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SUMMARY:MICDE Seminar: Michael Eldred\, Computation\, Computers\, Information\, and Mathematics Center\, Sandia National Laboratories
DESCRIPTION:Bio: Michael Eldred is a Distinguished Member of the Technical Staff in the Optimization and Uncertainty Quantification Department within the Computation\, Computers\, Information\, and Mathematics Center at Sandia National Laboratories. He received his B.S. in Aerospace Engineering from Virginia Tech in 1989\, his M.S.E. and Ph.D. in Aerospace Engineering from the University of Michigan in 1990 and 1993. Mike led the DAKOTA project\, a “… toolkit that provides a flexible\, extensible interface between analysis codes and iterative systems analysis methods…”\, for 15 years (1994-2009) and now leads algorithm research and development activities related to DAKOTA. Mike’s research interests include uncertainty quantification\, design under uncertainty\, surrogate-based optimization\, and high-performance computing\, with application to stockpile stewardship and energy initiatives through the NNSA ASC\, DOE ASCR\, and DOE SciDAC programs. \nMike is an Associate Fellow of the American Institute of Aeronautics and Astronautics (AIAA) and a member of the Society for Industrial and Applied Mathematics (SIAM)\, the International Society for Structural and Multidisciplinary Optimization (ISSMO)\, and the United States Association for Computational Mechanics (USACM). He currently serves as a member of the AIAA Nondeterministic Approaches Technical Committee and on the editorial board for the International Journal for Uncertainty Quantification. A number of his publications are available on the DAKOTA web site. \nTitle: Multilevel-Multifidelity Approaches for Uncertainty Quantification and Design\nIn the simulation of complex physics\, multiple model forms of varying fidelity and resolution are commonly available. In computational fluid dynamics\, for example\, common model fidelities include potential flow\, inviscid Euler\, Reynolds-averaged Navier-Stokes\, and large eddy simulation\, which may be further augmented by subgrid-scale model selections and spatio-temporal discretization levels. In this presentation\, we focus on novel algorithms that simultaneously exploit multiple model forms and multiple resolutions\, both for uncertainty quantification (UQ) and for optimization under uncertainty (OUU). These hybrid methods exploit multifidelity methods across the model form hierarchy in combination with multilevel accelerators across an associated discretization hierarchy\, manifesting as multilevel control variate Monte Carlo and multilevel polynomial expansion methods in the UQ case and recursive trust-region and multigrid optimization in the OUU case. These techniques will be demonstrated for both model problems and engineered systems\, and will be placed within the broader context of algorithm research and development within the Dakota project at Sandia. \nDr. Eldred is being hosted by Prof. Duraisamy (Aerospace Engineering) 
URL:https://micde.umich.edu/event/micde-seminar-michael-eldredcomputation-computers-information-and-mathematics-center-sandia-national-laboratories/
LOCATION:1008 FXB\, 1320 Beal Ave\, Ann Arbor\, MI\, 48109
CATEGORIES:Featured Events,MICDE Seminar Series,Seminar
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DTSTART;TZID=America/Detroit:20170308T140000
DTEND;TZID=America/Detroit:20170308T150000
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SUMMARY:SC2/MICDE Seminar: Eric Jankowski\, Materials Science and Engineering\, Boise State University
DESCRIPTION:Bio: Eric Jankowski is an assistant professor of Materials Science and Engineering at Boise State University. He earned his PhD in Chemical Engineering from the University of Michigan in 2012\, where he developed computational tools to study the self-assembly of nanoparticles. These tools leveraged graphics processors to accelerate computations and provided insight into systems of both theoretical and practical importance. Dr. Jankowski began focusing on renewable energy generation during his postdoctoral positions at the University of Colorado and the National Renewable Energy Laboratory. At these postdocs\, Dr. Jankowski applied techniques he developed during his thesis to understand factors that determine the ordering of molecules in organic solar cells. \nThis is a joint seminar of the Scientific Computing Student Club and MICDE\, sponsored in part by U-M Rackham Graduate School.   \n  \nCobbling together computational components to engineer inexpensive plastic solar panels\nIn order to meet projected global energy demands over the next 25 years\, the equivalent of building a 1GW power plant each day is needed. Existing clean power generation technologies can meet this demand in principle\, but their relatively large short-term costs have limited widespread adoption. In this work we explain manufacturing strategies for organic (plastic) solar panels that overcome economic barriers to adoption by optimizing the structure of the organic active layer responsible for generating electricity. We perform coarse-grained molecular dynamics simulations accelerated with graphics processing units to determine the thermodynamically stable morphologies for a variety of candidate ingredients. Using these morphologies we perform kinetic Monte Carlo charge transport simulations to determine which morphologies are better candidates for solar devices. The simulation pipeline developed here combines computational tools developed for solving unrelated problems\, and we discuss the evolving landscape of scientific computing education and how it overlaps with this work. \n 
