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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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DTSTART;TZID=America/Detroit:20231127T140000
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SUMMARY:Women in Computational Science Mini-Symposium (DISCOVER)
DESCRIPTION:Women in Computational Science\n			\n				\n				\n				\n				\n				The Women in Computational Science Symposium is the inaugural event for MICDE’s DISCOVER (Diversity and Innovation in Scientific Computing: Opportunities for Valuing Exploration and Representation) mini-symposium series. This mini-symposium provides a unique opportunity to delve into the pioneering research conducted by women in computational science while also gaining insight into their personal experiences and the challenges they face as researchers.\nThis year’s Women in Computational Science Symposium features: \nKeynote speaker: Katrin Heitmann\, Deputy Division Director Argonne National Laboratory – @ 3 pm\nBio: Katrin Heitmann is the deputy director of Argonne’s High Energy Physics division\, and a physicist and computational scientist. She is also a Senior Associate for the Kavli Institute for Cosmological Physics at the University of Chicago and a member of NAISE at Northwestern. Before joining Argonne\, Katrin was a staff member at Los Alamos National Laboratory. Her research currently focuses on computational cosmology\, in particular on trying to understand the causes for the accelerated expansion of the Universe. She is responsible for large simulation campaigns with HACC and for the tools in the associated analysis library\, CosmoTools. Katrin is a member of several major astrophysical surveys that aim to shed light on this question and is currently the Spokesperson for the LSST Dark Energy Science Collaboration. \nExploring the Dark Universe \nCosmology – the study of the origin\, evolution\, and constituents of the Universe – is now entering one of its most scientifically exciting phases. Three decades of surveying the sky have culminated in the celebrated “Cosmological Standard Model”. Yet\, two of its key pillars\, dark matter\, and dark energy – together accounting for 95% of the mass-energy of the Universe – remain mysterious. Next-generation observatories will open new routes to understand the true nature of the “Dark Universe”. These observations will pose tremendous challenges on many fronts – from the sheer size of the data that will be collected to its modeling and interpretation. The interpretation of the data requires sophisticated simulations on the world’s largest supercomputers. The cost of these simulations\, the uncertainties in our modeling abilities\, and the fact that we have only one Universe that we can observe opposed to carrying out controlled experiments\, all come together to create a major test for statistical methods of data analysis. In this talk\, I will give a brief introduction to the Dark Universe and outline the challenges ahead. I will describe how complex\, large-scale simulations will be used to extract the cosmological information from ongoing and next-generation surveys. \nGuest speakers @ 2 pm\nLiz Livingston\, PhD candidate in Mechanical Engineering and Scientific Computing at U-M \nTitle: Data to Differential Equations – Discovering Mathematical Models for Biological Systems \nBio: Liz Livingston is a 5th year PhD candidate in Mechanical Engineering and Scientific Computing at the University of Michigan\, advised by Professor Krishna Garikipati and Professor Alberto Figueroa. Her research focuses on data-driven modeling of biological systems. This work spans a range of topics including biomechanics\, numerical methods\, and high-performance computing. She received her BS and MS degrees from the University of Illinois at Urbana-Champaign where she studied the strength and microstructure of bone. Liz enjoys teaching and cultivates this interest through hands-on experience\, outreach\, and involvement in the American Society for Engineering Education (ASEE). \nAbstract: Complex phenomena\, such as those observed in biological systems\, can typically be modeled with partial differential equations (PDEs). Finding governing equations can be a daunting task\, often involving simplifications to the system such that the PDE does not fully capture the physics of the problem. Instead of reducing the complexity of the system with successive approximations\, the governing PDE can be discovered using data. One of the fastest and most popular techniques is machine learning\, where a surrogate is found as an approximation to the function. Alternatively\, inference techniques may be used to identify the strong or weak form of the governing equation via parameter estimation. The tools we develop for the discovery of governing equations have applications in many complex systems\, including biological ones such as flow through a stenosed artery and fracture in soft tissues. The goal of my PhD thesis is to develop and improve these mathematical methods to help expand our understanding of complex biological systems. \n  \nRachel Niemer\, Managing Director of WISE (Women in Science and Engineering) \nTitle: Who is WISE for and what should we do? Exploring levers of change to foster equity in STEM \nWISE info: The University of Michigan is at the forefront of equality in science and engineering\, and our focus on diversity\, equity\, and inclusion spans multiple dimensions\, including gender\, race\, SES\, first generation status\, to name a few. The University of Michigan’s Women in Science and Engineering (WISE) unit aims to increase the participation by women and gender minorities in careers in science\, technology\, engineering and mathematics\, and to foster their academic and professional success. We do this by cultivating students’ skills to thrive in STEM\, strengthening the community working toward STEM equity\, and working to mitigate systemic forces that impede retention of women\, and individuals from other historically underrepresented groups\, in STEM. \nAbstract: As we look at the evolving landscape of where women\, and other individuals from historically marginalized groups\, thrive and persist in STEM\, it makes sense to ask why more progress hasn’t been made. Women in Science and Engineering has been a resource for U-M students in STEM since 1980. Over that time\, WISE\, and similar units at other institutions\, have experimented with a range of interventions to help women thrive in STEM. What if we chose the wrong levers for change? Are there radically new ways we might support efforts to graduate more STEM majors from minoritized communities? This presentation will explore different models for advancing STEM equity. \nPanel discussion on navigating scientific careers – @ 4:10 pm\n\n\n\nKatrin Heitmann\, Deputy Division Director Argonne National Laboratory\nLisa Mesaros\, Vice President\, Product Management\, Simulation and Test Solutions at Siemens Digital Industries Software\nLiz Livingston\, Clare Boothe Luce Fellow & PhD candidate in Mechanical Engineering and Scientific Computing\, University of Michigan\nRachel Niemer\, Managing Director of WISE (Women in Science and Engineering)\, University of Michigan
URL:https://micde.umich.edu/event/conference-symposiummicde-discover-mini-symposium/
LOCATION:West Hall – 340
CATEGORIES:Discover,DISCOVER Series,Featured Events,Micde,Micde Seminar
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