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Suggested Citation:"Appendix A: Registered Workshop Participants." National Academies of Sciences, Engineering, and Medicine. 2016. Predictive Theoretical and Computational Approaches for Additive Manufacturing: Proceedings of a Workshop. Washington, DC: The National Academies Press. doi: 10.17226/23646.
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Appendix A

Registered Workshop Participants

Corbett Battaile, Sandia National Laboratories

Joseph Beaman, University of Texas at Austin

Joe Bishop, Sandia National Laboratories

Jian Cao, Northwestern University

Gengdong Cheng, Dalian University of Technology

Steve Daniewicz, Mississippi State University

Anthony DeCarmine, Oxford Performance Materials

Edward Dobner, Deloitte Consulting

Tahany El-Wardany, United Technologies Research Center

Marianne Francois, Los Alamos National Laboratory

Edward Garboczi, National Institute of Standards and Technology

Slade Gardner, Lockheed Martin Space Systems Company

Edward Glaessgen, National Aeronautics and Space Administration Langley Research Center

Xu Guo, Dalian University of Technology

Rainer Hebert, University of Connecticut

Martin Heinstein, Sandia National Laboratories

Neil Hodge, Lawrence Livermore National Laboratory

Linda Horton, United States Department of Energy Office of Science

David M. Keicher, Sandia National Laboratories

Saad Khairallah, Lawrence Livermore National Laboratory

Wayne King, Lawrence Livermore National Laboratory

Lyle E. Levine, National Institute of Standards and Technology

Suggested Citation:"Appendix A: Registered Workshop Participants." National Academies of Sciences, Engineering, and Medicine. 2016. Predictive Theoretical and Computational Approaches for Additive Manufacturing: Proceedings of a Workshop. Washington, DC: The National Academies Press. doi: 10.17226/23646.
×

Feng Lin, Tsinghua University

Wing Kam Liu, Northwestern University

Li Ma, National Institute of Standards and Technology

Ade Makinde, GE Global Research Center

Kalman Migler, National Institute of Standards and Technology

Peter Olmsted, Georgetown University

Tim Osswald, University of Wisconsin–Madison

Zhijian Pei, Kansas State University

Alonso Peralta-Duran, Honeywell International Inc.

Kara Peters, North Carolina State University

Michael Plesniak, The George Washington University

Richard Ricker, National Institute of Standards and Technology

Anthony Rollett, Carnegie Mellon University

Edwin Schwalbach, Air Force Research Laboratory

Yung C. Shin, Purdue University

John Siemon, Alcoa Technical Center

Ole Sigmund, Technical University of Denmark

David Snyder, QuesTek Innovations

David Stepp, United States Army Research Laboratory

Amy Sun, Lockheed Martin Space Systems Company

Stuart Trouton, Deloitte Consulting

John Turner, Oak Ridge National Laboratory

Max Voegler, Deutsche Forschungsgemeinschaft

Gregory Wagner, Northwestern University

Ian Wing, Deloitte Consulting

Kristopher Wise, National Aeronautics and Space Administration Langley Research Center

Peter Wriggers, Leibniz Universität

Yu-Ping Yang, EWI

Suggested Citation:"Appendix A: Registered Workshop Participants." National Academies of Sciences, Engineering, and Medicine. 2016. Predictive Theoretical and Computational Approaches for Additive Manufacturing: Proceedings of a Workshop. Washington, DC: The National Academies Press. doi: 10.17226/23646.
×
Page 129
Suggested Citation:"Appendix A: Registered Workshop Participants." National Academies of Sciences, Engineering, and Medicine. 2016. Predictive Theoretical and Computational Approaches for Additive Manufacturing: Proceedings of a Workshop. Washington, DC: The National Academies Press. doi: 10.17226/23646.
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Page 130
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 Predictive Theoretical and Computational Approaches for Additive Manufacturing: Proceedings of a Workshop
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Additive manufacturing (AM) methods have great potential for promoting transformative research in many fields across the vast spectrum of engineering and materials science. AM is one of the leading forms of advanced manufacturing which enables direct computer-aided design (CAD) to part production without part-specific tooling. In October 2015 the National Academies of Sciences, Engineering, and Medicine convened a workshop of experts from diverse communities to examine predictive theoretical and computational approaches for various AM technologies. While experimental workshops in AM have been held in the past, this workshop uniquely focused on theoretical and computational approaches and involved areas such as simulation-based engineering and science, integrated computational materials engineering, mechanics, materials science, manufacturing processes, and other specialized areas. This publication summarizes the presentations and discussions from the workshop.

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