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DTSTART;TZID=America/Detroit:20230412T160000
DTEND;TZID=America/Detroit:20230412T170000
DTSTAMP:20260606T073303
CREATED:20230714T151826Z
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SUMMARY:MICDE Seminar: Paul Kent\, PhD\, Distinguished Research Scientist at Oak Ridge National Laboratory
DESCRIPTION:Dr Kent`s research is focusing on predicting and explaining the properties of materials using computer simulation. Over the last two decades\, advances in simulation techniques coupled with increasing computer power have led to several methods that are able to predict physical properties of real materials to a useful accuracy. Moreover\, these methods use little or no experimental data\, making them especially valuable for the study of new materials and devices. Dr. Kent specializes in the application and development of these so-called “first principles” methods. \nHis research interests are broadly focused on atomistic materials simulation. His ongoing research projects include: \n\nQuantum Monte Carlo for real materials\nLarge length and timescale quantum molecular dynamics calculations\nCharacterization\, optimization\, and design of nanoscale systems with desired properties\nCombined density functional and many-body calculations of correlated electron systems such as the copper-oxide superconductors\nReactive classical molecular dynamics\nSimulation methods for exploitation of Exascale supercomputers and emergent architectures\n\n\n\n\n\n\nDr. Kent is the director of  the Center for Predictive Simulation of Functional Materials. He also leads the  development of the QMCPACK application for exascale computing as part of the Exascale Computing Project. QMCPACK is a high-performance Quantum Monte Carlo code for computing the electronic structure of atoms\, molecules and solids\, including metals. QMCPACK is open source and available on GitHub. \nDr Kent is a member of the Nanotheory Institute at the Center for Nanophase Materials Sciences (CNMS) and the Computational Chemical and Materials Science group in the Computational Science and Engineering Division. He spent three years at NREL with Alex Zunger after completing his PhD with Richard Needs at the University of Cambridge. For several years he worked with Mark Jarrell at the University of Cincinnati on high-temperature cuprate superconductors. In 2009 he transitioned from JICS/UT Knoxville to ORNL. \nAwards: \n\nORNL Director’s Award for Outstanding Individual Accomplishment in Science and Technology\, 2020.\nAPS Fellowship\, nominated by the Division of Computational Physics\, 2017.\nACM Gordon Bell Prize\, 2008.\n\nProfessional Service: \n\nGrant reviewer for US DOE and NSF\nReviewer for APS\, ACS\, IOP\, Elsevier\, Springer Nature etc.\n\nAccurate Quantum Materials  Predictions on the Largest Supercomputers\nAdvances in the field of computational materials science have helped to predict\, understand\, and optimize the properties of many classes of materials. These include new battery electrodes\, catalysts\, and arguably even higher-temperature superconductors. However\, we still lack a widely usable method where all the key uncertainties and approximations in the predictions can be assessed and systematically reduced. This is critical where the approximations in established methods fail\, such as in quantum materials\, or simply where greater accuracy is desired. In this talk I will first describe our recent advances in Quantum Monte Carlo methods that promise to meet this challenge. Second\, I will describe the new algorithms and performance portable software design and development strategies we have adopted to run efficiently on the largest supercomputers powered by GPU accelerators from NVIDIA\, AMD and Intel. The lessons learned can be applied in any area of scientific software development. \n\nThe MICDE Winter 2023 Seminar Series is open to all. University of Michigan faculty and students interested in predicting and explaining the properties of materials using computer simulation are encouraged to attend. \nThis seminar is cohosted by the Michigan Institute for Computational Discovery & Engineering (MICDE) and the Department of Physics. Dr. Kent will be hosted by Dr. Emanuel Gull\, Associate Professor of Theoretical Condensed Matter Physics. \nThis is an in-person event. \nGraduate Certificate in Computational Discovery and Engineering\, and MICDE fellows\, please use this form to record your attendance. \nQuestions? Email MICDE-events@umich.edu
URL:https://micde.umich.edu/event/micde-seminar-paul-kent-phd-distinguished-research-scientist-at-oak-ridge-national-laboratory/
LOCATION:411 West Hall (1085 S. University)\, 1085 S. University Ave\, Ann Arbor\, MI\, 48109\, United States
CATEGORIES:Education,Featured Events,MICDE Seminar Series,Seminar
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END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20230922T150000
DTEND;TZID=America/Detroit:20230922T160000
DTSTAMP:20260606T073303
CREATED:20230823T205958Z
LAST-MODIFIED:20231002T135627Z
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SUMMARY:MICDE / AIM Seminar: Lin Lin\, Professor of Mathematics at University of California Berkeley
DESCRIPTION:Bio: Lin Lin is a Professor in the Department of Mathematics at UC Berkeley\, and a Faculty Scientist in the Mathematics Group at Lawrence Berkeley National Laboratory. His research centers on solving quantum many-body problems by employing both classical and contemporary methods. These techniques prove valuable across various domains\, including quantum chemistry\, quantum physics\, materials science\, and quantum information theory. He has received the Sloan Research Fellowship (2015)\, the National Science Foundation CAREER award (2017)\, the Department of Energy Early Career award (2017)\, the (inaugural) SIAM Computational Science and Engineering (CSE) early career award (2017)\, the Presidential Early Career Awards for Scientists and Engineers (PECASE) (2019)\, the ACM Gordon Bell Prize (Team\, 2020)\, and the Simons Investigator in Mathematics award (2021). \nQuantum algorithms for eigenvalue problems\nThe problem of finding the smallest eigenvalue of a Hermitian matrix\, known as the ground state energy in quantum physics\, has broad applications. Recent years have witnessed significant algorithmic progresses including near-optimal asymptotic complexity\, algorithms with a minimal number of required logical qubits\, and even optimized preconstants. In this talk\, I will first introduce basic quantum algorithm concepts for a non-expert audience and overview these advancements. I will then introduce a recent progress in leveraging ideas from open quantum systems to solve the eigenvalue problem\, which allows us to start from a state with zero overlap with the target state. \n  \n\n  \nThe MICDE Fall 2023 Seminar Series is open to all. University of Michigan faculty and students interested in predicting and explaining the properties of materials using computer simulation are encouraged to attend. \nThis seminar is cohosted by the Michigan Institute for Computational Discovery & Engineering (MICDE) and Applied & Interdisciplinary Mathematics (AIM). Prof. Lin will be hosted by Dr. Emanuel Gull\, Associate Professor of Theoretical Condensed Matter Physics. \nThis is an in-person event. \nGraduate Certificate in Computational Discovery and Engineering\, and MICDE fellows\, please use this form to record your attendance. \nQuestions? Email MICDE-events@umich.edu
URL:https://micde.umich.edu/event/workshop-seminaraim-seminar-lin-lin/
LOCATION:East Hall – 1084
