Machine learning-driven modeling of the effect of variable valve timing on fuel consumption and emission reduction in a turbocharged port-injection engine
This study presents a hybrid methodology integrating Design of Experiments and Machine Learning to model brake specific fuel consumption alongside HC and NO x emissions in a turbocharged gasoline engine, demonstrating that a desired calibration accuracy can be achieved using only 50% of the experimental data.
The reviewed literature reveals four generational phases of ML adoption in diesel emissions control, from simple regression-based offline calibration tools to sophisticated real-time physics-informed adaptive systems, which consistently outperform purely data-driven approaches on the out-of-distribution conditions most...
Osariemen Imafidon· World Scientific News· 0 citations
Due to the depletion of global crude oil reserves and the unstable socio-political conditions in the regions with the highest production, there is a growing need to reduce oil consumption, more than 50% of which is associated with the transportation sector. One approach to decreasing oil demand is the incorporation of...
Michał Pająk, Marietta Markiewicz, R. Šmigins· Applied Sciences· 0 citations
The integrated use of experimental testing and predictive modeling offers a reliable framework for engine performance optimization and provides valuable insights for enhancing combustion efficiency in diesel engines.
A. J. Al-Nussairi, Ali B. M. Ali, S. V. Khandal et al.· Multiscale and Multidiscipli...· 0 citations
This study presents a computational framework that integrates an air-standard thermodynamic engine model with artificial neural networks to predict the performance of spark-ignition (SI) engines operating with alternative fuels of reduced lower heating value (LHV). A deterministic thermodynamic simulator was developed...
Marcos Gutierrez, Diana Taco· SAE technical paper series· 0 citations
Measurements of separation efficiency in the upstream oil and gas sector are conducted by a combination of statistical and deterministic pathways. Statistical methods of separation efficiency are typically based on computational models that utilize equations such as the Souders-Brown equation and prediction of separa...
J. N. Antia, D. S. Umobit, A. Ihom· SPE Nigeria Annual Internati...· 0 citations
The proposed framework successfully detected developing faults up to 140 operating hours before functional failure, demonstrating its suitability for onboard condition monitoring and for the performance optimization of marine diesel engines.
A. Ramesh, S. Vishnu, V. Jebasingh· International journal of res...· 0 citations
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