Artificial Neural Network Modeling and Numerical Simulation of Syngas Fuel and Injection Timing Effects on the Performance and Emissions of a Heavy-Duty Compression Ignition Engine
Saeed Foroutani, Gholamreza Salehi, Hossein Fallahsohi, Kamran Lary, Afshin Mohseni Arasteh
Abstract
-value) of optimal topology for training, validation, and testing are 0.99992, 0.96612, and 0.93424, respectively. The results for the optimum ANN model showed that the constructed model sufficiently predicts the performance and emissions of the CI diesel engine.
Topics & Concepts
SyngasHeavy dutyIgnition systemArtificial neural networkAutomotive engineeringEnvironmental scienceComputer scienceEngineeringAerospace engineeringArtificial intelligenceChemistryOrganic chemistryHydrogenAdvanced Combustion Engine TechnologiesVehicle emissions and performanceCombustion and flame dynamics