Publications

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This report provides a detailed analysis of the physical and chemical properties of three liquid hydrocarbon fuels: heptane, Bakken crude, and a diluted bitumen, that were subsequently tested in a series of 2-m pool fire experiments at Sandia National Laboratories for the National Research Council Canada. Properties such as relative density, vapor pressure (VPCR_x), composition, and heat of combustion were evaluated. The heptane analysis, with relative density = 0.69 (at 15°C), confirmed that the material tested was consistent with high-purity (>99%) n-heptane. The Bakken crude, with a relative density = 0.81 (at 15°C), exhibited a vapor pressure by VPCR_0.2 (37.8°C) in the range 120-157 kPa. The dilbit, with a relative density = 0.92 (at 15°C) exhibited a vapor pressure by VPCR 0.2 (37.8°C) in the range 85-98 kPa. Solids remaining in the test pans after the pool fires were also collected and weighed. No detectable solids were left after the heptane burns. In contrast, the crude oils left some brittle, black solid residue. On average, dilbit pool fires left about 40 more residue by mass than Bakken pool fires for equivalent mass of fuel feed.

This analysis shows that when lower density crude oil is injected into the top of an underground salt storage cavern containing more dense crude, separate oil phases can form and coexist indefinitely. This has been observed at the U.S. Strategic Petroleum Reserve in spite of geothermal heating and natural convection, which tend to mix the contents of containers with significant vertical extent subjected to wall and bottom heating. Such persistent layering can create operational challenges for meeting delivery specifications if high-value, low-vapor pressure oil becomes trapped below incoming low-density, high-vapor pressure oil, effectively blocking access to the lower layers until the top layer is removed. Previous conceptual models assumed that the oil injection process mixed incoming oil with resident oil in a storage cavern, forming a single oil phase with relatively homogeneous properties. Here, a review of historical data from the Strategic Petroleum Reserve revealed that several caverns contain multiple oil layers. As a result, oil layering needs to be another variable considered when planning oil movements at SPR in order to optimize low-vapor pressure oil availability to assist in oil delivery blending.

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The Water Network Tool for Resilience (WNTR, pronounced winter) is a Python package designed to simulate and analyze resilience of water distribution networks. Here, a network refers to the collection of pipes, pumps, valves, junctions, tanks, and reservoirs that make up a water distribution system. WNTR has an application programming interface (API) that is flexible and allows for changes to the network structure and operations, along with simulation of disruptive incidents and recovery actions. WNTR is based upon EPANET, which is a tool to simulate the movement and fate of drinking water constituents within distribution systems. Users are encouraged to be familiar with the use of EPANET and/or should have background knowledge in hydraulics and pressurized pipe network modeling before using WNTR. EPANET has a graphical user interface that might be a useful tool to facilitate the visualization of the network and the associated analysis results. Information on EPANET can be found at https://www.epa.gov/water-research/epanet. WNTR is compatible with EPANET 2.00.12 [Ross00]. In addition, users should have experience using Python, including the installation of additional Python packages. General information on Python can be found at https://www.python.org/.

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Crude oil stored at the U.S. Strategic Petroleum Reserve (SPR) requires mitigation procedures to maintain oil vapor pressure within program delivery standards. Crude oil degasification is one effective method for lowering crude oil vapor pressure, and was implemented at the West Hackberry SPR site from 2014-2018. Performance monitoring during and after degasification revealed a range of outcomes for caverns that had similar inventory and geometry.

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