Model Reduction

[jguarato]

This PR introduces a new ModelReduction class that provides a modular and extensible framework for applying different model reduction techniques. Currently, two reduction strategies are implemented:

• PseudoModal – reduction via modal transformation based on eigenvectors;
• Guyan – static condensation method to reduce system DOFs.

The ModelReduction class is now integrated into the Rotor.run_time_response() method, enabling model reduction during transient simulations.

Example Usage

Guyan Reduction:

compressor = rs.compressor_example()

dt = 1e-4
t = np.arange(0, 10, dt)
speed = 600

node = [29]
unb_mag = [0.003]
unb_phase = [0]

probe_nodes = [30]

# Unbalance force
F, _, _, _ = compressor.unbalance_force_over_time(
    node=node, magnitude=unb_mag, phase=unb_phase, omega=speed, t=t
)

response = compressor.run_time_response(
    speed,
    F.T,
    t,
    method="newmark",
    model_reduction={
        "method": "guyan",
        "include_nodes": probe_nodes, # Make sure to include output nodes
        "dof_mapping": ["x", "y"],
    },
)

PseudoModal:

response = compressor.run_time_response(
    speed,
    F.T,
    t,
    method="newmark",
    model_reduction={
        "method": "pseudomodal",
        "num_modes": 22,
    },
)

For the compressor model available as an example in ROSS, a good approximation with the reduction model was obtained and a computational time reduction of ~70%:

By extracting the maximum response over a range of speeds—using the reduced model of another system mounted with ROSS —it was possible to obtain the following comparison: