Accurate service-life prediction of structures is vital for taking appropriate measures in a time-
and cost-effective manner. However, the conventional prediction models rely on simplified …

Composite materials have been widely used in many industries due to their excellent
mechanical properties. It is difficult to analyze the integrity and durability of composite …

This study proposed deep learning-based ultrasonic nondestructive testing for porosity
evaluation of additively manufactured components. First, porosity mechanisms according to …

Aircraft structures are exposed to a variety of operational and environmental loads that can
cause structural deformation and fractures. Structural Health Monitoring (SHM) has emerged …

The inverse finite element method (iFEM) is one of the best candidates to perform
displacement monitoring (shape sensing) of structures using a set of on-board/embedded …

Recent high-profile successes in machine learning have found solutions to problems that
were long-thought to be decades away and has generated renewed interest in artificial …

This paper presents a new parallel distributed structural health monitoring technology based
on the wireless sensor network and multi-agent system for large scale engineering …

Composite materials have become the major materials of light-weight structure due to their
light weight, high strength, high modulus, and strong designability. However, as the …

Crack detection is a long-standing topic in structural health monitoring. Conventional
damage detection techniques rely on intensive, time-consuming, resource-intensive …

This paper is intended to introduce the Bayesian network in general and the Naïve-Bayes
classifier in particular as one of the most successful classification systems to simulate …