Delete ansys_script.py

ansys_script.py

@@ -1,61 +0,0 @@
-import pyansys
-import numpy as np
-import matplotlib.pyplot as plt
-
-def run_beam_analysis():
-    # Initialize ANSYS session
-    ansys = pyansys.Mapdl()
-
-    # Clear previous session data
-    ansys.clear()
-
-    # Preprocessing section
-    ansys.prep7()
-
-    # Define material properties (for steel)
-    ansys.mp('EX', 1, 210E9)   # Young's modulus (Pa)
-    ansys.mp('NUXY', 1, 0.3)   # Poisson's ratio
-    ansys.mp('DENS', 1, 7800)  # Density (kg/m³)
-
-    # Define geometry (a simple beam with length 1m, width 0.1m, height 0.1m)
-    ansys.block(0, 1, 0, 0.1, 0, 0.1)  # Define a solid block (beam)
-
-    # Meshing
-    ansys.et(1, 185)  # Solid element type (tetrahedron)
-    ansys.vmesh('ALL')  # Mesh all volumes
-
-    # Apply boundary conditions (fixed support at one end)
-    ansys.nsel('S', 'LOC', 'X', 0)  # Select nodes at x=0
-    ansys.d('ALL', 'UX', 0)         # Fix displacement in X direction
-    ansys.d('ALL', 'UY', 0)         # Fix displacement in Y direction
-    ansys.d('ALL', 'UZ', 0)         # Fix displacement in Z direction
-
-    # Apply load (a force at the free end of the beam)
-    ansys.nsel('S', 'LOC', 'X', 1)  # Select nodes at x=1 (free end)
-    ansys.sf('ALL', 1, 'F', 1000)   # Apply force of 1000N in Z direction
-
-    # Solve the model
-    ansys.solve()
-
-    # Post-processing to extract results (stress distribution)
-    ansys.post1()
-    ansys.set(1, 1)  # Set result set
-    stress = ansys.prnsol('S', 'ALL')  # Extract stress at all nodes/elements
-
-    # Convert stress values to numpy array for easier manipulation
-    stress_values = np.array(stress)
-
-    # Now let's plot the stress distribution
-    fig, ax = plt.subplots()
-    ax.plot(np.linspace(0, 1, len(stress_values)), stress_values, label='Stress Distribution')
-    ax.set_xlabel('Position along the Beam (m)')
-    ax.set_ylabel('Stress (Pa)')
-    ax.set_title('Stress Distribution in Beam')
-    ax.legend()
-
-    # Save the plot to a file
-    plot_path = "/tmp/stress_distribution.png"
-    plt.savefig(plot_path)
-
-    # Return plot path for visualization in Gradio
-    return plot_path