Abstract

In this paper a summary of the differences between structured query language (SQL) based traditional relational database management systems (RDBMS) and recently popular NoSQL based database are presented. The importance of selecting a NoSQL database for the implementation of digital Twin (DT) framework for nuclear reactor predictive maintenance has been discussed. Example of commercially available MongoDB based NoSQL database implementation with storing data from various sources: such as from virtual time-series temperature measurements (based on finite element-based heat transfer models) at thousands of nodal locations and from real sensor measurements (from continuous online monitoring based active ultrasonic sensors and from non-continuous nondestructive testing (NDT) based eddy current measurements is demonstrated.

Volume Subject Area:
Safety Engineering, Risk, and Reliability Analysis
Keywords:
digital twin, artificial intelligence, machine learning, relational database management systems, structured query language (SQL), NoSQL
Topics:
Boilers, Databases, Nuclear reactors, Pressurized water reactors, Relational databases, Artificial intelligence, Eddies (Fluid dynamics), Eddy currents (Electricity), Heat transfer, Machine learning, Maintenance, Nondestructive evaluation, Sensors, Temperature measurement, Time series, Ultrasonic transducers
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