Publications by authors named "Amy Mensch"

While the impact of wildland-urban interface fires is growing, firebrand exposure is a significant but not well understood contributor to fire spread. The ignition threat of firebrand exposures can be characterized by measuring the heat transfer of glowing firebrands to a surface. The current study presents a novel method for conducting time-resolved heat transfer measurements from individual firebrands across a range of flow conditions.

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This paper presents a study to examine the potential use of machine learning models to build a real-time detection algorithm for prevention of kitchen cooktop fires. Sixteen sets of time-dependent sensor signals were obtained from 60 normal/ignition cooking experiments. A total of 200 000 data instances are documented and analyzed.

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A thin laminar flow channel with a transverse temperature gradient was used to examine thermophoretic deposition of soot aerosol particles in experiments and modeled in Fire Dynamics Simulator (FDS) simulations. Conditions investigated included three flowrates, with nominal Reynolds number based on the hydraulic diameter of 55, 115 and 230, and two applied temperature gradients, nominally 10 °C/mm and 20 °C/mm, with repeats. Soot was generated from a propene diffusion flame.

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Article Synopsis
  • An analytical model was developed to predict inward leakage of air in self-contained breathing apparatus (SCBA) facepieces under negative pressure conditions.
  • The model estimated leakage rates based on the size of the leak and was validated through experiments that correlated negative pressure measurements with particle concentration.
  • Results showed that the model effectively predicted leakage rates, indicating its usefulness in assessing respirator protection during negative pressure scenarios.
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