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Automated non-destructive internal corrosion detection on radioactive drums (ZIKA)

Hatz, Nick 1; Averin, Anton; Lecompagnon, Julien
1 Institut für Technologie und Management im Baubetrieb (TMB), Karlsruher Institut für Technologie (KIT)

Abstract:

Against the backdrop of extended storage times in German interim storage facilities and the increase in low- and medium-level radioactive waste, monitoring container integrity is of critical importance. The ZIKA (Automated non-destructive internal corrosion detection on radioactive drums/15S9446A) research project, carried out as part of the FORKA funding initiative, presents an automated system for non-destructive testing (NDT) of radioactive waste drums. The primary goal is the reliable early detection of internal corrosion in order to identify safety risks before the integrity of the containers is compromised by externally visible degradation. As a further development of the predecessor project EMOS, the system architecture has been optimized for mobile use in a compact 10-foot container. The novel design integrates complex lifting mechanisms and robotics to ensure complete inspection of the entire drum surface, including the bottom. The multi-sensory approach combines laser scanners for topographic mapping, smart cameras for detecting external defects, and active thermography for identifying internal corrosion. Experimental validations by the Federal Institute for Materials Research and Testing (BAM) showed that laser thermography is more robust and reliable in defect detection than flash thermography. ... mehr


Verlagsausgabe §
DOI: 10.5445/IR/1000193350
Veröffentlicht am 19.05.2026
Originalveröffentlichung
DOI: 10.1515/kern-2025-0101
Cover der Publikation
Zugehörige Institution(en) am KIT Institut für Technologie und Management im Baubetrieb (TMB)
Publikationstyp Zeitschriftenaufsatz
Publikationsjahr 2026
Sprache Englisch
Identifikator ISSN: 0932-3902, 2195-8580
KITopen-ID: 1000193350
Erschienen in Kerntechnik
Verlag Carl Hanser Verlag
Vorab online veröffentlicht am 06.05.2026
Schlagwörter radioactive waste management; non-destructive testing (NDT); automated inspection systems; active thermography; corrosion detection; machine learning
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