Nuclear industry is in crisis and innovation is the central theme of its survival in future.
Artificial intelligence has made a quantum leap in last few years. This paper …

Nuclear energy can make an important contribution to low-carbon energy supply for Industry
4.0, while Industry 4.0 can reform this industry in return. As a typical and complex man …

Artificial Intelligence algorithms are being increasingly used in industrial applications. Their
important function is to support operation of diagnostic systems. This paper presents a new …

The widespread adoption and success of Machine Learning (ML) technologies depend on
thorough testing of the resilience and robustness to adversarial attacks. The testing should …

In nuclear power plants, the loss-of-coolant accident (LOCA) stands out as the most
prevalent and consequential incident. Accurate breach size diagnosis is crucial for the …

This work presents an approach for predicting break size and location in nuclear power
plants (NPP) loss of coolant accidents (LOCA) with or without emergency shutdown of a …

This study investigates the use of a non-linear autoregressive exogenous neural network
(NARX) model to investigate the nexus between energy usability, economic indicators, and …

If safety injection systems (SISs) do not work in the event of a loss-of-coolant accident
(LOCA), the accident can progress to a severe accident in which the reactor core is exposed …

Configuration-controllable phononic crystals (CCPCs) have broad application prospects in
engineering because of their adjustable vibration-reduction properties. Owing to the …

In this paper, a practical smart tool has been developed to predict CHF in LWRs. The tool is
based on the strengthen cascade feed forward ANNs in addition of some of the deep …