Hayes Stripling

  • Academic Institution: Texas A&M University
  • Program Year: 4
  • Practicum(s):
    Lawrence Livermore National Laboratory (2010)
    Argonne National Laboratory (2011)
  • Degree(s):
    B.S. Nuclear Engineering, Texas A&M University, 2009
  • Field of Study: Nuclear Engineering/Uncertainty Quantification
  • Academic Advisor: Marvin Adams

Summary of Research:

I am interested in the development and implementation of Uncertainty Quantification (UQ) methods for large-scale scientific computing applications. I completed the M.S. degree in Nuclear Engineering in December 2010. My Masters thesis described a framework, called the Method of Manufactured Universes (MMU), which can be used to help validate statistical UQ methods as applied to a simulation with myriad sources of error and uncertainty. We showed that an approach guided by MMU can expose misleading results given by “black-box” UQ methods and help a modeler tailor a general statistical approach to his/her specific problem.

My Ph.D. research is focused on the estimation of error and uncertainty in realistic nuclear reactor calculations. Specifically, I am focused on the development of adjoint algorithms and software that will scale towards the proposed Exascale platforms. The adjoint technique is a well-suited tool for addressing the critical UQ questions posed in the reactor design process; however, adjoint algorithms tend to be memory-intensive, posing interesting challenges for implementation on next generation, memory-limited architectures. I am working on the (co-‍)design, analysis, and implementation of software that will begin to address the challenges of Exascale and will be useful for advanced reactor design.

Publications:

Stripling, HF, Anitescu, M, and Adams, ML. A Generalized Adjoint Framework for Sensitivity and Error Estimates in Nuclear Engineering Applications. Submitted for review to the Annals of Nuclear Engineering Special Edition on Uncertainty Quantification.

Stripling, HF and McClarren, RG. A Calibration and Data Assimilation Method using the Bayesian MARS Emulator. Submitted for review to the Annals of Nuclear Engineering Special Edition on Uncertainty Quantification.

Stripling, HF, Adams, ML, McClarren, RG, and Mallick, BK. The Method of Manufactured Universes for Testing Uncertainty Quantification Methods. Reliability Engineering and Safety Systems. Appeared October 2010.

Conference Paper: Stripling, HF, McClarren, RG, Kuranz, CC and Grosskopf, M. Calibration of Uncertain Inputs to Computer Models using Experimentally Measured Quantities and the BMARS Emulator. The International Conference on Mathematics and Computational Methods applied to Nuclear Science and Engineering. Rio de Janeiro, Brazil. May 2011.

Conference Paper: Stripling, HF and McClarren, RG. Bayesian MARS for Uncertainty Quantification in Stochastic Transport Problems. The International Conference on Mathematics and Computational Methods applied to Nuclear Science and Engineering. Rio de Janeiro, Brazil. May 2011.

Podium Presentation: Stripling, HF and McClarren, RG. Gradient Enhanced Bayesian MARS for Regression and Uncertainty Quantification. American Nuclear Society Fall Meeting, Washington DC. October 2011.

Podium Presentation: Stripling, HF, Adams, ML, McClarren, RG, and Mallick, BK. The Method of Manufactured Universes for Testing Uncertainty Quantification Methods. ANS Student Conference, April 2010. Ann Arbor Michigan.

Poster Presentation: Stripling, HF and Johannesson, G. A Survey of BMARS Applications in Uncertainty Quantification. Lawrence Livermore National Laboratory Summer Student Symposium. First place, Graduate Student in Computation.

Poster Presentation: Stripling, Hayes, and Ryan McClarren. Calibrating Uncertain Inputs to Computer Models using a BMARS Emulator. Presented at the annual CRASH review at the University of Michigan.

Poster Presentation: Stripling, Hayes, Marvin Adams, and Ryan McClarren. The Method of Manufactured Universes for Testing Uncertainty Quantification Schemes. Presented at the 2009 Winter Meeting of the American Nuclear Society in Washington DC.

Awards:

Runner-Up: 6th Annual DOE CSGF Essay Competition. Essay appeared in the 2011 edition of DEIXIS magazine (available online).

First Place: Student Poster Symposium, Lawrence Livermore National Laboratory. August 2010.

Craig C. Brown Outstanding Senior Engineer Award - Given to 5 seniors each year in the College of Engineering based on proven excellence in academics, leadership, and character.

Fellow, Roy G. Post Foundation (2010).