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Sepehr
2026-02-22 23:27:31 +01:00
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@@ -113,19 +113,33 @@ All types support: `__repr__`, `__str__`, `__float__`, `__eq__`, `__add__`, `__s
| `FlowSource` | `(pressure_pa, temperature_k)` | Boundary source |
| `FlowSink` | `()` | Boundary sink |
### Solver
### Solver Configurations
| Config | Constructor | Description |
|-----------|------------|-------------|
| `NewtonConfig` | `(max_iterations, tolerance, line_search, timeout_ms, initial_state, use_numerical_jacobian, jacobian_freezing, convergence_criteria, timeout_config, previous_state, ...)` | Newton-Raphson settings |
| `PicardConfig` | `(max_iterations, tolerance, relaxation, initial_state, timeout_ms, convergence_criteria)` | Picard / Seq. Substitution settings |
| `FallbackConfig` | `(newton, picard)` | Fallback behavior |
| `ConvergenceCriteria`| `(pressure_tolerance_pa, mass_balance_tolerance_kgs, energy_balance_tolerance_w)`| Detailed component criteria |
| `JacobianFreezingConfig`| `(max_frozen_iters, threshold)`| Speeds up Newton-Raphson |
| `TimeoutConfig` | `(return_best_state_on_timeout, zoh_fallback)`| Behavior on timeout limit |
### Solver Running
```python
# Newton-Raphson (fast convergence)
config = entropyk.NewtonConfig(max_iterations=100, tolerance=1e-6, line_search=True)
# Strategy Enum approach
strategy = entropyk.SolverStrategy.newton(max_iterations=100, tolerance=1e-6)
# Or
strategy = entropyk.SolverStrategy.picard(relaxation=0.5)
# Picard / Sequential Substitution (more robust)
config = entropyk.PicardConfig(max_iterations=500, tolerance=1e-4, relaxation=0.5)
result = strategy.solve(system) # Returns ConvergedState
# Fallback (Newton → Picard on divergence)
config = entropyk.FallbackConfig(newton=newton_cfg, picard=picard_cfg)
result = config.solve(system) # Returns ConvergedState
# Legacy Config approach
config = entropyk.FallbackConfig(
newton=entropyk.NewtonConfig(max_iterations=100),
picard=entropyk.PicardConfig(max_iterations=500)
)
result = config.solve(system)
```
### Exceptions