PNNL

Abstract

Operators, national regulatory agencies and the IAEA will require the development of advanced technologies to efficiently control and safeguard nuclear material at increasingly large-scale nuclear recycling facilities. Ideally, the envisioned technologies would be capable of non-destructive, near-real-time (NRT), autonomous process monitoring. This paper describes results from proof-of-principle experiments designed to test the Multi-Isotope Process (MIP) Monitor, a novel approach to safeguarding reprocessing facilities. The MIP Monitor combines the detection of intrinsic gamma ray signatures emitted from process solutions with multivariate analysis to detect off-normal conditions in process streams nondestructively and in NRT. Commercial spent nuclear fuel of various irradiation histories was dissolved and separated using a PUREX-based batch solvent extraction. Extractions were performed at various nitric acid concentrations to mimic both normal and off-normal industrial plant operating conditions. Principal Component Analysis (PCA) was applied to the simulated gamma spectra to investigate pattern variations as a function of acid concentration, burnup and cooling time. Partial Least Squares (PLS) regression was applied to attempt to quantify both the acid concentration and burnup of the dissolved spent fuel during the initial separation stage of recycle. The MIP Monitor demonstrated sensitivity to induced variations of acid concentration, including the distinction of ±1.3 M variation from normal process conditions by way of PCA. Acid concentration was predicted using measurements from the organic extract and PLS resulting in predictions with