For over a century, reduced order models (ROMs) have been a fundamental discipline of
theoretical fluid mechanics. Early examples include Galerkin models inspired by the Orr …

This work addresses model order reduction for complex moving fronts, which are
transported by advection or through a reaction–diffusion process. Such systems are …

Abstract In this work, Sparse Identification of Nonlinear Dynamics (SINDy) algorithm is
generalized to nonlinear dynamic systems with multistable property. This study comes from …

Mapping coastal bathymetry from remote sensing becomes increasingly more attractive for
the coastal community. It is facilitated by a rising availability of drone and satellite data …

The current study aims to evaluate and investigate the development of projection-based
reduced-order models (ROMs) for efficient and accurate rotating detonation engine (RDE) …

Transport-dominated systems are characterized by the propagation of waves and occur in
many applications such as aerodynamics and chemical engineering. To predict the …

Hysteresis phenomenon widely exists in various metamaterials and smart actuators.
Governing equations can describe and predict the static/dynamic behavior of the systems …

The excitation mechanism of the thermoacoustic combustion instability (TCI) in a hydrogen-
rich ram combustor was investigated experientially, focusing on the effects of jet-to-crossflow …

Aerodynamics plays an important role in the aviation industry and aircraft design. Detecting
and minimizing the phenomenon of flow separation from scattered pressure data on the …

Convolutional neural network (CNN), a deep learning algorithm, has gained popularity in
technological applications that rely on interpreting images (typically, an image is a 2D field …