Research Topic

Modelling and Non-Destructive Monitoring of Smart Systems

About this Research Topic

Smart Materials, such as Magnetorheological (MR) materials, have found a variety of applications in engine mounts and clutch systems in the automotive industry, shock absorbing safety devices for cockpit seats in aerospace, shock absorption for prosthetic-leg movement in biomedical engineering, vibration comfort control for semi-active suspension seats in marine engineering and so forth. Thanks to their excellent rheological properties, MR systems can be controlled by an external magnetic field strength to maintain optimal working conditions in response to environmental changes. In the past decades numerous studies have been undertaken on the development of new MR materials, microscopic and macroscopic modelling, fabrication and industrial applications. However, the research on operation condition monitoring of these smart systems are relatively rare. The safety and reliability of the smart systems are of great importance for benign development and long-term applications of MR materials.

With breakthroughs in sensor technology, it is possible to measure various physical signals to investigate the dynamics and monitor the health conditions of smart systems; for example, piezoelectric sensors, industrial CT, and high speed CCD. More importantly, modern numerical simulation technology is now able to produce comparable accuracy to the experimental or real measurements in modelling very complex dynamic systems. The cutting-edge digital twins technique is able to integrate advanced sensing and numerical simulation technologies together to understand the actual performances of smart systems in support from real and virtual measurements. As a result, more advanced non-destructive monitoring paradigm can be developed to perform just-in-time maintenance decisions.

Driven by such motivation, this Research Topic is intended to offer insights into modelling and non-destructive monitoring of smart systems. Emerging modelling techniques are expected to visualize the undergoing physics inside the smart systems or to discover important parameters to perform non-destructive evaluation.

Areas covered by this Research Topic include but are not limited to:
Ø Design, analysis and optimization of smart systems
Ø New Artificial Intelligence (AI) based approaches for modelling of smart systems
Ø New sensor techniques for smart systems monitoring
Ø Digital twins for modelling and monitoring of smart systems
Ø Image processing and visualization for smart systems monitoring
Ø Case reports of engineering applications


Keywords: Magnetorheological materials, smart systems, non-destructive evaluation


Important Note: All contributions to this Research Topic must be within the scope of the section and journal to which they are submitted, as defined in their mission statements. Frontiers reserves the right to guide an out-of-scope manuscript to a more suitable section or journal at any stage of peer review.

Smart Materials, such as Magnetorheological (MR) materials, have found a variety of applications in engine mounts and clutch systems in the automotive industry, shock absorbing safety devices for cockpit seats in aerospace, shock absorption for prosthetic-leg movement in biomedical engineering, vibration comfort control for semi-active suspension seats in marine engineering and so forth. Thanks to their excellent rheological properties, MR systems can be controlled by an external magnetic field strength to maintain optimal working conditions in response to environmental changes. In the past decades numerous studies have been undertaken on the development of new MR materials, microscopic and macroscopic modelling, fabrication and industrial applications. However, the research on operation condition monitoring of these smart systems are relatively rare. The safety and reliability of the smart systems are of great importance for benign development and long-term applications of MR materials.

With breakthroughs in sensor technology, it is possible to measure various physical signals to investigate the dynamics and monitor the health conditions of smart systems; for example, piezoelectric sensors, industrial CT, and high speed CCD. More importantly, modern numerical simulation technology is now able to produce comparable accuracy to the experimental or real measurements in modelling very complex dynamic systems. The cutting-edge digital twins technique is able to integrate advanced sensing and numerical simulation technologies together to understand the actual performances of smart systems in support from real and virtual measurements. As a result, more advanced non-destructive monitoring paradigm can be developed to perform just-in-time maintenance decisions.

Driven by such motivation, this Research Topic is intended to offer insights into modelling and non-destructive monitoring of smart systems. Emerging modelling techniques are expected to visualize the undergoing physics inside the smart systems or to discover important parameters to perform non-destructive evaluation.

Areas covered by this Research Topic include but are not limited to:
Ø Design, analysis and optimization of smart systems
Ø New Artificial Intelligence (AI) based approaches for modelling of smart systems
Ø New sensor techniques for smart systems monitoring
Ø Digital twins for modelling and monitoring of smart systems
Ø Image processing and visualization for smart systems monitoring
Ø Case reports of engineering applications


Keywords: Magnetorheological materials, smart systems, non-destructive evaluation


Important Note: All contributions to this Research Topic must be within the scope of the section and journal to which they are submitted, as defined in their mission statements. Frontiers reserves the right to guide an out-of-scope manuscript to a more suitable section or journal at any stage of peer review.

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Submission Deadlines

05 October 2020 Abstract
02 February 2021 Manuscript

Participating Journals

Manuscripts can be submitted to this Research Topic via the following journals:

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Topic Editors

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Submission Deadlines

05 October 2020 Abstract
02 February 2021 Manuscript

Participating Journals

Manuscripts can be submitted to this Research Topic via the following journals:

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