ITR - (ASE) - (sim+dmc): Computational Toolbox for the Investigation of Multiscale Surface Processes

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This project focuses on the development of a computational toolbox for investigation of multiscalesurface processes that are central to nanotechnology as well as other current technologies. Two physicalsystems will be studied that span from nano-scale phenomena to large-scale deterministic transportphenomena. The algorithms and software, developed to simulate and extract information from multiscalesystems, are generic over a broad class of problems, and will contribute well beyond the applications usedin their development.The physical systems include electrodeposition of metallic nanoclusters with additives to achievespecific shapes, and environmental degradation through interaction of pits, crevices and cracks. Thephysical systems, chosen for their computational structure, are characteristic of a large class of systemswhere controlled shape evolution is exploited to produce desired structures. Key issues are to understandhow small-scale surface interactions guide spontaneous self-organization, how to extract insight fromnoisy data and uncertain fundamental understanding, and how to insure quality control at multiple scalesin manufacturing.Computational tools will be developed for simulation and sensitivity analysis in multi-phenomenamultiscale systems that require methods for coupling of stochastic and deterministic models. Challengesfor deterministic simulation include the effective use of parallel computers, and dealing with movingboundaries, ill-conditioning and stiffness. We will explore classes of preconditioners for the iterativemethods that solve large linear systems of equations at each time step, in particular a newly-developedmultigrid method that is well-suited to moving boundary problems. Challenges for stochastic simulationinclude stiffness, which has only recently been recognized as a barrier to efficiency for stochasticsimulation.Sensitivity analysis is an important part of this effort. For the deterministic computations, we willmake use of recently developed methods that are adaptive in space and time. We will develop newsensitivity analysis methods and software for stochastic systems, and couple them to deterministicsensitivity analysis for the physical systems of interest. We will facilitate the use of our toolkit byextension to larger-scale software systems of a recently-developed environment for the rapid creation ofGUIs for scientific and numerical software.This project addresses the National Priority Area of Advanced Science and Engineering (ASE), andthe Technical Focus Areas of Innovation in computational modeling or simulation in research oreducation (sim) (primary), and of Innovative approaches to the integration of data, models,communications, analysis and/or control systems, including dynamic, data-driven applications for use inprediction, risk-assessment and decision-making (dmc) (secondary).Broader ImpactsThe proposed project will impact the National Priority Area of ASE through the development ofalgorithms and software to enhance the use of high performance computers in the investigation ofmultiscale surface processes. The availability of such a toolbox will accelerate fundamental scientificresearch and engineering design in an area with the potential for large economic impact. Softwaredeveloped as a result of this project will be widely distributed in the scientific and engineering, computerscience and mathematical sciences communities.The educational activities feature a multidisciplinary, cross-institutional approach to graduateeducation. Students will work in multidisciplinary teams, with joint thesis advisors from a primary and asecondary discipline. This approach has recently been undertaken at UCSB with some success; we planto institutionalize this approach to graduate education in Computational Science and Engineering (CSE)at UCSB, and to export the model to UIUC. The model also includes industrial internships, careerdevelopment workshops, and mentoring of undergraduates. Both UIUC and UCSB have been pioneersin developing graduate programs in CSE and have programs with a similar structure which will facilitatethe sharing of educational ideas and innovations across the institutions.