Merge pull request #20 from mdidomiz/main

cleanup and prep for release 1.0

Author: mdidomiz

.gitignore

@@ -1,9 +1,7 @@
 # Editor directories and files
 .vscode/*
 .venv/*
-*.DS_Store
+.DS_Store
 
 # Logs
 *.log
-
-.DS_Store

MANUAL.pdf

@@ -3,28 +3,29 @@
 from scipy.integrate import solve_ivp
 
 # Constants
-stefan_boltzmann_constant = 5.67e-8
-initial_temperature = 293 # make sure it is in kelvins
-k_steel = 45  # Thermal conductivity of steel in W/mK
+stefan_boltzmann_constant = 5.67e-8 # (W/m^2K^4)
+initial_temperature = 293 # Initial temperature of the plate sensor (K)
 
 # User-defined variables
-emission_time = 20 * 60  # 1 minute in seconds
-wall_thickness = 0.001
-element_width = 0.05
-element_height = 0.10
-emissivity = 0.94
-steel_density = 8050 
-cp_steel = 490
-convective_hfc_exposed = 10
-convective_hfc_unexposed = 8
-#Initializing grid heat flux for the forward  model
+emission_time = 20 * 60  # Exposure time (s)
+wall_thickness = 0.001 # Thickness of the plate sensor (m)
+element_width = 0.05 # Size of a discrete element in the x dimension (m)
+element_height = 0.10 # Size of a discrete element in the y dimension (m)
+emissivity = 0.94 # Emissivity of the plate sensor
+steel_density = 8050 # Density of the plate sensor material (kg/m^3)
+cp_steel = 490 # Specific heat capacity of the plate sensor material (J/kgK)
+k_steel = 45  # Thermal conductivity of the plate sensor material (W/mK)
+convective_hfc_exposed = 10 # Convective heat transfer coefficient on the exposed side of the plate sensor (W/m^2K)
+convective_hfc_unexposed = 8 # Convective heat transfer coefficient on the unexposed side of the plate sensor (W/m^2K)
+
+# Initializing grid heat flux for the forward model
 grid_size = 3  # 3x3 grid --> the simplest 2D case possible
 central_heat_flux = 50000  # Central cell
-surrounding_heat_flux = 10000  # neighboring  cells
+surrounding_heat_flux = 10000  # neighboring cells
 heat_flux_grid = np.full((grid_size, grid_size), surrounding_heat_flux)
 heat_flux_grid[1, 1] = central_heat_flux  # Set central cell heat flux
 
-# energy blance for the 2D grid
+# Apply conservation of energy over the 2D grid
 def energy_balance_2d(t, T_flat):
     T = T_flat.reshape((grid_size, grid_size))
     dTdt = np.zeros_like(T)
@@ -47,7 +48,7 @@ def energy_balance_2d(t, T_flat):
             q_conv_exp = convective_hfc_exposed * area * (T[i, j] - initial_temperature)
             q_conv_unexp = convective_hfc_unexposed * area * (T[i, j] - initial_temperature)
             q_rad = 2*emissivity * stefan_boltzmann_constant * area * (T[i, j]**4 - initial_temperature**4)
-            print(q_cond)
+            # print(q_cond)
             # Energy balance
             dTdt[i, j] = (emissivity * q_in - q_conv_exp - q_conv_unexp - q_rad + q_cond) / (area * cp_steel * steel_density * wall_thickness)
 
@@ -61,14 +62,15 @@ def energy_balance_2d(t, T_flat):
 