CATEGORIES:Featured Events,Mathematics,Micde Seminar,MICDE Seminar Series
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END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20231002T160000
DTEND;TZID=America/Detroit:20231002T170000
DTSTAMP:20260606T073303
CREATED:20230913T145953Z
LAST-MODIFIED:20231013T144409Z
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SUMMARY:MICDE / ME Seminar:  Olivier Desjardins\, Professor of Mechanical and Aerospace Engineering at Cornell University
DESCRIPTION:Bio: Olivier Desjardins is a Professor at the Sibley School of Mechanical and Aerospace Engineering at Cornell University. He joined the Cornell MAE faculty in July 2011. Prior to that\, he was on the Mechanical Engineering faculty at the University of Colorado at Boulder. He received a Master of Science in Aeronautics and Astronautics from ENSAE (Supaero) in Toulouse\, France\, in 2004. The same year\, he received a Master of Science in Mechanical Engineering from Stanford University\, then in 2008 he obtained a Ph.D. in Mechanical Engineering from Stanford University. He received an NSF CAREER award in 2014 to work on turbulence modeling around liquid-gas interfaces\, and he was presented with the Junior Award from the International Conference on Multiphase Flow in 2016. \nResearch Interests: Prof. Desjardins’ research focuses on large-scale numerical modeling of turbulent reacting multiphase flows with industrial application. Using world-class parallel computers\, his group develops numerical methods and models to investigate the multi-scale and multi-physics fluid mechanics problems that arise in a range of engineering devices\, such as combustors or biomass reactors. \nHigh-fidelity computational techniques such as large-eddy simulations and direct numerical simulations are at the heart of Dr. Desjardins’ research. By enabling the exploration of complex non-linear flow physics from first principles\, these techniques have the potential to guide the development of highly optimized energy and propulsion systems. \nMulti-scale modeling of topology change in multiphase flow simulations\nLiquid atomization and spray formation are ubiquitous processes in nature as well as engineered system. Predicting droplet size distributions from first principle simulations presents a fantastic challenge due to the wide range of scales involved in topology change. In this talk\, we present new developments to the geometric volume of fluid method that enable the tracking of sub-grid scale interfacial features. By reconstructing the interface with multiple planar surfaces or with paraboloid surfaces\, we show that ligaments and sheets can be represented accurately independently of mesh resolution while preserving exact conservation\, good computational efficiency\, and easy integration with finite-volume-based flow solvers. A consequence of such strategies is that lack of mesh resolution no longer induces topology change\, which then needs to be reintroduced explicitly using physics-based models. We discuss various flavors of such models in the context of the break-up of thin liquid films\, a common feature in aerodynamic liquid atomization. \n  \n\n  \nThe MICDE Fall 2023 Seminar Series is open to all. University of Michigan faculty and students interested in predicting and explaining the properties of materials using computer simulation are encouraged to attend. \nThis seminar is cohosted by the Michigan Institute for Computational Discovery & Engineering (MICDE) and the Department of Mechanical Engineering (ME). Prof. Desjardins will be hosted by Dr. Jesse Capecelatro\, Associate Professor of Mechanical and Aerospace Engineering. \nThis is an in-person event. \nGraduate Certificate in Computational Discovery and Engineering\, and MICDE fellows\, please use this form to record your attendance. \nQuestions? Email MICDE-events@umich.edu
URL:https://micde.umich.edu/event/workshop-seminarmicde-me-seminar-olivier-desjardins/
LOCATION:1109 FXB\, 1320 Beal Ave.\, Ann Arbor\, MI\, United States
CATEGORIES:Aerospace Engineering,College Of Engineering,Mechanical Engineering,Micde Seminar,MICDE Seminar Series
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BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20231005T140000
DTEND;TZID=America/Detroit:20231005T150000
DTSTAMP:20260606T073303
CREATED:20230915T193609Z
LAST-MODIFIED:20231004T170032Z
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SUMMARY:LANL XPS Seminar: Mark W. Schraad\, Division Leader for Computational Physics at Los Alamos National Laboratory
DESCRIPTION:Bio: Mark W. Schraad earned his Ph.D. in Aerospace Engineering from the University of Michigan and has nearly three decades of research and development experience at Los Alamos National Laboratory. He focused his research career on materials physics\, with specialization in structured materials and material instabilities\, while also gaining scientific leadership experience across theoretical and computational physics\, modeling and simulation\, and scientific software development for advanced computing architectures and hardware. Mark has balanced experience across Los Alamos Science\, Technology\, and Engineering and Weapons Directorates\, and across the Laboratory’s basic science and mission application portfolios. In his current position\, he serves as Division Leader for Computational Physics within the Weapons Physics Directorate at Los Alamos National Laboratory. In this role\, he is responsible for the development and delivery of LANL’s suite of mission-critical modeling and simulation software\, which is used in the design\, certification\, and assessment of the U.S. nuclear stockpile. \nHigh-Performance Computing and the Future of Big Science for Department of Energy Applications\nLos Alamos is the birthplace of computational physics and has been at the forefront of high-performance computing for nearly eight decades. Integrating physics theory and advanced numerical methods in the instantiation of multi-physics software has allowed Los Alamos to address a broad range of science and technology applications. Today\, as one of 17 Department of Energy National Laboratories\, Los Alamos continues to develop and deploy advanced software in the execution of a complex mission across national security\, energy security\, and environmental and climate science. As part of that endeavor\, the Computational Physics Division at Los Alamos develops and delivers a continuously evolving suite of production software products to design and analyze large-scale integrated physics experiments and to enable the design\, assessment\, and confident certification of the U.S. nuclear stockpile. These software products are deployed on leading-edge\, high-performance computing platforms\, such as the Trinity and Crossroads supercomputers at Los Alamos\, and the Sierra and El Capitan machines at Lawrence Livermore National Laboratory. With a shifting geopolitical landscape\, our software serves a national security mission of ever-increasing importance. Yet\, simultaneously\, the rapid pace of science and technology change places a premium on agility\, with a diversity of computing platforms and architectures coming online\, and with AI poised to revolutionize approaches to modern science. Ultimately\, an integration of artificial intelligence methodologies with the co-design of software and future computing architectures will allow new levels of physics fidelity\, numerical accuracy\, and efficiency in time to solution for the most challenging scientific workflows to address a broad spectrum of future\, big-science problems. \n  \nSnacks and refreshments will be provided!
