Nuclear energy is crucial for achieving net-zero carbon emissions. A big challenge in the nuclear sector is ensuring the safety of radiation workers and the environment, while being cost-effective. Workplace monitoring is key to protecting workers from risks of ionising radiation. Traditional monitoring involves radiological surveillance via installed radiation monitors, continuously recording measurements like radiation fields and airborne particulate radioactivity concentrations, especially where sudden radiation changes could significantly impact workers. However, this approach struggles to detect incremental changes over a long period of time in the radiological measurements of the facility. To address this limitation, we propose abstracting a nuclear facility as a complex system. We then quantify the information complexity of the facility's radiological measurements using an entropic metric. Our findings indicate that the inferences and interpretations from our abstraction have a firm basis for interpretation and can enhance current workplace monitoring systems. We suggest the implementation of a radiological complexity-based alarm system to complement existing radiation level-based systems. The abstraction synthesized here is independent of the type of nuclear facility, and hence is a general approach to workplace monitoring at a nuclear facility.
Keywords: entropy analysis of radiological readings; radiological complexity; sample entropy; time series analysis; workplace monitoring.
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