Menu

NSE - Nuclear Science & Engineering at MIT

FAQ | Contact | Jobs | NSE Policies

PEOPLE

Benoit Forget

Benoit Forget

Associate Professor of Nuclear Science and Engineering

bforget@mit.edu
617-253-1655
617-258-8863 (fax)
24-214

MIT Computational Reactor Physics Group
OpenMC
Consortium for Advanced Simulation of Light Water Reactors (CASL)

Bio

Education

PhD, Georgia Institute of Technology, 2006
MS, École Polytechnique de Montréal, 2003
B.S., École Polytechnique de Montréal, 2003

Awards

  • Landis Young Member Engineering Achievement Award, American Nuclear Society, 2013
  • Ruth and Joel Spira Award for Distinguished Teaching
  • ANS Faculty/PIA Teaching Award

Research

Prof. Forget’s research interests are in the areas of computational reactor physics, radiative transport, and high performance computing. He is also the founder of the Computational Reactor Physics Group (CRPG).

Monte Carlo transport methods

Monte Carlo neutron transport methods have long been considered a reference solution since they model explicitly the random walk of neutrons in a nuclear system using the fundamental nuclear data. Recent advances in computing power bring these methods closer to performing realistic core analysis and design. CRPG has developed an open source Monte Carlo code, OpenMC, to perform large scale reactor analysis on modern computing architecture. CRPG focuses on the development of novel algorithms for improving the parallel efficiency of Monte Carlo methods, new communication schemes to reduce network load for massive tallies, and improved nuclear models to reduce memory requirements and increase fidelity. Current work is also focused on the analysis of inter-cycle correlations and the automation of Monte Carlo to achieve a given target accuracy.

Deterministic transport methods

In addition to the Monte Carlo work, CRPG has also developed new concepts to attain high-fidelity 3D deterministic simulations. This work has led to the development of OpenMOC, a 3D method of characteristics code designed for efficient multi-threading and low memory requirement. This project seeks to reduce current bottlenecks limiting the applicability of such methods to full core analysis, and develop new acceleration schemes for more efficient analysis.

Multiphysics coupling

CRPG also focuses on the development of methods enabling coupling of reactor physics codes with fuel performance or thermal-hydraulics codes for both steady-state and transient analysis. Current work focuses on the coupling of OpenMC with external frameworks using novel techniques to transfer information to irregular meshes and use returning temperature distributions within the Monte Carlo simulations. This work also focuses on the development of new approaches for dealing with the temperature dependence of nuclear data as to provide accurate feedback.

Uncertainty Quantification

CRPG is also exploring the area of nuclear data uncertainties by looking at the sensitivity of resonance parameters and the propagation of uncertainties on a given nuclear system. This information will not only provide a measure of uncertainty for quantities of interest, but can also better inform nuclear data evaluators for future data releases.

Publications

J. Miao, B. Forget, K.S. Smith, “Analysis of correlations and their impact on convergence in Monte Carlo eigenvalue simulations,” Annals of Nuclear Energy, 92, 81-95, 2016.

J. Tramm, G. Gunow, T. He, K. Smith, B. Forget, A. Siegel, “A task-based parallelism and vectorized approach to 3D Method of Characteristics reactor simulation for high performance computing architectures,” Computer Physics Communications, 202, 141-150, 2016.

W. Boyd, A. Siegel, B. Forget, K. Smith, “Parallel Performance Results for the OpenMOC Neutron Transport Code on Multi-Core Platforms,” International Journal of High Performance Computing Applications, 30, 3, pp. 360-375, 2016.

C. Josey, P. Ducru, B. Forget, K. Smith, “Windowed Multipole for Cross Section Doppler Broadening,” Journal of Computational Physics CASL Special Issue, 307, 715-727, 2015.

V. Sobes, L. Leal, G. Arbanas, B. Forget, “Nuclear Data Adjustment Based on Integral Experiments,” Nuclear Science and Engineering, accepted 2016.

B.R. Herman, B. Forget, K. Smith, “Progress towards Monte Carlo — Thermal Hydraulic Coupling using Low-Order Nonlinear Diffusion Acceleration Methods,” Annals of Nuclear Energy, special issue, 84, 63-72, 2015.

J. Roberts, M. Everson and B. Forget, “On the Convergence of the Eigenvalue Response Matrix Method,” Nuclear Science and Engineering, 181(3), 331-34, 2015.

J. Walsh, P. Romano, B. Forget, K. Smith, “Optimizations of the Energy Grid Search Algorithm in Continuous-Energy Monte Carlo Particle Transport Codes,” Computer Physics Communications, 196, pp. 134-142, 2015.

L. Li, K. Smith, B. Forget, R. Ferrer, “LOO: A Low-order Nonlinear Transport Scheme for Acceleration of Method of Characteristics,” Journal of Nuclear Science and Technology, PHYSOR 2014 Special Issue — Invited paper, 52, Issue 7-8, 2015.

P. Romano, N. Horelik, B. Herman, A. Nelson, B. Forget, K. Smith, “OpenMC: A state-of-the-art Monte Carlo code for research and development,” Annals of Nuclear Energy, special issue, 82, 90-97, 2015.

Patents

B. Forget and F. Rahnema, "Boundary Adjusted Critical Spectrum Methodology for Reactor Lattice Depletion", US Patent 7676015 Issued on March 9th, 2010.

Teaching

22.05 Neutron Science and Reactor Physics
22.13 Nuclear Energy Systems
22.211 Nuclear Reactor Physics I
22.212 Nuclear Reactor Physics II

News

Recent News

Department of Nuclear Science & Engineering

Massachusetts Institute of Technology
77 Massachusetts Avenue, 24-107, Cambridge, MA 02139
nse-info@mit.edu

Copyright © 2016 Department of Nuclear Science and Engineering