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Metals
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Metal Failure Analysis
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Metal Failure Analysis

A section of Metals (ISSN 2075-4701).

Section Information

The “Metal Failure Analysis” Section of Metals covers a broad field of failure processes. The main issue is related to the correlation of failure with the structure and the microstructure of metals and metal welds with their properties. Three main issues are related to metal failure analysis:

The first issue involves the prediction of failure based on the structural and microstructural characterization of metals, alloys, and their welds; even more importantly, a crucial issue is related to the correlation of structure and microstructure of metals alloys and their welds with electric, magnetic, optic, mechanical, and thermal properties, in order to non-destructively monitor the possible areas of failure. Inhomogeneity studies is a crucial issue of metal failure prediction. As an example, steels and their welds may be studied with respect to their dislocation density distribution, as well as with their magnetic and electric properties, the position and time failure may be predicted.

The second issue concerns the rehabilitation of metals, alloys, and their welds. Rehabilitation may occur with several methods, based on heat and localized heat processes, as well as on other methods, such as the KREEP process, mechanical treatment, etc. As an example, metal alloys and their welds may annihilate their stresses by using localized RF heating and, therefore, the stress relief process.

The third issue is the industrialization of the failure monitoring and metal rehabilitation process. The findings of basic research, concerning failure studies and rehabilitation processes should be implemented for industrial applications. As an example, the next generation of heat exchangers must demonstrate minimized levels of inhomogeneities, by implementing failure analysis and rehabilitation in industrial environments. This way, the development of automated processes with an emphasis on artificial intelligence and machine learning of automated systems for failure prognosis and treatment is also important.

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