For decades, MCNP has been the gold standard for Monte Carlo particle transport—trusted, validated, and extremely powerful, but notoriously difficult to visualize and debug.
The Monte Carlo N-Particle (MCNP) code, developed at Los Alamos National Laboratory, is a general-purpose Monte Carlo radiation transport code capable of simulating neutrons, photons, electrons, and coupled physics problems across complex geometries.
MCNP models are defined using a text-based input deck that describes geometry using constructive solid geometry (CSG), material definitions, sources, tallies, and physics options. This approach has remained largely unchanged for decades—by design.
MCNP predates modern graphical modeling tools. Its text-based geometry system was designed for flexibility, precision, and reproducibility—not visualization.
Using planes, cylinders, spheres, and Boolean operations, MCNP can represent extremely complex geometries. However, understanding what a deck actually describes requires deep experience and careful inspection.
MCNP geometry exists implicitly in text form. Users must mentally reconstruct 3D geometry from Boolean expressions involving dozens—or hundreds—of surfaces.
Errors such as overlapping cells, voids, or incorrect surface sense often only appear at runtime, leading to long debug cycles and repeated trial-and-error runs.
Tamarack does not replace MCNP—it enhances it. Tamarack provides a modern environment that preserves MCNP’s trusted input format while making geometry visible, understandable, and verifiable.
Tamarack brings decades-old MCNP workflows into a modern, visual environment without compromising accuracy or trust.
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