Materials Map

Discover the materials research landscape. Find experts, partners, networks.

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The Materials Map is an open tool for improving networking and interdisciplinary exchange within materials research. It enables cross-database search for cooperation and network partners and discovering of the research landscape.

The dashboard provides detailed information about the selected scientist, e.g. publications. The dashboard can be filtered and shows the relationship to co-authors in different diagrams. In addition, a link is provided to find contact information.

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The Materials Map is still under development. In its current state, it is only based on one single data source and, thus, incomplete and contains duplicates. We are working on incorporating new open data sources like ORCID to improve the quality and the timeliness of our data. We will update Materials Map as soon as possible and kindly ask for your patience.

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in Cooperation with on an Cooperation-Score of 37%

Topics

Publications (1/1 displayed)

  • 2019Data-Driven Autoregressive Model Identification for Structural Health Monitoring in an Anisotropic Composite Plate.citations

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Rebillat, Marc
1 / 8 shared
Mechbal, Nazih
1 / 17 shared
Paixao, Jessé
1 / 2 shared
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2019

Co-Authors (by relevance)

  • Rebillat, Marc
  • Mechbal, Nazih
  • Paixao, Jessé
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document

Data-Driven Autoregressive Model Identification for Structural Health Monitoring in an Anisotropic Composite Plate.

  • Silva, Samuel Da
  • Rebillat, Marc
  • Mechbal, Nazih
  • Paixao, Jessé
Abstract

A simple data-driven AutoRegressive (AR) model may be used to assess a model to describe and to predict the time-series outputs of the PZT sensors receiving Lamb waves for different operating conditions in composite structures. Thus, this paper presents the potentiality of the use of a set of AR models to detect, locate, and, manly, to extrapolate a damage sensitive index based on changes in onestep- ahead prediction errors. To illustrate this proposal, an aeronautical composite panel with bonded piezoelectric elements, that act both as sensors and actuators, is used to study the relationship between the variation of the parameters of the identified model and the presence of various simulated damage. A damage progression evaluation by extrapolating the AR parameters is also suggested and examined based on cubic spline functions to verify the future state and to observe how the damage could evolute, based on some simplified assumptions. This step could help to make a decision about a possible required repair without adopting a complicated and costly physical model.

Topics
  • impedance spectroscopy
  • anisotropic
  • composite