# plant-model

PWR plant model (point kinetics + lumped thermal-hydraulics) and
mode-specific continuous controllers for the HAHACS preliminary example.

## Overview

A 10-state coupled neutronics + thermal-hydraulics model in MATLAB:

- 6 delayed neutron precursor groups (U-235 thermal fission, Keepin)
- Lumped fuel, core coolant, and SG/cold-leg thermal nodes
- Steam generator heat removal `Q_sg(t)` as the bounded disturbance input
- Doppler and moderator temperature reactivity feedback
- External rod reactivity `u` as the controllable input

State vector: `x = [n; C1..C6; T_f; T_c; T_cold]` (10 states). See
`CLAUDE.md` for the naming convention.

## Quick Start

Open MATLAB in this directory and run:

```matlab
main
```

The default scenario runs two simulations of a 100% → 80% SG demand step:
once with `ctrl_null` (plant feedback only) and once with `ctrl_operation`
(proportional rod reactivity on T_avg error), and plots the comparison.

## Files

| File | Role |
|------|------|
| `main.m` | Entry point — scenario config and run |
| `pke_params.m` | Plant parameters and steady-state derivation |
| `pke_th_rhs.m` | Dynamics `ẋ = f(t, x, plant, Q_sg, u)` |
| `pke_initial_conditions.m` | Analytic steady-state `x0` |
| `pke_solver.m` | Closed-loop driver — takes a controller function handle |
| `plot_pke_results.m` | 4-panel results plot |
| `load_profile.m` | SG heat demand shapes |
| `controllers/ctrl_null.m` | `u = 0` baseline |
| `controllers/ctrl_operation.m` | Stabilizing mode: P on `T_avg` |

## Controllers

Controllers share a single signature:

```matlab
u = ctrl_<mode>(t, x, plant, ref)
```

Returns scalar `u` (external rod reactivity in `dk/k`). The solver swaps
controllers via function handle:

```matlab
[t, X, U] = pke_solver(plant, Q_sg, @ctrl_operation, ref, tspan);
```

Additional modes (`ctrl_heatup`, `ctrl_scram`, `ctrl_shutdown`) will land in
`controllers/` following the same signature.

## Running Different Scenarios

Swap `Q_sg` in `main.m`:

```matlab
% Step down to 90% at t = 10s
Q_sg = @(t) plant.P0 * (1.0 - 0.1 * (t >= 10));

% Interpolated time series
t_data = [0, 100, 200, 300];
q_data = [1.0, 0.85, 0.9, 1.0] * plant.P0;
Q_sg = @(t) interp1(t_data, q_data, t, 'linear', 'extrap');
```

Swap the controller:

```matlab
[t, X, U] = pke_solver(plant, Q_sg, @ctrl_null, [], tspan);
```

Change the reference (for modes that use one):

```matlab
ref.T_avg = plant.T_c0 + 5;   % track 5 C above nominal
```

## Requirements

MATLAB (R2020b or newer, tested on R2025b). Uses `ode15s` from base MATLAB
— no toolboxes required.