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NCSA Fellows Search |
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NCSA Fellows Abstracts for 2002-2003Barbara Bailey Nonlinear statistical models arise in many areas of research in a wide range of disciplines. The least squares principle is used to estimate the parameters in nonlinear models and iterative numerical methods are used to find the set of parameters that minimize the residual sum of squares surface. Nonlinear least squares regression problems are intrinsically hard, and it is generally possible to find a dataset that will defeat even the most robust numerical codes. The objective of this proposal is to integrate diagnostics of nonlinear regression fitting procedures and visualization of multidimensional parameter spaces to create an innovative graphics environment that will educate and provide insight for scientists from all disciplines that fit nonlinear models and/or interpret their results. The proposed activities are as follows:
Robert Hornbaker Recent advances in production agriculture have moved U.S. agriculture from a state of broad scale mechanization to a state of mechanization with precision. The widely use of computer in agriculture is further evolving U.S. agriculture into an "information agriculture" era. The core of information agriculture will be a computer-integrated production agriculture technology. It shall consist of five major areas: precision agriculture technologies, agribusiness optimization, operational information management, and system integration. To make those individual technologies useful to agricultural producers, multi-disciplinary research on the computer-integrated production agriculture technology is essential. This proposal is to initialize the computer-integrated agricultural technology research at UIUC. A multi-disciplinary research group, consisting of agronomist (Prof. Hoeft of Crop Sciences), economist (Prof. Hornbaker of Agricultural & Consumer Economics), engineers (Prof. Sreenivas of General Engineering and Prof. Zhang of Agricultural Engineering), and computer scientist (Dr. Welge of NCSA), will be teamed to perform the technology pioneering research work during the NCSA Fellow research project period. Qin Zhang and Robert Hornbaker will actively participate in the Fellows program. The overall goal of this proposed program is to establish a computer-integrated system technology for production agriculture applications. The goal of the proposed NCSA Fellows program is to define the conceptual infrastructure of the proposed technology. An extensive exchange between faculty and researchers from both NCSA and the Colleges of ACES and COE will be involved in the conceptual design phase to ensure the applicability of the designed conceptual infrastructure. Following the success on the conceptual design, the research will focus on the development of a few core information-processing algorithm to validate this defined conceptual infrastructure. In this proposed project, the algorithm development will focus on an information classification algorithm, an information fusion algorithm, and an attributes tracking algorithm for analyzing the production information. The expected outcome from this research will include two to three technical papers on the conceptual development of computer-integrated agricultural systems technology and on the developed core information processing algorithms. Seminars will be given at NCSA on this research to stimulate the inter-disciplinary exchanges. The proposed project will initialize the computer-integrated agricultural systems technology research. The multi-disciplinary collaboration and academic exchange between faculty of NCSA and the Colleges of ACES and COE will be continued after the completion of the NCSA Fellows project. Additional external funds will be brought in to support the expended research in the development of computer-integrated agricultural systems technology. Yonggang Huang Carbon nanotubes exhibit superior electrical properties. Metallic carbon nanotubes can carry extremely large current to serve as interconnects in nano-electronics. Semiconducting carbon nanotubes can be electrically switched on and off as field-effect transistors that are more than 500 times smaller than current devices. However, experiments have shown that electrical conductance of carbon nanotubes changes by two orders of magnitude upon mechanical deformation, i.e., metallic nanotubes become semiconducting ones after deformation. This unique electromechanical characteristic of carbon nanotubes has major implications to reliability of nanotube-based electronics because significant electrical property change due to large deformation in manufacture and operation processes may lead to device malfunction. Nanotube-based electronics involve multiple carbon nanotubes on substrates subjected to complex deformations as in manufacture and operation processes. Atomistic studies on electrical properties, however, are limited to a single carbon nanotube with simple deformations (e.g., tension, compression and torsion). A major hurdle in atomistic studies of nanotube-based electronics is the determination of all atomic positions in deformed carbon nanotubes. Conventional continuum analysis is very effective and robust to determine deformation of solids under arbitrary mechanical and thermal loadings, though it is not applicable at nanoscale. We propose to develop a new continuum analysis based on atomistic models, and establish a computational infrastructure for continuum analysis of carbon nanotubes. Specifically, the interatomic potential for carbon is directly incorporated into the continuum analysis via constitutive models. Such an approach retains the effectiveness and robustness of continuum analysis, and overcomes difficulties of atomistic studies to determine atomic positions in complex, deformed systems. Once atomic positions are known, tight binding calculations provide energy-dispersion relations, which govern electrical properties of deformed carbon nanotubes. For a single carbon nanotube subject to simple deformation (e.g., uniaxial tension), our preliminary results have agreed well with