SteadyState.solve()

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fullflow.SteadyState.solve

Solve the network steady-state nonlinear system.

solve() adjusts network iteration variables until all component and balance residual equations satisfy the requested residual tolerance.

The nonlinear system is solved using scipy.optimize.least_squares().

Parameters

Name	Type	Description
model	str, optional	Model to solve. If omitted, all registered Models use their currently active option.
evaluate_all_model_options	bool, optional	If True, attempts every option in the selected Model and returns successful solutions.
filename	str, optional	Output file used to save results.
return_type	{"dict", "dataframe"}, optional	Format of returned solution data.
verbose	bool, optional	Print solver diagnostics.
static	bool, optional	Perform a static evaluation instead of a nonlinear solve.
print_solution	bool, optional	Print exported solution values.
solver_method	{"trf", "dogbox", "lm"}, optional	Nonlinear least-squares algorithm.
jacobian_method	{"2-point", "3-point"}, optional	Finite-difference Jacobian scheme.
ftol	float, optional	Cost-function convergence tolerance.
xtol	float, optional	Variable convergence tolerance.
gtol	float, optional	Gradient convergence tolerance.
rtol	float, optional	Maximum acceptable residual magnitude.
state_max_passes	int, optional	Maximum number of state-settling passes.
state_tolerance	float, optional	Convergence tolerance for derived-state propagation.

Returns

Name	Type	Description
solution	dict or pandas.DataFrame	Solved network results.