A5035942484- Nuclear reactor physics and engineering
- Nuclear Physics and Applications
- Nuclear Materials and Properties
- Nuclear Engineering Thermal-Hydraulics
- Graphite, nuclear technology, radiation studies
- Mathematical Approximation and Integration
- Model Reduction and Neural Networks
- Gas Dynamics and Kinetic Theory
- Radiation Effects in Electronics
- Metaheuristic Optimization Algorithms Research
- Radiation Therapy and Dosimetry
- Water Quality Monitoring and Analysis
- Fault Detection and Control Systems
- Probabilistic and Robust Engineering Design
- Radiation Detection and Scintillator Technologies
- Nuclear and radioactivity studies
- Spectroscopy and Chemometric Analyses
- Traffic Prediction and Management Techniques
- Analytical Chemistry and Sensors
- Magnetic confinement fusion research
- Quasicrystal Structures and Properties
- Nuclear physics research studies
Oregon State University
2023-2025
University of Notre Dame
2022-2023
University of Michigan
2019-2021
The Center for Exascale Monte Carlo Neutron Transport is developing / Dynamic Code (MC/DC) as a portable neutron transport package rapid numerical methods exploration on CPU- and GPU-based high-performance computers. In this paper, we describe MC/DC's current event-based GPU algorithm well the just-in-time (JIT) compilation scheme use to enable operability Nvidia AMD GPUs from Python source. To analyze performance, conduct runtime tests of C5G7 k-eigenvalue benchmark problem...
The Iterative Quasi-Monte Carlo (iQMC) method is a recently developed hybrid for neutron transport simulations. iQMC replaces standard quadrature techniques used in deterministic linear solvers with simulation accurate and efficient solutions to the equation. Previous studies utilized fixed-seed approach wherein particles were reset same initial position direction of travel at start every sweep. While QMC samples offered greatly improved uniformity compared pseudo-random samples, meant that...
An extensive study of population control techniques (PCTs) for time-dependent and eigenvalue Monte Carlo (MC) neutron transport calculations is presented. We define PCT as a technique that takes censused returns controlled, unbiased population. A new perspective based on an abstraction particle census explored, paving the way to improved understanding application concepts. Five distinct PCTs identified from literature are reviewed: simple sampling, splitting-roulette (SR), combing (CO),...
The techniques used to generate pseudo-random numbers for Monte Carlo (MC) applications bear many implications on the quality and speed of that programs work. As a random number generator (RNG) slows, production begins dominate runtime. RNG output grows in correlation, final product becomes less reliable. These difficulties are further compounded by need reproducibility parallelism. For reproducibility, generated determine any outcome must be same each time simulation is run. However,...
Morgan et al., (2024). Monte Carlo / Dynamic Code (MC/DC): An accelerated Python package for fully transient neutron transport and rapid methods development. Journal of Open Source Software, 9(96), 6415, https://doi.org/10.21105/joss.06415
The iterative Quasi–Monte Carlo (iQMC) method is a recently proposed for neutron transport simulations. iQMC can be viewed as hybrid between deterministic techniques, Monte simulation, and techniques. holds several algorithmic characteristics that make it desirable high-performance computing environments, including an O(N−1) convergence scheme, ray-tracing sweep, highly parallelizable nature similar to analog Carlo. While there are many potential advantages of using iQMC, also inherent...
Multigroup constants for deterministic methods that preserve the time-dependent physics of neutron transport equations are derived. Alternative multigroup constant weighting spectra discussed: (1) fundamental k-eigenfunction, (2) α-eigenfunction, and (3) a composite several α-modes. To generate α-eigenfunction calculating constants, static α-eigenvalue method is implemented into open source Monte Carlo code OpenMC. Several kinetic problems devised to verify implementations investigate...
We present a new approach to calculating time eigenvalues of the neutron transport operator (also known as α eigenvalues) by extending dynamic mode decomposition (DMD) allow for nonuniform steps. The method, called variable (VDMD), is shown be accurate when computing systems that were infeasible with DMD due large separation in timescales (such those occur delayed supercritical systems). an infinite medium problem neutrons, and consequently having multiple, very different relevant...
