The last half decade has seen a steep rise in the number of contributions on safe learning
methods for real-world robotic deployments from both the control and reinforcement learning …

The critical importance of heat exchangers (HXs) on energy systems has been widely
recognized, which can largely determine the overall efficiency. With the rise of the topology …

Partial differential equations (PDEs) play a central role in the mathematical analysis and
modeling of complex dynamic processes across all corners of science and engineering …

Digital twin can be defined as a virtual representation of a physical asset enabled through
data and simulators for real-time prediction, optimization, monitoring, controlling, and …

Recent advances in attention-free sequence models rely on convolutions as alternatives to
the attention operator at the core of Transformers. In particular, long convolution sequence …

Numerical simulation of large-scale dynamical systems plays a fundamental role in studying
a wide range of complex physical phenomena; however, the inherent large-scale nature of …

Full scale aerodynamic wind tunnel testing, numerical simulation of high dimensional (full-
order) aerodynamic models or flight testing are some of the fundamental but complex steps …

Given the square matrices A,B,D,E and the matrix C of conforming dimensions, we consider
the linear matrix equation A\mathbfXE+D\mathbfXB=C in the unknown matrix \mathbfX. Our …

Supervised learning in function spaces is an emerging area of machine learning research
with applications to the prediction of complex physical systems such as fluid flows, solid …

We present a coevolutionary view of hydrologic systems, revolving around feedbacks
between environmental and social processes operating across different time scales. This …