On ultrasound propagation in composite laminates: Advances in numerical simulation

L Maio, P Fromme - Progress in Aerospace Sciences, 2022 - Elsevier
The growing use of composite materials for aerospace applications has resulted in the need
for quantitative methods to analyze composite components. Ultrasonic guided waves …

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 …

Prediction of maximum tensile stress in plain-weave composite laminates with interacting holes via stacked machine learning algorithms: A comparative study

F Bagherzadeh, T Shafighfard, RMA Khan… - … Systems and Signal …, 2023 - Elsevier
Plain weave composite is a long-lasting type of fabric composite that is stable enough when
being handled. Open-hole composites have been widely used in industry, though they have …

Machine learning assisted characterisation and simulation of compressive damage in composite laminates

J Reiner, R Vaziri, N Zobeiry - Composite Structures, 2021 - Elsevier
A data-rich framework is presented to consistently characterise the macroscopic strain-
softening response of laminated composites subjected to compressive loading. First, a …

Intelligent structural health monitoring of composite structures using machine learning, deep learning, and transfer learning: a review

MM Azad, S Kim, YB Cheon, HS Kim - Advanced Composite …, 2024 - Taylor & Francis
Structural health monitoring (SHM) methods are essential to guarantee the safety and
integrity of composite structures, which are extensively utilized in aerospace, automobile …

Damage detection in flat panels by guided waves based artificial neural network trained through finite element method

D Perfetto, A De Luca, M Perfetto, G Lamanna… - Materials, 2021 - mdpi.com
Artificial Neural Networks (ANNs) have rapidly emerged as a promising tool to solve
damage identification and localization problem, according to a Structural Health Monitoring …

Compression after multiple impact strength of composite laminates prediction method based on machine learning approach

J Zhao, B Wang, Q Lyu, W Xie, Z Guo… - Aerospace Science and …, 2023 - Elsevier
The intelligent structural health monitoring system that can evaluate the structural safety
online is the future development trend, in which the strength online prediction is the key step …

Development of aviation industry-oriented methodology for failure predictions of brittle bonded joints using probabilistic machine learning

Y Freed, N Zobeiry, M Salviato - Composite Structures, 2022 - Elsevier
The bonding assembly concept of cured aerospace composite parts is considered an
efficient approach from almost every perspective. It simplifies the design and provides great …

[HTML][HTML] A machine learning framework for real-time inverse modeling and multi-objective process optimization of composites for active manufacturing control

KD Humfeld, D Gu, GA Butler, K Nelson… - Composites Part B …, 2021 - Elsevier
For manufacturing of aerospace composites, several parts may be processed
simultaneously using convective heating in an autoclave. Due to uncertainties including tool …

Implementation of a probabilistic machine learning strategy for failure predictions of adhesively bonded joints using cohesive zone modeling

Y Freed, M Salviato, N Zobeiry - International Journal of Adhesion and …, 2022 - Elsevier
Adhesive bonding as an assembly procedure in aviation products is very efficient from both
weight and recurring cost points of view. However, even with strict inspections, process …