atomistic studies. For multiple carbon nanotubes interacting with the environment as in the nanotube-based electronics, effective computational methods and visualization techniques are critically needed. We will work with scientists at NCSA to develop parallel computing methods that are highly efficient, robust and scalable in order to study thousands of carbon nanotubes on substrates developed for nanotube-based electronics. We will also use the visualization capabilities at NCSA to assist our study of multiple carbon nanotubes interacting with the environment. This combination of computational continuum analysis, tight binding methods and visualization techniques provides an effective and robust way to determine electrical property change of multiple, distorted carbon nanotubes due to complex deformations, which is particularly important to the reliability of nanotube-based electronics. Glaucio Paulino Rapidly advancing developments in the manufacture of ceramic/metal functionally graded materials (FGMs) have created exciting new possibilities for their application in large-scale structural systems requiring ultra-high performance. Current examples include advanced thermal protections for new air/spacecrafts (e.g. space shuttle) and blast resistant systems of critical structural components. The proposed project focuses on developing an integrated multiscale computational environment for simulating spontaneous crack nucleation, initiation, and propagation by means of visualization (Vis), virtual reality (VR) and parallel processing techniques. The fracture events will be represented by a novel interface element for FGMs with tractions across the interface that follow a nonlinear cohesive model driven by work conjugate displacement jumps. This cohesive element may be inserted adaptively in the analysis. The visualization and virtual rendering techniques will allow a better understanding of the mechanics and physics of fracture of FGMs as it makes possible to quantitatively examine large amounts of data into graphical display measurements of physical variables in space and time. Through visualization/animation, the conventional representation of stress tensors, strain tensors, and constitutive relations can be transformed from a series of mathematical equations and matrix quantities to multidimensional visual objects in a dynamic interactive display environment using, for example, tensor glyphs, hyperstreamlines, and sound (to indicate various crack initiation events over time). The goals of this work are divided into two mainstreams:
We will work in collaboration with the NCSA scientists Dave Semeraro and William Sherman. The model described above will be implemented using the NCSA CAVE (Cave Automated Virtual Environment) and Immersadesk environments, which will provide greater immersion into the large amount of scientific data, thereby enhancing our understanding of the physics of progressive failure evolution in advanced composites such as FGMs. In addition, we intend to announce/present this work at the Seventh US National Congress of Computational Mechanics (USNCCM VII – Albuquerque, NM, July 27 - 31, 2003), which is one of the most important events in the field of computational mechanics. Mohan Ramamurthy Accurate prediction of hurricane track, intensity, timing and landfall is both a critical research problem and is of great importance from a societal impact standpoint. Improved predictions will reduce evacuation time and cost, mitigate property damage and save lives. However, research on hurricane track and intensity prediction is a computationally demanding task. The atmosphere is a chaotic dynamical system. Therefore, any small error in the initial condition will grow with time, eventually leading to a total loss of predictability. In hurricane predictions, errors in observations of initial hurricane position, structure, intensity, and environment are compounded by approximations inherent in numerical model treatment of physical processes, such as precipitation and boundary layer physics. As a result, significant errors currently appear in hurricane track, intensity, timing and landfall location. Presently, operational numerical hurricane forecasting is carried out using a deterministic approach - meaning each model forecast employs a single prediction for a given storm. There is a considerable body of research that this approach has serious limitations and improvements will require a fundamental shift towards a probabilistic approach through the use of ensemble modeling techniques. Ensemble forecasting (EF) entails many predictions per event to deal with the myriad uncertainties in a numerical weather prediction (NWP) system. A typical NWP system for the hurricane problem must account for the above uncertainties in initial and boundary conditions and model physics. Thoroughly addressing this problem requires making hundreds of forecasts for each event. Therefore, traditional cyber infrastructure environments and computational methodologies are ill-suited to carry out ensemble prediction research. New computational frameworks are needed for the design, execution, processing, mining and visualization of massive numbers of ensemble predictions. An additional consequence of this enormous problem is the need for the development of new tools and techniques for metadata and job management so that supercomputing resources are effectively and efficiently used. In other words, a new cyber infrastructure environment for end-to-end workflow is essential to carry out research on ensemble prediction of hurricanes. We will work with NCSA scientists and staff members to develop this new cyber infrastructure environment. A portal interface developed by NCSA will be applied to this effort, along with metadata cataloging and mining on the DTF Grid. Specifically, we will work with Jay Alameda on workflow and execution of jobs on the DTF and with Michael Welge on mining the data using the existing D2K environment. The data mining effort will include the development of new objective clustering algorithms for knowledge discovery, which will be imbedded into the D2K environment. This research will be conducted using the WRF model on