A novel spatial–temporal graph convolutional networks (STGCN) based method for the
regression task of localizing acoustic emission (AE) sources in composite panels is …

Nuclear power generation constitutes a significant component of the energy infrastructure
within the United States. The dry cask storage system canister, used for storing highly …

Monitoring the internal pressure of nuclear spent fuel canisters in high-temperature and
radioactive environments requires a nondestructive approach. Surface Acoustic Wave …

In this research, test methods followed by supervised machine learning (SML) modeling
were used to examine the effect of glass powder as a partial sand and cement substitute on …

Spent nuclear fuel (SNF) assemblies (FAs) contain high-level radioactive waste from
operation of nuclear power plants (NPPs). Their safe storage in dry casks is critical for …

Chloride corrosion is a key factor affecting the life of marine concrete, and surface chloride
concentration is the main parameter for analyzing its durability. In this paper, we first …

This study presents an innovative method for accurately picking the first-wave arrival time in
acoustic emission (AE) localization, particularly effective in environments with low or …

An acoustic emission (AE) and graph convolutional network (GCN) based single-sensor
method for structural damage localization in wind turbine blades is proposed in this paper …

The quantitative assessment of the formability of bulk metallic materials remains
challenging, primarily due to considerable difficulties in accurately identifying the initiation of …

The low-velocity impacts caused by debris and hail can be one of the main threats to the
integrity of the composite components of aircraft such as elevators. Recent improvements in …