Publications

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HfC has shown promise as a material for field emission due to the low work function of the (100) surface and a high melting point. Recently, HfC tips have exhibited unexpected failure after field emission at 2200 K. Characterization of the HfC tips identified faceting of the parabolic tip dominated by coexisting (100) and (111) surfaces. To investigate this phenomenon, we used density functional theory (DFT) simulations to identify the role of defects and impurities (Ta, N, O) on HfC surface properties. Carbon vacancies increased the surface energy of the (100) surface from 2.35 J/m2 to 4.75 J/m2 and decreased the surface energy of the carbon terminated (111) surface from 8.75 J/m2 to 3.48 J/m2. Once 60% of the carbon on the (100) surface have been removed the hafnium terminated (111) surface becomes the lowest energy surface, suggesting that carbon depletion may cause these surfaces to coexist. The addition of Ta and N impurities to the surface are energetically favorable and decrease the work function, making them candidate impurities for improving field emission at high temperatures. Overall, DFT simulations have demonstrated the importance of understanding the role of defects on the surface structure and properties of HfC.

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Line of sight jitter in staring sensor data combined with scene information can obscure critical information for change analysis or target detection. Consequently before the data analysis, the jitter effects must be significantly reduced. Conventional principal component analysis (PCA) has been used to obtain basis vectors for background estimation; however PCA requires image frames that contain the jitter variation that is to be modeled. Since jitter is usually chaotic and asymmetric, a data set containing all the variation without the changes to be detected is typically not available. An alternative approach, Scene Kinetics Mitigation, first obtains an image of the scene. Then it computes derivatives of that image in the horizontal and vertical directions. The basis set for estimation of the background and the jitter consists of the image and its derivative factors. This approach has several advantages including: (1) only a small number of images are required to develop the model, (2) the model can estimate backgrounds with jitter different from the input training images, (3) the method is particularly effective for sub-pixel jitter, and (4) the model can be developed from images before the change detection process. In addition the scores from projecting the factors on the background provide estimates of the jitter magnitude and direction for registration of the images. In this paper we will present a discussion of the theoretical basis for this technique, provide examples of its application, and discuss its limitations.

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Wide baseline matching is the state of the art for object recognition and image registration problems in computer vision. Though effective, the computational expense of these algorithms limits their application to many real-world problems. The performance of wide baseline matching algorithms may be improved by using a graphical processing unit as a fast multithreaded co-processor. In this paper, we present an implementation of the difference of Gaussian feature extractor, based on the CUDA system of GPU programming developed by NVIDIA, and implemented on their hardware. For a 2000x2000 pixel image, the GPU-based method executes nearly thirteen times faster than a comparable CPU-based method, with no significant loss of accuracy.

The Waste Isolation Pilot Plant (WIPP) is a US Department of Energy (DOE) facility for the permanent disposal of defense-related transuranic (TRU) waste. US Environmental Protection Agency (EPA) regulations specify that the DOE must demonstrate on a sound basis that the WIPP disposal system will effectively contain long-lived alpha-emitting radionuclides within its boundaries for 10,000 years following closure. In 1996, the DOE submitted the 40 CFR Part 191 Compliance Certification Application for the Waste Isolation Pilot Plant (CCA) to the EPA. The CCA proposed that the WIPP site complies with EPA's regulatory requirements. Contained within the CCA are descriptions of the scientific research conducted to characterize the properties of the WIPP site and the probabilistic performance assessment (PA) conducted to predict the containment properties of the WIPP disposal system. In May 1998, the EPA certified that the TRU waste disposal at the WIPP complies with its regulations. Waste disposal operations at WIPP commenced on 28 March 1999. The 1996 WIPP PA model of the disposal system included conceptual and mathematical representations of key hydrologic and geochemical processes. These key processes were identified over a 22-year period involving data collection, data interpretation, computer models, and sensitivity studies to evaluate the importance of uncertainty and of processes that were difficult to evaluate by other means. Key developments in the area of geochemistry were the evaluation of gas generation mechanisms in the repository; development of a model of chemical conditions in the repository and actinide concentrations in brine; selecting MgO backfill and demonstrating its effects experimentally; and, determining the chemical retardation capability of the Culebra. Key developments in the area of hydrology were evaluating the potential for groundwater to dissolve the Salado Formation (the repository host formation); development of a regional model for hydrologic conditions; development of a stochastic, probabilistic representation of hydraulic properties in the Culebra Member of the Rustler Formation; characterization of physical transport in the Culebra; and, the evaluation of brine and gas flow in the Salado. Additional confidence in the conceptual models used in the 1996 WIPP PA was gained through independent peer review in many stages of their development.