Create hardy_cross_solver.py

hardy_cross_solver.py

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+import numpy as np
+import pandas as pd
+
+def hardy_cross_solver(pipes_data, loops, max_iterations=10, tolerance=0.001):
+    df = pd.DataFrame(pipes_data)
+    df['area'] = np.pi * (df['diameter'] / 2) ** 2
+    df['R'] = (df['friction_factor'] * df['length']) / (df['diameter'] * 2 * 9.81 * df['area'] ** 2)
+    df['Q'] = df['initial_flow']
+    iteration_results = []
+    for iteration in range(max_iterations):
+        max_delta_Q = 0
+        for loop_id, loop_pipes in loops.items():
+            loop_df = df[df['pipe_id'].isin(loop_pipes)].copy()
+            loop_df['sign'] = loop_df.apply(lambda row: 1 if row['loop_id'] == loop_id else -1, axis=1)
+            loop_df['RQ_absQ'] = loop_df['R'] * loop_df['Q'] * np.abs(loop_df['Q']) * loop_df['sign']
+            loop_df['nR_absQ'] = 2 * loop_df['R'] * np.abs(loop_df['Q'])
+            numerator = loop_df['RQ_absQ'].sum()
+            denominator = loop_df['nR_absQ'].sum()
+            delta_Q = - numerator / denominator
+            df.loc[df['pipe_id'].isin(loop_pipes), 'Q'] += delta_Q * loop_df['sign']
+            max_delta_Q = max(max_delta_Q, abs(delta_Q))
+            iteration_results.append({
+                'iteration': iteration + 1,
+                'loop_id': loop_id,
+                'delta_Q': delta_Q,
+                'max_delta_Q': max_delta_Q,
+                'numerator': numerator,
+                'denominator': denominator,
+                'Q_values': df[['pipe_id', 'Q']].to_dict(orient='records')
+            })
+        if max_delta_Q < tolerance:
+            break
+    return iteration_results, df[['pipe_id', 'Q']]