6 papers
Scientific Machine Learning for Engine Health Management and Remaining Useful Life Prediction
Jostein Barry-Straume, Changmin Son, Adrian Sandu +4
Engine Health Management (EHM) depends on reliable forecasting of Remaining Useful Life (RUL) and on tracking thermal indicators such as turbine gas temperature (TGT). In practice,…
Benchmarking Machine Learning Uncertainty Quantification Methodologies for Predicting Turbine Gas Temperature Degradation
Jostein Barry-Straume, Changmin Son, Adrian Sandu +4
Effective prognostics and health management of modern engines relies on accurate turbine gas temperature predictions and robust uncertainty quantification to ensure reliability and…
A Patankar predictor-corrector approach for positivity-preserving time integration
Kamila Nurkhametova, Reid J. Gomillion, Amit N. Subrahmanya +1
Many natural processes, such as chemical reactions and wave dynamics, are modeled as production-destruction (PD) systems that obey positivity and linear conservation laws. Classica…
Ensemble based Closed-Loop Optimal Control using Physics-Informed Neural Networks
Jostein Barry-Straume, Adwait D. Verulkar, Arash Sarshar +2
The objective of designing a control system is to steer a dynamical system with a control signal, guiding it to exhibit the desired behavior. The Hamilton-Jacobi-Bellman (HJB) part…
A copula-based rank histogram ensemble filter
Amit N. Subrahmanya, Julie Bessac, Andrey A. Popov +1
Serial ensemble filters implement triangular probability transport maps to reduce high-dimensional inference problems to sequences of state-by-state univariate inference problems.…
Multirate methods for ordinary differential equations
Michael Günther, Adrian Sandu
This survey provides an overview of state-of-the art multirate schemes, which exploit the different time scales in the dynamics of a differential equation model by adapting the com…