Time-Dependent PDE-Constrained Optimization via Weak-Form Latent Dynamics
Optimization problems constrained by high-dimensional, time-dependent partial differential equations require repeated forward and sensitivity solves, making high-fidelity optimization computationally prohibitive in many-query design and control settings. We present a weak-form latent-space reduced-order modeling framework for accelerating gradient-based PDE-constrained optimization. The proposed approach builds on Weak-form Latent Space Dynamics Identification (WLaSDI), which compresses high-dimensional solution trajectories into a low-dimensional latent representation and identifies parametric latent dynamics using weak-form system identification. By avoiding explicit numerical different...
| Authors | April Tran, Terry Haut, David Bortz et al. |
|---|---|
| Primary category | math.OC |
| Published | 20 May 2026 |
| Last updated at source | 20 May 2026 |
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