The Development of a Multi-Exponential Prediction Algorithm for Calorimetry

Calorimetry allows very precise measurements of nuclear material to be carried out, but requires relatively long measurement times to do so. The ability to accurately predict the equilibrium response of a calorimeter would significantly reduce the amount of time required for calorimetric assays. An algorithm has been developed that is effective at predicting the equilibrium response. This multi-exponential prediction algorithm (MEPA) is based on an iterative technique utilizing commercial fitting routines that fit a constant plus a variable number of exponential terms to calorimeter data. Details of the implementation and the results of trials on a large number of calorimeter data sets will be presented.