OWEN — Open Workflow for Engineered Neutronics
Text editor + 3D viewer for MCNP, OpenMC, and Serpent decks with templates, linting, and quick previews.
- • Smart snippets for tallies, cells, surfaces
- • Syntax-aware highlighting by code family
- • Quick inserts for materials & sources
- • 3D viewport for geometry checks
- • Layer toggles and fast refresh
- • Ready-to-run example decks included
Choose Your Monte Carlo Code
Each code has unique strengths. MCNP for industry applications, OpenMC for Python-based research, and SERPENT for reactor physics and burnup analysis.
MCNP
Industry Standard
Monte Carlo N-Particle code from Los Alamos National Laboratory. Decades of validation for regulatory and safety analysis.
The industry standard for regulatory submissions and safety analysis. Excels at shielding design, complex geometry modeling, and coupled neutron-photon transport calculations.
Start MCNP TutorialOpenMC
Modern & Open Source
Modern Python-based Monte Carlo code developed at MIT. Ideal for research and computational workflows.
Ideal for researchers who need Python integration and automated workflows. Well-suited for depletion studies, burnup calculations, and rapid prototyping of reactor models.
Start OpenMC TutorialSERPENT
Reactor Physics Specialist
Continuous-energy Monte Carlo code optimized for reactor physics. Advanced burnup and group constant generation.
Optimized for lattice physics and few-group constant generation. Particularly strong in fuel depletion analysis, reactor core modeling, and producing group constants for nodal diffusion codes.
Start SERPENT TutorialMaster Monte Carlo Simulation for Nuclear Engineering
ReactorMC provides structured tutorials for MCNP, OpenMC, and SERPENT—the three most widely used Monte Carlo codes in nuclear engineering. Learn particle transport, reactor physics, and radiation analysis through practical examples and comprehensive theory.
Why Monte Carlo Methods?
Exact Geometry
Model complex 3D geometries without approximations. Handle curved surfaces and intricate structures with mathematical precision.
Statistical Rigor
Built-in uncertainty quantification with every result. Statistical confidence that improves with computational effort.
Physical Accuracy
Solve transport equations with minimal assumptions. Use detailed nuclear data for accurate particle interactions.
What You'll Learn
Theory & Mathematics
Master probability theory and random sampling techniques. Understand the Boltzmann transport equation and how Monte Carlo methods solve it. Learn to work with nuclear cross-section data and perform statistical analysis on simulation results.
Practical Skills
Develop proficiency in geometry modeling and tally design. Apply variance reduction methods to improve simulation efficiency. Analyze and validate output results for reactor physics and shielding applications.
Your Learning Path
Start with Theory
Build a strong foundation in Monte Carlo fundamentals before diving into code-specific tutorials. Understanding probability theory, transport physics, and variance reduction will make you proficient in any Monte Carlo code.
Our fundamentals section covers probability and random sampling, neutron transport theory, geometry modeling, and tally scoring. These concepts form the mathematical and physical basis for all Monte Carlo codes.
Explore TheoryThen Practice
Apply theory through hands-on tutorials with real reactor models. Each code tutorial includes annotated input files, step-by-step instructions, and explanations of output.
Tutorials progress from simple spheres to fuel pins, then lattice structures, and finally complete reactor assemblies. Source definitions advance from point sources to distributed sources and criticality eigenvalue problems. Tally techniques build from basic scoring to mesh tallies and variance reduction methods.
Typical Learning Timeline
Most engineers achieve basic proficiency in 2-4 weeks, working through simple input files and geometry models. Within 1-3 months, you'll build complete reactor models and analyze tally output. Advanced topics like variance reduction and optimization typically require 3-6 months of focused practice.
Monte Carlo Applications
Reactor Physics
Calculate criticality eigenvalues and map flux distributions throughout reactor cores. Model fuel burnup over time and determine control rod worth for safety analysis.
Shielding Analysis
Design radiation shields and calculate dose rates in complex geometries. Analyze streaming paths and optimize detector response for radiation protection applications.
Safety & Criticality
Evaluate fuel handling safety and model accident scenarios. Quantify uncertainties in safety margins and ensure regulatory compliance for nuclear facilities.
Research Applications
Apply Monte Carlo methods to medical physics, fusion neutronics, space radiation environments, and nuclear security challenges.
Popular Step-by-Step Examples
Jump straight into practical examples. Each tutorial walks through complete models with working code.
PWR Pin Cell
Complete pin cell geometry with fuel, gap, cladding, and moderator. Includes tallies and k-effective calculation.
View Example →Fuel Assembly
17×17 PWR assembly with lattice structures, guide tubes, and realistic enrichment patterns.
View Example →MCNP Terminology
Master essential MCNP concepts, definitions, and vocabulary before diving into input files.
Learn Terms →Python Pin Cell
Build a fuel pin model with Python. Includes materials, geometry, and automatic plotting capabilities.
View Example →Assembly Model
17×17 assembly using Python and lattices. Shows advanced OpenMC features and result visualization.
View Example →Cell Creation
Master OpenMC cell creation with boolean operations, fills, and complex geometry techniques.
View Guide →Parallel Computing
Configure MPI/OpenMP runs, batching, and scaling guidance for cluster executions.
Run Faster →SERPENT Pin Cell
Basic pin geometry with SERPENT syntax. Includes detectors and output analysis.
View Example →Assembly Example
Full assembly model with lattices and burnup capabilities for reactor physics analysis.
View Example →Troubleshooting
Common SERPENT errors, warnings, and solutions. Debug your models efficiently.
Debug Tips →Geometry Fundamentals
Universal geometry concepts applicable to all Monte Carlo codes. CSG, surfaces, and cells.
Learn Theory →