A. James Clark School of Engineering

Permanent URI for this communityhttp://hdl.handle.net/1903/1654

The collections in this community comprise faculty research works, as well as graduate theses and dissertations.

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    Moisture Content Effects on Energy and Emissions Released During Combustion of Pyrophytic Vegetation
    (2017) May, Nathaniel Andrew; Gollner, Michael J; Fire Protection Engineering; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)
    A series of small-scale laboratory fires were conducted to study the influence of species type and moisture content (MC) on the burning of vegetative fuels common in wildland fires. The experimental results seek to understand the effects these have on the release of gaseous emissions, namely carbon dioxide and carbon monoxide, as well as particulate matter (PM2.5), and fire radiative energy (FRE). Current wildland fire emissions estimates rely on remote sensing techniques coupled with empirically-based linear relationships to relate FRE to biomass consumed, regardless of fuel type and moisture content. Emission factors (EF) are then applied to the estimated fuel consumption to estimate total emissions of specific combustion byproducts. In this study, we revisit these assumptions under the influence of moisture content for species containing volatile oils (pyrophytic species). Experimental results show that while the relationship between FRE and biomass consumed remains linear for dead, dry fuels, pyrophytic species examined in this study failed to follow existing relationships when their moisture content was increased.
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    Motion Reconstruction of Animal Groups: From Schooling Fish to Swarming Mosquitoes
    (2012) Butail, Sachit; Paley, Derek A; Aerospace Engineering; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)
    The long-term goal of this research is to provide kinematic data for the design and validation of spatial models of collective behavior in animal groups. The specific research objective of this dissertation is to apply methods from nonlinear estimation and computer vision to construct multi-target tracking systems that process multi-view calibrated video to reconstruct the three-dimensional movement of animals in a group. We adapt the tracking systems for the study of two animal species: Danio aequipinnatus, a common species of schooling fish, and Anopheles gambiae, the most important vector of malaria in sub-Saharan Africa. Together these tracking systems span variability in target size on image, density, and movement. For tracking fish, we automatically initialize, predict, and reconstruct shape trajectories of multiple fish through occlusions. For mosquitoes, which appear appear as faded streaks on in-field footage, we provide methods to extract velocity information from the streaks, adaptively seek missing measurements, and resolve occlusions within a multi-hypothesis framework. In each case the research has yielded an unprecedented volume of trajectory data for subsequent analysis. We present kinematic data of fast-start response in fish schools and first-ever trajectories of wild mosquito swarming and mating events. The broader impact of this work is to advance the understanding of animal groups for the design of bio-inspired robotic systems, where, similar to the animal groups we study, the collective is able to perform tasks far beyond the capabilities of a single inexpensive robot.