 # Generate time steps
 t_eval = np.linspace(t_span[0], t_span[1],6000)  # Creates an array from 0 to emission_time with a specified time step
-print(t_eval)
+# print(t_eval)
+
 # Solve the 2D differential equation with specified time steps
 solution = solve_ivp(energy_balance_2d, t_span, T0_flat, method='RK45', t_eval=t_eval, dense_output=True)
-
 num_time_steps = len(solution.t)
-print((solution.y).shape)
+# print((solution.y).shape)
 T_values_2d = solution.y.reshape((grid_size, grid_size, num_time_steps))
-print(T_values_2d.shape)
+# print(T_values_2d.shape)
+
 # Plotting temperature distribution over time
 fig , ((ax1, ax2, ax3), (ax4, ax5, ax6), (ax7, ax8, ax9)) = plt.subplots(nrows=3, ncols=3, figsize=(14, 8) )
 axes = [ax1, ax2, ax3, ax4, ax5, ax6, ax7, ax8, ax9]
@@ -90,7 +92,7 @@ def energy_balance_2d(t, T_flat):
 # IHT Model Function
 def inverse_heat_transfer(T_values_2d, solution, k_steel, cp_steel, steel_density, element_width, element_height, wall_thickness, convective_hfc_exposed, convective_hfc_unexposed, emissivity):
     num_time_steps = T_values_2d.shape[2]
-    print(num_time_steps)
+    # print(num_time_steps)
     estimated_flux = np.zeros((grid_size, grid_size, num_time_steps))
 
     temp_grad = np.gradient(T_values_2d, axis=2) / np.gradient(solution.t)
@@ -112,7 +114,6 @@ def inverse_heat_transfer(T_values_2d, solution, k_steel, cp_steel, steel_densit
                 q_cond =  np.sum(grad_T) * wall_thickness
                 q_conv = (convective_hfc_exposed + convective_hfc_unexposed) * area * (T_values_2d[i, j, time_step] - initial_temperature)
                 q_rad = 2*emissivity * stefan_boltzmann_constant * area * (T_values_2d[i, j, time_step]**4 - initial_temperature**4)
-                
                 q_storage = cp_steel * steel_density * area * wall_thickness * temp_grad[i, j, time_step]
 
                 # Calculate the estimated incident heat flux
@@ -145,6 +146,6 @@ def inverse_heat_transfer(T_values_2d, solution, k_steel, cp_steel, steel_densit
         axx.legend(loc='upper right')
         # ax.grid(True)
         k += 1
-print(T_values_2d[1, 1, :])
+# print(T_values_2d[1, 1, :])
 plt.tight_layout()
 plt.show()

Scripts/.DS_Store

@@ -44,7 +44,6 @@ def k_gas(T_g):
 def k_metal(T_g):
     global global_state
     metal = global_state["wall material"].get()
-    # from engineeringtoolbox.com
     if metal == 'steel (FSRI)':
         k_metal = (-3.38759644163437 * 10**(-6) * T_g**2) + 0.017732749 + 13.6405477360128
     elif metal == 'steel (Engineering Toolbox)':
@@ -54,11 +53,11 @@ def k_metal(T_g):
     elif metal == 'copper':
         k_metal = -47.15 * np.log(T_g) + 674.98
     else:
-        print('Error: Metal is not in the list.')
+        print('Selected material is invalid, default values assumed.')
+        k_metal = 45
     return k_metal
 
 def cp_metal(T_g):
-    # from engineeringtoolbox.com
     global global_state
     metal = global_state["wall material"].get()
     if metal == 'steel (FSRI)':
@@ -70,11 +69,11 @@ def cp_metal(T_g):
     elif metal == 'copper':
         cp_metal = 0.0779 * np.log(T_g) - 0.0712
     else:
-        print('Error: Metal is not in the list.')
+        print('Selected material is invalid, default values assumed.')
+        cp_metal = 490
     return 1000*cp_metal
 
 def rho_metal(T_g):
-    # from engineeringtoolbox.com
     global global_state
     metal = global_state["wall material"].get()
     if metal == 'steel (FSRI)':
@@ -86,7 +85,8 @@ def rho_metal(T_g):
     elif metal == 'copper':
         rho_metal = -0.5124*np.log(T_g) + 9075.6
     else:
-        print('Error: Metal is not in the list.')
+        print('Selected material is invalid, default values assumed.')
+        rho_metal = 8050
     return rho_metal
 
 def Grashof(dT_w, T_film, T_amb):
@@ -102,7 +102,6 @@ def calculate_gradients(T_values_2d, i, j, element_width, element_height, use_hi
     grad_T = np.zeros(2)  # [grad_T_x, grad_T_y]
 
