20% biodiesel, 80% diesel), and MB5DEE5D90 (5% biodiesel, 5% DEE, 90% diesel). Among these, MB5DEE5D90 demonstrated comparatively improved performance, showing an 8% increase in Brake Thermal Efficiency (BTE) and a 10% reduction in Brake-Specific Fuel Consumption (BSFC) compared with diesel. Emission analysis indicated reductions of approximately 20% in CO and 18% in HC emissions, while life-cycle assessment suggested around 40% lower combustion-phase CO2 emissions. Heat release rate analysis indicated earlier and more efficient combustion behavior. Additionally, LSTM-based predictive modeling showed lower error margins compared with RNN, demonstrating improved prediction accuracy for engine performance parameters.
More Related Videos
11:28Biomass Conversion to Produce Hydrocarbon Liquid Fuel Via Hot-vapor Filtered Fast Pyrolysis and Catalytic Hydrotreating
Published on: December 25, 2016
11:44Qualitative Characterization of the Aqueous Fraction from Hydrothermal Liquefaction of Algae Using 2D Gas Chromatography with Time-of-flight Mass Spectrometry
Published on: March 6, 2016
Related Concept Videos
Biofuels
Standard Enthalpy of Formation
Heat Engines
Whenever we consider heat engines (and associated devices such as refrigerators and heat pumps), we do not use the standard sign convention for heat and work. For convenience, we assume that the symbols Qh, Qc, and W represent only the amounts of heat transferred...