Material characterization and testing are vital processes used in engineering, manufacturing, and research. They ensure product quality, aid in product development by selecting appropriate materials, optimize performance under various conditions, and ensure safety and compliance with regulations. Additionally, they help reduce costs, drive innovation, analyze failures, and assess environmental impacts. Non-destructive testing and evaluation techniques are becoming more and more popular in this field since they don't affect the integrity of the tested objects and are easy to use and execute. Key components of modern research objectives within this range include creating techniques that enable testing large quantities of material or analyzing material changes throughout the operating process without affecting its integrity. Nondestructive testing techniques, such as ultrasonic testing, radiography, infrared thermography, or eddy current testing or static of low frequency magnetic testing, play a vital role in characterizing material properties and evaluating defects.
However, with the ever increasing demand of characterizing material with higher accuracy and detecting smaller defects, new or improved nondestructive testing techniques are expected. In this aspect, the study of physical phenomena and the search for relationships and rules between them are the main research goals, and the use of advanced methods of searching for non-obvious relationships based on artificial intelligence methods can significantly improve the efficiency of diagnostic signal processing and accuracy of testing method. Therefore, this issue is devoted to works relating to the results of research using non-destructive techniques for observing various physical phenomena and building descriptions of the relationships between them using advanced data processing algorithms.
This Research Topic in Frontiers in Physics aims to attract contributions on advanced material characterization and testing using AI-enabled nondestructive testing techniques. We welcome original research articles and reviews on themes referring, but not limited to:
- New physics phenomenon in NDT
- Calculation of electromagnetic and ultrasonic fields
- Ultrasonic testing
- Radiographic testing
- Infrared testing
- Eddy current testing
- Magnetic Barkhausen noise testing
- Machine vision techniques for defect inspection
- New designs of NDT sensors
- Advanced signal and image processing in NDT
Keywords:
material characterization, nondestructive testing, defect evaluation, ultrasonic wave, electromagnetic field
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.
Material characterization and testing are vital processes used in engineering, manufacturing, and research. They ensure product quality, aid in product development by selecting appropriate materials, optimize performance under various conditions, and ensure safety and compliance with regulations. Additionally, they help reduce costs, drive innovation, analyze failures, and assess environmental impacts. Non-destructive testing and evaluation techniques are becoming more and more popular in this field since they don't affect the integrity of the tested objects and are easy to use and execute. Key components of modern research objectives within this range include creating techniques that enable testing large quantities of material or analyzing material changes throughout the operating process without affecting its integrity. Nondestructive testing techniques, such as ultrasonic testing, radiography, infrared thermography, or eddy current testing or static of low frequency magnetic testing, play a vital role in characterizing material properties and evaluating defects.
However, with the ever increasing demand of characterizing material with higher accuracy and detecting smaller defects, new or improved nondestructive testing techniques are expected. In this aspect, the study of physical phenomena and the search for relationships and rules between them are the main research goals, and the use of advanced methods of searching for non-obvious relationships based on artificial intelligence methods can significantly improve the efficiency of diagnostic signal processing and accuracy of testing method. Therefore, this issue is devoted to works relating to the results of research using non-destructive techniques for observing various physical phenomena and building descriptions of the relationships between them using advanced data processing algorithms.
This Research Topic in Frontiers in Physics aims to attract contributions on advanced material characterization and testing using AI-enabled nondestructive testing techniques. We welcome original research articles and reviews on themes referring, but not limited to:
- New physics phenomenon in NDT
- Calculation of electromagnetic and ultrasonic fields
- Ultrasonic testing
- Radiographic testing
- Infrared testing
- Eddy current testing
- Magnetic Barkhausen noise testing
- Machine vision techniques for defect inspection
- New designs of NDT sensors
- Advanced signal and image processing in NDT
Keywords:
material characterization, nondestructive testing, defect evaluation, ultrasonic wave, electromagnetic field
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.