Systems and Design Codes
Systems codes use reduced physics and engineering models to size a whole device rapidly, exploring the trade space before detailed simulation.
The whole-machine sizing problem
Before high-fidelity physics simulation, a designer must decide the rough size, field, current, and power of a device. A systems code answers this with a network of reduced models, plasma physics scalings, magnet engineering limits, heat-exchange balances, and geometric constraints, that together size a self-consistent machine in seconds rather than the weeks a full simulation takes.
The reduced models are deliberately simple: confinement from empirical scaling laws, magnet stress from analytic formulas, power balance from lumped terms. The point is breadth, not depth, scanning thousands of candidate designs to find the feasible region.
Constraints and optimization
A systems code enforces constraints, stay below the density limit, keep magnet stress under the material allowable, close the power balance, and searches for designs that satisfy all of them. This is naturally an optimization problem over the machine parameters.
The role in the design chain
Systems codes sit at the top of the design hierarchy. They identify promising operating points that higher-fidelity equilibrium, transport, and stability codes then scrutinize. Findings from those detailed codes feed back to recalibrate the reduced models, closing the loop between speed and fidelity.
Design relevance
The frozen parameters of the Hyperion breeder, a spherical tokamak at 9.86 MA plasma current with an 8 T on-axis field and 16.84 T peak, and of the Aegis and MetroVolt burner with its 26.49 T plug, are the kind of top-level quantities a systems study fixes before detailed physics simulation refines them. All remain design values, not measured performance.
- Reduced physics and engineering models
- Sizes a whole machine rapidly
- Enforces constraints and optimizes parameters
- Feeds candidate points to high-fidelity codes