Update app.py

more tolerance options

app.py

@@ -24,7 +24,6 @@ st.markdown(
     unsafe_allow_html=True
 )
 
-# Datos iniciales
 R = 10.73
 components = {
     'CO2': {'Tc': 547.91, 'Pc': 1071.0, 'omega': 0.2667, 'vol_shift': 0.0344, 'm_w': 0},
@@ -95,17 +94,15 @@ if selected_components:
 # Normalizar concentraciones
 ci = np.array([concentrations[comp] for comp in selected_components])
 if np.sum(ci) > 0:
-    ci /= np.sum(ci)  # Normalizar para que la suma sea 1
+    ci /= np.sum(ci)
 else:
     st.error("The sum of the concentrations must be greater than 0.")
 
-# Entradas para temperatura y presión
 T = st.slider("Temperature (°F):", min_value=-100.0, max_value=300.0, value=160.0) + 459.67
 P = st.slider("Pressure (psia):", min_value=50.0, max_value=5000.0, value=2000.0)
 
 # Add a dropdown menu for tolerance selection
 def generate_super_script(number):
-    """Genera una cadena con superíndices para un número dado."""
     superscript_map = {
         '0': '⁰',
         '1': '¹',
@@ -117,11 +114,11 @@ def generate_super_script(number):
         '7': '⁷',
         '8': '⁸',
         '9': '⁹',
-        '-': '⁻'  # Superíndice para el signo menos
+        '-': '⁻'  
     }
     return ''.join(superscript_map.get(char, char) for char in str(number))
 
-# Generar opciones de tolerancia desde 10^-1 hasta 10^-14
+# tolerance from 10^-1 to 10^-14
 tolerance_options = {}
 for exponent in range(1, 15):
     label = f"10{generate_super_script(-exponent)}"
@@ -134,7 +131,6 @@ tolerance = tolerance_options[selected_tolerance_label]
 # Display the selected tolerance
 st.write(f"Selected Tolerance: {selected_tolerance_label} ({tolerance})")
 
-# Extraer propiedades críticas
 Pci = np.array([components[comp]['Pc'] for comp in selected_components])
 Tci = np.array([components[comp]['Tc'] for comp in selected_components])
 omega = np.array([components[comp]['omega'] for comp in selected_components])
@@ -239,11 +235,11 @@ def calculate_z_factor(P, T, ci, Pci, Tci, omega):
 
 def calculate_mixture_density(P, Z, T, mole_fractions, MWs, b_vol_shifts):
     molar_density = P / (Z * R * T)  # lb-mole/ft³
-    print(f"Molar Density (without correction): {molar_density:.6f} lb-mole/ft³")
+    #print(f"Molar Density (without correction): {molar_density:.6f} lb-mole/ft³")
 
     # Step 2: Mixture volume shift parameter
     b_mixture = sum(x * b for x, b in zip(mole_fractions, b_vol_shifts))
-    print(f"Mixture Volume Shift: {b_mixture:.6f} ft³/lb-mole")
+    #print(f"Mixture Volume Shift: {b_mixture:.6f} ft³/lb-mole")
 
     # Step 3: Corrected molar density
     try:
@@ -254,11 +250,11 @@ def calculate_mixture_density(P, Z, T, mole_fractions, MWs, b_vol_shifts):
 
     # Step 4: Average molecular weight
     M_avg = sum(x * mw for x, mw in zip(mole_fractions, MWs))
-    print(f"Average Molecular Weight (M_avg): {M_avg:.6f} lb/lb-mole")
+    #print(f"Average Molecular Weight (M_avg): {M_avg:.6f} lb/lb-mole")
 
     # Step 5: Mass density
     mass_density = corrected_molar_density * M_avg  # lb/ft³
-    print(f"Mass Density: {mass_density:.6f} lb/ft³")
+    #print(f"Mass Density: {mass_density:.6f} lb/ft³")
 
     return corrected_molar_density, mass_density
 
@@ -293,9 +289,6 @@ def calculate_fugacity_coefficients(Z, A, B, ai, bi, a_m, b_m, ci, kij):
     return phi
 
 def ssm_method(P, T, ci, kij, components, tol=1e-3, max_iter=100):
-    #Pci = np.array([components[comp]['Pc'] for comp in components])
-    #Tci = np.array([components[comp]['Tc'] for comp in components])
-    #omega = np.array([components[comp]['omega'] for comp in components])
 
     Ki = np.exp(5.37 * (1 + omega) * (1 - Tci / T))
 
@@ -324,7 +317,7 @@ def ssm_method(P, T, ci, kij, components, tol=1e-3, max_iter=100):
             print("Warning: The method did not converge. Last values:")
             print(f"Z_liq={Z_liq}, Z_vap={Z_vap}, phi_liq={phi_liq}, phi_vap={phi_vap}")
 
-    print("Advertencia: No se logró la convergencia.")
+    print("Warning: Convergence was not achieved.")
     return Ki, None, None, None, None, max_iter
 
 if selected_components: