Author

Wen-Bo Cao

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Preprint Sep 2026

A Physics-Driven Framework for Parametric Periodic-Flow Modeling and Finite-Amplitude Aeroelastic Response Analysis

Periodic unsteady flows are common in forced-motion and fluid-structure interaction problems. Their parametric analysis typically requires repeated high-fidelity simulations, whereas existing reduced-order and surrogate models generally rely on pre-generated flow-field or aerodynamic data. This study proposes a purely...

Dai-Wei Dong, Wen-Bo Cao, Wei-Wei Zhang · 0 citations

#machine learning Preprint Sep 2026

Single-condition neural solvers encode transferable response spaces for parametric differential equations

This work shows that the output Jacobian of a neural solution model trained at one condition defines a reusable response space for cross-condition solution variations, and introduces Linearized Subspace Transfer (LST) to exploit this space and recover target solutions by minimizing the target PDE-system residual over r...

Wen-Bo Cao, Wei-Wei Zhang · 0 citations

#machine learning Preprint Jan 2026

Linearized subspace refinement framework to expose hidden accuracy in trained neural networks

This work presents Linearized Subspace Refinement (LSR), an architecture-agnostic post-training framework that exploits the local linearized model at a fixed trained state and exposes conditioning-limited attainable accuracy in trained-state linearized models and provides direct access to it.

Wen-Bo Cao, Wei-Wei Zhang · 0 citations