URL:https://micde.umich.edu/event/sc2micde-seminar-eric-jankowski-material-science-and-engineering-boise-state-university/
LOCATION:2540 G.G. Brown (2350 Hayward St.)\, 2300 Hayward St\, Ann Arbor\, MI\, 48109\, United States
CATEGORIES:Featured Events,MICDE Seminar Series,Seminar
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SUMMARY:MICDE Seminar: Yongjie Jessica Zhang\, Mechanical Engineering and Biomedical Engineering\, Carnegie Mellon University
DESCRIPTION:Bio: Yongjie Jessica Zhang is a Professor in Mechanical Engineering at Carnegie Mellon University with a courtesy appointment in Biomedical Engineering. She received her B.Eng. in Automotive Engineering\, and M.Eng. in Engineering Mechanics from Tsinghua University\, China; and M.Eng. in Aerospace Engineering and Engineering Mechanics and Ph.D. in Computational Engineering and Sciences from Institute for Computational Engineering and Sciences (ICES)\, The University of Texas at Austin. After staying two years at ICES as a postdoctoral fellow\, she joined CMU in 2007 as an assistant professor\, and then was promoted to an associate professor in 2012 and a full professor in 2016. Her research interests include computational geometry\, mesh generation\, computer graphics\, visualization\, finite element method\, isogeometric analysis and their application in computational biomedicine\, material sciences and engineering. She has co-authored over 140 publications in peer-reviewed journals and conference proceedings\, and received the Autodesk Best Paper Award 1st Place in SIAM Conference on Solid and Physical Modeling 2015\, the Best Paper Award in CompIMAGE’16 conference and one of the 5 Most Highly Cited Papers Published in Computer-Aided Design during 2014-2016. She recently published a book entitled “Geometric Modeling and Mesh Generation from Scanned Images” with CRC Press\, Taylor & Francis Group. She is the recipient of Presidential Early Career Award for Scientists and Engineers\, NSF CAREER Award\, Office of Naval Research Young Investigator Award\, USACM Gallagher Young Investigator Award\, Clarence H. Adamson Career Faculty Fellow in Mechanical Engineering\, George Tallman Ladd Research Award\, and Donald L. & Rhonda Struminger Faculty Fellow. \nImage-Based Mesh Generation and Volumetric T-Spline Modeling for Isogeometric Analysis with Engineering Applications\nWith finite element method and scanning technology seeing increased use in many research areas\, there is an emerging need for high-fidelity geometric modeling and mesh generation of spatially realistic domains. This talk will highlight research in three areas: image-based mesh generation for complicated domains\, trivariate spline modeling for isogeometric analysis\, as well as biomedical\, material sciences and engineering applications. First Prof. Zhang will present advances and challenges in image-based geometric modeling and meshing along with a comprehensive computational framework\, which integrates image processing\, geometric modeling\, mesh generation and quality improvement with multi-scale analysis at molecular\, cellular\, tissue and organ scales. Different from other existing methods\, the presented framework supports five unique features: high-fidelity meshing for heterogeneous domains with topology ambiguity resolved; multiscale geometric modeling for biomolecular complexes; automatic all-hexahedral mesh generation with sharp feature preservation; robust quality improvement for non-manifold meshes; and guaranteed-quality meshing. These unique capabilities enable accurate\, stable\, and efficient mechanics calculation for many biomedicine\, materials science and engineering applications. As a new advancement of traditional finite element method\, isogeometric analysis (IGA) was proposed to integrate design and analysis. In the second part of this talk\, she will present her latest research on volumetric T-spline parameterization for IGA applications. For arbitrary-topology objects\, we first build a polycube whose topology is equivalent to the input geometry and it serves as the parametric domain for the following trivariate T-spline construction. Boolean operations\, geometry skeleton and centroidal Voronoi tessellation based surface segmentation are used to preserve surface features. A parametric mapping is then used to build a one-to-one correspondence between the input geometry and the polycube boundary. After that\, we choose the deformed octree subdivision of the polycube as the initial T-mesh\, and make it valid through pillowing\, quality improvement\, and applying templates or truncated subdivision schemes to handle extraordinary nodes. Weighted and truncated T-spline basis functions are derived to enable analysis-suitability\, including partition of unity and linear independence. The developed pipelines have been incorporated into commercial software such as Rhino and Abaqus. \nProf. Zhang is being hosted by Prof. Garikipati (Mechanical Engineering)
URL:https://micde.umich.edu/event/micde-seminar-yongjie-jessica-zhang-mechanical-engineering-and-biomedical-engineering-carnegie-mellon-university/
LOCATION:1200 EECS\, 1301 Beal Ave.\, Ann Arbor\, MI\, 48109\, United States
CATEGORIES:Featured Events,MICDE Seminar Series,Seminar
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