most citedDevelopment of MC/DC: a performant, scalable, and portable Python-based Monte Carlo neutron transport code

2 citations · 4 across the 5 of their papers we have counts for

collaborators

5 papers

physics.comp-ph20231 cited

An effective initial particle sampling technique for Monte Carlo reactor transient simulations

Ilham Variansyah, Ryan G. McClarren

We propose a technique to effectively sample initial neutron and delayed neutron precursor particles for Monte Carlo (MC) simulations of typical off-critical reactor transients. Th…

physics.comp-ph20231 cited

High-fidelity treatment for object movement in time-dependent Monte Carlo transport simulations

Ilham Variansyah, Ryan G. McClarren

We investigate the use of time-dependent surfaces in Monte Carlo transport simulation to accurately model prescribed, continuous object movements. The performance of the continuous…

physics.comp-ph20232 cited

Development of MC/DC: a performant, scalable, and portable Python-based Monte Carlo neutron transport code

Ilham Variansyah, J. P. Morgan, Jordan Northrop +2

We discuss the current development of MC/DC (Monte Carlo Dynamic Code). MC/DC is primarily designed to serve as an exploratory Python-based MC transport code. However, it seeks to…

physics.comp-ph2022

A Quasi-Monte Carlo Method with Krylov Linear Solvers for Multigroup Neutron Transport Simulations

Sam Pasmann, Ilham Variansyah, C. T. Kelley +1

In this work we investigate replacing standard quadrature techniques used in deterministic linear solvers with a fixed-seed Quasi-Monte Carlo calculation to obtain more accurate an…

physics.comp-ph2022

Variable Dynamic Mode Decomposition for Estimating Time Eigenvalues in Nuclear Systems

Ethan Smith, Ilham Variansyah, Ryan McClarren

We present a new approach to calculating time eigenvalues of the neutron transport operator (also known as eigenvalues) by extending the dynamic mode decomposition (DMD) to all…