Uncertainty Quantification in Materials Modeling

July 28 - 31, 2015

Content

Overview

Advisory:

Please note, this workshop will take place at Purdue University in West Lafayette, Indiana.

Poster:

SW7.28-31.15_poster.pdf

Organizers:

Mark Benedict	US Air Force Research Laboratory
Andrea Browning	The Boeing Company
Stephen Christensen	The Boeing Company
Andrew Dienstfrey	National Institute of Standards and Technology
Paul Patrone	University of Minnesota, Twin Cities
Frederick Phelan Jr.	National Institute of Standards and Technology
Alejandro Strachan	Purdue University

Over the past few decades, modeling tools have advanced to the point where it is possible to routinely predict material properties, often before experiments are ever carried out. Armed with this knowledge, industries and research institutions alike are leading innovative theoretical studies to identify both high-performance materials and reduce time- and cost-to-market. However, the cutting-edge nature of this research means that modeling approaches are often pushed to their limit, and increasingly, there is a need for methods that can validate theoretical predictions before they are used for decision-making. In this context, uncertainty quantification (UQ) enters as a valuable tool that can address issues related to uncertainty propagation, model calibration and deficiency, optimal sampling techniques, and verification / validation of computer codes, to name a few.

This hot topics workshop is aimed at (i) providing hands on UQ experience to scientists in materials modeling, while (ii) exposing experts in UQ to some of the unique challenges in this realm of applications. The program will feature lectures and labs that give a foundation in basic UQ skills, gradually framing the discussion in terms of relevant applications. By the end of the third day, participants will have performed UQ calculations on problems across multiple length scales in materials science, with an emphasis on the multiscale nature of the phenomena. The workshop ends with a series of academic lectures on hot topics and recent advances at the intersection of both fields.

Accomodations

Participants will be staying in the Hilton Garden Inn West Lafayette Wabash Landing. Please call 765-743-2100 to make a reservation and use code UQMMM for the special rate by June 29.

Location

Parking and transportation will be provided to participants by email. Registration and the first three days of talks will take place in:

Hall for Discovery and Learning Research (DLR)
207 S. Martin Jischke Drive
West Lafayette, IN 47907

Last day of the workshop will take place in:

Neil Armstrong Hall of Engineering (ARMS)
701 W. Stadium Avenue
West Lafayette, IN 47907

Schedule

Tuesday, July 28, 2015

8:30 am - 9:30 am	Welcome, Registration, and Computer Checkout
9:30 am - 12:00 pm	Introduction to nanoHUB and Uncertainty Quantification Alejandro Strachan (Purdue University)	DLR Room 131
12:00 pm - 1:30 pm	Lunch
1:30 pm - 5:00 pm	Roles of Uncertainty Quantification in Materials Science Ralph Smith (North Carolina State University)	DLR Room 131

Wednesday, July 29, 2015

8:30 am - 12:00 pm	Introduction to Gaussian Process Regression Ilias Bilionis (Purdue University)	DLR Room 131
12:00 pm - 1:30 pm	Lunch
1:30 pm - 5:00 pm	Application of UQ Principles to Calibration, Sensitivity, and Experimental Design Omar Knio (Duke University)	DLR Room 131

Thursday, July 30, 2015

8:30 am - 12:00 pm	Designing Pseudopotentials for Density Functional Theory Kevin Garrity (National Institute of Standards and Technology)	DLR Room 143 A&B
12:00 pm - 1:30 pm	Lunch
1:30 pm - 5:00 pm	The Role of Uncertainty Quantification in Model Verification and Validation David Riha (Southwest Research Institute)	DLR Room 143 A&B

