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Advanced Techniques in Health Monitoring of Composite Structures

A special issue of Materials (ISSN 1996-1944). This special issue belongs to the section "Advanced Materials Characterization".

Deadline for manuscript submissions: closed (30 June 2024) | Viewed by 343

Special Issue Editors

Department of Mechanical, Robotics, and Energy Engineering, Dongguk University, Seoul 04620, Republic of Korea
Interests: ultrasonic sensors/transducers/harvesters; metastructure-based adaptive wave tailoring; physics and artificial-intelligence-based analysis/design
School of Aerospace Engineering, Beijing Institute of Technology, Beijing 100081, China
Interests: structural optimization; composite structure optimization; optimal sensor placement; health monitoring of composites
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Special Issue Information

Dear Colleagues,

Composite structures are susceptible to complex damage and failure modes during the manufacturing and service processes. Some typical defects of the composite structure include matrix cracking, fiber breakage, delamination, etc., which can deteriorate the integrity of the structure and cause catastrophic failures. The continuous monitoring of composite structure health conditions aids in identifying such damages early, and taking appropriate measures to prolong their service life. Advanced artificial intelligence techniques have been extensively integrated into health monitoring systems to enhance the performance of composite structures. A basic health monitoring process for composite structures coves data acquisition via sensing technologies, data-processing and analysis, and decision-making. This Special Issue aims to present recent advanced models, methods, and technologies related to the health monitoring of composite structures for structural safety and integrity. The topics of interest for the Special Issue include, but are not limited to, the following:

  • Sensor selection and optimal placement in composite structures;
  • Data acquisition from composite structures;
  • Pre-processing of data collected from composite structures;
  • Feature extraction for composite structures;
  • Decision-making on the damage detection of composite structures;
  • Health monitoring of composite structures;
  • Machine learning/deep learning/transfer learning in composite damage detection;
  • Physics-informed machine learning models for composite damage detection.

Dr. Soo-Ho Jo
Dr. Haichao An
Guest Editors

Manuscript Submission Information

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Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • structural health monitoring
  • composite structures
  • artificial intelligence
  • machine learning
  • damage detection
  • optimal sensor placement
  • data processing

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Published Papers

There is no accepted submissions to this special issue at this moment.
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