Scoping and Point-Design Codes
Scoping codes rapidly evaluate candidate machine parameters using analytic scalings, mapping the operating space before detailed design begins.
Fast exploration
Before committing to a detailed design, engineers need to understand how choices like size, field, and current interact. Scoping codes use analytic scalings and zero- or one-dimensional models to evaluate a candidate machine in fractions of a second, enabling exploration of vast parameter spaces.
The scaling backbone
At the heart of a scoping code are empirical scaling laws, most importantly the energy-confinement-time scaling derived from experimental databases. Combined with a power balance and geometric relations, these scalings let the code estimate performance for any point in the design space without solving the full physics.
Outputs
- Estimated confinement and fusion performance for each candidate
- Operating-space maps in density, temperature, and field
- Identification of which constraint binds at each design point
- Sensitivity of performance to key assumptions
Reading the maps
The value of scoping is not a single answer but a map: it shows where in the design space a machine can operate, which constraints are active, and how robust a candidate is to changes in assumptions. A design sitting on the edge of an operating window is flagged as fragile.
Honest limits
Scoping codes inherit the uncertainty of the scalings they use, which are extrapolations from existing machines. For compact or unconventional designs, those extrapolations can be shaky, so scoping results are treated as hypotheses to test with higher-fidelity codes, not as commitments.
Spherical tokamaks and other compact concepts are precisely the cases where confinement scaling carries the most uncertainty, so scoping outputs for such machines are always paired with the caveat that first-principles verification is required.