URL:https://micde.umich.edu/event/lanl-xps-seminar-mark-w-schraad-division-leader-los-alamos-national-laboratory/
LOCATION:Johnson Rooms\, Lurie Engineering Center\, 3rd Floor LEC 3213ABC\, 1221 Beal Ave.\, Ann Arbor\, MI\, United States
CATEGORIES:Micde Seminar,MICDE Seminar Series,Scientific Computing
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END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20231011T110000
DTEND;TZID=America/Detroit:20231011T120000
DTSTAMP:20260606T073303
CREATED:20230927T154544Z
LAST-MODIFIED:20231211T234457Z
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SUMMARY:MICDE / LANL T Division - James Patrick Colgan\, Deputy Division Leader Los Alamos  National Laboratory Theoretical Division
DESCRIPTION:Join us to learn more about the Theoretical Division of Los Alamos National Laboratory.  Are you familiar with the Oppenheimer movie?\nYou can also hear about the exciting opportunities available for graduate students and post docs at LANL. \nSpeaker: James Patrick Colgan\, Deputy Division Leader Los Alamos National Laboratory \n  \nBio: James Colgan is the Deputy Division Leader of Theoretical Division at Los\nAlamos National Laboratory. James received his BSc and PhD degrees in Theoretical\nPhysics from Queen’s University\, Belfast\, Northern Ireland. After a post-doctoral\nposition at Auburn University\, he joined LANL in 2003 as a post-doctoral researcher\nand was converted to a staff scientist position in 2005 in Theoretical Division. James\nbecame Group Leader of the Physics and Chemistry of Materials (T-1) in 2017 and\nbecame Deputy Division Leader in 2022. James has published extensively in atomic\nand plasma physics and was elected a Fellow of the American Physical Society (APS)\nin 2012 and a Fellow of the U.K. Institute of Physics (IOP) in 2021 \nAn overview of Los Alamos National Laboratory and the Theoretical Division\nAbstract: An overview of the activities of Los Alamos National Laboratory (LANL)\nare presented. LANL was founded in 1943 under the leadership of J. Robert\nOppenheimer to direct the “Manhattan Project” – a top-secret project to create the\natomic bomb. Now 80 years later\, in 2023\, LANL is tasked by the nation through the\nDepartment of Energy and National Nuclear Security Administration to deliver\nnational security solutions to address the issues faced by the nation and world.\nLANL achieves its mission by applying multidisciplinary science\, technology and\nengineering capabilities using unique experimental\, computational\, and nuclear\nfacilities.\nThis overview will provide a brief survey of LANL’s activities and then will focus on\nthe research & development portfolio of LANL’s Theoretical (T) Division (part of the\nDirectorate for Simulation & Computation). T Division\, which has existed since the\ninception of LANL\, aims to provide excellence in basic and applied theoretical\nresearch across many disciplines\, notably computational materials science and the\ndevelopment of cutting-edge computational tools to support the national security\nmission of the Laboratory.
URL:https://micde.umich.edu/event/workshop-seminaran-overview-of-los-alamos-national-laboratory-and-the-theoretical-division/
LOCATION:Lurie Robert H. Engin. Ctr – Johnson Rooms (LEC 3213)
CATEGORIES:Micde,Micde Seminar,MICDE Seminar Series
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END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20231027T160000
DTEND;TZID=America/Detroit:20231027T170000
DTSTAMP:20260606T073303
CREATED:20230913T002456Z
LAST-MODIFIED:20231112T073101Z
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SUMMARY:MICDE / ME Seminar: Erik Draeger\, Director of the High Performance Computing Innovation Center and RADIUSS project at Lawrence Livermore National Laboratory
DESCRIPTION:Bio: Dr. Erik Draeger is the Director of the High Performance Computing Innovation Center and RADIUSS project at Lawrence Livermore National Laboratory as well as the Scientific Computing group leader at the Center for Applied Scientific Computing. He is also the Deputy Director of Application Development for the Exascale Computing Project\, jointly overseeing a portfolio of 22 Office of Science applications\, 4 NNSA applications\, and 7 co-design projects. Erik earned a Bachelor’s degree in Physics from the University of California\, Berkeley in 1995 and received a PhD in theoretical condensed matter physics from the University of Illinois\, Urbana-Champaign in 2001. He has over a decade of experience developing scientific applications to achieve maximum scalability and time to solution on next-generation architectures. He has been a finalist for the Gordon Bell Prize six times since 2005 and won the prize in 2006. \nSupercomputing at the exascale and beyond: future trends and challenges\nFor the past seven years\, the U.S. Department of Energy’s Exascale Computing Project (ECP) has funded a comprehensive push to refactor 24 application projects to efficiently utilize exascale computing hardware to solve a varied set of complex science and engineering problems. Ambitious performance and capability goals were set for each application that demanded end-to-end rethinking of traditional approaches. Through detailed performance analysis\, integration with optimized co-design frameworks and software libraries\, and the use of programming abstractions to manage data placement and kernel execution\, ECP applications recently demonstrated substantial capability and performance improvements on newly-available exascale machines. Despite significant diversity in the methods and algorithms underlying the ECP application portfolio\, several common themes emerged in how to best adapt computational workloads to heterogeneous architectures. In this talk\, an overview of best practices and lessons learned on effectively utilizing exascale hardware from the perspective of ECP applications will be presented. Strategies for developing portable\, performant code will be discussed and examples of reexamining traditional algorithms and methods will be described. Armed with this knowledge\, researchers can go beyond simply surviving an uncertain and turbulent computing future to instead leading a wave of scientific and computational innovation as traditional approaches are reexamined and new approaches adopted. \n  \n\n  \nThe MICDE Fall 2023 Seminar Series is open to all. University of Michigan faculty and students interested in predicting and explaining the properties of materials using computer simulation are encouraged to attend. \nThis seminar is cohosted by the Michigan Institute for Computational Discovery & Engineering (MICDE) and the Department of Mechanical Engineering (ME). Dr. Draeger will be hosted by Dr. Vikram Gavini\, Professor of Mechanical Engineering. \nThis is an in-person event. \nGraduate Certificate in Computational Discovery and Engineering\, and MICDE fellows\, please use this form to record your attendance. \nQuestions? Email MICDE-events@umich.edu
URL:https://micde.umich.edu/event/micde-me-seminar-erik-draeger-director-hpc-innovation-center-llnl-deputy-director-doe-exascale-computing-project/
LOCATION:1670 Bob and Betty Beyster Building\, 2260 Hayward Street\, Ann Arbor\, MI\, 48109\, United States
CATEGORIES:Featured Events,Micde,Micde Seminar,MICDE Seminar Series
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BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20231101T150000
DTEND;TZID=America/Detroit:20231101T160000