In this work we investigate replacing standard quadrature techniques used in deterministic linear solvers with a fixed-seed Quasi–Monte Carlo (QMC) calculation to obtain more accurate and efficient solutions the neutron transport equation (NTE). QMC is use of low-discrepancy sequences sample phase-space place pseudorandom number generators by traditional Monte (MC). decrease variance stochastic sweep therefore increase accuracy iterative method. Historically, has largely been ignored...
We present a new approach to calculating time eigenvalues of the neutron transport operator (also known as α eigenvalues) by extending dynamic mode decomposition (DMD) allow for nonuniform steps.The method, called variable (VDMD), is shown be accurate when computing systems that were infeasible with DMD due large separation in scales (such those occur delayed supercritical systems).The an infinite medium problem neutrons and consequently having multiple, very different relevant are...
The iterative Quasi-Monte Carlo (iQMC) method is a recently proposed for multigroup neutron transport simulations. iQMC can be viewed as hybrid between deterministic techniques, Monte simulation, and techniques. holds several algorithmic characteristics that make it desirable high performance computing environments including $O(N^{-1})$ convergence scheme, ray tracing sweep, highly parallelizable nature similar to analog Carlo. While there are many potential advantages of using also inherent...
Finding a software engineering approach that allows for portability, rapid development, open collaboration, and performance high computing on GPUs CPUs is challenge. We implement portability scheme using the Numba compiler Python in Monte Carlo / Dynamic Code (MC/DC), new neutron transport application methods development. Using this scheme, we have built MC/DC as single source, language, can run pure Python, compiled CPU, or GPU solver. In mode, use paired with an asynchronous scheduler...
We discuss the current development of MC/DC (Monte Carlo Dynamic Code). is primarily designed to serve as an exploratory Python-based MC transport code. However, it seeks offer improved performance, massive scalability, and backend portability by leveraging Python code-generation libraries implementing innovative abstraction strategy compilation scheme. Here, we verify capabilities perform initial performance assessment. found that can run hundreds times faster than its pure mode about 2.5...
We investigate the use of time-dependent surfaces in Monte Carlo transport simulation to accurately model prescribed, continuous object movements. The performance surface technique, relative typical stepping approximations and recently proposed at-source geometry adjustment is assessed by running a simple test problem involving movements an absorbing object. A figure merit analysis, measured from method's accuracy total runtime, shows that more efficient than approximations. also demonstrate...
We propose a technique to effectively sample initial neutron and delayed precursor particles for Monte Carlo (MC) simulations of typical off-critical reactor transients. The can be seen as an improvement, or alternative, the existing ones. Similar some techniques, proposed sampling uses standard MC criticality calculation. However, different from others, produces uniform-weight around user-specified target sizes. is implemented into open-source Python-based code MC/DC verified against...
The Iterative Quasi-Monte Carlo method, or iQMC, replaces standard quadrature techniques used in deterministic linear solvers with simulation for more accurate and efficient solutions to the neutron transport equation. This work explores employing iQMC Monte-Carlo Dynamic Code (MCDC) solve k-eigenvalue problems both power iteration generalized Davidson a Krylov Subspace method. Results are verified 3-D, 2-group, Takeda-1 Benchmark problem.
To find deterministic solutions to the transient $S_N$ neutron transport equation, iterative schemes are typically used treat scattering (and fission) source terms. We explore one-cell inversion iteration scheme do this on GPU and make comparisons a scheme. examine convergence behavior, through analysis of spectral radii, both iterations. further boost parallel efficiency, we derive higher-order discretization method, simple corner balance (in space) multiple time), add more work threads...
Recently, iterative Quasi-Monte Carlo (iQMC) was introduced as a new method of neutron transport which combines deterministic methods and quasi-Monte simulation for more efficient solutions to the equation. Previous iQMC results utilized uniform Cartesian grid with piecewise-constant source. Similar "teleportation error" in Implicit Monte (IMC) methods, spatial discretization source can lead significant error that limits convergence overall method. Taking concepts from IMC, we have developed...