Tag: reduced-order modeling

Researchers showed that reducing the state space of a linear-quadratic optimal control problem automatically induces an equivalent reduced control space, ...

A new collective variable framework reduces the Kuramoto–Sivashinsky equation to six tractable evolution equations for amplitude, temporal position, width, chirp, ...

Researchers trained a machine learning surrogate on 120 simulations that predicts WAAM thermal histories in milliseconds and calibrates uncertain model ...

A systematic review of 127 studies finds deep learning tools for cerebrovascular planning advancing rapidly, while small vessel segmentation, material ...

A reduced-order numerical study found that optimized spline-shaped cam commands reduced near-resonant follower distortion, but the best design retained substantial ...

Every large power transformer hums with invisible activity. Deep inside its core and windings, electromagnetic losses deposit heat continuously, shaping ...

Researchers at the Georgia Institute of Technology have developed and validated a new computational framework for simulating nuclear thermal propulsion ...

A new PCA-EMD framework reveals patient-specific kinematic synergy patterns and a hidden fast oscillation in the gait of paraplegic patients.

Researchers have developed an enhanced convolutional autoencoder that compresses axial temperature fields in a gas-oxygen/gas-methane rocket igniter by up to ...