DTSTAMP:20260606T073303
CREATED:20230913T004822Z
LAST-MODIFIED:20231112T191452Z
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SUMMARY:MICDE / NERS Seminar:  Larry Aagesen\, Computational Scientist at Idaho National Laboratory
DESCRIPTION:Bio: Dr. Larry Aagesen is a Computational Scientist at Idaho National Laboratory (INL)\, and is the leader of the Computational Microstructure Science group there. He is a member of the development team for Marmot\, INL’s application for simulating microstructural evolution in nuclear fuels and reactor structural materials\, which is based on MOOSE\, INL’s framework for solving partial differential equations using the finite element method. His primary area of expertise is in the phase-field method\, having developed phase-field models for a variety of physical phenomena\, including fission gas bubble evolution\, solid-state precipitation\, solidification and coarsening in metallic alloys and ceramics\, and semiconductor growth. He received his undergraduate degree in Physics at the University of California\, Berkeley in 1997\, followed by service in the U. S. Navy’s nuclear propulsion program and work in industry. He then returned to graduate school\, completing his Ph.D. in Materials Science and Engineering at Northwestern University in 2010. This was followed by appointment as a postdoctoral researcher and Assistant Research Scientist in the Department of Materials Science and Engineering at the University of Michigan from 2010 to 2015\, after which he joined INL. \nMulti-scale modeling of the evolution of structure and properties in materials for nuclear energy applications\nNuclear energy is an important component of an overall strategy to address climate change. Idaho National Laboratory (INL) is the U.S. Department of Energy’s primary facility for research and development in nuclear science and technology for energy generation\, supporting the improvement and life extension of the existing reactor fleet and the development and licensing of new reactor designs. Computational modeling is an important component of these activities\, particularly in the area of materials for nuclear applications\, where experimental data can be very challenging and expensive to acquire\, and where data is especially scarce for new reactor designs. INL has used multi-scale modeling – linking atomistic\, mesoscale\, and engineering scales – to improve the ability to predict the performance of materials for nuclear energy applications. These modeling efforts make extensive of MOOSE (Multiphysics Object-Oriented Simulation Environment)\, a general-purpose open source finite element framework developed at INL. In this talk\, I will give an overview of the approach and tools used\, and several examples of application\, including performance of nuclear fuels\, understanding radiation-driven formation of nanoscale void and gas bubble superlattices\, and powder densification through electric field assisted sintering. \n  \n\n  \nThe MICDE Fall 2023 Seminar Series is open to all. University of Michigan faculty and students interested in predicting and explaining the properties of materials using computer simulation are encouraged to attend. \nThis seminar is cohosted by the Michigan Institute for Computational Discovery & Engineering (MICDE) and the Department of Nuclear Engineering and Radiological Sciences\, (NERS). Dr. Aagesen will be hosted by Dr. Kevin Field\, Associate Professor of Nuclear Engineering. \nThis is an in-person event. \nGraduate Certificate in Computational Discovery and Engineering\, and MICDE fellows\, please use this form to record your attendance. \n 
URL:https://micde.umich.edu/event/larry-aagesen-computational-scientist-idaho-national-laboratory-inl/
LOCATION:2150 H.H. Dow\, 2300 Hayward St\, Ann Arbor\, 48109\, United States
CATEGORIES:Featured Events,Micde Seminar,MICDE Seminar Series
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END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20231207T150000
DTEND;TZID=America/Detroit:20231207T160000
DTSTAMP:20260606T073303
CREATED:20231106T145227Z
LAST-MODIFIED:20231215T040145Z
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SUMMARY:MICDE Faculty seminar: Philip Roe\, Emeritus Professor\, Aerospace Engineering U-M
DESCRIPTION:Zoom link \nBio:  Philip Roe is an Emeritus Professor of Aerospace Engineering at the University of Michigan. He is recognized for his pioneering work in the field of Computational Fluid Dynamics and Magnetohydrodynamics. Roe made many fundamental contributions to the development of high-resolution schemes for hyperbolic conservation laws. He is best known for his work on the flux difference splitting for compressible flows with shocks\, typically referred to as the Roe scheme. \nMusings of a Computational Philosopher\nPhilosophy sets a great story by asking the right questions. Indeed a correct answer to the wrong question is seldom of any value. You can even obtain tenure\, I am told\, by asking questions that you cannot yet answer. For the past decade\, I have been trying to ask the right questions about computing compressible flow\, and I hope here to provide a glimpse of the answers. \nA “good” algorithm should “obviously” be accurate\, cheap\, and robust. Of these three desiderata\, I will try here to clarify the notion of accuracy. Although clearly a good thing\, it is almost always defined asymptotically in terms of the behavior at small mesh size or low frequency. This sets precise goals for analysis\, and although accuracy can be achieved in this sense\, in practice we often cannot afford the asymptotic regime. Moreover\, when we deal with compressible flow\, we are forced to deal with high frequencies. We require in fact only rather modest accuracy at low frequency\, but must extend this into the high frequency regime\, and doing this will require answering different questions. I will discuss a double-pronged approach to finding these questions and their answers. \nThis approach demands that the information flow in the computer should closely match that in real life. A great advance toward this was made by introducing Godunov-type methods\, but these merely distinguish left from right\, and their reliance on one-dimensional physics has many drawbacks. However\, for many kinds of problem there are integral solutions to the linear initial-value problem in multiple dimensions. My first prong is to show how these can be used to derive algorithms for linear and nonlinear problems for compressible fluid flow and other applications. These algorithms have remarkable properties\, including true incompressible limits and automatic boundary conditions. The information flow is different for advective and non-advective modes of the solution. \nAs a second way to achieve correct information flow\, I employ solution derivatives as degrees of freedom. This Hermitian representation is common in computer graphics and signal processing but almost unknown in CFD. Its great benefit consists of keeping the stencil compact. This brings about sharp discontinuities\, extends the spectrum and reduces communication overheads. Recently\, with my graduate student Iman Samani\, I have used both prongs of my approach to produce fifth-order solutions for linear elastodynamics on unstructured grids with automatic handling of material interfaces and remote boundaries. I will present these results\, summarize what remains to be done and describe some target applications.
