Publications

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The intent of this study is to examine the internal structure of the Bayou Choctaw salt dome utilizing the information obtained from graphical representations of sonar survey data of the internal cavern surfaces. Many of the Bayou Choctaw caverns have been abandoned. Some existing caverns were purchased by the Strategic Petroleum Reserve (SPR) program and have rather convoluted histories and complex cavern geometries. In fact, these caverns are typically poorly documented and are not particularly constructive to this study. Only two Bayou Choctaw caverns, 101 and 102, which were constructed using well-controlled solutioning methods, are well documented. One of these was constructed by the SPR for their use while the other was constructed and traded for another existing cavern. Consequently, compared to the SPR caverns of the West Hackberry and Big Hill domes, it is more difficult to obtain a general impression of the stratigraphy of the dome. Indeed, caverns of Bayou Choctaw show features significantly different than those encountered in the other two SPR facilities. In the number of abandoned caverns, and some of those existing caverns purchased by the SPR, extremely irregular solutioning has occurred. The two SPR constructed caverns suggest that some sections of the caverns may have undergone very regular solutioning to form uniform cylindrical shapes. Although it is not usually productive to speculate, some suggestions that point to the behavior of the Bayou Choctaw dome are examined. Also the primary differences in the Bayou Choctaw dome and the other SPR domes are noted.

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In 1997, an international team interested in the development of Remote Area Power Supply (RAPS) systems for rural electrification projects around the world was organized by the International Lead Zinc Research Organization (ILZRO) with the support of Sandia National Laboratories (SNL). The team focused on defining load and resource profiles for RAPS systems. They identified single family homes, small communities, and villages as candidates for RAPS applications, and defined several different size/power requirements for each. Based on renewable energy and resource data, the team devised a ''strawman'' series of load profiles. A RAPS system typically consists of a renewable and/or conventional generator, power conversion equipment, and a battery. The purpose of this report is to present data and information on insolation levels and load requirements for ''typical'' homes, small communities, and larger villages around the world in order to facilitate the development of robust design practices for RAPS systems, and especially for the storage battery component. These systems could have significant impact on areas of the world that would otherwise not be served by conventional electrical grids.

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Computational fluid dynamics simulations for dispersal of explosive vapors in interior spaces have been performed including details of typical ventilation systems. The interior spaces investigated include an office area, a single-family house, and a warehouse store. Explosive vapor sources are defined in the various interior spaces, and contours of the vapor concentration in the interior spaces relative to the source concentration are presented for relative concentrations down to 10-5. Training protocols for detection of explosive vapors in interior spaces should include an awareness of the time to equilibrium evident in these simulations as well as the significance of ventilation zones.3

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An interdisciplinary team of scientists and engineers having broad expertise in materials processing and properties, materials characterization, and computational mechanics was assembled to develop science-based modeling/simulation technology to design and reproducibly manufacture high performance and reliable, complex microelectronics and microsystems. The team's efforts focused on defining and developing a science-based infrastructure to enable predictive compaction, sintering, stress, and thermomechanical modeling in ''real systems'', including: (1) developing techniques to and determining materials properties and constitutive behavior required for modeling; (2) developing new, improved/updated models and modeling capabilities, (3) ensuring that models are representative of the physical phenomena being simulated; and (4) assessing existing modeling capabilities to identify advances necessary to facilitate the practical application of Sandia's predictive modeling technology.

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