Chemically Induced Surface Evolution with Level-Sets--ChISELS--is a parallel code for modeling 2D and 3D material depositions and etches at feature scales on patterned wafers at low pressures. Designed for efficient use on a variety of computer architectures ranging from single-processor workstations to advanced massively parallel computers running MPI, ChISELS is a platform on which to build and improve upon previous feature-scale modeling tools while taking advantage of the most recent advances in load balancing and scalable solution algorithms. Evolving interfaces are represented using the level-set method and the evolution equations time integrated using a Semi-Lagrangian approach [1]. The computational meshes used are quad-trees (2D) and oct-trees (3D), constructed such that grid refinement is localized to regions near the surface interfaces. As the interface evolves, the mesh is dynamically reconstructed as needed for the grid to remain fine only around the interface. For parallel computation, a domain decomposition scheme with dynamic load balancing is used to distribute the computational work across processors. A ballistic transport model is employed to solve for the fluxes incident on each of the surface elements. Surface chemistry is computed by either coupling to the CHEMKIN software [2] or by providing user defined subroutines. This report describes the theoretical underpinnings, methods, and practical use instruction of the ChISELS 1.0 computer code.
The Salt River Project (SRP), in conjunction with Sandia National Laboratories (SNL) and Energy Laboratories, Inc. (ELI), collaborated to develop, test, and evaluate an advanced solar water-heating product for new homes. SRP and SNL collaborated under a Department of Energy Cooperative Research and Development Agreement (CRADA), with ELI as SRP's industry partner. The project has resulted in the design and development of the Roof Integrated Thermal Siphon (RITH) system, an innovative product that features complete roof integration, a storage tank in the back of the collector and below the roofline, easy installation by homebuilders, and a low installed cost. SRP's market research guided the design, and the laboratory tests conducted at SNL provided information used to refine the design of field test units and indicated that the RITH concept is viable. ELI provided design and construction expertise and is currently configured to manufacture the units. This final report for the project provides all of the pertinent and available materials connected to the project including market research studies, the design features and development of the system, and the testing and evaluation conducted at SNL and at a model home test site in Phoenix, Arizona.
A method is developed for reliability analysis of dynamic systems under limited information. The available information includes one or more samples of the system output; any known information on features of the output can be used if available. The method is based on the theory of non-Gaussian translation processes and is shown to be particularly suitable for problems of practical interest. For illustration, we apply the proposed method to a series of simple example problems and compare with results given by traditional statistical estimators in order to establish the accuracy of the method. It is demonstrated that the method delivers accurate results for the case of linear and nonlinear dynamic systems, and can be applied to analyze experimental data and/or mathematical model outputs. Two complex applications of direct interest to Sandia are also considered. First, we apply the proposed method to assess design reliability of a MEMS inertial switch. Second, we consider re-entry body (RB) component vibration response during normal re-entry, where the objective is to estimate the time-dependent probability of component failure. This last application is directly relevant to re-entry random vibration analysis at Sandia, and may provide insights on test-based and/or model-based qualification of weapon components for random vibration environments.