URL:https://micde.umich.edu/event/micde-faculty-seminar-philip-roe-emeritus-professor-aerospace-engineering-u-m/
LOCATION:1109 FXB\, 1320 Beal Ave.\, Ann Arbor\, MI\, United States
CATEGORIES:Aerospace Engineering,Micde Seminar,MICDE Seminar Series,Michigan Engineering
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BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20240116T140000
DTEND;TZID=America/Detroit:20240116T150000
DTSTAMP:20260606T073303
CREATED:20230913T020425Z
LAST-MODIFIED:20240127T001751Z
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SUMMARY:MICDE / Astronomy Seminar:  Shy Genel\,  Associate Research Scientist at the Flatiron Institute\, Simons Foundation
DESCRIPTION:Bio: Dr. Shy Genel is an astrophysicist working in the field of computational galaxy formation and cosmology; he is studying how galaxies form and evolve and how they can be used to infer fundamental properties of our Universe. The main tool he employs in his research is cosmological hydrodynamical simulations\, which run on supercomputers and generate digital ‘mini-universes’ that can be analyzed in ways that are not available with observational data. In recent years he has been employing machine learning models to develop novel ways to extract information from this type of simulations.\nDr. Genel received his PhD in 2011 under the guidance of 2020 Nobel Prize in Physics laureate Prof. Reinhard Genzel at the Max-Planck-Institute for Extraterrestrial Physics in Garching\, near Munich. Between 2011-2016 he completed post-doctoral fellowships at the Harvard-Smithsonian Center for Astrophysics and at Columbia University\, and in 2016 he joined the newly-founded Center for Computational Astrophysics at the Flatiron Institute (a division of the Simons Foundation)\, where he serves today as a Research Scientist. \nCosmological Hydrodynamical Simulations and Machine Learning at the Intersection of Galaxy Formation and Cosmology\nAs galaxy surveys encode a wealth of information about the basic properties of our Universe\, improved modeling of galaxy formation will result in improved constraints on cosmology and fundamental physics. Cosmological hydrodynamical simulations\, which follow the coupled evolution of dark and ‘normal’ matter from cosmologically motivated initial conditions\, are a primary tool for studying how galaxies form. After a brief review of the revolution of the past decade in the scale and fidelity of cosmological simulations\, I will discuss a new direction the field is taking in the past few years\, where machine learning is opening new ways to extract cosmological information from the non-linear process of galaxy formation. \n  \n\n  \nThe MICDE Winter 2024 Seminar Series is open to all. University of Michigan faculty and students interested in predicting and explaining the properties of materials using computer simulation are encouraged to attend. \nThis seminar is cohosted by the Michigan Institute for Computational Discovery & Engineering (MICDE) and the Department of Astronomy\, Dr. Genel will be hosted by Dr. Monica Valluri\, Research Professor of Astronomy. \nThis is an in-person event. \nGraduate Certificate in Computational Discovery and Engineering\, and MICDE fellows\, please use this form to record your attendance. \n 
URL:https://micde.umich.edu/event/shy-genel-associate-research-scientist-flatiron-institute/
LOCATION:411 West Hall (1085 S. University)\, 1085 S. University Ave\, Ann Arbor\, MI\, 48109\, United States
CATEGORIES:Featured Events,Micde Seminar,MICDE Seminar Series
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DTSTART;TZID=America/Detroit:20240126T120000
DTEND;TZID=America/Detroit:20240126T130000
DTSTAMP:20260606T073303
CREATED:20240110T163210Z
LAST-MODIFIED:20240127T000733Z
UID:10000664-1706270400-1706274000@micde.umich.edu
SUMMARY:MICDE / CEE Seminar: Michael D. Shields\, Associate Professor of Civil & Systems Engineering at Johns Hopkins University
DESCRIPTION:Bio: Michael D. Shields is an Associate Professor in the Department of Civil & Systems Engineering at Johns Hopkins University. He holds a secondary appointment in the Department of Materials Science and Engineering\, and is a fellow of the Hopkins Extreme Materials Institute. Prof. Shields conducts methodological research in uncertainty quantification (UQ) and probabilistic modeling for problems in mechanics\, materials science\, and physics with applications ranging from multi-scale material modeling to assessing the reliability and safety of large-scale structures. He received his Ph.D. in Civil Engineering and Engineering Mechanics from Columbia University in 2010\, after which he was employed as a Research Engineer in applied computational mechanics at Weidlinger Associates\, Inc. He joined the faculty at Johns Hopkins in 2013. For his work in UQ\, Prof. Shields has been awarded the ONR Young Investigator Award\, the NSF CAREER Award\, the DOE Early Career Award\, and the Johns Hopkins University Catalyst Award. Prof. Shields and his group also develop the open-source UQpy (Uncertainty Quantification with Python) software\, which is a general toolbox and development environment for UQ in computational\, mathematical\, and physical systems. \nUQ for ML and ML for UQ: Why Uncertainty Quantification and Machine Learning Go Hand-in-Hand\nUncertainty Quantification (UQ) and Machine Learning (ML) play an increasingly important role in physics-based computational modeling. Especially with the recent rise of scientific machine learning (SciML) and physics-informed ML\, new computational tools are being harnessed to solve bigger and more challenging problems. Moreover\, UQ has become an integral part of any physics-based modeling effort because our models\, as carefully developed as they may be\, are rife with uncertainties (both epistemic and aleatory) in their parameters\, inputs/excitations\, and sometimes in the form of the models themselves. When SciML methods are then applied in these applications\, additional uncertainties are introduced. In this talk\, I will broadly introduce the interrelated roles that UQ and ML play in physics-based modeling. I specifically distinguish between “UQ for ML” and “ML for UQ” and describe the important role that each plays in the modern physics-based computational modeling paradigm – demonstrating the role of UQ/ML in various applications of interest ranging from multi-scale materials modeling to high energy-density physics. \n  \n\n  \nThe MICDE Winter 2024 Seminar Series is open to all. University of Michigan faculty and students interested in predicting and explaining the properties of materials using computer simulation are encouraged to attend. \nThis seminar is cohosted by the Michigan Institute for Computational Discovery & Engineering (MICDE) and the Department of Civil and Environmental Engineering (CEE). Dr. Shields will be hosted by Dr. Evgueni Filipov\, Associate Professor of Civil and Environmental Engineering. \nThis is an in-person event. \nGraduate Certificate in Computational Discovery and Engineering\, and MICDE fellows\, please use this form to record your attendance. \nQuestions? Email MICDE-events@umich.edu
URL:https://micde.umich.edu/event/micde-cee-seminar-michael-d-shields-associate-professor-of-civil-systems-engineering-at-johns-hopkins-university/
LOCATION:Johnson Rooms\, Lurie Engineering Center\, 3rd Floor LEC 3213ABC\, 1221 Beal Ave.\, Ann Arbor\, MI\, United States
CATEGORIES:Featured Events,Micde Seminar,MICDE Seminar Series
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DTSTART;TZID=America/Detroit:20240412T150000
DTEND;TZID=America/Detroit:20240412T160000
DTSTAMP:20260606T073303
CREATED:20240115T212036Z
LAST-MODIFIED:20240604T125820Z
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SUMMARY:MICDE/ MCAIM seminar: Boyce Griffith\, Professor at the University of North Carolina
