Multivariate regression studies for investigating and setting the action levels for the system water quality parameters of a nuclear plant

Abstract

A broad spectrum of water quality parameters is regularly monitored and assessed in auxiliary water systems. The integrity and availability status of a system are ensured by observing the trend of water quality indices which further warrants investigating the regulatory requirements of both safety and non‐safety‐related systems of a nuclear power plant. To evaluate the water chemistry state in a raw water system, we conducted a statistical study investigating water quality indices over 3 years. Obligatory statistical tools were utilized to comprehend and correlate the effects of the source water on the system. Most water quality parameters were found to be within an acceptable range, and correlations were found between the parameters, namely, conductivity, sodium, and chloride. Multivariate optimization and regression studies using the Box–Behnken design were conducted to minimize the system conductivity levels. The experimental data were fitted into a quadratic equation with an r2 value of 0.84. Model validation was conducted, and the fit between the experimental and model results was within 10%. This assessment identifies preventive action levels to avoid impairment of system integrity at an early stage.