The machine fault diagnosis is being considered in a larger-scale complex system with
numerous measurements from diverse subsystems or components, where the collected data …

The unprecedented surge in video data production in recent years necessitates efficient
tools to extract meaningful frames from videos for downstream tasks. Long-term temporal …

In this paper, we propose a deep learning model to detect combustion instability using high-
speed flame image sequences. The detection model combines Convolutional Neural …

Nowadays, despite a negative impact on the natural environment, coal combustion is still a
significant energy source. One way to minimize the adverse side effects is sophisticated …

Structural health monitoring (SHM) is usually focused on damage detection (eg, Yes/No) or
approximate estimation of damage size. Any additional details of the damage such as …

While analytical solutions of critical (phase) transitions in dynamical systems are abundant
for simple nonlinear systems, such analysis remains intractable for real-life dynamical …

This work utilizes data-driven methods to morph a series of time-resolved experimental OH-
PLIF images into corresponding three-component planar PIV fields in the closed domain of a …

Thermoacoustic instability (TAI) is a critical challenge for modern lean-burn combustion
systems. This phenomenon is commonly undesired and should be avoided or suppressed to …

The thermo-acoustic instabilities arising in combustion processes cause significant
deterioration and safety issues in various human-engineered systems such as land and air …

Combustion instabilities are prevalent in a variety of systems including gas turbine engines.
In this regard, the introduction of active control opens the potential for new paradigms in …