DESCRIPTION:Bio: Boyce Griffith is a Professor in the Department of Mathematics and Department of Biomedical Engineering at the University of North Carolina\, where he is also an Adjunct Professor of Applied Physical Sciences and Associate Chair for Research in the Department of Mathematics. His research group focuses on the development and application of numerical methods for simulating fluid-structure interaction with a particular focus on models of the heart and its valves. Their core approach is based on extensions of the immersed boundary method fluid-structure interaction. \nImmersed methods for fluid-structure interaction\nThe immersed boundary (IB) method is a framework for modeling systems in which an elastic structure interacts with a viscous incompressible fluid. The fundamental feature of the IB approach to such fluid-structure interaction (FSI) problems is its combination of an Eulerian formulation of the momentum equation and incompressibility constraint with a Lagrangian description of the structural deformations and resultant forces. In conventional IB methods\, Eulerian and Lagrangian variables are linked through integral equations with Dirac delta function kernels\, and these singular kernels are replaced by regularized delta functions when the equations are discretized for computer simulation. This talk will focus on three related extensions of the IB method. I first detail an IB approach to structural models that use the framework of large-deformation nonlinear elasticity. I will focus on efficient numerical methods that enable finite element structural models in large-scale simulations\, with examples focusing on models of the heart and its valves. Next\, I will describe an extension of the IB framework to simulate soft material failure using peridynamics\, which is a nonlocal structural mechanics formulation. Numerical examples demonstrate constitutive correspondence with classical mechanics for non-failure cases along with essentially grid-independent predictions of fluid-driven soft material failure. Finally\, I will introduce a reformulation of the IB large-deformation elasticity framework that enables accurate and efficient fluid-structure coupling through a version of the immersed interface method\, which is a sharp-interface IB-type method. Computational examples demonstrate the ability of this methodology to simulate a broad range of fluid-structure mass density ratios without suffering from artificial added mass instabilities\, and to facilitate subgrid contact models. I will also present biomedical applications of the methodology\, including models of clot capture by inferior vena cava filters. \n\n  \nThe MICDE Winter 2024 Seminar Series is open to all. University of Michigan faculty and students interested in predicting and explaining the properties of materials using computer simulation are encouraged to attend. \nThis seminar is cohosted by the Michigan Institute for Computational Discovery & Engineering (MICDE)\, the Department of Mathematics and the Michigan Center for Applied and Interdisciplinary Mathematics (AIM). \nThis is an in-person event. \nGraduate Certificate in Computational Discovery and Engineering\, and MICDE fellows\, please use this form to record your attendance. \n 
URL:https://micde.umich.edu/event/workshop-seminarmicde-mcaim-seminar-prof-boyce-griffith/
LOCATION:East Hall – 1084
CATEGORIES:College Of Engineering,Computational Science,Free,Graduate School,Lsaresearch,Mathematics,Micde,Micde Seminar,MICDE Seminar Series
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DTSTART;TZID=America/Detroit:20240918T120000
DTEND;TZID=America/Detroit:20240918T130000
DTSTAMP:20260606T073303
CREATED:20240910T182150Z
LAST-MODIFIED:20241011T124420Z
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SUMMARY:Data Science/Computational Social Science/MICDE Seminar: Yian Ma\, Assistant Professor\, UC San Diego
DESCRIPTION:Bio:  Yian Ma is an assistant professor at the Halıcıoğlu Data Science Institute\, UC San Diego\, where he serves as the vice chair for the graduate programs. Prior to UCSD\, he spent a year as a visiting faculty at Google Research. Before that\, he was a post-doctoral fellow at UC Berkeley\, hosted by Mike Jordan. Yian completed his Ph.D. at the University of Washington. His current research primarily revolves around scalable inference methods for credible machine learning\, with application to time series data and sequential decision-making tasks. He has received the Facebook research award\, the Stein fellowship\, and the best paper awards at the Neurips and ICML workshops. \nMCMC\, variational inference\, and reverse diffusion Monte Carlo\nProf. Ma will introduce some recent progress toward understanding the scalability of Markov chain Monte Carlo (MCMC) methods and their comparative advantage with respect to variational inference. I will fact-check the folklore that “variational inference is fast but biased\, MCMC is unbiased but slow”. I will then discuss a combination of the two via reverse diffusion\, which holds promise of solving some of the multi-modal problems. This talk will be motivated by the need for Bayesian computation in reinforcement learning problems and the differential privacy requirements we face. \nRSVP HERE \n\n  \nThe MICDE Winter 2025 Seminar Series is open to all. University of Michigan faculty and students. \nThis is an in-person event. \nGraduate Certificate in Computational Discovery and Engineering\, please use this form to record your attendance. \nQuestions? Email MICDE-events@umich.edu
URL:https://micde.umich.edu/event/data-science-computational-social-science-micde-seminar-yian-ma-assistant-professor-uc-san-diego/
LOCATION:438 West Hall\, 1085 UNIVERSITY AVE\, Ann Arbor\, 48109\, United States
CATEGORIES:Data Science,Featured Events,Micde Seminar,MICDE Seminar Series
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DTSTART;TZID=America/Detroit:20241001T150000
DTEND;TZID=America/Detroit:20241001T160000
DTSTAMP:20260606T073303
CREATED:20240925T142215Z
LAST-MODIFIED:20241011T124325Z
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SUMMARY:MICDE/ME Seminar: Krishnan Mahesh\, Professor\, University of Michigan NAME
DESCRIPTION:Bio:  Krishnan Mahesh is a Richard B. Couch Professor of Naval Architecture and Marine Engineering at the University of Michigan. His research focuses on the simulation of complex\, multi-physics turbulent flows. Mahesh received his Bachelor’s degree in Mechanical Engineering from the Indian Institute of Technology (Mumbai)\, and in 1996 obtained his Ph.D. degree in Mechanical Engineering from Stanford University. He is a 2018 Fulbright-Nehru Specialist\, a Fellow of the American Physical Society\, an Associate Fellow of the American Institute of Aeronautics and Astronautics\, and a Fellow of the Minnesota Supercomputing Institute. Mahesh is a recipient of the CAREER Award from the National Science Foundation and the Francois N. Frenkiel Award from the American Physical Society. He has received the Taylor Award for Distinguished Research\, McKnight Presidential Fellowship\, Guillermo E. Borja Award\, and McKnight Land-Grant Professorship from the University of Minnesota. \nLarge Eddy Simulation of Turbulent Cavitating Flows\nCavitation is a complex multi-scale phenomenon that has implications from intense sound production to erosion in engineering applications. This talk will discuss our efforts at developing the large-eddy simulation capability for the simulation of turbulent cavitating flows. LES of cavitation is challenged by phase change modeling\, acoustic stiffness\, sharp multiphase fronts\, strong compressibility effects\, consistent accounting of nuclei\, broadband turbulence and subgrid effects. \nLES of partial cavitation will be discussed under the same conditions as experiments in a sharp wedge configuration.  Physical mechanisms of cavity transition observed in the experiments\, i.e.\, re-entrant jet and bubbly shock waves\, are both captured in the LES over their respective regimes. Vapor volume fraction data obtained from the LES will be quantitatively compared to X-ray densitometry\, and the results will be discussed. Cavitation nuclei are likely to be introduced through the free-stream as well as at solid surfaces. We will present a novel approach based on Gibbs free energy minimization to predict nuclei concentrations. The results from the proposed work will be applied to account for dissolved gas content in CSM measurements and predict several decades of experimentally observed trends in nuclei concentrations. Cavitating flows possess a range of vapor length scales ranging from tiny vapor bubbles to large vapor pockets. We will discuss a compressible hybrid model to capture both sub-grid vapor nuclei and massive sheet cavity dynamics. Finally\, physical aspects of inception due to the interaction of a counter–rotating vortex pair generated behind a pair of hydrofoils will be presented. \n\n  \nThe MICDE Fall 2025 Seminar Series is open to all. University of Michigan faculty and students. \nThis is an in-person event. \nGraduate Certificate in Computational Discovery and Engineering\, please use this form to record your attendance. \nQuestions? Email MICDE-events@umich.edu
