Self‐powered wearable piezoelectric monitoring of human motion and physiological signals for the postpandemic era: a review

Y Wang, Y Yu, X Wei, F Narita - Advanced Materials …, 2022 - Wiley Online Library
As society advances, the shift from passive medical care to health management and
preventive medical care has become an important issue, with the realization of wearable …

Recent developments and future trends in fatigue life assessment of additively manufactured metals with particular emphasis on machine learning modeling

Z Zhan, X He, D Tang, L Dang, A Li… - Fatigue & Fracture of …, 2023 - Wiley Online Library
Additive manufacturing (AM) has emerged as a very promising technology for producing
complex metallic components with enhanced design flexibility. However, the mechanical …

Enhanced Network QoS in Large Scale and High Sensor Node Density Wireless Sensor Networks Using (IR-DV-Hop) localization algorithm and mobile data collector …

R Gantassi, S Messous, Z Masood, QA Sias… - IEEE Access, 2024 - ieeexplore.ieee.org
This paper poses new challenges, especially when designing routing protocols to improve
the quality of service (QoS) criteria and the lifetime of large-scale wireless sensor networks …

Multi-scale correlation of impact-induced defects in carbon fiber composites using X-ray scattering and machine learning

AH Sexton, H Suhonen, MK Huss-Hansen… - Scientific Reports, 2024 - nature.com
Impact-induced defects in carbon fiber-reinforced polymers (CFRPs)-spanning from
nanometer to macroscopic length scales-can be monitored using an aggregate of X-ray …

Novel process for monitoring stress in carbon fiber reinforced polymer composites using magnetostrictive wires from cryogenic to high temperatures

K Katabira, R Komagome, F Narita - Mechanics of Advanced …, 2024 - Taylor & Francis
Carbon-fiber-reinforced polymer (CFRP) is widely used in aerospace owing to its high
strength, high elasticity, and low density. Recently, CFRP has been used at different …

Experimental investigations ANN and GEP modeling of failure load for AA7075-T6/CFRP adhesive bond

B Hamamci - Neural Computing and Applications, 2023 - Springer
It is known that bond strength is affected by the application conditions and methods of
adhesive connections. Knowing which method can increase the joint strength more and …

Classifying Tensile Loading History of Continuous Carbon Fiber Composites Using X‐Ray Scattering and Machine Learning

A Sexton, M Kanters, H Demchenko… - Advanced …, 2024 - Wiley Online Library
The tensile loading history of continuous carbon fiber composites is classified using
machine learning (ML) and crystallographic data from the polymer matrix. Composites with …

The influence of several carbon fiber architecture on the drapability effect

YP Chuves, M Pitanga, I Grether, MO Cioffi, F Monticeli - Textiles, 2022 - mdpi.com
The growth of the aeronautical sector leads to the growth of polymer composites application,
creating new demand for components applications in complex dimensions and shapes …

Predicting the mechanical behavior of carbon fiber-reinforced polymer using machine learning methods: a systematic review

FM Monticeli, FC Alves, LF de Paula Santos… - Machine Intelligence in …, 2024 - Elsevier
Considering the complexity of the mechanic analysis in advanced composite materials,
studies in the literature have demonstrated the use of machine learning (ML) methods …

Análise estrutural de compósitos auto-regeneráveis via RTM: delaminação no modo II de abertura da trinca

MY Pitanga - 2024 - repositorio.unesp.br
O uso de compósitos tem tido um destaque crescente na indústria, principalmente nas
áreas aeronáutica e aeroespacial. Esses materiais possuem diversas vantagens, dentre as …