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Smoldering Propensity in Upholstered Furniture: Using Computational and Experimental Methods to Aid the Selection of an Appropriate Smoldering Scenario



Jiuling Yang, Mauro Zammarano, Guillermo Rein, Haixiang Chen


Inspired by our experiments on the effects of mockup configuration, used to assess and regulate smoldering propensity in residential upholstered furniture (RUF), a novel 2-D computational model is developed to predict the smoldering behavior in different mockups. In this model, two pieces of flexible polyurethane foams are placed perpendicularly to each other, one vertically and one horizontally. Smoldering modes in two mockup configurations have been modeled: the standard mockup (SM, where the foam is in direct contact with the frame) and modified mockup (MM, where an air gap is added between the foam and frame). In the SM, the first smoldering wave (controlled by foam pyrolysis and foam oxidation) spreads upward and downward slowly. Once the first wave approaches the top surface, the second smoldering wave is generated near the top surface and then is driven downward faster by char oxidation. The oxygen diffusion from the top surface controls the smoldering spread in the SM. In the MM, the open boundaries at bottom increase the buoyant force that drives more oxygen to the smoldering front, in which the convective mass flux from the bottom contributes a greater part. With the increase in foam thickness, the difference of the mass loss between the SM and MM is narrowed. It means that the thinner the foam, the more significant of the effects of buoyancy change by mockup design are. The model reproduced the experimental results and gives the detailed interpretations for the enhanced smoldering propensity in MM from the point of view of oxygen supply. The predicted results can provide guidelines for the selection of a proper smoldering scenario for better regulating smoldering propensity in bench-scale tests.
Technical Note (NIST TN) - 2087
Report Number


Polyurethane foam, Smoldering propensity, Buoyant airflow, Computational model
Created February 24, 2020, Updated September 10, 2020