2023 review
A Future with Machine Learning: Review of Condition Assessment of Structures and Mechanical Systems in Nuclear Facilities
[Review of ]. ENERGIES, 16(6).
author keywords: condition assessment; artificial intelligence; deep learning; damage detection; signal processing; data management; nuclear piping; concrete; advanced reactors; digital twin
TL;DR:
AI can play a greater role in the condition assessment and can be extended to recognize concrete degradation before cracks develop, and data assimilation and storage is another challenging aspect of autonomous control.
(via Semantic Scholar)
www.mdpi.com (publisher PDF)
UN Sustainable Development Goal Categories
11. Sustainable Cities and Communities
(Web of Science)
Source: Web Of Science
Added: April 17, 2023
The nuclear industry is exploring applications of Artificial Intelligence (AI), including autonomous control and management of reactors and components. A condition assessment framework that utilizes AI and sensor data is an important part of such an autonomous control system. A nuclear power plant has various structures, systems, and components (SSCs) such as piping-equipment that carries coolant to the reactor. Piping systems can degrade over time because of flow-accelerated corrosion and erosion. Any cracks and leakages can cause loss of coolant accident (LOCA). The current industry standards for conducting maintenance of vital SSCs can be time and cost-intensive. AI can play a greater role in the condition assessment and can be extended to recognize concrete degradation (chloride-induced damage and alkali–silica reaction) before cracks develop. This paper reviews developments in condition assessment and AI applications of structural and mechanical systems. The applicability of existing techniques to nuclear systems is somewhat limited because its response requires characterization of high and low-frequency vibration modes, whereas previous studies focus on systems where a single vibration mode can define the degraded state. Data assimilation and storage is another challenging aspect of autonomous control. Advances in AI and data mining world can help to address these challenges.
