METHODS OF MONITORING THE CONSISTENCY OF SETS OF RECOMMENDED DATA FOR THE DECAY CHARACTERISTICS OF RADIOACTIVE NUCLIDES IONIZING RADIATION MEASUREMENTS

An estimate of the nuclear data of radionuclide decay is necessary in order to determine the most reliable (“best” or preferable) value of the characteristic considered [1]. The majority of decay characteristics, with the exception of the halflife, the value of which is estimated only from a set of results of direct measurements, are related to one another by different balance relations in the known decay scheme. After a set of recommended (estimated) decay data has been obtained using different statistical procedures, one can monitor the reliability (consistency) of these data using the results of independent measurements or estimates of several key quantities. These include the absolute probability P γ of the emission of the most intense γ-radiation, the total decay energy Q and the absolute intensities of the characteristic KX and LX x-rays. The procedure presented below combines these three methods of monitoring the consistency of the recommended (estimated) values of the decay and radiation characteristics of radioactive nuclides. The list of monitored characteristics includes the total decay energy of the radionuclide, the energies and probabilities of nuclear transitions, the internal conversion coefficients, the energies and absolute probabilities of the emission of α-particles, electrons, γ-rays, characteristics x-rays, and certain atomic constants (fluorescence yields). The procedure has been verified on a number of practical results of estimates obtained when compiling standard handbooks of data for a large group of widely employed radionuclides [2‐6]. It corresponds to the rules and procedures used to estimate the decay characteristics of radionuclides by the international cooperation Decay Data Evaluation Project (DDEP). This cooperation includes representatives of the world’s leading metrological and nuclear laboratories [7‐11]. 1. Method of Monitoring the Consistency of Data Using a Normalization Factor for the Transition from the