The heat-release rate (HRR) of a burning item is key to understanding the thermal effects of a fire on its surroundings. It is, perhaps, the most important variable used to characterize a burning fuel packet and is defined as the rate of energy released by the fire. HRR is typically determined using a gas measurement calorimetry method. In this study, an inversion algorithm is presented for conducting calorimeter on fires with unknown HRRs located in a compartment. The algorithm compares predictions of a forward model with observed heat fluxes from synthetically generated data sets to determine the HRR that minimizes a cost function. The effects of tuning a weighting parameter in the cost function and the issues associated with two different forward models of a compartment fire are examined.

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