PhD Thesis

UQ of Monte Carlo XS Generation for HTRs

Ann Arbor, MI

Advised by Prof. Thomas Downar

Aug 2023

  • Thesis title: Quantification and Minimization the Uncertainty Propagation of Monte Carlo Cross Section Generation for HTR Applications
  • Developed an analytic UQ methods based on perturbation theory for UQ of MC generated XS, implemented in AGREE
  • Developed a stochastic UQ methods based on randomly sampling for UQ of MC generated XS, implemented with Dakota, coupled with AGREE and SAM
  • Monte Carlo-Deterministic hybrid methods for HTR neutronics analysis, SAM system code for thermal-hydraulics simulation
  • Methods were demonstrated on HTR-10 steady-state benchmark and gFHR steady-state / transient simulations
  • UQ
  • MC XS
  • Hybrid method
  • HTR


Argonne National Laboratory Summer Intern

Lemont, IL

Graduate Research Aid

May 2022 - Aug 2022

  • SAM code development using C++ and MOOSE framework, implemented a control rod module with spacial effect
  • Implemented a numerical ODE solver to solve xenon/iodine Bateman equations
  • Created demo cases and unit tests for the newly implemented module/solver
  • gFHR neutronics/thermo-fluids modeling and simulation
  • C++
  • MatLab
  • Python

North Carolina State University Summer Intern

Raleigh, NC

Undergraduate Student Intern

Aug 2018 - Sept 2018

  • Sensitivity analysis and uncertainty quantification
  • Developed C++/Python scripts to calculate sensitivity and covariance data
  • Developed MatLab scripts to quantify uncertainty and create plots
  • SFR neutronics modeling and simulation
  • C++
  • MatLab
  • Python


RSOR - Linear Solver Preconditioner

  • Implemented RSOR (Reduced Successive Over Relaxation) preconditioner for banded matrices, improving run time by ~25%
  • The method was applied in the numerical library Futility to improve the performance of linear solvers
  • C++
  • Fortran


  • Implemented a linear prolongation approach to accelerate the convergence of CMFD (Coarse Mesh Finite Difference) solver by ~30% iterations, the stability was also improved
  • The algorithm was applied in reactor simulation code MPACT
  • Fortran


gFHR Modeling and Simulations

  • Fluoride-cooled High-temperature Reactor (FHR), pebble-bed based design
  • Monte Carlo - Deterministic Hybrid Method with Serpent 2 code and AGREE code
  • Coupled neutronics / thermo-fluids simulation of the core and primary/secondary loops using system analysis code SAM
  • Model development for the Digital Twin (DT) training


  • Molten Salt Reactor Experiment modeling and simulation
  • Neutronics simulation using hybrid method with Serpent/Shift and PARCS


  • Development of the transient capability for the NEAMS neutronics code PROTEUS
  • Modeling and Simulation of the SPERT experimental benchmark


  • Jin Li, et al. “Uncertainty Propagation and Quantification of Monte Carlo Cross Section Generation for HTR Applications.” Nuclear Science and Engineering (submitted)
  • Jin Li, et al. “Neutronics and Thermo-fluids Simulation of gFHR with Monte Carlo-Deterministic Hybrid Methods.” Nuclear Technology (submitted)
  • Jin Li, et al. “Neutronics and Thermal-Hydraulics Simulation of Generic Pebble-Bed Fluoride-Salt-Cooled High-Temperature Reactor (gFHR).” PHYSOR (2022)
  • Kaitlyn Barr, et al. “Verification of AGREE and Serpent for the Steady State HTR-10 Benchmark Problems.” PHYSOR (2022)
  • Jin Li, et al. “Neutronics Simulation of the Molten Salt Reactor Experiment with Serpent/Shift and PARCS.” Mathematics & Computation (2021)
  • Jin Li, et al. “Demonstration of a Linear Prolongation CMFD Method on MOC.” PHYSOR (2020)
  • Yugao Ma, et al. “Neutronics and thermal-hydraulics coupling analysis in accelerator-driven subcritical system.” Progress in Nuclear Energy (2020)
  • Won Sik Yang, et al. “Development of Transient Capabilities for the NEAMS Neutronics Code PROTEUS.” NEUP report DOE-PUR-0008561 (2019)
  • Ishita Trivedi, et al. “Impact of Nuclear Data Uncertainties on Lead-cooled Fast Reactor Simulations.” Best Estimate Plus Uncertainty (2018)
  • Yiran Wang, Jin Li. “Research on the Monte Carlo Simulation Methods of ADS MYRRHA.” Reactor Physics Asia (2017)
  • Xiaotong Shang, et al. “Subcritical Multiplication Factor and Burnup Analysis of ADS with RMC.” ANS Winter Meeting (2017)

Jin Li


New PhD grad (Aug 2023) major in nuclear engineering. Good at math, data analysis and programming, interested in advanced nuclear reactor design, modeling and simulation, multi-physics coupled analysis, reactor physics code development. Seeking positions for reactor core research and development.


    • Doctor of Philosophy (2023)
    • Nuclear Engineering and Radiological Sciences
    • GPA = 3.926
    • University of Michigan, Ann Arbor
      Bachelor of Engineering (2018)
    • Engineering Physics
    • Tsinghua University, China


    • Reactor Simulation Code
    • Serpent
    • MCNP
    • PARCS
    • OpenMC
    • SAM
    • AGREE
    • MPACT
    • MOOSE Framework
    • C++
    • Python
    • MATLAB
    • Fortran
    • C
    • Bash/Zsh
      Developer Tools
    • Linux system
    • Git
    • Docker
    • Conda
    • CMake/XMake
    • LaTeX
    • Markdown
    • Microsoft Office
    • Adobe Tools


  • Tennis
  • Ski
  • Cooking
  • Building website