Tag: Reduced-order modeling

Researchers have developed a reduced-order model that captures how peak tapping forces, residual gaps, and humidity govern electrical output in ...

Aerospace researchers have demonstrated a time-varying-delay active disturbance rejection controller that stabilizes airfoil flutter across transonic speeds despite fluctuating control-loop ...

Researchers built regressor chain surrogate models that predict pressure and stress fields across varied wing planforms with modest prediction errors ...

Researchers applied proper generalized decomposition to transient thermoelastic analysis and cut computation time to roughly one-fourth of their in-house finite ...

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

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 ...

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.

Additive manufacturing, widely recognized as 3D printing, has been revolutionary in the field of manufacturing technologies, providing unprecedented capabilities in ...