Toward the Application of Smart Self-Sensing Nanocomposites to Structural Health Monitoring
A special issue of Sensors (ISSN 1424-8220). This special issue belongs to the section "Sensor Materials".
Deadline for manuscript submissions: closed (31 March 2022) | Viewed by 663
Special Issue Editors
Interests: digital-twin; development and application of statistical and numerical methods for the solution of inverse problems in the context of structural anomaly and structural load identification; inverse FEM; physics-informed machine learning; Bayesian inference and Monte-Carlo methods for model updating; damage prognosis of composite structures; sensor network optimization; active and passive impact monitoring; implementation of multifunctional composite materials with self-sensing and self-heating functions
Special Issues, Collections and Topics in MDPI journals
Interests: multifunctional composite materials; self-healing materials; 3D printed nanocomposites; structural health monitoring
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
The multifunctional properties of epoxy-based nanocomposites reinforced with carbon nanoparticles are attracting the attention of scientists and designers of structural and prognostic health monitoring systems. The idea of creating a composite structure capable of self-sensing potential deterioration mechanisms within the material by a measure of its piezoresistivity could potentially revolutionize the concept of sensor network design. However, one main factor limits the move toward the industrial application of this technology: the lack of self-sensing robustness hampers the predictability of the sensor performance in terms of sensitivity to the presence of damage and the capability to track its trend during the course of its evolution.
This Special Issue is intended to bring together the various efforts made in developing methods to increase the readiness of this technology for future industrial application, including manufacturing strategies, modeling frameworks, and the development of ternary-state nanocomposites, with a special focus on increasing the sensor performance predictability.
Dr. Claudio Sbarufatti
Prof. Dr. Alberto Jiménez Suárez
Guest Editors
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Keywords
- self-sensing
- nanocomposites
- ternary-state nanocomposites
- carbon nanotubes
- structural health monitoring
- prognostic health monitoring
- performance
- robustness
- predictability
- modeling
- digital twin
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