The rate of particle removal from a surface by air jet impingement has been evaluated for 3 different types of trace explosives. Samples of research development explosive (cyclotrimethylenetrinitramine), trinitrotoluene, and C-4 were each transferred to glass surfaces and then subjected to a short burst of air from a jet with varying diameter, standoff distance, and backpressure to achieve a range of shear stresses at the surface. TNT was observed to be easiest to remove, while C-4 required the greatest shear force to resuspend. An analytical model has been developed to predict removal of spherical particles as a function of particle diameter and nondimensionalized downstream distance from a gas jet. This model was fitted to experimental data from the removal of ceramic microspheres of various sizes. The removal rate of these ceramic microspheres was observed to be much greater than that of the 3 types of explosive particles, despite the particles' similar sizes.
Organic materials are an attractive choice for structural components due to their light weight and versatility. However, because they decompose at low temperatures relative to tradiational materials they pose a safety risk due to fire and loss of structural integrity. To quantify this risk, analysts use chem- ical kinetics models to describe the material pyrolysis and oxidation using thermogravimetric analysis. This process requires the calibration of many model parameters to closely match experimental data. Previous e?orts in this field have largely been limited to finding a single best-fit set of parame- ters even though the experimental data may be very noisy. Furthermore the chemical kinetics models are often simplified representations of the true de- composition process. The simplification induces model-form errors that the fitting process cannot capture. In this work we propose a methodology for calibrating decomposition models to thermogravimetric analysis data that accounts for uncertainty in the model-form and experimental data simul- taneously. The methodology is applied to the decomposition of a carbon fiber epoxy composite with a three-stage reaction network and Arrhenius kinetics. The results show a good overlap between the model predictions and thermogravimetric analysis data. Uncertainty bounds capture devia- tions of the model from the data. The calibrated parameter distributions are also presented. The distributions may be used in forward propagation of uncertainty in models that leverage this material.
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