URL:https://micde.umich.edu/event/micde-me-seminar-krishnan-mahesh-professor-university-of-michigan-name/
LOCATION:2150 H.H. Dow\, 2300 Hayward St\, Ann Arbor\, 48109\, United States
CATEGORIES:Computational Science,Engineering,Featured Events,Free,Mechanical Engineering,Micde Seminar,MICDE Seminar Series,Michigan Engineering,Naval Architecture and Marine Engineering
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DTSTART;TZID=America/Detroit:20260129T140000
DTEND;TZID=America/Detroit:20260129T150000
DTSTAMP:20260606T073303
CREATED:20251125T210910Z
LAST-MODIFIED:20260522T151806Z
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SUMMARY:MICDE - Mechanical Engineering Seminar - Elif Ertekin\, University of Illinois Urbana-Champaign
DESCRIPTION:Bio: Elif Ertekin is an Andersen Faculty Scholar\, Associate Professor\, and Associate Head for Graduate Programs in the Mechanical Science and Engineering Department at the University of Illinois at Urbana-Champaign. She is a faculty affiliate of the National Center for Supercomputing Applications (NCSA) and the Materials Research Laboratory (MRL). Her research interests center on the theory and modeling of materials\, with an emphasis on probabilistic and stochastic methods. She focuses on developing a microscopic understanding of atomic and electronic scale processes in materials\, with applications areas in thermal transport\, energy conversion\, and defect chemistry. She received BS degrees in Mathematics and in Engineering Science and Mechanics from Penn State\, a PhD in Materials Science and Engineering from UC Berkeley\, and she carried out post-doctoral work at the Berkeley Nanoscience and Nanoengineering Institute and the Massachusetts Institute of Technology. She is an Associate Editor for the Journal of Applied Physics and a Divisional Associate Editor for\nPhysical Review Letters. \nPhysical Mechanisms or Learned Patterns? Reconciling First-Principles Models with Machine Learning for Predictive Materials\nPredictive materials simulation has long been rooted in first-principles descriptions of physical mechanisms\, grounded in quantum mechanics but limited by tractable length scales\, sampling challenges\, and the accuracy-cost tradeoff. Today\, machine-learning methods seek to transform materials science by revealing patterns in data extending beyond conventional modeling. My talk will explore how these two paradigms\, mechanistic simulation and data-driven learning\, can act synergistically to accelerate materials discovery and understanding. I will begin by outlining what first-principles simulations can currently achieve and where their limitations arise\, using examples from our work in thermoelectrics\, wide-band-gap semiconductors\, ion-transport materials\, and structural alloys. Building on this foundation\, I will show how machine-learning approaches\, when designed with materials-specific considerations such as symmetries and invariances\, can enhance traditional methods. Examples include symmetry-aware generative models for inorganic crystalline solids and machine-learning solutions to the many-body electronic-structure problem that rival high-accuracy quantum methods. Together\, these examples highlight how integrating mechanisms and patterns can help advance predictive materials simulations.\ \n\nThe MICDE 2025-26 Seminar Series is open to all. \nThis seminar is organized by the Michigan Institute for Computational Discovery & Engineering (MICDE) and the Department of Mechanical Engineering. Prof. Ertekin will be hosted by Prof. Chenhui Shao\, Associate Professor of Mechanical Engineering. \nThis is an in-person event. This seminar will not be recorded! \nGraduate Certificate in Computational Discovery and Engineering\, and MICDE fellows\, please use this form to record your attendance. \nQuestions? Email MICDE-events@umich.edu
URL:https://micde.umich.edu/event/micde-seminar-elif-ertekin-uiuc/
LOCATION:Lurie Robert H. Engin. Ctr – Johnson Rooms (LEC 3213)
CATEGORIES:College Of Engineering,Featured Events,Mechanical Engineering,Micde,Micde Seminar,MICDE Seminar Series,Seminar
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DTSTART;TZID=America/Detroit:20260210T150000
DTEND;TZID=America/Detroit:20260210T160000
DTSTAMP:20260606T073303
CREATED:20260127T154702Z
LAST-MODIFIED:20260128T143051Z
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SUMMARY:MICDE - NERS - MIPSE Joint Seminar: Brian Haines\, Los Alamos National Laboratory
DESCRIPTION:Bio: Brian M. Haines is a Senior Distinguished Scientist in the Eulerian Codes group in the X-Computational Physics division at Los Alamos National Laboratory. He is currently the lead for the Ignition Applications project\, which includes the THOR and BrassOwl experimental campaigns on the National Ignition Facility. Brian leads the effort to produce LANL xRAGE pre-shot predictions and post-shot analysis of high-yield implosion attempts on the National Ignition Facility. Brian led the decadal effort to develop the xRAGE radiation-hydrodynamics code into a state-of-the-art tool for modeling inertial confinement fusion (ICF) and high-energy density physics experiments and has pioneered the use of xRAGE to perform large-scale high-resolution full-physics three-dimensional simulations of ICF implosions to understand the impacts of hydrodynamic instabilities and engineering features. Prior to his current position\, Brian was a Metropolis postdoc in the Methods & Algorithms group from 2011-2013 and did various internships as a student with Argonne National Laboratory\, LANL\, the National Security Agency\, and the Institute for Defense Analyses’ Center for Communications Research. Brian received a Ph.D. in mathematics from Penn State University in 2011 and a B.A. in mathematics and physics from New York University in 2006. Brian has co-authored 100 peer-reviewed publications that have received over 3\,400 citations and has been awarded a Secretary’s Honor Award from DOE\, four distinguished performance awards from LANL\, five defense program awards of excellence from NNSA\, an ICF program award from Lawrence Livermore National Laboratory (LLNL)\, and a Director’s Science and Technology Award from LLNL. \n  \nRadiation-hydrodynamics Modeling & Application to Prediction of Inertial Confinement Fusion Experiments\nThe xRAGE radiation-hydrodynamics code is a state-of-the art simulation tool for modeling inertial confinement fusion experiments. xRAGE is one of only three radiation-hydrodynamics codes developed in the U.S. with sufficient physics to credibly model both capsule implosions as well as the high-Z cylindrical hohlraums used to convert laser energy into an X-ray drive for the capsule. xRAGE solves the equations for hydrodynamics and other physics in an Eulerian reference frame and features adaptive mesh refinement\, which makes it uniquely well-suited to accurately modeling capsule defects and engineering features that are important factors limiting capsule performance. In the first half of this talk\, we will discuss the physics modeling capabilities and algorithms available in xRAGE with an emphasis on those relevant to high-energy-density physics and inertial confinement fusion. In the second half of the talk\, we will discuss the successful application of xRAGE to provide pre-shot predictions for seventeen high-yield capsule implosions on the National Ignition Facility. This will include the modeling methodology\, how we establish prediction uncertainties\, and how we have learned from prediction failures to improve the methodology. Our predictions have exhibited a 67% success rate thus far\, which is much higher than other pre-shot predictions over the same set of experiments. \n  \n\n  \nThe MICDE 2025-26 Seminar Series is open to all. \nThis seminar is organized by the Michigan Institute for Computational Discovery & Engineering (MICDE)\, the Department of Nuclear Engineering & Radiological Sciences (NERS) and the Michigan Institute for Plasma Science and Engineering (MIPSE). \nThis is an in-person event. \nGraduate Certificate in Computational Discovery and Engineering\, and MICDE fellows\, please use this form to record your attendance. \nQuestions? Email MICDE-events@umich.edu
