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<oai_dc:dc xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd">
  <dc:contributor>D.C. Buesch</dc:contributor>
  <dc:creator>J.B. Case</dc:creator>
  <dc:date>2004</dc:date>
  <dc:description>Predictions of waste canister and repository driftwall temperatures as functions of space and time are important to evaluate pre-closure performance of the proposed repository for spent nuclear fuel and high-level radioactive waste at Yucca Mountain, Nevada. Variations in the lithostratigraphic features in densely welded and crystallized rocks of the 12.8-million-year-old Topopah Spring Tuff, especially the porosity resulting from lithophysal cavities, affect thermal properties. A simulated emplacement drift is based on projecting lithophysal cavity porosity values 50 to 800 m from the Enhanced Characterization of the Repository Block cross drift. Lithophysal cavity porosity varies from 0.00 to 0.05 cm3/cm3 in the middle nonlithophysal zone and from 0.03 to 0.28 cm3/cm3 in the lower lithophysal zone. A ventilation model and computer program titled "Monte Carlo Simulation of Ventilation" (MCSIMVENT), which is based on a composite thermal-pulse calculation, simulates statistical variability and uncertainty of rock-mass thermal properties and ventilation performance along a simulated emplacement drift for a pre-closure period of 50 years. Although ventilation efficiency is relatively insensitive to thermal properties, variations in lithophysal porosity along the drift can result in a range of peak driftwall temperatures can range from 40 to 85??C for the preclosure period. Copyright ?? 2004 by ASME.</dc:description>
  <dc:format>application/pdf</dc:format>
  <dc:language>en</dc:language>
  <dc:title>Simulation of ventilation efficiency, and pre-closure temperatures in emplacement drifts at Yucca Mountain, Nevada, using Monte Carlo and composite thermal-pulse methods</dc:title>
  <dc:type>text</dc:type>
</oai_dc:dc>