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DTSTART;TZID=America/Detroit:20231011T110000
DTEND;TZID=America/Detroit:20231011T120000
DTSTAMP:20260605T080441
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
ATTACH;FMTTYPE=image/png:https://micde.umich.edu/wp-content/uploads/2023/09/LANL-Logo.png
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BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20231012T110000
DTEND;TZID=America/Detroit:20231012T130000
DTSTAMP:20260605T080441
CREATED:20230915T150330Z
LAST-MODIFIED:20231018T173554Z
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SUMMARY:SciML Webinar Justin Beroz: A closed-form mathematical framework for modeling turbulent fluids
DESCRIPTION:Speaker: Justin Beroz (ReynKo Inc.) \n\nSession Chair: Varun Shankar (Physics Inverted Mataerials) \nAbstract: Despite significant advances over the past two centuries\, a complete general mathematical framework for turbulent fluid motion has yet to be put forth\, and remains the longest standing unsolved problem in classical physics. I will present such a framework\, which is based on constructing a spectral decomposition for the fluid’s kinetic energy from first principles. The approach departs from the usual Reynolds decomposition and yields a set of closed and solvable ordinary differential equations in matrix form. Within this prescription\, the linear terms in the Navier-Stokes equations correspond to a symmetric matrix operator\, and the nonlinear convective term enters as an anti-symmetric operator that provides coupling between eigenstates of turbulent fluctuation. Specifically\, I will present a derivation for the turbulent energy spectrum\, including the Kolmogorov energy cascade; elucidate instability mechanisms for the transition to turbulence;  and detail the analytical solution for turbulence in a box. Careful attention will be given to the physical picture and scaling\, in addition to the rigorous mathematical program. The talk will conclude with a forward look into current efforts implementing the model into a numerical simulation within my company\, ReynKo Inc.
URL:https://micde.umich.edu/event/workshop-seminarsciml-webinar-justin-beroz/
LOCATION:MI
CATEGORIES:Micde,Scientific Computing,Sciml,SciML Webinar Series,Webinar
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BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20231019T110000
DTEND;TZID=America/Detroit:20231019T130000
DTSTAMP:20260605T080441
CREATED:20230915T150343Z
LAST-MODIFIED:20231025T194805Z
UID:10000646-1697713200-1697720400@micde.umich.edu
SUMMARY:SciML Webinar Ji Qi: DImensionality-Reduced Encoded Clusters with sTratified (DIRECT) sampling for Robust Training of Machine Learning Interatomic Potentials
DESCRIPTION:https://umich.zoom.us/j/95111677727?pwd=V1Q5MkUwT2NpOFVhd0ZRVGR1YTM3Zz09 \n\nSpeaker: Ji Qi (UC San Diego and LLNL)\nSession Chair: Daniel Schwalbe-Koda (UC Los Angeles) \nAbstract: Machine learning interatomic potentials (MLIPs) enable accurate simulations of materials at scales beyond conventional first-principles approaches\, and they have played increasingly important roles in understanding and design of materials. However\, MLIPs are only as accurate and robust as the data they are trained on. In this seminar\, I will present DImensionality-Reduced Encoded Clusters with sTratified (DIRECT) sampling as an approach to select a robust training set of structures from a large and complex configuration space. By applying DIRECT sampling on the Materials Project relaxation trajectories dataset with over one million structures and 89 elements\, we develop an improved materials 3-body graph network (M3GNet) universal potential that extrapolate more reliably to unseen structures. We further show that molecular dynamics (MD) simulations with universal potentials such as M3GNet can be used in place of expensive ab initio MD to rapidly create a large configuration space for target materials systems. For demonstration\, we combined this scheme with DIRECT sampling to develop a reliable moment tensor potential for titanium hydrides without the need for iterative augmentation of training structures. \nIn this seminar\, I will walk through two Jupiter notebooks to showcase DIRECT sampling with the two example cases demonstrated in our manuscript\, so that audience can expect to reproduce our major results with no trouble. Hopefully\, DIRECT sampling will serve as a straightforward\, efficient\, useful plug-in for the robust training of MLIPs across any compositional complexity.
URL:https://micde.umich.edu/event/workshop-seminarsciml-webinar-ji-qi-2/
LOCATION:MI
CATEGORIES:Micde,Scientific Computing,Sciml,SciML Webinar Series,Webinar
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BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20231026T110000
DTEND;TZID=America/Detroit:20231026T130000
DTSTAMP:20260605T080441
CREATED:20231017T170318Z
LAST-MODIFIED:20231107T231334Z
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SUMMARY:SciML Webinar: Bowen Deng - CHGNet: pretrained universal interatomic potential to study electron coupled ionic systems.
DESCRIPTION:https://umich.zoom.us/j/95111677727?pwd=V1Q5MkUwT2NpOFVhd0ZRVGR1YTM3Zz09 \n\nSpeaker: Bowen Deng (UC Berkeley)\nSession Chair: Sakidja Ridwan (Missouri State University) \nAbstract: Large-scale simulations with complex electron interactions remain one of the greatest challenges for atomistic modeling. Although classical force fields often fail to describe the\ncoupling between electronic states and ionic rearrangements\, the more accurate ab-initio molecular dynamics suffers from computational complexity that prevents long-time and large-\nscale simulations\, which are essential to study technologically relevant phenomena. Our work presents the Crystal Hamiltonian Graph Neural Network (CHGNet)\, a graph-neural-\nnetwork-based machine-learning interatomic potential (MLIP) that models the universal potential energy surface. CHGNet is pretrained on the energies\, forces\, stresses\, and magnetic moments\nfrom the Materials Project Trajectory Dataset\, which consists of over 10 years of density functional theory calculations of ∼ 1.5 million inorganic structures. The explicit inclusion of\nmagnetic moments enables CHGNet to learn and accurately represent the orbital occupancy of electrons\, enhancing its capability to describe both atomic and electronic degrees of freedom.\nWe demonstrate several applications of CHGNet in solid-state materials and energy storage applications.
URL:https://micde.umich.edu/event/sciml-webinar-bowen-deng/
LOCATION:MI
CATEGORIES:Micde,Scientific Computing,Sciml,SciML Webinar Series,Webinar
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BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20231027T160000
DTEND;TZID=America/Detroit:20231027T170000
DTSTAMP:20260605T080441
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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