A method to predict burn injuries of firefighters considering heterogeneous skin thickness distribution based on the instrumented manikin system.

An approach was proposed to predict skin burns during heat exposure based on computational fluid dynamics and Python language. Both uniform and heterogeneous skin thickness distributions of the whole body were considered and significant differences were observed. 100% second-degree burns were reached for the uniform skin model after 4-s flash fire, and maintained during the cooling phase. Third-degree burns occurred for the heterogeneous skin model during fire exposure, and the proportion increased in the cooling phase. Results indicated that the model with uniform skin thickness probably overestimates skin burns in the early stage of fire exposure. The prediction at the latter stage of the model with heterogeneous skin thickness tended to be more serious. Ignoring blood perfusion and dynamic thermophysical parameters of the skin model was the limitation of this study. Nevertheless, this method provides the basis for further advancements in thermal protective ensembles, to enhance occupational safety of firefighters.