Intelligently Synthesized In Situ Suspension Carbon Black/Styrene/Butylacrylate Composites: Using Artificial Neural Networks towards Printing Inks with Well-Controlled Properties

2019 ◽  
Vol 61 (5) ◽  
pp. 667-680 ◽  
Author(s):  
Maryam Ataeefard ◽  
Yousef Mohammadi ◽  
Mohammad Reza Saeb
Keyword(s):  
Neural Networks ◽  
Artificial Neural Networks ◽  
Carbon Black ◽  
Printing Inks ◽  
Artificial Neural

scholarly journals Wave resource characterization through in-situ measurement followed by artificial neural networks' modeling

2018 ◽  
Vol 115 ◽  
pp. 1055-1066 ◽  
Author(s):  
Antonio Santos Sánchez ◽  
Diego Arruda Rodrigues ◽  
Raony Maia Fontes ◽  
Márcio Fernandes Martins ◽  
Ricardo de Araújo Kalid ◽  
...  
Keyword(s):  
Neural Networks ◽  
Artificial Neural Networks ◽  
In Situ Measurement ◽  
Artificial Neural

scholarly journals Damage Detection in Composites By Artificial Neural Networks Trained By Using in Situ Distributed Strains

2020 ◽  
Vol 27 (5) ◽  
pp. 657-671
Author(s):  
America Califano ◽  
Neha Chandarana ◽  
Luigi Grassia ◽  
Alberto D’Amore ◽  
Constantinos Soutis
Keyword(s):  
Neural Networks ◽  
Artificial Neural Networks ◽  
Full Range ◽  
Composite Plates ◽  
Optical Fibre Sensor ◽  
Artificial Neural ◽  
Set Up ◽  
Structural Inspection ◽  
The Given

Abstract In this paper, a passive structural health monitoring (SHM) method capable of detecting the presence of damage in carbon fibre/epoxy composite plates is developed. The method requires the measurement of strains from the considered structure, which are used to set up, train, and test artificial neural networks (ANNs). At the end of the training phase, the networks find correlations between the given strains, which represent the ‘fingerprint’ of the structure under investigation. Changes in the distribution of these strains is captured by assessing differences in the previously identified strain correlations. If any cause generates damage that alters the strain distribution, this is considered as a reason for further detailed structural inspection. The novelty of the strain algorithm comes from its independence from both the choice of material and the loading condition. It does not require the prior knowledge of material properties based on stress-strain relationships and, as the strain correlations represent the structure and its mechanical behaviour, they are valid for the full range of operating loads. An implementation of such approach is herein presented based on the usage of a distributed optical fibre sensor that allows to obtain strain measurement with an incredibly high resolution.

Modelling net radiation at surface using “in situ” netpyrradiometer measurements with artificial neural networks

2011 ◽  
Author(s):  
Antonio Geraldo-Ferreira ◽  
Emilio Soria-Olivas ◽  
Juan Gómez-Sanchis ◽  
Antonio José Serrano-López ◽  
Almudena Velázquez-Blazquez ◽  
...  
Keyword(s):  
Neural Networks ◽  
Artificial Neural Networks ◽  
Net Radiation ◽  
Artificial Neural
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