<p>The use of biomass-derived additives in diesel fuel mixtures has the potential to increase the fuel’s efficiency, decrease the formation of particulate matter during its combustion, and retain the fuel’s behavior in cold weather. To this end, identifying compounds that enable these behaviors is paramount. The present work proposes a series of linear and non-linear equations in parallel with artificial neural networks to predict the cetane number, yield sooting index, kinematic viscosity, cloud point, and lower heating value of multi-component blends. Lower heating values for individual components are predicted using existing equations, and the remaining properties for individual components are predicted using artificial neural networks. Individual component predictions and expected errors are propagated through linear and non-linear equations to obtain property predictions for blends. Individual component property prediction errors, defined by test set median absolute error, are 4.74 units, 6.87 units, 0.09 cSt, and 0.29 degrees Celsius for cetane number, yield sooting index, kinematic viscosity, and cloud point respectively. Lower heating value predictions are assumed to have up to 3.8% error. On average, property predictions for blends are shown to be accurate to within 5% of the blends’ experimental values. Further, a multitude of compounds expected to be produced from catalytically upgrading products of fast pyrolysis are evaluated with respect to their behavior in diesel fuel blends.</p>

Evaluating Diesel/Biofuel Blends Using Artificial Neural Networks and Linear/Nonlinear Equations

Paper Proceedings: https://asmedigitalcollection.asme.org/ICEF/ICEF2021/volume/85512

ASME 2021 Internal Combustion Engine Division Fall Technical Conference (ICEF2021)

Supporting the need among researchers worldwide for additional online and multimedia content, ASME now offers the ASME Conference Video Collection. This platform will collect and provide long-term access to conference presentation videos, encompassing all technology areas within ASME's technical conference and events program. About 30,000-40,000 engineers across all mechanical engineering and related disciplines participate in ASME conferences each year. This includes authors of approximately 6,000 to 8,000 technical papers published by ASME, the majority of whom also submit video presentations for our virtual conferences. The video collection will be available as an add-on to existing product packages or as a separate subscription.