Application of Non-Destructive Inspection Methods for Material and Structural Degradation

This Frontiers collection relates to the application of inspection techniques upon surfaces and / or structures ranging from meso to macro scale, relating to all construction methods, inclusive of construction elements from subtractive or additive manufacturing. This includes the use of waves to detect hidden defects beneath multilayer coatings (paint, protective coatings) including signs of corrosion or delamination, heat sources to create thermal contrasts that reveal hidden corrosion under metal surfaces or beneath coatings, probes to detect surface defects by changes in signal/output under illumination, and autonomous vehicles to survey large structures or hard-to-reach surfaces. The aforementioned include the application of Deep and Machine Learning techniques for classification, prediction, anomaly detection in data (e.g. image data, eddy current signals, thermographic images), from thereof combined sensor data (multi-modal), simulation data, and digital twins, to predict where regions of interest are likely to appear or propagate.

This special issue aims to present recent advances in non-destructive inspection methodologies for assessing structural integrity across meso to macro scale systems, inclusive of their construction methods via subtractive or additive manufacturing. Emphasis is placed on wave-based, thermal, optical, and probe-based techniques for detecting subsurface defects, corrosion, as well as on autonomous inspection platforms for large or inaccessible structures. The issue further seeks to explore the integration of Deep Learning, Machine Learning, Data Fusion, and Digital Twin technologies to enhance the detection, classification, and prediction of structural degradation. The aim is to support the development of intelligent, data-driven inspection frameworks.

The scope of this Research Topic encompasses experimental, computational, and data-driven studies focused on non-destructive inspection and monitoring of structural materials and systems. Contributions are invited that address the development, optimization, and application of inspection techniques, such as ultrasonic, thermographic, optical, and multi-modal, for detecting surface and subsurface defects. Studies integrating artificial intelligence, machine learning, data fusion, and digital twins to enhance defect characterization and predictive maintenance are also encouraged. Applications may include marine, aerospace, civil, and industrial structures, as well as autonomous and robotic inspection systems.

Article types and fees

This Research Topic accepts the following article types, unless otherwise specified in the Research Topic description:

• Brief Research Report
• Editorial
• FAIR² Data
• Hypothesis and Theory
• Methods
• Mini Review
• Opinion
• Original Research
• Perspective
• ... View all formats

Articles that are accepted for publication by our external editors following rigorous peer review incur a publishing fee charged to Authors, institutions, or funders.

Article types

This Research Topic accepts the following article types, unless otherwise specified in the Research Topic description:

• Brief Research Report
• Editorial
• FAIR² Data
• Hypothesis and Theory
• Methods
• Mini Review
• Opinion
• Original Research
• Perspective
• Review

Keywords: Condition monitoring, Inspection techniques, Structural health monitoring, Integrity assessment, Corrosion detection, Offshore and subsea maintenance.

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.