James S. Bollinger

Perspective on Department of Energy Geospatial Science: Past, Present, and Future

ABSTRACT For many decades, the Department of Energy (DOE) has been an international leader in basic scientific and engineering research that utilizes geospatial science to advance the state of knowledge in disciplines impacting national security, energy sustainability, environmental stewardship, and associated basic research. However, the realized benefits from cross-cutting geospatial science contributions have fallen short of what they could have been with greater collaboration across the DOE complex, stronger emphasis on core geographic information science (GIScience) research and development to support advanced applications, increased strategic institutional support (e.g., for management of legacy data), and additional education and outreach concerning how geospatial science can benefit DOE programs and operations. We propose a vision for DOEs geospatial science based on expanded collaboration to address major national problems, additional advanced GIScience research and development, and a long-term strategy to better manage DOEs geospatial science resources (personnel, facilities, shared data, etc.).

3-D HYDRODYNAMIC MODELING IN A GEOSPATIAL FRAMEWORK

ABSTRACT 3-D hydrodynamic models are used by the Savannah River National Laboratory (SRNL) to simulate the transport of thermal and radionuclide discharges in coastal estuary systems. Development of such models requires accurate bathymetry, coastline, and boundary condition data in conjunction with the ability to rapidly discretize model domains and interpolate the required geospatial data onto the domain. To facilitate rapid and accurate hydrodynamic model development, SRNL has developed a pre- and post-processor application in a geospatial framework to automate the creation of models using existing data. This automated capability allows development of very detailed models to maximize exploitation of available surface water radionuclide sample data and thermal imagery.

A Brief History of Geospatial Science in the Department of Energy.

ABSTRACT The U.S. Department of Energy (DOE) has a rich history of significant contributions to geospatial science spanning the past four decades. In the early years, work focused on basic research, such as development of algorithms for processing geographic data and early use of LANDSAT imagery. The emphasis shifted in the mid-1970s to development of geographic information system (GIS) applications to support programs such as the National Uranium Resource Evaluation (NURE), and later to issue-oriented GIS applications supporting programs such as environmental restoration and management (mid-1980s through present). Throughout this period, the DOE national laboratories represented a strong chorus of voices advocating the importance of geospatial science and technology in the decades to come. The establishment of a Geospatial Science Program by the DOE Office of the Chief Information Officer in 2005 reflects the continued potential of geospatial science to enhance DOEs science, projects, and operations

Remote Measurement of Heat Flux from Power Plant Cooling Lakes

AbstractLaboratory experiments have demonstrated a correlation between the rate of heat loss q″ from an experimental fluid to the air above and the standard deviation σ of the thermal variability in images of the fluid surface. These experimental results imply that q″ can be derived directly from thermal imagery by computing σ. This paper analyses thermal imagery collected over two power plant cooling lakes to determine if the same relationship exists. Turbulent boundary layer theory predicts a linear relationship between q″ and σ when both forced (wind driven) and free (buoyancy driven) convection are present. Datasets derived from ground- and helicopter-based imagery collections had correlation coefficients between σ and q″ of 0.45 and 0.76, respectively. Values of q″ computed from a function of σ and friction velocity u* derived from turbulent boundary layer theory had higher correlations with measured values of q″ (0.84 and 0.89). This research may be applicable to the problem of calculating losses of...

Data mining for ontology development.

A multi-laboratory ontology construction effort during the summer and fall of 2009 prototyped an ontology for counterfeit semiconductor manufacturing. This effort included an ontology development team and an ontology validation methods team. Here the third team of the Ontology Project, the Data Analysis (DA) team reports on their approaches, the tools they used, and results for mining literature for terminology pertinent to counterfeit semiconductor manufacturing. A discussion of the value of ontology-based analysis is presented, with insights drawn from other ontology-based methods regularly used in the analysis of genomic experiments. Finally, suggestions for future work are offered.

Performance Analysis for Mechanical Draft Cooling Tower

Industrial processes use mechanical draft cooling towers (MDCT’s) to dissipate waste heat by transferring heat from water to air via evaporative cooling, which causes air humidification. The Savannah River Site (SRS) has cross-flow and counter-current MDCT’s consisting of four independent compartments called cells. Each cell has its own fan to help maximize heat transfer between ambient air and circulated water. The primary objective of the work is to simulate the cooling tower performance for the counter-current cooling tower and to conduct a parametric study under different fan speeds and ambient air conditions. The Savannah River National Laboratory (SRNL) developed a computational fluid dynamics (CFD) model and performed the benchmarking analysis against the integral measurement results to accomplish the objective. The model uses three-dimensional steady-state momentum, continuity equations, air-vapor species balance equation, and two-equation turbulence as the basic governing equations. It was assumed that vapor phase is always transported by the continuous air phase with no slip velocity. In this case, water droplet component was considered as discrete phase for the interfacial heat and mass transfer via Lagrangian approach. Thus, the air-vapor mixture model with discrete water droplet phase is used for the analysis. A series of parametric calculations was performed to investigate the impact of wind speeds and ambient conditions on the thermal performance of the cooling tower when fans were operating and when they were turned off. The model was also benchmarked against the literature data and the SRS integral test results for key parameters such as air temperature