URL:https://micde.umich.edu/event/brian-haines-los-alamos-national-laboratory/
LOCATION:Lurie Robert H. Engin. Ctr – Johnson Rooms (LEC 3213)
CATEGORIES:College Of Engineering,Featured Events,Micde,Micde Seminar,MICDE Seminar Series,Nuclear Engineering and Radiological Sciences,Seminar
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DTSTART;TZID=America/Detroit:20260317T160000
DTEND;TZID=America/Detroit:20260317T170000
DTSTAMP:20260606T073303
CREATED:20260306T144640Z
LAST-MODIFIED:20260306T144640Z
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SUMMARY:Mathematics - MICDE - MCAIM joint colloquium: Peter Bosler\, Sandia National Laboratories
DESCRIPTION:Bio:  Dr. Bosler received his B.S. degree with Honors in Oceanography from the U.S. Naval Academy in 2002. In 2002-2007\, he served as an officer in the U.S. Navy with active duty service that included both surface warfare and meteorology/oceanography operational support. Upon completing his service\, he started graduate studies at the University of Michigan and received a Ph.D. degree in Applied and Interdisciplinary Mathematics in 2013. In 2014\, he received the John von Neumann Postdoctoral Fellowship at Sandia National Laboratories\, and thereafter\, he became a staff member in the Center for Computing Research at Sandia. His projects involve close coupling between numerical methods development\, data collection\, application science\, and high-performance computing. Recent projects focus on climate modeling and plasma physics. Dr. Bosler received the Department of Energy Early Career Award for Advanced Scientific Computing in 2022 and the Presidential Early Career Award for Science and Engineering in 2025. \nAccelerating Earth System Simulation\nAbstract: Providing high-quality “actionable information” for strategic risk analysis is amongst the primary goals of the U.S. Department of Energy’s Exascale Earth System Model (E3SM). The simulation speed required to generate high-quality localized predictions at seasonal-to-decadal time scales is very high. In this talk\, we highlight some algorithmic design decisions that combine new research with classical numerical methods to enable E3SM’s ultra-high resolution configuration to achieve exascale performance and win the inaugural Gordon Bell Prize for Climate in 2023. Our design strategies tailor mathematical methods to both the unique features of the application space and to the heterogeneous computing architectures of exascale supercomputers. Ultimately\, these efforts doubled the speed of the most computationally demanding component of E3SM\, its atmosphere model. We will also discuss new and ongoing research associated with opportunities afforded by these performance gains. \n  \n\n  \nThe MICDE 2025-26 Seminar Series is open to all. \nGraduate Certificate in Computational Discovery and Engineering\, and MICDE fellows\, please use this form to record your attendance. \nQuestions? Email MICDE-events@umich.edu
URL:https://micde.umich.edu/event/math-micde-mcaim-peter-bosler-sandia/
LOCATION:1360 East Hall\, 530 Church St.\, Ann Arbor\, MI\, 48109\, United States
CATEGORIES:Climate and Space Sciences and Engineering,College Of Engineering,Featured Events,Mathematics,Mechanical Engineering,Micde,Micde Seminar,MICDE Seminar Series,Seminar
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DTSTART;TZID=America/Detroit:20260529T110000
DTEND;TZID=America/Detroit:20260529T120000
DTSTAMP:20260606T073303
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LAST-MODIFIED:20260601T195905Z
UID:10000862-1780052400-1780056000@micde.umich.edu
SUMMARY:MICDE - Mechanical Engineering seminar: Phani Motamarri\, Indian Institute of Science\, Bangalore
DESCRIPTION:Bio: Phani Motamarri is an Assistant Professor in the Department of Computational and Data Sciences at the Indian Institute of Science\, Bengaluru\, where he leads the MATRIX Lab. He is an alumnus of the University of Michigan–Ann Arbor\, where he earned his PhD in Mechanical Engineering.\nHis research lies at the intersection of computational mechanics\, materials science\, numerical analysis\, and high-performance computing. His work focuses on developing mathematical techniques and hardware-aware algorithms for quantum modeling of materials\, with applications to structural and functional materials and multiscale modeling methodologies. He is also interested in machine learning frameworks for accelerating materials discovery and quantum computing\, particularly in the context of quantum-centric supercomputing. \nProf. Motamarri’s research contributions include advances in finite-element methods\, numerical analysis\, and large-scale scientific software development. He is one of the lead developers of DFT-FE\, an open-source\, massively parallel finite-element code for density functional theory calculations. He received the ACM Gordon Bell Prize in 2023 and was a finalist for the ACM Gordon Bell Prize in 2019. \nInexact yet Accurate: Unlocking Quantum Modeling of Materials at Scale through Approximation-Tolerant Algorithms\nAbstract:  Modern computing architectures increasingly rely on iterative solvers that employ reduced-precision computation and communication-reduction techniques to lower time-to-solution and improve scalability. However\, eigensolvers in scientific simulations have struggled to exploit such approximations without compromising accuracy. We present an eigensolver R-ChFSI\, a residual-based reformulation of Chebyshev Filtered Subspace Iteration (ChFSI) provably tolerant to inexact matrix–vector products. By expressing the Chebyshev recurrence in terms of residuals rather than eigenvector estimates\, R-ChFSI naturally accommodates multiple sources of approximation\, including reduced-precision arithmetic (FP32 and TF32) in the filtering step\, lossy compression with compression ratios exceeding 4x for inter-process communication\, and approximate inverses for generalized eigenproblems\, while preserving eigensolver robustness. Large-scale experiments on GPU accelerators are conducted using finite-element discretized generalized eigenproblems arising in Kohn–Sham density functional theory for quantum modeling of materials. The results demonstrate that R-ChFSI achieves eigen-residual norms orders of magnitude smaller than standard ChFSI under comparable inexactness\, while delivering substantial performance gains. This work provides a practical pathway toward approximation-tolerant eigensolvers enabling accurate and scalable simulations on modern computing architectures. \n\nThe MICDE 2025-26 Seminar Series is open to all. \nGraduate Certificate in Computational Discovery and Engineering\, and MICDE fellows\, please use this form to record your attendance. \nQuestions? Email MICDE-events@umich.edu
URL:https://micde.umich.edu/event/micde-me-seminar-phani-motamarri-iisc/
LOCATION:1311 EECS\, 1301 Beal Ave.\, Ann Arbor\, MI\, 48109\, United States
CATEGORIES:College Of Engineering,Computational Science,Featured Events,Graduate Students,Mechanical Engineering,Micde,Micde Seminar,MICDE Seminar Series,Seminar
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