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Fixed directional convention of energy flows in thermal_simulation.py #1

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Fixed directional convention of energy flows in thermal_simulation.py #1

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20 changes: 10 additions & 10 deletions pydhn/solving/thermal_simulation.py
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Original file line number Diff line number Diff line change
Expand Up @@ -90,14 +90,14 @@ def _prepare_arrays(E, mass_flow):
edge_mask = np.where(np.abs(E).sum(axis=0) != 0)[0]
E = E[np.ix_(node_mask, edge_mask)]

E_in = (E + np.abs(E)) / 2
E_out = (np.abs(E)-E) / 2
rows = np.argmax(E, axis=0)
columns = np.argmin(E, axis=0)

# Compute total inlet mass flow of each node
mass_flow_in = E_in @ np.abs(mass_flow[edge_mask])
# Compute total outlet mass flow of each node
mass_flow_out = E_out @ np.abs(mass_flow[edge_mask])

return E, E_in, edge_mask, node_mask, rows, columns, mass_flow_in
return E, E_out, edge_mask, node_mask, rows, columns, mass_flow_out


def solve_thermal(
Expand Down Expand Up @@ -134,11 +134,11 @@ def solve_thermal(

# Initialize matrices of the network graph oriented as the mass flow:
# - E -> Incidence matrix , without 0 mass flow elements
# - E_in -> Incidence matrix of inlet edges only built from E
# - E_out -> Incidence matrix of outlet edges only built from E
E = net.incidence_matrix

arrays = _prepare_arrays(E, mass_flow)
E, E_in, edge_mask, node_mask, rows, columns, mass_flow_in = arrays
E, E_out, edge_mask, node_mask, rows, columns, mass_flow_out = arrays

dim = len(node_mask)

Expand All @@ -159,15 +159,15 @@ def solve_thermal(

jac = np.zeros((dim, dim))
for n, (i, j) in enumerate(zip(rows, columns)):
jac[i][j] = t_out_der[edge_mask][n] * np.abs(mass_flow)[edge_mask][n]
jac[i][j] = -t_out_der[edge_mask][n] * np.abs(mass_flow)[edge_mask][n]

jac -= np.diag(mass_flow_in)
jac += np.diag(mass_flow_out)

errors = np.zeros((dim, dim))
for n, (i, j) in enumerate(zip(rows, columns)):
errors[i][j] = t_out[edge_mask][n] * np.abs(mass_flow)[edge_mask][n]
errors[i][j] = -t_out[edge_mask][n] * np.abs(mass_flow)[edge_mask][n]

errors -= np.diag(mass_flow_in * t_nodes[node_mask])
errors += np.diag(mass_flow_out * t_nodes[node_mask])
errors = errors.sum(axis=1)

error = np.max(np.abs(errors))
Expand Down