{ "131475-21868583": { "datetime_modified":"20250120T160504", "datetime_start":"20250128T160000", "datetime_end":"20250128T170000", "has_end_time":1, "date_start":"2025-01-28", "date_end":"2025-01-28", "time_start":"16:00:00", "time_end":"17:00:00", "time_zone":"America\/Detroit", "event_title":"ME Seminar Series: Allison M. Beese", "occurrence_title":"", "combined_title":"ME Seminar Series: Allison M. Beese", "event_subtitle":"", "event_type":"Lecture \/ Discussion", "event_type_id":"13", "description":"Join us in-person or on Zoom for the ME Seminar Series\r\n\r\nAdditive Manufacturing: Machine Learning, Mechanics, and Metallurgy\r\n\r\nAllison M. Beese \u2013 Professor of Materials Science and Engineering and Mechanical Engineering; Associate Head for Diversity, Equity, Inclusion, and Belonging; Director, Additive Manufacturing & Design Graduate Program, Penn State University\r\n\r\nZoom Passcode: 690323\r\n\r\nAbstract:\r\nThe thermal histories in laser-based additive manufacturing (AM) of metal alloys results in microstructures that may contain phases, grain morphologies, or internal pores different from those seen in their conventionally processed counterparts. These microstructures dictate the resulting mechanical properties of the alloys; thus, to enable the adoption of AM for structural applications, an understanding of the links between microstructure and deformation and\/or fracture is required to reliably design against failure. In this talk, I will present our work in three general areas: using in situ process monitoring to link processing signatures to defects and mechanical properties, modeling the impact of internal defects on the multiaxial failure behavior of additively manufactured metallic materials, and the development of a framework for designing functionally graded materials in which the composition is spatially tailored to impart site-specific properties within a 3D component.\r\n\r\nBio:\r\nAllison Beese is a professor in the Department of Materials Science and Engineering at Penn State University. She also serves as Director of Penn State\u2019s Additive Manufacturing and Design graduate program and co-director of Penn State\u2019s Additive Manufacturing center (CIMP-3D). Her multiscale mechanics of materials research group focuses on using experimental and computational methods to identify and model the links between microstructural features and deformation and failure of materials, with a focus on additively manufactured metallic materials. She received her B.S. in Mechanical Engineering from Penn State, and M.S. and Ph.D. in Mechanical Engineering from MIT.", "occurrence_notes":null, "guid":"131475-21868583@events.umich.edu", "permalink":"http:\/\/events.umich.edu\/event\/131475", "building_id":"1000407", "building_name":"GG Brown Laboratory", "campus_maps_id":"21", "room":"2540 GGB", "location_name":"GG Brown Laboratory", "has_livestream":0, "cost":"", "tags":["Undergraduate Students","seminar","Michigan Engineering","Mechanical Engineering","Graduate Students"], "website":"https:\/\/umich.zoom.us\/j\/91423673184", "sponsors":[ { "group_name":"Mechanical Engineering", "group_id":"4323", "website":"https:\/\/www.facebook.com\/MechanicalEngineeringUniversityOfMichigan\/" } ], "image_url":"https:\/\/events.umich.edu\/media\/attachments\/2025\/01\/event_131475_original-1.png", "styled_images":{ "event_thumb":"https:\/\/events.umich.edu\/media\/cache\/event_thumb\/media\/attachments\/2025\/01\/event_131475_original-1.png", 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"description":"Alison Vander Roest, Ph.D.\r\nAssistant Professor\r\nBiomedical Engineering\r\nUniversity of Michigan", "occurrence_notes":null, "guid":"130048-21865179@events.umich.edu", "permalink":"http:\/\/events.umich.edu\/event\/130048", "building_id":"1000210", "building_name":"Buhl Res Cen for Human Genetics", "campus_maps_id":"22", "room":"5915", "location_name":"Buhl Res Cen for Human Genetics", "has_livestream":0, "cost":"", "tags":["Public Health","Undergraduate Students","seminar","Science","Research","Rackham","AEM Featured","Postdoctoral Research Fellows","Medicine","Life Science","Lecture","In Person","Basic Science","Biointerfaces","Biology","biomedical","biomedical engineering","Biosciences","Ecology","Education","Engineering","Free","Graduate School","Graduate Students","human genetics","Interdisciplinary"], 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"time_end":"17:00:00", "time_zone":"America\/Detroit", "event_title":"MICDE Seminar: Joshua Dolence, Research Scientist, Los Alamos National Lab", "occurrence_title":"", "combined_title":"MICDE Seminar: Joshua Dolence, Research Scientist, Los Alamos National Lab: Parthenon: a flexible framework for rapid development of performance portable multiphysics codes", "event_subtitle":"Parthenon: a flexible framework for rapid development of performance portable multiphysics codes", "event_type":"Workshop \/ Seminar", "event_type_id":"21", "description":"Bio: Josh Dolence is a scientist in the Computational Physics & Methods Group at Los Alamos National Laboratory and a founding member of the LANL Michigan SPARC, a permanent LANL presence at U-M in Ann Arbor. Before joining LANL, he received a PhD in Astronomy from UIUC in 2011 and spent three years in Astrophysical Sciences at Princeton University where he worked in computational astrophysics, studying topics like black hole accretion and supernovae. More recently, he leads the Methods for Multiscale, Multiphysics Accelerated Prediction project for LANL\u2019s Advanced Simulation and Computing Program, focusing efforts on enabling unprecedented fidelity and scale in modeling complex systems like high energy density physics experiments.\r\n\r\nAbstract: In many areas of computational science, developing new, state-of-the-art capabilities has become a high-cost, risky proposition. The complexity and diversity of models, methods, algorithms, and machines often lead to fundamental challenges in designing and building codes that enable advances in science and engineering. In fields like high energy density physics and astrophysics, multi-physics simulations leveraging adaptive meshes, particles, and a variety of numerical methods are foundational to progress but difficult to realize performantly on ever-evolving high-performance computing platforms. In this talk, I will present the Parthenon framework, an open-source code base that aims to facilitate the development of highly adaptive multi-physics codes that are fast, scalable, and capable of leveraging modern platforms with both CPUs and GPUs. I will describe the basic principles behind its design and some of its most enabling features and highlight the ~10 downstream codes it already supports.", "occurrence_notes":null, "guid":"131060-21867662@events.umich.edu", "permalink":"http:\/\/events.umich.edu\/event\/131060", "building_id":"1000397", "building_name":"Lurie Robert H. Engin. Ctr", "campus_maps_id":"90", "room":"3213ABC, Johnson Rooms", "location_name":"Lurie Robert H. Engin. 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