CANARY: Event Detection Software
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Stochastic Environmental Research and Risk Assessment
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This report summarizes the experimental and modeling effort undertaken to understand solute mixing in a water distribution network conducted during the last year of a 3-year project. The experimental effort involves measurement of extent of mixing within different configurations of pipe networks, measurement of dynamic mixing in a single mixing tank, and measurement of dynamic solute mixing in a combined network-tank configuration. High resolution analysis of turbulence mixing is carried out via high speed photography as well as 3D finite-volume based Large Eddy Simulation turbulence models. Macroscopic mixing rules based on flow momentum balance are also explored, and in some cases, implemented in EPANET. A new version EPANET code was developed to yield better mixing predictions. The impact of a storage tank on pipe mixing in a combined pipe-tank network during diurnal fill-and-drain cycles is assessed. Preliminary comparison between dynamic pilot data and EPANET-BAM is also reported.
IAMG 2009 - Computational Methods for the Earth, Energy and Environmental Sciences
While connectivity is an important aspect of heterogeneous media, methods to measure and simulate connectivity are limited. For this study, we use natural aquifer analogs developed through lidar imagery to track the importance of connectivity on dispersion characteristics. A 221.8 cm by 50 cm section of a braided sand and gravel deposit of the Ceja Formation in Bernalillo County, New Mexico is selected for the study. The use of two-point (SISIM) and multipoint (Snesim and Filtersim) stochastic simulation methods are then compared based on their ability to replicate dispersion characteristics using the aquifer analog. Detailed particle tracking simulations are used to explore the streamline-based connectivity that is preserved using each method. Connectivity analysis suggests a strong relationship between the length distribution of sand and gravel facies along streamlines and dispersion characteristics.
Progress in Geomathematics
This paper investigates the use of strip transect sampling to estimate object abundance when the underlying spatial distribution is assumed to be Poisson. A design-rather than model-based approach to estimation is investigated through computer simulation, with both homogeneous and non-homogeneous fields representing individual realizations of spatial point processes being considered. Of particular interest are the effects of changing the number of transects and transect width (or alternatively, coverage percent or fraction) on the quality of the estimate. A specific application to the characterization of unexploded ordnance (UXO) in the subsurface at former military firing ranges is discussed. The results may be extended to the investigation of outcrop characteristics as well as subsurface geological features. © 2008 Springer-Verlag Berlin Heidelberg.
World Environmental and Water Resources Congress 2008: Ahupua'a - Proceedings of the World Environmental and Water Resources Congress 2008
To protect drinking water systems, a contamination warning system can use in-line sensors to detect accidental and deliberate contamination. Currently, detection of an incident occurs when data from a single station detects an anomaly. This paper considers the possibility of combining data from multiple locations to reduce false alarms and help determine the contaminant's injection source and time. If we consider the location and time of individual detections as points resulting from a random space-time point process, we can use Kulldorff's scan test to find statistically significant clusters of detections. Using EPANET, we simulate a contaminant moving through a water network and detect significant clusters of events. We show these significant clusters can distinguish true events from random false alarms and the clusters help identify the time and source of the contaminant. Fusion results show reduced errors with only 25% more sensors needed over a nonfusion approach. © 2008 ASCE.
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Water Resources Research
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