Friday, July 31, 2015

8:30 am - 9:10 am	State of the Art and Recent Progress in Uncertainty Quantification for Electronic Systems (i.e. Variation-Aware or Stochastic Simulation) Luca Daniel (Massachusetts Institute of Technology)	ARMS Room 1010
9:10 am - 9:50 am	Optimal Filters for High-Speed Compressive Detection in Spectroscopy Greg Buzzard (Purdue University)	ARMS Room 1010
9:50 am - 10:30 am	Quantifying the Influence of Conformational Uncertainty in Biomolecular Solvation Using a L1 Minimization with Basis Rotation Algorithm Guang Lin (Purdue University)	ARMS Room 1010
10:30 am - 10:45 am	Break
10:45 am - 11:00 am	Lecture Daniel Pantuso (Intel Corporation)	ARMS Room 1010
11:00 am - 11:15 am	Pertinent and Exciting Uncertainty Quantification Problem Spaces in Materials and Manufacturing Amanda Criner (US Air Force Research Laboratory)	ARMS Room 1010
11:15 am - 11:30 am	Sensitivity Analysis of Multiscale Reaction Networks with Stochastic Averaging Araz Hashemi (University of Delaware)	ARMS Room 1010
11:30 am - 11:45 am	Uncertainty Quantification in Glass Properties Prediction Adama Tandia (Corning Incorporated)	ARMS Room 1010
11:45 am - 12:00 pm	Uncertainty in Composite Material Development Matthew Jackson (Cytec)	ARMS Room 1010
12:00 pm - 12:15 pm	Lecture Samuel Tucker (The Boeing Company)	ARMS Room 1010
12:15 pm - 12:30 pm	Closing Remarks

Participants

Name	Department	Affiliation
Gerard Awanou	Mathematics, Statistics, and Computer Science Department	University of Illinois, Chicago
Mark Benedict		US Air Force Research Laboratory
Ilias Bilionis	School of Mechanical Engineering	Purdue University
Ben Blaiszik	Computation Institute	University of Chicago
Greg Buzzard	Department of Mathematics	Purdue University
Carlos Cardoso Borges	Department of Mathematics	Courant Institute of Mathematical Sciences
Rozlyn Chambliss		The Boeing Company
Faical Yannick Congo	Department of Computer Science	Blaise Pascal University
Amanda Criner		US Air Force Research Laboratory
Luca Daniel	Department of Electrical Engineering and Computer Science	Massachusetts Institute of Technology
Michael DePersio	Department of Mathematics	University of Delaware
Andrew Dienstfrey	Applied and Computational Mathematics Division	National Institute of Standards and Technology
Carla Estridge		The Boeing Company
Weifu Fang	Department of Mathematics & Statistics	Wright State University
Kevin Garrity	Materials Measurement Lab	National Institute of Standards and Technology
Nathan Gibson	Department of Mathematics	Oregon State University
Zeaid Hasan		The Boeing Company
Araz Hashemi	Department of Mathematical Sciences	University of Delaware
Adam Hinkle	Materials Science	Johns Hopkins University
Kyle Huston	Department of Chemical Engineering	University of Michigan
Matthew Jackson		Cytec
Omar Knio	Mechanical Engineering and Materials Science	Duke University
Guang Lin	Department of Mathematics	Purdue University
Nithin Mathew	Department of Chemistry	University of Missouri
Sungkwang Mun	Center for Advanced Vehicular Systems	Mississippi State University
Daniel Pantuso		Intel Corporation
Paul Patrone	Institute for Mathematics and its Applications	University of Minnesota, Twin Cities
Frederick Phelan Jr.	Materials Science and Engineering Division	National Institute of Standards and Technology
Eugene Ragasa	Material Science and Engineering	University of Florida
David Riha	Mechanical Engineering Division	Southwest Research Institute
Vyacheslav Romanov	National Energy Technology Laboratory	Department of Energy
Thomas Rosch		National Institute of Standards and Technology
Puttha Sakkaplangkul	Department of Mathematics	Oregon State University
Jeffrey Sanders	Materials Science	Schrodinger, Inc.
Piyush Singh	Mechanical Science and Engineering	University of Illinois at Urbana-Champaign
Ralph Smith	Department of Mathematics	North Carolina State University
Alejandro Strachan	School of Materials Engineering	Purdue University
James Sturnfield	E&PS- Process Optimization	Dow Chemical Company
Adama Tandia	Department of Modeling and Simulation	Corning Incorporated
Krishnaprasad Thirunarayan	Department of Computer Science and Engineering	Wright State University
Carlos Tolmasky	Institute for Mathematics and its Applications	University of Minnesota, Twin Cities
Samuel Tucker		The Boeing Company
Wayne Isaac Uy	Center for Applied Mathematics	Cornell University
Erik von Schwerin	Department of Mathematical Sciences	University of Delaware
Lingle Wang		Schrodinger, Inc.
Xufeng Wang	Department of Electrical and Computer Engineering	Purdue University