3 papers
cs.LG2026
Bayesian Calibration of Engine-out NOx Models for Engine-to-Engine Transferability
Shrenik Zinage, Peter Meckl, Ilias Bilionis
Accurate prediction of engine-out NOx is essential for meeting stringent emissions regulations and optimizing engine performance. Traditional approaches rely on models trained on d…
stat.AP2026
Modeling diesel output particulate matter as the Ornstein-Uhlenbeck process
Maxwell Bolt, Alex Alberts, Akash S. Desai +2
Diesel engine particulate matter (PM) is one of the most challenging emission constituents to predict. As engines become cleaner and emissions levels drop, manufacturers need relia…
cs.LG2026
A Causal Graph-Enhanced Gaussian Process Regression for Modeling Engine-out NOx
Shrenik Zinage, Ilias Bilionis, Peter Meckl
The stringent regulatory requirements on nitrogen oxides (NOx) emissions from diesel compression ignition engines require accurate and reliable models for real time monitoring and…