Hayes Stripling

  • Program Years: 2009-2013
  • Academic Institution: Texas A&M University
  • Field of Study: Nuclear Engineering/Uncertainty Quantification
  • Academic Advisor: Marvin Adams
  • Practicum(s):
    Lawrence Livermore National Laboratory (2010)
    Argonne National Laboratory (2011)
  • Degree(s):
    Ph.D. Nuclear Engineering, Texas A&M University, 2013
    M.S. Nuclear Engineering, Texas A&M University, 2010
    B.S. Nuclear Engineering, Texas A&M University, 2009

Current Status

  • Status: Research Engineer, ExxonMobil, Houston TX
  • Research Area: Computational Science and High Performance Computing
  • 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

    Fred A. Howes Scholar Award, DOE CSGF Program, 2014

    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).