Application of a CNN to the Boda Claystone Formation for high-level radioactive waste disposal.

ABSTRACT: Nations relying on nuclear power generation face great responsibilities when designing their firmly secured final repositories. In Hungary, the potential host rock [the Boda Claystone Formation (BCF)] of the deep geological repository is under extensive examination. To promote a deeper comprehension of potential radioactive isotope transport and ultimately synthesis for site evaluation purposes, we have efficiently tailored geospatial image processing using a convolutional neural network (CNN). We customized the CNN according to the intricate nature of the fracture geometries in the BCF, enabling the recognition process to be particularly sensitive to details and to interpret them in the correct tectonic context. Furthermore, we set the highest processing scale standards to measure the per

SUBMITTER: Lovasz V 

PROVIDER: S-EPMC10073294 | biostudies-literature | 2023 Apr

REPOSITORIES: biostudies-literature