     if use_higher_order:
-        # Higher order discretization using numpy's gradient
         grad_y, grad_x = np.gradient(T_values_2d, axis=(0, 1))
         grad_T[0] = grad_y[i, j] * element_height / element_width
         grad_T[1] = grad_x[i, j] * element_width / element_height
@@ -121,9 +120,9 @@ def inverse_heat_transfer(time_series_data, element_width, element_height, time_
 
     if global_state["temperature_unit_var"].get() == "Celsius":
         time_series_data += 273.15
-        print('Temperature unit is set to Kelvin')
+        print('Temperature unit will be converted from Celsius to Kelvin.')
     else:
-        print('Temperature unit was already set to Kelvin')
+        print('Temperature unit was set to Kelvin, no conversion needed.')
     rows, cols, num_time_steps = time_series_data.shape
     estimated_flux = np.zeros(time_series_data.shape)
     hfc = np.zeros(time_series_data.shape)
@@ -243,7 +242,7 @@ def Tfilm_interp(width , height , nt):
         grid_z.append(griddata(points, values, (grid_x, grid_y), method='nearest'))
     # Check the shape to confirm it matches the custom resolution
     output = np.stack(grid_z , axis = 2)
-    print("Interpolated film temperature grid shape:", output.shape, output)
+    print("Interpolated film temperature grid shape: ", output.shape, output)
     return(output)
 
 def check_h5py_files(folder):
@@ -379,7 +378,7 @@ def process_directory_and_plot(source_dir, dest_dir, element_width, element_heig
         h5py_Tf.close()
         h5py_T0.close()
 
-    print("All files are processed and saved in the destination folder.")  
+    print("All files have been processed and saved in the destination folder.")  
 
 def apply_inverse_model():
     global global_state, DEFAULTS
@@ -514,7 +513,7 @@ def load_data_frames(folder, file_type, file_name = "", batch_start=None, batch_
                 selected_files = files[batch_start:batch_end]
             else:
                 selected_files = files
-            return [pd.read_csv(file, header=None) for file in tqdm(selected_files, desc = "Loading dataframes for video generation ")]
+            return [pd.read_csv(file, header=None) for file in tqdm(selected_files, desc = "Loading dataframes for video generation: ")]
 
 def create_video(source_folder, dest_folder, source_file_type, dest_file_type,global_max_source, global_max_dest, Time_Step_Size_s, batch_size):
     # Determine the total number of frames based on file type and content
@@ -523,7 +522,7 @@ def create_video(source_folder, dest_folder, source_file_type, dest_file_type,gl
         if source_h5py_path:
             with h5py.File(source_h5py_path, 'r') as h5_file:
                 total_frames = len(h5_file.keys())
-                print(f"Total frames : {total_frames}")
+                print(f"Total frames: {total_frames}")
 
     else:
         total_frames = max(len(glob.glob(os.path.join(source_folder, '*.csv'))),

Scripts/2D_IHT_validation.py

@@ -247,15 +247,15 @@ def update_h5py_size_entry_state(self):
 
     def select_source_folder(self):
         self.source_folder = filedialog.askdirectory()
-        print("Selected Source Folder:", self.source_folder)
+        print("Selected Source Folder: ", self.source_folder)
 
     def select_dest_folder(self):
         self.dest_folder = filedialog.askdirectory()
-        print("Selected Destination Folder:", self.dest_folder)
+        print("Selected Destination Folder: ", self.dest_folder)
 
     def select_Folder_for_Time_Array(self):
         self.Time_Array_folder = filedialog.askdirectory()
-        print("Selected Time Array Folder:", self.Time_Array_folder)
+        print("Selected Time Array Folder: ", self.Time_Array_folder)
 
     def assemble_time_array(self):
         time_row = 3
@@ -291,7 +291,7 @@ def assemble_time_array(self):
 
     def select_csv_file(self):
         self.csv_file = filedialog.askopenfilename(filetypes=[("CSV files", "*.csv")])
-        print("Selected sample CSV File:", self.csv_file)
+        print("Selected sample CSV File: ", self.csv_file)
 
     def process_images(self):
         if self.source_folder and self.dest_folder and self.csv_file: