[HTML][HTML] Improving aircraft performance using machine learning: A review

S Le Clainche, E Ferrer, S Gibson, E Cross… - Aerospace Science and …, 2023 - Elsevier
This review covers the new developments in machine learning (ML) that are impacting the
multi-disciplinary area of aerospace engineering, including fundamental fluid dynamics …

Machine learning based quantitative damage monitoring of composite structure

X Qing, Y Liao, Y Wang, B Chen, F Zhang… - International journal of …, 2022 - Taylor & Francis
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 …

Damage characterization of CFRP laminates using acoustic emission and digital image correlation: Clustering, damage identification and classification

LB Andraju, G Raju - Engineering Fracture Mechanics, 2023 - Elsevier
Damage mechanisms in composite laminates are quite complex, and it is necessary to
perceive their effects on the degradation of laminate mechanical properties. This work …

Determination of vehicle loads on bridges by acoustic emission and an improved ensemble artificial neural network

KC Laxman, A Ross, L Ai, A Henderson… - … and Building Materials, 2023 - Elsevier
Bridges are significant hubs in the US national economy, facilitating the movement of goods
and vehicles. The condition of bridges in the state of South Carolina is currently under …

Damage assessment of smart composite structures via machine learning: a review

A Khan, N Kim, JK Shin, HS Kim, BD Youn - JMST Advances, 2019 - Springer
Composite materials are heterogeneous in nature and suffer from complex non-linear
modes of failure, such as delamination, matrix crack, fiber-breakage, and voids, among …

Unsupervised acoustic emission data clustering for the analysis of damage mechanisms in glass/polyester composites

AR Oskouei, H Heidary, M Ahmadi, M Farajpur - Materials & Design, 2012 - Elsevier
In using acoustic emissions (AEs) for mechanical diagnostics, one major problem is the
discrimination of events due to different types of damage occurring during loading of …

[HTML][HTML] Localisation and identification of fatigue matrix cracking and delamination in a carbon fibre panel by acoustic emission

D Crivelli, M Guagliano, M Eaton, M Pearson… - Composites Part B …, 2015 - Elsevier
Abstract Background The use of Acoustic Emission (AE) as a Structural Health Monitoring
(SHM) technique is very attractive thanks to its ability to detect not only damage sources in …

Advanced damage detection technique by integration of unsupervised clustering into acoustic emission

A Behnia, HK Chai, M GhasemiGol… - Engineering Fracture …, 2019 - Elsevier
The use of acoustic emission (AE) technique for damage diagnostic is typically challenging
due to difficulties associated with discrimination of events that occur during different stages …

Prediction of delamination growth in laminated composites using acoustic emission and cohesive zone modeling techniques

M Saeedifar, M Fotouhi, MA Najafabadi… - Composite …, 2015 - Elsevier
Mode I delamination is the most common failure mode in laminated composite materials.
Determination of the crack growth has a vital role in the damage tolerance analyses of the …

[HTML][HTML] Development of an artificial neural network processing technique for the analysis of damage evolution in pultruded composites with acoustic emission

D Crivelli, M Guagliano, A Monici - Composites Part B: Engineering, 2014 - Elsevier
Acoustic Emission (AE) is a promising technique for the damage detection and the real-time
structural monitoring of composite lightweight structures; however data interpretation and …