the TeraGrid. The hurricane prediction problem is not the only one likely to benefit from the new cyber infrastructure environment. The atmospheric sciences community has embraced the ensemble approach for predictions on all scales, from the simulation of thunderstorms to multi-decadal climate simulations. Any techniques and methodologies that will be developed in the proposed project will benefit other researchers engaged in similarly challenging computational problems. Lawrence Schook The genetic basis for inter- and intra-species variation to the susceptibility to infectious agents has been observed for leprosy, tuberculosis, HIV, malaria and hepatitis B persistence. Defining the genetic elements that contribute to susceptibility have proven difficult to define using traditional approaches such as population associations, artificial challenge studies and in defining the threshold phenotype in various environments. Analysis of the susceptibility to infectious diseases has been described as potentially the most complex area of genetics for complex traits. This proposal will support the development of an integrated database associated with human and animal genome projects as well as clinical and pathology databases. The NCSA data mining approaches will permit us to develop models for future experimental validation with respect to the genetic susceptibility to infectious diseases. This will permit studies into novel therapeutics, monitoring protocols for infectious agents (bioterrorism), and increased insights into infectious diseases. This proposal also provides support for the development of a tutorial in data mining for life scientists working in genomics and health. Brenda Trofanenko The web and various other means of dissemination of digital information have facilitated access to, and use of, cultural historical materials that were previously available only through physical access to specific holding institutions. As image collections appear on the web, patterns of student learning in classrooms are changing to utilize and accommodate this new resource. Images are increasingly understood to be valuable primary and secondary resources documenting the material culture and the past they represent. The increased use of web-based resources in classrooms has not examined how classroom users are accessing on-line collections for historical understanding, nor how this information accommodates previous knowledge. It is critical for those involved in teaching history to identify, examine, and analyze the behaviors of classroom users with access to organized visual and textual collections that are easy to navigate, to search, and to gain information. The goals of this proposed project will be to track how classroom users in a high school history classroom utilize digitized resources in understanding the past. This work will draw upon the multi-disciplinary expertise of practitioners and researchers in the museum and library fields, as well as those in NCSA in working with data mining and the learning that results from various texts. This project will provide theory about classroom users behavior and the transference of knowledge between digital and non-digital sources. Qin Zhang Recent advances in production agriculture have moved U.S. agriculture from a state of broad scale mechanization to a state of mechanization with precision. The widely use of computer in agriculture is further evolving U.S. agriculture into an "information agriculture" era. The core of information agriculture will be a computer-integrated production agriculture technology. It shall consist of five major areas: precision agriculture technologies, agribusiness optimization, operational information management, and system integration. To make those individual technologies useful to agricultural producers, multi-disciplinary research on the computer-integrated production agriculture technology is essential. This proposal is to initialize the computer-integrated agricultural technology research at UIUC. A multi-disciplinary research group, consisting of agronomist (Prof. Hoeft of Crop Sciences), economist (Prof. Hornbaker of Agricultural & Consumer Economics), engineers (Prof. Sreenivas of General Engineering and Prof. Zhang of Agricultural Engineering), and computer scientist (Dr. Welge of NCSA), will be teamed to perform the technology pioneering research work during the NCSA Fellow research project period. Qin Zhang and Robert Hornbaker will actively participate in the Fellows program. The overall goal of this proposed program is to establish a computer-integrated system technology for production agriculture applications. The goal of the proposed NCSA Fellows program is to define the conceptual infrastructure of the proposed technology. An extensive exchange between faculty and researchers from both NCSA and the Colleges of ACES and COE will be involved in the conceptual design phase to ensure the applicability of the designed conceptual infrastructure. Following the success on the conceptual design, the research will focus on the development of a few core information-processing algorithm to validate this defined conceptual infrastructure. In this proposed project, the algorithm development will focus on an information classification algorithm, an information fusion algorithm, and an attributes tracking algorithm for analyzing the production information. The expected outcome from this research will include two to three technical papers on the conceptual development of computer-integrated agricultural systems technology and on the developed core information processing algorithms. Seminars will be given at NCSA on this research to stimulate the inter-disciplinary exchanges. The proposed project will initialize the computer-integrated agricultural systems technology research. The multi-disciplinary collaboration and academic exchange between faculty of NCSA and the Colleges of ACES and COE will be continued after the completion of the NCSA Fellows project. Additional external funds will be brought in to support the expended research in the development of computer-integrated agricultural systems technology. |
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